A common type system for clinical natural language processing.

PubMed

Wu, Stephen T; Kaggal, Vinod C; Dligach, Dmitriy; Masanz, James J; Chen, Pei; Becker, Lee; Chapman, Wendy W; Savova, Guergana K; Liu, Hongfang; Chute, Christopher G

2013-01-03

One challenge in reusing clinical data stored in electronic medical records is that these data are heterogenous. Clinical Natural Language Processing (NLP) plays an important role in transforming information in clinical text to a standard representation that is comparable and interoperable. Information may be processed and shared when a type system specifies the allowable data structures. Therefore, we aim to define a common type system for clinical NLP that enables interoperability between structured and unstructured data generated in different clinical settings. We describe a common type system for clinical NLP that has an end target of deep semantics based on Clinical Element Models (CEMs), thus interoperating with structured data and accommodating diverse NLP approaches. The type system has been implemented in UIMA (Unstructured Information Management Architecture) and is fully functional in a popular open-source clinical NLP system, cTAKES (clinical Text Analysis and Knowledge Extraction System) versions 2.0 and later. We have created a type system that targets deep semantics, thereby allowing for NLP systems to encapsulate knowledge from text and share it alongside heterogenous clinical data sources. Rather than surface semantics that are typically the end product of NLP algorithms, CEM-based semantics explicitly build in deep clinical semantics as the point of interoperability with more structured data types.

Discourse analysis: towards an understanding of its place in nursing.

PubMed

Crowe, Marie

2005-07-01

This paper describes how discourse analysis, and in particular critical discourse analysis, can be used in nursing research, and provides an example to illustrate the techniques involved. Discourse analysis has risen to prominence in the 1980s and 1990s in disciplines such as the social sciences, literary theory and cultural studies and is increasingly used in nursing. This paper investigates discourse analysis as a useful methodology for conducting nursing research. Effective clinical reasoning relies on employing several different kinds of knowledge and research that draw on different perspectives, methodologies and techniques to generate breadth of knowledge and depth of understanding of clinical practices and patients' experiences of those practices. The steps in a discourse analysis include: choosing the text, and identifying the explicit purpose of the text, the processes used for claiming authority connections to other discourses, construction of major concepts, processes of naming and categorizing, construction of subject positions, construction of reality and social relations and implications for the practice of nursing. The limitations of discourse analysis, its relationship to other qualitative approaches and questions for evaluating the rigour of research using discourse analysis are also explored. The example of discourse analysis shows how a text influences the practice of nursing by shaping knowledge, values and beliefs. Discourse analysis can make a contribution to the development of nursing knowledge by providing a research strategy to examine dominant discourses that influence nursing practice.

Patients Covertly Recording Clinical Encounters: Threat or Opportunity? A Qualitative Analysis of Online Texts

PubMed Central

Tsulukidze, Maka; Grande, Stuart W.; Thompson, Rachel; Rudd, Kenneth; Elwyn, Glyn

2015-01-01

Background The phenomenon of patients covertly recording clinical encounters has generated controversial media reports. This study aims to examine the phenomenon and analyze the underlying issues. Methods and Findings We conducted a qualitative analysis of online posts, articles, blogs, and forums (texts) discussing patients covertly recording clinical encounters. Using Google and Google Blog search engines, we identified and analyzed 62 eligible texts published in multiple countries between 2006 and 2013. Thematic analysis revealed four key themes: 1) a new behavior that elicits strong reactions, both positive and negative, 2) an erosion of trust, 3) shifting patient-clinician roles and relationships, and 4) the existence of confused and conflicting responses. When patients covertly record clinical encounters – a behavior made possible by various digital recording technologies – strong reactions are evoked among a range of stakeholders. The behavior represents one consequence of an erosion of trust between patients and clinicians, and when discovered, leads to further deterioration of trust. Confused and conflicting responses to the phenomenon by patients and clinicians highlight the need for policy guidance. Conclusions This study describes strong reactions, both positive and negative, to the phenomenon of patients covertly recording clinical encounters. The availability of smartphones capable of digital recording, and shifting attitudes to patient-clinician relationships, seems to have led to this behavior, mostly viewed as a threat by clinicians but as a welcome and helpful innovation by some patients, possibly indicating a perception of subordination and a lack of empowerment. Further examination of this tension and its implications is needed. PMID:25933002

Smart Extraction and Analysis System for Clinical Research.

PubMed

Afzal, Muhammad; Hussain, Maqbool; Khan, Wajahat Ali; Ali, Taqdir; Jamshed, Arif; Lee, Sungyoung

2017-05-01

With the increasing use of electronic health records (EHRs), there is a growing need to expand the utilization of EHR data to support clinical research. The key challenge in achieving this goal is the unavailability of smart systems and methods to overcome the issue of data preparation, structuring, and sharing for smooth clinical research. We developed a robust analysis system called the smart extraction and analysis system (SEAS) that consists of two subsystems: (1) the information extraction system (IES), for extracting information from clinical documents, and (2) the survival analysis system (SAS), for a descriptive and predictive analysis to compile the survival statistics and predict the future chance of survivability. The IES subsystem is based on a novel permutation-based pattern recognition method that extracts information from unstructured clinical documents. Similarly, the SAS subsystem is based on a classification and regression tree (CART)-based prediction model for survival analysis. SEAS is evaluated and validated on a real-world case study of head and neck cancer. The overall information extraction accuracy of the system for semistructured text is recorded at 99%, while that for unstructured text is 97%. Furthermore, the automated, unstructured information extraction has reduced the average time spent on manual data entry by 75%, without compromising the accuracy of the system. Moreover, around 88% of patients are found in a terminal or dead state for the highest clinical stage of disease (level IV). Similarly, there is an ∼36% probability of a patient being alive if at least one of the lifestyle risk factors was positive. We presented our work on the development of SEAS to replace costly and time-consuming manual methods with smart automatic extraction of information and survival prediction methods. SEAS has reduced the time and energy of human resources spent unnecessarily on manual tasks.

Distinguishing benign and malignant breast tumors: preliminary comparison of kinetic modeling approaches using multi-institutional dynamic contrast-enhanced MRI data from the International Breast MR Consortium 6883 trial.

PubMed

Sorace, Anna G; Partridge, Savannah C; Li, Xia; Virostko, Jack; Barnes, Stephanie L; Hippe, Daniel S; Huang, Wei; Yankeelov, Thomas E

2018-01-01

Comparative preliminary analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data collected in the International Breast MR Consortium 6883 multicenter trial was performed to distinguish benign and malignant breast tumors. Prebiopsy DCE-MRI data from 45 patients with suspicious breast lesions were obtained. Semiquantitative mean signal-enhancement ratio ([Formula: see text]) was calculated for all lesions, and quantitative pharmacokinetic, parameters [Formula: see text], [Formula: see text], and [Formula: see text], were calculated for the subset with available [Formula: see text] maps ([Formula: see text]). Diagnostic performance was estimated for DCE-MRI parameters and compared to standard clinical MRI assessment. Quantitative and semiquantitative metrics discriminated benign and malignant lesions, with receiver operating characteristic area under the curve (AUC) values of 0.71, 0.70, and 0.82 for [Formula: see text], [Formula: see text], and [Formula: see text], respectively ([Formula: see text]). At equal 94% sensitivity, the specificity and positive predictive value of [Formula: see text] (53% and 63%, respectively) and K trans (42% and 58%) were higher than clinical MRI assessment (32% and 54%). A multivariable model combining [Formula: see text] and clinical MRI assessment had an AUC value of 0.87. Quantitative pharmacokinetic and semiquantitative analyses of DCE-MRI improves discrimination of benign and malignant breast tumors, with our findings suggesting higher diagnostic accuracy using [Formula: see text]. [Formula: see text] has potential to help reduce unnecessary biopsies resulting from routine breast imaging.

A social constructionist analysis of talk in episodes of psychiatric student nurses conversations with clients in community clinics.

PubMed

Middleton, Lyn; Uys, Leana

2009-03-01

This paper is a report of a study of the 'discursive doings' of psychiatric nursing students' practice as they are jointly constructed in conversations with clients in community psychiatric clinics. This construction of psychiatric nursing as a therapeutic, holistic, person-centred, interactional process is central to the identity of psychiatric nursing as a discipline. However, recent studies are beginning to suggest a dissonance between the person-centred rhetoric and institutional practice. A discourse analysis was conducted in 2002-03 using the transcripts of seven conversations between nursing students and clients visiting psychiatric community clinics on a monthly basis. These were selected from a sample of 20 conversations based on their clarity and completeness. Texts were analysed using the notational systems of Silverman and Mishler and some of Fairclough's analytic text structure features. In all the transcripts, an agenda for surveillance was explicitly established in the students' opening sequences of each text. Almost all exchanges in the texts were organized around cycles of questions from students and responses from clients, which allowed students to control the conversations. Information delivery was also found to be at work within the texts, although it is not as prominent or as persistent as the question and answer structure. Students took up the responses of clients selectively as though working to a pre-set agenda. These discursive activities manifest a symptom-like approach to nursing care and have the effect of disabling the development of client-authorized expressions of agency.

Using digital notifications to improve attendance in clinic: systematic review and meta-analysis.

PubMed

Robotham, Dan; Satkunanathan, Safarina; Reynolds, John; Stahl, Daniel; Wykes, Til

2016-10-24

Assess the impact of text-based electronic notifications on improving clinic attendance, in relation to study quality (according to risk of bias), and to assess simple ways in which notifications can be optimised (ie, impact of multiple notifications). Systematic review, study quality appraisal assessing risk of bias, data synthesised in meta-analyses. MEDLINE, EMBASE, PsycINFO, Web of Science and Cochrane Database of Systematic Reviews (01.01.05 until 25.4.15). A systematic search to discover all studies containing quantitative data for synthesis into meta-analyses. Studies examining the effect of text-based electronic notifications on prescheduled appointment attendance in healthcare settings. Primary analysis included experimental studies where randomisation was used to define allocation to intervention and where a control group consisting of 'no reminders' was used. Secondary meta-analysis included studies comparing text reminders with voice reminders. Studies lacking sufficient information for inclusion (after attempting to contact study authors) were excluded. Primary outcomes were rate of attendance/non-attendance at healthcare appointments. Secondary outcome was rate of rescheduled and cancelled appointments. 26 articles were included. 21 included in the primary meta-analysis (8345 patients receiving electronic text notifications, 7731 patients receiving no notifications). Studies were included from Europe (9), Asia (7), Africa (2), Australia (2) and America (1). Patients who received notifications were 23% more likely to attend clinic than those who received no notification (risk ratio=1.23, 67% vs 54%). Those receiving notifications were 25% less likely to 'no show' for appointments (risk ratio=.75, 15% vs 21%). Results were similar when accounting for risk of bias, region and publication year. Multiple notifications were significantly more effective at improving attendance than single notifications. Voice notifications appeared more effective than text notifications at improving attendance. Electronic text notifications improve attendance and reduce no shows across healthcare settings. Sending multiple notifications could improve attendance further. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

[Systematic analysis of the readability of patient information on websites of German nonuniversity ENT hospitals].

PubMed

Meyer, M F; Bacher, R; Roth, K S; Beutner, D; Luers, J C

2014-03-01

Besides their function as one of the main contact points, websites of hospitals serve as medical information portals. All patients should be able to understand medical information texts; regardless of their literacy skills and educational level. Online texts should thus have an appropriate structure to ease their comprehension. Patient information texts on every German nonuniversity ENT hospital website (n = 125) were systematically analysed. For ten different ENT topics a representative medical information text was extracted from each website. Using objective text parameters and five established readability indices, the texts were analysed in terms of their readability and structure. Furthermore, we stratified the analysis in relation to the hospital organisation system and geographical region in Germany. Texts from 142 internet sites could be used for the definite analysis. On average, texts consisted of 15 sentences and 237 words. Readability indices congruously showed that the analysed texts could generally only be understood by a well-educated or even academic reader. The majority of patient information texts on German hospital websites are difficult to understand for most patients. In order to fulfil their goal of adequately informing the general population about disease, therapeutic options and the particular focal points of the clinic, a revision of most medical texts on the websites of German ENT hospitals is recommended.

[Application of text mining approach to pre-education prior to clinical practice].

PubMed

Koinuma, Masayoshi; Koike, Katsuya; Nakamura, Hitoshi

2008-06-01

We developed a new survey analysis technique to understand students' actual aims for effective pretraining prior to clinical practice. We asked third-year undergraduate students to write fixed-style complete and free sentences on "preparation of drug dispensing." Then, we converted their sentence data in to text style and performed Japanese-language morphologic analysis on the data using language analysis software. We classified key words, which were created on the basis of the word class information of the Japanese language morphologic analysis, into categories based on causes and characteristics. In addition to this, we classified the characteristics into six categories consisting of those concepts including "knowledge," "skill and attitude," "image," etc. with the KJ method technique. The results showed that the awareness of students of "preparation of drug dispensing" tended to be approximately three-fold more frequent in "skill and attitude," "risk," etc. than in "knowledge." Regarding the characteristics in the category of the "image," words like "hard," "challenging," "responsibility," "life," etc. frequently occurred. The results of corresponding analysis showed that the characteristics of the words "knowledge" and "skills and attitude" were independent. As the result of developing a cause-and-effect diagram, it was demonstrated that the phase "hanging tough" described most of the various factors. We thus could understand students' actual feelings by applying text-mining as a new survey analysis technique.

Discovering body site and severity modifiers in clinical texts

PubMed Central

Dligach, Dmitriy; Bethard, Steven; Becker, Lee; Miller, Timothy; Savova, Guergana K

2014-01-01

Objective To research computational methods for discovering body site and severity modifiers in clinical texts. Methods We cast the task of discovering body site and severity modifiers as a relation extraction problem in the context of a supervised machine learning framework. We utilize rich linguistic features to represent the pairs of relation arguments and delegate the decision about the nature of the relationship between them to a support vector machine model. We evaluate our models using two corpora that annotate body site and severity modifiers. We also compare the model performance to a number of rule-based baselines. We conduct cross-domain portability experiments. In addition, we carry out feature ablation experiments to determine the contribution of various feature groups. Finally, we perform error analysis and report the sources of errors. Results The performance of our method for discovering body site modifiers achieves F1 of 0.740–0.908 and our method for discovering severity modifiers achieves F1 of 0.905–0.929. Discussion Results indicate that both methods perform well on both in-domain and out-domain data, approaching the performance of human annotators. The most salient features are token and named entity features, although syntactic dependency features also contribute to the overall performance. The dominant sources of errors are infrequent patterns in the data and inability of the system to discern deeper semantic structures. Conclusions We investigated computational methods for discovering body site and severity modifiers in clinical texts. Our best system is released open source as part of the clinical Text Analysis and Knowledge Extraction System (cTAKES). PMID:24091648

Discovering body site and severity modifiers in clinical texts.

PubMed

Dligach, Dmitriy; Bethard, Steven; Becker, Lee; Miller, Timothy; Savova, Guergana K

2014-01-01

To research computational methods for discovering body site and severity modifiers in clinical texts. We cast the task of discovering body site and severity modifiers as a relation extraction problem in the context of a supervised machine learning framework. We utilize rich linguistic features to represent the pairs of relation arguments and delegate the decision about the nature of the relationship between them to a support vector machine model. We evaluate our models using two corpora that annotate body site and severity modifiers. We also compare the model performance to a number of rule-based baselines. We conduct cross-domain portability experiments. In addition, we carry out feature ablation experiments to determine the contribution of various feature groups. Finally, we perform error analysis and report the sources of errors. The performance of our method for discovering body site modifiers achieves F1 of 0.740-0.908 and our method for discovering severity modifiers achieves F1 of 0.905-0.929. Results indicate that both methods perform well on both in-domain and out-domain data, approaching the performance of human annotators. The most salient features are token and named entity features, although syntactic dependency features also contribute to the overall performance. The dominant sources of errors are infrequent patterns in the data and inability of the system to discern deeper semantic structures. We investigated computational methods for discovering body site and severity modifiers in clinical texts. Our best system is released open source as part of the clinical Text Analysis and Knowledge Extraction System (cTAKES).

Automated assessment of medical training evaluation text.

PubMed

Zhang, Rui; Pakhomov, Serguei; Gladding, Sophia; Aylward, Michael; Borman-Shoap, Emily; Melton, Genevieve B

2012-01-01

Medical post-graduate residency training and medical student training increasingly utilize electronic systems to evaluate trainee performance based on defined training competencies with quantitative and qualitative data, the later of which typically consists of text comments. Medical education is concomitantly becoming a growing area of clinical research. While electronic systems have proliferated in number, little work has been done to help manage and analyze qualitative data from these evaluations. We explored the use of text-mining techniques to assist medical education researchers in sentiment analysis and topic analysis of residency evaluations with a sample of 812 evaluation statements. While comments were predominantly positive, sentiment analysis improved the ability to discriminate statements with 93% accuracy. Similar to other domains, Latent Dirichlet Analysis and Information Gain revealed groups of core subjects and appear to be useful for identifying topics from this data.

Text mining-based in silico drug discovery in oral mucositis caused by high-dose cancer therapy.

PubMed

Kirk, Jon; Shah, Nirav; Noll, Braxton; Stevens, Craig B; Lawler, Marshall; Mougeot, Farah B; Mougeot, Jean-Luc C

2018-08-01

Oral mucositis (OM) is a major dose-limiting side effect of chemotherapy and radiation used in cancer treatment. Due to the complex nature of OM, currently available drug-based treatments are of limited efficacy. Our objectives were (i) to determine genes and molecular pathways associated with OM and wound healing using computational tools and publicly available data and (ii) to identify drugs formulated for topical use targeting the relevant OM molecular pathways. OM and wound healing-associated genes were determined by text mining, and the intersection of the two gene sets was selected for gene ontology analysis using the GeneCodis program. Protein interaction network analysis was performed using STRING-db. Enriched gene sets belonging to the identified pathways were queried against the Drug-Gene Interaction database to find drug candidates for topical use in OM. Our analysis identified 447 genes common to both the "OM" and "wound healing" text mining concepts. Gene enrichment analysis yielded 20 genes representing six pathways and targetable by a total of 32 drugs which could possibly be formulated for topical application. A manual search on ClinicalTrials.gov confirmed no relevant pathway/drug candidate had been overlooked. Twenty-five of the 32 drugs can directly affect the PTGS2 (COX-2) pathway, the pathway that has been targeted in previous clinical trials with limited success. Drug discovery using in silico text mining and pathway analysis tools can facilitate the identification of existing drugs that have the potential of topical administration to improve OM treatment.

Simulating Expert Clinical Comprehension: Adapting Latent Semantic Analysis to Accurately Extract Clinical Concepts from Psychiatric Narrative

PubMed Central

Cohen, Trevor; Blatter, Brett; Patel, Vimla

2008-01-01

Cognitive studies reveal that less-than-expert clinicians are less able to recognize meaningful patterns of data in clinical narratives. Accordingly, psychiatric residents early in training fail to attend to information that is relevant to diagnosis and the assessment of dangerousness. This manuscript presents cognitively motivated methodology for the simulation of expert ability to organize relevant findings supporting intermediate diagnostic hypotheses. Latent Semantic Analysis is used to generate a semantic space from which meaningful associations between psychiatric terms are derived. Diagnostically meaningful clusters are modeled as geometric structures within this space and compared to elements of psychiatric narrative text using semantic distance measures. A learning algorithm is defined that alters components of these geometric structures in response to labeled training data. Extraction and classification of relevant text segments is evaluated against expert annotation, with system-rater agreement approximating rater-rater agreement. A range of biomedical informatics applications for these methods are suggested. PMID:18455483

Incorporating Semantics into Data Driven Workflows for Content Based Analysis

NASA Astrophysics Data System (ADS)

Argüello, M.; Fernandez-Prieto, M. J.

Finding meaningful associations between text elements and knowledge structures within clinical narratives in a highly verbal domain, such as psychiatry, is a challenging goal. The research presented here uses a small corpus of case histories and brings into play pre-existing knowledge, and therefore, complements other approaches that use large corpus (millions of words) and no pre-existing knowledge. The paper describes a variety of experiments for content-based analysis: Linguistic Analysis using NLP-oriented approaches, Sentiment Analysis, and Semantically Meaningful Analysis. Although it is not standard practice, the paper advocates providing automatic support to annotate the functionality as well as the data for each experiment by performing semantic annotation that uses OWL and OWL-S. Lessons learnt can be transmitted to legacy clinical databases facing the conversion of clinical narratives according to prominent Electronic Health Records standards.

Feminism, biomedicine and the 'reproductive destiny' of women in clinical texts on the birth control pill.

PubMed

Carson, Andrea

2018-07-01

The birth control pill is one of the most popular forms of contraception in North America and has been a key player in women's rights activism for over 50 years. In this paper, I conduct a feminist deconstructive analysis of 12 biomedical texts on the birth control pill, published between 1965 and 2016. This study is situated amongst the feminist scholarship that challenges the representation of women's bodies in biomedicine. Findings suggest that clinical texts on the birth control pill continue to universalise women's lives and experiences, and essentialise them based on their reproductive capacities. One way the texts accomplish this is by making women absent or passive in the literature thereby losing concern for the diversity of their lives, interpretations and identities as more than reproductive beings. The consequence of such representations is that biomedical texts disseminate limited forms of knowledge, in particular concerning definitions of 'natural' and 'normal' behaviour, with important consequences for the embodied experiences of women.

[Technologies for Complex Intelligent Clinical Data Analysis].

PubMed

Baranov, A A; Namazova-Baranova, L S; Smirnov, I V; Devyatkin, D A; Shelmanov, A O; Vishneva, E A; Antonova, E V; Smirnov, V I

2016-01-01

The paper presents the system for intelligent analysis of clinical information. Authors describe methods implemented in the system for clinical information retrieval, intelligent diagnostics of chronic diseases, patient's features importance and for detection of hidden dependencies between features. Results of the experimental evaluation of these methods are also presented. Healthcare facilities generate a large flow of both structured and unstructured data which contain important information about patients. Test results are usually retained as structured data but some data is retained in the form of natural language texts (medical history, the results of physical examination, and the results of other examinations, such as ultrasound, ECG or X-ray studies). Many tasks arising in clinical practice can be automated applying methods for intelligent analysis of accumulated structured array and unstructured data that leads to improvement of the healthcare quality. the creation of the complex system for intelligent data analysis in the multi-disciplinary pediatric center. Authors propose methods for information extraction from clinical texts in Russian. The methods are carried out on the basis of deep linguistic analysis. They retrieve terms of diseases, symptoms, areas of the body and drugs. The methods can recognize additional attributes such as "negation" (indicates that the disease is absent), "no patient" (indicates that the disease refers to the patient's family member, but not to the patient), "severity of illness", disease course", "body region to which the disease refers". Authors use a set of hand-drawn templates and various techniques based on machine learning to retrieve information using a medical thesaurus. The extracted information is used to solve the problem of automatic diagnosis of chronic diseases. A machine learning method for classification of patients with similar nosology and the methodfor determining the most informative patients'features are also proposed. Authors have processed anonymized health records from the pediatric center to estimate the proposed methods. The results show the applicability of the information extracted from the texts for solving practical problems. The records ofpatients with allergic, glomerular and rheumatic diseases were used for experimental assessment of the method of automatic diagnostic. Authors have also determined the most appropriate machine learning methods for classification of patients for each group of diseases, as well as the most informative disease signs. It has been found that using additional information extracted from clinical texts, together with structured data helps to improve the quality of diagnosis of chronic diseases. Authors have also obtained pattern combinations of signs of diseases. The proposed methods have been implemented in the intelligent data processing system for a multidisciplinary pediatric center. The experimental results show the availability of the system to improve the quality of pediatric healthcare.

Patient perspectives on delays in diagnosis and treatment of cancer: a qualitative analysis of free-text data.

PubMed

Parsonage, Rachel K; Hiscock, Julia; Law, Rebecca-Jane; Neal, Richard D

2017-01-01

Earlier cancer diagnosis is crucial in improving cancer survival. The International Cancer Benchmarking Partnership Module 4 (ICBP4) is a quantitative survey study that explores the reasons for delays in diagnosis and treatment of breast, colorectal, lung, and ovarian cancer. To further understand the associated diagnostic processes, it is also important to explore the patient perspectives expressed in the free-text comments. To use the free-text data provided by patients completing the ICBP4 survey to augment the understanding of patients' perspectives of their diagnostic journey. Qualitative analysis of the free-text data collected in Wales between October 2013 and December 2014 as part of the ICBP4 survey. Newly-diagnosed patients with either breast, ovarian, colorectal, or lung cancer were identified from registry data and then invited by their GPs to participate in the survey. A thematic framework was used to analyse the free-text comments provided at the end of the ICBP4 survey. Of the 905 patients who returned a questionnaire, 530 included comments. The free-text data provided information about patients' perspectives of the diagnostic journey. Analysis identified factors that acted as either barriers or facilitators at different stages of the diagnostic process. Some factors, such as screening, doctor-patient familiarity, and private treatment, acted as both barriers and facilitators depending on the context. Factors identified in this study help to explain how existing models of cancer diagnosis (for example, the Pathways to Treatment Model) work in practice. It is important that clinicians are aware of how these factors may interact with individual clinical cases and either facilitate, or act as a barrier to, subsequent cancer diagnosis. Understanding and implementing this knowledge into clinical practice may result in quicker cancer diagnoses. © British Journal of General Practice 2017.

Dense Annotation of Free-Text Critical Care Discharge Summaries from an Indian Hospital and Associated Performance of a Clinical NLP Annotator.

PubMed

Ramanan, S V; Radhakrishna, Kedar; Waghmare, Abijeet; Raj, Tony; Nathan, Senthil P; Sreerama, Sai Madhukar; Sampath, Sriram

2016-08-01

Electronic Health Record (EHR) use in India is generally poor, and structured clinical information is mostly lacking. This work is the first attempt aimed at evaluating unstructured text mining for extracting relevant clinical information from Indian clinical records. We annotated a corpus of 250 discharge summaries from an Intensive Care Unit (ICU) in India, with markups for diseases, procedures, and lab parameters, their attributes, as well as key demographic information and administrative variables such as patient outcomes. In this process, we have constructed guidelines for an annotation scheme useful to clinicians in the Indian context. We evaluated the performance of an NLP engine, Cocoa, on a cohort of these Indian clinical records. We have produced an annotated corpus of roughly 90 thousand words, which to our knowledge is the first tagged clinical corpus from India. Cocoa was evaluated on a test corpus of 50 documents. The overlap F-scores across the major categories, namely disease/symptoms, procedures, laboratory parameters and outcomes, are 0.856, 0.834, 0.961 and 0.872 respectively. These results are competitive with results from recent shared tasks based on US records. The annotated corpus and associated results from the Cocoa engine indicate that unstructured text mining is a viable method for cohort analysis in the Indian clinical context, where structured EHR records are largely absent.

TEPAPA: a novel in silico feature learning pipeline for mining prognostic and associative factors from text-based electronic medical records.

PubMed

Lin, Frank Po-Yen; Pokorny, Adrian; Teng, Christina; Epstein, Richard J

2017-07-31

Vast amounts of clinically relevant text-based variables lie undiscovered and unexploited in electronic medical records (EMR). To exploit this untapped resource, and thus facilitate the discovery of informative covariates from unstructured clinical narratives, we have built a novel computational pipeline termed Text-based Exploratory Pattern Analyser for Prognosticator and Associator discovery (TEPAPA). This pipeline combines semantic-free natural language processing (NLP), regular expression induction, and statistical association testing to identify conserved text patterns associated with outcome variables of clinical interest. When we applied TEPAPA to a cohort of head and neck squamous cell carcinoma patients, plausible concepts known to be correlated with human papilloma virus (HPV) status were identified from the EMR text, including site of primary disease, tumour stage, pathologic characteristics, and treatment modalities. Similarly, correlates of other variables (including gender, nodal status, recurrent disease, smoking and alcohol status) were also reliably recovered. Using highly-associated patterns as covariates, a patient's HPV status was classifiable using a bootstrap analysis with a mean area under the ROC curve of 0.861, suggesting its predictive utility in supporting EMR-based phenotyping tasks. These data support using this integrative approach to efficiently identify disease-associated factors from unstructured EMR narratives, and thus to efficiently generate testable hypotheses.

Building a common pipeline for rule-based document classification.

PubMed

Patterson, Olga V; Ginter, Thomas; DuVall, Scott L

2013-01-01

Instance-based classification of clinical text is a widely used natural language processing task employed as a step for patient classification, document retrieval, or information extraction. Rule-based approaches rely on concept identification and context analysis in order to determine the appropriate class. We propose a five-step process that enables even small research teams to develop simple but powerful rule-based NLP systems by taking advantage of a common UIMA AS based pipeline for classification. Our proposed methodology coupled with the general-purpose solution provides researchers with access to the data locked in clinical text in cases of limited human resources and compact timelines.

Using the patchwork text assessment as a vehicle for evaluating students' perceptions of their clinical leadership development.

PubMed

Leigh, J A; Rutherford, J; Wild, J; Cappleman, J; Hynes, C

2012-01-01

A shift in universities world wide in providing theoretical post graduate programmes of study underpinned by traditional assessment strategies to work based learning programmes supported by innovative assessment strategies is required if Higher education institutions are to effectively educate contemporary healthcare leaders. Concurrently generating the evidence to evaluate the effectiveness of educational programmes is required by commissioners of healthcare education (DH, 2010). This paper reports on the perceptions of twelve post graduate students attending a clinical leadership masters programme of their leadership development through analysis of the critical commentary provided by students as part of assessment strategy that utilised the Patchwork Text Assessment. Following a thematic content analysis six themes emerged: programme philosophy and its impact on the success of the Patchwork Text Assessment; leadership development targeted against leadership frameworks; application and applicability of learning to the students own healthcare organisation; integrating theory to practice through theoretical development and work based activities; the value of networking; and the importance of multi-professional reflective groups. This study has clearly demonstrated how the success of the Patchwork Text Assessment in promoting deep learning is determined by its integration into the overall philosophy of the programme. Concurrently systems needed to be in place to ensure that Patchwork text Assessment is operationalised effectively and embedded within the day to day management of the programme. Copyright © 2011 Elsevier Ltd. All rights reserved.

A PC-Based Free Text DSS for Health Care

NASA Technical Reports Server (NTRS)

Grams, Ralph R.; Buchanan, Paul; Massey, James K.; Jin, Ming

1987-01-01

A free Decision Support System(DST) has been constructed for health care professional that allows the analysis of complex medical cases and the creation of diagnostic list of potential diseases for clinical evaluation.The system uses a PC-based text management system specifically designed for desktop operation. The texts employed in the decision support package include the Merck Manual (published by Merck Sharpe & Dohme) and Control of Communicable Diseas in Man (published by the American Public Health Association). The background and design of the database are discussed along with a structured analysis procedure for handling free text DSS system. A case study is presented to show the application of this technology and conclusions are drawn in the summary that point to expanded areas of professional intention and new frontiers yet to be explored in this rapidly progressing field.

Computer-assisted liver graft steatosis assessment via learning-based texture analysis.

PubMed

Moccia, Sara; Mattos, Leonardo S; Patrini, Ilaria; Ruperti, Michela; Poté, Nicolas; Dondero, Federica; Cauchy, François; Sepulveda, Ailton; Soubrane, Olivier; De Momi, Elena; Diaspro, Alberto; Cesaretti, Manuela

2018-05-23

Fast and accurate graft hepatic steatosis (HS) assessment is of primary importance for lowering liver dysfunction risks after transplantation. Histopathological analysis of biopsied liver is the gold standard for assessing HS, despite being invasive and time consuming. Due to the short time availability between liver procurement and transplantation, surgeons perform HS assessment through clinical evaluation (medical history, blood tests) and liver texture visual analysis. Despite visual analysis being recognized as challenging in the clinical literature, few efforts have been invested to develop computer-assisted solutions for HS assessment. The objective of this paper is to investigate the automatic analysis of liver texture with machine learning algorithms to automate the HS assessment process and offer support for the surgeon decision process. Forty RGB images of forty different donors were analyzed. The images were captured with an RGB smartphone camera in the operating room (OR). Twenty images refer to livers that were accepted and 20 to discarded livers. Fifteen randomly selected liver patches were extracted from each image. Patch size was [Formula: see text]. This way, a balanced dataset of 600 patches was obtained. Intensity-based features (INT), histogram of local binary pattern ([Formula: see text]), and gray-level co-occurrence matrix ([Formula: see text]) were investigated. Blood-sample features (Blo) were included in the analysis, too. Supervised and semisupervised learning approaches were investigated for feature classification. The leave-one-patient-out cross-validation was performed to estimate the classification performance. With the best-performing feature set ([Formula: see text]) and semisupervised learning, the achieved classification sensitivity, specificity, and accuracy were 95, 81, and 88%, respectively. This research represents the first attempt to use machine learning and automatic texture analysis of RGB images from ubiquitous smartphone cameras for the task of graft HS assessment. The results suggest that is a promising strategy to develop a fully automatic solution to assist surgeons in HS assessment inside the OR.

Automated validation of patient safety clinical incident classification: macro analysis.

PubMed

Gupta, Jaiprakash; Patrick, Jon

2013-01-01

Patient safety is the buzz word in healthcare. Incident Information Management System (IIMS) is electronic software that stores clinical mishaps narratives in places where patients are treated. It is estimated that in one state alone over one million electronic text documents are available in IIMS. In this paper we investigate the data density available in the fields entered to notify an incident and the validity of the built in classification used by clinician to categories the incidents. Waikato Environment for Knowledge Analysis (WEKA) software was used to test the classes. Four statistical classifier based on J48, Naïve Bayes (NB), Naïve Bayes Multinominal (NBM) and Support Vector Machine using radial basis function (SVM_RBF) algorithms were used to validate the classes. The data pool was 10,000 clinical incidents drawn from 7 hospitals in one state in Australia. In first part of the study 1000 clinical incidents were selected to determine type and number of fields worth investigating and in the second part another 5448 clinical incidents were randomly selected to validate 13 clinical incident types. Result shows 74.6% of the cells were empty and only 23 fields had content over 70% of the time. The percentage correctly classified classes on four algorithms using categorical dataset ranged from 42 to 49%, using free-text datasets from 65% to 77% and using both datasets from 72% to 79%. Kappa statistic ranged from 0.36 to 0.4. for categorical data, from 0.61 to 0.74. for free-text and from 0.67 to 0.77 for both datasets. Similar increases in performance in the 3 experiments was noted on true positive rate, precision, F-measure and area under curve (AUC) of receiver operating characteristics (ROC) scores. The study demonstrates only 14 of 73 fields in IIMS have data that is usable for machine learning experiments. Irrespective of the type of algorithms used when all datasets are used performance was better. Classifier NBM showed best performance. We think the classifier can be improved further by reclassifying the most confused classes and there is scope to apply text mining tool on patient safety classifications.

Coronary artery disease risk assessment from unstructured electronic health records using text mining.

PubMed

Jonnagaddala, Jitendra; Liaw, Siaw-Teng; Ray, Pradeep; Kumar, Manish; Chang, Nai-Wen; Dai, Hong-Jie

2015-12-01

Coronary artery disease (CAD) often leads to myocardial infarction, which may be fatal. Risk factors can be used to predict CAD, which may subsequently lead to prevention or early intervention. Patient data such as co-morbidities, medication history, social history and family history are required to determine the risk factors for a disease. However, risk factor data are usually embedded in unstructured clinical narratives if the data is not collected specifically for risk assessment purposes. Clinical text mining can be used to extract data related to risk factors from unstructured clinical notes. This study presents methods to extract Framingham risk factors from unstructured electronic health records using clinical text mining and to calculate 10-year coronary artery disease risk scores in a cohort of diabetic patients. We developed a rule-based system to extract risk factors: age, gender, total cholesterol, HDL-C, blood pressure, diabetes history and smoking history. The results showed that the output from the text mining system was reliable, but there was a significant amount of missing data to calculate the Framingham risk score. A systematic approach for understanding missing data was followed by implementation of imputation strategies. An analysis of the 10-year Framingham risk scores for coronary artery disease in this cohort has shown that the majority of the diabetic patients are at moderate risk of CAD. Copyright © 2015 Elsevier Inc. All rights reserved.

Examining the Utility of Topic Models for Linguistic Analysis of Couple Therapy

ERIC Educational Resources Information Center

Doeden, Michelle A.

2012-01-01

This study examined the basic utility of topic models, a computational linguistics model for text-based data, to the investigation of the process of couple therapy. Linguistic analysis offers an additional lens through which to examine clinical data, and the topic model is presented as a novel methodology within couple and family psychology that…

The Mobile Insulin Titration Intervention (MITI) for Insulin Glargine Titration in an Urban, Low-Income Population: Randomized Controlled Trial Protocol.

PubMed

Levy, Natalie; Moynihan, Victoria; Nilo, Annielyn; Singer, Karyn; Bernik, Lidia S; Etiebet, Mary-Ann; Fang, Yixin; Cho, James; Natarajan, Sundar

2015-03-13

Patients on insulin glargine typically visit a clinician to obtain advice on how to adjust their insulin dose. These multiple clinic visits can be costly and time-consuming, particularly for low-income patients. It may be feasible to achieve insulin titration through text messages and phone calls with patients instead of face-to-face clinic visits. The objectives of this study are to (1) evaluate if the Mobile Insulin Titration Intervention (MITI) is clinically effective by helping patients reach their optimal dose of insulin glargine, (2) determine if the intervention is feasible within the setting and population, (3) assess patient satisfaction with the intervention, and (4) measure the costs associated with this intervention. This is a pilot study evaluating an approach to insulin titration using text messages and phone calls among patients with insulin-dependent type 2 diabetes in the outpatient medical clinic of Bellevue Hospital Center, a safety-net hospital in New York City. Patients will be randomized in a 1:1 ratio to either the MITI arm (texting/phone call intervention) or the usual-care arm (in-person clinic visits). Using a Web-based platform, weekday text messages will be sent to patients in the MITI arm, asking them to text back their fasting blood glucose values. In addition to daily reviews for alarm values, a clinician will rereview the texted values weekly, consult our physician-approved titration algorithm, and call the patients with advice on how to adjust their insulin dose. The primary outcome will be whether or not a patient reaches his/her optimal dose of insulin glargine within 12 weeks. Recruitment for this study occurred between June 2013 and December 2014. We are continuing to collect intervention and follow-up data from our patients who are currently enrolled. The results of our data analysis are expected to be available in 2015. This study explores the use of widely-available text messaging and voice technologies for insulin titration. We aim to show that remote insulin titration is clinically effective, feasible, satisfactory, and cost saving for low-income patients in a busy, urban clinic. Clinicaltrials.gov NCT01879579; http://clinicaltrials.gov/ct2/show/NCT01879579 (Archived by WebCite at http://www.webcitation.org/6WUEgjZUO).

Extensor Pollicis Longus Injury in Addition to De Quervain’s with Text Messaging on Mobile Phones

PubMed Central

Kumar, Bhaskaranand; Bhat, Anil K; Venugopal, Anand

2014-01-01

Objective: To do a clinical and ultrasonic evaluation of subjects with thumb pain with text messaging. Background: Thumbs are commonly used for text messaging, which are not as well designed for fine manipulative or dexterous work. Repetitive use as in text messaging can lead to the injury to the tendons of the thumb. Materials and Methods: Ninety eight students with symptoms of Repetitive Strain Type of injuries of the thumb were selected from a survey and evaluated both clinically and by ultrasound analysis of the musculotendinous unit of the thumb to note changes due to excessive use of the mobile phone. Age and sex matched controls were also subjected to ultrasound evaluation. Results: Clinical examination showed positive Finkelstein test in 40% of the cases, significant reduction in the lateral and tip pinch strengths in the cases. Ultrasound detected changes in the first and the third compartments in 19% of the cases. Conclusion: Isolated cases of pain in the thumb have been reported but this study noted changes both clinically and by ultrasound in the tendons of the thumb. These changes should be taken as warning signs of possible subclinical changes taking place in the soft tissues of the thumb in these subjects due to repetitive use of mobile phones and thus, making them prone for developing painful Musculoskeletal Disorders. Application: Repetitive use of mobile phones for text messaging can lead to the damage of Extensor pollicis longus of the thumb in addition to the tendons of the first compartment of the wrist. PMID:25584249

A fast and simple dose-calibrator-based quality control test for the radionuclidic purity of cyclotron-produced 99mTc

NASA Astrophysics Data System (ADS)

Tanguay, J.; Hou, X.; Esquinas, P.; Vuckovic, M.; Buckley, K.; Schaffer, P.; Bénard, F.; Ruth, T. J.; Celler, A.

2015-11-01

Cyclotron production of {{}99\\text{m}} Tc through the 100Mo(p,2n){{}99\\text{m}} Tc reaction channel is actively being investigated as an alternative to reactor-based 99Mo generation by nuclear fission of 235U. Like most radioisotope production methods, cyclotron production of {{}99\\text{m}} Tc will result in creation of unwanted impurities, including Tc and non-Tc isotopes. It is important to measure the amounts of these impurities for release of cyclotron-produced {{}99\\text{m}} Tc (CPTc) for clinical use. Detection of radioactive impurities will rely on measurements of their gamma (γ) emissions. Gamma spectroscopy is not suitable for this purpose because the overwhelming presence of {{}99\\text{m}} Tc and the count-rate limitations of γ spectroscopy systems preclude fast and accurate measurement of small amounts of impurities. In this article we describe a simple and fast method for measuring γ emission rates from radioactive impurities in CPTc. The proposed method is similar to that used to identify 99Mo breakthrough in generator-produced {{}99\\text{m}} Tc: one dose calibrator (DC) reading of a CPTc source placed in a lead shield is followed by a second reading of the same source in air. Our experimental and theoretical analysis show that the ratio of DC readings in lead to those in air are linearly related to γ emission rates from impurities per MBq of {{}99\\text{m}} Tc over a large range of clinically-relevant production conditions. We show that estimates of the γ emission rates from Tc impurities per MBq of {{}99\\text{m}} Tc can be used to estimate increases in radiation dose (relative to pure {{}99\\text{m}} Tc) to patients injected with CPTc-based radiopharmaceuticals. This enables establishing dosimetry-based clinical-release criteria that can be tested using commercially-available dose calibrators. We show that our approach is highly sensitive to the presence of {{}93\\text{g}} Tc, {{}93\\text{m}} Tc, {{}94\\text{g}} Tc, {{}94\\text{m}} Tc, {{}95\\text{m}} Tc, {{}95\\text{g}} Tc, and {{}96\\text{g}} Tc, in addition to a number of non-Tc impurities.

CLAMP - a toolkit for efficiently building customized clinical natural language processing pipelines.

PubMed

Soysal, Ergin; Wang, Jingqi; Jiang, Min; Wu, Yonghui; Pakhomov, Serguei; Liu, Hongfang; Xu, Hua

2017-11-24

Existing general clinical natural language processing (NLP) systems such as MetaMap and Clinical Text Analysis and Knowledge Extraction System have been successfully applied to information extraction from clinical text. However, end users often have to customize existing systems for their individual tasks, which can require substantial NLP skills. Here we present CLAMP (Clinical Language Annotation, Modeling, and Processing), a newly developed clinical NLP toolkit that provides not only state-of-the-art NLP components, but also a user-friendly graphic user interface that can help users quickly build customized NLP pipelines for their individual applications. Our evaluation shows that the CLAMP default pipeline achieved good performance on named entity recognition and concept encoding. We also demonstrate the efficiency of the CLAMP graphic user interface in building customized, high-performance NLP pipelines with 2 use cases, extracting smoking status and lab test values. CLAMP is publicly available for research use, and we believe it is a unique asset for the clinical NLP community. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Temporal reasoning over clinical text: the state of the art

PubMed Central

Sun, Weiyi; Rumshisky, Anna; Uzuner, Ozlem

2013-01-01

Objectives To provide an overview of the problem of temporal reasoning over clinical text and to summarize the state of the art in clinical natural language processing for this task. Target audience This overview targets medical informatics researchers who are unfamiliar with the problems and applications of temporal reasoning over clinical text. Scope We review the major applications of text-based temporal reasoning, describe the challenges for software systems handling temporal information in clinical text, and give an overview of the state of the art. Finally, we present some perspectives on future research directions that emerged during the recent community-wide challenge on text-based temporal reasoning in the clinical domain. PMID:23676245

The effects of a lifestyle-focused text-messaging intervention on adherence to dietary guideline recommendations in patients with coronary heart disease: an analysis of the TEXT ME study.

PubMed

Santo, Karla; Hyun, Karice; de Keizer, Laura; Thiagalingam, Aravinda; Hillis, Graham S; Chalmers, John; Redfern, Julie; Chow, Clara K

2018-05-23

A healthy diet is an important component of secondary prevention of coronary heart disease (CHD). The TEXT ME study was a randomised clinical trial of people with CHD that were randomised into standard care or a text-message programme in addition to standard care. This analysis aimed to: 1) assess the effects of the intervention onadherence to the dietary guideline recommendations; 2) assess the consistency of effect across sub-groups; and 3) assess whether adherence to the dietary guideline recommendations mediated the improvements in objective clinical outcomes. Dietary data were collected using a self-report questionnaire to evaluate adherence to eight dietary guideline recommendations in Australia, including consumption of vegetables, fruits, fish, type of fat used for cooking and in spreads, takeaway food, salt and standard alcohol drinks. The primary outcome of this analysis was the proportion of patients adhering to ≥ 4 dietary guideline recommendations concomitantly and each recommendation was assessed individually as secondary outcomes. Data were analysed using log-binomial regression for categorical variables and analysis of covariance for continuous variables. Among 710 patients, 54% were adhering to ≥ 4 dietary guideline recommendations (intervention 53% vs control 56%, p = 0.376) at baseline. At six months, the intervention group had a significantly higher proportion of patients adhering to ≥ 4 recommendations (314, 93%) compared to the control group (264, 75%, RR 1.23, 95% CI 1.15-1.31, p < 0.001). In addition, the intervention patients reported consuming higher amounts of vegetables, fruits, and fish per week; less takeaway foods per week; and greater salt intake control. The intervention had a similar effect in all sub-groups tested. There were significant mediational effects of the increase in adherence to the recommendations for the association between the intervention and LDL-cholesterol (p < 0.001) and body mass index (BMI) at six months follow-up (p = 0.005). A lifestyle-focused text-message programme improved adherence to the dietary guideline recommendations, and specifically improved self-reported consumption of vegetables, fruits, fish, takeaway foods and salt intake. Importantly, these improvements partially mediated improvements in LDL-cholesterol and BMI. This simple and scalable text-messaging intervention could be used as a strategy to improve diet in people with CHD. Australia and New Zealand Clinical Trials Registry ACTRN12611000161921 . Registered on 10 February 2011.

Citation Sentiment Analysis in Clinical Trial Papers

PubMed Central

Xu, Jun; Zhang, Yaoyun; Wu, Yonghui; Wang, Jingqi; Dong, Xiao; Xu, Hua

2015-01-01

In scientific writing, positive credits and negative criticisms can often be seen in the text mentioning the cited papers, providing useful information about whether a study can be reproduced or not. In this study, we focus on citation sentiment analysis, which aims to determine the sentiment polarity that the citation context carries towards the cited paper. A citation sentiment corpus was annotated first on clinical trial papers. The effectiveness of n-gram and sentiment lexicon features, and problem-specified structure features for citation sentiment analysis were then examined using the annotated corpus. The combined features from the word n-grams, the sentiment lexicons and the structure information achieved the highest Micro F-score of 0.860 and Macro-F score of 0.719, indicating that it is feasible to use machine learning methods for citation sentiment analysis in biomedical publications. A comprehensive comparison between citation sentiment analysis of clinical trial papers and other general domains were conducted, which additionally highlights the unique challenges within this domain. PMID:26958274

Intra-protocol repeatability and inter-protocol agreement for the analysis of scapulo-humeral coordination.

PubMed

Parel, I; Cutti, A G; Kraszewski, A; Verni, G; Hillstrom, H; Kontaxis, A

2014-03-01

Multi-center clinical trials incorporating shoulder kinematics are currently uncommon. The absence of repeatability and limits of agreement (LoA) studies between different centers employing different motion analysis protocols has led to a lack dataset compatibility. Therefore, the aim of this work was to determine the repeatability and LoA between two shoulder kinematic protocols. The first one uses a scapula tracker (ST), the International Society of Biomechanics anatomical frames and an optoelectronic measurement system, and the second uses a spine tracker, the INAIL Shoulder and Elbow Outpatient protocol (ISEO) and an inertial and magnetic measurement system. First within-protocol repeatability for each approach was assessed on a group of 23 healthy subjects and compared with the literature. Then, the between-protocol agreement was evaluated. The within-protocol repeatability was similar for the ST ([Formula: see text] = 2.35°, [Formula: see text] = 0.97°, SEM = 2.5°) and ISEO ([Formula: see text] = 2.24°, [Formula: see text] = 0.97°, SEM = 2.3°) protocols and comparable with data from published literature. The between-protocol agreement analysis showed comparable scapula medio-lateral rotation measurements for up to 120° of flexion-extension and up to 100° of scapula plane ab-adduction. Scapula protraction-retraction measurements were in agreement for a smaller range of humeral elevation. The results of this study suggest comparable repeatability for the ST and ISEO protocols and between-protocol agreement for two scapula rotations. Different thresholds for repeatability and LoA may be adapted to suit different clinical hypotheses.

Named Entity Recognition in Chinese Clinical Text Using Deep Neural Network.

PubMed

Wu, Yonghui; Jiang, Min; Lei, Jianbo; Xu, Hua

2015-01-01

Rapid growth in electronic health records (EHRs) use has led to an unprecedented expansion of available clinical data in electronic formats. However, much of the important healthcare information is locked in the narrative documents. Therefore Natural Language Processing (NLP) technologies, e.g., Named Entity Recognition that identifies boundaries and types of entities, has been extensively studied to unlock important clinical information in free text. In this study, we investigated a novel deep learning method to recognize clinical entities in Chinese clinical documents using the minimal feature engineering approach. We developed a deep neural network (DNN) to generate word embeddings from a large unlabeled corpus through unsupervised learning and another DNN for the NER task. The experiment results showed that the DNN with word embeddings trained from the large unlabeled corpus outperformed the state-of-the-art CRF's model in the minimal feature engineering setting, achieving the highest F1-score of 0.9280. Further analysis showed that word embeddings derived through unsupervised learning from large unlabeled corpus remarkably improved the DNN with randomized embedding, denoting the usefulness of unsupervised feature learning.

Natural language processing and the representation of clinical data.

PubMed Central

Sager, N; Lyman, M; Bucknall, C; Nhan, N; Tick, L J

1994-01-01

OBJECTIVE: Develop a representation of clinical observations and actions and a method of processing free-text patient documents to facilitate applications such as quality assurance. DESIGN: The Linguistic String Project (LSP) system of New York University utilizes syntactic analysis, augmented by a sublanguage grammar and an information structure that are specific to the clinical narrative, to map free-text documents into a database for querying. MEASUREMENTS: Information precision (I-P) and information recall (I-R) were measured for queries for the presence of 13 asthma-health-care quality assurance criteria in a database generated from 59 discharge letters. RESULTS: I-P, using counts of major errors only, was 95.7% for the 28-letter training set and 98.6% for the 31-letter test set. I-R, using counts of major omissions only, was 93.9% for the training set and 92.5% for the test set. PMID:7719796

A machine learning based approach to identify protected health information in Chinese clinical text.

PubMed

Du, Liting; Xia, Chenxi; Deng, Zhaohua; Lu, Gary; Xia, Shuxu; Ma, Jingdong

2018-08-01

With the increasing application of electronic health records (EHRs) in the world, protecting private information in clinical text has drawn extensive attention from healthcare providers to researchers. De-identification, the process of identifying and removing protected health information (PHI) from clinical text, has been central to the discourse on medical privacy since 2006. While de-identification is becoming the global norm for handling medical records, there is a paucity of studies on its application on Chinese clinical text. Without efficient and effective privacy protection algorithms in place, the use of indispensable clinical information would be confined. We aimed to (i) describe the current process for PHI in China, (ii) propose a machine learning based approach to identify PHI in Chinese clinical text, and (iii) validate the effectiveness of the machine learning algorithm for de-identification in Chinese clinical text. Based on 14,719 discharge summaries from regional health centers in Ya'an City, Sichuan province, China, we built a conditional random fields (CRF) model to identify PHI in clinical text, and then used the regular expressions to optimize the recognition results of the PHI categories with fewer samples. We constructed a Chinese clinical text corpus with PHI tags through substantial manual annotation, wherein the descriptive statistics of PHI manifested its wide range and diverse categories. The evaluation showed with a high F-measure of 0.9878 that our CRF-based model had a good performance for identifying PHI in Chinese clinical text. The rapid adoption of EHR in the health sector has created an urgent need for tools that can parse patient specific information from Chinese clinical text. Our application of CRF algorithms for de-identification has shown the potential to meet this need by offering a highly accurate and flexible solution to analyzing Chinese clinical text. Copyright © 2018 Elsevier B.V. All rights reserved.

Medical school clinical placements - the optimal method for assessing the clinical educational environment from a graduate entry perspective.

PubMed

Hyde, Sarah; Hannigan, Ailish; Dornan, Tim; McGrath, Deirdre

2018-01-05

Educational environment is a strong determinant of student satisfaction and achievement. The learning environments of medical students on clinical placements are busy workplaces, composed of many variables. There is no universally accepted method of evaluating the clinical learning environment, nor is there consensus on what concepts or aspects should be measured. The aims of this study were to compare the Dundee ready educational environment measure (DREEM - the current de facto standard) and the more recently developed Manchester clinical placement index (MCPI) for the assessment of the clinical learning environment in a graduate entry medical student cohort by correlating the scores of each and analysing free text comments. This study also explored student perceptionof how the clinical educational environment is assessed. An online, anonymous survey comprising of both the DREEM and MCPI instruments was delivered to students on clinical placement in a graduate entry medical school. Additional questions explored students' perceptions of instruments for giving feedback. Numeric variables (DREEM score, MCPI score, ratings) were tested for normality and summarised. Pearson's correlation coefficient was used to measure the strength of the association between total DREEM score and total MCPI scores. Thematic analysis was used to analyse the free text comments. The overall response rate to the questionnaire was 67% (n = 180), with a completed response rate for the MCPI of 60% (n = 161) and for the DREEM of 58% (n = 154). There was a strong, positive correlation between total DREEM and MCPI scores (r = 0.71, p < 0.001). On a scale of 0 to 7, the mean rating for how worthwhile students found completing the DREEM was 3.27 (SD 1.41) and for the MCPI was 3.49 (SD 1.57). 'Finding balance' and 'learning at work' were among the themes to emerge from analysis of free text comments. The present study confirms that DREEM and MCPI total scores are strongly correlated. Graduate entry students tended to favour this method of evaluation over the DREEM with the MCPI prompting rich description of the clinical learning environment. Further study is warranted to determine if this finding is transferable to all clinical medical student cohorts.

Understanding of safety monitoring in clinical trials by individuals with CF or their parents: A qualitative analysis.

PubMed

Kern-Goldberger, Andrew S; Hessels, Amanda J; Saiman, Lisa; Quittell, Lynne M

2018-03-14

Recruiting both pediatric and adult participants for clinical trials in CF is currently of paramount importance as numerous new therapies are being developed. However, recruitment is challenging as parents of children with CF and adults with CF cite safety concerns as a principal barrier to enrollment. In conjunction with the CF Foundation (CFF) Data Safety Monitoring Board (DSMB), a pilot brochure was developed to inform patients and parents of the multiple levels of safety monitoring; the CFF simultaneously created an infographic representing the safety monitoring process. This study explores the attitudes and beliefs of CF patients and families regarding safety monitoring and clinical trial participation, and elicits feedback regarding the educational materials. Semi-structured interviews were conducted using a pre-tested interview guide and audio-recorded during routine CF clinic visits. Participants included 5 parents of children with CF <16years old; 5 adolescents and young adults with CF 16-21years old; and 5 adults with CF ≥22years old from pediatric and adult CF centers. The study team performed systematic text condensation analysis of the recorded interviews using an iterative process. Four major thematic categories with subthemes emerged as supported by exemplar quotations: attitudes toward clinical trials, safety values, conceptualizing the safety monitoring process, and priorities for delivery of patient education. Participant feedback was used to revise the pilot brochure; text was shortened, unfamiliar words clarified (e.g., "pipeline"), abbreviations eliminated, and redundancy avoided. Qualitative analysis of CF patient and family interviews provided insights into barriers to participation in clinical trials, safety concerns, perspectives on safety monitoring and educational priorities. We plan a multicenter study to determine if the revised brochure reduces knowledge, attitude and practice barriers regarding participation in CF clinical trials. Copyright © 2018 European Cystic Fibrosis Society. Published by Elsevier B.V. All rights reserved.

Unsupervised Biomedical Named Entity Recognition: Experiments with Clinical and Biological Texts

PubMed Central

Zhang, Shaodian; Elhadad, Nóemie

2013-01-01

Named entity recognition is a crucial component of biomedical natural language processing, enabling information extraction and ultimately reasoning over and knowledge discovery from text. Much progress has been made in the design of rule-based and supervised tools, but they are often genre and task dependent. As such, adapting them to different genres of text or identifying new types of entities requires major effort in re-annotation or rule development. In this paper, we propose an unsupervised approach to extracting named entities from biomedical text. We describe a stepwise solution to tackle the challenges of entity boundary detection and entity type classification without relying on any handcrafted rules, heuristics, or annotated data. A noun phrase chunker followed by a filter based on inverse document frequency extracts candidate entities from free text. Classification of candidate entities into categories of interest is carried out by leveraging principles from distributional semantics. Experiments show that our system, especially the entity classification step, yields competitive results on two popular biomedical datasets of clinical notes and biological literature, and outperforms a baseline dictionary match approach. Detailed error analysis provides a road map for future work. PMID:23954592

Educational effects using a robot patient simulation system for development of clinical attitude.

PubMed

Abe, S; Noguchi, N; Matsuka, Y; Shinohara, C; Kimura, T; Oka, K; Okura, K; Rodis, O M M; Kawano, F

2017-11-01

The aim of this study was to assess the effectiveness of improving the attitude of dental students towards the use of a full-body patient simulation system (SIMROID) compared to the traditional mannequin (CLINSIM) for dental clinical education. The participants were 10 male undergraduate dental students who had finished clinical training in the university hospital 1 year before this study started. They performed a crown preparation on an upper pre-molar tooth using SIMROID and CLINSIM as the practical clinical trials. The elapsed time for preparation was recorded. The taper of the abutment teeth was measured using a 3-dimensional shape-measuring device after this trial. In addition, a self-reported questionnaire was collected that included physical pain, treatment safety and maintaining a clean area for each simulator. Qualitative data analysis of a free format report about SIMROID was performed using text mining analysis. This trial was performed twice at 1-month intervals. The students considered physical pain, treatment safety and a clean area for SIMROID significantly better than that for CLINSIM (P < .01). The elapsed time of preparation in the second practical clinical trial was significantly lower than in the first for SIMROID and CLINSIM (P < .01). However, there were no significant differences between the abutment tapers for both systems. For the text mining analysis, most of the students wrote that SIMROID was similar to real patients. The use of SIMROID was proven to be effective in improving the attitude of students towards patients, thereby giving importance to considerations for actual patients during dental treatment. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Study design in high-dimensional classification analysis.

PubMed

Sánchez, Brisa N; Wu, Meihua; Song, Peter X K; Wang, Wen

2016-10-01

Advances in high throughput technology have accelerated the use of hundreds to millions of biomarkers to construct classifiers that partition patients into different clinical conditions. Prior to classifier development in actual studies, a critical need is to determine the sample size required to reach a specified classification precision. We develop a systematic approach for sample size determination in high-dimensional (large [Formula: see text] small [Formula: see text]) classification analysis. Our method utilizes the probability of correct classification (PCC) as the optimization objective function and incorporates the higher criticism thresholding procedure for classifier development. Further, we derive the theoretical bound of maximal PCC gain from feature augmentation (e.g. when molecular and clinical predictors are combined in classifier development). Our methods are motivated and illustrated by a study using proteomics markers to classify post-kidney transplantation patients into stable and rejecting classes. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Online discourse on fibromyalgia: text-mining to identify clinical distinction and patient concerns.

PubMed

Park, Jungsik; Ryu, Young Uk

2014-10-07

The purpose of this study was to evaluate the possibility of using text-mining to identify clinical distinctions and patient concerns in online memoires posted by patients with fibromyalgia (FM). A total of 399 memoirs were collected from an FM group website. The unstructured data of memoirs associated with FM were collected through a crawling process and converted into structured data with a concordance, parts of speech tagging, and word frequency. We also conducted a lexical analysis and phrase pattern identification. After examining the data, a set of FM-related keywords were obtained and phrase net relationships were set through a web-based visualization tool. The clinical distinction of FM was verified. Pain is the biggest issue to the FM patients. The pains were affecting body parts including 'muscles,' 'leg,' 'neck,' 'back,' 'joints,' and 'shoulders' with accompanying symptoms such as 'spasms,' 'stiffness,' and 'aching,' and were described as 'sever,' 'chronic,' and 'constant.' This study also demonstrated that it was possible to understand the interests and concerns of FM patients through text-mining. FM patients wanted to escape from the pain and symptoms, so they were interested in medical treatment and help. Also, they seemed to have interest in their work and occupation, and hope to continue to live life through the relationships with the people around them. This research shows the potential for extracting keywords to confirm the clinical distinction of a certain disease, and text-mining can help objectively understand the concerns of patients by generalizing their large number of subjective illness experiences. However, it is believed that there are limitations to the processes and methods for organizing and classifying large amounts of text, so these limits have to be considered when analyzing the results. The development of research methodology to overcome these limitations is greatly needed.

[Text Comprehensibility of Hospital Report Cards].

PubMed

Sander, U; Kolb, B; Christoph, C; Emmert, M

2016-12-01

Objectives: Recently, the number of hospital report cards that compare quality of hospitals and present information from German quality reports has greatly increased. Objectives of this study were to a) identify suitable methods for measuring the readability and comprehensibility of hospital report cards, b) to obtain reliable information on the comprehensibility of texts for laymen, c) to give recommendations for improvements and d) to recommend public health actions. Methods: The readability and comprehensibility of the texts were tested with a) a computer-aided evaluation of formal text characteristics (readability indices Flesch (German formula) and 1. Wiener Sachtextformel formula), b) an expert-based heuristic analysis of readability and comprehensibility of texts (counting technical terms and analysis of text simplicity as well as brevity and conciseness using the Hamburg intelligibility model) and c) a survey of subjects about the comprehensibility of individual technical terms, the assessment of the comprehensibility of the presentations and the subjects' decisions in favour of one of the 5 presented clinics due to the better quality of data. In addition, the correlation between the results of the text analysis with the results from the survey of subjects was tested. Results: The assessment of texts with the computer-aided evaluations showed poor comprehensibility values. The assessment of text simplicity using the Hamburg intelligibility model showed poor comprehensibility values (-0.3). On average, 6.8% of the words used were technical terms. A review of 10 technical terms revealed that in all cases only a minority of respondents (from 4.4% to 39.1%) exactly knew what was meant by each of them. Most subjects (62.4%) also believed that unclear terms worsened their understanding of the information offered. The correlation analysis showed that presentations with a lower frequency of technical terms and better values for the text simplicity were better understood. Conclusion: The determination of the frequency of technical terms and the assessment of text simplicity using the Hamburg intelligibility model were suitable methods to determine the readability and comprehensibility of presentations of quality indicators. The analysis showed predominantly poor comprehensibility values and indicated the need to improve the texts of report cards. © Georg Thieme Verlag KG Stuttgart · New York.

The Database for Aggregate Analysis of ClinicalTrials.gov (AACT) and Subsequent Regrouping by Clinical Specialty

PubMed Central

Tasneem, Asba; Aberle, Laura; Ananth, Hari; Chakraborty, Swati; Chiswell, Karen; McCourt, Brian J.; Pietrobon, Ricardo

2012-01-01

Background The ClinicalTrials.gov registry provides information regarding characteristics of past, current, and planned clinical studies to patients, clinicians, and researchers; in addition, registry data are available for bulk download. However, issues related to data structure, nomenclature, and changes in data collection over time present challenges to the aggregate analysis and interpretation of these data in general and to the analysis of trials according to clinical specialty in particular. Improving usability of these data could enhance the utility of ClinicalTrials.gov as a research resource. Methods/Principal Results The purpose of our project was twofold. First, we sought to extend the usability of ClinicalTrials.gov for research purposes by developing a database for aggregate analysis of ClinicalTrials.gov (AACT) that contains data from the 96,346 clinical trials registered as of September 27, 2010. Second, we developed and validated a methodology for annotating studies by clinical specialty, using a custom taxonomy employing Medical Subject Heading (MeSH) terms applied by an NLM algorithm, as well as MeSH terms and other disease condition terms provided by study sponsors. Clinical specialists reviewed and annotated MeSH and non-MeSH disease condition terms, and an algorithm was created to classify studies into clinical specialties based on both MeSH and non-MeSH annotations. False positives and false negatives were evaluated by comparing algorithmic classification with manual classification for three specialties. Conclusions/Significance The resulting AACT database features study design attributes parsed into discrete fields, integrated metadata, and an integrated MeSH thesaurus, and is available for download as Oracle extracts (.dmp file and text format). This publicly-accessible dataset will facilitate analysis of studies and permit detailed characterization and analysis of the U.S. clinical trials enterprise as a whole. In addition, the methodology we present for creating specialty datasets may facilitate other efforts to analyze studies by specialty groups. PMID:22438982

The database for aggregate analysis of ClinicalTrials.gov (AACT) and subsequent regrouping by clinical specialty.

PubMed

Tasneem, Asba; Aberle, Laura; Ananth, Hari; Chakraborty, Swati; Chiswell, Karen; McCourt, Brian J; Pietrobon, Ricardo

2012-01-01

The ClinicalTrials.gov registry provides information regarding characteristics of past, current, and planned clinical studies to patients, clinicians, and researchers; in addition, registry data are available for bulk download. However, issues related to data structure, nomenclature, and changes in data collection over time present challenges to the aggregate analysis and interpretation of these data in general and to the analysis of trials according to clinical specialty in particular. Improving usability of these data could enhance the utility of ClinicalTrials.gov as a research resource. The purpose of our project was twofold. First, we sought to extend the usability of ClinicalTrials.gov for research purposes by developing a database for aggregate analysis of ClinicalTrials.gov (AACT) that contains data from the 96,346 clinical trials registered as of September 27, 2010. Second, we developed and validated a methodology for annotating studies by clinical specialty, using a custom taxonomy employing Medical Subject Heading (MeSH) terms applied by an NLM algorithm, as well as MeSH terms and other disease condition terms provided by study sponsors. Clinical specialists reviewed and annotated MeSH and non-MeSH disease condition terms, and an algorithm was created to classify studies into clinical specialties based on both MeSH and non-MeSH annotations. False positives and false negatives were evaluated by comparing algorithmic classification with manual classification for three specialties. The resulting AACT database features study design attributes parsed into discrete fields, integrated metadata, and an integrated MeSH thesaurus, and is available for download as Oracle extracts (.dmp file and text format). This publicly-accessible dataset will facilitate analysis of studies and permit detailed characterization and analysis of the U.S. clinical trials enterprise as a whole. In addition, the methodology we present for creating specialty datasets may facilitate other efforts to analyze studies by specialty groups.

Lessons learned from IDeAl - 33 recommendations from the IDeAl-net about design and analysis of small population clinical trials.

PubMed

Hilgers, Ralf-Dieter; Bogdan, Malgorzata; Burman, Carl-Fredrik; Dette, Holger; Karlsson, Mats; König, Franz; Male, Christoph; Mentré, France; Molenberghs, Geert; Senn, Stephen

2018-05-11

IDeAl (Integrated designs and analysis of small population clinical trials) is an EU funded project developing new statistical design and analysis methodologies for clinical trials in small population groups. Here we provide an overview of IDeAl findings and give recommendations to applied researchers. The description of the findings is broken down by the nine scientific IDeAl work packages and summarizes results from the project's more than 60 publications to date in peer reviewed journals. In addition, we applied text mining to evaluate the publications and the IDeAl work packages' output in relation to the design and analysis terms derived from in the IRDiRC task force report on small population clinical trials. The results are summarized, describing the developments from an applied viewpoint. The main result presented here are 33 practical recommendations drawn from the work, giving researchers a comprehensive guidance to the improved methodology. In particular, the findings will help design and analyse efficient clinical trials in rare diseases with limited number of patients available. We developed a network representation relating the hot topics developed by the IRDiRC task force on small population clinical trials to IDeAl's work as well as relating important methodologies by IDeAl's definition necessary to consider in design and analysis of small-population clinical trials. These network representation establish a new perspective on design and analysis of small-population clinical trials. IDeAl has provided a huge number of options to refine the statistical methodology for small-population clinical trials from various perspectives. A total of 33 recommendations developed and related to the work packages help the researcher to design small population clinical trial. The route to improvements is displayed in IDeAl-network representing important statistical methodological skills necessary to design and analysis of small-population clinical trials. The methods are ready for use.

Analysis of Documentation Speed Using Web-Based Medical Speech Recognition Technology: Randomized Controlled Trial.

PubMed

Vogel, Markus; Kaisers, Wolfgang; Wassmuth, Ralf; Mayatepek, Ertan

2015-11-03

Clinical documentation has undergone a change due to the usage of electronic health records. The core element is to capture clinical findings and document therapy electronically. Health care personnel spend a significant portion of their time on the computer. Alternatives to self-typing, such as speech recognition, are currently believed to increase documentation efficiency and quality, as well as satisfaction of health professionals while accomplishing clinical documentation, but few studies in this area have been published to date. This study describes the effects of using a Web-based medical speech recognition system for clinical documentation in a university hospital on (1) documentation speed, (2) document length, and (3) physician satisfaction. Reports of 28 physicians were randomized to be created with (intervention) or without (control) the assistance of a Web-based system of medical automatic speech recognition (ASR) in the German language. The documentation was entered into a browser's text area and the time to complete the documentation including all necessary corrections, correction effort, number of characters, and mood of participant were stored in a database. The underlying time comprised text entering, text correction, and finalization of the documentation event. Participants self-assessed their moods on a scale of 1-3 (1=good, 2=moderate, 3=bad). Statistical analysis was done using permutation tests. The number of clinical reports eligible for further analysis stood at 1455. Out of 1455 reports, 718 (49.35%) were assisted by ASR and 737 (50.65%) were not assisted by ASR. Average documentation speed without ASR was 173 (SD 101) characters per minute, while it was 217 (SD 120) characters per minute using ASR. The overall increase in documentation speed through Web-based ASR assistance was 26% (P=.04). Participants documented an average of 356 (SD 388) characters per report when not assisted by ASR and 649 (SD 561) characters per report when assisted by ASR. Participants' average mood rating was 1.3 (SD 0.6) using ASR assistance compared to 1.6 (SD 0.7) without ASR assistance (P<.001). We conclude that medical documentation with the assistance of Web-based speech recognition leads to an increase in documentation speed, document length, and participant mood when compared to self-typing. Speech recognition is a meaningful and effective tool for the clinical documentation process.

Subgraph augmented non-negative tensor factorization (SANTF) for modeling clinical narrative text

PubMed Central

Xin, Yu; Hochberg, Ephraim; Joshi, Rohit; Uzuner, Ozlem; Szolovits, Peter

2015-01-01

Objective Extracting medical knowledge from electronic medical records requires automated approaches to combat scalability limitations and selection biases. However, existing machine learning approaches are often regarded by clinicians as black boxes. Moreover, training data for these automated approaches at often sparsely annotated at best. The authors target unsupervised learning for modeling clinical narrative text, aiming at improving both accuracy and interpretability. Methods The authors introduce a novel framework named subgraph augmented non-negative tensor factorization (SANTF). In addition to relying on atomic features (e.g., words in clinical narrative text), SANTF automatically mines higher-order features (e.g., relations of lymphoid cells expressing antigens) from clinical narrative text by converting sentences into a graph representation and identifying important subgraphs. The authors compose a tensor using patients, higher-order features, and atomic features as its respective modes. We then apply non-negative tensor factorization to cluster patients, and simultaneously identify latent groups of higher-order features that link to patient clusters, as in clinical guidelines where a panel of immunophenotypic features and laboratory results are used to specify diagnostic criteria. Results and Conclusion SANTF demonstrated over 10% improvement in averaged F-measure on patient clustering compared to widely used non-negative matrix factorization (NMF) and k-means clustering methods. Multiple baselines were established by modeling patient data using patient-by-features matrices with different feature configurations and then performing NMF or k-means to cluster patients. Feature analysis identified latent groups of higher-order features that lead to medical insights. We also found that the latent groups of atomic features help to better correlate the latent groups of higher-order features. PMID:25862765

The outcomes and acceptability of near-peer teaching among medical students in clinical skills.

PubMed

Khaw, Carole; Raw, Lynne

2016-06-12

To determine the outcomes and acceptability of final-year students tutoring in Clinical Skills to Years 1-2 students in a 4-week Medical Education elective. A paper-based survey with 14 questions requiring responses on a Likert-like scale and 2 questions with free-text responses was used to investigate Year 6 student-tutor (n=45) and Years 1-2 tutee (n=348) perceptions of near-peer teaching in Clinical Skills. The independent t-test compared mean responses from student-tutors and tutees, and thematic analysis of free-text responses was conducted. Tutee perceptions were significantly higher than student-tutor self-perceptions in small-group teaching and facilitation skills (p=0.000), teaching history-taking skills (p=0.046) and teaching physical examination skills (p=0.000). Perceptions in aspects of 'Confidence in tutoring' were not significantly different for student-tutors and tutees, with both having lowest perceptions for identifying and providing remediation for underperforming tutees. Student-tutors rated all areas of personal and professional development highly. Main themes emerging from analysis of student comments were the benefits to student-tutors, benefits to tutees and areas needing improvement, with outcomes of this near-peer teaching relating well to cognitive and social theories in the literature. Both student tutors and their tutees perceived near-peer teaching in Clinical Skills to be acceptable and beneficial with particular implications for Medical Education.

[Pilot study of domain-specific terminology adaptation for morphological analysis: research on unknown terms in national examination documents of radiological technologists].

PubMed

Tsuji, Shintarou; Nishimoto, Naoki; Ogasawara, Katsuhiko

2008-07-20

Although large medical texts are stored in electronic format, they are seldom reused because of the difficulty of processing narrative texts by computer. Morphological analysis is a key technology for extracting medical terms correctly and automatically. This process parses a sentence into its smallest unit, the morpheme. Phrases consisting of two or more technical terms, however, cause morphological analysis software to fail in parsing the sentence and output unprocessed terms as "unknown words." The purpose of this study was to reduce the number of unknown words in medical narrative text processing. The results of parsing the text with additional dictionaries were compared with the analysis of the number of unknown words in the national examination for radiologists. The ratio of unknown words was reduced 1.0% to 0.36% by adding terminologies of radiological technology, MeSH, and ICD-10 labels. The terminology of radiological technology was the most effective resource, being reduced by 0.62%. This result clearly showed the necessity of additional dictionary selection and trends in unknown words. The potential for this investigation is to make available a large body of clinical information that would otherwise be inaccessible for applications other than manual health care review by personnel.

Students' Learning Experiences from Didactic Teaching Sessions Including Patient Case Examples as Either Text or Video: A Qualitative Study.

PubMed

Pedersen, Kamilla; Moeller, Martin Holdgaard; Paltved, Charlotte; Mors, Ole; Ringsted, Charlotte; Morcke, Anne Mette

2017-10-06

The aim of this study was to explore medical students' learning experiences from the didactic teaching formats using either text-based patient cases or video-based patient cases with similar content. The authors explored how the two different patient case formats influenced students' perceptions of psychiatric patients and students' reflections on meeting and communicating with psychiatric patients. The authors conducted group interviews with 30 medical students who volunteered to participate in interviews and applied inductive thematic content analysis to the transcribed interviews. Students taught with text-based patient cases emphasized excitement and drama towards the personal clinical narratives presented by the teachers during the course, but never referred to the patient cases. Authority and boundary setting were regarded as important in managing patients. Students taught with video-based patient cases, in contrast, often referred to the patient cases when highlighting new insights, including the importance of patient perspectives when communicating with patients. The format of patient cases included in teaching may have a substantial impact on students' patient-centeredness. Video-based patient cases are probably more effective than text-based patient cases in fostering patient-centered perspectives in medical students. Teachers sharing stories from their own clinical experiences stimulates both engagement and excitement, but may also provoke unintended stigma and influence an authoritative approach in medical students towards managing patients in clinical psychiatry.

Care by cell phone: text messaging for chronic disease management.

PubMed

Fischer, Henry H; Moore, Susan L; Ginosar, David; Davidson, Arthur J; Rice-Peterson, Cecilia M; Durfee, Michael J; MacKenzie, Thomas D; Estacio, Raymond O; Steele, Andrew W

2012-02-01

To assess the feasibility of engaging adults with diabetes in self management behaviors between clinic visits by using cell phone text messaging to provide blood sugar measurement prompts and appointment reminders. Quasi-experimental pilot among adult diabetic patients with cell phones who receive regular care at a federally qualified community health center in Denver, Colorado, which serves a population that is predominantly either uninsured (41%) or on Medicaid or Medicare (56%). Patients (N = 47) received text message prompts over a 3-month period. Blood sugar readings were requested 3 times per week (Monday, Wednesday, and Friday). Reminders were sent 7, 3, and 1 day(s) before each scheduled appointment. Acknowledgments were returned for all patient-sent messages. Focus groups were conducted in English and Spanish with selected patients (n = 8). Patients of all ages were active participants. Correctly formatted responses were received for 67.3% of 1585 prompts. More than three-fourths (79%) of the cohort responded to more than 50% of their prompts. The appointment analysis was underpowered to detect significant changes in attendance. Participants reported increased social support, feelings that the program "made them accountable," and increased awareness of health information. Two-thirds (66%) of patients provided glucose readings when prompted during the study, compared with 12% at 2 preceding clinic visits. For certain patients, cell phone-based text messaging may enhance chronic disease management support and patient-provider communications beyond the clinic setting.

[Characteristics of clinical trials in Hungary based on the analysis of an international database].

PubMed

Tóth, Tamás; Pollner, Péter; Palla, Gergely; Dinya, Elek

2017-03-01

Intorduction: The ClinicalTrials.gov website, which is operated by the US government, collects data about clinical trials. We have processed data related to Hungary by downloading from the website as XML files. Most of the data describe trials performed after 2000, so we got an overview about the clinical research of the last 10 to 15 years. As the majority of the data fields are collected as free text, significant data cleaning was needed. The database contained 2863 trials related to Hungary from 189 settlements. Only 20 per cent of the actual research organizations could have been identified as many times only an "id" number or a general name was given, thus this information was anonymised in many cases. Besides the analysis of the information obtained from this database, our study points out the relevant issues that may influence the international view of the Hungarian clinical research. Orv. Hetil., 2017, 158(9), 345-351.

Comparison of warfarin therapy clinical outcomes following implementation of an automated mobile phone-based critical laboratory value text alert system.

PubMed

Lin, Shu-Wen; Kang, Wen-Yi; Lin, Dong-Tsamn; Lee, James; Wu, Fe-Lin; Chen, Chuen-Liang; Tseng, Yufeng J

2014-01-01

Computerized alert and reminder systems have been widely accepted and applied to various patient care settings, with increasing numbers of clinical laboratories communicating critical laboratory test values to professionals via either manual notification or automated alerting systems/computerized reminders. Warfarin, an oral anticoagulant, exhibits narrow therapeutic range between treatment response and adverse events. It requires close monitoring of prothrombin time (PT)/international normalized ratio (INR) to ensure patient safety. This study was aimed to evaluate clinical outcomes of patients on warfarin therapy following implementation of a Personal Handy-phone System-based (PHS) alert system capable of generating and delivering text messages to communicate critical PT/INR laboratory results to practitioners' mobile phones in a large tertiary teaching hospital. A retrospective analysis was performed comparing patient clinical outcomes and physician prescribing behavior following conversion from a manual laboratory result alert system to an automated system. Clinical outcomes and practitioner responses to both alert systems were compared. Complications to warfarin therapy, warfarin utilization, and PT/INR results were evaluated for both systems, as well as clinician time to read alert messages, time to warfarin therapy modification, and monitoring frequency. No significant differences were detected in major hemorrhage and thromboembolism, warfarin prescribing patterns, PT/INR results, warfarin therapy modification, or monitoring frequency following implementation of the PHS text alert system. In both study periods, approximately 80% of critical results led to warfarin discontinuation or dose reduction. Senior physicians' follow-up response time to critical results was significantly decreased in the PHS alert study period (46.3% responded within 1 day) compared to the manual notification study period (24.7%; P = 0.015). No difference in follow-up response time was detected for junior physicians. Implementation of an automated PHS-based text alert system did not adversely impact clinical or safety outcomes of patients on warfarin therapy. Approximately 80% immediate recognition of text alerts was achieved. The potential benefits of an automated PHS alert for senior physicians were demonstrated.

Design of an extensive information representation scheme for clinical narratives.

PubMed

Deléger, Louise; Campillos, Leonardo; Ligozat, Anne-Laure; Névéol, Aurélie

2017-09-11

Knowledge representation frameworks are essential to the understanding of complex biomedical processes, and to the analysis of biomedical texts that describe them. Combined with natural language processing (NLP), they have the potential to contribute to retrospective studies by unlocking important phenotyping information contained in the narrative content of electronic health records (EHRs). This work aims to develop an extensive information representation scheme for clinical information contained in EHR narratives, and to support secondary use of EHR narrative data to answer clinical questions. We review recent work that proposed information representation schemes and applied them to the analysis of clinical narratives. We then propose a unifying scheme that supports the extraction of information to address a large variety of clinical questions. We devised a new information representation scheme for clinical narratives that comprises 13 entities, 11 attributes and 37 relations. The associated annotation guidelines can be used to consistently apply the scheme to clinical narratives and are https://cabernet.limsi.fr/annotation_guide_for_the_merlot_french_clinical_corpus-Sept2016.pdf . The information scheme includes many elements of the major schemes described in the clinical natural language processing literature, as well as a uniquely detailed set of relations.

Secure Secondary Use of Clinical Data with Cloud-based NLP Services. Towards a Highly Scalable Research Infrastructure.

PubMed

Christoph, J; Griebel, L; Leb, I; Engel, I; Köpcke, F; Toddenroth, D; Prokosch, H-U; Laufer, J; Marquardt, K; Sedlmayr, M

2015-01-01

The secondary use of clinical data provides large opportunities for clinical and translational research as well as quality assurance projects. For such purposes, it is necessary to provide a flexible and scalable infrastructure that is compliant with privacy requirements. The major goals of the cloud4health project are to define such an architecture, to implement a technical prototype that fulfills these requirements and to evaluate it with three use cases. The architecture provides components for multiple data provider sites such as hospitals to extract free text as well as structured data from local sources and de-identify such data for further anonymous or pseudonymous processing. Free text documentation is analyzed and transformed into structured information by text-mining services, which are provided within a cloud-computing environment. Thus, newly gained annotations can be integrated along with the already available structured data items and the resulting data sets can be uploaded to a central study portal for further analysis. Based on the architecture design, a prototype has been implemented and is under evaluation in three clinical use cases. Data from several hundred patients provided by a University Hospital and a private hospital chain have already been processed. Cloud4health has shown how existing components for secondary use of structured data can be complemented with text-mining in a privacy compliant manner. The cloud-computing paradigm allows a flexible and dynamically adaptable service provision that facilitates the adoption of services by data providers without own investments in respective hardware resources and software tools.

Exploring associations of clinical and social parameters with violent behaviors among psychiatric patients.

PubMed

Dai, Hong-Jie; Su, Emily Chia-Yu; Uddin, Mohy; Jonnagaddala, Jitendra; Wu, Chi-Shin; Syed-Abdul, Shabbir

2017-11-01

Evidence has revealed interesting associations of clinical and social parameters with violent behaviors of patients with psychiatric disorders. Men are more violent preceding and during hospitalization, whereas women are more violent than men throughout the 3days following a hospital admission. It has also been proven that mental disorders may be a consistent risk factor for the occurrence of violence. In order to better understand violent behaviors of patients with psychiatric disorders, it is important to investigate both the clinical symptoms and psychosocial factors that accompany violence in these patients. In this study, we utilized a dataset released by the Partners Healthcare and Neuropsychiatric Genome-scale and RDoC Individualized Domains project of Harvard Medical School to develop a unique text mining pipeline that processes unstructured clinical data in order to recognize clinical and social parameters such asage, gender, history of alcohol use, and violent behaviors, and explored the associations between these parameters and violent behaviors of patients with psychiatric disorders. The aim of our work was to demonstrate the feasibility of mining factors that are strongly associated with violent behaviors among psychiatric patients from unstructured psychiatric evaluation records using clinical text mining. Experiment results showed that stimulants, followed by a family history of violent behavior, suicidal behaviors, and financial stress were strongly associated with violent behaviors. Key aspects explicated in this paper include employing our text mining pipeline to extract clinical and social factors linked with violent behaviors, generating association rules to uncover possible associations between these factors and violent behaviors, and lastly the ranking of top rules associated with violent behaviors using statistical analysis and interpretation. Copyright © 2017. Published by Elsevier Inc.

Improving treatment adherence for blood pressure lowering via mobile phone SMS-messages in South Africa: a qualitative evaluation of the SMS-text Adherence SuppoRt (StAR) trial.

PubMed

Leon, Natalie; Surender, Rebecca; Bobrow, Kirsty; Muller, Jocelyn; Farmer, Andrew

2015-07-03

Effective use of proven treatments for high blood pressure, a preventable health risk, is challenging for many patients. Prompts via mobile phone SMS-text messaging may improve adherence to clinic visits and treatment, though more research is needed on impact and patient perceptions of such support interventions, especially in low-resource settings. An individually-randomised controlled trial in a primary care clinic in Cape Town (2012-14), tested the effect of an adherence support intervention delivered via SMS-texts, on blood pressure control and adherence to medication, for hypertensive patients. ( ClinicalTrials.gov NCT02019823). We report on a qualitative evaluation that explored the trial participants' experiences and responses to the SMS-text messages, and identified barriers and facilitators to delivering adherence support via patients' own mobile phones. Two focus groups and fifteen individual interviews were conducted. We used comparative and thematic analysis approaches to identify themes and triangulated our analysis amongst three researchers. Most participants were comfortable with the technology of using SMS-text messages. Messages were experienced as acceptable, relevant and useful to a broad range of participants. The SMS-content, the respectful tone and the delivery (timing of reminders and frequency) and the relational aspect of trial participation (feeling cared for) were all highly valued. A subgroup who benefitted the most, were those who had been struggling with adherence due to high levels of personal stress. The intervention appeared to coincide with their readiness for change, and provided practical and emotional support for improving adherence behaviour. Change may have been facilitated through increased acknowledgement of their health status and attitudinal change towards greater self-responsibility. Complex interaction of psycho-social stressors and health service problems were reported as broader challenges to adherence behaviours. Adherence support for treatment of raised blood pressure, delivered via SMS-text message on the patient's own phone, was found to be acceptable, relevant and helpful, even for those who already had their own reminder systems in place. Our findings begin to identify for whom and what core elements of the SMS-text message intervention appear to work best in a low-resource operational setting, issues that future research should explore in greater depth.

Quantitative Analysis of Uncertainty in Medical Reporting: Creating a Standardized and Objective Methodology.

PubMed

Reiner, Bruce I

2018-04-01

Uncertainty in text-based medical reports has long been recognized as problematic, frequently resulting in misunderstanding and miscommunication. One strategy for addressing the negative clinical ramifications of report uncertainty would be the creation of a standardized methodology for characterizing and quantifying uncertainty language, which could provide both the report author and reader with context related to the perceived level of diagnostic confidence and accuracy. A number of computerized strategies could be employed in the creation of this analysis including string search, natural language processing and understanding, histogram analysis, topic modeling, and machine learning. The derived uncertainty data offers the potential to objectively analyze report uncertainty in real time and correlate with outcomes analysis for the purpose of context and user-specific decision support at the point of care, where intervention would have the greatest clinical impact.

The early evolution of Jean Piaget's clinical method.

PubMed

Mayer, Susan Jean

2005-11-01

This article analyzes the early evolution of Jean Piaget's renowned "clinical method" in order to investigate the method's strikingly original and generative character. Throughout his 1st decade in the field, Piaget frequently discussed and justified the many different approaches to data collection he used. Analysis of his methodological progression during this period reveals that Piaget's determination to access the genuine convictions of children eventually led him to combine 3 distinct traditions in which he had been trained-naturalistic observation, psychometrics, and the psychiatric clinical examination. It was in this amalgam, first evident in his 4th text, that Piaget discovered the clinical dynamic that would drive the classic experiments for which he is most well known.

Prevalence Estimation of Protected Health Information in Swedish Clinical Text.

PubMed

Henriksson, Aron; Kvist, Maria; Dalianis, Hercules

2017-01-01

Obscuring protected health information (PHI) in the clinical text of health records facilitates the secondary use of healthcare data in a privacy-preserving manner. Although automatic de-identification of clinical text using machine learning holds much promise, little is known about the relative prevalence of PHI in different types of clinical text and whether there is a need for domain adaptation when learning predictive models from one particular domain and applying it to another. In this study, we address these questions by training a predictive model and using it to estimate the prevalence of PHI in clinical text written (1) in different clinical specialties, (2) in different types of notes (i.e., under different headings), and (3) by persons in different professional roles. It is demonstrated that the overall PHI density is 1.57%; however, substantial differences exist across domains.

Interleukin and interleukin receptor gene polymorphisms in inflammatory bowel diseases susceptibility.

PubMed

Magyari, Lili; Kovesdi, Erzsebet; Sarlos, Patricia; Javorhazy, Andras; Sumegi, Katalin; Melegh, Bela

2014-03-28

Inflammatory bowel disease (IBD), which includes Crohn's disease (CD) and ulcerative colitis (UC), represents a group of chronic inflammatory disorders caused by dysregulated immune responses in genetically predisposed individuals. Genetic markers are associated with disease phenotype and long-term evolution, but their value in everyday clinical practice is limited at the moment. IBD has a clear immunological background and interleukins play key role in the process. Almost 130 original papers were revised including meta-analysis. It is clear these data are very important for understanding the base of the disease, especially in terms of clinical utility and validity, but text often do not available for the doctors use these in the clinical practice nowadays. We conducted a systematic review of the current literature on interleukin and interleukin receptor gene polymorphisms associated with IBD, performing an electronic search of PubMed Database from publications of the last 10 years, and used the following medical subject heading terms and/or text words: IBD, CD, UC, interleukins and polymorphisms.

Interleukin and interleukin receptor gene polymorphisms in inflammatory bowel diseases susceptibility

PubMed Central

Magyari, Lili; Kovesdi, Erzsebet; Sarlos, Patricia; Javorhazy, Andras; Sumegi, Katalin; Melegh, Bela

2014-01-01

Inflammatory bowel disease (IBD), which includes Crohn’s disease (CD) and ulcerative colitis (UC), represents a group of chronic inflammatory disorders caused by dysregulated immune responses in genetically predisposed individuals. Genetic markers are associated with disease phenotype and long-term evolution, but their value in everyday clinical practice is limited at the moment. IBD has a clear immunological background and interleukins play key role in the process. Almost 130 original papers were revised including meta-analysis. It is clear these data are very important for understanding the base of the disease, especially in terms of clinical utility and validity, but text often do not available for the doctors use these in the clinical practice nowadays. We conducted a systematic review of the current literature on interleukin and interleukin receptor gene polymorphisms associated with IBD, performing an electronic search of PubMed Database from publications of the last 10 years, and used the following medical subject heading terms and/or text words: IBD, CD, UC, interleukins and polymorphisms. PMID:24695754

Profiling Lung Cancer Patients Using Electronic Health Records.

PubMed

Menasalvas Ruiz, Ernestina; Tuñas, Juan Manuel; Bermejo, Guzmán; Gonzalo Martín, Consuelo; Rodríguez-González, Alejandro; Zanin, Massimiliano; González de Pedro, Cristina; Méndez, Marta; Zaretskaia, Olga; Rey, Jesús; Parejo, Consuelo; Cruz Bermudez, Juan Luis; Provencio, Mariano

2018-05-31

If Electronic Health Records contain a large amount of information about the patient's condition and response to treatment, which can potentially revolutionize the clinical practice, such information is seldom considered due to the complexity of its extraction and analysis. We here report on a first integration of an NLP framework for the analysis of clinical records of lung cancer patients making use of a telephone assistance service of a major Spanish hospital. We specifically show how some relevant data, about patient demographics and health condition, can be extracted; and how some relevant analyses can be performed, aimed at improving the usefulness of the service. We thus demonstrate that the use of EHR texts, and their integration inside a data analysis framework, is technically feasible and worth of further study.

Challenges and Insights in Using HIPAA Privacy Rule for Clinical Text Annotation.

PubMed

Kayaalp, Mehmet; Browne, Allen C; Sagan, Pamela; McGee, Tyne; McDonald, Clement J

2015-01-01

The Privacy Rule of Health Insurance Portability and Accountability Act (HIPAA) requires that clinical documents be stripped of personally identifying information before they can be released to researchers and others. We have been manually annotating clinical text since 2008 in order to test and evaluate an algorithmic clinical text de-identification tool, NLM Scrubber, which we have been developing in parallel. Although HIPAA provides some guidance about what must be de-identified, translating those guidelines into practice is not as straightforward, especially when one deals with free text. As a result we have changed our manual annotation labels and methods six times. This paper explains why we have made those annotation choices, which have been evolved throughout seven years of practice on this field. The aim of this paper is to start a community discussion towards developing standards for clinical text annotation with the end goal of studying and comparing clinical text de-identification systems more accurately.

Building a comprehensive syntactic and semantic corpus of Chinese clinical texts.

PubMed

He, Bin; Dong, Bin; Guan, Yi; Yang, Jinfeng; Jiang, Zhipeng; Yu, Qiubin; Cheng, Jianyi; Qu, Chunyan

2017-05-01

To build a comprehensive corpus covering syntactic and semantic annotations of Chinese clinical texts with corresponding annotation guidelines and methods as well as to develop tools trained on the annotated corpus, which supplies baselines for research on Chinese texts in the clinical domain. An iterative annotation method was proposed to train annotators and to develop annotation guidelines. Then, by using annotation quality assurance measures, a comprehensive corpus was built, containing annotations of part-of-speech (POS) tags, syntactic tags, entities, assertions, and relations. Inter-annotator agreement (IAA) was calculated to evaluate the annotation quality and a Chinese clinical text processing and information extraction system (CCTPIES) was developed based on our annotated corpus. The syntactic corpus consists of 138 Chinese clinical documents with 47,426 tokens and 2612 full parsing trees, while the semantic corpus includes 992 documents that annotated 39,511 entities with their assertions and 7693 relations. IAA evaluation shows that this comprehensive corpus is of good quality, and the system modules are effective. The annotated corpus makes a considerable contribution to natural language processing (NLP) research into Chinese texts in the clinical domain. However, this corpus has a number of limitations. Some additional types of clinical text should be introduced to improve corpus coverage and active learning methods should be utilized to promote annotation efficiency. In this study, several annotation guidelines and an annotation method for Chinese clinical texts were proposed, and a comprehensive corpus with its NLP modules were constructed, providing a foundation for further study of applying NLP techniques to Chinese texts in the clinical domain. Copyright © 2017. Published by Elsevier Inc.

Text de-identification for privacy protection: a study of its impact on clinical text information content.

PubMed

Meystre, Stéphane M; Ferrández, Óscar; Friedlin, F Jeffrey; South, Brett R; Shen, Shuying; Samore, Matthew H

2014-08-01

As more and more electronic clinical information is becoming easier to access for secondary uses such as clinical research, approaches that enable faster and more collaborative research while protecting patient privacy and confidentiality are becoming more important. Clinical text de-identification offers such advantages but is typically a tedious manual process. Automated Natural Language Processing (NLP) methods can alleviate this process, but their impact on subsequent uses of the automatically de-identified clinical narratives has only barely been investigated. In the context of a larger project to develop and investigate automated text de-identification for Veterans Health Administration (VHA) clinical notes, we studied the impact of automated text de-identification on clinical information in a stepwise manner. Our approach started with a high-level assessment of clinical notes informativeness and formatting, and ended with a detailed study of the overlap of select clinical information types and Protected Health Information (PHI). To investigate the informativeness (i.e., document type information, select clinical data types, and interpretation or conclusion) of VHA clinical notes, we used five different existing text de-identification systems. The informativeness was only minimally altered by these systems while formatting was only modified by one system. To examine the impact of de-identification on clinical information extraction, we compared counts of SNOMED-CT concepts found by an open source information extraction application in the original (i.e., not de-identified) version of a corpus of VHA clinical notes, and in the same corpus after de-identification. Only about 1.2-3% less SNOMED-CT concepts were found in de-identified versions of our corpus, and many of these concepts were PHI that was erroneously identified as clinical information. To study this impact in more details and assess how generalizable our findings were, we examined the overlap between select clinical information annotated in the 2010 i2b2 NLP challenge corpus and automatic PHI annotations from our best-of-breed VHA clinical text de-identification system (nicknamed 'BoB'). Overall, only 0.81% of the clinical information exactly overlapped with PHI, and 1.78% partly overlapped. We conclude that automated text de-identification's impact on clinical information is small, but not negligible, and that improved clinical acronyms and eponyms disambiguation could significantly reduce this impact. Copyright © 2014 Elsevier Inc. All rights reserved.

Medical Language Processing for Knowledge Representation and Retrievals

PubMed Central

Lyman, Margaret; Sager, Naomi; Chi, Emile C.; Tick, Leo J.; Nhan, Ngo Thanh; Su, Yun; Borst, Francois; Scherrer, Jean-Raoul

1989-01-01

The Linguistic String Project-Medical Language Processor, a system for computer analysis of narrative patient documents in English, is being adapted for French Lettres de Sortie. The system converts the free-text input to a semantic representation which is then mapped into a relational database. Retrievals of clinical data from the database are described.

Mayo clinic NLP system for patient smoking status identification.

PubMed

Savova, Guergana K; Ogren, Philip V; Duffy, Patrick H; Buntrock, James D; Chute, Christopher G

2008-01-01

This article describes our system entry for the 2006 I2B2 contest "Challenges in Natural Language Processing for Clinical Data" for the task of identifying the smoking status of patients. Our system makes the simplifying assumption that patient-level smoking status determination can be achieved by accurately classifying individual sentences from a patient's record. We created our system with reusable text analysis components built on the Unstructured Information Management Architecture and Weka. This reuse of code minimized the development effort related specifically to our smoking status classifier. We report precision, recall, F-score, and 95% exact confidence intervals for each metric. Recasting the classification task for the sentence level and reusing code from other text analysis projects allowed us to quickly build a classification system that performs with a system F-score of 92.64 based on held-out data tests and of 85.57 on the formal evaluation data. Our general medical natural language engine is easily adaptable to a real-world medical informatics application. Some of the limitations as applied to the use-case are negation detection and temporal resolution.

Vaccine adverse event text mining system for extracting features from vaccine safety reports.

PubMed

Botsis, Taxiarchis; Buttolph, Thomas; Nguyen, Michael D; Winiecki, Scott; Woo, Emily Jane; Ball, Robert

2012-01-01

To develop and evaluate a text mining system for extracting key clinical features from vaccine adverse event reporting system (VAERS) narratives to aid in the automated review of adverse event reports. Based upon clinical significance to VAERS reviewing physicians, we defined the primary (diagnosis and cause of death) and secondary features (eg, symptoms) for extraction. We built a novel vaccine adverse event text mining (VaeTM) system based on a semantic text mining strategy. The performance of VaeTM was evaluated using a total of 300 VAERS reports in three sequential evaluations of 100 reports each. Moreover, we evaluated the VaeTM contribution to case classification; an information retrieval-based approach was used for the identification of anaphylaxis cases in a set of reports and was compared with two other methods: a dedicated text classifier and an online tool. The performance metrics of VaeTM were text mining metrics: recall, precision and F-measure. We also conducted a qualitative difference analysis and calculated sensitivity and specificity for classification of anaphylaxis cases based on the above three approaches. VaeTM performed best in extracting diagnosis, second level diagnosis, drug, vaccine, and lot number features (lenient F-measure in the third evaluation: 0.897, 0.817, 0.858, 0.874, and 0.914, respectively). In terms of case classification, high sensitivity was achieved (83.1%); this was equal and better compared to the text classifier (83.1%) and the online tool (40.7%), respectively. Our VaeTM implementation of a semantic text mining strategy shows promise in providing accurate and efficient extraction of key features from VAERS narratives.

Knowledge and expectations of women undergoing cancer genetic risk assessment: a qualitative analysis of free-text questionnaire comments.

PubMed

Phelps, C; Wood, F; Bennett, P; Brain, K; Gray, J

2007-08-01

Individuals undergoing cancer genetic risk assessment have been found to have a poor understanding of the process, which may affect how well they cope with learning their risk. This paper reports free-text data from questionnaires completed by women undergoing a randomised controlled trial of a psychological intervention. Of the 268 women undergoing genetic assessment for familial breast/ovarian cancer risk who were invited to take part in the trial, 157 women returned research questionnaires. Of these, 97 women provided free-text comments upon referral to a cancer genetics clinic, 62 provided comments whilst waiting for risk information (average, moderate or high), and 36 women provided comments following notification of risk. This paper reports a thematic analysis of the free-text data. Themes reflected individuals' poor knowledge and uncertainty about genetic risk assessment. How well individuals responded to learning their risk depended upon whether expectations had been met. Regardless of risk, individuals undergoing cancer genetic risk assessment are likely to benefit from increased information about its process and timescales, and access to increased psychological support. Free-text comments can provide valuable data about individuals' expectations and knowledge of genetics services.

Patient mobile telephone 'text' reminder: a novel way to reduce non-attendance at the ENT out-patient clinic.

PubMed

Geraghty, M; Glynn, F; Amin, M; Kinsella, J

2008-03-01

Non-attendance at out-patient clinics is a seemingly intractable problem, estimated to cost 65 pounds sterling (97 euros) per incident. This results in under-utilisation of resources and prolonged waiting lists. In an effort to reduce out-patient clinic non-attendance, our ENT department, in conjunction with the information and communication technology department, instigated the use of a mobile telephone short message service ('text') reminder, to be sent out to each patient three days prior to their out-patient clinic appointment. To audit non-attendance rates at ENT out-patient clinics following the introduction of a text reminder system. Retrospective review. Non-attendance at our institution's ENT out-patient clinics was audited, following introduction of a text message reminder system in August 2003. Rates of non-attendance were compared for the text message reminder group and a historical control group. Before the introduction of the text message reminder system, the mean rate of non-attendance was 33.6 per cent. Following the introduction of the system, the mean rate of non-attendance reduced to 22 per cent. Sending text message reminders is a simple and cost-effective way to improve non-attendance at ENT out-patient clinics.

Interactive weekly mobile phone text messaging plus motivational interviewing in promotion of breastfeeding among women living with HIV in South Africa: study protocol for a randomized controlled trial.

PubMed

Zunza, Moleen; Cotton, Mark F; Mbuagbaw, Lawrence; Lester, Richard; Thabane, Lehana

2017-07-17

South Africa recently phased out access to free formula milk in the public sector in support of breastfeeding for women living with HIV. Few women living with HIV in South Africa choose breastfeeding and among those who do, many stop breastfeeding early. We sought to explore the feasibility of using mobile phone text messaging coupled with motivational interviewing to enhance adherence to breastfeeding practices. A randomized, parallel group, single-center pilot trial. Electronic sequence generation and random allocation will be done centrally. Women of low socioeconomic status, from Cape Town, South Africa will be randomly assigned within 24 h of giving birth at a primary healthcare clinic to a structured weekly text message plus motivational interviewing and usual standard of care, using a permutation of different block sizes. Criteria for feasibility success will include: five participants recruited per week (over 12 weeks), about 75% of all eligible participants consent for study participation, complete evaluation of outcomes in at least 70% of all recruited participants, breastfeeding adherence rates of at least 70% in the intervention group, six months after delivery. Participants will be evaluated soon after giving birth and post-delivery at weeks 2, 6, 10, and 24. Primary analysis will follow the "intention-to-treat" principle. Sub-group analysis will be used to assess sub-group effects. This pilot trial will evaluate the feasibility of conducting a larger trial on communication and support approaches to improve adherence to breastfeeding by HIV-infected women. Text messaging and motivational interviewing are simple interventions which may allow participants to access personalized adherence advice and support. ClinicalTrials.gov: NCT02949713 . Registered on 26 October 2016; Pan African Clinical Trial Registry PACTR201611001855404 . Registered on 8 November 2016.

Deep learning in breast cancer risk assessment: evaluation of convolutional neural networks on a clinical dataset of full-field digital mammograms.

PubMed

Li, Hui; Giger, Maryellen L; Huynh, Benjamin Q; Antropova, Natalia O

2017-10-01

To evaluate deep learning in the assessment of breast cancer risk in which convolutional neural networks (CNNs) with transfer learning are used to extract parenchymal characteristics directly from full-field digital mammographic (FFDM) images instead of using computerized radiographic texture analysis (RTA), 456 clinical FFDM cases were included: a "high-risk" BRCA1/2 gene-mutation carriers dataset (53 cases), a "high-risk" unilateral cancer patients dataset (75 cases), and a "low-risk dataset" (328 cases). Deep learning was compared to the use of features from RTA, as well as to a combination of both in the task of distinguishing between high- and low-risk subjects. Similar classification performances were obtained using CNN [area under the curve [Formula: see text]; standard error [Formula: see text

[Systematic analysis of the readability of patient information on the websites of clinics for plastic surgery].

PubMed

Esfahani, B Janghorban; Faron, A; Roth, K S; Schaller, H-E; Medved, F; Lüers, J-C

2014-12-01

The Internet is becoming increasing-ly important as a source of information for patients in medical issues. However, many patients have problems to adequately understand texts, especially with medical content. A basic requirement to understand a written text is the read-ability of a text. The aim of the present study was to examine texts on the websites of German -plastic-surgical hospitals with patient information regarding their readability. In this study, the read-ability of texts of 27 major departments of plastic and Hand surgery in Germany was systematically analysed using 5 recognised readability indices. First, texts were searched based on 20 representative key words and themes. Thereafter, texts were assigned to one of 3 major themes in order to enable statistical analysis. In addition to the 5 readability indices, further objective text parameters were also recorded. Overall, 288 texts were found for analyzation. Most articles were found on the topic of "handsurgery" (n=124), less were found for "facial plastic surgery" (n=80) and "flaps, breast and reconstructive surgery" (n=84). Consistently, all readability indices showed a poor readability for the vast majority of analysed texts with the text appearing readable only for readers with a higher educational level. No significant differences in readability were found between the 3 major themes. Especially in the communication of medical information, it is important to consider the knowledge and education of the addressee. The texts studied consistently showed a readability that is understandable only for academics. Thus, a large part of the intended target group is probably not reached. In order to adequately deliver online information material, a revision of the analysed internet texts appears to be recommendable. © Georg Thieme Verlag KG Stuttgart · New York.

Adaptive semantic tag mining from heterogeneous clinical research texts.

PubMed

Hao, T; Weng, C

2015-01-01

To develop an adaptive approach to mine frequent semantic tags (FSTs) from heterogeneous clinical research texts. We develop a "plug-n-play" framework that integrates replaceable unsupervised kernel algorithms with formatting, functional, and utility wrappers for FST mining. Temporal information identification and semantic equivalence detection were two example functional wrappers. We first compared this approach's recall and efficiency for mining FSTs from ClinicalTrials.gov to that of a recently published tag-mining algorithm. Then we assessed this approach's adaptability to two other types of clinical research texts: clinical data requests and clinical trial protocols, by comparing the prevalence trends of FSTs across three texts. Our approach increased the average recall and speed by 12.8% and 47.02% respectively upon the baseline when mining FSTs from ClinicalTrials.gov, and maintained an overlap in relevant FSTs with the base- line ranging between 76.9% and 100% for varying FST frequency thresholds. The FSTs saturated when the data size reached 200 documents. Consistent trends in the prevalence of FST were observed across the three texts as the data size or frequency threshold changed. This paper contributes an adaptive tag-mining framework that is scalable and adaptable without sacrificing its recall. This component-based architectural design can be potentially generalizable to improve the adaptability of other clinical text mining methods.

Best clinical trials reported in 2010.

PubMed

Garner, John B; Grayburn, Paul A; Yancy, Clyde W

2011-07-01

Each year, a number of clinical trials emerge with data sufficient to change clinical practice. Determining which findings will result in practice change and which will provide only incremental benefit can be a dilemma for clinicians. The authors review selected clinical trials reported in 2010 in journals, at society meetings, and at conferences, focusing on those studies that have the potential to change clinical practice. This review offers 3 separate means of analysis: an abbreviated text summary, organized by subject area; a comprehensive table of relevant clinical trials that provides a schematic review of the hypotheses, interventions, methods, primary end points, results, and implications; and a complete bibliography for further reading as warranted. It is hoped that this compilation of relevant clinical trials and their important findings released in 2010 will be of benefit in the everyday practice of cardiovascular medicine. Copyright © 2011 Elsevier Inc. All rights reserved.

Full-text automated detection of surgical site infections secondary to neurosurgery in Rennes, France.

PubMed

Campillo-Gimenez, Boris; Garcelon, Nicolas; Jarno, Pascal; Chapplain, Jean Marc; Cuggia, Marc

2013-01-01

The surveillance of Surgical Site Infections (SSI) contributes to the management of risk in French hospitals. Manual identification of infections is costly, time-consuming and limits the promotion of preventive procedures by the dedicated teams. The introduction of alternative methods using automated detection strategies is promising to improve this surveillance. The present study describes an automated detection strategy for SSI in neurosurgery, based on textual analysis of medical reports stored in a clinical data warehouse. The method consists firstly, of enrichment and concept extraction from full-text reports using NOMINDEX, and secondly, text similarity measurement using a vector space model. The text detection was compared to the conventional strategy based on self-declaration and to the automated detection using the diagnosis-related group database. The text-mining approach showed the best detection accuracy, with recall and precision equal to 92% and 40% respectively, and confirmed the interest of reusing full-text medical reports to perform automated detection of SSI.

Using Medical Text Extraction, Reasoning and Mapping System (MTERMS) to Process Medication Information in Outpatient Clinical Notes

PubMed Central

Zhou, Li; Plasek, Joseph M; Mahoney, Lisa M; Karipineni, Neelima; Chang, Frank; Yan, Xuemin; Chang, Fenny; Dimaggio, Dana; Goldman, Debora S.; Rocha, Roberto A.

2011-01-01

Clinical information is often coded using different terminologies, and therefore is not interoperable. Our goal is to develop a general natural language processing (NLP) system, called Medical Text Extraction, Reasoning and Mapping System (MTERMS), which encodes clinical text using different terminologies and simultaneously establishes dynamic mappings between them. MTERMS applies a modular, pipeline approach flowing from a preprocessor, semantic tagger, terminology mapper, context analyzer, and parser to structure inputted clinical notes. Evaluators manually reviewed 30 free-text and 10 structured outpatient clinical notes compared to MTERMS output. MTERMS achieved an overall F-measure of 90.6 and 94.0 for free-text and structured notes respectively for medication and temporal information. The local medication terminology had 83.0% coverage compared to RxNorm’s 98.0% coverage for free-text notes. 61.6% of mappings between the terminologies are exact match. Capture of duration was significantly improved (91.7% vs. 52.5%) from systems in the third i2b2 challenge. PMID:22195230

What Experiences in Medical School Trigger Professional Identity Development?

PubMed

Kay, Denise; Berry, Andrea; Coles, Nicholas A

2018-04-02

Phenomenon: This qualitative inquiry used conceptual change theory as a theoretical lens to illuminate experiences in medical school that trigger professional identity formation. According to conceptual change theory, changes in personal conceptualizations are initiated when cognitive disequilibrium is introduced. We sought to identify the experiences that trigger cognitive disequilibrium and to subsequently describe students' perceptions of self-in-profession prior to the experience; the nature of the experience; and, when applicable, the outcomes of the experience. This article summarizes findings from portions of data collected in a larger qualitative study conducted at a new medical school in the United States that utilizes diverse pedagogies and experiences to develop student knowledge, clinical skills, attitudes, and dispositions. Primary data sources included focus groups and individual interviews with students across the 4 years of the curriculum (audio data). Secondary data included students' comments from course and end-of-year evaluations for the 2013-2017 classes (text data). Data treatment tools available in robust qualitative software, NVivo 10, were utilized to expedite coding of both audio and text data. Content analysis was adopted as the analysis method for both audio and text data. We identified four experiences that triggered cognitive disequilibrium in relationship to students' perceptions of self-in-profession: (a) transition from undergraduate student to medical student, (b) clinical experiences in the preclinical years, (c) exposure to the business of medicine, and (d) exposure to physicians in clinical practice. Insights: We believe these experiences represent vulnerable periods of professional identity formation during medical school. Educators interested in purposefully shaping curriculum to encourage adaptive professional identity development during medical school may find it useful to integrate educational interventions that assist students with navigating the disequilibrium that is introduced during these periods.

How Have Cancer Clinical Trial Eligibility Criteria Evolved Over Time?

PubMed Central

Yaman, Anil; Chakrabarti, Shreya; Sen, Anando; Weng, Chunhua

2016-01-01

Knowledge reuse of cancer trial designs may benefit from a temporal understanding of the evolution of the target populations of cancer studies over time. Therefore, we conducted a retrospective analysis of the trends of cancer trial eligibility criteria between 1999 and 2014. The yearly distributions of eligibility concepts for chemicals and drugs, procedures, observations, and medical conditions extracted from free-text eligibility criteria of 32,000 clinical trials for 89 cancer types were analyzed. We identified the concepts that trend upwards or downwards in all or selected cancer types, and the concepts that show anomalous trends for some cancers. Later, concept trends were studied in a disease-specific manner and illustrated for breast cancer. Criteria trends observed in this study are also validated and interpreted using evidence from the existing medical literature. This study contributes a method for concept trend analysis and original knowledge of the trends in cancer clinical trial eligibility criteria. PMID:27570681

Automatic de-identification of textual documents in the electronic health record: a review of recent research

PubMed Central

2010-01-01

Background In the United States, the Health Insurance Portability and Accountability Act (HIPAA) protects the confidentiality of patient data and requires the informed consent of the patient and approval of the Internal Review Board to use data for research purposes, but these requirements can be waived if data is de-identified. For clinical data to be considered de-identified, the HIPAA "Safe Harbor" technique requires 18 data elements (called PHI: Protected Health Information) to be removed. The de-identification of narrative text documents is often realized manually, and requires significant resources. Well aware of these issues, several authors have investigated automated de-identification of narrative text documents from the electronic health record, and a review of recent research in this domain is presented here. Methods This review focuses on recently published research (after 1995), and includes relevant publications from bibliographic queries in PubMed, conference proceedings, the ACM Digital Library, and interesting publications referenced in already included papers. Results The literature search returned more than 200 publications. The majority focused only on structured data de-identification instead of narrative text, on image de-identification, or described manual de-identification, and were therefore excluded. Finally, 18 publications describing automated text de-identification were selected for detailed analysis of the architecture and methods used, the types of PHI detected and removed, the external resources used, and the types of clinical documents targeted. All text de-identification systems aimed to identify and remove person names, and many included other types of PHI. Most systems used only one or two specific clinical document types, and were mostly based on two different groups of methodologies: pattern matching and machine learning. Many systems combined both approaches for different types of PHI, but the majority relied only on pattern matching, rules, and dictionaries. Conclusions In general, methods based on dictionaries performed better with PHI that is rarely mentioned in clinical text, but are more difficult to generalize. Methods based on machine learning tend to perform better, especially with PHI that is not mentioned in the dictionaries used. Finally, the issues of anonymization, sufficient performance, and "over-scrubbing" are discussed in this publication. PMID:20678228

Automatic de-identification of textual documents in the electronic health record: a review of recent research.

PubMed

Meystre, Stephane M; Friedlin, F Jeffrey; South, Brett R; Shen, Shuying; Samore, Matthew H

2010-08-02

In the United States, the Health Insurance Portability and Accountability Act (HIPAA) protects the confidentiality of patient data and requires the informed consent of the patient and approval of the Internal Review Board to use data for research purposes, but these requirements can be waived if data is de-identified. For clinical data to be considered de-identified, the HIPAA "Safe Harbor" technique requires 18 data elements (called PHI: Protected Health Information) to be removed. The de-identification of narrative text documents is often realized manually, and requires significant resources. Well aware of these issues, several authors have investigated automated de-identification of narrative text documents from the electronic health record, and a review of recent research in this domain is presented here. This review focuses on recently published research (after 1995), and includes relevant publications from bibliographic queries in PubMed, conference proceedings, the ACM Digital Library, and interesting publications referenced in already included papers. The literature search returned more than 200 publications. The majority focused only on structured data de-identification instead of narrative text, on image de-identification, or described manual de-identification, and were therefore excluded. Finally, 18 publications describing automated text de-identification were selected for detailed analysis of the architecture and methods used, the types of PHI detected and removed, the external resources used, and the types of clinical documents targeted. All text de-identification systems aimed to identify and remove person names, and many included other types of PHI. Most systems used only one or two specific clinical document types, and were mostly based on two different groups of methodologies: pattern matching and machine learning. Many systems combined both approaches for different types of PHI, but the majority relied only on pattern matching, rules, and dictionaries. In general, methods based on dictionaries performed better with PHI that is rarely mentioned in clinical text, but are more difficult to generalize. Methods based on machine learning tend to perform better, especially with PHI that is not mentioned in the dictionaries used. Finally, the issues of anonymization, sufficient performance, and "over-scrubbing" are discussed in this publication.

Randomized Double-blind Trial of Ringer Lactate Versus Normal Saline in Pediatric Acute Severe Diarrheal Dehydration.

PubMed

Kartha, Gayathri Bhuvaneswaran; Rameshkumar, Ramachandran; Mahadevan, Subramanian

2017-12-01

The aim of this study was to compare the effectiveness of Ringer lactate (RL) versus normal saline (NS) in the correction of pediatric acute severe diarrheal dehydration, as measured by improvement in clinical status and pH (≥7.35). A total of 68 children ages 1 month to 12 years with acute severe diarrheal dehydration (World Health Organization [WHO] classification) were randomized into RL (n = 34) and NS groups (n = 34) and received 100 mL/kg of the assigned intravenous fluid according to WHO PLAN-C for the management of diarrheal dehydration. The primary outcome was an improvement in clinical status and pH (≥7.35) at the end of 6 hours. Secondary outcomes were changes in serum electrolytes, renal and blood gas parameters, the volume of fluid required for dehydration correction excluding the first cycle, time to start oral feeding, hospital stay, and cost-effectiveness analysis. Primary outcome was achieved in 38% versus 23% (relative risk = 1.63, 95% confidence interval 0.80-3.40) in RL and NS groups, respectively. No significant differences were observed in secondary outcomes in electrolytes, renal, and blood gas parameters. None required second cycle of dehydration correction. Median (interquartile range) time to start oral feeding (1.0 [0.19-2.0] vs 1.5 [0.5-2.0] hours) and hospital stay (2.0 [1.0-2.0] vs 2.0 [2.0-2.0] days) was similar. The median total cost was higher in RL than NS group ((Equation is included in full-text article.)120 [(Equation is included in full-text article.)120-(Equation is included in full-text article.)180] vs (Equation is included in full-text article.)55 [(Equation is included in full-text article.)55-(Equation is included in full-text article.)82], P ≤ 0.001). In pediatric acute severe diarrheal dehydration, resuscitation with RL and NS was associated with similar clinical improvement and biochemical resolution. Hence, NS is to be considered as the fluid of choice because of the clinical improvement, cost, and availability.

PlateRunner: A Search Engine to Identify EMR Boilerplates.

PubMed

Divita, Guy; Workman, T Elizabeth; Carter, Marjorie E; Redd, Andrew; Samore, Matthew H; Gundlapalli, Adi V

2016-01-01

Medical text contains boilerplated content, an artifact of pull-down forms from EMRs. Boilerplated content is the source of challenges for concept extraction on clinical text. This paper introduces PlateRunner, a search engine on boilerplates from the US Department of Veterans Affairs (VA) EMR. Boilerplates containing concepts should be identified and reviewed to recognize challenging formats, identify high yield document titles, and fine tune section zoning. This search engine has the capability to filter negated and asserted concepts, save and search query results. This tool can save queries, search results, and documents found for later analysis.

A Cloud-based Approach to Medical NLP

PubMed Central

Chard, Kyle; Russell, Michael; Lussier, Yves A.; Mendonça, Eneida A; Silverstein, Jonathan C.

2011-01-01

Natural Language Processing (NLP) enables access to deep content embedded in medical texts. To date, NLP has not fulfilled its promise of enabling robust clinical encoding, clinical use, quality improvement, and research. We submit that this is in part due to poor accessibility, scalability, and flexibility of NLP systems. We describe here an approach and system which leverages cloud-based approaches such as virtual machines and Representational State Transfer (REST) to extract, process, synthesize, mine, compare/contrast, explore, and manage medical text data in a flexibly secure and scalable architecture. Available architectures in which our Smntx (pronounced as semantics) system can be deployed include: virtual machines in a HIPAA-protected hospital environment, brought up to run analysis over bulk data and destroyed in a local cloud; a commercial cloud for a large complex multi-institutional trial; and within other architectures such as caGrid, i2b2, or NHIN. PMID:22195072

A cloud-based approach to medical NLP.

PubMed

Chard, Kyle; Russell, Michael; Lussier, Yves A; Mendonça, Eneida A; Silverstein, Jonathan C

2011-01-01

Natural Language Processing (NLP) enables access to deep content embedded in medical texts. To date, NLP has not fulfilled its promise of enabling robust clinical encoding, clinical use, quality improvement, and research. We submit that this is in part due to poor accessibility, scalability, and flexibility of NLP systems. We describe here an approach and system which leverages cloud-based approaches such as virtual machines and Representational State Transfer (REST) to extract, process, synthesize, mine, compare/contrast, explore, and manage medical text data in a flexibly secure and scalable architecture. Available architectures in which our Smntx (pronounced as semantics) system can be deployed include: virtual machines in a HIPAA-protected hospital environment, brought up to run analysis over bulk data and destroyed in a local cloud; a commercial cloud for a large complex multi-institutional trial; and within other architectures such as caGrid, i2b2, or NHIN.

Evaluating current automatic de-identification methods with Veteran's health administration clinical documents.

PubMed

Ferrández, Oscar; South, Brett R; Shen, Shuying; Friedlin, F Jeffrey; Samore, Matthew H; Meystre, Stéphane M

2012-07-27

The increased use and adoption of Electronic Health Records (EHR) causes a tremendous growth in digital information useful for clinicians, researchers and many other operational purposes. However, this information is rich in Protected Health Information (PHI), which severely restricts its access and possible uses. A number of investigators have developed methods for automatically de-identifying EHR documents by removing PHI, as specified in the Health Insurance Portability and Accountability Act "Safe Harbor" method.This study focuses on the evaluation of existing automated text de-identification methods and tools, as applied to Veterans Health Administration (VHA) clinical documents, to assess which methods perform better with each category of PHI found in our clinical notes; and when new methods are needed to improve performance. We installed and evaluated five text de-identification systems "out-of-the-box" using a corpus of VHA clinical documents. The systems based on machine learning methods were trained with the 2006 i2b2 de-identification corpora and evaluated with our VHA corpus, and also evaluated with a ten-fold cross-validation experiment using our VHA corpus. We counted exact, partial, and fully contained matches with reference annotations, considering each PHI type separately, or only one unique 'PHI' category. Performance of the systems was assessed using recall (equivalent to sensitivity) and precision (equivalent to positive predictive value) metrics, as well as the F(2)-measure. Overall, systems based on rules and pattern matching achieved better recall, and precision was always better with systems based on machine learning approaches. The highest "out-of-the-box" F(2)-measure was 67% for partial matches; the best precision and recall were 95% and 78%, respectively. Finally, the ten-fold cross validation experiment allowed for an increase of the F(2)-measure to 79% with partial matches. The "out-of-the-box" evaluation of text de-identification systems provided us with compelling insight about the best methods for de-identification of VHA clinical documents. The errors analysis demonstrated an important need for customization to PHI formats specific to VHA documents. This study informed the planning and development of a "best-of-breed" automatic de-identification application for VHA clinical text.

Integration of Basic and Clinical Science Courses in US PharmD Programs

PubMed Central

Talukder, Rahmat M.; Taheri, Reza; Blanchard, Nicholas

2016-01-01

Objective. To determine the current status of and faculty perceptions regarding integration of basic and clinical science courses in US pharmacy programs. Methods. A 25-item survey instrument was developed and distributed to 132 doctor of pharmacy (PharmD) programs. Survey data were analyzed using Mann-Whitney U test or Kruskal-Wallis test. Thematic analysis of text-based comments was performed using the constant comparison method. Results. One hundred twelve programs responded for a response rate of 85%. Seventy-eight (70%) offered integrated basic and clinical science courses. The types of integration included: full integration with merging disciplinary contents (n=25), coordinated delivery of disciplinary contents (n=50), and standalone courses with integrated laboratory (n=3). Faculty perceptions of course integration were positive. Themes that emerged from text-based comments included positive learning experiences as well as the challenges, opportunities, and skepticism associated with course integration. Conclusion. The results suggest wide variations in the design and implementation of integrated courses among US pharmacy programs. Faculty training and buy-in play a significant role in successful implementation of curricular integration. PMID:28179715

Integration of Basic and Clinical Science Courses in US PharmD Programs.

PubMed

Islam, Mohammed A; Talukder, Rahmat M; Taheri, Reza; Blanchard, Nicholas

2016-12-25

Objective. To determine the current status of and faculty perceptions regarding integration of basic and clinical science courses in US pharmacy programs. Methods. A 25-item survey instrument was developed and distributed to 132 doctor of pharmacy (PharmD) programs. Survey data were analyzed using Mann-Whitney U test or Kruskal-Wallis test. Thematic analysis of text-based comments was performed using the constant comparison method. Results. One hundred twelve programs responded for a response rate of 85%. Seventy-eight (70%) offered integrated basic and clinical science courses. The types of integration included: full integration with merging disciplinary contents (n=25), coordinated delivery of disciplinary contents (n=50), and standalone courses with integrated laboratory (n=3). Faculty perceptions of course integration were positive. Themes that emerged from text-based comments included positive learning experiences as well as the challenges, opportunities, and skepticism associated with course integration. Conclusion. The results suggest wide variations in the design and implementation of integrated courses among US pharmacy programs. Faculty training and buy-in play a significant role in successful implementation of curricular integration.

What are the concerns and goals of women attending a urogynaecology clinic? Content analysis of free-text data from an electronic pelvic floor assessment questionnaire (ePAQ-PF).

PubMed

Gray, Thomas; Strickland, Scarlett; Pooranawattanakul, Sarita; Li, Weiguang; Campbell, Patrick; Jones, Georgina; Radley, Stephen

2018-06-27

Understanding patients' concerns and goals is essential for providing individualised care in urogynaecology. The study objectives were to undertake a content analysis of free-text concerns and goals recorded by patients using an electronic pelvic-floor questionnaire (ePAQ-PF) and measure how these related to self-reported symptom and health-related quality-of-life (HRQOL) data also recorded using ePAQ-PF. A total of 1996 consenting patients completed ePAQ-PF. Content analysis was undertaken of free-text responses to the item: 'Considering the issues that currently concern you the most, what do you hope to achieve from any help, advice or treatment?' Key content themes were identified by the lead researcher, and three researchers read and coded all recorded responses. Student's t test was used to compare ePAQ-PF domain scores for patients reporting concerns in the relevant domain with those who did not. In total, 63% of participants who completed the questionnaire, recorded at least one free-text item. Content analysis identified 1560 individual concerns coding into the 19 ePAQ-PF domains. Symptom scores were significantly higher for patients reporting free-text concerns in 18 domains (p < 0.05). Additional concerns relating specifically to body image were recorded by 11% of patients. Key areas of importance emerging for personal goals included cure/improvement, better understanding, incontinence pad use, sexual function and surgery. Free-text reporting in ePAQ-PF is utilised by patients and facilitates self-expression and discussion of issues impacting on HRQOL. The significant relationship between recorded free-text concerns and ePAQ-PF domain scores suggests convergent validity for the instrument. Development and psychometric testing of a domain to assess body image is proposed.

Impact of a new vaccine clinic on hepatitis B vaccine completion and immunological response rates in an HIV-positive cohort.

PubMed

Rock, Clare; de Barra, Eoghan; Sadlier, Corinna; Kelly, Sinead; Dowling, Catherine; McNally, Cora; Bergin, Colm

2013-06-01

Hepatitis B virus vaccination (HBVV) in the HIV-infected population has poor reported completion rates and immunological response rates. At our HIV clinic, we established a vaccine clinic to improve HBVV outcomes using interventions such as SMS text reminders and double-dose (DD) HBVV for standard-dose non-responders (SD NRs). A five-year (2003-2008) retrospective review of the completion rates and immunological response rates for HBVV after the establishment of the dedicated vaccine clinic was conducted. Statistical significance was assumed at p<0.05, and the analysis was performed using SPSS (v16). A total of 354 HIV-infected patients were included. Seventy-five percent (268/354) of patients completed the SD HBVV, an 84% (226/268) returned for the hepatitis B surface antibody evaluation. Only 47.3% (107/226) responded to standard-dose hepatitis B vaccination. Responders had higher absolute numbers (p=0.017) and percentages of CD4 cells (p<0.001) and were more likely to be receiving HAART (p=0.001). There was a 70% (48/69) response rate to DD HBVV among SD NRs. On-treatment analysis showed an 88% (155/176) overall immunological response to SD HBVV and DD HBVV, if required. High HBVV completion and response rates in this HIV cohort were enabled through the use of multiple interventions, including the use of SMS text message reminders and routine referral for DD vaccination. Copyright © 2012 King Saud Bin Abdulaziz University for Health Sciences. Published by Elsevier Ltd. All rights reserved.

Electro-Acupuncture is Beneficial for Knee Osteoarthritis: The Evidence from Meta-Analysis of Randomized Controlled Trials.

PubMed

Chen, Na; Wang, Jing; Mucelli, Attilio; Zhang, Xu; Wang, Changqing

2017-01-01

Knee osteoarthritis (KOA) is a common chronic degenerative disease of the elderly. Electro-acupuncture (EA) is considered as a beneficial treatment for KOA, but the conclusion is controversial. This systematic review compiled the evidence from 11 randomized controlled trials to objectively assess the effectiveness and safety of EA for KOA. Eight databases including PubMed, Cochrane Library, Clinic trials, Foreign Medical Literature Retrial Service (FMRS), Science Direct, China National Knowledge Infrastructure (CNKI), Chinese Scientific Journal Database (VIP), and Wanfang Data were extensively searched up to 5 July 2016. The outcomes included the evaluation of effectiveness, pain and physical function. Risk of bias was evaluated according to the Cochrane risk of bias tool. Eleven RCTs with 695 participants were included. Meta-analysis indicated that EA was more effective than pharmacological treatment (RR [Formula: see text] 1.14; 95% CI [Formula: see text] 1.01,1.28; [Formula: see text]) and manual acupuncture (RR [Formula: see text] 1.12; 95% CI [Formula: see text] 1.02,1.22; [Formula: see text]). Also, EA had a more significant effect in reducing the pain intensity (SMD [Formula: see text]; 95% CI [Formula: see text]; [Formula: see text]) and improving the physical function in the perspective of WOMAC (MD [Formula: see text]; 95% CI [Formula: see text], 5.56; [Formula: see text]) and LKSS (pharmacological treatment: MD [Formula: see text]; 95% CI [Formula: see text], 6.64; [Formula: see text]). Furthermore, these studies implied that EA should be performed for at least 4 weeks. Conclusively, the results indicate that EA is a great opportunity to remarkably alleviate the pain and improve the physical function of KOA patients with a low risk of adverse reaction. Therefore, more high quality RCTs with rigorous methods of design, measurement and evaluation are needed to confirm the long-term effects of EA for KOA.

An exploratory analysis of PubMed's free full-text limit on citation retrieval for clinical questions.

PubMed

Krieger, Mary M; Richter, Randy R; Austin, Tricia M

2008-10-01

The research sought to determine (1) how use of the PubMed free full-text (FFT) limit affects citation retrieval and (2) how use of the FFT limit impacts the types of articles and levels of evidence retrieved. Four clinical questions based on a research agenda for physical therapy were searched in PubMed both with and without the use of the FFT limit. Retrieved citations were examined for relevancy to each question. Abstracts of relevant citations were reviewed to determine the types of articles and levels of evidence. Descriptive analysis was used to compare the total number of citations, number of relevant citations, types of articles, and levels of evidence both with and without the use of the FFT limit. Across all 4 questions, the FFT limit reduced the number of citations to 11.1% of the total number of citations retrieved without the FFT limit. Additionally, high-quality evidence such as systematic reviews and randomized controlled trials were missed when the FFT limit was used. Health sciences librarians play a key role in educating users about the potential impact the FFT limit has on the number of citations, types of articles, and levels of evidence retrieved.

Terminology Services: Standard Terminologies to Control Health Vocabulary.

PubMed

González Bernaldo de Quirós, Fernán; Otero, Carlos; Luna, Daniel

2018-04-22

Healthcare Information Systems should capture clinical data in a structured and preferably coded format. This is crucial for data exchange between health information systems, epidemiological analysis, quality and research, clinical decision support systems, administrative functions, among others. Structured data entry is an obstacle for the usability of electronic health record (EHR) applications and their acceptance by physicians who prefer to document patient EHRs using "free text". Natural language allows for rich expressiveness but at the same time is ambiguous; it has great dependence on context and uses jargon and acronyms. Although much progress has been made in knowledge and natural language processing techniques, the result is not yet satisfactory enough for the use of free text in all dimensions of clinical documentation. In order to address the trade-off between capturing data with free text and at the same time coding data for computer processing, numerous terminological systems for the systematic recording of clinical data have been developed. The purpose of terminology services consists of representing facts that happen in the real world through database management in order to allow for semantic interoperability and computerized applications. These systems interrelate concepts of a particular domain and provide references to related terms with standards codes. In this way, standard terminologies allow the creation of a controlled medical vocabulary, making terminology services a fundamental component for health data management in the healthcare environment. The Hospital Italiano de Buenos Aires has been working in the development of its own terminology server. This work describes its experience in the field. Georg Thieme Verlag KG Stuttgart.

A systematic review of the reporting of Data Monitoring Committees' roles, interim analysis and early termination in pediatric clinical trials

PubMed Central

2009-01-01

Background Decisions about interim analysis and early stopping of clinical trials, as based on recommendations of Data Monitoring Committees (DMCs), have far reaching consequences for the scientific validity and clinical impact of a trial. Our aim was to evaluate the frequency and quality of the reporting on DMC composition and roles, interim analysis and early termination in pediatric trials. Methods We conducted a systematic review of randomized controlled clinical trials published from 2005 to 2007 in a sample of four general and four pediatric journals. We used full-text databases to identify trials which reported on DMCs, interim analysis or early termination, and included children or adolescents. Information was extracted on general trial characteristics, risk of bias, and a set of parameters regarding DMC composition and roles, interim analysis and early termination. Results 110 of the 648 pediatric trials in this sample (17%) reported on DMC or interim analysis or early stopping, and were included; 68 from general and 42 from pediatric journals. The presence of DMCs was reported in 89 of the 110 included trials (81%); 62 papers, including 46 of the 89 that reported on DMCs (52%), also presented information about interim analysis. No paper adequately reported all DMC parameters, and nine (15%) reported all interim analysis details. Of 32 trials which terminated early, 22 (69%) did not report predefined stopping guidelines and 15 (47%) did not provide information on statistical monitoring methods. Conclusions Reporting on DMC composition and roles, on interim analysis results and on early termination of pediatric trials is incomplete and heterogeneous. We propose a minimal set of reporting parameters that will allow the reader to assess the validity of trial results. PMID:20003383

Searching for Clinically Relevant Biomarkers in Geriatric Oncology.

PubMed

Katsila, Theodora; Patrinos, George P; Kardamakis, Dimitrios

2018-01-01

Ageing, which is associated with a progressive decline and functional deterioration in multiple organ systems, is highly heterogeneous, both inter- and intraindividually. For this, tailored-made theranostics and optimum patient stratification become fundamental, when decision-making in elderly patients is considered. In particular, when cancer incidence and cancer-related mortality and morbidity are taken into account, elderly patient care is a public health concern. In this review, we focus on oncogeriatrics and highlight current opportunities and challenges with an emphasis on the unmet need of clinically relevant biomarkers in elderly cancer patients. We performed a literature search on PubMed and Scopus databases for articles published in English between 2000 and 2017 coupled to text mining and analysis. Considering the top insights, we derived from our literature analysis that information knowledge needs to turn into knowledge growth in oncogeriatrics towards clinically relevant biomarkers, cost-effective practices, updated educational schemes for health professionals (in particular, geriatricians and oncologists), and awareness of ethical issues. We conclude with an interdisciplinary call to omics, geriatricians, oncologists, informatics, and policy-makers communities that Big Data should be translated into decision-making in the clinic.

Medical Student and Tutor Perceptions of Video Versus Text in an Interactive Online Virtual Patient for Problem-Based Learning: A Pilot Study.

PubMed

Woodham, Luke A; Ellaway, Rachel H; Round, Jonathan; Vaughan, Sophie; Poulton, Terry; Zary, Nabil

2015-06-18

The impact of the use of video resources in primarily paper-based problem-based learning (PBL) settings has been widely explored. Although it can provide many benefits, the use of video can also hamper the critical thinking of learners in contexts where learners are developing clinical reasoning. However, the use of video has not been explored in the context of interactive virtual patients for PBL. A pilot study was conducted to explore how undergraduate medical students interpreted and evaluated information from video- and text-based materials presented in the context of a branched interactive online virtual patient designed for PBL. The goal was to inform the development and use of virtual patients for PBL and to inform future research in this area. An existing virtual patient for PBL was adapted for use in video and provided as an intervention to students in the transition year of the undergraduate medicine course at St George's, University of London. Survey instruments were used to capture student and PBL tutor experiences and perceptions of the intervention, and a formative review meeting was run with PBL tutors. Descriptive statistics were generated for the structured responses and a thematic analysis was used to identify emergent themes in the unstructured responses. Analysis of student responses (n=119) and tutor comments (n=18) yielded 8 distinct themes relating to the perceived educational efficacy of information presented in video and text formats in a PBL context. Although some students found some characteristics of the videos beneficial, when asked to express a preference for video or text the majority of those that responded to the question (65%, 65/100) expressed a preference for text. Student responses indicated that the use of video slowed the pace of PBL and impeded students' ability to review and critically appraise the presented information. Our findings suggest that text was perceived to be a better source of information than video in virtual patients for PBL. More specifically, the use of video was perceived as beneficial for providing details, visual information, and context where text was unable to do so. However, learner acceptance of text was higher in the context of PBL, particularly when targeting clinical reasoning skills. This pilot study has provided the foundation for further research into the effectiveness of different virtual patient designs for PBL.

Selection of the effect size for sample size determination for a continuous response in a superiority clinical trial using a hybrid classical and Bayesian procedure.

PubMed

Ciarleglio, Maria M; Arendt, Christopher D; Peduzzi, Peter N

2016-06-01

When designing studies that have a continuous outcome as the primary endpoint, the hypothesized effect size ([Formula: see text]), that is, the hypothesized difference in means ([Formula: see text]) relative to the assumed variability of the endpoint ([Formula: see text]), plays an important role in sample size and power calculations. Point estimates for [Formula: see text] and [Formula: see text] are often calculated using historical data. However, the uncertainty in these estimates is rarely addressed. This article presents a hybrid classical and Bayesian procedure that formally integrates prior information on the distributions of [Formula: see text] and [Formula: see text] into the study's power calculation. Conditional expected power, which averages the traditional power curve using the prior distributions of [Formula: see text] and [Formula: see text] as the averaging weight, is used, and the value of [Formula: see text] is found that equates the prespecified frequentist power ([Formula: see text]) and the conditional expected power of the trial. This hypothesized effect size is then used in traditional sample size calculations when determining sample size for the study. The value of [Formula: see text] found using this method may be expressed as a function of the prior means of [Formula: see text] and [Formula: see text], [Formula: see text], and their prior standard deviations, [Formula: see text]. We show that the "naïve" estimate of the effect size, that is, the ratio of prior means, should be down-weighted to account for the variability in the parameters. An example is presented for designing a placebo-controlled clinical trial testing the antidepressant effect of alprazolam as monotherapy for major depression. Through this method, we are able to formally integrate prior information on the uncertainty and variability of both the treatment effect and the common standard deviation into the design of the study while maintaining a frequentist framework for the final analysis. Solving for the effect size which the study has a high probability of correctly detecting based on the available prior information on the difference [Formula: see text] and the standard deviation [Formula: see text] provides a valuable, substantiated estimate that can form the basis for discussion about the study's feasibility during the design phase. © The Author(s) 2016.

A general natural-language text processor for clinical radiology.

PubMed Central

Friedman, C; Alderson, P O; Austin, J H; Cimino, J J; Johnson, S B

1994-01-01

OBJECTIVE: Development of a general natural-language processor that identifies clinical information in narrative reports and maps that information into a structured representation containing clinical terms. DESIGN: The natural-language processor provides three phases of processing, all of which are driven by different knowledge sources. The first phase performs the parsing. It identifies the structure of the text through use of a grammar that defines semantic patterns and a target form. The second phase, regularization, standardizes the terms in the initial target structure via a compositional mapping of multi-word phrases. The third phase, encoding, maps the terms to a controlled vocabulary. Radiology is the test domain for the processor and the target structure is a formal model for representing clinical information in that domain. MEASUREMENTS: The impression sections of 230 radiology reports were encoded by the processor. Results of an automated query of the resultant database for the occurrences of four diseases were compared with the analysis of a panel of three physicians to determine recall and precision. RESULTS: Without training specific to the four diseases, recall and precision of the system (combined effect of the processor and query generator) were 70% and 87%. Training of the query component increased recall to 85% without changing precision. PMID:7719797

Meta-analysis of Huangqi injection for the adjunctive therapy of aplastic anemia

PubMed Central

Zhu, Changtai; Gao, Yulu; Jiang, Ting; Hao, Cao; Gao, Zongshuai; Sun, Yongning

2015-01-01

Aplastic anemia therapy remains difficult, due to lack of effective treatment regimens. In recent years, Huangqi injection for the adjunctive therapy of aplastic anemia has been reported in many clinical trials. Considering that Huangqi injection may be a novel approach to aplastic anemia treatment, we conducted a meta-analysis of clinical controlled trials to assess the clinical value of Huangqi injection in the treatment of aplastic anemia. We searched the Chinese Biomedical Literature Database (CBM), China National Knowledge Infrastructure (CNKI), Chinese Scientific Journals Full-text Database (VIP), Wanfang Database, PubMed and EMBASE database to collect the data about the trials of Huangqi injection combined with androgens for treating aplastic anemia. A total of ten studies involving 720 patients with aplastic anemia were included in this study. The meta-analysis showed significant increases in the pool effectiveness rate, white blood cells (WBC), haematoglobin (Hb), platelets (PLT), and reticulocytes (Ret) between the experimental group versus the control group. No severe side effects were found in this study. However, the lower Jadad scores and asymmetric funnel plot degrades the validity of the meta-analysis as the clinical evidence. Therefore, Huangqi injection may significantly enhance the efficacy of androgens for aplastic anemia, suggesting that the novel approach of Chinese traditional medicine combined with Western medicine is promising. The exact outcome required confirmation with rigorously well-designed multi-center trials. PMID:26379817

Traditional Chinese Medications for Knee Osteoarthritis Pain: A Meta-Analysis of Randomized Controlled Trials.

PubMed

Chen, Bo; Zhan, Hongsheng; Marszalek, Jolanta; Chung, Mei; Lin, Xun; Zhang, Min; Pang, Jian; Wang, Chenchen

2016-01-01

Traditional Chinese medication (TCM) has analgesic and anti-inflammatory effects in patients with knee osteoarthritis (OA). We conducted the first systematic review of the best quantitative and qualitative evidence currently available in order to evaluate the effectiveness of TCM in relieving pain in knee OA. A comprehensive literature search was conducted using three English and four Chinese biomedical databases from their inception through March 1, 2015. We included randomized controlled trials of TCM for knee OA with intervention durations of at least two weeks. The effects of TCM on pain and other clinical symptoms were measured with the visual analog scale (VAS) and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). The total effectiveness rate, which was used to assess overall pain, physical performance and wellness, was also measured. Two researchers independently extracted data on study design, population characteristics, duration, intervention, outcomes, risk of bias, and primary results. We performed a random-effects meta-analysis when appropriate. We also explored factors that could explain the heterogeneity by conducting subgroup and meta-regression analyses. Twenty-three studies, totaling 2362 subjects, met the eligibility criteria. Treatments were formulated with an average of 8 Chinese herbs and were prescribed based on the traditional Chinese diagnostic method of syndrome differentiation. The mean treatment duration was seven weeks, with oral administration occurring one to three times a day. Compared with non-steroidal anti-inflammatory drugs and intra-articular hyaluronate injections, 18 of the studies showed significantly improved VAS pain scores (Mean Difference [MD] [Formula: see text] 0.56; 95% confidence interval [CI], 0.18 to 0.94; [Formula: see text]), six of the studies showed significantly improved WOMAC pain subscale scores (MD [Formula: see text] 2.23; 95% CI, 0.56 to 3.91; [Formula: see text]), and 16 of the trials showed significantly improved total effectiveness rates (risk ratio [Formula: see text] 1.12; 95% CI, 1.05 to 1.19; [Formula: see text] 0.0003). In addition, TCM showed a lower risk of adverse events than standard western treatments. This evidence suggests that TCM is safe and effective for improving pain, function, and wellness in treatments of knee OA. However, there is inherent clinical heterogeneity (diverse TCM formulations, controls, and treatment regimens) among the included trials. Despite these limitations, the potential analgesic effects of TCM warrant further methodologically rigorous research to determine the clinical implications of TCM on pain management in knee OA.

Evaluation of an open source tool for indexing and searching enterprise radiology and pathology reports

NASA Astrophysics Data System (ADS)

Kim, Woojin; Boonn, William

2010-03-01

Data mining of existing radiology and pathology reports within an enterprise health system can be used for clinical decision support, research, education, as well as operational analyses. In our health system, the database of radiology and pathology reports exceeds 13 million entries combined. We are building a web-based tool to allow search and data analysis of these combined databases using freely available and open source tools. This presentation will compare performance of an open source full-text indexing tool to MySQL's full-text indexing and searching and describe implementation procedures to incorporate these capabilities into a radiology-pathology search engine.

[A customized method for information extraction from unstructured text data in the electronic medical records].

PubMed

Bao, X Y; Huang, W J; Zhang, K; Jin, M; Li, Y; Niu, C Z

2018-04-18

There is a huge amount of diagnostic or treatment information in electronic medical record (EMR), which is a concrete manifestation of clinicians actual diagnosis and treatment details. Plenty of episodes in EMRs, such as complaints, present illness, past history, differential diagnosis, diagnostic imaging, surgical records, reflecting details of diagnosis and treatment in clinical process, adopt Chinese description of natural language. How to extract effective information from these Chinese narrative text data, and organize it into a form of tabular for analysis of medical research, for the practical utilization of clinical data in the real world, is a difficult problem in Chinese medical data processing. Based on the EMRs narrative text data in a tertiary hospital in China, a customized information extracting rules learning, and rule based information extraction methods is proposed. The overall method consists of three steps, which includes: (1) Step 1, a random sample of 600 copies (including the history of present illness, past history, personal history, family history, etc.) of the electronic medical record data, was extracted as raw corpora. With our developed Chinese clinical narrative text annotation platform, the trained clinician and nurses marked the tokens and phrases in the corpora which would be extracted (with a history of diabetes as an example). (2) Step 2, based on the annotated corpora clinical text data, some extraction templates were summarized and induced firstly. Then these templates were rewritten using regular expressions of Perl programming language, as extraction rules. Using these extraction rules as basic knowledge base, we developed extraction packages in Perl, for extracting data from the EMRs text data. In the end, the extracted data items were organized in tabular data format, for later usage in clinical research or hospital surveillance purposes. (3) As the final step of the method, the evaluation and validation of the proposed methods were implemented in the National Clinical Service Data Integration Platform, and we checked the extraction results using artificial verification and automated verification combined, proved the effectiveness of the method. For all the patients with diabetes as diagnosed disease in the Department of Endocrine in the hospital, the medical history episode of these patients showed that, altogether 1 436 patients were dismissed in 2015, and a history of diabetes medical records extraction results showed that the recall rate was 87.6%, the accuracy rate was 99.5%, and F-Score was 0.93. For all the 10% patients (totally 1 223 patients) with diabetes by the dismissed dates of August 2017 in the same department, the extracted diabetes history extraction results showed that the recall rate was 89.2%, the accuracy rate was 99.2%, F-Score was 0.94. This study mainly adopts the combination of natural language processing and rule-based information extraction, and designs and implements an algorithm for extracting customized information from unstructured Chinese electronic medical record text data. It has better results than existing work.

Assigning clinical codes with data-driven concept representation on Dutch clinical free text.

PubMed

Scheurwegs, Elyne; Luyckx, Kim; Luyten, Léon; Goethals, Bart; Daelemans, Walter

2017-05-01

Clinical codes are used for public reporting purposes, are fundamental to determining public financing for hospitals, and form the basis for reimbursement claims to insurance providers. They are assigned to a patient stay to reflect the diagnosis and performed procedures during that stay. This paper aims to enrich algorithms for automated clinical coding by taking a data-driven approach and by using unsupervised and semi-supervised techniques for the extraction of multi-word expressions that convey a generalisable medical meaning (referred to as concepts). Several methods for extracting concepts from text are compared, two of which are constructed from a large unannotated corpus of clinical free text. A distributional semantic model (i.c. the word2vec skip-gram model) is used to generalize over concepts and retrieve relations between them. These methods are validated on three sets of patient stay data, in the disease areas of urology, cardiology, and gastroenterology. The datasets are in Dutch, which introduces a limitation on available concept definitions from expert-based ontologies (e.g. UMLS). The results show that when expert-based knowledge in ontologies is unavailable, concepts derived from raw clinical texts are a reliable alternative. Both concepts derived from raw clinical texts perform and concepts derived from expert-created dictionaries outperform a bag-of-words approach in clinical code assignment. Adding features based on tokens that appear in a semantically similar context has a positive influence for predicting diagnostic codes. Furthermore, the experiments indicate that a distributional semantics model can find relations between semantically related concepts in texts but also introduces erroneous and redundant relations, which can undermine clinical coding performance. Copyright © 2017. Published by Elsevier Inc.

Improving Terminology Mapping in Clinical Text with Context-Sensitive Spelling Correction.

PubMed

Dziadek, Juliusz; Henriksson, Aron; Duneld, Martin

2017-01-01

The mapping of unstructured clinical text to an ontology facilitates meaningful secondary use of health records but is non-trivial due to lexical variation and the abundance of misspellings in hurriedly produced notes. Here, we apply several spelling correction methods to Swedish medical text and evaluate their impact on SNOMED CT mapping; first in a controlled evaluation using medical literature text with induced errors, followed by a partial evaluation on clinical notes. It is shown that the best-performing method is context-sensitive, taking into account trigram frequencies and utilizing a corpus-based dictionary.

Texting Test Results Reduces the Time to Treatment for Sexually Transmitted Infections.

PubMed

Bilello, Lori A; Livingood, William C; Lukens-Bull, Katryne; Smotherman, Carmen; Choe, Ulyee

2018-06-07

Sexually transmitted infections (STIs) continue to be a major health problem and source of health disparities in the United States. With diminishing resources, public health agencies are challenged to limit inefficient STI practices and still maintain effective population health. The purpose of this study was to implement a text-messaging strategy to convey STI test results and to assess whether texting positive results was associated with a shorter treatment time frame. Quasi-experimental design. Six counties in Florida. Sexually transmitted infection clients in 6 county health departments. Clients tested for gonorrhea, chlamydia, and syphilis were given the option to receive their results by a text message or the regular notification process (phone or follow-up clinic visit). The time to treatment after a positive test result for those clients who received their results by a text message versus the regular notification process. Those who were presumptively treated were excluded from the analysis. Over a 10-month period, 4081 clients were offered the texting option and 47.8% agreed to participate. For the counties combined, there was a higher percentage of those who received treatment within 1 to 4 days who received their positive test results by text message (53.0%) versus those who received their results by traditional methods (42.0%). In addition, there was a lower percentage of those who either did not get treated or were treated 8 days or more who received their positive test results by text message (26.1%) versus those who received their results by traditional methods (35.2%). Providing a text-messaging option is a viable strategy for clinics to provide timely results to their clients, and these clients were more likely to be treated in 1 to 4 days. Important for public health quality improvement, and increased efficiency and adoption of emerging technologies.

Short message service or disService: issues with text messaging in a complex medical environment.

PubMed

Wu, Robert; Appel, Lora; Morra, Dante; Lo, Vivian; Kitto, Simon; Quan, Sherman

2014-04-01

Hospitals today are experiencing major changes in their clinical communication workflows as conventional numeric paging and face-to-face verbal conversations are being replaced by computer mediated communication systems. In this paper, we highlight the importance of understanding this transition and discuss some of the impacts that may emerge when verbal clinical conversations are replaced by short text messages. In-depth interviews (n=108) and non-participatory observation sessions (n=260h) were conducted on the General Internal Medicine wards at five academic teaching hospitals in Toronto, Canada. From our analysis of the qualitative data, we identified two major themes. De-contextualization of complex issues led to an increase in misinterpretation and an increase in back and forth messaging for clarification. Depersonalization of communication was due to less verbal conversations and face-to-face interactions and led to a negative impact on work relationships. Text-based communication in hospital settings led to the oversimplification of messages and the depersonalization of communication. It is important to recognize and understand these unintended consequences of new technology to avoid the negative impacts to patient care and work relationships. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Semantic Role Labeling of Clinical Text: Comparing Syntactic Parsers and Features

PubMed Central

Zhang, Yaoyun; Jiang, Min; Wang, Jingqi; Xu, Hua

2016-01-01

Semantic role labeling (SRL), which extracts shallow semantic relation representation from different surface textual forms of free text sentences, is important for understanding clinical narratives. Since semantic roles are formed by syntactic constituents in the sentence, an effective parser, as well as an effective syntactic feature set are essential to build a practical SRL system. Our study initiates a formal evaluation and comparison of SRL performance on a clinical text corpus MiPACQ, using three state-of-the-art parsers, the Stanford parser, the Berkeley parser, and the Charniak parser. First, the original parsers trained on the open domain syntactic corpus Penn Treebank were employed. Next, those parsers were retrained on the clinical Treebank of MiPACQ for further comparison. Additionally, state-of-the-art syntactic features from open domain SRL were also examined for clinical text. Experimental results showed that retraining the parsers on clinical Treebank improved the performance significantly, with an optimal F1 measure of 71.41% achieved by the Berkeley parser. PMID:28269926

Schizophrenia Patient or Spiritually Advanced Personality? A Qualitative Case Analysis.

PubMed

Bhargav, Hemant; Jagannathan, Aarti; Raghuram, Nagarathna; Srinivasan, T M; Gangadhar, Bangalore N

2015-10-01

Many aspects of spiritual experience are similar in form and content to symptoms of psychosis. Both spiritually advanced people and patients suffering from psychopathology experience alterations in their sense of 'self.' Psychotic experiences originate from derangement of the personality, whereas spiritual experiences involve systematic thinning out of the selfish ego, allowing individual consciousness to merge into universal consciousness. Documented instances and case studies suggest possible confusion between the spiritually advanced and schizophrenia patients. Clinical practice contains no clear guidelines on how to distinguish them. Here we use a case presentation to help tabulate clinically useful points distinguishing spiritually advanced persons from schizophrenia patients. A 34-year-old unmarried male reported to our clinic with four main complaints: lack of sense of self since childhood; repeated thoughts questioning whether he existed or not; social withdrawal; and inability to continue in any occupation. Qualitative case analysis and discussions using descriptions from ancient texts and modern psychology led to the diagnosis of schizophrenia rather than spiritual advancement.

Healthcare resource utilisation by patients with coronary heart disease receiving a lifestyle-focused text message support program: an analysis from the TEXT ME study.

PubMed

Thakkar, Jay; Redfern, Julie; Khan, Ehsan; Atkins, Emily; Ha, Jeffrey; Vo, Kha; Thiagalingam, Aravinda; Chow, Clara K

2018-05-23

The 'Tobacco, Exercise and Diet Messages' (TEXT ME) study was a 6-month, single-centre randomised clinical trial (RCT) that found a text message support program improved levels of cardiovascular risk factors in patients with coronary heart disease (CHD). The current analyses examined whether receipt of text messages influenced participants' engagement with conventional healthcare resources. The TEXT ME study database (N=710) was linked with routinely collected health department databases. Number of doctor consultations, investigations and cardiac medication prescriptions in the two study groups were compared. The most frequently accessed health service was consultations with a General Practitioner (mean 7.1, s.d. 5.4). The numbers of medical consultations, biochemical tests or cardiac-specific investigations were similar between the study groups. There was at least one prescription registered for statin, ACEI/ARBs and β-blockers in 79, 66 and 50% of patients respectively, with similar refill rates in both the study groups. The study identified TEXT ME text messaging program did not increase use of Medicare Benefits Schedule (MBS) and Pharmaceutical Benefits Scheme (PBS) captured healthcare services. The observed benefits of TEXT ME reflect direct effects of intervention independent of conventional healthcare resource engagement.

Digital divide: variation in internet and cellular phone use among women attending an urban sexually transmitted infections clinic.

PubMed

Samal, Lipika; Hutton, Heidi E; Erbelding, Emily J; Brandon, Elizabeth S; Finkelstein, Joseph; Chander, Geetanjali

2010-01-01

We sought to describe: (1) the prevalence of internet, cellular phone, and text message use among women attending an urban sexually transmitted infections (STI) clinic, (2) the acceptability of health advice by each mode of information and communication technology (ICT), and (3) demographic characteristics associated with ICT use. This study is a cross-sectional survey of 200 English-speaking women presenting to a Baltimore City STI clinic with STI complaints. Participants completed a self-administered survey querying ICT use and demographic characteristics. Three separate questions asked about interest in receiving health advice delivered by the three modalities: internet, cellular phone, and text message. We performed logistic regression to examine how demographic factors (age, race, and education) are associated with likelihood of using each modality. The median age of respondents was 27 years; 87% were African American, and 71% had a high school diploma. The rate of any internet use was 80%; 31% reported daily use; 16% reported weekly use; and 32% reported less frequent use. Almost all respondents (93%) reported cellular phone use, and 79% used text messaging. Acceptability of health advice by each of the three modalities was about 60%. In multivariate analysis, higher education and younger age were associated with internet use, text messaging, and cellular phone use. Overall rate of internet use was high, but there was an educational disparity in internet use. Cellular phone use was almost universal in this sample. All three modalities were equally acceptable forms of health communication. Describing baseline ICT access and the acceptability of health advice via ICT, as we have done, is one step toward determining the feasibility of ICT-delivered health interventions in urban populations.

Parsing clinical text: how good are the state-of-the-art parsers?

PubMed

Jiang, Min; Huang, Yang; Fan, Jung-wei; Tang, Buzhou; Denny, Josh; Xu, Hua

2015-01-01

Parsing, which generates a syntactic structure of a sentence (a parse tree), is a critical component of natural language processing (NLP) research in any domain including medicine. Although parsers developed in the general English domain, such as the Stanford parser, have been applied to clinical text, there are no formal evaluations and comparisons of their performance in the medical domain. In this study, we investigated the performance of three state-of-the-art parsers: the Stanford parser, the Bikel parser, and the Charniak parser, using following two datasets: (1) A Treebank containing 1,100 sentences that were randomly selected from progress notes used in the 2010 i2b2 NLP challenge and manually annotated according to a Penn Treebank based guideline; and (2) the MiPACQ Treebank, which is developed based on pathology notes and clinical notes, containing 13,091 sentences. We conducted three experiments on both datasets. First, we measured the performance of the three state-of-the-art parsers on the clinical Treebanks with their default settings. Then we re-trained the parsers using the clinical Treebanks and evaluated their performance using the 10-fold cross validation method. Finally we re-trained the parsers by combining the clinical Treebanks with the Penn Treebank. Our results showed that the original parsers achieved lower performance in clinical text (Bracketing F-measure in the range of 66.6%-70.3%) compared to general English text. After retraining on the clinical Treebank, all parsers achieved better performance, with the best performance from the Stanford parser that reached the highest Bracketing F-measure of 73.68% on progress notes and 83.72% on the MiPACQ corpus using 10-fold cross validation. When the combined clinical Treebanks and Penn Treebank was used, of the three parsers, the Charniak parser achieved the highest Bracketing F-measure of 73.53% on progress notes and the Stanford parser reached the highest F-measure of 84.15% on the MiPACQ corpus. Our study demonstrates that re-training using clinical Treebanks is critical for improving general English parsers' performance on clinical text, and combining clinical and open domain corpora might achieve optimal performance for parsing clinical text.

The Effect of Multimedia Replacing Text in Resident Clinical Decision-Making Assessment

ERIC Educational Resources Information Center

Chang, Todd P.; Schrager, Sheree M.; Rake, Alyssa J.; Chan, Michael W.; Pham, Phung K.; Christman, Grant

2017-01-01

Multimedia in assessing clinical decision-making skills (CDMS) has been poorly studied, particularly in comparison to traditional text-based assessments. The literature suggests multimedia is more difficult for trainees. We hypothesize that pediatric residents score lower in diagnostic skill when clinical vignettes use multimedia rather than text…

Predictive factors for the placebo effect in clinical trials for dry eye: a pooled analysis of three clinical trials.

PubMed

Imanaka, Takahiro; Sato, Izumi; Tanaka, Shiro; Kawakami, Koji

2017-11-01

Placebo effect is one of the methodological difficulties in dry eye clinical trials. If we could elucidate the tendencies of the placebo response and find predictors, we could reduce the placebo response in clinical trials for dry eye. In this study, we investigated the predictive factors for the placebo effect in dry eye clinical trials. A total of 205 patients with dry eye assigned to the placebo arms of three placebo-controlled randomised clinical trials were analysed by simple and multivariable regression analysis. The corneal fluorescein (FL) staining score and dry eye symptoms were studied at week 4. The variables of interest included gender, age, complications of Sjögren's syndrome, Schirmer's test I value, tear break-up time and conjunctival hyperaemia score. We also conducted a stratified analysis according to the patients' age. Among all the studied endpoints, the baseline scores were significantly related to the corresponding placebo response. In addition, for the FL score and the dryness score, age was a significant predictor of the placebo response (p=0.04 and p<0.0001, respectively). Stratified analysis by age showed that patients more than 40 years of age are more likely to have a stronger placebo response in the FL and dryness scores. The baseline scores and age were predictive factors of the placebo response in frequently used endpoints, such as FL score or dryness symptoms. These patient characteristics can be controlled by study design, and our findings enable the design of more efficient placebo-controlled studies with good statistical power. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

The COPD Knowledge Base: enabling data analysis and computational simulation in translational COPD research.

PubMed

Cano, Isaac; Tényi, Ákos; Schueller, Christine; Wolff, Martin; Huertas Migueláñez, M Mercedes; Gomez-Cabrero, David; Antczak, Philipp; Roca, Josep; Cascante, Marta; Falciani, Francesco; Maier, Dieter

2014-11-28

Previously we generated a chronic obstructive pulmonary disease (COPD) specific knowledge base (http://www.copdknowledgebase.eu) from clinical and experimental data, text-mining results and public databases. This knowledge base allowed the retrieval of specific molecular networks together with integrated clinical and experimental data. The COPDKB has now been extended to integrate over 40 public data sources on functional interaction (e.g. signal transduction, transcriptional regulation, protein-protein interaction, gene-disease association). In addition we integrated COPD-specific expression and co-morbidity networks connecting over 6 000 genes/proteins with physiological parameters and disease states. Three mathematical models describing different aspects of systemic effects of COPD were connected to clinical and experimental data. We have completely redesigned the technical architecture of the user interface and now provide html and web browser-based access and form-based searches. A network search enables the use of interconnecting information and the generation of disease-specific sub-networks from general knowledge. Integration with the Synergy-COPD Simulation Environment enables multi-scale integrated simulation of individual computational models while integration with a Clinical Decision Support System allows delivery into clinical practice. The COPD Knowledge Base is the only publicly available knowledge resource dedicated to COPD and combining genetic information with molecular, physiological and clinical data as well as mathematical modelling. Its integrated analysis functions provide overviews about clinical trends and connections while its semantically mapped content enables complex analysis approaches. We plan to further extend the COPDKB by offering it as a repository to publish and semantically integrate data from relevant clinical trials. The COPDKB is freely available after registration at http://www.copdknowledgebase.eu.

Clinical periodontal variables in patients with and without dementia-a systematic review and meta-analysis.

PubMed

Maldonado, Alejandra; Laugisch, Oliver; Bürgin, Walter; Sculean, Anton; Eick, Sigrun

2018-06-22

Considering the increasing number of elderly people, dementia has gained an important role in today's society. Although the contributing factors for dementia have not been fully understood, chronic periodontitis (CP) seems to have a possible link to dementia. To conduct a systematic review including meta-analysis in order to assess potential differences in clinical periodontal variables between patients with dementia and non-demented individuals. The following focused question was evaluated: is periodontitis associated with dementia? Electronic searches in two databases, MEDLINE and EMBASE, were conducted. Meta-analysis was performed with the collected data in order to find a statistically significant difference in clinical periodontal variables between the group of dementia and the cognitive normal controls. Forty-two articles remained for full text reading. Finally, seven articles met the inclusion criteria and only five studies provided data suitable for meta-analysis. Periodontal probing depth (PPD), bleeding on probing (BOP), gingival bleeding index (GBI), clinical attachment level (CAL), and plaque index (PI) were included as periodontal variables in the meta-analysis. Each variable revealed a statistically significant difference between the groups. In an attempt to reveal an overall difference between the periodontal variables in dementia patients and non-demented individuals, the chosen variables were transformed into units that resulted in a statistically significant overall difference (p < 0.00001). The current findings indicate that compared to systemically healthy individuals, demented patients show significantly worse clinical periodontal variables. However, further epidemiological studies including a high numbers of participants, the use of exact definitions both for dementia and chronic periodontitis and adjusted for cofounders is warranted. These findings appear to support the putative link between CP and dementia. Consequently, the need for periodontal screening and treatment of elderly demented people should be emphasized.

BoB, a best-of-breed automated text de-identification system for VHA clinical documents.

PubMed

Ferrández, Oscar; South, Brett R; Shen, Shuying; Friedlin, F Jeffrey; Samore, Matthew H; Meystre, Stéphane M

2013-01-01

De-identification allows faster and more collaborative clinical research while protecting patient confidentiality. Clinical narrative de-identification is a tedious process that can be alleviated by automated natural language processing methods. The goal of this research is the development of an automated text de-identification system for Veterans Health Administration (VHA) clinical documents. We devised a novel stepwise hybrid approach designed to improve the current strategies used for text de-identification. The proposed system is based on a previous study on the best de-identification methods for VHA documents. This best-of-breed automated clinical text de-identification system (aka BoB) tackles the problem as two separate tasks: (1) maximize patient confidentiality by redacting as much protected health information (PHI) as possible; and (2) leave de-identified documents in a usable state preserving as much clinical information as possible. We evaluated BoB with a manually annotated corpus of a variety of VHA clinical notes, as well as with the 2006 i2b2 de-identification challenge corpus. We present evaluations at the instance- and token-level, with detailed results for BoB's main components. Moreover, an existing text de-identification system was also included in our evaluation. BoB's design efficiently takes advantage of the methods implemented in its pipeline, resulting in high sensitivity values (especially for sensitive PHI categories) and a limited number of false positives. Our system successfully addressed VHA clinical document de-identification, and its hybrid stepwise design demonstrates robustness and efficiency, prioritizing patient confidentiality while leaving most clinical information intact.

Using phrases and document metadata to improve topic modeling of clinical reports.

PubMed

Speier, William; Ong, Michael K; Arnold, Corey W

2016-06-01

Probabilistic topic models provide an unsupervised method for analyzing unstructured text, which have the potential to be integrated into clinical automatic summarization systems. Clinical documents are accompanied by metadata in a patient's medical history and frequently contains multiword concepts that can be valuable for accurately interpreting the included text. While existing methods have attempted to address these problems individually, we present a unified model for free-text clinical documents that integrates contextual patient- and document-level data, and discovers multi-word concepts. In the proposed model, phrases are represented by chained n-grams and a Dirichlet hyper-parameter is weighted by both document-level and patient-level context. This method and three other Latent Dirichlet allocation models were fit to a large collection of clinical reports. Examples of resulting topics demonstrate the results of the new model and the quality of the representations are evaluated using empirical log likelihood. The proposed model was able to create informative prior probabilities based on patient and document information, and captured phrases that represented various clinical concepts. The representation using the proposed model had a significantly higher empirical log likelihood than the compared methods. Integrating document metadata and capturing phrases in clinical text greatly improves the topic representation of clinical documents. The resulting clinically informative topics may effectively serve as the basis for an automatic summarization system for clinical reports. Copyright © 2016 Elsevier Inc. All rights reserved.

Sexual Self-Schemas in the Real World: Investigating the Ecological Validity of Language-Based Markers of Childhood Sexual Abuse

PubMed Central

Stanton, Amelia M.; Meston, Cindy M.

2017-01-01

Abstract This is the first study to examine language use and sexual self-schemas in natural language data extracted from posts to a large online forum. Recently, two studies applied advanced text analysis techniques to examine differences in language use and sexual self-schemas between women with and without a history of childhood sexual abuse. The aim of the current study was to test the ecological validity of the differences in language use and sexual self-schema themes that emerged between these two groups of women in the laboratory. Archival natural language data were extracted from a social media website and analyzed using LIWC2015, a computerized text analysis program, and other word counting approaches. The differences in both language use and sexual self-schema themes that manifested in recent laboratory research were replicated and validated in the large online sample. To our knowledge, these results provide the first empirical examination of sexual cognitions as they occur in the real world. These results also suggest that natural language analysis of text extracted from social media sites may be a potentially viable precursor or alternative to laboratory measurement of sexual trauma phenomena, as well as clinical phenomena, more generally. PMID:28570129

Clinical Outcomes of Comparing Soft Tissue Alternatives to Free Gingival Graft: A Systematic Review and Meta-Analysis
.

PubMed

Dragan, Irina F; Hotlzman, Lucrezia Paterno; Karimbux, Nadeem Y; Morin, Rebecca A; Bassir, Seyed Hossein

2017-12-01

This systematic review and meta-analysis aimed to compare clinical outcomes and width of keratinized tissue (KT) around teeth, following the soft tissue alter- natives and free gingival graft (FGG) procedures. The specific graft materials that were explored were extracellular matrix membrane, bilayer collagen membrane, living cellular construct, and acellular dermal matrix. Four different databases were queried to identify human controlled clinical trials and randomized controlled clinical trials that fulfilled the eligibility criteria. Relevant studies were identified by 3 independent reviewers, compiling the results of the electronic and handsearches. Studies identified through electronic and handsearches were reviewed by title, abstract, and full text using Covidence Software. Primary outcome in the present study was change in the width of KT. Results of the included studies were pooled to estimate the effect size, expressed as weighted mean differences and 95% confidence interval. A random-effects model was used to perform the meta-analyses. Six hundred thirty-eight articles were screened by title, 55 articles were screened by abstracts, and 34 full-text articles were reviewed. Data on quantitative changes in width of KT were provided in 7 studies. Quantitative analyses revealed a significant difference in changes in width of KT between patients treated with soft tissue alternatives and patients treated with FGGs (P < .001). The weighted mean difference of changes in the width of KT was 21.39 (95% confidence interval: 21.82 to 20.96; heterogeneity I 5 70.89%), indicating patients who were treated with soft tissue alternatives gained 1.39 mm less KT width compared with the patients who received free gingival graft. Based on the clinical outcomes, the results of this systematic review and meta-analysis showed that soft tissue alternatives result in an increased width of KT. Patients in the soft tissue alternatives group obtained 1.39 mm less KT compared with those in the FGGs group. Copyright © 2017 Elsevier Inc. All rights reserved.

An exploratory analysis of PubMed's free full-text limit on citation retrieval for clinical questions

PubMed Central

Krieger, Mary M.; Richter, Randy R.; Austin, Tricia M.

2008-01-01

Objective: The research sought to determine (1) how use of the PubMed free full-text (FFT) limit affects citation retrieval and (2) how use of the FFT limit impacts the types of articles and levels of evidence retrieved. Methods: Four clinical questions based on a research agenda for physical therapy were searched in PubMed both with and without the use of the FFT limit. Retrieved citations were examined for relevancy to each question. Abstracts of relevant citations were reviewed to determine the types of articles and levels of evidence. Descriptive analysis was used to compare the total number of citations, number of relevant citations, types of articles, and levels of evidence both with and without the use of the FFT limit. Results: Across all 4 questions, the FFT limit reduced the number of citations to 11.1% of the total number of citations retrieved without the FFT limit. Additionally, high-quality evidence such as systematic reviews and randomized controlled trials were missed when the FFT limit was used. Conclusions: Health sciences librarians play a key role in educating users about the potential impact the FFT limit has on the number of citations, types of articles, and levels of evidence retrieved. PMID:18974812

Online self-expression and experimentation as 'reflectivism': Using text analytics to examine the participatory forum Hello Sunday Morning.

PubMed

Carah, Nicholas; Meurk, Carla; Angus, Daniel

2017-03-01

Hello Sunday Morning is an online health promotion organisation that began in 2009. Hello Sunday Morning asks participants to stop consuming alcohol for a period of time, set a goal and document their progress on a personal blog. Hello Sunday Morning is a unique health intervention for three interrelated reasons: (1) it was generated outside a clinical setting, (2) it uses new media technologies to create structured forms of participation in an iterative and open-ended way and (3) participants generate a written record of their progress along with demographic, behavioural and engagement data. This article presents a text analysis of the blog posts of Hello Sunday Morning participants using the software program Leximancer. Analysis of blogs illustrates how participants' expressions change over time. In the first month, participants tended to set goals, describe their current drinking practices in individual and cultural terms, express hopes and anxieties and report on early efforts to change. After month 1, participants continued to report on efforts to change and associated challenges and reflect on their place as individuals in a drinking culture. In addition to this, participants evaluated their efforts to change and presented their 'findings' and 'theorised' them to provide advice for others. We contextualise this text analysis with respect to Hello Sunday Morning's development of more structured forms of online participation. We offer a critical appraisal of the value of text analytics in the development of online health interventions.

Methods and Techniques for Clinical Text Modeling and Analytics

ERIC Educational Resources Information Center

Ling, Yuan

2017-01-01

This study focuses on developing and applying methods/techniques in different aspects of the system for clinical text understanding, at both corpus and document level. We deal with two major research questions: First, we explore the question of "How to model the underlying relationships from clinical notes at corpus level?" Documents…

UMLS content views appropriate for NLP processing of the biomedical literature vs. clinical text.

PubMed

Demner-Fushman, Dina; Mork, James G; Shooshan, Sonya E; Aronson, Alan R

2010-08-01

Identification of medical terms in free text is a first step in such Natural Language Processing (NLP) tasks as automatic indexing of biomedical literature and extraction of patients' problem lists from the text of clinical notes. Many tools developed to perform these tasks use biomedical knowledge encoded in the Unified Medical Language System (UMLS) Metathesaurus. We continue our exploration of automatic approaches to creation of subsets (UMLS content views) which can support NLP processing of either the biomedical literature or clinical text. We found that suppression of highly ambiguous terms in the conservative AutoFilter content view can partially replace manual filtering for literature applications, and suppression of two character mappings in the same content view achieves 89.5% precision at 78.6% recall for clinical applications. Published by Elsevier Inc.

Quality clinical placements: The perspectives of undergraduate nursing students and their supervising nurses.

PubMed

Ford, Karen; Courtney-Pratt, Helen; Marlow, Annette; Cooper, John; Williams, Danielle; Mason, Ron

2016-02-01

Clinical placement for students of nursing is a central component of tertiary nursing programs but continues to be a complex and multifaceted experience for all stakeholders. This paper presents findings from a longitudinal 3-year study across multiple sites within the Australian context investigating the quality of clinical placements. A study using cross-sectional survey. Acute care, aged care and subacute health care facilities. A total of 1121 Tasmanian undergraduate nursing students and 932 supervising ward nurses. Survey data were collected at completion of practicum from participating undergraduate students and supervising ward nurses across the domains of "welcome and belonging," "competence and confidence: reflections on learning," and "support for learning." In addition, free text comments were sought to further inform understandings of what constitutes quality clinical placements. Overwhelmingly quantitative data demonstrate high-quality clinical placements are provided. Analysis of free text responses indicates further attention to the intersect between the student and the supervising ward nurse is required, including the differing expectations that each holds for the other. While meaningful interpersonal interactions are pivotal for learning, these seemingly concentrated on the relationship between student and their supervisor-the patient/client was not seen to be present. Meaningful learning occurs within an environment that facilitates mutual respect and shared expectations. The role the patient has in student learning was not made obvious in the results and therefore requires further investigation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Evaluating machine learning algorithms estimating tremor severity ratings on the Bain-Findley scale

NASA Astrophysics Data System (ADS)

Yohanandan, Shivanthan A. C.; Jones, Mary; Peppard, Richard; Tan, Joy L.; McDermott, Hugh J.; Perera, Thushara

2016-12-01

Tremor is a debilitating symptom of some movement disorders. Effective treatment, such as deep brain stimulation (DBS), is contingent upon frequent clinical assessments using instruments such as the Bain-Findley tremor rating scale (BTRS). Many patients, however, do not have access to frequent clinical assessments. Wearable devices have been developed to provide patients with access to frequent objective assessments outside the clinic via telemedicine. Nevertheless, the information they report is not in the form of BTRS ratings. One way to transform this information into BTRS ratings is through linear regression models (LRMs). Another, potentially more accurate method is through machine learning classifiers (MLCs). This study aims to compare MLCs and LRMs, and identify the most accurate model that can transform objective tremor information into tremor severity ratings on the BTRS. Nine participants with upper limb tremor had their DBS stimulation amplitude varied while they performed clinical upper-extremity exercises. Tremor features were acquired using the tremor biomechanics analysis laboratory (TREMBAL). Movement disorder specialists rated tremor severity on the BTRS from video recordings. Seven MLCs and 6 LRMs transformed TREMBAL features into tremor severity ratings on the BTRS using the specialists’ ratings as training data. The weighted Cohen’s kappa ({κ\\text{w}} ) defined the models’ rating accuracy. This study shows that the Random Forest MLC was the most accurate model ({κ\\text{w}}   =  0.81) at transforming tremor information into BTRS ratings, thereby improving the clinical interpretation of tremor information obtained from wearable devices.

Customizing clinical narratives for the electronic medical record interface using cognitive methods.

PubMed

Sharda, Pallav; Das, Amar K; Cohen, Trevor A; Patel, Vimla

2006-05-01

As healthcare practice transitions from paper-based to computer-based records, there is increasing need to determine an effective electronic format for clinical narratives. Our research focuses on utilizing a cognitive science methodology to guide the conversion of medical texts to a more structured, user-customized presentation in the electronic medical record (EMR). We studied the use of discharge summaries by psychiatrists with varying expertise-experts, intermediates, and novices. Experts were given two hypothetical emergency care scenarios with narrative discharge summaries and asked to verbalize their clinical assessment. Based on the results, the narratives were presented in a more structured form. Intermediate and novice subjects received a narrative and a structured discharge summary, and were asked to verbalize their assessments of each. A qualitative comparison of the interview transcripts of all subjects was done by analysis of recall and inference made with respect to level of expertise. For intermediate and novice subjects, recall was greater with the structured form than with the narrative. Novices were also able to make more inferences (not always accurate) from the structured form than with the narrative. Errors occurred in assessments using the narrative form but not the structured form. Our cognitive methods to study discharge summary use enabled us to extract a conceptual representation of clinical narratives from end-users. This method allowed us to identify clinically relevant information that can be used to structure medical text for the EMR and potentially improve recall and reduce errors.

Classifying nursing errors in clinical management within an Australian hospital.

PubMed

Tran, D T; Johnson, M

2010-12-01

Although many classification systems relating to patient safety exist, no taxonomy was identified that classified nursing errors in clinical management. To develop a classification system for nursing errors relating to clinical management (NECM taxonomy) and to describe contributing factors and patient consequences. We analysed 241 (11%) self-reported incidents relating to clinical management in nursing in a metropolitan hospital. Descriptive analysis of numeric data and content analysis of text data were undertaken to derive the NECM taxonomy, contributing factors and consequences for patients. Clinical management incidents represented 1.63 incidents per 1000 occupied bed days. The four themes of the NECM taxonomy were nursing care process (67%), communication (22%), administrative process (5%), and knowledge and skill (6%). Half of the incidents did not cause any patient harm. Contributing factors (n=111) included the following: patient clinical, social conditions and behaviours (27%); resources (22%); environment and workload (18%); other health professionals (15%); communication (13%); and nurse's knowledge and experience (5%). The NECM taxonomy provides direction to clinicians and managers on areas in clinical management that are most vulnerable to error, and therefore, priorities for system change management. Any nurses who wish to classify nursing errors relating to clinical management could use these types of errors. This study informs further research into risk management behaviour, and self-assessment tools for clinicians. Globally, nurses need to continue to monitor and act upon patient safety issues. © 2010 The Authors. International Nursing Review © 2010 International Council of Nurses.

Application of a temporal reasoning framework tool in analysis of medical device adverse events.

PubMed

Clark, Kimberly K; Sharma, Deepak K; Chute, Christopher G; Tao, Cui

2011-01-01

The Clinical Narrative Temporal Relation Ontology (CNTRO)1 project offers a semantic-web based reasoning framework, which represents temporal events and relationships within clinical narrative texts, and infer new knowledge over them. In this paper, the CNTRO reasoning framework is applied to temporal analysis of medical device adverse event files. One specific adverse event was used as a test case: late stent thrombosis. Adverse event narratives were obtained from the Food and Drug Administration's (FDA) Manufacturing and User Facility Device Experience (MAUDE) database2. 15 adverse event files in which late stent thrombosis was confirmed were randomly selected across multiple drug eluting stent devices. From these files, 81 events and 72 temporal relations were annotated. 73 temporal questions were generated, of which 65 were correctly answered by the CNTRO system. This results in an overall accuracy of 89%. This system should be pursued further to continue assessing its potential benefits in temporal analysis of medical device adverse events.

DECISION-COMPONENTS OF NICE'S TECHNOLOGY APPRAISALS ASSESSMENT FRAMEWORK.

PubMed

de Folter, Joost; Trusheim, Mark; Jonsson, Pall; Garner, Sarah

2018-01-01

Value assessment frameworks have gained prominence recently in the context of U.S. healthcare. Such frameworks set out a series of factors that are considered in funding decisions. The UK's National Institute of Health and Care Excellence (NICE) is an established health technology assessment (HTA) agency. We present a novel application of text analysis that characterizes NICE's Technology Appraisals in the context of the newer assessment frameworks and present the results in a visual way. A total of 243 documents of NICE's medicines guidance from 2007 to 2016 were analyzed. Text analysis was used to identify a hierarchical set of decision factors considered in the assessments. The frequency of decision factors stated in the documents was determined and their association with terms related to uncertainty. The results were incorporated into visual representations of hierarchical factors. We identified 125 decision factors, and hierarchically grouped these into eight domains: Clinical Effectiveness, Cost Effectiveness, Condition, Current Practice, Clinical Need, New Treatment, Studies, and Other Factors. Textual analysis showed all domains appeared consistently in the guidance documents. Many factors were commonly associated with terms relating to uncertainty. A series of visual representations was created. This study reveals the complexity and consistency of NICE's decision-making processes and demonstrates that cost effectiveness is not the only decision-criteria. The study highlights the importance of processes and methodology that can take both quantitative and qualitative information into account. Visualizations can help effectively communicate this complex information during the decision-making process and subsequently to stakeholders.

Statistical analysis of 4 types of neck whiplash injuries based on classical meridian theory.

PubMed

Chen, Yemeng; Zhao, Yan; Xue, Xiaolin; Li, Hui; Wu, Xiuyan; Zhang, Qunce; Zheng, Xin; Wang, Tianfang

2015-01-01

As one component of the Chinese medicine meridian system, the meridian sinew (Jingjin, (see text), tendino-musculo) is specially described as being for acupuncture treatment of the musculoskeletal system because of its dynamic attributes and tender point correlations. In recent decades, the therapeutic importance of the sinew meridian has become revalued in clinical application. Based on this theory, the authors have established therapeutic strategies of acupuncture treatment in Whiplash-Associated Disorders (WAD) by categorizing four types of neck symptom presentations. The advantage of this new system is to make it much easier for the clinician to find effective acupuncture points. This study attempts to prove the significance of the proposed therapeutic strategies by analyzing data collected from a clinical survey of various WAD using non-supervised statistical methods, such as correlation analysis, factor analysis, and cluster analysis. The clinical survey data have successfully verified discrete characteristics of four neck syndromes, based upon the range of motion (ROM) and tender point location findings. A summary of the relationships among the symptoms of the four neck syndromes has shown the correlation coefficient as having a statistical significance (P < 0.01 or P < 0.05), especially with regard to ROM. Furthermore, factor and cluster analyses resulted in a total of 11 categories of general symptoms, which implies syndrome factors are more related to the Liver, as originally described in classical theory. The hypothesis of meridian sinew syndromes in WAD is clearly supported by the statistical analysis of the clinical trials. This new discovery should be beneficial in improving therapeutic outcomes.

The Full Spectrum of Clinical Ethical Issues in Kidney Failure. Findings of a Systematic Qualitative Review.

PubMed

Kahrass, Hannes; Strech, Daniel; Mertz, Marcel

2016-01-01

When treating patients with kidney failure, unavoidable ethical issues often arise. Current clinical practice guidelines some of them, but lack comprehensive information about the full range of relevant ethical issues in kidney failure. A systematic literature review of such ethical issues supports medical professionalism in nephrology, and offers a solid evidential base for efforts that aim to improve ethical conduct in health care. To identify the full spectrum of clinical ethical issues that can arise for patients with kidney failure in a systematic and transparent manner. A systematic review in Medline (publications in English or German between 2000 and 2014) and Google Books (with no restrictions) was conducted. Ethical issues were identified by qualitative text analysis and normative analysis. The literature review retrieved 106 references that together mentioned 27 ethical issues in clinical care of kidney failure. This set of ethical issues was structured into a matrix consisting of seven major categories and further first and second-order categories. The systematically-derived matrix helps raise awareness and understanding of the complexity of ethical issues in kidney failure. It can be used to identify ethical issues that should be addressed in specific training programs for clinicians, clinical practice guidelines, or other types of policies dealing with kidney failure.

The Full Spectrum of Clinical Ethical Issues in Kidney Failure. Findings of a Systematic Qualitative Review

PubMed Central

Kahrass, Hannes; Strech, Daniel; Mertz, Marcel

2016-01-01

Background When treating patients with kidney failure, unavoidable ethical issues often arise. Current clinical practice guidelines some of them, but lack comprehensive information about the full range of relevant ethical issues in kidney failure. A systematic literature review of such ethical issues supports medical professionalism in nephrology, and offers a solid evidential base for efforts that aim to improve ethical conduct in health care. Aim To identify the full spectrum of clinical ethical issues that can arise for patients with kidney failure in a systematic and transparent manner. Method A systematic review in Medline (publications in English or German between 2000 and 2014) and Google Books (with no restrictions) was conducted. Ethical issues were identified by qualitative text analysis and normative analysis. Results The literature review retrieved 106 references that together mentioned 27 ethical issues in clinical care of kidney failure. This set of ethical issues was structured into a matrix consisting of seven major categories and further first and second-order categories. Conclusions The systematically-derived matrix helps raise awareness and understanding of the complexity of ethical issues in kidney failure. It can be used to identify ethical issues that should be addressed in specific training programs for clinicians, clinical practice guidelines, or other types of policies dealing with kidney failure. PMID:26938863

Text Mining for Precision Medicine: Bringing structure to EHRs and biomedical literature to understand genes and health

PubMed Central

Simmons, Michael; Singhal, Ayush; Lu, Zhiyong

2018-01-01

The key question of precision medicine is whether it is possible to find clinically actionable granularity in diagnosing disease and classifying patient risk. The advent of next generation sequencing and the widespread adoption of electronic health records (EHRs) have provided clinicians and researchers a wealth of data and made possible the precise characterization of individual patient genotypes and phenotypes. Unstructured text — found in biomedical publications and clinical notes — is an important component of genotype and phenotype knowledge. Publications in the biomedical literature provide essential information for interpreting genetic data. Likewise, clinical notes contain the richest source of phenotype information in EHRs. Text mining can render these texts computationally accessible and support information extraction and hypothesis generation. This chapter reviews the mechanics of text mining in precision medicine and discusses several specific use cases, including database curation for personalized cancer medicine, patient outcome prediction from EHR-derived cohorts, and pharmacogenomic research. Taken as a whole, these use cases demonstrate how text mining enables effective utilization of existing knowledge sources and thus promotes increased value for patients and healthcare systems. Text mining is an indispensable tool for translating genotype-phenotype data into effective clinical care that will undoubtedly play an important role in the eventual realization of precision medicine. PMID:27807747

Text Mining for Precision Medicine: Bringing Structure to EHRs and Biomedical Literature to Understand Genes and Health.

PubMed

Simmons, Michael; Singhal, Ayush; Lu, Zhiyong

2016-01-01

The key question of precision medicine is whether it is possible to find clinically actionable granularity in diagnosing disease and classifying patient risk. The advent of next-generation sequencing and the widespread adoption of electronic health records (EHRs) have provided clinicians and researchers a wealth of data and made possible the precise characterization of individual patient genotypes and phenotypes. Unstructured text-found in biomedical publications and clinical notes-is an important component of genotype and phenotype knowledge. Publications in the biomedical literature provide essential information for interpreting genetic data. Likewise, clinical notes contain the richest source of phenotype information in EHRs. Text mining can render these texts computationally accessible and support information extraction and hypothesis generation. This chapter reviews the mechanics of text mining in precision medicine and discusses several specific use cases, including database curation for personalized cancer medicine, patient outcome prediction from EHR-derived cohorts, and pharmacogenomic research. Taken as a whole, these use cases demonstrate how text mining enables effective utilization of existing knowledge sources and thus promotes increased value for patients and healthcare systems. Text mining is an indispensable tool for translating genotype-phenotype data into effective clinical care that will undoubtedly play an important role in the eventual realization of precision medicine.

Bidirectional Text Messaging to Improve Adherence to Recommended Lipid Testing.

PubMed

Baldwin, Laura-Mae; Morrison, Caitlin; Griffin, Jonathan; Anderson, Nick; Edwards, Kelly; Green, Jeff; Waldren, Cleary; Reiter, William

2017-01-01

Synergies between technology and health care in the United States are accelerating, increasing opportunities to leverage these technologies to improve patient care. This study was a collaboration between an academic study team, a rural primary care clinic, and a local nonprofit informatics company developing tools to improve patient care through population management. Our team created a text messaging management tool, then developed methods for and tested the feasibility of bidirectional text messaging to remind eligible patients about the need for lipid testing. We measured patient response to the text messages, then interviewed 8 patients to explore their text messaging experience. Of the 129 patients the clinic was able to contact by phone, 29.4% had no cell phone or text-messaging capabilities. An additional 20% refused to participate. Two thirds of the 28 patients who participated in the text messaging intervention (67.9%) responded to at least 1 of the up to 3 messages. Seven of 8 interviewed patients had a positive text-messaging experience. Bidirectional text messaging is a feasible and largely acceptable form of communication for test reminders that has the potential to reach large numbers of patients in clinical care. © Copyright 2017 by the American Board of Family Medicine.

Parsing clinical text: how good are the state-of-the-art parsers?

PubMed Central

2015-01-01

Background Parsing, which generates a syntactic structure of a sentence (a parse tree), is a critical component of natural language processing (NLP) research in any domain including medicine. Although parsers developed in the general English domain, such as the Stanford parser, have been applied to clinical text, there are no formal evaluations and comparisons of their performance in the medical domain. Methods In this study, we investigated the performance of three state-of-the-art parsers: the Stanford parser, the Bikel parser, and the Charniak parser, using following two datasets: (1) A Treebank containing 1,100 sentences that were randomly selected from progress notes used in the 2010 i2b2 NLP challenge and manually annotated according to a Penn Treebank based guideline; and (2) the MiPACQ Treebank, which is developed based on pathology notes and clinical notes, containing 13,091 sentences. We conducted three experiments on both datasets. First, we measured the performance of the three state-of-the-art parsers on the clinical Treebanks with their default settings. Then we re-trained the parsers using the clinical Treebanks and evaluated their performance using the 10-fold cross validation method. Finally we re-trained the parsers by combining the clinical Treebanks with the Penn Treebank. Results Our results showed that the original parsers achieved lower performance in clinical text (Bracketing F-measure in the range of 66.6%-70.3%) compared to general English text. After retraining on the clinical Treebank, all parsers achieved better performance, with the best performance from the Stanford parser that reached the highest Bracketing F-measure of 73.68% on progress notes and 83.72% on the MiPACQ corpus using 10-fold cross validation. When the combined clinical Treebanks and Penn Treebank was used, of the three parsers, the Charniak parser achieved the highest Bracketing F-measure of 73.53% on progress notes and the Stanford parser reached the highest F-measure of 84.15% on the MiPACQ corpus. Conclusions Our study demonstrates that re-training using clinical Treebanks is critical for improving general English parsers' performance on clinical text, and combining clinical and open domain corpora might achieve optimal performance for parsing clinical text. PMID:26045009

Taming Big Data: An Information Extraction Strategy for Large Clinical Text Corpora.

PubMed

Gundlapalli, Adi V; Divita, Guy; Carter, Marjorie E; Redd, Andrew; Samore, Matthew H; Gupta, Kalpana; Trautner, Barbara

2015-01-01

Concepts of interest for clinical and research purposes are not uniformly distributed in clinical text available in electronic medical records. The purpose of our study was to identify filtering techniques to select 'high yield' documents for increased efficacy and throughput. Using two large corpora of clinical text, we demonstrate the identification of 'high yield' document sets in two unrelated domains: homelessness and indwelling urinary catheters. For homelessness, the high yield set includes homeless program and social work notes. For urinary catheters, concepts were more prevalent in notes from hospitalized patients; nursing notes accounted for a majority of the high yield set. This filtering will enable customization and refining of information extraction pipelines to facilitate extraction of relevant concepts for clinical decision support and other uses.

NIH Seeks Input on In-patient Clinical Research Areas | Division of Cancer Prevention

Cancer.gov

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The full spectrum of ethical issues in dementia care: systematic qualitative review.

PubMed

Strech, Daniel; Mertz, Marcel; Knüppel, Hannes; Neitzke, Gerald; Schmidhuber, Martina

2013-06-01

Integrating ethical issues in dementia-specific training material, clinical guidelines and national strategy plans requires an unbiased awareness of all the relevant ethical issues. To determine systematically and transparently the full spectrum of ethical issues in clinical dementia care. We conducted a systematic review in Medline (restricted to English and German literature published between 2000 and 2011) and Google books (with no restrictions). We applied qualitative text analysis and normative analysis to categorise the spectrum of ethical issues in clinical dementia care. The literature review retrieved 92 references that together mentioned a spectrum of 56 ethical issues in clinical dementia care. The spectrum was structured into seven major categories that consist of first- and second-order categories for ethical issues. The systematically derived spectrum of ethical issues in clinical dementia care presented in this paper can be used as training material for healthcare professionals, students and the public for raising awareness and understanding of the complexity of ethical issues in dementia care. It can also be used to identify ethical issues that should be addressed in dementia-specific training programmes, national strategy plans and clinical practice guidelines. Further research should evaluate whether this new genre of systematic reviews can be applied to the identification of ethical issues in other cognitive and somatic diseases. Also, the practical challenges in addressing ethical issues in training material, guidelines and policies need to be evaluated.

Early termination of cardiovascular trials as a consequence of poor accrual: analysis of ClinicalTrials.gov 2006-2015.

PubMed

Baldi, Ileana; Lanera, Corrado; Berchialla, Paola; Gregori, Dario

2017-06-15

To present a snapshot of experimental cardiovascular research with a focus on geographical and temporal patterns of early termination due to poor accrual. The Aggregate Analysis of ClinicalTrials.gov (AACT) database, reflecting ClinicalTrials.gov as of 27 March 2016. The AACT database was searched for all cardiovascular clinical trials that started from January 2006 up to December 2015. Thirteen thousand and seven hundred twenty-nine cardiovascular trials were identified. Of these, 8900 (65%) were classified as closed studies. Globally, 11% of closed trials were terminated. This proportion varied from 9.6% to 14% for trials recruiting from Europe and Americas, respectively, with a slightly decreasing trend (p=0.02) over the study period. The most common reason for trials failing to complete was poor accrual (41%). Intercontinental trials exhibited lower figures of poor accrual as the reason for their early stopping, as compared with trials recruiting in a single continent (28% vs 44%, p=0.002). Poor accrual significantly challenges the successful completion of cardiovascular clinical trials. Findings are suggestive of a positive effect of globalisation of cardiovascular clinical research on the achievement of enrolment goals within a reasonable time frame. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Medical Student and Tutor Perceptions of Video Versus Text in an Interactive Online Virtual Patient for Problem-Based Learning: A Pilot Study

PubMed Central

Ellaway, Rachel H; Round, Jonathan; Vaughan, Sophie; Poulton, Terry; Zary, Nabil

2015-01-01

Background The impact of the use of video resources in primarily paper-based problem-based learning (PBL) settings has been widely explored. Although it can provide many benefits, the use of video can also hamper the critical thinking of learners in contexts where learners are developing clinical reasoning. However, the use of video has not been explored in the context of interactive virtual patients for PBL. Objective A pilot study was conducted to explore how undergraduate medical students interpreted and evaluated information from video- and text-based materials presented in the context of a branched interactive online virtual patient designed for PBL. The goal was to inform the development and use of virtual patients for PBL and to inform future research in this area. Methods An existing virtual patient for PBL was adapted for use in video and provided as an intervention to students in the transition year of the undergraduate medicine course at St George’s, University of London. Survey instruments were used to capture student and PBL tutor experiences and perceptions of the intervention, and a formative review meeting was run with PBL tutors. Descriptive statistics were generated for the structured responses and a thematic analysis was used to identify emergent themes in the unstructured responses. Results Analysis of student responses (n=119) and tutor comments (n=18) yielded 8 distinct themes relating to the perceived educational efficacy of information presented in video and text formats in a PBL context. Although some students found some characteristics of the videos beneficial, when asked to express a preference for video or text the majority of those that responded to the question (65%, 65/100) expressed a preference for text. Student responses indicated that the use of video slowed the pace of PBL and impeded students’ ability to review and critically appraise the presented information. Conclusions Our findings suggest that text was perceived to be a better source of information than video in virtual patients for PBL. More specifically, the use of video was perceived as beneficial for providing details, visual information, and context where text was unable to do so. However, learner acceptance of text was higher in the context of PBL, particularly when targeting clinical reasoning skills. This pilot study has provided the foundation for further research into the effectiveness of different virtual patient designs for PBL. PMID:26088435

Qualitative analysis of healthcare professionals' viewpoints on the role of ethics committees and hospitals in the resolution of clinical ethical dilemmas.

PubMed

Marcus, Brian S; Shank, Gary; Carlson, Jestin N; Venkat, Arvind

2015-03-01

Ethics consultation is a commonly applied mechanism to address clinical ethical dilemmas. However, there is little information on the viewpoints of health care providers towards the relevance of ethics committees and appropriate application of ethics consultation in clinical practice. We sought to use qualitative methodology to evaluate free-text responses to a case-based survey to identify thematically the views of health care professionals towards the role of ethics committees in resolving clinical ethical dilemmas. Using an iterative and reflexive model we identified themes that health care providers support a role for ethics committees and hospitals in resolving clinical ethical dilemmas, that the role should be one of mediation, rather than prescription, but that ultimately legal exposure was dispositive compared to ethical theory. The identified theme of legal fears suggests that the mediation role of ethics committees is viewed by health care professionals primarily as a practical means to avoid more worrisome medico-legal conflict.

Antenatal health promotion via short message service at a Midwife Obstetrics Unit in South Africa: a mixed methods study.

PubMed

Lau, Yan Kwan; Cassidy, Tali; Hacking, Damian; Brittain, Kirsty; Haricharan, Hanne Jensen; Heap, Marion

2014-08-21

Adequate antenatal care is important to both the health of a pregnant woman and her unborn baby. Given South Africa's high rate of cellphone penetration, mobile health interventions have been touted as a potentially powerful means to disseminate health information. This study aimed to increase antenatal health knowledge and awareness by disseminating text messages about clinic procedures at antenatal visits, and how to be healthy during pregnancy. Participants recruited were pregnant women attending a primary health care facility in Cape Town. A controlled clinical trial was carried out where the intervention group (n = 102) received text messages staggered according to the week of pregnancy at the time of recruitment. The control group (n = 104) received no text messages. These text messages contained antenatal health information, and were delivered in English, Xhosa or Afrikaans, according to the preference of each participant. A baseline knowledge questionnaire with nine questions was administered prior to the intervention. The same questionnaire was used with added health-related behaviour questions for the intervention group at exit. A modified intention-to-treat analysis was done. To compare the control and intervention group's knowledge, Fisher's exact tests and two-sample t-tests tests were carried out for binary and continuous outcomes, respectively. A focus group of seven participants from the intervention group was then conducted to gain more insight into how the text messages were perceived. There was substantial loss to follow-up during the study with only 57% of the participants retained at exit. No statistically significant difference was detected between the control and intervention group in any of the nine knowledge questions at exit (all p > 0.05). Responses from the focus group indicated that the text messages acted as a welcome reminder and a source of positive motivation, and were perceived as extended care from the health care provider. While the intervention failed to improve antenatal health knowledge, evidence from self-reported behaviour and the focus group suggests that text messages have the potential to motivate change in health-seeking behaviour. One should be mindful of loss to follow-up when rolling out mobile health interventions in developing country settings. Pan African Clinical Trials Registry PACTR201406000841188. Registered 3 June 2014.

Can physicians recognize their own patients in de-identified notes?

PubMed

Meystre, Stéphane; Shen, Shuying; Hofmann, Deborah; Gundlapalli, Adi

2014-01-01

The adoption of Electronic Health Records is growing at a fast pace, and this growth results in very large quantities of patient clinical information becoming available in electronic format, with tremendous potentials, but also equally growing concern for patient confidentiality breaches. De-identification of patient information has been proposed as a solution to both facilitate secondary uses of clinical information, and protect patient information confidentiality. Automated approaches based on Natural Language Processing have been implemented and evaluated, allowing for much faster text de-identification than manual approaches. A U.S. Veterans Affairs clinical text de-identification project focused on investigating the current state of the art of automatic clinical text de-identification, on developing a best-of-breed de-identification application for clinical documents, and on evaluating its impact on subsequent text uses and the risk for re-identification. To evaluate this risk, we de-identified discharge summaries from 86 patients using our 'best-of-breed' text de-identification application with resynthesis of the identifiers detected. We then asked physicians working in the ward the patients were hospitalized in if they could recognize these patients when reading the de-identified documents. Each document was examined by at least one resident and one attending physician, and with 4.65% of the documents, physicians thought they recognized the patient because of specific clinical information, but after verification, none was correctly re-identified.

Randomized Trial of a Web-Based Intervention to Address Barriers to Clinical Trials.

PubMed

Meropol, Neal J; Wong, Yu-Ning; Albrecht, Terrance; Manne, Sharon; Miller, Suzanne M; Flamm, Anne Lederman; Benson, Al Bowen; Buzaglo, Joanne; Collins, Michael; Egleston, Brian; Fleisher, Linda; Katz, Michael; Kinzy, Tyler G; Liu, Tasnuva M; Margevicius, Seunghee; Miller, Dawn M; Poole, David; Roach, Nancy; Ross, Eric; Schluchter, Mark D

2016-02-10

Lack of knowledge and negative attitudes have been identified as barriers to participation in clinical trials by patients with cancer. We developed Preparatory Education About Clinical Trials (PRE-ACT), a theory-guided, Web-based, interactive computer program, to deliver tailored video educational content to patients in an effort to overcome barriers to considering clinical trials as a treatment option. A prospective, randomized clinical trial compared PRE-ACT with a control condition that provided general clinical trials information produced by the National Cancer Institute (NCI) in text format. One thousand two hundred fifty-five patients with cancer were randomly allocated before their initial visit with an oncologist to PRE-ACT (n = 623) or control (n = 632). PRE-ACT had three main components: assessment of clinical trials knowledge and attitudinal barriers, values assessment with clarification back to patients, and provision of a video library tailored to address each patient's barriers. Outcomes included knowledge and attitudes and preparation for decision making about clinical trials. Both PRE-ACT and control interventions improved knowledge and attitudes (all P < .001) compared with baseline. Patients randomly allocated to PRE-ACT showed a significantly greater increase in knowledge (P < .001) and a significantly greater decrease in attitudinal barriers (P < .001) than did their control (text-only) counterparts. Participants in both arms significantly increased their preparedness to consider clinical trials (P < .001), and there was a trend favoring the PRE-ACT group (P < .09). PRE-ACT was also associated with greater patient satisfaction than was NCI text alone. These data show that patient education before the first oncologist visit improves knowledge, attitudes, and preparation for decision making about clinical trials. Both text and tailored video were effective. The PRE-ACT interactive video program was more effective than NCI text in improving knowledge and reducing attitudinal barriers. © 2015 by American Society of Clinical Oncology.

Multidimensional Interactive Radiology Report and Analysis: standardization of workflow and reporting for renal mass tracking and quantification

NASA Astrophysics Data System (ADS)

Hwang, Darryl H.; Ma, Kevin; Yepes, Fernando; Nadamuni, Mridula; Nayyar, Megha; Liu, Brent; Duddalwar, Vinay; Lepore, Natasha

2015-12-01

A conventional radiology report primarily consists of a large amount of unstructured text, and lacks clear, concise, consistent and content-rich information. Hence, an area of unmet clinical need consists of developing better ways to communicate radiology findings and information specific to each patient. Here, we design a new workflow and reporting system that combines and integrates advances in engineering technology with those from the medical sciences, the Multidimensional Interactive Radiology Report and Analysis (MIRRA). Until recently, clinical standards have primarily relied on 2D images for the purpose of measurement, but with the advent of 3D processing, many of the manually measured metrics can be automated, leading to better reproducibility and less subjective measurement placement. Hence, we make use this newly available 3D processing in our workflow. Our pipeline is used here to standardize the labeling, tracking, and quantifying of metrics for renal masses.

A text-based data mining and toxicity prediction modeling system for a clinical decision support in radiation oncology: A preliminary study

NASA Astrophysics Data System (ADS)

Kim, Kwang Hyeon; Lee, Suk; Shim, Jang Bo; Chang, Kyung Hwan; Yang, Dae Sik; Yoon, Won Sup; Park, Young Je; Kim, Chul Yong; Cao, Yuan Jie

2017-08-01

The aim of this study is an integrated research for text-based data mining and toxicity prediction modeling system for clinical decision support system based on big data in radiation oncology as a preliminary research. The structured and unstructured data were prepared by treatment plans and the unstructured data were extracted by dose-volume data image pattern recognition of prostate cancer for research articles crawling through the internet. We modeled an artificial neural network to build a predictor model system for toxicity prediction of organs at risk. We used a text-based data mining approach to build the artificial neural network model for bladder and rectum complication predictions. The pattern recognition method was used to mine the unstructured toxicity data for dose-volume at the detection accuracy of 97.9%. The confusion matrix and training model of the neural network were achieved with 50 modeled plans (n = 50) for validation. The toxicity level was analyzed and the risk factors for 25% bladder, 50% bladder, 20% rectum, and 50% rectum were calculated by the artificial neural network algorithm. As a result, 32 plans could cause complication but 18 plans were designed as non-complication among 50 modeled plans. We integrated data mining and a toxicity modeling method for toxicity prediction using prostate cancer cases. It is shown that a preprocessing analysis using text-based data mining and prediction modeling can be expanded to personalized patient treatment decision support based on big data.

Finding Cervical Cancer Symptoms in Swedish Clinical Text using a Machine Learning Approach and NegEx

PubMed Central

Weegar, Rebecka; Kvist, Maria; Sundström, Karin; Brunak, Søren; Dalianis, Hercules

2015-01-01

Detection of early symptoms in cervical cancer is crucial for early treatment and survival. To find symptoms of cervical cancer in clinical text, Named Entity Recognition is needed. In this paper the Clinical Entity Finder, a machine-learning tool trained on annotated clinical text from a Swedish internal medicine emergency unit, is evaluated on cervical cancer records. The Clinical Entity Finder identifies entities of the types body part, finding and disorder and is extended with negation detection using the rule-based tool NegEx, to distinguish between negated and non-negated entities. To measure the performance of the tools on this new domain, two physicians annotated a set of clinical notes from the health records of cervical cancer patients. The inter-annotator agreement for finding, disorder and body part obtained an average F-score of 0.677 and the Clinical Entity Finder extended with NegEx had an average F-score of 0.667. PMID:26958270

Finding Cervical Cancer Symptoms in Swedish Clinical Text using a Machine Learning Approach and NegEx.

PubMed

Weegar, Rebecka; Kvist, Maria; Sundström, Karin; Brunak, Søren; Dalianis, Hercules

2015-01-01

Detection of early symptoms in cervical cancer is crucial for early treatment and survival. To find symptoms of cervical cancer in clinical text, Named Entity Recognition is needed. In this paper the Clinical Entity Finder, a machine-learning tool trained on annotated clinical text from a Swedish internal medicine emergency unit, is evaluated on cervical cancer records. The Clinical Entity Finder identifies entities of the types body part, finding and disorder and is extended with negation detection using the rule-based tool NegEx, to distinguish between negated and non-negated entities. To measure the performance of the tools on this new domain, two physicians annotated a set of clinical notes from the health records of cervical cancer patients. The inter-annotator agreement for finding, disorder and body part obtained an average F-score of 0.677 and the Clinical Entity Finder extended with NegEx had an average F-score of 0.667.

Family nurse practitioner student perception of journal abstract usefulness in clinical decision making: a randomized controlled trial.

PubMed

Johnson, Heather L; Fontelo, Paul; Olsen, Cara H; Jones, Kenneth D; Gimbel, Ronald W

2013-11-01

To assess family nurse practitioner (FNP) student perception of research abstract usefulness in clinical decision making. A randomized controlled trial conducted in a simulated environment with graduate FNP students of the Graduate School of Nursing, Uniformed Services University of the Health Sciences. Given a clinical case study and modified MEDLINE search tool accessible via an iPad device, participants were asked to develop a treatment plan and complete a data collection form. The primary measure was perceived usefulness of the research abstracts in clinical decision making regarding a simulated obese patient seeking to prevent type 2 diabetes. Secondary measures related to participant demographics and accessibility and usefulness of full-text manuscripts. The majority of NP students identified readily available research abstracts as useful in shaping their clinical decision making. The presence or absence of full-text manuscripts associated with the abstracts did not appear to influence the perceived abstract usefulness. The majority of students with full-text manuscript access in the timed simulated clinical encounter read at least one paper, but cited insufficient time to read full-text as a constraint. Research abstracts at point of care may be valuable to FNPs if easily accessible and integrated into clinical workflow. ©2013 The Author(s) ©2013 American Association of Nurse Practitioners.

Computers in the clinical encounter: a scoping review and thematic analysis.

PubMed

Crampton, Noah H; Reis, Shmuel; Shachak, Aviv

2016-05-01

Patient-clinician communication has been associated with increased patient satisfaction, trust in the clinician, adherence to prescribed therapy, and various health outcomes. The impact of health information technology (HIT) on the clinical encounter in general and patient-clinician communication in particular is a growing concern. The purpose of this study was to review the current literature on HIT use during the clinical encounter to update best practices and inform the continuous development of HIT policies and educational interventions. We conducted a literature search of four databases. After removing duplicates, reviewing titles and abstracts, performing a full-text review, and snowballing from references and citations, 51 articles were included in the analysis. We employed a qualitative thematic analysis to compare and contrast the findings across studies. Our analysis revealed that the use of HIT affects consultations in complex ways, impacting eye contact and gaze, information sharing, building relationships, and pauses in the conversation. Whether these impacts are positive or negative largely depends on the combination of consultation room layout, patient and clinician styles of interaction with HIT as well as each other, and the strategies and techniques employed by clinicians to integrate HIT into consultations. The in-depth insights into the impact of HIT on the clinical encounter, especially the strategies and techniques employed by clinicians to adapt to using HIT in consultations, can inform policies, educational interventions, and research. In contrast to the common negative views of HIT, it affects the clinical encounter in multiple ways. By applying identified strategies and best practices, HIT can support patient-clinician interactions rather than interfering with them. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

A survey of the use of text messaging for communication with partners in the process of provider-led partner notification.

PubMed

Gilbart, Victoria Louise; Town, Katy; Lowndes, Catherine Mary

2015-03-01

Partner notification (PN) is important for sexually transmitted infection (STI) control. With developments in technology, such as text messaging, contacting partners is now easier. This study investigates the frequency and acceptability of text messaging in UK sexual health clinics for STI provider-led PN. A questionnaire was distributed to health advisers (HAs), cascaded by the Society of Sexual Health Advisers and posted on their website. 65 questionnaires were returned. Most HAs use telephone for the first and second provider-led PN attempt (61, 94% and 51, 78%, respectively) with text messaging as preferred second choice (19, 29% and 32, 49%, respectively). Overall, 56 clinics (86%) used text messaging at some stage, even if not the preferred option. 29 (52%) clinics had text messaging guidelines and 31 (55%) used messaging templates. Messages varied; 33 (59%) request partner make contact, 11 (20%) mention risk of infection, 9 (16%) name the infection and 20 (36%) use a combination of messages. Six (10%) had contact with their Caldicott Guardian about text messaging. No confidentiality concerns were reported and no complaints were reported from partners about receiving unsolicited text messages. Text messaging is widely used and is an important and acceptable tool for STI provider-led PN. It is the second preferred method for contacting partners after telephone for first and second provider-led PN attempts. A small number of clinics never use it. Message content varied; few named the infection. Concerns about confidentiality or negative impact for the partner were not reported. National guidance for the use of text messaging for provider-led PN is needed. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Text Messaging for Enhancement of Testing and Treatment for Tuberculosis, Human Immunodeficiency Virus, and Syphilis: A Survey of Attitudes Toward Cellular Phones and Healthcare

PubMed Central

Person, Anna K.; Blain, Michela L.M.; Jiang, Helen; Rasmussen, Petra W.

2011-01-01

Abstract Objectives: The objective of this study was to assess knowledge, attitudes, and behaviors surrounding healthcare-related mobile phone use and text messaging among persons at risk for or infected with tuberculosis (TB) or the human immunodeficiency virus (HIV). Methods: An anonymous survey was conducted in three groups of subjects: (1) HIV-infected persons attending an HIV clinic; (2) persons with latent TB infection at a public health clinic; and (3) persons presenting for TB, HIV, and syphilis screening at a community screening site. Results: Three hundred fifteen (n  = 315) persons responded to the survey, of whom 241 (76.5%) owned a cell phone. Cell phone owners were younger and more educated than nonowners. Transportation difficulty and forgetting appointments were cited as significant barriers by 34.2% and 39.5% of respondents, respectively. Fifty-six percent of subjects felt it would be acceptable to receive text message appointment reminders, and 33% felt that text message reminders to take medications would be acceptable. Younger age and cell phone ownership were significantly associated with acceptance of text message reminders. Black and Hispanic subjects were more likely to feel that text message reminders for appointments or medications were helpful than White subjects. Further, Black and Hispanic subjects, as well as subjects with lower educational attainment, were more receptive to healthcare-related educational text messages. Conclusions: Cell phones and text messaging were prevalent among our subjects attending HIV and TB clinics, and subjects were generally receptive to text messaging for healthcare-related communication. Interventions that explore the potential for text messaging to improve clinic attendance, medication adherence, and health knowledge should be explored. PMID:21457085

Automatic recognition of disorders, findings, pharmaceuticals and body structures from clinical text: an annotation and machine learning study.

PubMed

Skeppstedt, Maria; Kvist, Maria; Nilsson, Gunnar H; Dalianis, Hercules

2014-06-01

Automatic recognition of clinical entities in the narrative text of health records is useful for constructing applications for documentation of patient care, as well as for secondary usage in the form of medical knowledge extraction. There are a number of named entity recognition studies on English clinical text, but less work has been carried out on clinical text in other languages. This study was performed on Swedish health records, and focused on four entities that are highly relevant for constructing a patient overview and for medical hypothesis generation, namely the entities: Disorder, Finding, Pharmaceutical Drug and Body Structure. The study had two aims: to explore how well named entity recognition methods previously applied to English clinical text perform on similar texts written in Swedish; and to evaluate whether it is meaningful to divide the more general category Medical Problem, which has been used in a number of previous studies, into the two more granular entities, Disorder and Finding. Clinical notes from a Swedish internal medicine emergency unit were annotated for the four selected entity categories, and the inter-annotator agreement between two pairs of annotators was measured, resulting in an average F-score of 0.79 for Disorder, 0.66 for Finding, 0.90 for Pharmaceutical Drug and 0.80 for Body Structure. A subset of the developed corpus was thereafter used for finding suitable features for training a conditional random fields model. Finally, a new model was trained on this subset, using the best features and settings, and its ability to generalise to held-out data was evaluated. This final model obtained an F-score of 0.81 for Disorder, 0.69 for Finding, 0.88 for Pharmaceutical Drug, 0.85 for Body Structure and 0.78 for the combined category Disorder+Finding. The obtained results, which are in line with or slightly lower than those for similar studies on English clinical text, many of them conducted using a larger training data set, show that the approaches used for English are also suitable for Swedish clinical text. However, a small proportion of the errors made by the model are less likely to occur in English text, showing that results might be improved by further tailoring the system to clinical Swedish. The entity recognition results for the individual entities Disorder and Finding show that it is meaningful to separate the general category Medical Problem into these two more granular entity types, e.g. for knowledge mining of co-morbidity relations and disorder-finding relations. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Text-messaging versus telephone reminders to reduce missed appointments in an academic primary care clinic: a randomized controlled trial

PubMed Central

2013-01-01

Background Telephone or text-message reminders have been shown to significantly reduce the rate of missed appointments in different medical settings. Since text-messaging is less resource-demanding, we tested the hypothesis that text-message reminders would be as effective as telephone reminders in an academic primary care clinic. Methods A randomized controlled non-inferiority trial was conducted in the academic primary care division of the Geneva University Hospitals between November 2010 and April 2011. Patients registered for an appointment at the clinic, and for whom a cell phone number was available, were randomly selected to receive a text-message or a telephone call reminder 24 hours before the planned appointment. Patients were included each time they had an appointment. The main outcome was the rate of unexplained missed appointments. Appointments were not missed if they were cancelled or re-scheduled before or independently from the intervention. We defined non-inferiority as a difference below 2% in the rate of missed appointments and powered the study accordingly. A satisfaction survey was conducted among a random sample of 900 patients (response rate 41%). Results 6450 patients were included, 3285 in the text-message group and 3165 in the telephone group. The rate of missed appointments was similar in the text-message group (11.7%, 95% CI: 10.6-12.8) and in the telephone group (10.2%, 95% CI: 9.2-11.3 p = 0.07). However, only text message reminders were cost-effective. No patient reported any disturbance by any type of reminder in the satisfaction survey. Three quarters of surveyed patients recommended its regular implementation in the clinic. Conclusions Text-message reminders are equivalent to telephone reminders in reducing the proportion of missed appointments in an academic primary care clinic and are more cost-effective. Both types of reminders are well accepted by patients. PMID:23557331

Undergraduate nursing students' transformational learning during clinical training.

PubMed

Melin-Johansson, Christina; Österlind, Jane; Hagelin, Carina Lundh; Henoch, Ingela; Ek, Kristina; Bergh, Ingrid; Browall, Maria

2018-04-02

Undergraduate nursing students encounter patients at the end of life during their clinical training. They need to confront dying and death under supportive circumstances in order to be prepared for similar situations in their future career. To explore undergraduate nursing students' descriptions of caring situations with patients at the end of life during supervised clinical training. A qualitative study using the critical incident technique was chosen. A total of 85 students wrote a short text about their experiences of caring for patients at the end of life during their clinical training. These critical incident reports were then analysed using deductive and inductive content analysis. The theme 'students' transformational learning towards becoming a professional nurse during clinical training' summarises how students relate to patients and relatives, interpret the transition from life to death, feel when caring for a dead body and learn end-of-life caring actions from their supervisors. As a preparation for their future profession, students undergoing clinical training need to confront death and dying while supported by trained supervisors and must learn how to communicate about end-of-life issues and cope with emotional stress and grief.

Generation of silver standard concept annotations from biomedical texts with special relevance to phenotypes.

PubMed

Oellrich, Anika; Collier, Nigel; Smedley, Damian; Groza, Tudor

2015-01-01

Electronic health records and scientific articles possess differing linguistic characteristics that may impact the performance of natural language processing tools developed for one or the other. In this paper, we investigate the performance of four extant concept recognition tools: the clinical Text Analysis and Knowledge Extraction System (cTAKES), the National Center for Biomedical Ontology (NCBO) Annotator, the Biomedical Concept Annotation System (BeCAS) and MetaMap. Each of the four concept recognition systems is applied to four different corpora: the i2b2 corpus of clinical documents, a PubMed corpus of Medline abstracts, a clinical trails corpus and the ShARe/CLEF corpus. In addition, we assess the individual system performances with respect to one gold standard annotation set, available for the ShARe/CLEF corpus. Furthermore, we built a silver standard annotation set from the individual systems' output and assess the quality as well as the contribution of individual systems to the quality of the silver standard. Our results demonstrate that mainly the NCBO annotator and cTAKES contribute to the silver standard corpora (F1-measures in the range of 21% to 74%) and their quality (best F1-measure of 33%), independent from the type of text investigated. While BeCAS and MetaMap can contribute to the precision of silver standard annotations (precision of up to 42%), the F1-measure drops when combined with NCBO Annotator and cTAKES due to a low recall. In conclusion, the performances of individual systems need to be improved independently from the text types, and the leveraging strategies to best take advantage of individual systems' annotations need to be revised. The textual content of the PubMed corpus, accession numbers for the clinical trials corpus, and assigned annotations of the four concept recognition systems as well as the generated silver standard annotation sets are available from http://purl.org/phenotype/resources. The textual content of the ShARe/CLEF (https://sites.google.com/site/shareclefehealth/data) and i2b2 (https://i2b2.org/NLP/DataSets/) corpora needs to be requested with the individual corpus providers.

Intercultural Usage of Mori Folium: Comparison Review from a Korean Medical Perspective

PubMed Central

Joh, Byungjin; Jeon, Eun Sang; Lim, Su Hye; Park, Yu Lee; Park, Wansu

2015-01-01

Objectives. A review on studies related to the use of Mori folium, the leaves of Morus alba, was conducted with the goal of identifying new clinical applications in Korean medicine. Methods. Global literature search was conducted using three electronic databases up to January 2015 with the term Morus alba and its Korean terms. KM literatures including textbooks and standard pharmacopoeia were separately hand-searched and reviewed to provide comparison. Data were extracted according to predetermined criteria, and clinical uses were standardized with ICD-10 categories. Results. 159 potentially relevant studies were identified, and 18 articles including 12 ethnopharmacologic and 6 clinical studies were finally included in this analysis. Ethnopharmacologic studies from 8 countries provided 17 clinical uses. We found that five out of six clinical trials were related to diabetes and suggested a moderate short-term to mild long-term effect. And 43 Korean texts also provided 156 clinical uses in 35 categories including ocular and respiratory disorders. Discussion and Conclusions. Though majority of the clinical uses were also found in Korean medicine literature, treatment of infertility, jaundice, cognitive disorder, and hyperpigmentation was found to be effective and diabetes with Morus alba was recognized to have clinical importance. PMID:26539223

Input analysis for two public consultations on the EU Clinical Trials Regulation.

PubMed

Langhof, Holger; Lander, Jonas; Strech, Daniel

2016-09-17

The European Union's (EU) Clinical Trials Directive was replaced by an EU-Regulation as of 2016. The policy revision process was subject to a formal impact assessment exercised by the European Commission (EC) from 2008 to 2014. Following the EU principles of Good Governance, deliberation with stakeholders was an integral part of this impact assessment and the policy formulation process. Hence, two public consultations (PCs) were held by the EC in 2009 and 2011, respectively. Various stakeholders contributed and submitted their written input to the EC. Though often cited in the further revision process, the input gathered in the PC was not communicated with full transparency and it is unclear how and to what extent the input has been processed and used in the policy formulation. The objective of this study was an analysis of submissions to both PCs in order to systematically present what topics have been discussed and which possible policy options have been raised by the stakeholders. All written submissions publicly available were downloaded from the EC's homepage and assessed for stakeholder characteristics. Thematic text analysis was applied to assess the full text of a random sample of 33% of these submissions. A total of 198 different stakeholders from the EU and the United States of America contributed to one or both of the two PCs. In total, 44 various themes have been addressed that could be clustered under 24 main themes, including the articulation of problems as well as possible policy solutions to face these problems. The two PCs on the Clinical Trials Directive were highly appreciated by the various stakeholders and their input allowed an in-depth view on their particular interests. This input provided a rich source of information for all stakeholders in the field of clinical trials as well as to the EC's impact assessment. Although the EC obviously gathered a large quantity of expert knowledge on practical implications of trials legislation by consulting stakeholders, it remained unclear how this input was used in the development of the new regulation. For the sake of transparency, it is recommended that in future PCs the EC uses better standardized methods for a more transparent analysis and presentation of results.

Correlating mammographic and pathologic findings in clinical decision support using natural language processing and data mining methods.

PubMed

Patel, Tejal A; Puppala, Mamta; Ogunti, Richard O; Ensor, Joe E; He, Tiancheng; Shewale, Jitesh B; Ankerst, Donna P; Kaklamani, Virginia G; Rodriguez, Angel A; Wong, Stephen T C; Chang, Jenny C

2017-01-01

A key challenge to mining electronic health records for mammography research is the preponderance of unstructured narrative text, which strikingly limits usable output. The imaging characteristics of breast cancer subtypes have been described previously, but without standardization of parameters for data mining. The authors searched the enterprise-wide data warehouse at the Houston Methodist Hospital, the Methodist Environment for Translational Enhancement and Outcomes Research (METEOR), for patients with Breast Imaging Reporting and Data System (BI-RADS) category 5 mammogram readings performed between January 2006 and May 2015 and an available pathology report. The authors developed natural language processing (NLP) software algorithms to automatically extract mammographic and pathologic findings from free text mammogram and pathology reports. The correlation between mammographic imaging features and breast cancer subtype was analyzed using one-way analysis of variance and the Fisher exact test. The NLP algorithm was able to obtain key characteristics for 543 patients who met the inclusion criteria. Patients with estrogen receptor-positive tumors were more likely to have spiculated margins (P = .0008), and those with tumors that overexpressed human epidermal growth factor receptor 2 (HER2) were more likely to have heterogeneous and pleomorphic calcifications (P = .0078 and P = .0002, respectively). Mammographic imaging characteristics, obtained from an automated text search and the extraction of mammogram reports using NLP techniques, correlated with pathologic breast cancer subtype. The results of the current study validate previously reported trends assessed by manual data collection. Furthermore, NLP provides an automated means with which to scale up data extraction and analysis for clinical decision support. Cancer 2017;114-121. © 2016 American Cancer Society. © 2016 American Cancer Society.

Free software to analyse the clinical relevance of drug interactions with antiretroviral agents (SIMARV®) in patients with HIV/AIDS.

PubMed

Giraldo, N A; Amariles, P; Monsalve, M; Faus, M J

Highly active antiretroviral therapy has extended the expected lifespan of patients with HIV/AIDS. However, the therapeutic benefits of some drugs used simultaneously with highly active antiretroviral therapy may be adversely affected by drug interactions. The goal was to design and develop a free software to facilitate analysis, assessment, and clinical decision making according to the clinical relevance of drug interactions in patients with HIV/AIDS. A comprehensive Medline/PubMed database search of drug interactions was performed. Articles that recognized any drug interactions in HIV disease were selected. The publications accessed were limited to human studies in English or Spanish, with full texts retrieved. Drug interactions were analyzed, assessed, and grouped into four levels of clinical relevance according to gravity and probability. Software to systematize the information regarding drug interactions and their clinical relevance was designed and developed. Overall, 952 different references were retrieved and 446 selected; in addition, 67 articles were selected from the citation lists of identified articles. A total of 2119 pairs of drug interactions were identified; of this group, 2006 (94.7%) were drug-drug interactions, 1982 (93.5%) had an identified pharmacokinetic mechanism, and 1409 (66.5%) were mediated by enzyme inhibition. In terms of clinical relevance, 1285 (60.6%) drug interactions were clinically significant in patients with HIV (levels 1 and 2). With this information, a software program that facilitates identification and assessment of the clinical relevance of antiretroviral drug interactions (SIMARV ® ) was developed. A free software package with information on 2119 pairs of antiretroviral drug interactions was designed and developed that could facilitate analysis, assessment, and clinical decision making according to the clinical relevance of drug interactions in patients with HIV/AIDS. Copyright © 2016 Elsevier Inc. All rights reserved.

Integrating natural language processing expertise with patient safety event review committees to improve the analysis of medication events.

PubMed

Fong, Allan; Harriott, Nicole; Walters, Donna M; Foley, Hanan; Morrissey, Richard; Ratwani, Raj R

2017-08-01

Many healthcare providers have implemented patient safety event reporting systems to better understand and improve patient safety. Reviewing and analyzing these reports is often time consuming and resource intensive because of both the quantity of reports and length of free-text descriptions in the reports. Natural language processing (NLP) experts collaborated with clinical experts on a patient safety committee to assist in the identification and analysis of medication related patient safety events. Different NLP algorithmic approaches were developed to identify four types of medication related patient safety events and the models were compared. Well performing NLP models were generated to categorize medication related events into pharmacy delivery delays, dispensing errors, Pyxis discrepancies, and prescriber errors with receiver operating characteristic areas under the curve of 0.96, 0.87, 0.96, and 0.81 respectively. We also found that modeling the brief without the resolution text generally improved model performance. These models were integrated into a dashboard visualization to support the patient safety committee review process. We demonstrate the capabilities of various NLP models and the use of two text inclusion strategies at categorizing medication related patient safety events. The NLP models and visualization could be used to improve the efficiency of patient safety event data review and analysis. Copyright © 2017 Elsevier B.V. All rights reserved.

Text analysis methods, text analysis apparatuses, and articles of manufacture

DOEpatents

Whitney, Paul D; Willse, Alan R; Lopresti, Charles A; White, Amanda M

2014-10-28

Text analysis methods, text analysis apparatuses, and articles of manufacture are described according to some aspects. In one aspect, a text analysis method includes accessing information indicative of data content of a collection of text comprising a plurality of different topics, using a computing device, analyzing the information indicative of the data content, and using results of the analysis, identifying a presence of a new topic in the collection of text.

Comparing data accuracy between structured abstracts and full-text journal articles: implications in their use for informing clinical decisions.

PubMed

Fontelo, Paul; Gavino, Alex; Sarmiento, Raymond Francis

2013-12-01

The abstract is the most frequently read section of a research article. The use of 'Consensus Abstracts', a clinician-oriented web application formatted for mobile devices to search MEDLINE/PubMed, for informing clinical decisions was proposed recently; however, inaccuracies between abstracts and the full-text article have been shown. Efforts have been made to improve quality. We compared data in 60 recent-structured abstracts and full-text articles from six highly read medical journals. Data inaccuracies were identified and then classified as either clinically significant or not significant. Data inaccuracies were observed in 53.33% of articles ranging from 3.33% to 45% based on the IMRAD format sections. The Results section showed the highest discrepancies (45%) although these were deemed to be mostly not significant clinically except in one. The two most common discrepancies were mismatched numbers or percentages (11.67%) and numerical data or calculations found in structured abstracts but not mentioned in the full text (40%). There was no significant relationship between journals and the presence of discrepancies (Fisher's exact p value =0.3405). Although we found a high percentage of inaccuracy between structured abstracts and full-text articles, these were not significant clinically. The inaccuracies do not seem to affect the conclusion and interpretation overall. Structured abstracts appear to be informative and may be useful to practitioners as a resource for guiding clinical decisions.

Clinical evaluation of BrainTree, a motor imagery hybrid BCI speller

NASA Astrophysics Data System (ADS)

Perdikis, S.; Leeb, R.; Williamson, J.; Ramsay, A.; Tavella, M.; Desideri, L.; Hoogerwerf, E.-J.; Al-Khodairy, A.; Murray-Smith, R.; Millán, J. d. R.

2014-06-01

Objective. While brain-computer interfaces (BCIs) for communication have reached considerable technical maturity, there is still a great need for state-of-the-art evaluation by the end-users outside laboratory environments. To achieve this primary objective, it is necessary to augment a BCI with a series of components that allow end-users to type text effectively. Approach. This work presents the clinical evaluation of a motor imagery (MI) BCI text-speller, called BrainTree, by six severely disabled end-users and ten able-bodied users. Additionally, we define a generic model of code-based BCI applications, which serves as an analytical tool for evaluation and design. Main results. We show that all users achieved remarkable usability and efficiency outcomes in spelling. Furthermore, our model-based analysis highlights the added value of human-computer interaction techniques and hybrid BCI error-handling mechanisms, and reveals the effects of BCI performances on usability and efficiency in code-based applications. Significance. This study demonstrates the usability potential of code-based MI spellers, with BrainTree being the first to be evaluated by a substantial number of end-users, establishing them as a viable, competitive alternative to other popular BCI spellers. Another major outcome of our model-based analysis is the derivation of a 80% minimum command accuracy requirement for successful code-based application control, revising upwards previous estimates attempted in the literature.

Data mining of mental health issues of non-bone marrow donor siblings.

PubMed

Takita, Morihito; Tanaka, Yuji; Kodama, Yuko; Murashige, Naoko; Hatanaka, Nobuyo; Kishi, Yukiko; Matsumura, Tomoko; Ohsawa, Yukio; Kami, Masahiro

2011-07-20

Allogenic hematopoietic stem cell transplantation is a curative treatment for patients with advanced hematologic malignancies. However, the long-term mental health issues of siblings who were not selected as donors (non-donor siblings, NDS) in the transplantation have not been well assessed. Data mining is useful in discovering new findings from a large, multidisciplinary data set and the Scenario Map analysis is a novel approach which allows extracting keywords linking different conditions/events from text data of interviews even when the keywords appeared infrequently. The aim of this study is to assess mental health issues on NDSs and to find helpful keywords for the clinical follow-up using a Scenario Map analysis. A 47-year-old woman whose younger sister had undergone allogenic hematopoietic stem cell transplantation 20 years earlier was interviewed as a NDS. The text data from the interview transcriptions was analyzed using Scenario Mapping. Four clusters of words and six keywords were identified. Upon review of the word clusters and keywords, both the subject and researchers noticed that the subject has had mental health issues since the disease onset to date with being a NDS. The issues have been alleviated by her family. This single subject study suggested the advantages of data mining in clinical follow-up for mental health issues of patients and/or their families.

Clinical evaluation of BrainTree, a motor imagery hybrid BCI speller.

PubMed

Perdikis, S; Leeb, R; Williamson, J; Ramsay, A; Tavella, M; Desideri, L; Hoogerwerf, E-J; Al-Khodairy, A; Murray-Smith, R; Millán, J D R

2014-06-01

While brain-computer interfaces (BCIs) for communication have reached considerable technical maturity, there is still a great need for state-of-the-art evaluation by the end-users outside laboratory environments. To achieve this primary objective, it is necessary to augment a BCI with a series of components that allow end-users to type text effectively. This work presents the clinical evaluation of a motor imagery (MI) BCI text-speller, called BrainTree, by six severely disabled end-users and ten able-bodied users. Additionally, we define a generic model of code-based BCI applications, which serves as an analytical tool for evaluation and design. We show that all users achieved remarkable usability and efficiency outcomes in spelling. Furthermore, our model-based analysis highlights the added value of human-computer interaction techniques and hybrid BCI error-handling mechanisms, and reveals the effects of BCI performances on usability and efficiency in code-based applications. This study demonstrates the usability potential of code-based MI spellers, with BrainTree being the first to be evaluated by a substantial number of end-users, establishing them as a viable, competitive alternative to other popular BCI spellers. Another major outcome of our model-based analysis is the derivation of a 80% minimum command accuracy requirement for successful code-based application control, revising upwards previous estimates attempted in the literature.

Text analysis devices, articles of manufacture, and text analysis methods

DOEpatents

Turner, Alan E; Hetzler, Elizabeth G; Nakamura, Grant C

2013-05-28

Text analysis devices, articles of manufacture, and text analysis methods are described according to some aspects. In one aspect, a text analysis device includes processing circuitry configured to analyze initial text to generate a measurement basis usable in analysis of subsequent text, wherein the measurement basis comprises a plurality of measurement features from the initial text, a plurality of dimension anchors from the initial text and a plurality of associations of the measurement features with the dimension anchors, and wherein the processing circuitry is configured to access a viewpoint indicative of a perspective of interest of a user with respect to the analysis of the subsequent text, and wherein the processing circuitry is configured to use the viewpoint to generate the measurement basis.

Generation of Natural-Language Textual Summaries from Longitudinal Clinical Records.

PubMed

Goldstein, Ayelet; Shahar, Yuval

2015-01-01

Physicians are required to interpret, abstract and present in free-text large amounts of clinical data in their daily tasks. This is especially true for chronic-disease domains, but holds also in other clinical domains. We have recently developed a prototype system, CliniText, which, given a time-oriented clinical database, and appropriate formal abstraction and summarization knowledge, combines the computational mechanisms of knowledge-based temporal data abstraction, textual summarization, abduction, and natural-language generation techniques, to generate an intelligent textual summary of longitudinal clinical data. We demonstrate our methodology, and the feasibility of providing a free-text summary of longitudinal electronic patient records, by generating summaries in two very different domains - Diabetes Management and Cardiothoracic surgery. In particular, we explain the process of generating a discharge summary of a patient who had undergone a Coronary Artery Bypass Graft operation, and a brief summary of the treatment of a diabetes patient for five years.

Robotic surgery claims on United States hospital websites.

PubMed

Jin, Linda X; Ibrahim, Andrew M; Newman, Naeem A; Makarov, Danil V; Pronovost, Peter J; Makary, Martin A

2011-11-01

To examine the prevalence and content of robotic surgery information presented on websites of U.S. hospitals. We completed a systematic analysis of 400 randomly selected U.S. hospital websites in June of 2010. Data were collected on the presence and location of robotic surgery information on a hospital's website; use of images or text provided by the manufacturer; use of direct link to manufacturer website; statements of clinical superiority; statements of improved cancer outcome; mention of a comparison group for a statement; citation of supporting data and mention of specific risks. Forty-one percent of hospital websites described robotic surgery. Among these, 37% percent presented robotic surgery on their homepage, 73% used manufacturer-provided stock images or text, and 33% linked to a manufacturer website. Statements of clinical superiority were made on 86% of websites, with 32% describing improved cancer control, and 2% described a reference group. No hospital website mentioned risks. Materials provided by hospitals regarding the surgical robot overestimate benefits, largely ignore risks and are strongly influenced by the manufacturer. © 2011 National Association for Healthcare Quality.

Towards symbiosis in knowledge representation and natural language processing for structuring clinical practice guidelines.

PubMed

Weng, Chunhua; Payne, Philip R O; Velez, Mark; Johnson, Stephen B; Bakken, Suzanne

2014-01-01

The successful adoption by clinicians of evidence-based clinical practice guidelines (CPGs) contained in clinical information systems requires efficient translation of free-text guidelines into computable formats. Natural language processing (NLP) has the potential to improve the efficiency of such translation. However, it is laborious to develop NLP to structure free-text CPGs using existing formal knowledge representations (KR). In response to this challenge, this vision paper discusses the value and feasibility of supporting symbiosis in text-based knowledge acquisition (KA) and KR. We compare two ontologies: (1) an ontology manually created by domain experts for CPG eligibility criteria and (2) an upper-level ontology derived from a semantic pattern-based approach for automatic KA from CPG eligibility criteria text. Then we discuss the strengths and limitations of interweaving KA and NLP for KR purposes and important considerations for achieving the symbiosis of KR and NLP for structuring CPGs to achieve evidence-based clinical practice.

Design and Implementation of a Comprehensive Web-based Survey for Ovarian Cancer Survivorship with an Analysis of Prediagnosis Symptoms via Text Mining

PubMed Central

Sun, Jiayang; Bogie, Kath M; Teagno, Joe; Sun, Yu-Hsiang (Sam); Carter, Rebecca R; Cui, Licong; Zhang, Guo-Qiang

2014-01-01

Ovarian cancer (OvCa) is the most lethal gynecologic disease in the United States, with an overall 5-year survival rate of 44.5%, about half of the 89.2% for all breast cancer patients. To identify factors that possibly contribute to the long-term survivorship of women with OvCa, we conducted a comprehensive online Ovarian Cancer Survivorship Survey from 2009 to 2013. This paper presents the design and implementation of our survey, introduces its resulting data source, the OVA-CRADLE™ (Clinical Research Analytics and Data Lifecycle Environment), and illustrates a sample application of the survey and data by an analysis of prediagnosis symptoms, using text mining and statistics. The OVA-CRADLE™ is an application of our patented Physio-MIMI technology, facilitating Web-based access, online query and exploration of data. The prediagnostic symptoms and association of early-stage OvCa diagnosis with endometriosis provide potentially important indicators for future studies in this field. PMID:25861211

Coherence, disorganization, and fragmentation in traumatic memory reconsidered: A response to Rubin et al. (2016).

PubMed

Brewin, Chris R

2016-10-01

Although clinical theories of posttraumatic stress disorder (PTSD) claim that in this condition trauma memories tend to be disorganized and fragmented, this has been disputed by some autobiographical memory researchers, such as Rubin, Berntsen, and their colleagues (e.g., Rubin et al., 2016). In this article I review the evidence for and against the fragmentation hypothesis and identify important sources of methodological variability between the studies. This analysis suggests that fragmentation and disorganization are associated with differences in the type of narrative (specifically, with detailed rather than general narratives) and in the focus of the analysis (specifically, with a local focus on sections of text concerned with the worst moments of the trauma rather than with a global focus on the text as a whole). The implication is that apparently discrepant data and discrepant views can be accommodated within a more comprehensive formulation of memory impairment in PTSD. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

A Randomized Controlled Trial of a Text Messaging Intervention to Promote Virologic Suppression and Retention in Care in an Urban Safety-Net HIV Clinic: The Connect4Care (C4C) Trial.

PubMed

Christopoulos, Katerina A; Riley, Elise D; Carrico, Adam W; Tulsky, Jacqueline; Moskowitz, Judith T; Dilworth, Samantha; Coffin, Lara S; Wilson, Leslie; Peretz, Jason Johnson; Hilton, Joan F

2018-02-21

Text messaging is a promising strategy to support HIV care engagement, but little is known about its efficacy in urban safety-net HIV clinic populations. We conducted a randomized controlled trial of a supportive and motivational text messaging intervention, Connect4Care (C4C), among viremic patients who had a history of poor retention or were new to clinic. Participants were randomized (stratified by new HIV diagnosis status) to receive one of the following for 12 months: 1) thrice-weekly intervention messages, plus texted primary care appointment reminders and a monthly text message requesting confirmation of study participation, or; 2) texted reminders and monthly messages alone. Viral load was assessed at 6 and 12 months. The primary outcome was virologic suppression (<200 copies/mL) at 12 months, estimated via repeated measures log-binomial regression, adjusted for new diagnosis status. The secondary outcome was retention in clinic care. Between August 2013-November 2015, 230 participants were randomized. Virologic suppression at 12 months was similar between intervention and control participants (48.8% vs. 45.8%), with negligible change from 6-month estimates, yielding RR 1.07 (95% CI: 0.82, 1.39). Suppression was higher in the newly diagnosed (78.3% vs. 45.3%). There were no intervention effects on the secondary outcome. Exploratory analyses suggested that patients with more responses to study text messages had better outcomes, regardless of arm. The C4C text messaging intervention did not significantly increase virologic suppression or retention in care. Response to text messages may be a useful way for providers to gauge risk for poor HIV outcomes. NCT01917994.

Student perspectives on using egocentric video recorded by smart glasses to assess communicative and clinical skills with standardised patients.

PubMed

Zahl, D A; Schrader, S M; Edwards, P C

2018-05-01

This exploratory study evaluated student perceptions of their ability to self- and peer assess (i) interpersonal communication skills and (ii) clinical procedures (a head and neck examination) during standardised patient (SP) interactions recorded by Google Glass compared to a static camera. Students compared the Google Glass and static camera recordings using an instrument consisting of 20 Likert-type items and four open- and closed-text items. The Likert-type items asked students to rate how effectively they could assess specific aspects of interpersonal communication and a head and neck examination in these two different types of recordings. The interpersonal communication items included verbal, paraverbal and non-verbal subscales. The open- and closed-text items asked students to report on more globally the differences between the two types of recordings. Descriptive and inferential statistical analyses were conducted for all survey items. An inductive thematic analysis was conducted to determine qualitative emergent themes from the open-text questions. Students found the Glass videos more effective for assessing verbal (t 22 = 2.091, P = 0.048) and paraverbal communication skills (t 22 = 3.304, P = 0.003), whilst they reported that the static camera video was more effective for assessing non-verbal communication skills (t 22 = -2.132, P = 0.044). Four principle themes emerged from the students' open-text responses comparing Glass to static camera recordings for self- and peer assessment: (1) first-person perspective, (2) assessment of non-verbal communication, (3) audiovisual experience and (4) student operation of Glass. Our findings suggest that students perceive that Google Glass is a valuable tool for facilitating self- and peer assessment of SP examinations because of students' perceived ability to emphasise and illustrate communicative and clinical activities from a first-person perspective. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

A systematic review of near real-time and point-of-care clinical decision support in anesthesia information management systems.

PubMed

Simpao, Allan F; Tan, Jonathan M; Lingappan, Arul M; Gálvez, Jorge A; Morgan, Sherry E; Krall, Michael A

2017-10-01

Anesthesia information management systems (AIMS) are sophisticated hardware and software technology solutions that can provide electronic feedback to anesthesia providers. This feedback can be tailored to provide clinical decision support (CDS) to aid clinicians with patient care processes, documentation compliance, and resource utilization. We conducted a systematic review of peer-reviewed articles on near real-time and point-of-care CDS within AIMS using the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols. Studies were identified by searches of the electronic databases Medline and EMBASE. Two reviewers screened studies based on title, abstract, and full text. Studies that were similar in intervention and desired outcome were grouped into CDS categories. Three reviewers graded the evidence within each category. The final analysis included 25 articles on CDS as implemented within AIMS. CDS categories included perioperative antibiotic prophylaxis, post-operative nausea and vomiting prophylaxis, vital sign monitors and alarms, glucose management, blood pressure management, ventilator management, clinical documentation, and resource utilization. Of these categories, the reviewers graded perioperative antibiotic prophylaxis and clinical documentation as having strong evidence per the peer reviewed literature. There is strong evidence for the inclusion of near real-time and point-of-care CDS in AIMS to enhance compliance with perioperative antibiotic prophylaxis and clinical documentation. Additional research is needed in many other areas of AIMS-based CDS.

Factors Determining the Success and Failure of eHealth Interventions: Systematic Review of the Literature.

PubMed

Granja, Conceição; Janssen, Wouter; Johansen, Monika Alise

2018-05-01

eHealth has an enormous potential to improve healthcare cost, effectiveness, and quality of care. However, there seems to be a gap between the foreseen benefits of research and clinical reality. Our objective was to systematically review the factors influencing the outcome of eHealth interventions in terms of success and failure. We searched the PubMed database for original peer-reviewed studies on implemented eHealth tools that reported on the factors for the success or failure, or both, of the intervention. We conducted the systematic review by following the patient, intervention, comparison, and outcome framework, with 2 of the authors independently reviewing the abstract and full text of the articles. We collected data using standardized forms that reflected the categorization model used in the qualitative analysis of the outcomes reported in the included articles. Among the 903 identified articles, a total of 221 studies complied with the inclusion criteria. The studies were heterogeneous by country, type of eHealth intervention, method of implementation, and reporting perspectives. The article frequency analysis did not show a significant discrepancy between the number of reports on failure (392/844, 46.5%) and on success (452/844, 53.6%). The qualitative analysis identified 27 categories that represented the factors for success or failure of eHealth interventions. A quantitative analysis of the results revealed the category quality of healthcare (n=55) as the most mentioned as contributing to the success of eHealth interventions, and the category costs (n=42) as the most mentioned as contributing to failure. For the category with the highest unique article frequency, workflow (n=51), we conducted a full-text review. The analysis of the 23 articles that met the inclusion criteria identified 6 barriers related to workflow: workload (n=12), role definition (n=7), undermining of face-to-face communication (n=6), workflow disruption (n=6), alignment with clinical processes (n=2), and staff turnover (n=1). The reviewed literature suggested that, to increase the likelihood of success of eHealth interventions, future research must ensure a positive impact in the quality of care, with particular attention given to improved diagnosis, clinical management, and patient-centered care. There is a critical need to perform in-depth studies of the workflow(s) that the intervention will support and to perceive the clinical processes involved. ©Conceição Granja, Wouter Janssen, Monika Alise Johansen. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 01.05.2018.

Factors Determining the Success and Failure of eHealth Interventions: Systematic Review of the Literature

PubMed Central

Janssen, Wouter; Johansen, Monika Alise

2018-01-01

Background eHealth has an enormous potential to improve healthcare cost, effectiveness, and quality of care. However, there seems to be a gap between the foreseen benefits of research and clinical reality. Objective Our objective was to systematically review the factors influencing the outcome of eHealth interventions in terms of success and failure. Methods We searched the PubMed database for original peer-reviewed studies on implemented eHealth tools that reported on the factors for the success or failure, or both, of the intervention. We conducted the systematic review by following the patient, intervention, comparison, and outcome framework, with 2 of the authors independently reviewing the abstract and full text of the articles. We collected data using standardized forms that reflected the categorization model used in the qualitative analysis of the outcomes reported in the included articles. Results Among the 903 identified articles, a total of 221 studies complied with the inclusion criteria. The studies were heterogeneous by country, type of eHealth intervention, method of implementation, and reporting perspectives. The article frequency analysis did not show a significant discrepancy between the number of reports on failure (392/844, 46.5%) and on success (452/844, 53.6%). The qualitative analysis identified 27 categories that represented the factors for success or failure of eHealth interventions. A quantitative analysis of the results revealed the category quality of healthcare (n=55) as the most mentioned as contributing to the success of eHealth interventions, and the category costs (n=42) as the most mentioned as contributing to failure. For the category with the highest unique article frequency, workflow (n=51), we conducted a full-text review. The analysis of the 23 articles that met the inclusion criteria identified 6 barriers related to workflow: workload (n=12), role definition (n=7), undermining of face-to-face communication (n=6), workflow disruption (n=6), alignment with clinical processes (n=2), and staff turnover (n=1). Conclusions The reviewed literature suggested that, to increase the likelihood of success of eHealth interventions, future research must ensure a positive impact in the quality of care, with particular attention given to improved diagnosis, clinical management, and patient-centered care. There is a critical need to perform in-depth studies of the workflow(s) that the intervention will support and to perceive the clinical processes involved. PMID:29716883

Evaluating the effects of cognitive support on psychiatric clinical comprehension.

PubMed

Dalai, Venkata V; Khalid, Sana; Gottipati, Dinesh; Kannampallil, Thomas; John, Vineeth; Blatter, Brett; Patel, Vimla L; Cohen, Trevor

2014-10-01

Clinicians' attention is a precious resource, which in the current healthcare practice is consumed by the cognitive demands arising from complex patient conditions, information overload, time pressure, and the need to aggregate and synthesize information from disparate sources. The ability to organize information in ways that facilitate the generation of effective diagnostic solutions is a distinguishing characteristic of expert physicians, suggesting that automated systems that organize clinical information in a similar manner may augment physicians' decision-making capabilities. In this paper, we describe the design and evaluation of a theoretically driven cognitive support system (CSS) that assists psychiatrists in their interpretation of clinical cases. The system highlights, and provides the means to navigate to, text that is organized in accordance with a set of diagnostically and therapeutically meaningful higher-level concepts. To evaluate the interface, 16 psychiatry residents interpreted two clinical case scenarios, with and without the CSS. Think-aloud protocols captured during their interpretation of the cases were transcribed and analyzed qualitatively. In addition, the frequency and relative position of content related to key higher-level concepts in a verbal summary of the case were evaluated. In addition the transcripts from both groups were compared to an expert derived reference standard using latent semantic analysis (LSA). Qualitative analysis showed that users of the system better attended to specific clinically important aspects of both cases when these were highlighted by the system, and revealed ways in which the system mediates hypotheses generation and evaluation. Analysis of the summary data showed differences in emphasis with and without the system. The LSA analysis suggested users of the system were more "expert-like" in their emphasis, and that cognitive support was more effective in the more complex case. Cognitive support impacts upon clinical comprehension. This appears to be largely helpful, but may also lead to neglect of information (such as the psychosocial history) that the system does not highlight. The results have implications for the design of CSSs for clinical narratives including the role of information organization and textual embellishments for more efficient clinical case presentation and comprehension. Copyright © 2014 Elsevier B.V. All rights reserved.

Evaluating the effects of cognitive support on psychiatric clinical comprehension

PubMed Central

Dalai, Venkata V.; Khalid, Sana; Gottipati, Dinesh; Kannampallil, Thomas; John, Vineeth; Blatter, Brett; Patel, Vimla L.; Cohen, Trevor

2014-01-01

Objective Clinicians’ attention is a precious resource, which in the current healthcare practice is consumed by the cognitive demands arising from complex patient conditions, information overload, time pressure, and the need to aggregate and synthesize information from disparate sources. The ability to organize information in ways that facilitate the generation of effective diagnostic solutions is a distinguishing characteristic of expert physicians, suggesting that automated systems that organize clinical information in a similar manner may augment physicians’ decision-making capabilities. In this paper, we describe the design and evaluation of a theoretically driven cognitive support system (CSS) that assists psychiatrists in their interpretation of clinical cases. The system highlights, and provides the means to navigate to, text that is organized in accordance with a set of diagnostically and therapeutically meaningful higher-level concepts. Methods and Materials To evaluate the interface, 16 psychiatry residents interpreted two clinical case scenarios, with and without the CSS. Think-aloud protocols captured during their interpretation of the cases were transcribed and analyzed qualitatively. In addition, the frequency and relative position of content related to key higher-level concepts in a verbal summary of the case were evaluated. In addition the transcripts from both groups were compared to an expert derived reference standard using latent semantic analysis (LSA). Results Qualitative analysis showed that users of the system better attended to specific clinically important aspects of both cases when these were highlighted by the system, and revealed ways in which the system mediates hypotheses generation and evaluation. Analysis of the summary data showed differences in emphasis with and without the system. The LSA analysis suggested users of the system were more “expert-like” in their emphasis, and that cognitive support was more effective in the more complex case. Conclusions Cognitive support impacts upon clinical comprehension. This appears to be largely helpful, but may also lead to neglect of information (such as the psychosocial history) that the system does not highlight. The results have implications for the design of CSSs for clinical narratives including the role of information organization and textual embellishments for more efficient clinical case presentation and comprehension. PMID:25179216

Text messaging in health care: a systematic review of impact studies.

PubMed

Yeager, Valerie A; Menachemi, Nir

2011-01-01

Studies suggest text messaging is beneficial to health care; however, no one has synthesized the overall evidence on texting interventions. In response to this need, we conducted a systematic review of the impacts of text messaging in health care. PubMed database searches and subsequent reference list reviews sought English-language, peer-reviewed studies involving text messaging in health care. Commentaries, conference proceedings, and feasibilities studies were excluded. Data was extracted using an article coding sheet and input into a database for analysis. Of the 61 papers reviewed, 50 articles (82%) found text messaging had a positive effect on the primary outcome. Average sample sizes in articles reporting positive findings (n=813) were significantly larger than those that did not find a positive impact (n=178) on outcomes (p = 0.032). Articles were categorized into focal groups as follows: 27 articles (44.3%) investigated the impact of texting on disease management, 24 articles (39.3%) focused texting's impact to public health related outcomes, and 10 articles (16.4%) examined texting and its influence on administrative processes. Articles in focal groups differed by the purpose of the study, direction of the communication, and where they were published, but not in likelihood of reporting a positive impact from texting. Current evidence indicates that text messaging health care interventions are largely beneficial clinically, in public health related uses, and in terms of administrative processes. However, despite the promise of these findings, literature gaps exist, especially in primary care settings, across geographic regions and with vulnerable populations.

Over ten thousand cases and counting: acidbase.org is serving the critical care community.

PubMed

Elbers, Paul W G; Van Regenmortel, Niels; Gatz, Rainer

2015-01-01

Acidbase.org has been serving the critical care community for over a decade. The backbone of this online resource consists of Peter Stewart's original text "How to understand Acid-Base" which is freely available to everyone. In addition, Stewart's Textbook of Acid Base, which puts the theory in today's clinical context is available for purchase from the website. However, many intensivists use acidbase.org on a daily basis for its educational content and in particular for its analysis module. This review provides an overview of the history of the website, a tutorial and descriptive statistics of over 10,000 queries submitted to the analysis module.

Document Exploration and Automatic Knowledge Extraction for Unstructured Biomedical Text

NASA Astrophysics Data System (ADS)

Chu, S.; Totaro, G.; Doshi, N.; Thapar, S.; Mattmann, C. A.; Ramirez, P.

2015-12-01

We describe our work on building a web-browser based document reader with built-in exploration tool and automatic concept extraction of medical entities for biomedical text. Vast amounts of biomedical information are offered in unstructured text form through scientific publications and R&D reports. Utilizing text mining can help us to mine information and extract relevant knowledge from a plethora of biomedical text. The ability to employ such technologies to aid researchers in coping with information overload is greatly desirable. In recent years, there has been an increased interest in automatic biomedical concept extraction [1, 2] and intelligent PDF reader tools with the ability to search on content and find related articles [3]. Such reader tools are typically desktop applications and are limited to specific platforms. Our goal is to provide researchers with a simple tool to aid them in finding, reading, and exploring documents. Thus, we propose a web-based document explorer, which we called Shangri-Docs, which combines a document reader with automatic concept extraction and highlighting of relevant terms. Shangri-Docsalso provides the ability to evaluate a wide variety of document formats (e.g. PDF, Words, PPT, text, etc.) and to exploit the linked nature of the Web and personal content by performing searches on content from public sites (e.g. Wikipedia, PubMed) and private cataloged databases simultaneously. Shangri-Docsutilizes Apache cTAKES (clinical Text Analysis and Knowledge Extraction System) [4] and Unified Medical Language System (UMLS) to automatically identify and highlight terms and concepts, such as specific symptoms, diseases, drugs, and anatomical sites, mentioned in the text. cTAKES was originally designed specially to extract information from clinical medical records. Our investigation leads us to extend the automatic knowledge extraction process of cTAKES for biomedical research domain by improving the ontology guided information extraction process. We will describe our experience and implementation of our system and share lessons learned from our development. We will also discuss ways in which this could be adapted to other science fields. [1] Funk et al., 2014. [2] Kang et al., 2014. [3] Utopia Documents, http://utopiadocs.com [4] Apache cTAKES, http://ctakes.apache.org

Challenges and practical approaches with word sense disambiguation of acronyms and abbreviations in the clinical domain.

PubMed

Moon, Sungrim; McInnes, Bridget; Melton, Genevieve B

2015-01-01

Although acronyms and abbreviations in clinical text are used widely on a daily basis, relatively little research has focused upon word sense disambiguation (WSD) of acronyms and abbreviations in the healthcare domain. Since clinical notes have distinctive characteristics, it is unclear whether techniques effective for acronym and abbreviation WSD from biomedical literature are sufficient. The authors discuss feature selection for automated techniques and challenges with WSD of acronyms and abbreviations in the clinical domain. There are significant challenges associated with the informal nature of clinical text, such as typographical errors and incomplete sentences; difficulty with insufficient clinical resources, such as clinical sense inventories; and obstacles with privacy and security for conducting research with clinical text. Although we anticipated that using sophisticated techniques, such as biomedical terminologies, semantic types, part-of-speech, and language modeling, would be needed for feature selection with automated machine learning approaches, we found instead that simple techniques, such as bag-of-words, were quite effective in many cases. Factors, such as majority sense prevalence and the degree of separateness between sense meanings, were also important considerations. The first lesson is that a comprehensive understanding of the unique characteristics of clinical text is important for automatic acronym and abbreviation WSD. The second lesson learned is that investigators may find that using simple approaches is an effective starting point for these tasks. Finally, similar to other WSD tasks, an understanding of baseline majority sense rates and separateness between senses is important. Further studies and practical solutions are needed to better address these issues.

Effect of experience on clinical decision making by cardiorespiratory physiotherapists in acute care settings.

PubMed

Smith, Megan; Higgs, Joy; Ellis, Elizabeth

2010-02-01

This article investigates clinical decision making in acute care hospitals by cardiorespiratory physiotherapists with differing degrees of clinical experience. Participants were observed as they engaged in their everyday practice and were interviewed about their decision making. Texts of the data were interpreted by using a hermeneutic approach that involved repeated reading and analysis of fieldnotes and interview transcripts to develop an understanding of the effect of experience on clinical decision making. Participants were classified into categories of cardiorespiratory physiotherapy experience: less experienced (<2 years), intermediate experience (2.5-4 years), and more experienced (>7 years). Four dimensions characteristic of increasing experience in cardiorespiratory physiotherapy clinical decision making were identified: 1) an individual practice model, 2) refined approaches to clinical decision making, 3) working in context, and 4) social and emotional capability. Underpinning these dimensions was evidence of reflection on practice, motivation to achieve best practice, critique of new knowledge, increasing confidence, and relationships with knowledgeable colleagues. These findings reflect characteristics of physiotherapy expertise that have been described in the literature. This study adds knowledge about the field of cardiorespiratory physiotherapy to the existing body of research on clinical decision making and broadens the existing understanding of characteristics of physiotherapy expertise.

Alternatives to relational database: comparison of NoSQL and XML approaches for clinical data storage.

PubMed

Lee, Ken Ka-Yin; Tang, Wai-Choi; Choi, Kup-Sze

2013-04-01

Clinical data are dynamic in nature, often arranged hierarchically and stored as free text and numbers. Effective management of clinical data and the transformation of the data into structured format for data analysis are therefore challenging issues in electronic health records development. Despite the popularity of relational databases, the scalability of the NoSQL database model and the document-centric data structure of XML databases appear to be promising features for effective clinical data management. In this paper, three database approaches--NoSQL, XML-enabled and native XML--are investigated to evaluate their suitability for structured clinical data. The database query performance is reported, together with our experience in the databases development. The results show that NoSQL database is the best choice for query speed, whereas XML databases are advantageous in terms of scalability, flexibility and extensibility, which are essential to cope with the characteristics of clinical data. While NoSQL and XML technologies are relatively new compared to the conventional relational database, both of them demonstrate potential to become a key database technology for clinical data management as the technology further advances. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Pre-pregnancy counselling for women with chronic kidney disease: a retrospective analysis of nine years' experience.

PubMed

Wiles, Kate S; Bramham, Kate; Vais, Alina; Harding, Kate R; Chowdhury, Paramit; Taylor, Cath J; Nelson-Piercy, Catherine

2015-03-14

Women with chronic kidney disease have an increased risk of maternal and fetal complications in pregnancy. Pre-pregnancy counselling is recommended but the format of the counselling process and the experience of the patient have never been assessed. This study examines the experience of women with chronic kidney disease attending pre-pregnancy counselling and evaluates their pregnancy outcomes. This is a cross-sectional assessment of 179 women with chronic kidney disease attending a pre-pregnancy counselling clinic (2003-2011) with retrospective evaluation of aetiology, comorbidity, treatment and adverse pregnancy outcome compared with 277 hospital controls. It includes an analysis of descriptive data and free text content from 72 questionnaire responders. 65/72 (90%) of women found the clinic informative. 66 women (92%) felt that the consultation had helped them decide about pursuing pregnancy. 12 women (17%) found the multidisciplinary process intimidating. Free text comments supported the positive nature of the counselling experience, but also highlighted issues of access and emotional impact. Adverse pregnancy outcome rates were significantly higher in women with chronic kidney disease: 7/35 (20%) had pre-eclampsia (p < 0.001), 8/35 (23%) infants were small for gestational age (p < 0.001), 11/35 (31%) had preterm deliveries (<37 weeks) (p < 0.001) and 5/35 (14%) had a pregnancy loss compared with 4%, 10%, 8% and 3% of controls respectively. Women with a diverse range of renal disease severity and complexity attend pre-pregnancy counselling. Factors affecting pregnancy include hypertension, proteinuria and teratogenic medication. It is important to be able to inform women of the risks to them and their babies before pregnancy in order to facilitate informed-decision making. Most women with chronic kidney disease attending a pre-pregnancy counselling clinic report a positive experience.

What factors facilitate good learning experiences in clinical studies in nursing: bachelor students' perceptions.

PubMed

Dale, Bjørg; Leland, Arne; Dale, Jan Gunnar

2013-12-17

Clinical studies constitute 50% of the bachelor program in nursing education in Norway, and the quality of these studies may be decisive for the students' opportunities to learn and develop their professional competences. The aim of this study was to explore what bachelor students' in nursing perceived to be important for having good learning experiences in clinical studies. Data was collected in a focus group interview with eight nursing students who were in the last year of the educational program. The interview was transcribed verbatim, and qualitative content analysis was used for exploring and interpreting the content of the interview text. One main theme emerged from the analysis: "being in a vulnerable and exposed position characterized by conflicting needs." Four categories were found: "aspects related to the clinical setting", "aspects related to the nurse supervisor," "aspects related to the student," and "aspects related to the student-supervisor relationship". The findings revealed that the students' learning experiences and motivation were related to individual, relational, and organizational aspects. The students highlighted their own as well as their supervisors' attitudes and competences and the importance of positive relationships. In addition, feeling welcomed, included, and valued in the ward improved their motivation, self-confidence, and self-respect.

[Critical reading aptitude of clinical research texts in teaching specialist doctors].

PubMed

Carranza Lira, Sebastián; Varela, Alejandro

2007-11-01

Learning can be divided in two types: the unconscious learning and the significant learning. The critical aptitude for reading clinical research articles is a learning experience that reflects the doctor's active participation in article reading. To know the degree of aptitude for critical reading of clinical research articles in specialists under training. To all the specialist that were under training in the different services of the Hospital, a previous validated evaluation instrument for critical reading of clinical research studies was applied. Kruskal-Wallis and Mann-Whitney's U test were used for statistical analysis. After the application of the evaluation instrument, it was found that the global score had a median of 42.5 (12-89) points. In the results obtained by indicator it was found that there was a greater score for to interpret, than for to judge and for to propose. In the analysis of domain degrees according to the interpret indicator, the greater proportion was in low level. According to the indicators to judge and to propose, most of the results were in the by chance expected level. The critical reading aptitude it's not developed in specialized physicians that are under training. The development of this aptitude will allow them to have a greater profit in their courses.

CUILESS2016: a clinical corpus applying compositional normalization of text mentions.

PubMed

Osborne, John D; Neu, Matthew B; Danila, Maria I; Solorio, Thamar; Bethard, Steven J

2018-01-10

Traditionally text mention normalization corpora have normalized concepts to single ontology identifiers ("pre-coordinated concepts"). Less frequently, normalization corpora have used concepts with multiple identifiers ("post-coordinated concepts") but the additional identifiers have been restricted to a defined set of relationships to the core concept. This approach limits the ability of the normalization process to express semantic meaning. We generated a freely available corpus using post-coordinated concepts without a defined set of relationships that we term "compositional concepts" to evaluate their use in clinical text. We annotated 5397 disorder mentions from the ShARe corpus to SNOMED CT that were previously normalized as "CUI-less" in the "SemEval-2015 Task 14" shared task because they lacked a pre-coordinated mapping. Unlike the previous normalization method, we do not restrict concept mappings to a particular set of the Unified Medical Language System (UMLS) semantic types and allow normalization to occur to multiple UMLS Concept Unique Identifiers (CUIs). We computed annotator agreement and assessed semantic coverage with this method. We generated the largest clinical text normalization corpus to date with mappings to multiple identifiers and made it freely available. All but 8 of the 5397 disorder mentions were normalized using this methodology. Annotator agreement ranged from 52.4% using the strictest metric (exact matching) to 78.2% using a hierarchical agreement that measures the overlap of shared ancestral nodes. Our results provide evidence that compositional concepts can increase semantic coverage in clinical text. To our knowledge we provide the first freely available corpus of compositional concept annotation in clinical text.

[The method and application to construct experience recommendation platform of acupuncture ancient books based on data mining technology].

PubMed

Chen, Chuyun; Hong, Jiaming; Zhou, Weilin; Lin, Guohua; Wang, Zhengfei; Zhang, Qufei; Lu, Cuina; Lu, Lihong

2017-07-12

To construct a knowledge platform of acupuncture ancient books based on data mining technology, and to provide retrieval service for users. The Oracle 10 g database was applied and JAVA was selected as development language; based on the standard library and ancient books database established by manual entry, a variety of data mining technologies, including word segmentation, speech tagging, dependency analysis, rule extraction, similarity calculation, ambiguity analysis, supervised classification technology were applied to achieve text automatic extraction of ancient books; in the last, through association mining and decision analysis, the comprehensive and intelligent analysis of disease and symptom, meridians, acupoints, rules of acupuncture and moxibustion in acupuncture ancient books were realized, and retrieval service was provided for users through structure of browser/server (B/S). The platform realized full-text retrieval, word frequency analysis and association analysis; when diseases or acupoints were searched, the frequencies of meridian, acupoints (diseases) and techniques were presented from high to low, meanwhile the support degree and confidence coefficient between disease and acupoints (special acupoint), acupoints and acupoints in prescription, disease or acupoints and technique were presented. The experience platform of acupuncture ancient books based on data mining technology could be used as a reference for selection of disease, meridian and acupoint in clinical treatment and education of acupuncture and moxibustion.

Automated Outcome Classification of Computed Tomography Imaging Reports for Pediatric Traumatic Brain Injury.

PubMed

Yadav, Kabir; Sarioglu, Efsun; Choi, Hyeong Ah; Cartwright, Walter B; Hinds, Pamela S; Chamberlain, James M

2016-02-01

The authors have previously demonstrated highly reliable automated classification of free-text computed tomography (CT) imaging reports using a hybrid system that pairs linguistic (natural language processing) and statistical (machine learning) techniques. Previously performed for identifying the outcome of orbital fracture in unprocessed radiology reports from a clinical data repository, the performance has not been replicated for more complex outcomes. To validate automated outcome classification performance of a hybrid natural language processing (NLP) and machine learning system for brain CT imaging reports. The hypothesis was that our system has performance characteristics for identifying pediatric traumatic brain injury (TBI). This was a secondary analysis of a subset of 2,121 CT reports from the Pediatric Emergency Care Applied Research Network (PECARN) TBI study. For that project, radiologists dictated CT reports as free text, which were then deidentified and scanned as PDF documents. Trained data abstractors manually coded each report for TBI outcome. Text was extracted from the PDF files using optical character recognition. The data set was randomly split evenly for training and testing. Training patient reports were used as input to the Medical Language Extraction and Encoding (MedLEE) NLP tool to create structured output containing standardized medical terms and modifiers for negation, certainty, and temporal status. A random subset stratified by site was analyzed using descriptive quantitative content analysis to confirm identification of TBI findings based on the National Institute of Neurological Disorders and Stroke (NINDS) Common Data Elements project. Findings were coded for presence or absence, weighted by frequency of mentions, and past/future/indication modifiers were filtered. After combining with the manual reference standard, a decision tree classifier was created using data mining tools WEKA 3.7.5 and Salford Predictive Miner 7.0. Performance of the decision tree classifier was evaluated on the test patient reports. The prevalence of TBI in the sampled population was 159 of 2,217 (7.2%). The automated classification for pediatric TBI is comparable to our prior results, with the notable exception of lower positive predictive value. Manual review of misclassified reports, 95.5% of which were false-positives, revealed that a sizable number of false-positive errors were due to differing outcome definitions between NINDS TBI findings and PECARN clinical important TBI findings and report ambiguity not meeting definition criteria. A hybrid NLP and machine learning automated classification system continues to show promise in coding free-text electronic clinical data. For complex outcomes, it can reliably identify negative reports, but manual review of positive reports may be required. As such, it can still streamline data collection for clinical research and performance improvement. © 2016 by the Society for Academic Emergency Medicine.

Automated Outcome Classification of Computed Tomography Imaging Reports for Pediatric Traumatic Brain Injury

PubMed Central

Yadav, Kabir; Sarioglu, Efsun; Choi, Hyeong-Ah; Cartwright, Walter B.; Hinds, Pamela S.; Chamberlain, James M.

2016-01-01

Background The authors have previously demonstrated highly reliable automated classification of free text computed tomography (CT) imaging reports using a hybrid system that pairs linguistic (natural language processing) and statistical (machine learning) techniques. Previously performed for identifying the outcome of orbital fracture in unprocessed radiology reports from a clinical data repository, the performance has not been replicated for more complex outcomes. Objectives To validate automated outcome classification performance of a hybrid natural language processing (NLP) and machine learning system for brain CT imaging reports. The hypothesis was that our system has performance characteristics for identifying pediatric traumatic brain injury (TBI). Methods This was a secondary analysis of a subset of 2,121 CT reports from the Pediatric Emergency Care Applied Research Network (PECARN) TBI study. For that project, radiologists dictated CT reports as free text, which were then de-identified and scanned as PDF documents. Trained data abstractors manually coded each report for TBI outcome. Text was extracted from the PDF files using optical character recognition. The dataset was randomly split evenly for training and testing. Training patient reports were used as input to the Medical Language Extraction and Encoding (MedLEE) NLP tool to create structured output containing standardized medical terms and modifiers for negation, certainty, and temporal status. A random subset stratified by site was analyzed using descriptive quantitative content analysis to confirm identification of TBI findings based upon the National Institute of Neurological Disorders and Stroke Common Data Elements project. Findings were coded for presence or absence, weighted by frequency of mentions, and past/future/indication modifiers were filtered. After combining with the manual reference standard, a decision tree classifier was created using data mining tools WEKA 3.7.5 and Salford Predictive Miner 7.0. Performance of the decision tree classifier was evaluated on the test patient reports. Results The prevalence of TBI in the sampled population was 159 out of 2,217 (7.2%). The automated classification for pediatric TBI is comparable to our prior results, with the notable exception of lower positive predictive value (PPV). Manual review of misclassified reports, 95.5% of which were false positives, revealed that a sizable number of false-positive errors were due to differing outcome definitions between NINDS TBI findings and PECARN clinical important TBI findings, and report ambiguity not meeting definition criteria. Conclusions A hybrid NLP and machine learning automated classification system continues to show promise in coding free-text electronic clinical data. For complex outcomes, it can reliably identify negative reports, but manual review of positive reports may be required. As such, it can still streamline data collection for clinical research and performance improvement. PMID:26766600

A Mobile Health Strategy to Support Adherence to Antiretroviral Preexposure Prophylaxis.

PubMed

Fuchs, Jonathan D; Stojanovski, Kristefer; Vittinghoff, Eric; McMahan, Vanessa M; Hosek, Sybill G; Amico, K Rivet; Kouyate, Aminta; Gilmore, Hailey J; Buchbinder, Susan P; Lester, Richard T; Grant, Robert M; Liu, Albert Y

2018-03-01

Preexposure prophylaxis is a highly protective HIV prevention strategy, yet nonadherence can significantly reduce its effectiveness. We conducted a mixed methods evaluation of a mobile health intervention (iText) that utilized weekly bidirectional text or e-mail support messages to encourage preexposure prophylaxis (PrEP) adherence among participants in the multi-site iPrEx open-label extension study. A convenience sample of PrEP users from the San Francisco and Chicago sites participated in a 12-week pilot study. Fifty-six men who have sex with men were enrolled; a quarter of them were less than 30 years of age, 13% were black/African American, 11% were Latino, and most (88%) completed some college. Two-thirds opted for text message delivery. Of the 667 messages sent, only 1 individual requested support; initial nonresponse was observed in 22% and was higher among e-mail compared to text message recipients. Poststudy, a majority of participants would recommend the intervention to others, especially during PrEP initiation. Moreover, younger participants and men of color were more likely to report that they would use the iText strategy if it were available to them. Several participants commented that while they were aware that the messages were automated, they felt supported and encouraged that "someone was always there." Study staff reported that the intervention is feasible to administer and can be incorporated readily into clinic flow. A pre-post intervention regression discontinuity analysis using clinic-based pill counts showed a 50% reduction in missed doses [95% confidence interval (CI) 16-71; p = 0.008] and 77% (95% CI 33-92; p = 0.007) when comparing pill counts at quarterly visits just before and after iText enrollment. A mobile health intervention using weekly bidirectional messaging was highly acceptable and demonstrated promising effects on PrEP adherence warranting further evaluation for efficacy in a randomized controlled trial.

Correlates of Healthy Lifestyle Beliefs and Behaviors in Parents of Overweight or Obese Preschool Children Before and After a Cognitive Behavioral Therapy Intervention With Text Messaging.

PubMed

Militello, Lisa K; Melnyk, Bernadette Mazurek; Hekler, Eric; Small, Leigh; Jacobson, Diana

2016-01-01

Significant gaps exist in the published literature regarding the treatment of overweight/obesity in preschool-aged children, especially in primary care settings. Parental influence plays an important factor in the development of healthy behaviors in children, yet there is no consensus about why some behavior change intervention strategies for parents of young children are more influential and effective than others. The purpose of this secondary data analysis was to assess correlations among the study variables (healthy lifestyle beliefs, perceived difficulty, and healthy lifestyle behaviors) in parents of overweight/obese preschool children. A second aim explored if the parent's level of cognitive beliefs and perceived difficulty of engaging in healthy lifestyle behaviors correlated with text messaging cognitive behavioral support. Fifteen preschool-parent dyads from primary care clinics completed a 7-week cognitive behavioral skills building intervention. Beck's Cognitive Theory guided the intervention content, and Fogg's Behavior Model guided the implementation. The intervention was delivered using a combination of face-to-face clinic visits and ecological momentary interventions using text messaging. Supported are the interconnected relationships among the study variables, that is, parental healthy lifestyle beliefs, thoughts, and behaviors. At baseline, parental healthy lifestyle belief scores significantly correlated with perceived difficulty (rs = 0.598, p < .05) and healthy lifestyle behaviors (rs = 0.545, p < .05). These associations strengthened after the intervention. Furthermore, as parental healthy lifestyle beliefs increased and perceived difficulty lessened, their response rate and subsequent feedback lessened to the static text messaging support. Findings from this study support the interconnections between parents' thoughts, feelings, and actions toward healthy lifestyles. As parental beliefs became stronger through cognitive behavioral skills building and tailored text messaging, the need for general support via text messaging lessened, warranting additional research. Published by Elsevier Inc.

What should we teach the teachers? Identifying the learning priorities of clinical supervisors.

PubMed

Bearman, Margaret; Tai, Joanna; Kent, Fiona; Edouard, Vicki; Nestel, Debra; Molloy, Elizabeth

2018-03-01

Clinicians who teach are essential for the health workforce but require faculty development to improve their educational skills. Curricula for faculty development programs are often based on expert frameworks without consideration of the learning priorities as defined by clinical supervisors themselves. We sought to inform these curricula by highlighting clinical supervisors own requirements through answering the research question: what do clinical supervisors identify as relative strengths and areas for improvement in their teaching practice? This mixed methods study employed a modified version of the Maastricht Clinical Teaching Questionnaire (mMCTQ) which included free-text reflections. Descriptive statistics were calculated and content analysis was conducted on textual comments. 481 (49%) of 978 clinical supervisors submitted their mMCTQs and associated reflections for the research study. Clinical supervisors self-identified relatively strong capability with interpersonal skills or attributes and indicated least capability with assisting learners to explore strengths, weaknesses and learning goals. The qualitative category 'establishing relationships' was the most reported strength with 224 responses. The qualitative category 'feedback' was the most reported area for improvement, with 151 responses. Key areas for curricular focus include: improving feedback practices; stimulating reflective and agentic learning; and managing the logistics of a clinical education environment. Clinical supervisors' self-identified needs provide a foundation for designing engaging and relevant faculty development programs.

Perceptions of HIV infected patients on the use of cell phone as a tool to support their antiretroviral adherence; a cross-sectional study in a large referral hospital in Kenya.

PubMed

Kinyua, Florence; Kiptoo, Michael; Kikuvi, Gideon; Mutai, Joseph; Meyers, Adrienne F A; Muiruri, Peter; Songok, Elijah

2013-10-21

Clinical trials were conducted to assess the feasibility of using a cell phone text messaging-based system to follow up Human Immunodeficiency Virus (HIV) infected patients on antiretroviral (ARTs) and assess for improved adherence to their medication. However there is need to evaluate the perceptions of the HIV infected patients towards the use of these cell phones in an effort to better aid in the clinical management of their HIV infection. The objective of this study was therefore to determine the perceptions of HIV infected patients on the use of cell phone text messaging as a tool to support adherence to their ART medication. A cross sectional survey was conducted among patients receiving Highly Active Anti-Retroviral Therapy (HAART) at the Kenyatta National Hospital Comprehensive Care Clinic in Nairobi between May and July, 2011. Pre-tested questionnaires were used to collect the socio-demographic and perceptions data. The recruitment of the participants was done using the random probability sampling method and statistical analysis of data performed using Statistical Package for Social Sciences (SPSS) version 16.0. A total of 500 HIV infected patients (Male-107, Female-307) aged 19-72 years were interviewed. The majority of individuals (99%) had access to cell phones and 99% of the HIV infected patients interviewed supported the idea of cell phone use in management of their HIV infection. A large proportion (46%) claimed that they needed cell phone access for medical advice and guidance on factors that hinder their adherence to medication and only 3% of them needed it as a reminder to take their drugs. The majority (72%) preferred calling the healthcare provider with their own phones for convenience and confidential purposes with only 0.4% preferring to be called or texted by the health care provider. Most (94%), especially the older patients, had no problem with their confidentiality being infringed in the process of the conversation as per the bivariate analysis results. Cell phone communications are acceptable and in fact preferable over cell phone reminders.

Perceptions of HIV infected patients on the use of cell phone as a tool to support their antiretroviral adherence; a cross-sectional study in a large referral hospital in Kenya

PubMed Central

2013-01-01

Background Clinical trials were conducted to assess the feasibility of using a cell phone text messaging-based system to follow up Human Immunodeficiency Virus (HIV) infected patients on antiretroviral (ARTs) and assess for improved adherence to their medication. However there is need to evaluate the perceptions of the HIV infected patients towards the use of these cell phones in an effort to better aid in the clinical management of their HIV infection. The objective of this study was therefore to determine the perceptions of HIV infected patients on the use of cell phone text messaging as a tool to support adherence to their ART medication. Methods A cross sectional survey was conducted among patients receiving Highly Active Anti-Retroviral Therapy (HAART) at the Kenyatta National Hospital Comprehensive Care Clinic in Nairobi between May and July, 2011. Pre-tested questionnaires were used to collect the socio-demographic and perceptions data. The recruitment of the participants was done using the random probability sampling method and statistical analysis of data performed using Statistical Package for Social Sciences (SPSS) version 16.0. Results A total of 500 HIV infected patients (Male-107, Female-307) aged 19-72 years were interviewed. The majority of individuals (99%) had access to cell phones and 99% of the HIV infected patients interviewed supported the idea of cell phone use in management of their HIV infection. A large proportion (46%) claimed that they needed cell phone access for medical advice and guidance on factors that hinder their adherence to medication and only 3% of them needed it as a reminder to take their drugs. The majority (72%) preferred calling the healthcare provider with their own phones for convenience and confidential purposes with only 0.4% preferring to be called or texted by the health care provider. Most (94%), especially the older patients, had no problem with their confidentiality being infringed in the process of the conversation as per the bivariate analysis results. Conclusion Cell phone communications are acceptable and in fact preferable over cell phone reminders. PMID:24143931

Bayesian survival analysis in clinical trials: What methods are used in practice?

PubMed

Brard, Caroline; Le Teuff, Gwénaël; Le Deley, Marie-Cécile; Hampson, Lisa V

2017-02-01

Background Bayesian statistics are an appealing alternative to the traditional frequentist approach to designing, analysing, and reporting of clinical trials, especially in rare diseases. Time-to-event endpoints are widely used in many medical fields. There are additional complexities to designing Bayesian survival trials which arise from the need to specify a model for the survival distribution. The objective of this article was to critically review the use and reporting of Bayesian methods in survival trials. Methods A systematic review of clinical trials using Bayesian survival analyses was performed through PubMed and Web of Science databases. This was complemented by a full text search of the online repositories of pre-selected journals. Cost-effectiveness, dose-finding studies, meta-analyses, and methodological papers using clinical trials were excluded. Results In total, 28 articles met the inclusion criteria, 25 were original reports of clinical trials and 3 were re-analyses of a clinical trial. Most trials were in oncology (n = 25), were randomised controlled (n = 21) phase III trials (n = 13), and half considered a rare disease (n = 13). Bayesian approaches were used for monitoring in 14 trials and for the final analysis only in 14 trials. In the latter case, Bayesian survival analyses were used for the primary analysis in four cases, for the secondary analysis in seven cases, and for the trial re-analysis in three cases. Overall, 12 articles reported fitting Bayesian regression models (semi-parametric, n = 3; parametric, n = 9). Prior distributions were often incompletely reported: 20 articles did not define the prior distribution used for the parameter of interest. Over half of the trials used only non-informative priors for monitoring and the final analysis (n = 12) when it was specified. Indeed, no articles fitting Bayesian regression models placed informative priors on the parameter of interest. The prior for the treatment effect was based on historical data in only four trials. Decision rules were pre-defined in eight cases when trials used Bayesian monitoring, and in only one case when trials adopted a Bayesian approach to the final analysis. Conclusion Few trials implemented a Bayesian survival analysis and few incorporated external data into priors. There is scope to improve the quality of reporting of Bayesian methods in survival trials. Extension of the Consolidated Standards of Reporting Trials statement for reporting Bayesian clinical trials is recommended.

Convolution-based estimation of organ dose in tube current modulated CT

NASA Astrophysics Data System (ADS)

Tian, Xiaoyu; Segars, W. Paul; Dixon, Robert L.; Samei, Ehsan

2016-05-01

Estimating organ dose for clinical patients requires accurate modeling of the patient anatomy and the dose field of the CT exam. The modeling of patient anatomy can be achieved using a library of representative computational phantoms (Samei et al 2014 Pediatr. Radiol. 44 460-7). The modeling of the dose field can be challenging for CT exams performed with a tube current modulation (TCM) technique. The purpose of this work was to effectively model the dose field for TCM exams using a convolution-based method. A framework was further proposed for prospective and retrospective organ dose estimation in clinical practice. The study included 60 adult patients (age range: 18-70 years, weight range: 60-180 kg). Patient-specific computational phantoms were generated based on patient CT image datasets. A previously validated Monte Carlo simulation program was used to model a clinical CT scanner (SOMATOM Definition Flash, Siemens Healthcare, Forchheim, Germany). A practical strategy was developed to achieve real-time organ dose estimation for a given clinical patient. CTDIvol-normalized organ dose coefficients ({{h}\\text{Organ}} ) under constant tube current were estimated and modeled as a function of patient size. Each clinical patient in the library was optimally matched to another computational phantom to obtain a representation of organ location/distribution. The patient organ distribution was convolved with a dose distribution profile to generate {{≤ft(\\text{CTD}{{\\text{I}}\\text{vol}}\\right)}\\text{organ, \\text{convolution}}} values that quantified the regional dose field for each organ. The organ dose was estimated by multiplying {{≤ft(\\text{CTD}{{\\text{I}}\\text{vol}}\\right)}\\text{organ, \\text{convolution}}} with the organ dose coefficients ({{h}\\text{Organ}} ). To validate the accuracy of this dose estimation technique, the organ dose of the original clinical patient was estimated using Monte Carlo program with TCM profiles explicitly modeled. The discrepancy between the estimated organ dose and dose simulated using TCM Monte Carlo program was quantified. We further compared the convolution-based organ dose estimation method with two other strategies with different approaches of quantifying the irradiation field. The proposed convolution-based estimation method showed good accuracy with the organ dose simulated using the TCM Monte Carlo simulation. The average percentage error (normalized by CTDIvol) was generally within 10% across all organs and modulation profiles, except for organs located in the pelvic and shoulder regions. This study developed an improved method that accurately quantifies the irradiation field under TCM scans. The results suggested that organ dose could be estimated in real-time both prospectively (with the localizer information only) and retrospectively (with acquired CT data).

Semi-Spontaneous Oral Text Production: Measurements in Clinical Practice

ERIC Educational Resources Information Center

Lind, Marianne; Kristoffersen, Kristian Emil; Moen, Inger; Simonsen, Hanne Gram

2009-01-01

Functionally relevant assessment of the language production of speakers with aphasia should include assessment of connected speech production. Despite the ecological validity of everyday conversations, more controlled and monological types of texts may be easier to obtain and analyse in clinical practice. This article discusses some simple…

An Ontology-Enabled Natural Language Processing Pipeline for Provenance Metadata Extraction from Biomedical Text (Short Paper).

PubMed

Valdez, Joshua; Rueschman, Michael; Kim, Matthew; Redline, Susan; Sahoo, Satya S

2016-10-01

Extraction of structured information from biomedical literature is a complex and challenging problem due to the complexity of biomedical domain and lack of appropriate natural language processing (NLP) techniques. High quality domain ontologies model both data and metadata information at a fine level of granularity, which can be effectively used to accurately extract structured information from biomedical text. Extraction of provenance metadata, which describes the history or source of information, from published articles is an important task to support scientific reproducibility. Reproducibility of results reported by previous research studies is a foundational component of scientific advancement. This is highlighted by the recent initiative by the US National Institutes of Health called "Principles of Rigor and Reproducibility". In this paper, we describe an effective approach to extract provenance metadata from published biomedical research literature using an ontology-enabled NLP platform as part of the Provenance for Clinical and Healthcare Research (ProvCaRe). The ProvCaRe-NLP tool extends the clinical Text Analysis and Knowledge Extraction System (cTAKES) platform using both provenance and biomedical domain ontologies. We demonstrate the effectiveness of ProvCaRe-NLP tool using a corpus of 20 peer-reviewed publications. The results of our evaluation demonstrate that the ProvCaRe-NLP tool has significantly higher recall in extracting provenance metadata as compared to existing NLP pipelines such as MetaMap.

Objective cardiovascular assessment in the neonatal intensive care unit.

PubMed

Dempsey, Eugene M; El-Khuffash, Afif Faisal

2018-01-01

Traditionally, cardiovascular well-being was essentially based on whether the mean blood pressure was above or below a certain value. However, this singular crude method of assessment provides limited insight into overall cardiovascular well-being. Echocardiography has become increasingly used and incorporated into clinical care. New objective modality assessments of cardiovascular status continue to evolve and are being evaluated and incorporated into clinical care. In this review article, we will discuss some of the recent advances in objective assessment of cardiovascular well-being, including the concept of multimodal monitoring. Sophisticated haemodynamic monitoring systems are being developed, including mechanisms of data acquisition and analysis. Their incorporation into clinical care represents an exciting next stage in the management of the infant with cardiovascular compromise. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Patient Electronic Health Records as a Means to Approach Genetic Research in Gastroenterology

PubMed Central

Ananthakrishnan, Ashwin N; Lieberman, David

2015-01-01

Electronic health records (EHR) are being increasingly utilized and form a unique source of extensive data gathered during routine clinical care. Through use of codified and free text concepts identified using clinical informatics tools, disease labels can be assigned with a high degree of accuracy. Analysis linking such EHR-assigned disease labels to a biospecimen repository has demonstrated that genetic associations identified in prospective cohorts can be replicated with adequate statistical power, and novel phenotypic associations identified. In addition, genetic discovery research can be performed utilizing clinical, laboratory, and procedure data obtained during care. Challenges with such research include the need to tackle variability in quality and quantity of EHR data and importance of maintaining patient privacy and data security. With appropriate safeguards, this novel and emerging field of research offers considerable promise and potential to further scientific research in gastroenterology efficiently, cost-effectively, and with engagement of patients and communities. PMID:26073373

HER2 testing of gastro-oesophageal adenocarcinoma: a commentary and guidance document from the Association of Clinical Pathologists Molecular Pathology and Diagnostics Committee.

PubMed

Wong, Newton A C S; Amary, Fernanda; Butler, Rachel; Byers, Richard; Gonzalez, David; Haynes, Harry R; Ilyas, Mohammad; Salto-Tellez, Manuel; Taniere, Philippe

2018-05-01

The use of biologics targeted to the human epidermal growth factor receptor 2 (HER2) protein is the latest addition to the armamentarium used to fight advanced gastric or gastro-oesophageal junction adenocarcinoma. The decision to treat with the biologic trastuzumab is completely dependent on HER2 testing of tumour tissue. In 2017, the College of American Pathologists, American Society for Clinical Pathology and the American Society of Clinical Oncology jointly published guidelines for HER2 testing and clinical decision making in gastro-oesophageal adenocarcinoma. The Association of Clinical Pathologists Molecular Pathology and Diagnostics Committee has issued the following document as a commentary of these guidelines and, in parallel, to provide guidance on HER2 testing in National Health Service pathology departments within the UK. This guidance covers issues related to case selection, preanalytical aspects, analysis and interpretation of such HER2 testing. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Automated detection of follow-up appointments using text mining of discharge records.

PubMed

Ruud, Kari L; Johnson, Matthew G; Liesinger, Juliette T; Grafft, Carrie A; Naessens, James M

2010-06-01

To determine whether text mining can accurately detect specific follow-up appointment criteria in free-text hospital discharge records. Cross-sectional study. Mayo Clinic Rochester hospitals. Inpatients discharged from general medicine services in 2006 (n = 6481). Textual hospital dismissal summaries were manually reviewed to determine whether the records contained specific follow-up appointment arrangement elements: date, time and either physician or location for an appointment. The data set was evaluated for the same criteria using SAS Text Miner software. The two assessments were compared to determine the accuracy of text mining for detecting records containing follow-up appointment arrangements. Agreement of text-mined appointment findings with gold standard (manual abstraction) including sensitivity, specificity, positive predictive and negative predictive values (PPV and NPV). About 55.2% (3576) of discharge records contained all criteria for follow-up appointment arrangements according to the manual review, 3.2% (113) of which were missed through text mining. Text mining incorrectly identified 3.7% (107) follow-up appointments that were not considered valid through manual review. Therefore, the text mining analysis concurred with the manual review in 96.6% of the appointment findings. Overall sensitivity and specificity were 96.8 and 96.3%, respectively; and PPV and NPV were 97.0 and 96.1%, respectively. of individual appointment criteria resulted in accuracy rates of 93.5% for date, 97.4% for time, 97.5% for physician and 82.9% for location. Text mining of unstructured hospital dismissal summaries can accurately detect documentation of follow-up appointment arrangement elements, thus saving considerable resources for performance assessment and quality-related research.

The growth and evolution of cardiovascular magnetic resonance: a 20-year history of the Society for Cardiovascular Magnetic Resonance (SCMR) annual scientific sessions.

PubMed

Lee, Daniel C; Markl, Michael; Dall'Armellina, Erica; Han, Yuchi; Kozerke, Sebastian; Kuehne, Titus; Nielles-Vallespin, Sonia; Messroghli, Daniel; Patel, Amit; Schaeffter, Tobias; Simonetti, Orlando; Valente, Anne Marie; Weinsaft, Jonathan W; Wright, Graham; Zimmerman, Stefan; Schulz-Menger, Jeanette

2018-01-31

The purpose of this work is to summarize cardiovascular magnetic resonance (CMR) research trends and highlights presented at the annual Society for Cardiovascular Magnetic Resonance (SCMR) scientific sessions over the past 20 years. Scientific programs from all SCMR Annual Scientific Sessions from 1998 to 2017 were obtained. SCMR Headquarters also provided data for the number and the country of origin of attendees and the number of accepted abstracts according to type. Data analysis included text analysis (key word extraction) and visualization by 'word clouds' representing the most frequently used words in session titles for 5-year intervals. In addition, session titles were sorted into 17 major subject categories to further evaluate research and clinical CMR trends over time. Analysis of SCMR annual scientific sessions locations, attendance, and number of accepted abstracts demonstrated substantial growth of CMR research and clinical applications. As an international field of study, significant growth of CMR was documented by a strong increase in SCMR scientific session attendance (> 500%, 270 to 1406 from 1998 to 2017, number of accepted abstracts (> 700%, 98 to 701 from 1998 to 2018) and number of international participants (42-415% increase for participants from Asia, Central and South America, Middle East and Africa in 2004-2017). 'Word clouds' based evaluation of research trends illustrated a shift from early focus on 'MRI technique feasibility' to new established techniques (e.g. late gadolinium enhancement) and their clinical applications and translation (key words 'patient', 'disease') and more recently novel techniques and quantitative CMR imaging (key words 'mapping', 'T1', 'flow', 'function'). Nearly every topic category demonstrated an increase in the number of sessions over the 20-year period with 'Clinical Practice' leading all categories. Our analysis identified three growth areas 'Congenital', 'Clinical Practice', and 'Structure/function/flow'. The analysis of the SCMR historical archives demonstrates a healthy and internationally active field of study which continues to undergo substantial growth and expansion into new and emerging CMR topics and clinical application areas.

The mother in the text: metapsychology and phantasy in the work of interpretation.

PubMed

Petrella, Fausto

2008-06-01

In this paper the author discusses some characteristics of a psychoanalytic text on the basis of two pages of Freud's essay, Delusions and dreams in Jensen's 'Gradiva' (Freud, 1906), on the concept of the return of the repressed. Analysis of the text shows that the four references (Horace, Rops, Rousseau, and a clinical vignette) occurring in it present unexpected connections both with each other and with the phenomenon they illustrate. There thus emerges a hidden scenario that reveals a concealed level of the text, relating to the maternal imago. Particular attention is devoted to the importance of the figurative apparatus and images (examples in the form of narrations and visual images, metaphors, and similes) that accompany the metapsychological and conceptual construction of Freud's text. Representation in visual form is necessary for the description and construction of the psyche and for conferring life on its conceptual formulations. However, metapsychological definition also reveals a phantasy dimension underlying the text. In addition, the author shows how certain textual constraints limit the intrinsic intuitive and arbitrary nature of interpretation. Finally, the complexity of the psychoanalytic text (with its various planes and levels) is emphasized, as well as the network of possible connections fundamental to the work of interpretation. A diagram illustrates the spatio-temporal aspects of the interpretive process, as defined by the interaction between conceptual factors and specific flights of the imagination which also have to do with unconscious affects, whether in the text, the author, or the reader.

Texting Teens in Transition: The Use of Text Messages in Clinical Intervention Research

PubMed Central

Nicholas, David B

2014-01-01

Background The rapidly growing population of young adults living with congenital heart disease (CHD), currently challenging ill-prepared cardiac care systems, presents a novel population in which to consider the use of mHealth. This methodological study was part of a larger study that tested the effectiveness of a clinic-based nursing intervention to prepare teens for transfer from pediatric to adult cardiology care. The intervention included creation of a MyHealth Passport and subsequently SMS (short message service) text messages between the intervention nurse and study participant. Objective Our aim was to determine (1) the preference of teens with CHD to be contacted via text message following the nursing intervention, (2) the effectiveness of texting to collect data regarding the use of MyHealth Passport after participation in the intervention, (3) the nature of the texting interaction, and (4) the risks and benefits of texting. Methods Participants were recruited through the intervention study (n=24) by either choosing to receive information from the study coordinator through text message, or texting a question to the study nurses. Inclusion criteria were age 15-17 years, diagnosed with moderate or complex heart disease, and currently being followed by the Division of Cardiology at Stollery Children’s Hospital. Exclusion criteria were heart transplantation and/or less than a 6th grade reading and comprehension ability. Text message transcripts were analyzed by qualitative inductive content analysis. Results Two-thirds of teens (16/24, 67%) chose text messaging as their preferred contact, making them eligible for the study. Texting was effective in collecting information regarding the MyHealth Passport; all but one teen had their MyHealth Passport on them, and many reported carrying it with them wherever they went. All teens reported showing their MyHealth Passport to at least one person. Seven themes were identified in the texting transcripts: mixing formal and informal language, the passive teen, interaction with health care providers, texting teens in transition, texting as a mechanism to initiate other forms of communication, affirmation, and the nurse as an educator. Benefits of texting were identified as flexibility, ability to respond over time, information presented in byte-sized amounts, and information directly related to patient questions. Risks of texting were identified as the possibility that interactions may not be in-depth, distraction of teen and researcher, and invasiveness. Conclusions Text messaging was useful in collecting data regarding the use of the MyHealth Passport. Text messaging resulted in conversations with the teens that were sometimes in-depth and meaningful, especially when combined with other communication modalities. Using text messaging in a manner resulting in full conversations with the patients requires more study and may benefit from protocols and the use of solid theoretical foundations that would standardize the interaction so that more conclusions could be drawn. PMID:25379624

Texting teens in transition: the use of text messages in clinical intervention research.

PubMed

Rempel, Gwen R; Ballantyne, Ross T; Magill-Evans, Joyce; Nicholas, David B; Mackie, Andrew S

2014-11-06

The rapidly growing population of young adults living with congenital heart disease (CHD), currently challenging ill-prepared cardiac care systems, presents a novel population in which to consider the use of mHealth. This methodological study was part of a larger study that tested the effectiveness of a clinic-based nursing intervention to prepare teens for transfer from pediatric to adult cardiology care. The intervention included creation of a MyHealth Passport and subsequently SMS (short message service) text messages between the intervention nurse and study participant. Our aim was to determine (1) the preference of teens with CHD to be contacted via text message following the nursing intervention, (2) the effectiveness of texting to collect data regarding the use of MyHealth Passport after participation in the intervention, (3) the nature of the texting interaction, and (4) the risks and benefits of texting. Participants were recruited through the intervention study (n=24) by either choosing to receive information from the study coordinator through text message, or texting a question to the study nurses. Inclusion criteria were age 15-17 years, diagnosed with moderate or complex heart disease, and currently being followed by the Division of Cardiology at Stollery Children's Hospital. Exclusion criteria were heart transplantation and/or less than a 6th grade reading and comprehension ability. Text message transcripts were analyzed by qualitative inductive content analysis. Two-thirds of teens (16/24, 67%) chose text messaging as their preferred contact, making them eligible for the study. Texting was effective in collecting information regarding the MyHealth Passport; all but one teen had their MyHealth Passport on them, and many reported carrying it with them wherever they went. All teens reported showing their MyHealth Passport to at least one person. Seven themes were identified in the texting transcripts: mixing formal and informal language, the passive teen, interaction with health care providers, texting teens in transition, texting as a mechanism to initiate other forms of communication, affirmation, and the nurse as an educator. Benefits of texting were identified as flexibility, ability to respond over time, information presented in byte-sized amounts, and information directly related to patient questions. Risks of texting were identified as the possibility that interactions may not be in-depth, distraction of teen and researcher, and invasiveness. Text messaging was useful in collecting data regarding the use of the MyHealth Passport. Text messaging resulted in conversations with the teens that were sometimes in-depth and meaningful, especially when combined with other communication modalities. Using text messaging in a manner resulting in full conversations with the patients requires more study and may benefit from protocols and the use of solid theoretical foundations that would standardize the interaction so that more conclusions could be drawn.

Speech pathologists' experience of involving people with stroke-induced aphasia in clinical decision making during rehabilitation.

PubMed

Berg, Karianne; Rise, Marit By; Balandin, Susan; Armstrong, Elizabeth; Askim, Torunn

2016-01-01

Although client participation has been part of legislation and clinical guidelines for several years, the evidence of these recommendations being implemented into clinical practice is scarce, especially for people with communication disorders. The aim of this study was to investigate how speech pathologists experienced client participation during the process of goal-setting and clinical decision making for people with aphasia. Twenty speech pathologists participated in four focus group interviews. A qualitative analysis using Systematic Text Condensation was undertaken. Analysis revealed three different approaches to client participation: (1) client-oriented, (2) next of kin-oriented and (3) professional-oriented participation. Participants perceived client-oriented participation as the gold standard. The three approaches were described as overlapping, with each having individual characteristics incorporating different facilitators and barriers. There is a need for greater emphasis on how to involve people with severe aphasia in goal setting and treatment planning, and frameworks made to enhance collaboration could preferably be used. Participants reported use of next of kin as proxies in goal-setting and clinical decision making for people with moderate-to-severe aphasia, indicating the need for awareness towards maintaining the clients' autonomy and addressing the goals of next of kin. Speech pathologists, and most likely other professionals, should place greater emphasis on client participation to ensure active involvement of people with severe aphasia. To achieve this, existing tools and techniques made to enhance collaborative goal setting and clinical decision making have to be better incorporated into clinical rehabilitation practice. To ensure the autonomy of the person with aphasia, as well as to respect next of kin's own goals, professionals need to make ethical considerations when next of kin are used as proxies in collaborative goal setting and clinical decision making.

Does recruitment source moderate treatment effectiveness? A subgroup analysis from the EVIDENT study, a randomised controlled trial of an internet intervention for depressive symptoms.

PubMed

Klein, Jan Philipp; Gamon, Carla; Späth, Christina; Berger, Thomas; Meyer, Björn; Hohagen, Fritz; Hautzinger, Martin; Lutz, Wolfgang; Vettorazzi, Eik; Moritz, Steffen; Schröder, Johanna

2017-07-13

This study aims to examine whether the effects of internet interventions for depression generalise to participants recruited in clinical settings. This study uses subgroup analysis of the results of a randomised, controlled, single-blind trial. The study takes place in five diagnostic centres in Germany. A total of 1013 people with mild to moderate depressive symptoms were recruited from clinical sources as well as internet forums, statutory insurance companies and other sources. This study uses either care-as-usual alone (control) or a 12-week internet intervention (Deprexis) plus usual care (intervention). The primary outcome measure was self-rated depression severity (Patient Health Questionnaire-9) at 3 months and 6 months. Further measures ranged from demographic and clinical parameters to a measure of attitudes towards internet interventions (Attitudes towards Psychological Online Interventions Questionnaire). The recruitment source was only associated with very few of the examined demographic and clinical characteristics. Compared with participants recruited from clinical sources, participants recruited through insurance companies were more likely to be employed. Clinically recruited participants were as severely affected as those from other recruitment sources but more sceptical of internet interventions. The effectiveness of the intervention was not differentially associated with recruitment source (treatment by recruitment source interaction=0.28, p=0.84). Our results support the hypothesis that the intervention we studied is effective across different recruitment sources including clinical settings. ClinicalTrials.gov NCT01636752. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Challenges in clinical natural language processing for automated disorder normalization.

PubMed

Leaman, Robert; Khare, Ritu; Lu, Zhiyong

2015-10-01

Identifying key variables such as disorders within the clinical narratives in electronic health records has wide-ranging applications within clinical practice and biomedical research. Previous research has demonstrated reduced performance of disorder named entity recognition (NER) and normalization (or grounding) in clinical narratives than in biomedical publications. In this work, we aim to identify the cause for this performance difference and introduce general solutions. We use closure properties to compare the richness of the vocabulary in clinical narrative text to biomedical publications. We approach both disorder NER and normalization using machine learning methodologies. Our NER methodology is based on linear-chain conditional random fields with a rich feature approach, and we introduce several improvements to enhance the lexical knowledge of the NER system. Our normalization method - never previously applied to clinical data - uses pairwise learning to rank to automatically learn term variation directly from the training data. We find that while the size of the overall vocabulary is similar between clinical narrative and biomedical publications, clinical narrative uses a richer terminology to describe disorders than publications. We apply our system, DNorm-C, to locate disorder mentions and in the clinical narratives from the recent ShARe/CLEF eHealth Task. For NER (strict span-only), our system achieves precision=0.797, recall=0.713, f-score=0.753. For the normalization task (strict span+concept) it achieves precision=0.712, recall=0.637, f-score=0.672. The improvements described in this article increase the NER f-score by 0.039 and the normalization f-score by 0.036. We also describe a high recall version of the NER, which increases the normalization recall to as high as 0.744, albeit with reduced precision. We perform an error analysis, demonstrating that NER errors outnumber normalization errors by more than 4-to-1. Abbreviations and acronyms are found to be frequent causes of error, in addition to the mentions the annotators were not able to identify within the scope of the controlled vocabulary. Disorder mentions in text from clinical narratives use a rich vocabulary that results in high term variation, which we believe to be one of the primary causes of reduced performance in clinical narrative. We show that pairwise learning to rank offers high performance in this context, and introduce several lexical enhancements - generalizable to other clinical NER tasks - that improve the ability of the NER system to handle this variation. DNorm-C is a high performing, open source system for disorders in clinical text, and a promising step toward NER and normalization methods that are trainable to a wide variety of domains and entities. (DNorm-C is open source software, and is available with a trained model at the DNorm demonstration website: http://www.ncbi.nlm.nih.gov/CBBresearch/Lu/Demo/tmTools/#DNorm.). Published by Elsevier Inc.

Status of knowledge on student-learning environments in nursing homes: A mixed-method systematic review.

PubMed

Husebø, Anne Marie Lunde; Storm, Marianne; Våga, Bodil Bø; Rosenberg, Adriana; Akerjordet, Kristin

2018-04-01

To give an overview of empirical studies investigating nursing homes as a learning environment during nursing students' clinical practice. A supportive clinical learning environment is crucial to students' learning and for their development into reflective and capable practitioners. Nursing students' experience with clinical practice can be decisive in future workplace choices. A competent workforce is needed for the future care of older people. Opportunities for maximum learning among nursing students during clinical practice studies in nursing homes should therefore be explored. Mixed-method systematic review using PRISMA guidelines, on learning environments in nursing homes, published in English between 2005-2015. Search of CINAHL with Full Text, Academic Search Premier, MEDLINE and SocINDEX with Full Text, in combination with journal hand searches. Three hundred and thirty-six titles were identified. Twenty studies met the review inclusion criteria. Assessment of methodological quality was based on the Mixed Methods Appraisal Tool. Data were extracted and synthesised using a data analysis method for integrative reviews. Twenty articles were included. The majority of the studies showed moderately high methodological quality. Four main themes emerged from data synthesis: "Student characteristic and earlier experience"; "Nursing home ward environment"; "Quality of mentoring relationship and learning methods"; and "Students' achieved nursing competencies." Nursing home learning environments may be optimised by a well-prepared academic-clinical partnership, supervision by encouraging mentors and high-quality nursing care of older people. Positive learning experiences may increase students' professional development through achievement of basic nursing skills and competencies and motivate them to choose the nursing home as their future workplace. An optimal learning environment can be ensured by thorough preplacement preparations in academia and in nursing home wards, continuous supervision and facilitation of team learning. © 2018 John Wiley & Sons Ltd.

Video- or text-based e-learning when teaching clinical procedures? A randomized controlled trial.

PubMed

Buch, Steen Vigh; Treschow, Frederik Philip; Svendsen, Jesper Brink; Worm, Bjarne Skjødt

2014-01-01

This study investigated the effectiveness of two different levels of e-learning when teaching clinical skills to medical students. Sixty medical students were included and randomized into two comparable groups. The groups were given either a video- or text/picture-based e-learning module and subsequently underwent both theoretical and practical examination. A follow-up test was performed 1 month later. The students in the video group performed better than the illustrated text-based group in the practical examination, both in the primary test (P<0.001) and in the follow-up test (P<0.01). Regarding theoretical knowledge, no differences were found between the groups on the primary test, though the video group performed better on the follow-up test (P=0.04). Video-based e-learning is superior to illustrated text-based e-learning when teaching certain practical clinical skills.

Video- or text-based e-learning when teaching clinical procedures? A randomized controlled trial

PubMed Central

Buch, Steen Vigh; Treschow, Frederik Philip; Svendsen, Jesper Brink; Worm, Bjarne Skjødt

2014-01-01

Background and aims This study investigated the effectiveness of two different levels of e-learning when teaching clinical skills to medical students. Materials and methods Sixty medical students were included and randomized into two comparable groups. The groups were given either a video- or text/picture-based e-learning module and subsequently underwent both theoretical and practical examination. A follow-up test was performed 1 month later. Results The students in the video group performed better than the illustrated text-based group in the practical examination, both in the primary test (P<0.001) and in the follow-up test (P<0.01). Regarding theoretical knowledge, no differences were found between the groups on the primary test, though the video group performed better on the follow-up test (P=0.04). Conclusion Video-based e-learning is superior to illustrated text-based e-learning when teaching certain practical clinical skills. PMID:25152638

Repurposing the clinical record: can an existing natural language processing system de-identify clinical notes?

PubMed

Morrison, Frances P; Li, Li; Lai, Albert M; Hripcsak, George

2009-01-01

Electronic clinical documentation can be useful for activities such as public health surveillance, quality improvement, and research, but existing methods of de-identification may not provide sufficient protection of patient data. The general-purpose natural language processor MedLEE retains medical concepts while excluding the remaining text so, in addition to processing text into structured data, it may be able provide a secondary benefit of de-identification. Without modifying the system, the authors tested the ability of MedLEE to remove protected health information (PHI) by comparing 100 outpatient clinical notes with the corresponding XML-tagged output. Of 809 instances of PHI, 26 (3.2%) were detected in output as a result of processing and identification errors. However, PHI in the output was highly transformed, much appearing as normalized terms for medical concepts, potentially making re-identification more difficult. The MedLEE processor may be a good enhancement to other de-identification systems, both removing PHI and providing coded data from clinical text.

A preliminary approach to creating an overview of lactoferrin multi-functionality utilizing a text mining method.

PubMed

Shimazaki, Kei-ichi; Kushida, Tatsuya

2010-06-01

Lactoferrin is a multi-functional metal-binding glycoprotein that exhibits many biological functions of interest to many researchers from the fields of clinical medicine, dentistry, pharmacology, veterinary medicine, nutrition and milk science. To date, a number of academic reports concerning the biological activities of lactoferrin have been published and are easily accessible through public data repositories. However, as the literature is expanding daily, this presents challenges in understanding the larger picture of lactoferrin function and mechanisms. In order to overcome the "analysis paralysis" associated with lactoferrin information, we attempted to apply a text mining method to the accumulated lactoferrin literature. To this end, we used the information extraction system GENPAC (provided by Nalapro Technologies Inc., Tokyo). This information extraction system uses natural language processing and text mining technology. This system analyzes the sentences and titles from abstracts stored in the PubMed database, and can automatically extract binary relations that consist of interactions between genes/proteins, chemicals and diseases/functions. We expect that such information visualization analysis will be useful in determining novel relationships among a multitude of lactoferrin functions and mechanisms. We have demonstrated the utilization of this method to find pathways of lactoferrin participation in neovascularization, Helicobacter pylori attack on gastric mucosa, atopic dermatitis and lipid metabolism.

Comparing the characteristics of users of an online service for STI self-sampling with clinic service users: a cross-sectional analysis.

PubMed

Barnard, Sharmani; Free, Caroline; Bakolis, Ioannis; Turner, Katy M E; Looker, Katharine J; Baraitser, Paula

2018-02-07

Online services for self-sampling at home could improve access to STI testing; however, little is known about those using this new modality of care. This study describes the characteristics of users of online services and compares them with users of clinic services. We conducted a cross-sectional analysis of routinely collected data on STI testing activity from online and clinic sexual health services in Lambeth and Southwark between 1January 2016 and 31March 2016. Activity was included for chlamydia, gonorrhoea, HIV and syphilis testing for residents of the boroughs aged 16 years and older. Logistic regression models were used to explore potential associations between type of service use with age group, gender, ethnic group, sexual orientation, positivity and Index of Multiple Deprivation (IMD) quintiles. We used the same methods to explore potential associations between return of complete samples for testing with age group, gender, ethnic group, sexual orientation and IMD quintiles among online users. 6456 STI tests were carried out by residents in the boroughs. Of these, 3582 (55.5%) were performed using clinic services and 2874 (44.5%) using the online service. In multivariate analysis, online users were more likely than clinic users to be aged between 20 and 30 years, female, white British, homosexual or bisexual, test negative for chlamydia or gonorrhoea and live in less deprived areas. Of the individuals that ordered a kit from the online service, 72.5% returned sufficient samples. In multivariate analysis, returners were more likely than non-returners to be aged >20 years and white British. Nearly half (44.5%) of all basic STI testing was done online, although the characteristics of users of clinic and online services differed and positivity rates for those using the online service for testing were lower. Clinics remain an important point of access for some groups. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

An environmental scan of weight assessment and management practices in paediatric spina bifida clinics across Canada.

PubMed

McPherson, Amy C; Leo, Jennifer; Church, Paige; Lyons, Julia; Chen, Lorry; Swift, Judy

2014-01-01

Childhood obesity is a global health concern, but children with spina bifida in particular have unique interacting risk factors for increased weight. To identify and explore current clinical practices around weight assessment and management in pediatric spina bifida clinics. An online, self-report survey of healthcare professionals (HCPs) was conducted in all pediatric spina bifida clinics across Canada (15 clinics). Summary and descriptive statistics were calculated and descriptive thematic analysis was performed on free text responses. 52 responses across all 15 clinics indicated that weight and height were assessed and recorded most of the time using a wide variety of methods, although some HCPs questioned their suitability for children with spina bifida. Weight and height information was not routinely communicated to patients and their families and HCPS identified considerable barriers to discussing weight-related information in consultations. Despite weight and height reportedly being measured regularly, HCPs expressed concern over the lack of appropriate assessment and classification tools. Communication across multi-disciplinary team members is required to ensure that children with weight-related issues do not inadvertently get overlooked. Specific skill training around weight-related issues and optimizing consultation time should be explored further for HCPs working with this population.

Enhanced functionalities for annotating and indexing clinical text with the NCBO Annotator.

PubMed

Tchechmedjiev, Andon; Abdaoui, Amine; Emonet, Vincent; Melzi, Soumia; Jonnagaddala, Jitendra; Jonquet, Clement

2018-06-01

Second use of clinical data commonly involves annotating biomedical text with terminologies and ontologies. The National Center for Biomedical Ontology Annotator is a frequently used annotation service, originally designed for biomedical data, but not very suitable for clinical text annotation. In order to add new functionalities to the NCBO Annotator without hosting or modifying the original Web service, we have designed a proxy architecture that enables seamless extensions by pre-processing of the input text and parameters, and post processing of the annotations. We have then implemented enhanced functionalities for annotating and indexing free text such as: scoring, detection of context (negation, experiencer, temporality), new output formats and coarse-grained concept recognition (with UMLS Semantic Groups). In this paper, we present the NCBO Annotator+, a Web service which incorporates these new functionalities as well as a small set of evaluation results for concept recognition and clinical context detection on two standard evaluation tasks (Clef eHealth 2017, SemEval 2014). The Annotator+ has been successfully integrated into the SIFR BioPortal platform-an implementation of NCBO BioPortal for French biomedical terminologies and ontologies-to annotate English text. A Web user interface is available for testing and ontology selection (http://bioportal.lirmm.fr/ncbo_annotatorplus); however the Annotator+ is meant to be used through the Web service application programming interface (http://services.bioportal.lirmm.fr/ncbo_annotatorplus). The code is openly available, and we also provide a Docker packaging to enable easy local deployment to process sensitive (e.g. clinical) data in-house (https://github.com/sifrproject). andon.tchechmedjiev@lirmm.fr. Supplementary data are available at Bioinformatics online.

Stability of ARDS subphenotypes over time in two randomised controlled trials.

PubMed

Delucchi, Kevin; Famous, Katie R; Ware, Lorraine B; Parsons, Polly E; Thompson, B Taylor; Calfee, Carolyn S

2018-05-01

Two distinct acute respiratory distress syndrome (ARDS) subphenotypes have been identified using data obtained at time of enrolment in clinical trials; it remains unknown if these subphenotypes are durable over time. To determine the stability of ARDS subphenotypes over time. Secondary analysis of data from two randomised controlled trials in ARDS, the ARMA trial of lung protective ventilation (n=473; patients randomised to low tidal volumes only) and the ALVEOLI trial of low versus high positive end-expiratory pressure (n=549). Latent class analysis (LCA) and latent transition analysis (LTA) were applied to data from day 0 and day 3, independent of clinical outcomes. In ALVEOLI, LCA indicated strong evidence of two ARDS latent classes at days 0 and 3; in ARMA, evidence of two classes was stronger at day 0 than at day 3. The clinical and biological features of these two classes were similar to those in our prior work and were largely stable over time, though class 2 demonstrated evidence of progressive organ failures by day 3, compared with class 1. In both LCA and LTA models, the majority of patients (>94%) stayed in the same class from day 0 to day 3. Clinical outcomes were statistically significantly worse in class 2 than class 1 and were more strongly associated with day 3 class assignment. ARDS subphenotypes are largely stable over the first 3 days of enrolment in two ARDS Network trials, suggesting that subphenotype identification may be feasible in the context of clinical trials. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Mobile Phone Messaging During Unobserved "Home" Induction to Buprenorphine.

PubMed

Tofighi, Babak; Grossman, Ellie; Sherman, Scott; Nunes, Edward V; Lee, Joshua D

2016-01-01

The deployment of health information technologies promises to optimize clinical outcomes for populations with substance use disorders. Electronic health records, web-based counseling interventions, and mobile phone applications enhance the delivery of evidence-based behavioral and pharmacological treatments, with minimal burden to clinical personnel, infrastructure, and work flows. This clinical case shares a recent experience utilizing mobile phone text messaging between an office-based buprenorphine provider in a safety net ambulatory clinic and a patient seeking buprenorphine treatment for opioid use disorder. The case highlights the use of text message-based physician-patient communication to facilitate unobserved "home" induction onto buprenorphine.

Accuracy of clinical tests in the diagnosis of anterior cruciate ligament injury: a systematic review

PubMed Central

2014-01-01

Background Numerous clinical tests are used in the diagnosis of anterior cruciate ligament (ACL) injury but their accuracy is unclear. The purpose of this study is to evaluate the diagnostic accuracy of clinical tests for the diagnosis of ACL injury. Methods Study Design: Systematic review. The review protocol was registered through PROSPERO (CRD42012002069). Electronic databases (PubMed, MEDLINE, EMBASE, CINAHL) were searched up to 19th of June 2013 to identify diagnostic studies comparing the accuracy of clinical tests for ACL injury to an acceptable reference standard (arthroscopy, arthrotomy, or MRI). Risk of bias was appraised using the QUADAS-2 checklist. Index test accuracy was evaluated using a descriptive analysis of paired likelihood ratios and displayed as forest plots. Results A total of 285 full-text articles were assessed for eligibility, from which 14 studies were included in this review. Included studies were deemed to be clinically and statistically heterogeneous, so a meta-analysis was not performed. Nine clinical tests from the history (popping sound at time of injury, giving way, effusion, pain, ability to continue activity) and four from physical examination (anterior draw test, Lachman’s test, prone Lachman’s test and pivot shift test) were investigated for diagnostic accuracy. Inspection of positive and negative likelihood ratios indicated that none of the individual tests provide useful diagnostic information in a clinical setting. Most studies were at risk of bias and reported imprecise estimates of diagnostic accuracy. Conclusion Despite being widely used and accepted in clinical practice, the results of individual history items or physical tests do not meaningfully change the probability of ACL injury. In contrast combinations of tests have higher diagnostic accuracy; however the most accurate combination of clinical tests remains an area for future research. Clinical relevance Clinicians should be aware of the limitations associated with the use of clinical tests for diagnosis of ACL injury. PMID:25187877

Domain Adaption of Parsing for Operative Notes

PubMed Central

Wang, Yan; Pakhomov, Serguei; Ryan, James O.; Melton, Genevieve B.

2016-01-01

Background Full syntactic parsing of clinical text as a part of clinical natural language processing (NLP) is critical for a wide range of applications, such as identification of adverse drug reactions, patient cohort identification, and gene interaction extraction. Several robust syntactic parsers are publicly available to produce linguistic representations for sentences. However, these existing parsers are mostly trained on general English text and often require adaptation for optimal performance on clinical text. Our objective was to adapt an existing general English parser for the clinical text of operative reports via lexicon augmentation, statistics adjusting, and grammar rules modification based on a set of biomedical text. Method The Stanford unlexicalized probabilistic context-free grammar (PCFG) parser lexicon was expanded with SPECIALIST lexicon along with statistics collected from a limited set of operative notes tagged with a two of POS taggers (GENIA tagger and MedPost). The most frequently occurring verb entries of the SPECIALIST lexicon were adjusted based on manual review of verb usage in operative notes. Stanford parser grammar production rules were also modified based on linguistic features of operative reports. An analogous approach was then applied to the GENIA corpus to test the generalizability of this approach to biomedical text. Results The new unlexicalized PCFG parser extended with the extra lexicon from SPECIALIST along with accurate statistics collected from an operative note corpus tagged with GENIA POS tagger improved the parser performance by 2.26% from 87.64% to 89.90%. There was a progressive improvement with the addition of multiple approaches. Most of the improvement occurred with lexicon augmentation combined with statistics from the operative notes corpus. Application of this approach on the GENIA corpus showed that parsing performance was boosted by 3.81% with a simple new grammar and the addition of the GENIA corpus lexicon. Conclusion Using statistics collected from clinical text tagged with POS taggers along with proper modification of grammars and lexicons of an unlexicalized PCFG parser can improve parsing performance. PMID:25661593

Initial Readability Assessment of Clinical Trial Eligibility Criteria

PubMed Central

Kang, Tian; Elhadad, Noémie; Weng, Chunhua

2015-01-01

Various search engines are available to clinical trial seekers. However, it remains unknown how comprehensible clinical trial eligibility criteria used for recruitment are to a lay audience. This study initially investigated this problem. Readability of eligibility criteria was assessed according to (i) shallow and lexical characteristics through the use of an established, generic readability metric; (ii) syntactic characteristics through natural language processing techniques; and (iii) health terminological characteristics through an automated comparison to technical and lay health texts. We further stratified clinical trials according to various study characteristics (e.g., source country or study type) to understand potential factors influencing readability. Mainly caused by frequent use of technical jargons, a college reading level was found to be necessary to understand eligibility criteria text, a level much higher than the average literacy level of the general American population. The use of technical jargons should be minimized to simplify eligibility criteria text. PMID:26958204

Singapore Armed Forces Medical Corps-Ministry of Health clinical practice guidelines: management of heat injury.

PubMed

Lee, L; Fock, K M; Lim, C L F; Ong, E H M; Poon, B H; Pwee, K H; O'Muircheartaigh, C R; Seet, B; Tan, C L B; Teoh, C S

2010-10-01

The Singapore Armed Forces (SAF) Medical Corps and the Ministry of Health (MOH) have published clinical practice guidelines on Management of Heat Injury to provide doctors and patients in Singapore with evidence-based guidance on the prevention and clinical management of exertional heat injuries. This article reproduces the introduction and executive summary (with recommendations from the guidelines) from the SAF Medical Corps-MOH clinical practice guidelines on Management of Heat Injury, for the information of readers of the Singapore Medical Journal. Chapters and page numbers mentioned in the reproduced extract refer to the full text of the guidelines, which are available from the Ministry of Health website: http://www.moh.gov.sg/mohcorp/publications.aspx?id=25178. The recommendations should be used with reference to the full text of the guidelines. Following this article are multiple choice questions based on the full text of the guidelines.

Computerized content analysis of some adolescent writings of Napoleon Bonaparte: a test of the validity of the method.

PubMed

Gottschalk, Louis A; DeFrancisco, Don; Bechtel, Robert J

2002-08-01

The aim of this study was to test the validity of a computer software program previously demonstrated to be capable of making DSM-IV neuropsychiatric diagnoses from the content analysis of speech or verbal texts. In this report, the computer program was applied to three personal writings of Napoleon Bonaparte when he was 12 to 16 years of age. The accuracy of the neuropsychiatric evaluations derived from the computerized content analysis of these writings of Napoleon was independently corroborated by two biographers who have described pertinent details concerning his life situations, moods, and other emotional reactions during this adolescent period of his life. The relevance of this type of computer technology to psychohistorical research and clinical psychiatry is suggested.

The South London and Maudsley NHS Foundation Trust Biomedical Research Centre (SLAM BRC) case register: development and descriptive data.

PubMed

Stewart, Robert; Soremekun, Mishael; Perera, Gayan; Broadbent, Matthew; Callard, Felicity; Denis, Mike; Hotopf, Matthew; Thornicroft, Graham; Lovestone, Simon

2009-08-12

Case registers have been used extensively in mental health research. Recent developments in electronic medical records, and in computer software to search and analyse these in anonymised format, have the potential to revolutionise this research tool. We describe the development of the South London and Maudsley NHS Foundation Trust (SLAM) Biomedical Research Centre (BRC) Case Register Interactive Search tool (CRIS) which allows research-accessible datasets to be derived from SLAM, the largest provider of secondary mental healthcare in Europe. All clinical data, including free text, are available for analysis in the form of anonymised datasets. Development involved both the building of the system and setting in place the necessary security (with both functional and procedural elements). Descriptive data are presented for the Register database as of October 2008. The database at that point included 122,440 cases, 35,396 of whom were receiving active case management under the Care Programme Approach. In terms of gender and ethnicity, the database was reasonably representative of the source population. The most common assigned primary diagnoses were within the ICD mood disorders (n = 12,756) category followed by schizophrenia and related disorders (8158), substance misuse (7749), neuroses (7105) and organic disorders (6414). The SLAM BRC Case Register represents a 'new generation' of this research design, built on a long-running system of fully electronic clinical records and allowing in-depth secondary analysis of both numerical, string and free text data, whilst preserving anonymity through technical and procedural safeguards.

Middle school students' reading comprehension of mathematical texts and algebraic equations

NASA Astrophysics Data System (ADS)

Duru, Adem; Koklu, Onder

2011-06-01

In this study, middle school students' abilities to translate mathematical texts into algebraic representations and vice versa were investigated. In addition, students' difficulties in making such translations and the potential sources for these difficulties were also explored. Both qualitative and quantitative methods were used to collect data for this study: questionnaire and clinical interviews. The questionnaire consisted of two general types of items: (1) selected-response (multiple-choice) items for which the respondent selects from multiple options and (2) open-ended items for which the respondent constructs a response. In order to further investigate the students' strategies while they were translating the given mathematical texts to algebraic equations and vice versa, five randomly chosen (n = 5) students were interviewed. Data were collected in the 2007-2008 school year from 185 middle-school students in five teachers' classrooms in three different schools in the city of Adıyaman, Turkey. After the analysis of data, it was found that students who participated in this study had difficulties in translating the mathematical texts into algebraic equations by using symbols. It was also observed that these students had difficulties in translating the symbolic representations into mathematical texts because of their weak reading comprehension. In addition, finding of this research revealed that students' difficulties in translating the given mathematical texts into symbolic representations or vice versa come from different sources.

Text Analysis: Critical Component of Planning for Text-Based Discussion Focused on Comprehension of Informational Texts

ERIC Educational Resources Information Center

Kucan, Linda; Palincsar, Annemarie Sullivan

2018-01-01

This investigation focuses on a tool used in a reading methods course to introduce reading specialist candidates to text analysis as a critical component of planning for text-based discussions. Unlike planning that focuses mainly on important text content or information, a text analysis approach focuses both on content and how that content is…

Direct-to-consumer advertising in oncology: a content analysis of print media.

PubMed

Abel, Gregory A; Lee, Stephanie J; Weeks, Jane C

2007-04-01

Content analysis of cancer-related direct-to-consumer advertising (DTCA), with a focus on how benefit and risk/adverse effect information is presented, is essential to understanding its potential impact on oncology outcomes. We reviewed all oncology DTCA appearing in three patient-focused cancer magazines and a sample of selected popular magazines from January 2003 to June 2006. We determined the Flesch reading ease score (FRES) for the text in each advertisement (a score > or = 65 is readable for the average person). We also assessed the proportion, type size, and placement of benefits and risks/adverse effects, as well as the nature and content of advertising appeals. Of 284 advertisements identified, 49 were unique. Oncology-related DTCA was rare in the popular magazines, and appeared mostly in those aimed at female readership. About equal amounts of text were devoted to benefits and risks/adverse effects, and all text was difficult to read. The mean FRES for benefit text was 39.71; for risk/adverse effect text, it was 38.22, a difference of 1.49 (95% CI, -4.02 to 7.00). The largest font size for benefits was 4.60 mm on average; for risks/adverse effects, it was 2.38 mm, a difference of 2.22 mm (95% CI, 1.35 to 3.09). Appeals to medication effectiveness were frequent (95%) and often made with clinical trial data (61%). Oncology print DTCA is prevalent in cancer-related, patient-directed magazines, and infrequent in the popular press. The information presented is considerably difficult to read, raising important questions about the appropriateness of direct-to-consumer marketing for oncologic medications.

Discrepancies between ClinicalTrials.gov recruitment status and actual trial status: a cross-sectional analysis.

PubMed

Jones, Christopher W; Safferman, Michelle R; Adams, Amanda C; Platts-Mills, Timothy F

2017-10-11

To determine the accuracy of the recruitment status listed on ClinicalTrials.gov as compared with the actual trial status. Cross-sectional analysis. Random sample of interventional phase 2-4 clinical trials registered between 2010 and 2012 on ClinicalTrials.gov. For each trial which was listed within ClinicalTrials.gov as ongoing, two investigators performed a comprehensive literature search for evidence that the trial had actually been completed. For each trial listed as completed or terminated early by ClinicalTrials.gov, we compared the date that the trial was actually concluded with the date the registry was updated to reflect the study's conclusion status. Among the 405 included trials, 92 had a registry status indicating that study activity was either ongoing or the recruitment status was unknown. Of these, published results were available for 34 (37%). Among the 313 concluded trials, the median delay between study completion and a registry update reflecting that the study had ended was 141 days (IQR 48-419), with delays of over 1 year present for 29%. In total, 125 trials (31%) either had a listed recruitment status which was incorrect or had a delay of more than 1 year between the time the study was concluded and the time the registry recruitment status was updated. At present, registry recruitment status information in ClinicalTrials.gov is often outdated or wrong. This inaccuracy has implications for the ability of researchers to identify completed trials and accurately characterise all available medical knowledge on a given subject. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

"I couldn't do this with opposition from my colleagues": A qualitative study of physicians' experiences as clinical tutors

PubMed Central

2011-01-01

Background Clinical contact in the early curriculum and workplace learning with active tutorship are important parts of modern medical education. In a previously published study, we found that medical students' tutors experienced a heavier workload, less reasonable demands and less encouragement, than students. The aim of this interview study was to further illuminate physicians' experiences as clinical tutors. Methods Twelve tutors in the Early Professional Contact course were interviewed. In the explorative interviews, they were asked to reflect upon their experiences of working as tutors in this course. Systematic text condensation was used as the analysis method. Results In the analysis, five main themes of physicians' experiences as clinical tutors in the medical education emerged: (a) Pleasure and stimulation. Informants appreciated tutorship and meeting both students and fellow tutors, (b) Disappointment and stagnation. Occasionally, tutors were frustrated and expressed negative feelings, (c) Demands and duty. Informants articulated an ambition to give students their best; a desire to provide better medical education but also a duty to meet demands of the course management, (d) Impact of workplace relations. Tutoring was made easier when the clinic's management provided active support and colleagues accepted students at the clinic, and (e) Multitasking difficulties. Combining several duties with those of a tutorship was often reported as difficult. Conclusions It is important that tutors' tasks are given adequate time, support and preparation. Accordingly, it appears highly important to avoid multitasking and too heavy a workload among tutors in order to facilitate tutoring. A crucial factor is acceptance and active organizational support from the clinic's management. This implies that tutoring by workplace learning in medical education should play an integrated and accepted role in the healthcare system. PMID:21975057

Automatic Decision Support for Clinical Diagnostic Literature Using Link Analysis in a Weighted Keyword Network.

PubMed

Li, Shuqing; Sun, Ying; Soergel, Dagobert

2017-12-23

We present a novel approach to recommending articles from the medical literature that support clinical diagnostic decision-making, giving detailed descriptions of the associated ideas and principles. The specific goal is to retrieve biomedical articles that help answer questions of a specified type about a particular case. Based on the filtered keywords, MeSH(Medical Subject Headings) lexicon and the automatically extracted acronyms, the relationship between keywords and articles was built. The paper gives a detailed description of the process of by which keywords were measured and relevant articles identified based on link analysis in a weighted keywords network. Some important challenges identified in this study include the extraction of diagnosis-related keywords and a collection of valid sentences based on the keyword co-occurrence analysis and existing descriptions of symptoms. All data were taken from medical articles provided in the TREC (Text Retrieval Conference) clinical decision support track 2015. Ten standard topics and one demonstration topic were tested. In each case, a maximum of five articles with the highest relevance were returned. The total user satisfaction of 3.98 was 33% higher than average. The results also suggested that the smaller the number of results, the higher the average satisfaction. However, a few shortcomings were also revealed since medical literature recommendation for clinical diagnostic decision support is so complex a topic that it cannot be fully addressed through the semantic information carried solely by keywords in existing descriptions of symptoms. Nevertheless, the fact that these articles are actually relevant will no doubt inspire future research.

Analysis of sex and gender-specific research reveals a common increase in publications and marked differences between disciplines

PubMed Central

2010-01-01

Background The incorporation of sex and gender-specific analysis in medical research is increasing due to pressure from public agencies, funding bodies, and the clinical and research community. However, generations of knowledge and publication trends in this discipline are currently spread over distinct specialties and are difficult to analyze comparatively. Methods Using a text-mining approach, we have analysed sex and gender aspects in research within nine clinical subspecialties - Cardiology, Pulmonology, Nephrology, Endocrinology, Gastroenterology, Haematology, Oncology, Rheumatology, Neurology - using six paradigmatic diseases in each one. Articles have been classified into five pre-determined research categories - Epidemiology, Pathophysiology, Clinical research, Management and Outcomes. Additional information has been collected on the type of study (human/animal) and the number of subjects included. Of the 8,836 articles initially retrieved, 3,466 (39%) included sex and gender-specific research and have been further analysed. Results Literature incorporating sex/gender analysis increased over time and displays a stronger trend if compared to overall publication increase. All disciplines, but cardiology (22%), demonstrated an underrepresentation of research about gender differences in management, which ranges from 3 to 14%. While the use of animal models for identification of sex differences in basic research varies greatly among disciplines, studies involving human subjects are frequently conducted in large cohorts with more than 1,000 patients (24% of all human studies). Conclusions Heterogeneity characterizes sex and gender-specific research. Although large cohorts are often analysed, sex and gender differences in clinical management are insufficiently investigated leading to potential inequalities in health provision and outcomes. PMID:21067576

How GPs implement clinical guidelines in everyday clinical practice--a qualitative interview study.

PubMed

Le, Jette V; Hansen, Helle P; Riisgaard, Helle; Lykkegaard, Jesper; Nexøe, Jørgen; Bro, Flemming; Søndergaard, Jens

2015-12-01

Clinical guidelines are considered to be essential for improving quality and safety of health care. However, interventions to promote implementation of guidelines have demonstrated only partial effectiveness and the reasons for this apparent failure are not yet fully understood. To investigate how GPs implement clinical guidelines in everyday clinical practice and how implementation approaches differ between practices. Individual semi-structured open-ended interviews with seven GPs who were purposefully sampled with regard to gender, age and practice form. Interviews were recorded, transcribed verbatim and then analysed using systematic text condensation. Analysis of the interviews revealed three different approaches to the implementation of guidelines in clinical practice. In some practices the GPs prioritized time and resources on collective implementation activities and organized their everyday practice to support these activities. In other practices GPs discussed guidelines collectively but left the application up to the individual GP whilst others again saw no need for discussion or collective activities depending entirely on the individual GP's decision on whether and how to manage implementation. Approaches to implementation of clinical guidelines vary substantially between practices. Supporting activities should take this into account. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Comparing deep learning and concept extraction based methods for patient phenotyping from clinical narratives.

PubMed

Gehrmann, Sebastian; Dernoncourt, Franck; Li, Yeran; Carlson, Eric T; Wu, Joy T; Welt, Jonathan; Foote, John; Moseley, Edward T; Grant, David W; Tyler, Patrick D; Celi, Leo A

2018-01-01

In secondary analysis of electronic health records, a crucial task consists in correctly identifying the patient cohort under investigation. In many cases, the most valuable and relevant information for an accurate classification of medical conditions exist only in clinical narratives. Therefore, it is necessary to use natural language processing (NLP) techniques to extract and evaluate these narratives. The most commonly used approach to this problem relies on extracting a number of clinician-defined medical concepts from text and using machine learning techniques to identify whether a particular patient has a certain condition. However, recent advances in deep learning and NLP enable models to learn a rich representation of (medical) language. Convolutional neural networks (CNN) for text classification can augment the existing techniques by leveraging the representation of language to learn which phrases in a text are relevant for a given medical condition. In this work, we compare concept extraction based methods with CNNs and other commonly used models in NLP in ten phenotyping tasks using 1,610 discharge summaries from the MIMIC-III database. We show that CNNs outperform concept extraction based methods in almost all of the tasks, with an improvement in F1-score of up to 26 and up to 7 percentage points in area under the ROC curve (AUC). We additionally assess the interpretability of both approaches by presenting and evaluating methods that calculate and extract the most salient phrases for a prediction. The results indicate that CNNs are a valid alternative to existing approaches in patient phenotyping and cohort identification, and should be further investigated. Moreover, the deep learning approach presented in this paper can be used to assist clinicians during chart review or support the extraction of billing codes from text by identifying and highlighting relevant phrases for various medical conditions.

Use of text messaging to audit early clinical outcome following vasectomy in primary care.

PubMed

Cooper, Graham; Walker, Jean; Harris, Douglas; Stewart, Rorie; Nicol, Douglas; Ogg, Mike

2011-04-01

Fifty patients undergoing vasectomy at community-based day surgery clinics in Grampian were invited to participate in follow-up by text message. Forty-six (92%) of the patients responded, 14 reporting problems, generally of a minor nature, but severe enough to result in unscheduled time off work (n = 4) and oral antibiotic therapy (n = 5). Text messaging appears to be a useful form of communication for audit in this setting. The study findings have influenced the information provided by the authors at preoperative counselling.

Accuracy of clinical tests in the diagnosis of anterior cruciate ligament injury: a systematic review.

PubMed

Swain, Michael S; Henschke, Nicholas; Kamper, Steven J; Downie, Aron S; Koes, Bart W; Maher, Chris G

2014-01-01

Numerous clinical tests are used in the diagnosis of anterior cruciate ligament (ACL) injury but their accuracy is unclear. The purpose of this study is to evaluate the diagnostic accuracy of clinical tests for the diagnosis of ACL injury. Systematic review. The review protocol was registered through PROSPERO (CRD42012002069). Electronic databases (PubMed, MEDLINE, EMBASE, CINAHL) were searched up to 19th of June 2013 to identify diagnostic studies comparing the accuracy of clinical tests for ACL injury to an acceptable reference standard (arthroscopy, arthrotomy, or MRI). Risk of bias was appraised using the QUADAS-2 checklist. Index test accuracy was evaluated using a descriptive analysis of paired likelihood ratios and displayed as forest plots. A total of 285 full-text articles were assessed for eligibility, from which 14 studies were included in this review. Included studies were deemed to be clinically and statistically heterogeneous, so a meta-analysis was not performed. Nine clinical tests from the history (popping sound at time of injury, giving way, effusion, pain, ability to continue activity) and four from physical examination (anterior draw test, Lachman's test, prone Lachman's test and pivot shift test) were investigated for diagnostic accuracy. Inspection of positive and negative likelihood ratios indicated that none of the individual tests provide useful diagnostic information in a clinical setting. Most studies were at risk of bias and reported imprecise estimates of diagnostic accuracy. Despite being widely used and accepted in clinical practice, the results of individual history items or physical tests do not meaningfully change the probability of ACL injury. In contrast combinations of tests have higher diagnostic accuracy; however the most accurate combination of clinical tests remains an area for future research. Clinicians should be aware of the limitations associated with the use of clinical tests for diagnosis of ACL injury.

Towards automated processing of clinical Finnish: sublanguage analysis and a rule-based parser.

PubMed

Laippala, Veronika; Ginter, Filip; Pyysalo, Sampo; Salakoski, Tapio

2009-12-01

In this paper, we present steps taken towards more efficient automated processing of clinical Finnish, focusing on daily nursing notes in a Finnish Intensive Care Unit (ICU). First, we analyze ICU Finnish as a sublanguage, identifying its specific features facilitating, for example, the development of a specialized syntactic analyser. The identified features include frequent omission of finite verbs, limitations in allowed syntactic structures, and domain-specific vocabulary. Second, we develop a formal grammar and a parser for ICU Finnish, thus providing better tools for the development of further applications in the clinical domain. The grammar is implemented in the LKB system in a typed feature structure formalism. The lexicon is automatically generated based on the output of the FinTWOL morphological analyzer adapted to the clinical domain. As an additional experiment, we study the effect of using Finnish constraint grammar to reduce the size of the lexicon. The parser construction thus makes efficient use of existing resources for Finnish. The grammar currently covers 76.6% of ICU Finnish sentences, producing highly accurate best-parse analyzes with F-score of 91.1%. We find that building a parser for the highly specialized domain sublanguage is not only feasible, but also surprisingly efficient, given an existing morphological analyzer with broad vocabulary coverage. The resulting parser enables a deeper analysis of the text than was previously possible.

Directed Activities Related to Text: Text Analysis and Text Reconstruction.

ERIC Educational Resources Information Center

Davies, Florence; Greene, Terry

This paper describes Directed Activities Related to Text (DART), procedures that were developed and are used in the Reading for Learning Project at the University of Nottingham (England) to enhance learning from texts and that fall into two broad categories: (1) text analysis procedures, which require students to engage in some form of analysis of…

A Study of Asynchronous Mobile-Enabled SMS Text Psychotherapy.

PubMed

Hull, Thomas D; Mahan, Kush

2017-03-01

Many obstacles to obtaining psychotherapy continue to diminish its reach despite its documented positive effects. Using short message service (SMS) texting and Web platforms to enable licensed psychotherapists to deliver therapy directly to the lived context of the client is one possible solution. Employing a feasibility study design, this pilot trial further evaluated the external validity for treatment outcomes of text therapy and extended findings to include mobile-enabled text platforms. Adults seeking text therapy treatment for a variety of disorders were recruited from a text therapy service (N = 57). Clinical outcomes were measured using the General Health Questionnaire-12 (GHQ-12) through 15 weeks of treatment. A process variable, the therapeutic alliance, was measured with the Working Alliance Inventory. Treatment acceptability was assessed with ratings of satisfaction for several aspects of the treatment, including affordability, effectiveness, convenience, wait times to receiving treatment, and cost-effectiveness. Results indicate evidence for the effectiveness of the intervention (GHQ-12, Cohen's d = 1.3). Twenty-five (46%) participants experienced clinically significant symptom remission. Therapeutic alliance scores were lower than those found in traditional treatment settings, but still predicted symptom improvement (R 2  = 0.299). High levels of satisfaction with text therapy were reported on dimensions of affordability, convenience, and effectiveness. Cost-effectiveness analyses suggest that text therapy is 42.2% the cost of traditional services and offers much reduced wait times. Mobile-enabled asynchronous text therapy with a licensed therapist is an acceptable and clinically beneficial medium for individuals with various diagnoses and histories of psychological distress.

Knowledge discovery for Deep Phenotyping serious mental illness from Electronic Mental Health records.

PubMed

Jackson, Richard; Patel, Rashmi; Velupillai, Sumithra; Gkotsis, George; Hoyle, David; Stewart, Robert

2018-01-01

Background: Deep Phenotyping is the precise and comprehensive analysis of phenotypic features in which the individual components of the phenotype are observed and described. In UK mental health clinical practice, most clinically relevant information is recorded as free text in the Electronic Health Record, and offers a granularity of information beyond what is expressed in most medical knowledge bases. The SNOMED CT nomenclature potentially offers the means to model such information at scale, yet given a sufficiently large body of clinical text collected over many years, it is difficult to identify the language that clinicians favour to express concepts. Methods: By utilising a large corpus of healthcare data, we sought to make use of semantic modelling and clustering techniques to represent the relationship between the clinical vocabulary of internationally recognised SMI symptoms and the preferred language used by clinicians within a care setting. We explore how such models can be used for discovering novel vocabulary relevant to the task of phenotyping Serious Mental Illness (SMI) with only a small amount of prior knowledge.  Results: 20 403 terms were derived and curated via a two stage methodology. The list was reduced to 557 putative concepts based on eliminating redundant information content. These were then organised into 9 distinct categories pertaining to different aspects of psychiatric assessment. 235 concepts were found to be expressions of putative clinical significance. Of these, 53 were identified having novel synonymy with existing SNOMED CT concepts. 106 had no mapping to SNOMED CT. Conclusions: We demonstrate a scalable approach to discovering new concepts of SMI symptomatology based on real-world clinical observation. Such approaches may offer the opportunity to consider broader manifestations of SMI symptomatology than is typically assessed via current diagnostic frameworks, and create the potential for enhancing nomenclatures such as SNOMED CT based on real-world expressions.

Knowledge discovery for Deep Phenotyping serious mental illness from Electronic Mental Health records

PubMed Central

Jackson, Richard; Patel, Rashmi; Velupillai, Sumithra; Gkotsis, George; Hoyle, David; Stewart, Robert

2018-01-01

Background: Deep Phenotyping is the precise and comprehensive analysis of phenotypic features in which the individual components of the phenotype are observed and described. In UK mental health clinical practice, most clinically relevant information is recorded as free text in the Electronic Health Record, and offers a granularity of information beyond what is expressed in most medical knowledge bases. The SNOMED CT nomenclature potentially offers the means to model such information at scale, yet given a sufficiently large body of clinical text collected over many years, it is difficult to identify the language that clinicians favour to express concepts. Methods: By utilising a large corpus of healthcare data, we sought to make use of semantic modelling and clustering techniques to represent the relationship between the clinical vocabulary of internationally recognised SMI symptoms and the preferred language used by clinicians within a care setting. We explore how such models can be used for discovering novel vocabulary relevant to the task of phenotyping Serious Mental Illness (SMI) with only a small amount of prior knowledge.  Results: 20 403 terms were derived and curated via a two stage methodology. The list was reduced to 557 putative concepts based on eliminating redundant information content. These were then organised into 9 distinct categories pertaining to different aspects of psychiatric assessment. 235 concepts were found to be expressions of putative clinical significance. Of these, 53 were identified having novel synonymy with existing SNOMED CT concepts. 106 had no mapping to SNOMED CT. Conclusions: We demonstrate a scalable approach to discovering new concepts of SMI symptomatology based on real-world clinical observation. Such approaches may offer the opportunity to consider broader manifestations of SMI symptomatology than is typically assessed via current diagnostic frameworks, and create the potential for enhancing nomenclatures such as SNOMED CT based on real-world expressions. PMID:29899974

Human prenatal diagnosis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Filkins, K.; Russo, R.J.

The multiauthor text is written as a ''guide to rationalize and clarify certain aspects of diagnosis, general counseling and intervention'' for ''health professionals who provide care to pregnant women.'' The text is not aimed at the ultrasonographer but rather at the physicians who are clinically responsible for patient management. Chapters of relevance to radiologists include an overview of prenatal screening and counseling, diagnosis of neural tube defects, ultrasonographic (US) scanning of fetal disorders in the first and second trimesters of pregnancy, US scanning in the third trimester, multiple gestation and selective termination, fetal echo and Doppler studies, and fetal therapy.more » Also included are overviews of virtually all currently utilized prenatal diagnostic techniques including amniocentesis, fetal blood sampling, fetoscopy, recombinant DNA detection of hemoglobinopathies, chorionic villus sampling, embryoscopy, legal issues, and diagnosis of Mendelian disorders by DNA analysis.« less

Comparing standard office-based follow-up with text-based remote monitoring in the management of postpartum hypertension: a randomised clinical trial.

PubMed

Hirshberg, Adi; Downes, Katheryne; Srinivas, Sindhu

2018-04-27

Monitoring blood pressure at 72 hours and 7-10 days post partum in women with hypertensive disorders is recommended to decrease morbidity. However, there are no recommendations as to how to achieve this. To compare the effectiveness of text-based blood pressure monitoring to in-person visits for women with hypertensive disorders of pregnancy in the immediate postpartum period. Randomised clinical trial among 206 postpartum women with pregnancy-related hypertension diagnosed during the delivery admission between August 2016 and January 2017. Women were randomised to 2 weeks of text-based surveillance using a home blood pressure cuff and previously tested automated platform or usual care blood pressure check at their prenatal clinic 4-6 days following discharge. The primary study outcome was a single recorded blood pressure in the first 10 days post partum. The ability to meet American Congress of Obstetricians and Gynecologists (ACOG) guidelines, defined as having a blood pressure recorded on postpartum days 3-4 and 7-10 was evaluated in the text message group. The study was powered to detect a 1.4-fold increase in a single recorded blood pressure using text messaging. All outcomes were analysed as intention to treat. 206 women were randomised (103 in each arm). Baseline characteristics were similar. There was a statistically significant increase in a single blood pressure obtained in the texting group in the first 10 days post partum as compared with the office group (92.2% vs 43.7%; adjusted OR 58.2 (16.2-208.1), p<0.001). Eighty-four per cent of patients undergoing text-based surveillance met ACOG criteria for blood pressures at both recommended points. Text-based monitoring is more effective in obtaining blood pressures and meeting current clinical guidelines in the immediate postdischarge period in women with pregnancy-related hypertension compared with traditional office-based follow-up. NCT03185455, Remote Surveillance of Postpartum Hypertension (TextBP), https://clinicaltrials.gov. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

DEEPEN: A negation detection system for clinical text incorporating dependency relation into NegEx

PubMed Central

Mehrabi, Saeed; Krishnan, Anand; Sohn, Sunghwan; Roch, Alexandra M; Schmidt, Heidi; Kesterson, Joe; Beesley, Chris; Dexter, Paul; Schmidt, C. Max; Liu, Hongfang; Palakal, Mathew

2018-01-01

In Electronic Health Records (EHRs), much of valuable information regarding patients’ conditions is embedded in free text format. Natural language processing (NLP) techniques have been developed to extract clinical information from free text. One challenge faced in clinical NLP is that the meaning of clinical entities is heavily affected by modifiers such as negation. A negation detection algorithm, NegEx, applies a simplistic approach that has been shown to be powerful in clinical NLP. However, due to the failure to consider the contextual relationship between words within a sentence, NegEx fails to correctly capture the negation status of concepts in complex sentences. Incorrect negation assignment could cause inaccurate diagnosis of patients’ condition or contaminated study cohorts. We developed a negation algorithm called DEEPEN to decrease NegEx’s false positives by taking into account the dependency relationship between negation words and concepts within a sentence using Stanford dependency parser. The system was developed and tested using EHR data from Indiana University (IU) and it was further evaluated on Mayo Clinic dataset to assess its generalizability. The evaluation results demonstrate DEEPEN, which incorporates dependency parsing into NegEx, can reduce the number of incorrect negation assignment for patients with positive findings, and therefore improve the identification of patients with the target clinical findings in EHRs. PMID:25791500

Fate of abstracts presented at the 2002 IFCC meeting.

PubMed

Uysal, Sezer; Tuglu, Birsen; Ozalp, Ylmaz; Onvural, Banu

2008-01-01

Poster presentations at major meetings serve to rapidly present and share study results with the scientific community. On the other hand, full-text publication of abstracts in peer-reviewed journals provides dissemination of knowledge. The purpose of this study was to evaluate the publication rate of abstracts presented at the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) Meeting, to assess the factors influencing publication and determine the impact factor of these journals. All poster abstracts presented at the 2002 IFCC Meeting were included in the study. A Medline search was performed to identify a matching journal article. Topics, country of origin, study type, study center and publication year were tabulated. Journals and impact factors of publication were noted. Out of 900 presented abstracts, 125 (13.9%) were published as full-text articles. Publication rates according to topics of the meeting, country of origin and university affiliation demonstrated significant differences. Abstracts from multi-centered studies had higher publication rates, and the journals they were published in had higher impact factors than single center studies. The median impact factor of the journals was 2.093. According to regression analysis, the major predictors for publication were interventional research and university affiliation (odds ratios 2.916 and 1.782, respectively; p < 0.05). The publication rate for abstracts of this clinical chemistry meeting was lower than rates from other fields of medicine. Factors leading to failure require elucidation. Encouraging authors to submit their presentations for full-text publication might improve the rate of publication.

Single-breath-hold abdominal [Formula: see text]  mapping using 3D Cartesian Look-Locker with spatiotemporal sparsity constraints.

PubMed

Lugauer, Felix; Wetzl, Jens; Forman, Christoph; Schneider, Manuel; Kiefer, Berthold; Hornegger, Joachim; Nickel, Dominik; Maier, Andreas

2018-06-01

Our aim was to develop and validate a 3D Cartesian Look-Locker [Formula: see text] mapping technique that achieves high accuracy and whole-liver coverage within a single breath-hold. The proposed method combines sparse Cartesian sampling based on a spatiotemporally incoherent Poisson pattern and k-space segmentation, dedicated for high-temporal-resolution imaging. This combination allows capturing tissue with short relaxation times with volumetric coverage. A joint reconstruction of the 3D + inversion time (TI) data via compressed sensing exploits the spatiotemporal sparsity and ensures consistent quality for the subsequent multistep [Formula: see text] mapping. Data from the National Institute of Standards and Technology (NIST) phantom and 11 volunteers, along with reference 2D Look-Locker acquisitions, are used for validation. 2D and 3D methods are compared based on [Formula: see text] values in different abdominal tissues at 1.5 and 3 T. [Formula: see text] maps obtained from the proposed 3D method compare favorably with those from the 2D reference and additionally allow for reformatting or volumetric analysis. Excellent agreement is shown in phantom [bias[Formula: see text] < 2%, bias[Formula: see text] < 5% for (120; 2000) ms] and volunteer data (3D and 2D deviation < 4% for liver, muscle, and spleen) for clinically acceptable scan (20 s) and reconstruction times (< 4 min). Whole-liver [Formula: see text] mapping with high accuracy and precision is feasible in one breath-hold using spatiotemporally incoherent, sparse 3D Cartesian sampling.

The identification of clinically important elements within medical journal abstracts: Patient-Population-Problem, Exposure-Intervention, Comparison, Outcome, Duration and Results (PECODR).

PubMed

Dawes, Martin; Pluye, Pierre; Shea, Laura; Grad, Roland; Greenberg, Arlene; Nie, Jian-Yun

2007-01-01

Information retrieval in primary care is becoming more difficult as the volume of medical information held in electronic databases expands. The lexical structure of this information might permit automatic indexing and improved retrieval. To determine the possibility of identifying the key elements of clinical studies, namely Patient-Population-Problem, Exposure-Intervention, Comparison, Outcome, Duration and Results (PECODR), from abstracts of medical journals. We used a convenience sample of 20 synopses from the journal Evidence-Based Medicine (EBM) and their matching original journal article abstracts obtained from PubMed. Three independent primary care professionals identified PECODR-related extracts of text. Rules were developed to define each PECODR element and the selection process of characters, words, phrases and sentences. From the extracts of text related to PECODR elements, potential lexical patterns that might help identify those elements were proposed and assessed using NVivo software. A total of 835 PECODR-related text extracts containing 41,263 individual text characters were identified from 20 EBM journal synopses. There were 759 extracts in the corresponding PubMed abstracts containing 31,947 characters. PECODR elements were found in nearly all abstracts and synopses with the exception of duration. There was agreement on 86.6% of the extracts from the 20 EBM synopses and 85.0% on the corresponding PubMed abstracts. After consensus this rose to 98.4% and 96.9% respectively. We found potential text patterns in the Comparison, Outcome and Results elements of both EBM synopses and PubMed abstracts. Some phrases and words are used frequently and are specific for these elements in both synopses and abstracts. Results suggest a PECODR-related structure exists in medical abstracts and that there might be lexical patterns specific to these elements. More sophisticated computer-assisted lexical-semantic analysis might refine these results, and pave the way to automating PECODR indexing, and improve information retrieval in primary care.

The effectiveness of acupuncture, acupressure and chiropractic interventions on treatment of chronic nonspecific low back pain in Iran: A systematic review and meta-analysis.

PubMed

Yeganeh, Mohsen; Baradaran, Hamid Reza; Qorbani, Mostafa; Moradi, Yousef; Dastgiri, Saeed

2017-05-01

Low back pain (LBP) is one of the most common health problems in adults. The impact of LBP on the individual can cause loss of health status and function related to pain in the back. To reduce the impact of LBP on adults, drug therapy is the most frequently recommended intervention. But over the last decade, a substantial number of randomized clinical trials of non-pharmacological intervention for LBP have been published. To determine the effectiveness of acupuncture, acupressure and chiropractic (non-pharmacological) interventions on the treatment of chronic nonspecific low back pain in Iran. Systematic review and meta-analysis. A systematic literature search was completed without date restrictions up to May 2013 in five major databases (Medline, CINAHL, Science Direct, CAJ Full-text Database, and Cochrane databases). Only randomized controlled trials published in Persian (Farsi) or English languages were included. Two independent reviewers extracted the data. The quality of the papers was assessed using the Cochrane Back Review Risk of Bias criteria. Initial searches revealed 415 papers, 382 of which were excluded on the basis of abstract alone. After excluding 23 papers due to duplication, the remaining 10 trial papers were subjected to a more detailed analysis of the full text, which resulted in three being excluded. The seven remaining trials had a lack of methodological and clinical homogeneity, precluding a meta-analysis. The trials used different comparators with regards to the primary outcomes, the number of treatments, the duration of treatment and the duration of follow-up. This systematic review demonstrates that acupuncture, acupressure and chiropractic may have a favorable effect on self-reported pain and functional limitations on NSCLBP. However, the results should be interpreted in the context of the limitations identified, particularly in relation to the heterogeneity in the study characteristics and the low methodological quality in many of the included studies. Copyright © 2016 Elsevier Ltd. All rights reserved.

A breast cancer clinical registry in an Italian comprehensive cancer center: an instrument for descriptive, clinical, and experimental research.

PubMed

Baili, Paolo; Torresani, Michele; Agresti, Roberto; Rosito, Giuseppe; Daidone, Maria Grazia; Veneroni, Silvia; Cavallo, Ilaria; Funaro, Francesco; Giunco, Marco; Turco, Alberto; Amash, Hade; Scavo, Antonio; Minicozzi, Pamela; Bella, Francesca; Meneghini, Elisabetta; Sant, Milena

2015-01-01

In clinical research, many potentially useful variables are available via the routine activity of cancer center-based clinical registries (CCCR). We present the experience of the breast cancer clinical registry at Fondazione IRCCS "Istituto Nazionale dei Tumori" to give an example of how a CCCR can be planned, implemented, and used. Five criteria were taken into consideration while planning our CCCR: (a) available clinical and administrative databases ought to be exploited to the maximum extent; (b) open source software should be used; (c) a Web-based interface must be designed; (d) CCCR data must be compatible with population-based cancer registry data; (e) CCCR must be an open system, able to be connected with other data repositories. The amount of work needed for the implementation of a CCCR is inversely linked with the amount of available coded data: the fewer data are available in the input databases as coded variables, the more work will be necessary, for information technology staff, text mining analysis, and registrars (for collecting data from clinical records). A cancer registry in a comprehensive cancer center can be used for several research aspects, such as estimate of the number of cases needed for clinical studies, assessment of biobank specimens with specific characteristics, evaluation of clinical practice and adhesion to clinical guidelines, comparative studies between clinical and population sets of patients, studies on cancer prognosis, and studies on cancer survivorship.

Clinical records anonymisation and text extraction (CRATE): an open-source software system.

PubMed

Cardinal, Rudolf N

2017-04-26

Electronic medical records contain information of value for research, but contain identifiable and often highly sensitive confidential information. Patient-identifiable information cannot in general be shared outside clinical care teams without explicit consent, but anonymisation/de-identification allows research uses of clinical data without explicit consent. This article presents CRATE (Clinical Records Anonymisation and Text Extraction), an open-source software system with separable functions: (1) it anonymises or de-identifies arbitrary relational databases, with sensitivity and precision similar to previous comparable systems; (2) it uses public secure cryptographic methods to map patient identifiers to research identifiers (pseudonyms); (3) it connects relational databases to external tools for natural language processing; (4) it provides a web front end for research and administrative functions; and (5) it supports a specific model through which patients may consent to be contacted about research. Creation and management of a research database from sensitive clinical records with secure pseudonym generation, full-text indexing, and a consent-to-contact process is possible and practical using entirely free and open-source software.

Dietary supplements for treating osteoarthritis: a systematic review and meta-analysis.

PubMed

Liu, Xiaoqian; Machado, Gustavo C; Eyles, Jillian P; Ravi, Varshini; Hunter, David J

2018-02-01

To investigate the efficacy and safety of dietary supplements for patients with osteoarthritis. An intervention systematic review with random effects meta-analysis and meta-regression. MEDLINE, EMBASE, Cochrane Register of Controlled Trials, Allied and Complementary Medicine and Cumulative Index to Nursing and Allied Health Literature were searched from inception to April 2017. Randomised controlled trials comparing oral supplements with placebo for hand, hip or knee osteoarthritis. Of 20 supplements investigated in 69 eligible studies, 7 (collagen hydrolysate, passion fruit peel extract, Curcuma longa extract, Boswellia serrata extract, curcumin, pycnogenol and L-carnitine) demonstrated large (effect size >0.80) and clinically important effects for pain reduction at short term. Another six (undenatured type II collagen, avocado soybean unsaponifiables, methylsulfonylmethane, diacerein, glucosamine and chondroitin) revealed statistically significant improvements on pain, but were of unclear clinical importance. Only green-lipped mussel extract and undenatured type II collagen had clinically important effects on pain at medium term. No supplements were identified with clinically important effects on pain reduction at long term. Similar results were found for physical function. Chondroitin demonstrated statistically significant, but not clinically important structural improvement (effect size -0.30, -0.42 to -0.17). There were no differences between supplements and placebo for safety outcomes, except for diacerein. The Grading of Recommendations Assessment, Development and Evaluation suggested a wide range of quality evidence from very low to high. The overall analysis including all trials showed that supplements provided moderate and clinically meaningful treatment effects on pain and function in patients with hand, hip or knee osteoarthritis at short term, although the quality of evidence was very low. Some supplements with a limited number of studies and participants suggested large treatment effects, while widely used supplements such as glucosamine and chondroitin were either ineffective or showed small and arguably clinically unimportant treatment effects. Supplements had no clinically important effects on pain and function at medium-term and long-term follow-ups. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Identifying clinical features in primary care electronic health record studies: methods for codelist development.

PubMed

Watson, Jessica; Nicholson, Brian D; Hamilton, Willie; Price, Sarah

2017-11-22

Analysis of routinely collected electronic health record (EHR) data from primary care is reliant on the creation of codelists to define clinical features of interest. To improve scientific rigour, transparency and replicability, we describe and demonstrate a standardised reproducible methodology for clinical codelist development. We describe a three-stage process for developing clinical codelists. First, the clear definition a priori of the clinical feature of interest using reliable clinical resources. Second, development of a list of potential codes using statistical software to comprehensively search all available codes. Third, a modified Delphi process to reach consensus between primary care practitioners on the most relevant codes, including the generation of an 'uncertainty' variable to allow sensitivity analysis. These methods are illustrated by developing a codelist for shortness of breath in a primary care EHR sample, including modifiable syntax for commonly used statistical software. The codelist was used to estimate the frequency of shortness of breath in a cohort of 28 216 patients aged over 18 years who received an incident diagnosis of lung cancer between 1 January 2000 and 30 November 2016 in the Clinical Practice Research Datalink (CPRD). Of 78 candidate codes, 29 were excluded as inappropriate. Complete agreement was reached for 44 (90%) of the remaining codes, with partial disagreement over 5 (10%). 13 091 episodes of shortness of breath were identified in the cohort of 28 216 patients. Sensitivity analysis demonstrates that codes with the greatest uncertainty tend to be rarely used in clinical practice. Although initially time consuming, using a rigorous and reproducible method for codelist generation 'future-proofs' findings and an auditable, modifiable syntax for codelist generation enables sharing and replication of EHR studies. Published codelists should be badged by quality and report the methods of codelist generation including: definitions and justifications associated with each codelist; the syntax or search method; the number of candidate codes identified; and the categorisation of codes after Delphi review. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Analyzing psychotherapy process as intersubjective sensemaking: an approach based on discourse analysis and neural networks.

PubMed

Nitti, Mariangela; Ciavolino, Enrico; Salvatore, Sergio; Gennaro, Alessandro

2010-09-01

The authors propose a method for analyzing the psychotherapy process: discourse flow analysis (DFA). DFA is a technique representing the verbal interaction between therapist and patient as a discourse network, aimed at measuring the therapist-patient discourse ability to generate new meanings through time. DFA assumes that the main function of psychotherapy is to produce semiotic novelty. DFA is applied to the verbatim transcript of the psychotherapy. It defines the main meanings active within the therapeutic discourse by means of the combined use of text analysis and statistical techniques. Subsequently, it represents the dynamic interconnections among these meanings in terms of a "discursive network." The dynamic and structural indexes of the discursive network have been shown to provide a valid representation of the patient-therapist communicative flow as well as an estimation of its clinical quality. Finally, a neural network is designed specifically to identify patterns of functioning of the discursive network and to verify the clinical validity of these patterns in terms of their association with specific phases of the psychotherapy process. An application of the DFA to a case of psychotherapy is provided to illustrate the method and the kinds of results it produces.

Multilingual Information Retrieval in Thoracic Radiology: Feasibility Study

PubMed Central

Castilla, André Coutinho; Furuie, Sérgio Shiguemi; Mendonça, Eneida A.

2014-01-01

Most of essential information contained on Electronic Medical Record is stored as text, imposing several difficulties on automated data extraction and retrieval. Natural language processing is an approach that can unlock clinical information from free texts. The proposed methodology uses the specialized natural language processor MEDLEE developed for English language. To use this processor on Portuguese medical texts, chest x-ray reports were Machine Translated into English. The result of serial coupling of MT an NLP is tagged text which needs further investigation for extracting clinical findings. The objective of this experiment was to investigate normal reports and reports with device description on a set of 165 chest x-ray reports. We obtained sensitivity and specificity of 1 and 0.71 for the first condition and 0.97 and 0.97 for the second respectively. The reference was formed by the opinion of two radiologists. The results of this experiment indicate the viability of extracting clinical findings from chest x-ray reports through coupling MT and NLP. PMID:17911745

Ministry of Health clinical practice guidelines: Management of Rhinosinusitis and Allergic Rhinitis.

PubMed

Siow, J K; Alshaikh, N A; Balakrishnan, A; Chan, K O; Chao, S S; Goh, L G; Hwang, S Y; Lee, C Y; Leong, J L; Lim, L; Menon, A; Sethi, D S; Tan, H; Wang, D Y

2010-03-01

The Ministry of Health publishes national clinical practice guidelines to provide doctors and patients in Singapore with evidence-based guidance on managing important medical conditions. This article reproduces the introduction and executive summary (with recommendations from the guidelines) from the Ministry of Health clinical practice guidelines on Management of Rhinosinusitis and Allergic Rhinitis, for the information of readers of the Singapore Medical Journal. Chapters, page and figure numbers mentioned in the reproduced extract refer to the full text of the guidelines, which are available from the Ministry of Health website (http://www.moh.gov.sg/mohcorp/publications.aspx?id=24046). The recommendations should be used with reference to the full text of the guidelines. Following this article are multiple choice questions based on the full text of the guidelines.

Real-Time Data Collection Using Text Messaging in a Primary Care Clinic.

PubMed

Rai, Manisha; Moniz, Michelle H; Blaszczak, Julie; Richardson, Caroline R; Chang, Tammy

2017-12-01

The use of text messaging is nearly ubiquitous and represents a promising method of collecting data from diverse populations. The purpose of this study was to assess the feasibility and acceptability of text message surveys in a clinical setting and to describe key lessons to minimize attrition. We obtained a convenience sample of individuals who entered the waiting room of a low-income, primary care clinic. Participants were asked to answer between 17 and 30 survey questions on a variety of health-related topics, including both open- and closed-ended questions. Descriptive statistics were used to characterize the participants and determine the response rates. Bivariate analyses were used to identify predictors of incomplete surveys. Our convenience sample consisted of 461 individuals. Of those who attempted the survey, 80% (370/461) completed it in full. The mean age of respondents was 35.4 years (standard deviation = 12.4). Respondents were predominantly non-Hispanic black (42%) or non-Hispanic white (41%), female (75%), and with at least some college education (70%). Of those who completed the survey, 84% (312/370) reported willingness to do another text message survey. Those with incomplete surveys answered a median of nine questions before stopping. Smartphone users were less likely to leave the survey incomplete compared with non-smartphone users (p = 0.004). Text-message surveys are a feasible and acceptable method to collect real-time data among low-income, clinic-based populations. Offering participants a setting for immediate survey completion, minimizing survey length, simplifying questions, and allowing "free text" responses for all questions may optimize response rates.

The applications of regenerative medicine in sinus lift procedures: A systematic review.

PubMed

Correia, Francisco; Pozza, Daniel Humberto; Gouveia, Sónia; Felino, António; Faria E Almeida, Ricardo

2018-04-01

Findings in regenerative medicine applied to the sinus lift procedures. Evaluate the effectiveness of regenerative medicine in sinus lift. An extensive search for manuscripts were performed by using different combinations of keywords and MeSH terms (Pub-med; Embase; Scopus; Web of Science Core Collection; Medline; Current Contents Connect; Derwent Innovations Index; Scielo Citation Index; Cochrane library). The full text selected articles are written in English, Portuguese, Spanish, Italian, German, or French, and published until 28 of November 2016. Inclusion criteria were: implant osteointegration, radiographic, histologic, and/or histomorphometric analysis, clinical studies in humans using of regenerative medicine. This systematic review was performed by selecting only randomized controlled clinical trials and controlled clinical trials. Eighteen published studies (11 CT and 7 RCT) were considered eligible for inclusion in the present systematic review. These studies demonstrated considerable variation of biomaterial and cell technics used, study design, sinus lift technic, outcomes, follow-up, and results. Only few studies have demonstrated potential of regenerative medicine in sinus lift; further randomized clinical trials are needed to achieve more accurate results. © 2017 Wiley Periodicals, Inc.

Systematic text condensation: a strategy for qualitative analysis.

PubMed

Malterud, Kirsti

2012-12-01

To present background, principles, and procedures for a strategy for qualitative analysis called systematic text condensation and discuss this approach compared with related strategies. Giorgi's psychological phenomenological analysis is the point of departure and inspiration for systematic text condensation. The basic elements of Giorgi's method and the elaboration of these in systematic text condensation are presented, followed by a detailed description of procedures for analysis according to systematic text condensation. Finally, similarities and differences compared with other frequently applied methods for qualitative analysis are identified, as the foundation of a discussion of strengths and limitations of systematic text condensation. Systematic text condensation is a descriptive and explorative method for thematic cross-case analysis of different types of qualitative data, such as interview studies, observational studies, and analysis of written texts. The method represents a pragmatic approach, although inspired by phenomenological ideas, and various theoretical frameworks can be applied. The procedure consists of the following steps: 1) total impression - from chaos to themes; 2) identifying and sorting meaning units - from themes to codes; 3) condensation - from code to meaning; 4) synthesizing - from condensation to descriptions and concepts. Similarities and differences comparing systematic text condensation with other frequently applied qualitative methods regarding thematic analysis, theoretical methodological framework, analysis procedures, and taxonomy are discussed. Systematic text condensation is a strategy for analysis developed from traditions shared by most of the methods for analysis of qualitative data. The method offers the novice researcher a process of intersubjectivity, reflexivity, and feasibility, while maintaining a responsible level of methodological rigour.

Open Source Clinical NLP - More than Any Single System.

PubMed

Masanz, James; Pakhomov, Serguei V; Xu, Hua; Wu, Stephen T; Chute, Christopher G; Liu, Hongfang

2014-01-01

The number of Natural Language Processing (NLP) tools and systems for processing clinical free-text has grown as interest and processing capability have surged. Unfortunately any two systems typically cannot simply interoperate, even when both are built upon a framework designed to facilitate the creation of pluggable components. We present two ongoing activities promoting open source clinical NLP. The Open Health Natural Language Processing (OHNLP) Consortium was originally founded to foster a collaborative community around clinical NLP, releasing UIMA-based open source software. OHNLP's mission currently includes maintaining a catalog of clinical NLP software and providing interfaces to simplify the interaction of NLP systems. Meanwhile, Apache cTAKES aims to integrate best-of-breed annotators, providing a world-class NLP system for accessing clinical information within free-text. These two activities are complementary. OHNLP promotes open source clinical NLP activities in the research community and Apache cTAKES bridges research to the health information technology (HIT) practice.

Spatial and dynamical handwriting analysis in mild cognitive impairment.

PubMed

Kawa, Jacek; Bednorz, Adam; Stępień, Paula; Derejczyk, Jarosław; Bugdol, Monika

2017-03-01

Background and Objectives Standard clinical procedure of Mild Cognitive Impairment (MCI) assessment employs time-consuming tests of psychological evaluation and requires the involvement of specialists. The employment of quantitative methods proves to be superior to clinical judgment, yet reliable, fast and inexpensive tests are not available. This study was conducted as a first step towards the development of a diagnostic tool based on handwriting. Methods In this paper the handwriting sample of a group of 37 patients with MCI (mean age 76.1±5.8) and 37 healthy controls (mean age 74.8±5.7) was collected using a Livescribe Echo Pen while completing three tasks: (1) regular writing, (2) all-capital-letters writing, and (3) single letter multiply repeated. Parameters differentiating both groups were selected in each task. Results Subjects with confirmed MCI needed more time to complete task one (median 119.5s, IQR - interquartile range - 38.1 vs. 95.1s, IQR 29.2 in control and MCI group, p-value <0.05) and two (median 84.2s, IQR 49.2 and 53.7s, IQR 30.5 in control and MCI group) as their writing was significantly slower. These results were associated with a longer time to complete a single stroke of written text. The written text was also noticeably larger in the MCI group in all three tasks (e.g. median height of the text block in task 2 being 22.3mm, IQR 12.9 in MCI and 20.2mm, IQR 8.7 in control group). Moreover, the MCI group showed more variation in the dynamics of writing: longer pause between strokes in task 1 and 2. The all-capital-letters task produced most of the discriminating features. Conclusion Proposed handwriting features are significant in distinguishing MCI patients. Inclusion of quantitative handwriting analysis in psychological assessment may be a step forward towards a fast MCI diagnosis. Copyright © 2017 Elsevier Ltd. All rights reserved.

Relating UMLS semantic types and task-based ontology to computer-interpretable clinical practice guidelines.

PubMed

Kumar, Anand; Ciccarese, Paolo; Quaglini, Silvana; Stefanelli, Mario; Caffi, Ezio; Boiocchi, Lorenzo

2003-01-01

Medical knowledge in clinical practice guideline (GL) texts is the source of task-based computer-interpretable clinical guideline models (CIGMs). We have used Unified Medical Language System (UMLS) semantic types (STs) to understand the percentage of GL text which belongs to a particular ST. We also use UMLS semantic network together with the CIGM-specific ontology to derive a semantic meaning behind the GL text. In order to achieve this objective, we took nine GL texts from the National Guideline Clearinghouse (NGC) and marked up the text dealing with a particular ST. The STs we took into consideration were restricted taking into account the requirements of a task-based CIGM. We used DARPA Agent Markup Language and Ontology Inference Layer (DAML + OIL) to create the UMLS and CIGM specific semantic network. For the latter, as a bench test, we used the 1999 WHO-International Society of Hypertension Guidelines for the Management of Hypertension. We took into consideration the UMLS STs closest to the clinical tasks. The percentage of the GL text dealing with the ST "Health Care Activity" and subtypes "Laboratory Procedure", "Diagnostic Procedure" and "Therapeutic or Preventive Procedure" were measured. The parts of text belonging to other STs or comments were separated. A mapping of terms belonging to other STs was done to the STs under "HCA" for representation in DAML + OIL. As a result, we found that the three STs under "HCA" were the predominant STs present in the GL text. In cases where the terms of related STs existed, they were mapped into one of the three STs. The DAML + OIL representation was able to describe the hierarchy in task-based CIGMs. To conclude, we understood that the three STs could be used to represent the semantic network of the task-bases CIGMs. We identified some mapping operators which could be used for the mapping of other STs into these.

Developing a corpus of clinical notes manually annotated for part-of-speech.

PubMed

Pakhomov, Serguei V; Coden, Anni; Chute, Christopher G

2006-06-01

This paper presents a project whose main goal is to construct a corpus of clinical text manually annotated for part-of-speech (POS) information. We describe and discuss the process of training three domain experts to perform linguistic annotation. Three domain experts were trained to perform manual annotation of a corpus of clinical notes. A part of this corpus was combined with the Penn Treebank corpus of general purpose English text and another part was set aside for testing. The corpora were then used for training and testing statistical part-of-speech taggers. We list some of the challenges as well as encouraging results pertaining to inter-rater agreement and consistency of annotation. We used the Trigrams'n'Tags (TnT) [T. Brants, TnT-a statistical part-of-speech tagger, In: Proceedings of NAACL/ANLP-2000 Symposium, 2000] tagger trained on general English data to achieve 89.79% correctness. The same tagger trained on a portion of the medical data annotated for this project improved the performance to 94.69%. Furthermore, we find that discriminating between different types of discourse represented by different sections of clinical text may be very beneficial to improve correctness of POS tagging. Our preliminary experimental results indicate the necessity for adapting state-of-the-art POS taggers to the sublanguage domain of clinical text.

Reading Comprehension Assessment through Retelling: Performance Profiles of Children with Dyslexia and Language-Based Learning Disability

PubMed Central

Kida, Adriana de S. B.; de Ávila, Clara R. B.; Capellini, Simone A.

2016-01-01

Purpose: To study reading comprehension performance profiles of children with dyslexia as well as language-based learning disability (LBLD) by means of retelling tasks. Method: One hundred and five children from 2nd to 5th grades of elementary school were gathered into six groups: Dyslexia group (D; n = 19), language-based learning disability group (LBLD; n = 16); their respective control groups paired according to different variables – age, gender, grade and school system (public or private; D-control and LBLD-control); and other control groups paired according to different reading accuracy (D-accuracy; LBLD-accuracy). All of the children read an expository text and orally retold the story as they understood it. The analysis quantified propositions (main ideas and details) and retold links. A retelling reference standard (3–0) was also established from the best to the worst performance. We compared both clinical groups (D and LBLD) with their respective control groups by means of Mann–Whitney tests. Results: D showed the same total of propositions, links and reference standards as D-control, but performed better than D-accuracy in macro structural (total of links) and super structural (retelling reference standard) measures. Results suggest that dyslexic children are able to use their linguistic competence and their own background knowledge to minimize the effects of their decoding deficit, especially at the highest text processing levels. LBLD performed worse than LBLD-control in all of the retelling measures and LBLD showed worse performance than LBLD-accuracy in the total retold links and retelling reference standard. Those results suggest that both decoding and linguistic difficulties affect reading comprehension. Moreover, the linguistic deficits presented by LBLD students do not allow these pupils to perform as competently in terms of text comprehension as the children with dyslexia do. Thus, failure in the macro and super-structural information processing of the expository text were evidenced. Conclusion: Each clinical group showed a different retelling profile. Such findings support the view that there are differences between these two clinical populations in the non-phonological dimensions of language. PMID:27313551

Semantic characteristics of NLP-extracted concepts in clinical notes vs. biomedical literature.

PubMed

Wu, Stephen; Liu, Hongfang

2011-01-01

Natural language processing (NLP) has become crucial in unlocking information stored in free text, from both clinical notes and biomedical literature. Clinical notes convey clinical information related to individual patient health care, while biomedical literature communicates scientific findings. This work focuses on semantic characterization of texts at an enterprise scale, comparing and contrasting the two domains and their NLP approaches. We analyzed the empirical distributional characteristics of NLP-discovered named entities in Mayo Clinic clinical notes from 2001-2010, and in the 2011 MetaMapped Medline Baseline. We give qualitative and quantitative measures of domain similarity and point to the feasibility of transferring resources and techniques. An important by-product for this study is the development of a weighted ontology for each domain, which gives distributional semantic information that may be used to improve NLP applications.

Physiotherapy clinical educators' perceptions of student fitness to practise.

PubMed

Lo, Kristin; Curtis, Heather; Keating, Jennifer L; Bearman, Margaret

2017-01-17

Health professional students are expected to maintain Fitness to Practise (FTP) including clinical competence, professional behaviour and freedom from impairment (physical/mental health). FTP potentially affects students, clinicians and clients, yet the impact of supervising students across the spectrum of FTP issues remains relatively under-reported. This study describes clinical educators' perceptions of supporting students with FTP issues. Between November 2012 and January 2013 an online survey was emailed to physiotherapy clinical educators from 34 sites across eight health services in Australia. The self-developed survey contained both closed and open ended questions. Demographic data and Likert scale responses were summarised using descriptive statistics. The hypotheses that years of clinical experience increased clinical educator confidence and comfort in supporting specific student FTP issues were explored with correlational analysis. Open text questions were analysed based on thematic analysis. Sixty-one percent of the 79 respondents reported supervising one or more students with FTP issues. Observed FTP concerns were clinical competence (76%), mental health (51%), professional behaviour (47%) and physical health (36%). Clinicians considered 52% (95% CI 38-66) of these issues avoidable through early disclosure, student and clinician education, maximising student competency prior to commencing placements, and human resources. Clinicians were confident and comfortable supporting clinical competence, professional behaviour and physical health issues but not mental health issues. Experience significantly increased confidence to support all FTP issues but not comfort. Student FTP issues affects the clinical educator role with 83% (95% CI 75-92) of clinicians reporting that work satisfaction was affected due to time pressures, emotional impact, lack of appreciation of educator time, quality of care conflict and a mismatch in role perception. Educators also considered that FTP issues affect service delivery and impact on those seeking health care. Strategies to support student FTP have potential to positively impact on students, clinicians and clients. Collaboration between these stakeholders is required, particularly in supporting mental health. Universities are strategically placed to implement appropriate support such as communication support.

Clinical guidance of community physiotherapists regarding people with MS: professional development and continuity of care.

PubMed

Normann, Britt; Sørgaard, Knut W; Salvesen, Rolf; Moe, Siri

2014-03-01

Clinical guidance to community physiotherapists (cPTs) is an integral part of physiotherapy service offered in hospital outpatient (OP) clinics for people with multiple sclerosis (PwMS). There is currently a lack of knowledge on the significance of such guidance. The aims of this study were 1) to identify the features that cPTs perceive to be significant in clinical guidance and 2) how this guidance may affect the cPTs' subsequent treatment of PwMS. A phenomenological-hermeneutical framework was selected, and qualitative research interviews were performed and complemented with non-participating observations of a strategic sample of nine cPTs who received clinical guidance for their patients. The interviews were recorded and transcribed, and content analysis was conducted by using systematic text condensation, using theories of practice knowledge as analytic perspectives. The results indicate that cPTs identify participation in authentic movement analysis of a familiar patient as significant for professional development. Vital features are evaluation of the interplay between body parts, exploration of improvement of movement embedded in the OP clinic physiotherapist's explanations, followed by discussion. These elements provide access to dynamic elements in practice knowledge that are available only through first-hand experience and promote clinical reasoning through enhanced reflection during action as well as following action. Such guidance suggests direction for subsequent treatment and may enhance the continuity of care, particularly if the cPTs are experienced. Mutual information flow implementing the cPTs' perspective is requested, as are the use of plain language and supervision of the cPTs handling skills. Professional guidance for cPTs in OP clinics for PwMS should be considered when programmes aiming to develop competency in neurological physiotherapy are designed and when continuity of care for PwMS is discussed. More research regarding potential long-term impact of professional guidance in these clinics is requested. Copyright © 2013 John Wiley & Sons, Ltd.

The Validity of a New Structured Assessment of Gastrointestinal Symptoms Scale (SAGIS) for Evaluating Symptoms in the Clinical Setting.

PubMed

Koloski, N A; Jones, M; Hammer, J; von Wulffen, M; Shah, A; Hoelz, H; Kutyla, M; Burger, D; Martin, N; Gurusamy, S R; Talley, N J; Holtmann, G

2017-08-01

The clinical assessments of patients with gastrointestinal symptoms can be time-consuming, and the symptoms captured during the consultation may be influenced by a variety of patient and non-patient factors. To facilitate standardized symptom assessment in the routine clinical setting, we developed the Structured Assessment of Gastrointestinal Symptom (SAGIS) instrument to precisely characterize symptoms in a routine clinical setting. We aimed to validate SAGIS including its reliability, construct and discriminant validity, and utility in the clinical setting. Development of the SAGIS consisted of initial interviews with patients referred for the diagnostic work-up of digestive symptoms and relevant complaints identified. The final instrument consisted of 22 items as well as questions on extra intestinal symptoms and was given to 1120 consecutive patients attending a gastroenterology clinic randomly split into derivation (n = 596) and validation datasets (n = 551). Discriminant validity along with test-retest reliability was assessed. The time taken to perform a clinical assessment with and without the SAGIS was recorded along with doctor satisfaction with this tool. Exploratory factor analysis conducted on the derivation sample suggested five symptom constructs labeled as abdominal pain/discomfort (seven items), gastroesophageal reflux disease/regurgitation symptoms (four items), nausea/vomiting (three items), diarrhea/incontinence (five items), and difficult defecation and constipation (2 items). Confirmatory factor analysis conducted on the validation sample supported the initially developed five-factor measurement model ([Formula: see text], p < 0.0001, χ 2 /df = 4.6, CFI = 0.90, TLI = 0.88, RMSEA = 0.08). All symptom groups demonstrated differentiation between disease groups. The SAGIS was shown to be reliable over time and resulted in a 38% reduction of the time required for clinical assessment. The SAGIS instrument has excellent psychometric properties and supports the clinical assessment of and symptom-based categorization of patients with a wide spectrum of gastrointestinal symptoms.

Research trends and perspectives of male infertility: a bibliometric analysis of 20 years of scientific literature.

PubMed

Zhang, Y; Xiao, F; Lu, S; Song, J; Zhang, C; Li, J; Gu, K; Lan, A; Lv, B; Zhang, R; Mo, F; Jiang, G; Zhang, X; Yang, X

2016-11-01

To carry out an in-depth analysis of the scientific research on male infertility, we performed the first bibliometric analysis focusing on studies involving male infertility worldwide during the period 1995-2014. Analysis of 6357 articles in the field of male infertility showed a significant increasing trend in the number of publications over the period 1995-2014. Obstetrics and Gynecology was an important subject category and Multidisciplinary Sciences was the newest interest. Authors were mainly from Europe and USA, with researchers from Cleveland Clinic producing the most articles, and those from the Tel Aviv Sourasky Medical Center and the University of Utah having the highest-quality articles. The USA contributed the most independent and international collaborative articles. The Cleveland Clinic and the University of Munster were the most productive institutions. The Cleveland Clinic and the University of Giessen had the most international collaboration publications. Harvard University had the most collaborators. The most common interests were pathogenesis and therapy, and new interests were hypogonadism, obesity, and cryopreservation. In conclusion, rapid development of the male infertility field was observed. Overall, collaborative and multidisciplinary science research has become more popular. The USA and its institutions play a dominant role, followed by European countries. Thanks to the common research focus worldwide, more insight into male fertility has been gained in the scientific literature over the past 20 years. [Correction added on September 21, 2016, after online publication: the term "institute" has been replaced by the term "institution" throughout the text.]. © 2016 American Society of Andrology and European Academy of Andrology.

Classification of hepatocellular carcinoma stages from free-text clinical and radiology reports

PubMed Central

Yim, Wen-wai; Kwan, Sharon W; Johnson, Guy; Yetisgen, Meliha

2017-01-01

Cancer stage information is important for clinical research. However, they are not always explicitly noted in electronic medical records. In this paper, we present our work on automatic classification of hepatocellular carcinoma (HCC) stages from free-text clinical and radiology notes. To accomplish this, we defined 11 stage parameters used in the three HCC staging systems, American Joint Committee on Cancer (AJCC), Barcelona Clinic Liver Cancer (BCLC), and Cancer of the Liver Italian Program (CLIP). After aggregating stage parameters to the patient-level, the final stage classifications were achieved using an expert-created decision logic. Each stage parameter relevant for staging was extracted using several classification methods, e.g. sentence classification and automatic information structuring, to identify and normalize text as cancer stage parameter values. Stage parameter extraction for the test set performed at 0.81 F1. Cancer stage prediction for AJCC, BCLC, and CLIP stage classifications were 0.55, 0.50, and 0.43 F1.

caTIES: a grid based system for coding and retrieval of surgical pathology reports and tissue specimens in support of translational research.

PubMed

Crowley, Rebecca S; Castine, Melissa; Mitchell, Kevin; Chavan, Girish; McSherry, Tara; Feldman, Michael

2010-01-01

The authors report on the development of the Cancer Tissue Information Extraction System (caTIES)--an application that supports collaborative tissue banking and text mining by leveraging existing natural language processing methods and algorithms, grid communication and security frameworks, and query visualization methods. The system fills an important need for text-derived clinical data in translational research such as tissue-banking and clinical trials. The design of caTIES addresses three critical issues for informatics support of translational research: (1) federation of research data sources derived from clinical systems; (2) expressive graphical interfaces for concept-based text mining; and (3) regulatory and security model for supporting multi-center collaborative research. Implementation of the system at several Cancer Centers across the country is creating a potential network of caTIES repositories that could provide millions of de-identified clinical reports to users. The system provides an end-to-end application of medical natural language processing to support multi-institutional translational research programs.

A Bayesian network coding scheme for annotating biomedical information presented to genetic counseling clients.

PubMed

Green, Nancy

2005-04-01

We developed a Bayesian network coding scheme for annotating biomedical content in layperson-oriented clinical genetics documents. The coding scheme supports the representation of probabilistic and causal relationships among concepts in this domain, at a high enough level of abstraction to capture commonalities among genetic processes and their relationship to health. We are using the coding scheme to annotate a corpus of genetic counseling patient letters as part of the requirements analysis and knowledge acquisition phase of a natural language generation project. This paper describes the coding scheme and presents an evaluation of intercoder reliability for its tag set. In addition to giving examples of use of the coding scheme for analysis of discourse and linguistic features in this genre, we suggest other uses for it in analysis of layperson-oriented text and dialogue in medical communication.

A systematic review of clinical assessment for undergraduate nursing students.

PubMed

Wu, Xi Vivien; Enskär, Karin; Lee, Cindy Ching Siang; Wang, Wenru

2015-02-01

Consolidated clinical practicum prepares pre-registration nursing students to function as beginning practitioners. The clinical competencies of final-year nursing students provide a key indication of professional standards of practice and patient safety. Thus, clinical assessment of nursing students is a crucial issue for educators and administrators. The aim of this systematic review was to explore the clinical competency assessment for undergraduate nursing students. PubMed, CINAHL, ScienceDirect, Web of Science, and EBSCO were systematically searched from January 2000 to December 2013. The systematic review was in line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Published quantitative and qualitative studies that examined clinical assessment practices and tools used in clinical nursing education were retrieved. Quality assessment, data extraction, and analysis were completed on all included studies. This review screened 2073 titles, abstracts and full-text records, resulting in 33 included studies. Two reviewers assessed the quality of the included studies. Fourteen quantitative and qualitative studies were identified for this evaluation. The evidence was ordered into emergent themes; the overarching themes were current practices in clinical assessment, issues of learning and assessment, development of assessment tools, and reliability and validity of assessment tools. There is a need to develop a holistic clinical assessment tool with reasonable level of validity and reliability. Clinical assessment is a robust activity and requires collaboration between clinical partners and academia to enhance the clinical experiences of students, the professional development of preceptors, and the clinical credibility of academics. Copyright © 2014 Elsevier Ltd. All rights reserved.

Patient preferences and access to text messaging for health care reminders in a safety-net setting.

PubMed

Zallman, Leah; Bearse, Adriana; West, Catherine; Bor, David; McCormick, Danny

2017-01-01

Text messaging may be an effective method for providing health care reminders to patients. We aimed to understand patient access to and preferences for receiving health-related reminders via text message among patients receiving care in safety-net hospitals. We conducted face-to-face surveys with 793 patients seeking care in three hospital emergency departments at a large safety-net institution and determined clinical and demographic predictors of preferences for text messaging for health care reminders. 95% of respondents reported having daily access to text messaging. Text messaging was preferred over e-mail, phone, and letters for communication. 78% of respondents wanted to receive appointment reminders, 56% wanted expiring insurance reminders, and 36% wanted reminders to take their medications. We found no clinical predictors but did find some demographic predictors-including age, ethnicity, insurance status, and income-of wanting text message reminders. In our convenience sample of safety-net patients, text messaging is an accessible, acceptable, and patient-preferred modality for receiving health care reminders. Text messaging may be a promising patient-centered approach for providing health care and insurance reminders to patients seeking care at safety-net institutions.

Evaluation of the Expressiveness of an ICNP-based Nursing Data Dictionary in a Computerized Nursing Record System

PubMed Central

Cho, InSook; Park, Hyeoun-Ae

2006-01-01

This study evaluated the domain completeness and expressiveness issues of the International Classification for Nursing Practice-based (ICNP) nursing data dictionary (NDD) through its application in an enterprise electronic medical record (EMR) system as a standard vocabulary at a single tertiary hospital in Korea. Data from 2,262 inpatients obtained over a period of 9 weeks (May to July 2003) were extracted from the EMR system for analysis. Among the 530,218 data-input events, 401,190 (75.7%) were entered from the NDD, 20,550 (3.9%) used only free text, and 108,478 (20.4%) used a combination of coded data and free text. A content analysis of the free-text events showed that 80.3% of the expressions could be found in the NDD, whereas 10.9% were context-specific expressions such as direct quotations of patient complaints and responses, and references to the care plan or orders of physicians. A total of 7.8% of the expressions was used for a supplementary purpose such as adding a conjunction or end verb to make an expression appear as natural language. Only 1.0% of the expressions were identified as not being covered by the NDD. This evaluation study demonstrates that the ICNP-based NDD has sufficient power to cover most of the expressions used in a clinical nursing setting. PMID:16622170

A Comparison Between Phone-Based Psychotherapy With and Without Text Messaging Support In Between Sessions for Crisis Patients

PubMed Central

2014-01-01

Background Few studies have tested whether individually tailored text messaging interventions have an effect on clinical outcomes when used to supplement traditional psychotherapy. This is despite the potential to improve outcomes through symptom monitoring, prompts for between-session activities, and psychoeducation. Objective The intent of the study was to explore the use of individually tailored between-session text messaging, or short message service (SMS), as an adjunct to telephone-based psychotherapy for consumers who present to the Emergency Department (ED) in situational and/or emotional crises. Methods Over a 4-month period, two therapists offered 68 prospective consumers of a telephone-based psychotherapy service individually tailored between-session text messaging alongside their telephone-based psychotherapy. Attendance and clinical outcomes (depression, anxiety, functional impairment) of those receiving messages were compared against a historical control group (n=157) who received telephone psychotherapy only. Results A total of 66% (45/68) of the consumers offered SMS accepted the intervention. A total of 432 messages were sent over the course of the trial, the majority involving some kind of psychoeducation or reminders to engage in therapy goals. There were no significant differences in clinical outcomes between consumers who received the SMS and those in the control group. There was a trend for participants in the intervention group to attend fewer sessions than those in the control group (mean 3.7, SD 1.9 vs mean 4.4, SD 2.3). Conclusions Both groups showed significant improvement over time. Individually tailored SMS were not found to improve clinical outcomes in consumers receiving telephone-based psychotherapy, but the study was underpowered, given the effect sizes noted and the significance level chosen. Given the ease of implementation and positive feedback from therapists and clients, individually tailored text messages should be explored further in future trials with a focus on enhancing the clinical impact of the tailored text messages, and utilizing designs with additional power to test for between-group effects. PMID:25295667

A comparison between phone-based psychotherapy with and without text messaging support in between sessions for crisis patients.

PubMed

Furber, Gareth; Jones, Gabrielle Margaret; Healey, David; Bidargaddi, Niranjan

2014-10-08

Few studies have tested whether individually tailored text messaging interventions have an effect on clinical outcomes when used to supplement traditional psychotherapy. This is despite the potential to improve outcomes through symptom monitoring, prompts for between-session activities, and psychoeducation. The intent of the study was to explore the use of individually tailored between-session text messaging, or short message service (SMS), as an adjunct to telephone-based psychotherapy for consumers who present to the Emergency Department (ED) in situational and/or emotional crises. Over a 4-month period, two therapists offered 68 prospective consumers of a telephone-based psychotherapy service individually tailored between-session text messaging alongside their telephone-based psychotherapy. Attendance and clinical outcomes (depression, anxiety, functional impairment) of those receiving messages were compared against a historical control group (n=157) who received telephone psychotherapy only. A total of 66% (45/68) of the consumers offered SMS accepted the intervention. A total of 432 messages were sent over the course of the trial, the majority involving some kind of psychoeducation or reminders to engage in therapy goals. There were no significant differences in clinical outcomes between consumers who received the SMS and those in the control group. There was a trend for participants in the intervention group to attend fewer sessions than those in the control group (mean 3.7, SD 1.9 vs mean 4.4, SD 2.3). Both groups showed significant improvement over time. Individually tailored SMS were not found to improve clinical outcomes in consumers receiving telephone-based psychotherapy, but the study was underpowered, given the effect sizes noted and the significance level chosen. Given the ease of implementation and positive feedback from therapists and clients, individually tailored text messages should be explored further in future trials with a focus on enhancing the clinical impact of the tailored text messages, and utilizing designs with additional power to test for between-group effects.

Use of an android phone application for automated text messages in international settings: A case study in an HIV clinical trial in St. Petersburg, Russia.

PubMed

Forman, Leah S; Patts, Gregory J; Coleman, Sharon M; Blokhina, Elena; Lu, John; Yaroslavtseva, Tatiana; Gnatienko, Natalia; Krupitsky, Evgeny; Samet, Jeffrey H; Chaisson, Christine E

2018-02-01

Reproducible outcomes in clinical trials depend on adherence to study protocol. Short message service (also known as text message) reminders have been shown to improve clinical trial adherence in the United States and elsewhere. However, due to systematic differences in mobile data plans, languages, and technology, these systems are not easily translated to international settings. To gauge technical capabilities for international projects, we developed SMSMessenger, an automated Android application that uses a US server to send medication reminders to participants in a clinical trial in St. Petersburg, Russia (Zinc for HIV disease among alcohol users-a randomized controlled trial in the Russia Alcohol Research Collaboration on HIV/AIDS cohort). The application is downloaded once onto an Android study phone. When it is time for the text message reminders to be sent, study personnel access the application on a local phone, which in turn accesses the existing clinical trial database hosted on a US web server. The application retrieves a list of participants with the following information: phone number, whether a message should be received at that time, and the appropriate text of the message. The application is capable of storing multiple outgoing messages. With a few clicks, text messages are sent to study participants who can reply directly to the message. Study staff can check the local phone for incoming messages. The SMSMessenger application uses an existing clinical trial database and is able to receive real-time updates. All communications between the application and server are encrypted, and phone numbers are stored in a secure database behind a firewall. No sensitive data are stored on the phone, as outgoing messages are sent through the application and not by messaging features on the phone itself. Messages are sent simultaneously to study participants, which reduces the burden on local study staff. Costs and setup are minimal. The only local requirements are an Android phone and data plan. The SMSMessenger technology could be modified to be applied anywhere in the world, in any language, script, or alphabet, and for many different purposes. The novel application of this existing low-cost technology can improve the usefulness of text messaging in advancing the goals of international clinical trials.

Characterization of Change and Significance for Clinical Findings in Radiology Reports Through Natural Language Processing.

PubMed

Hassanpour, Saeed; Bay, Graham; Langlotz, Curtis P

2017-06-01

We built a natural language processing (NLP) method to automatically extract clinical findings in radiology reports and characterize their level of change and significance according to a radiology-specific information model. We utilized a combination of machine learning and rule-based approaches for this purpose. Our method is unique in capturing different features and levels of abstractions at surface, entity, and discourse levels in text analysis. This combination has enabled us to recognize the underlying semantics of radiology report narratives for this task. We evaluated our method on radiology reports from four major healthcare organizations. Our evaluation showed the efficacy of our method in highlighting important changes (accuracy 99.2%, precision 96.3%, recall 93.5%, and F1 score 94.7%) and identifying significant observations (accuracy 75.8%, precision 75.2%, recall 75.7%, and F1 score 75.3%) to characterize radiology reports. This method can help clinicians quickly understand the key observations in radiology reports and facilitate clinical decision support, review prioritization, and disease surveillance.

Patient Electronic Health Records as a Means to Approach Genetic Research in Gastroenterology.

PubMed

Ananthakrishnan, Ashwin N; Lieberman, David

2015-10-01

Electronic health records (EHRs) are being increasingly utilized and form a unique source of extensive data gathered during routine clinical care. Through use of codified and free text concepts identified using clinical informatics tools, disease labels can be assigned with a high degree of accuracy. Analysis linking such EHR-assigned disease labels to a biospecimen repository has demonstrated that genetic associations identified in prospective cohorts can be replicated with adequate statistical power and novel phenotypic associations identified. In addition, genetic discovery research can be performed utilizing clinical, laboratory, and procedure data obtained during care. Challenges with such research include the need to tackle variability in quality and quantity of EHR data and importance of maintaining patient privacy and data security. With appropriate safeguards, this novel and emerging field of research offers considerable promise and potential to further scientific research in gastroenterology efficiently, cost-effectively, and with engagement of patients and communities. Copyright © 2015 AGA Institute. Published by Elsevier Inc. All rights reserved.

The role of the nurse teacher in clinical practice: an empirical study of Finnish student nurse experiences.

PubMed

Saarikoski, Mikko; Warne, Tony; Kaila, Päivi; Leino-Kilpi, Helena

2009-08-01

This paper focuses on the role of the nurse teacher (NT) in supporting student nurse education in clinical practice. The paper draws on the outcomes of a study aimed at exploring student nurse experiences of the pedagogical relationship with NTs during their clinical placements. The participants (N=549) were student nurses studying on pre-registration nursing programmes in Finland. Data were analysed using descriptive statistics, cross-tabulation and ANOVA. The study showed that the core aspect of NTs work in clinical practice revolved around the relationship between student, mentor and NT. Higher levels of satisfaction were experienced in direct proportion to the number of meetings held between the student and NT. However, whilst the importance of this relationship has been reported elsewhere, an additional aspect of this relationship emerged in the data analysis. Those NT who facilitated good face to face contact also used other methods to enhance the relationship, particularly e-mail, virtual learning environment and texting. This outcome suggests that NT's interpersonal and communicative skills are as important as their clinical knowledge and skills in promoting effective learning in the clinical practice area. The paper argues for such approaches to be utilised within the emergent opportunities afforded by new communication and educational technologies.

Augmenting Oracle Text with the UMLS for enhanced searching of free-text medical reports.

PubMed

Ding, Jing; Erdal, Selnur; Dhaval, Rakesh; Kamal, Jyoti

2007-10-11

The intrinsic complexity of free-text medical reports imposes great challenges for information retrieval systems. We have developed a prototype search engine for retrieving clinical reports that leverages the powerful indexing and querying capabilities of Oracle Text, and the rich biomedical domain knowledge and semantic structures that are captured in the UMLS Metathesaurus.

The relationship between Vitamin D status and exacerbation in COPD patients- a literature review.

PubMed

Ferrari, Renata; Caram, Laura M O; Tanni, Suzana E; Godoy, Irma; Rupp de Paiva, Sergio Alberto

2018-06-01

To investigate the relationship between Vitamin D and exacerbation in COPD patients. The PubMed database was searched for articles published from 2012 onwards using search terms related to Vitamin D and exacerbation in COPD patients. Meta-analysis, clinical trials, observational studies, and human studies were included. Non-English articles or articles with full text unavailable were excluded; a total of 15 articles were selected. The association between exacerbation frequency and Vitamin D levels in observational studies remains controversial, however, meta-analysis revealed a negative association between serum Vitamin D and exacerbation. Also, two clinical trials showed that Vitamin D3 supplementation in COPD patients reduced the risk of moderate and severe exacerbation. Vitamin D binding protein (VDBP) polymorphisms seem to affect patient exacerbation susceptibility. Few studies in literature have data related to diet, 25-hydroxyVitamin D [25(OH)D] and polymorphism in COPD exacerbation. One clinical trial indicates Vitamin D supplementation plays a role in COPD patients with hypovitaminosis D in preventing exacerbations. Further studies are needed to elucidate the role of Vitamin D in this population and to establish the best marker for Vitamin D, which patient subgroups will benefit, and the best supplement dosage without leading to toxicity. Copyright © 2018 Elsevier Ltd. All rights reserved.

Hydrogen Production Cost Analysis Map (Text Version) | Hyrdrogen and Fuel

Science.gov Websites

Cells | Hydrogen and Fuel Cells | NREL Analysis Map (Text Version) Hydrogen Production Cost Analysis Map (Text Version) Below is a text version of the U.S. map that provides the results of NREL's

Clinically significant drug-drug interactions involving opioid analgesics used for pain treatment in patients with cancer: a systematic review.

PubMed

Kotlinska-Lemieszek, Aleksandra; Klepstad, Pål; Haugen, Dagny Faksvåg

2015-01-01

Opioids are the most frequently used drugs to treat pain in cancer patients. In some patients, however, opioids can cause adverse effects and drug-drug interactions. No advice concerning the combination of opioids and other drugs is given in the current European guidelines. To identify studies that report clinically significant drug-drug interactions involving opioids used for pain treatment in adult cancer patients. Systematic review with searches in Embase, MEDLINE, and Cochrane Central Register of Controlled Trials from the start of the databases (Embase from 1980) through January 2014. In addition, reference lists of relevant full-text papers were hand-searched. Of 901 retrieved papers, 112 were considered as potentially eligible. After full-text reading, 17 were included in the final analysis, together with 15 papers identified through hand-searching of reference lists. All of the 32 included publications were case reports or case series. Clinical manifestations of drug-drug interactions involving opioids were grouped as follows: 1) sedation and respiratory depression, 2) other central nervous system symptoms, 3) impairment of pain control and/or opioid withdrawal, and 4) other symptoms. The most common mechanisms eliciting drug-drug interactions were alteration of opioid metabolism by inhibiting the activity of cytochrome P450 3A4 and pharmacodynamic interactions due to the combined effect on opioid, dopaminergic, cholinergic, and serotonergic activity in the central nervous system. Evidence for drug-drug interactions associated with opioids used for pain treatment in cancer patients is very limited. Still, the cases identified in this systematic review give some important suggestions for clinical practice. Physicians prescribing opioids should recognize the risk of drug-drug interactions and if possible avoid polypharmacy.

Repair of restorations--criteria for decision making and clinical recommendations.

PubMed

Hickel, Reinhard; Brüshaver, Katrin; Ilie, Nicoleta

2013-01-01

In the last decade, repair of restorations has become more and more popular while teaching repair of restorations is now included in most universities in Europe and North America. The aim of this paper was therefore to systematically review the clinical and the in vitro aspects of repair of restorations by considering different restorative materials--resin-based composites, amalgam, glass-ionomer cements, ceramics or metals. The paper gives also an overview of the occurrences of teaching repair in different universities. Furthermore, the paper outlines criteria for decision making when to treat a defect restoration with refurbishment, repair, replacement or no treatment. The database search strategy for resin based composite restoration repair (n=360) and the following hand search (n=95) retrieved 455 potentially eligible studies. After de-duplication, 260 records were examined by the titles and abstracts. 154 studies were excluded and 106 articles were assessed for eligibility by analyzing the full texts. Following the same search and selection process, 42 studies for amalgam repair, 51 studies for cast, inlay or porcelain restoration repair and 8 studies for teaching were assessed for eligibility by analysis of the full texts. Following databases were analyzed: Cochrane Library, MEDLINE, EMBASE, BIOSIS and PUBMED. Papers were selected if they met the following criteria: replacement, refurbishment or repair of resin composite restorations or amalgam restorations or inlay, cast restoration or porcelain repair. Clinical studies, in vitro studies and reports about teaching were included. Repair of restoration is a valuable method to improve the quality of restorations and is accepted, practiced and taught in many universities. However, there is a need for methodologically sound randomized controlled long-term clinical trials to be able to give an evidence based recommendation. Copyright © 2012 Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.

Freud's Little Oedipus: Hans as exception to the oedipal rule.

PubMed

Ahbel-Rappe, Karin

2008-09-01

Freud's "The Analysis of a Phobia in a Five-Year-Old Boy" is regarded by Freud and by analytic readers and commentators as a prototype of his conception of the oedipus complex. A literary methodology is used to show that the interpretation of the oedipus complex at work in Freud's text in fact differs from Freud's standard view of it. While studying the paper as text, not as case report, may obscure or distort some clinical matters, it is valuable in that it makes legible a sort of theoretical unconscious in the text. In contrast to Freud's typically tragic view of the oedipus complex (in the tradition of ancient Greek tragedy), the Hans study evokes a comic vision (in the tradition of Greek New Comedy). This comic vision allows Hans a happy imaginative ending to the oedipal dilemma, challenges certain epistemic pretensions, and emphasizes the oedipus complex as a set of abiding existential questions. Given the deep link between Freud"s oedipus concept and a tragic view of human life, this departure in the Hans paper is a fascinating anomaly.

Diagnostic Performance of Electronic Syndromic Surveillance Systems in Acute Care

PubMed Central

Kashiouris, M.; O’Horo, J.C.; Pickering, B.W.; Herasevich, V.

2013-01-01

Context Healthcare Electronic Syndromic Surveillance (ESS) is the systematic collection, analysis and interpretation of ongoing clinical data with subsequent dissemination of results, which aid clinical decision-making. Objective To evaluate, classify and analyze the diagnostic performance, strengths and limitations of existing acute care ESS systems. Data Sources All available to us studies in Ovid MEDLINE, Ovid EMBASE, CINAHL and Scopus databases, from as early as January 1972 through the first week of September 2012. Study Selection: Prospective and retrospective trials, examining the diagnostic performance of inpatient ESS and providing objective diagnostic data including sensitivity, specificity, positive and negative predictive values. Data Extraction Two independent reviewers extracted diagnostic performance data on ESS systems, including clinical area, number of decision points, sensitivity and specificity. Positive and negative likelihood ratios were calculated for each healthcare ESS system. A likelihood matrix summarizing the various ESS systems performance was created. Results The described search strategy yielded 1639 articles. Of these, 1497 were excluded on abstract information. After full text review, abstraction and arbitration with a third reviewer, 33 studies met inclusion criteria, reporting 102,611 ESS decision points. The yielded I2 was high (98.8%), precluding meta-analysis. Performance was variable, with sensitivities ranging from 21% –100% and specificities ranging from 5%-100%. Conclusions There is significant heterogeneity in the diagnostic performance of the available ESS implements in acute care, stemming from the wide spectrum of different clinical entities and ESS systems. Based on the results, we introduce a conceptual framework using a likelihood ratio matrix for evaluation and meaningful application of future, frontline clinical decision support systems. PMID:23874359

A Concept-Wide Association Study of Clinical Notes to Discover New Predictors of Kidney Failure.

PubMed

Singh, Karandeep; Betensky, Rebecca A; Wright, Adam; Curhan, Gary C; Bates, David W; Waikar, Sushrut S

2016-12-07

Identifying predictors of kidney disease progression is critical toward the development of strategies to prevent kidney failure. Clinical notes provide a unique opportunity for big data approaches to identify novel risk factors for disease. We used natural language processing tools to extract concepts from the preceding year's clinical notes among patients newly referred to a tertiary care center's outpatient nephrology clinics and retrospectively evaluated these concepts as predictors for the subsequent development of ESRD using proportional subdistribution hazards (competing risk) regression. The primary outcome was time to ESRD, accounting for a competing risk of death. We identified predictors from univariate and multivariate (adjusting for Tangri linear predictor) models using a 5% threshold for false discovery rate (q value <0.05). We included all patients seen by an adult outpatient nephrologist between January 1, 2004 and June 18, 2014 and excluded patients seen only by transplant nephrology, with preexisting ESRD, with fewer than five clinical notes, with no follow-up, or with no baseline creatinine values. Among the 4013 patients selected in the final study cohort, we identified 960 concepts in the unadjusted analysis and 885 concepts in the adjusted analysis. Novel predictors identified included high-dose ascorbic acid (adjusted hazard ratio, 5.48; 95% confidence interval, 2.80 to 10.70; q<0.001) and fast food (adjusted hazard ratio, 4.34; 95% confidence interval, 2.55 to 7.40; q<0.001). Novel predictors of human disease may be identified using an unbiased approach to analyze text from the electronic health record. Copyright © 2016 by the American Society of Nephrology.

Ministry of Health Clinical Practice Guidelines: Prevention, Diagnosis and Management of Tuberculosis

PubMed Central

Wang, Yee Tang Sonny; Chee, Cynthia Bin Eng; Hsu, Li Yang; Jagadesan, Raghuram; Kaw, Gregory Jon Leng; Kong, Po Marn; Lew, Yii Jen; Lim, Choon Seng; Lim, Ting Ting Jayne; Lu, Kuo Fan Mark; Ooi, Peng Lim; Sng, Li-Hwei; Thoon, Koh Cheng

2016-01-01

The Ministry of Health (MOH) has developed the clinical practice guidelines on Prevention, Diagnosis and Management of Tuberculosis to provide doctors and patients in Singapore with evidence-based treatment for tuberculosis. This article reproduces the introduction and executive summary (with recommendations from the guidelines) from the MOH clinical practice guidelines on Prevention, Diagnosis and Management of Tuberculosis, for the information of SMJ readers. The chapters and page numbers mentioned in the reproduced extract refer to the full text of the guidelines, which are available from the Ministry of Health website: http://www.moh.gov.sg/content/moh_web/healthprofessionalsportal/doctors/guidelines/cpg_medical.html. The recommendations should be used with reference to the full text of the guidelines. Following this article are multiple choice questions based on the full text of the guidelines. PMID:26996216

Opening communication channels with people living with HIV using mobile phone text messaging: insights from the CAMPS trial.

PubMed

Mbuagbaw, Lawrence; Thabane, Lehana; Ongolo-Zogo, Pierre

2013-04-04

Using two-way mobile phone text messages to improve adherence to antiretroviral medication enhances communication between patients and health workers. We describe the implications of participants' responses to text messages in the Cameroon Mobile Phone SMS (CAMPS) trial. This is a cross-sectional analysis of data from the intervention arm of the CAMPS trial. CAMPS was a randomized controlled trial of motivational text messaging versus usual care to improve adherence to antiretroviral medication among people living with HIV in Yaounde, Cameroon (n = 200) over a 6 month period. Participants in the intervention arm (n = 101) were given a contact phone number, but were not required to respond to their reminder messages. If they did, their responses were noted and reported as counts and percentages. We received 99 phone calls and 55 text messages (154 responses) from 48 participants during the study period. The median number of responses was 1 (first quartile [Q1]: 1; third quartile [Q3]: 3). Half (n = 79, 51.1%) of them were expressions of gratitude. The rest included requests for logistical (n = 21, 13.6%), medical (n = 20, 12.9%) and financial (n = 11, 7.1%) support. Initiating two-way mobile communication opens more channels for people living with HIV to express unmet needs. Researchers, policy makers and clinicians should be ready to respond to the needs expressed by patients who respond to text messages. Pan-African Clinical Trials Registry: PACTR201011000261458;

The South London and Maudsley NHS Foundation Trust Biomedical Research Centre (SLAM BRC) case register: development and descriptive data

PubMed Central

Stewart, Robert; Soremekun, Mishael; Perera, Gayan; Broadbent, Matthew; Callard, Felicity; Denis, Mike; Hotopf, Matthew; Thornicroft, Graham; Lovestone, Simon

2009-01-01

Background Case registers have been used extensively in mental health research. Recent developments in electronic medical records, and in computer software to search and analyse these in anonymised format, have the potential to revolutionise this research tool. Methods We describe the development of the South London and Maudsley NHS Foundation Trust (SLAM) Biomedical Research Centre (BRC) Case Register Interactive Search tool (CRIS) which allows research-accessible datasets to be derived from SLAM, the largest provider of secondary mental healthcare in Europe. All clinical data, including free text, are available for analysis in the form of anonymised datasets. Development involved both the building of the system and setting in place the necessary security (with both functional and procedural elements). Results Descriptive data are presented for the Register database as of October 2008. The database at that point included 122,440 cases, 35,396 of whom were receiving active case management under the Care Programme Approach. In terms of gender and ethnicity, the database was reasonably representative of the source population. The most common assigned primary diagnoses were within the ICD mood disorders (n = 12,756) category followed by schizophrenia and related disorders (8158), substance misuse (7749), neuroses (7105) and organic disorders (6414). Conclusion The SLAM BRC Case Register represents a 'new generation' of this research design, built on a long-running system of fully electronic clinical records and allowing in-depth secondary analysis of both numerical, string and free text data, whilst preserving anonymity through technical and procedural safeguards. PMID:19674459

Representations of disability and normality in rehabilitation technology promotional materials.

PubMed

Phelan, Shanon K; Wright, Virginia; Gibson, Barbara E

2014-01-01

To explore the ways in which promotional materials for two rehabilitation technologies reproduce commonly held perspectives about disability and rehabilitation. Our analysis was informed by critical disability studies using techniques from discourse analysis to examine texts (words and images) and their relation to social practices and power. Using this approach, promotional materials for (a) hearing aid and (b) robotic gait training technologies were interrogated using three central questions: (1) Who are represented? (2) What is promised? and (3) Who has authority? Messages of normalization pervaded representations of disabled children and their families, and the promises offered by the technologies. The latter included efficiency and effectiveness, progress and improvement, success and inclusion, and opportunities for a normal life. Normalization discourses construct childhood disability through texts and images. These discourses reinforce pervasive negative messages about disability that are taken up by children and families and have ethical implications for clinical practice. Rehabilitation has largely focused on "fixing" the individual, whereas broadening the clinical gaze to the social dimensions of disablement may lead to a more sensitive and informed approach within family-clinician discussions surrounding these advanced technologies and the use they make of promotional materials. Implications for Rehabilitation Awareness of the potential effects of implicit and explicit messages about disability in promotional materials may lead to a more sensitive and informed approach within family-clinician discussions surrounding rehabilitation technologies. In practice, it is important for rehabilitation professionals to remember that parents' and children's values and beliefs are shaped over time, and parents' and professionals' perspectives on disability strongly influence how disabled children internalize what disability means to them.

Dante and cardiology: Physiopathology and clinical features of cardiovascular diseases in the Middle Ages.

PubMed

Riva, M A; Cambioli, L; Castagna, F; Cianci, N; Varrenti, M; Giannattasio, C; Cesana, G

2015-02-15

Ancient non-medical texts can unexpectedly provide useful information on the development of knowledge about the heart and its diseases throughout history. The 750th anniversary of the birth of the Italian poet Dante Alighieri (1265-1321) provides a timely opportunity to analyze medical references in his works, in particular, focusing on literary descriptions that may be attributed to cardiovascular disorders. Dante's high level of medical knowledge, probably derived from his academic studies, is testified by his affiliation to the Florentine Guild of physicians and pharmacists. In all his works, the poet shows a deep interest for the heart. However, his anatomical and physiological knowledge of the circulatory system appears to be poor, probably due to it being based on theories and concepts brought forth by Aristotle and Galen, which were taught in medieval universities. Despite this, accurate descriptions of some symptoms (emotional syncope, orthopnea, dyspnea on exertion) and signs (ascites, paleness), which may be attributed to cardiovascular disorders, can be easily found in Dante's works, particularly in his masterpiece, the Divine Comedy. The literary and historical analysis of cardiovascular signs and symptoms allows us to assume that clinical features due to alterations of heart function were probably known by medieval physicians, but their etiology and pathophysiological mechanisms were not completely understood in that period. Historians of cardiology and clinicians should consider analysis of non-medical texts (including poetry) as an opportunity to better investigate the evolution of their discipline throughout the ages. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

A mainstream monitoring system for respiratory CO2 concentration and gasflow.

PubMed

Yang, Jiachen; Chen, Bobo; Burk, Kyle; Wang, Haitao; Zhou, Jianxiong

2016-08-01

Continuous respiratory gas monitoring is an important tool for clinical monitoring. In particular, measurement of respiratory [Formula: see text] concentration and gasflow can reflect the status of a patient by providing parameters such as volume of carbon dioxide, end-tidal [Formula: see text] respiratory rate and alveolar deadspace. However, in the majority of previous work, [Formula: see text] concentration and gasflow have been studied separately. This study focuses on a mainstream system which simultaneously measures respiratory [Formula: see text] concentration and gasflow at the same location, allowing for volumetric capnography to be implemented. A non-dispersive infrared monitor is used to measure [Formula: see text] concentration and a differential pressure sensor is used to measure gasflow. In developing this new device, we designed a custom airway adapter which can be placed in line with the breathing circuit and accurately monitor relevant respiratory parameters. Because the airway adapter is used both for capnography and gasflow, our system reduces mechanical deadspace. The finite element method was used to design the airway adapter which can provide a strong differential pressure while reducing airway resistance. Statistical analysis using the coefficient of variation was performed to find the optimal driving voltage of the pressure transducer. Calibration between variations and flows was used to avoid pressure signal drift. We carried out targeted experiments using the proposed device and confirmed that the device can produce stable signals.

Text analysis devices, articles of manufacture, and text analysis methods

DOEpatents

Turner, Alan E; Hetzler, Elizabeth G; Nakamura, Grant C

2015-03-31

Text analysis devices, articles of manufacture, and text analysis methods are described according to some aspects. In one aspect, a text analysis device includes a display configured to depict visible images, and processing circuitry coupled with the display and wherein the processing circuitry is configured to access a first vector of a text item and which comprises a plurality of components, to access a second vector of the text item and which comprises a plurality of components, to weight the components of the first vector providing a plurality of weighted values, to weight the components of the second vector providing a plurality of weighted values, and to combine the weighted values of the first vector with the weighted values of the second vector to provide a third vector.

Clinical Benefits of Joint Mobilization on Ankle Sprains: A Systematic Review and Meta-Analysis.

PubMed

Weerasekara, Ishanka; Osmotherly, Peter; Snodgrass, Suzanne; Marquez, Jodie; de Zoete, Rutger; Rivett, Darren A

2018-07-01

To assess the clinical benefits of joint mobilization for ankle sprains. MEDLINE, MEDLINE In-Process, Embase, AMED, PsycINFO, CINAHL, Cochrane Library, PEDro, Scopus, SPORTDiscus, and Dissertations and Theses were searched from inception to June 2017. Studies investigating humans with grade I or II lateral or medial sprains of the ankle in any pathologic state from acute to chronic, who had been treated with joint mobilization were considered for inclusion. Any conservative intervention was considered as a comparator. Commonly reported clinical outcomes were considered such as ankle range of movement, pain, and function. After screening of 1530 abstracts, 56 studies were selected for full-text screening, and 23 were eligible for inclusion. Eleven studies on chronic sprains reported sufficient data for meta-analysis. Data were extracted using the participants, interventions, comparison, outcomes, and study design approach. Clinically relevant outcomes (dorsiflexion range, proprioception, balance, function, pain threshold, pain intensity) were assessed at immediate, short-term, and long-term follow-up points. Methodological quality was assessed independently by 2 reviewers, and most studies were found to be of moderate quality, with no studies rated as poor. Meta-analysis revealed significant immediate benefits of joint mobilization compared with comparators on improving posteromedial dynamic balance (P=.0004), but not for improving dorsiflexion range (P=.16), static balance (P=.96), or pain intensity (P=.45). Joint mobilization was beneficial in the short-term for improving weight-bearing dorsiflexion range (P=.003) compared with a control. Joint mobilization appears to be beneficial for improving dynamic balance immediately after application, and dorsiflexion range in the short-term. Long-term benefits have not been adequately investigated. Copyright © 2017 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Clinical map document based on XML (cMDX): document architecture with mapping feature for reporting and analysing prostate cancer in radical prostatectomy specimens.

PubMed

Eminaga, Okyaz; Hinkelammert, Reemt; Semjonow, Axel; Neumann, Joerg; Abbas, Mahmoud; Koepke, Thomas; Bettendorf, Olaf; Eltze, Elke; Dugas, Martin

2010-11-15

The pathology report of radical prostatectomy specimens plays an important role in clinical decisions and the prognostic evaluation in Prostate Cancer (PCa). The anatomical schema is a helpful tool to document PCa extension for clinical and research purposes. To achieve electronic documentation and analysis, an appropriate documentation model for anatomical schemas is needed. For this purpose we developed cMDX. The document architecture of cMDX was designed according to Open Packaging Conventions by separating the whole data into template data and patient data. Analogue custom XML elements were considered to harmonize the graphical representation (e.g. tumour extension) with the textual data (e.g. histological patterns). The graphical documentation was based on the four-layer visualization model that forms the interaction between different custom XML elements. Sensible personal data were encrypted with a 256-bit cryptographic algorithm to avoid misuse. In order to assess the clinical value, we retrospectively analysed the tumour extension in 255 patients after radical prostatectomy. The pathology report with cMDX can represent pathological findings of the prostate in schematic styles. Such reports can be integrated into the hospital information system. "cMDX" documents can be converted into different data formats like text, graphics and PDF. Supplementary tools like cMDX Editor and an analyser tool were implemented. The graphical analysis of 255 prostatectomy specimens showed that PCa were mostly localized in the peripheral zone (Mean: 73% ± 25). 54% of PCa showed a multifocal growth pattern. cMDX can be used for routine histopathological reporting of radical prostatectomy specimens and provide data for scientific analysis.

Clinical map document based on XML (cMDX): document architecture with mapping feature for reporting and analysing prostate cancer in radical prostatectomy specimens

PubMed Central

2010-01-01

Background The pathology report of radical prostatectomy specimens plays an important role in clinical decisions and the prognostic evaluation in Prostate Cancer (PCa). The anatomical schema is a helpful tool to document PCa extension for clinical and research purposes. To achieve electronic documentation and analysis, an appropriate documentation model for anatomical schemas is needed. For this purpose we developed cMDX. Methods The document architecture of cMDX was designed according to Open Packaging Conventions by separating the whole data into template data and patient data. Analogue custom XML elements were considered to harmonize the graphical representation (e.g. tumour extension) with the textual data (e.g. histological patterns). The graphical documentation was based on the four-layer visualization model that forms the interaction between different custom XML elements. Sensible personal data were encrypted with a 256-bit cryptographic algorithm to avoid misuse. In order to assess the clinical value, we retrospectively analysed the tumour extension in 255 patients after radical prostatectomy. Results The pathology report with cMDX can represent pathological findings of the prostate in schematic styles. Such reports can be integrated into the hospital information system. "cMDX" documents can be converted into different data formats like text, graphics and PDF. Supplementary tools like cMDX Editor and an analyser tool were implemented. The graphical analysis of 255 prostatectomy specimens showed that PCa were mostly localized in the peripheral zone (Mean: 73% ± 25). 54% of PCa showed a multifocal growth pattern. Conclusions cMDX can be used for routine histopathological reporting of radical prostatectomy specimens and provide data for scientific analysis. PMID:21078179

Occupational medicine specialist referral triggers: Mixed-methods analysis of teleconsult cases.

PubMed

Eaton, J L; Mohammad, A; Mohr, D C; Brustein, D J; Kirkhorn, S R

2017-12-30

Qualitative analyses can yield critical lessons for learning organizations in healthcare. Few studies have applied these techniques in the field of occupational and environmental medicine (OEM). To describe the characteristics of complex cases referred for OEM subspecialty evaluation and variation by referring provider's training. Using a mixed methods approach, we conducted a content analysis of clinical cases submitted to a national OEM teleconsult service. Consecutive cases entered between April 2014 and July 2015 were screened, coded and analysed. 108 cases were available for analysis. Local Veterans Health Administration (VHA) non-specialist providers entered a primary medical diagnosis in 96% of cases at the time of intake. OEM speciality physicians coded significant medical conditions based on free text comments. Coder inter-rater reliability was 84%. The most frequent medical diagnosis types associated with tertiary OEM referral by non-specialists were endocrine (19%), cardiovascular (18%) and mental health (16%). Concern for usage of controlled and/or sedating medications was cited in 1% of cases. Compared to referring non-specialists, OEM physicians were more likely to attribute case complexity to musculoskeletal (OR: 2.3, 1.68-3.14) or neurological (OR: 1.69, 1.28-2.24) conditions. Medication usage (OR: 2.2, 1.49-2.26) was more likely to be a source of clinical concern among referring providers. The findings highlight the range of triggers for OEM physician subspecialty referral in clinical practice with employee patients. The results of this study can be used to inform development of provider education, standardized clinical practice pathways, and quality review activities for occupational medicine practitioners. Published by Oxford University Press on behalf of The Society of Occupational Medicine 2017.

[History of clinical pharmacology in France: adaptation, evaluation, defense and illustration of drug in France 1978-1981].

PubMed

Montastruc, Paul

2014-01-01

This text illustrates some unknown aspects of the history and beginnings of clinical pharmacology in France in the late 1970s and early 1980s From the current situation, development and objectives of clinical pharmacology are recalled as well as obstacles necessary to overcome to change the paradigm in the field of drug evaluation and appropriate use in France. The text recalls this important moment where French medicine and medical pharmacology entered the modern era. © 2014 Société Française de Pharmacologie et de Thérapeutique.

Tailoring vocabularies for NLP in sub-domains: a method to detect unused word sense.

PubMed

Figueroa, Rosa L; Zeng-Treitler, Qing; Goryachev, Sergey; Wiechmann, Eduardo P

2009-11-14

We developed a method to help tailor a comprehensive vocabulary system (e.g. the UMLS) for a sub-domain (e.g. clinical reports) in support of natural language processing (NLP). The method detects unused sense in a sub-domain by comparing the relational neighborhood of a word/term in the vocabulary with the semantic neighborhood of the word/term in the sub-domain. The semantic neighborhood of the word/term in the sub-domain is determined using latent semantic analysis (LSA). We trained and tested the unused sense detection on two clinical text corpora: one contains discharge summaries and the other outpatient visit notes. We were able to detect unused senses with precision from 79% to 87%, recall from 48% to 74%, and an area under receiver operation curve (AUC) of 72% to 87%.

Incorporating Guideline Adherence and Practice Implementation Issues into the Design of Decision Support for Beta-Blocker Titration for Heart Failure.

PubMed

Smith, Michael W; Brown, Charnetta; Virani, Salim S; Weir, Charlene R; Petersen, Laura A; Kelly, Natalie; Akeroyd, Julia; Garvin, Jennifer H

2018-04-01

 The recognition of and response to undertreatment of heart failure (HF) patients can be complicated. A clinical reminder can facilitate use of guideline-concordant β-blocker titration for HF patients with depressed ejection fraction. However, the design must consider the cognitive demands on the providers and the context of the work.  This study's purpose is to develop requirements for a clinical decision support tool (a clinical reminder) by analyzing the cognitive demands of the task along with the factors in the Cabana framework of physician adherence to guidelines, the health information technology (HIT) sociotechnical framework, and the Promoting Action on Research Implementation in Health Services (PARIHS) framework of health services implementation. It utilizes a tool that extracts information from medical records (including ejection fraction in free text reports) to identify qualifying patients at risk of undertreatment.  We conducted interviews with 17 primary care providers, 5 PharmDs, and 5 Registered Nurses across three Veterans Health Administration outpatient clinics. The interviews were based on cognitive task analysis (CTA) methods and enhanced through the inclusion of the Cabana, HIT sociotechnical, and PARIHS frameworks. The analysis of the interview data led to the development of requirements and a prototype design for a clinical reminder. We conducted a small pilot usability assessment of the clinical reminder using realistic clinical scenarios.  We identified organizational challenges (such as time pressures and underuse of pharmacists), knowledge issues regarding the guideline, and information needs regarding patient history and treatment status. We based the design of the clinical reminder on how to best address these challenges. The usability assessment indicated the tool could help the decision and titration processes.  Through the use of CTA methods enhanced with adherence, sociotechnical, and implementation frameworks, we designed a decision support tool that considers important challenges in the decision and execution of β-blocker titration for qualifying HF patients at risk of undertreatment. Schattauer GmbH Stuttgart.

A system for classifying disease comorbidity status from medical discharge summaries using automated hotspot and negated concept detection.

PubMed

Ambert, Kyle H; Cohen, Aaron M

2009-01-01

OBJECTIVE Free-text clinical reports serve as an important part of patient care management and clinical documentation of patient disease and treatment status. Free-text notes are commonplace in medical practice, but remain an under-used source of information for clinical and epidemiological research, as well as personalized medicine. The authors explore the challenges associated with automatically extracting information from clinical reports using their submission to the Integrating Informatics with Biology and the Bedside (i2b2) 2008 Natural Language Processing Obesity Challenge Task. DESIGN A text mining system for classifying patient comorbidity status, based on the information contained in clinical reports. The approach of the authors incorporates a variety of automated techniques, including hot-spot filtering, negated concept identification, zero-vector filtering, weighting by inverse class-frequency, and error-correcting of output codes with linear support vector machines. MEASUREMENTS Performance was evaluated in terms of the macroaveraged F1 measure. RESULTS The automated system performed well against manual expert rule-based systems, finishing fifth in the Challenge's intuitive task, and 13(th) in the textual task. CONCLUSIONS The system demonstrates that effective comorbidity status classification by an automated system is possible.

Effects of Phone and Text Message Reminders on Completion of the Human Papillomavirus Vaccine Series.

PubMed

Rand, Cynthia M; Vincelli, Phyllis; Goldstein, Nicolas P N; Blumkin, Aaron; Szilagyi, Peter G

2017-01-01

To assess the effect of phone or text message reminders to parents of adolescents on human papillomavirus (HPV) vaccine series completion in Rochester, NY. We performed parallel randomized controlled trials of phone and text reminders for HPV vaccine for parents of 11- to 17-year olds in three urban primary care clinics. The main outcome measures were time to receipt of the third dose of HPV vaccine and HPV vaccination rates. We enrolled 178 phone intervention (180 control) and 191 text intervention (200 control) participants. In multivariate survival analysis controlling for gender, age, practice, insurance, race, and ethnicity, the time from enrollment to receipt of the third HPV dose for those receiving a phone reminder compared with controls was not significant overall (hazard ratio [HR] = 1.30, p = .12) but was for those enrolling at dose 1 (HR = 1.91, p = .007). There was a significant difference in those receiving a text reminder compared with controls (HR = 2.34, p < .0001; an average of 71 days earlier). At the end of the study, 48% of phone intervention versus 40% of phone control (p = .34), and 49% of text intervention versus 30% of text control (p = .001) adolescents had received 3 HPV vaccine doses. In this urban population of parents of adolescents, text message reminders for HPV vaccine completion for those who had already started the series were effective, whereas phone message reminders were only effective for those enrolled at dose 1. Copyright © 2016 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Spatial Paradigm for Information Retrieval and Exploration

DOE Office of Scientific and Technical Information (OSTI.GOV)

The SPIRE system consists of software for visual analysis of primarily text based information sources. This technology enables the content analysis of text documents without reading all the documents. It employs several algorithms for text and word proximity analysis. It identifies the key themes within the text documents. From this analysis, it projects the results onto a visual spatial proximity display (Galaxies or Themescape) where items (documents and/or themes) visually close to each other are known to have content which is close to each other. Innovative interaction techniques then allow for dynamic visual analysis of large text based information spaces.

SPIRE1.03. Spatial Paradigm for Information Retrieval and Exploration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Adams, K.J.; Bohn, S.; Crow, V.

The SPIRE system consists of software for visual analysis of primarily text based information sources. This technology enables the content analysis of text documents without reading all the documents. It employs several algorithms for text and word proximity analysis. It identifies the key themes within the text documents. From this analysis, it projects the results onto a visual spatial proximity display (Galaxies or Themescape) where items (documents and/or themes) visually close to each other are known to have content which is close to each other. Innovative interaction techniques then allow for dynamic visual analysis of large text based information spaces.

Identifying Patients for Clinical Studies from Electronic Health Records: TREC 2012 Medical Records Track at OHSU

DTIC Science & Technology

2012-11-01

causes of hypertension ") AND NOT(report_text:"pulmonary| portal hypertension " OR report_text:"secondary to hypertension ") 182 Patients with Ischemic... hypertension , and tachycardia (discharge_icd_codes_txt:293.0 OR report_text:delirium) AND (discharge_icd_codes_txt:401.* OR discharge_icd_codes_txt:405...report_text:"**AGE[in teens") 162 Patients with hypertension on anti- hypertensive medication (report_text:" hypertension " OR report_text:"high blood

Open Source Clinical NLP – More than Any Single System

PubMed Central

Masanz, James; Pakhomov, Serguei V.; Xu, Hua; Wu, Stephen T.; Chute, Christopher G.; Liu, Hongfang

2014-01-01

The number of Natural Language Processing (NLP) tools and systems for processing clinical free-text has grown as interest and processing capability have surged. Unfortunately any two systems typically cannot simply interoperate, even when both are built upon a framework designed to facilitate the creation of pluggable components. We present two ongoing activities promoting open source clinical NLP. The Open Health Natural Language Processing (OHNLP) Consortium was originally founded to foster a collaborative community around clinical NLP, releasing UIMA-based open source software. OHNLP’s mission currently includes maintaining a catalog of clinical NLP software and providing interfaces to simplify the interaction of NLP systems. Meanwhile, Apache cTAKES aims to integrate best-of-breed annotators, providing a world-class NLP system for accessing clinical information within free-text. These two activities are complementary. OHNLP promotes open source clinical NLP activities in the research community and Apache cTAKES bridges research to the health information technology (HIT) practice. PMID:25954581

Impact of Prominent Themes in Clinician-Patient Conversations on Caregiver's Perceived Quality of Communication with Paediatric Dental Visits.

PubMed

Wong, Hai Ming; Bridges, Susan Margaret; McGrath, Colman Patrick; Yiu, Cynthia Kar Yung; Zayts, Olga A; Au, Terry Kit Fong

2017-01-01

Patients' perceived satisfaction is a key performance index of the quality health care service. Good communication has been found to increase patient's perceived satisfaction. The purpose of this study was to examine the impact of the prominent themes arising from clinician-patient conversations on the caregiver's perceived quality of communication during paediatric dental visits. 162 video recordings of clinical dental consultations for 62 cases attending the Paediatric Dentistry Clinic of The Prince Philip Dental Hospital in Hong Kong were captured and transcribed. The patients' demographic information and the caregiver's perceived quality of communication with the clinicians were recorded using the 16-item Dental Patient Feedback on Consultation skills questionnaires. Visual text analytics (Leximancer™) indicated five prominent themes 'disease / treatment', 'treatment procedure related instructions', 'preparation for examination', 'positive reinforcement / reassurance', and 'family / social history' from the clinician-patient conversation of the recorded videos, with 60.2% of the total variance in concept words in this study explained through principal components analysis. Significant variation in perceived quality of communication was noted in five variables regarding the prominent theme 'Positive reinforcement / reassurance': 'number of related words' (p = 0.002), 'number of related utterances' (p = 0.001), 'percentage of the related words in total number of words' (p = 0.005), 'percentage of the related utterances in total number of utterances' (p = 0.035) and 'percentage of time spent in total time duration' (p = 0.023). Clinicians were perceived to be more patient-centered and empathetic if a larger proportion of their conversation showed positive reinforcement and reassurance via using related key words. Care-giver's involvement, such as clinicians' mention of the parent, was also seen as critical to perceptions of quality clinical experience. The study reveals the potential of the application of visual text analytics software in clinical consultations with implications for professional development regarding clinicians' communication skills for improving patients' clinical experiences and treatment satisfaction.

ASCOT: a text mining-based web-service for efficient search and assisted creation of clinical trials

PubMed Central

2012-01-01

Clinical trials are mandatory protocols describing medical research on humans and among the most valuable sources of medical practice evidence. Searching for trials relevant to some query is laborious due to the immense number of existing protocols. Apart from search, writing new trials includes composing detailed eligibility criteria, which might be time-consuming, especially for new researchers. In this paper we present ASCOT, an efficient search application customised for clinical trials. ASCOT uses text mining and data mining methods to enrich clinical trials with metadata, that in turn serve as effective tools to narrow down search. In addition, ASCOT integrates a component for recommending eligibility criteria based on a set of selected protocols. PMID:22595088

ASCOT: a text mining-based web-service for efficient search and assisted creation of clinical trials.

PubMed

Korkontzelos, Ioannis; Mu, Tingting; Ananiadou, Sophia

2012-04-30

Clinical trials are mandatory protocols describing medical research on humans and among the most valuable sources of medical practice evidence. Searching for trials relevant to some query is laborious due to the immense number of existing protocols. Apart from search, writing new trials includes composing detailed eligibility criteria, which might be time-consuming, especially for new researchers. In this paper we present ASCOT, an efficient search application customised for clinical trials. ASCOT uses text mining and data mining methods to enrich clinical trials with metadata, that in turn serve as effective tools to narrow down search. In addition, ASCOT integrates a component for recommending eligibility criteria based on a set of selected protocols.

Text mining a self-report back-translation.

PubMed

Blanch, Angel; Aluja, Anton

2016-06-01

There are several recommendations about the routine to undertake when back translating self-report instruments in cross-cultural research. However, text mining methods have been generally ignored within this field. This work describes a text mining innovative application useful to adapt a personality questionnaire to 12 different languages. The method is divided in 3 different stages, a descriptive analysis of the available back-translated instrument versions, a dissimilarity assessment between the source language instrument and the 12 back-translations, and an item assessment of item meaning equivalence. The suggested method contributes to improve the back-translation process of self-report instruments for cross-cultural research in 2 significant intertwined ways. First, it defines a systematic approach to the back translation issue, allowing for a more orderly and informed evaluation concerning the equivalence of different versions of the same instrument in different languages. Second, it provides more accurate instrument back-translations, which has direct implications for the reliability and validity of the instrument's test scores when used in different cultures/languages. In addition, this procedure can be extended to the back-translation of self-reports measuring psychological constructs in clinical assessment. Future research works could refine the suggested methodology and use additional available text mining tools. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Piloting a Text Message-based Social Support Intervention for Patients With Chronic Pain: Establishing Feasibility and Preliminary Efficacy.

PubMed

Guillory, Jamie; Chang, Pamara; Henderson, Charles R; Shengelia, Rouzi; Lama, Sonam; Warmington, Marcus; Jowza, Maryam; Waldman, Seth; Gay, Geri; Reid, M Carrington

2015-06-01

To examine preliminarily the effectiveness of a short message service (SMS) text message-based social support intervention for reducing daily pain and pain interference levels, improving affect and perceptions of social support in patients with chronic noncancer pain, and exploring the feasibility of a novel mobile application to track perceptions of pain and pain interference. Participants (17 men, 51 women) from 2 pain clinics in New York City downloaded a pain tracking application (App) on their Smartphone and used it to record twice-daily pain, pain interference, and affect scores over the 4-week study period. Participants were randomly assigned to receive standard care (control) or standard care along with receipt of twice-daily supportive SMS text messages delivered during the second and third week of the study (intervention). Demographic and clinical data were obtained at baseline, and social support measures were administered at baseline and at 4 weeks. Statistical analysis was carried out using general linear mixed models, taking into account variances associated with time of assessments and with patients. The social support intervention reduced perceptions of pain and pain interference and improved positive affect for chronic noncancer pain patients assigned to the intervention condition in comparison with controls. Participants completed approximately 80% of the daily measurements requested. These findings establish the feasibility of collecting daily pain data using a mobile tracking App and provide significant implications and insight into a nuanced approach to reducing the daily experience of pain through mobile technology, especially because of its accessibility.

A literature review of quantitative indicators to measure the quality of labor and delivery care.

PubMed

Tripathi, Vandana

2016-02-01

Strengthening measurement of the quality of labor and delivery (L&D) care in low-resource countries requires an understanding of existing approaches. To identify quantitative indicators of L&D care quality and assess gaps in indicators. PubMed, CINAHL Plus, and Embase databases were searched for research published in English between January 1, 1990, and October 31, 2013, using structured terms. Studies describing indicators for L&D care quality assessment were included. Those whose abstracts contained inclusion criteria underwent full-text review. Study characteristics, including indicator selection and data sources, were extracted via a standard spreadsheet. The structured search identified 1224 studies. After abstract and full-text review, 477 were included in the analysis. Most studies selected indicators by using literature review, clinical guidelines, or expert panels. Few indicators were empirically validated; most studies relied on medical record review to measure indicators. Many quantitative indicators have been used to measure L&D care quality, but few have been validated beyond expert opinion. There has been limited use of clinical observation in quality assessment of care processes. The findings suggest the need for validated, efficient consensus indicators of the quality of L&D care processes, particularly in low-resource countries. Copyright © 2015 International Federation of Gynecology and Obstetrics. Published by Elsevier Ireland Ltd. All rights reserved.

In Vivo and In Vitro Effectiveness of Rotary Nickel-Titanium vs Manual Stainless Steel Instruments for Root Canal Therapy: Systematic Review and Meta-analysis.

PubMed

Del Fabbro, Massimo; Afrashtehfar, Kelvin Ian; Corbella, Stefano; El-Kabbaney, Ahmed; Perondi, Isabella; Taschieri, Silvio

2018-03-01

This systematic review evaluated the effectiveness of nickel-titanium (NiTi) rotary files compared to stainless-steel (SST) hand files. An electronic search was performed on Medline, EMBASE, CENTRAL and Scopus databases up to February 2016. An additional hand searching was performed in 13 journals. The studies were classified according to study type and the outcome variables. Two reviewers independently applied eligibility criteria, extracted data, and three reviewers independently assessed the quality of the evidence of each included study according to The Cochrane Collaboration's procedures. A meta-analysis was performed whenever it was possible. The electronic and hand search strategies yielded 1155 references of studies after removal of duplicates. Four clinical studies (two prospective and two retrospective studies) and 18 in vitro studies (on extracted teeth) were included for the qualitative synthesis after full-text evaluation of the eligible studies. The overall level of methodological quality of the studies included can be considered inadequate. Only one clinical study was judged at low risk of bias, whereas most non-clinical studies had a low risk of bias. Three meta-analyses, based on a very limited number of studies, could be performed. Each meta-analysis contained two studies. Of these, one meta-analysis was based on clinical studies. The results of this systematic review suggested that NiTi rotary instruments were associated with lower canal transportation and apical extrusion when compared to SST hand files, whereas both groups had similar outcomes in terms of success of therapy, amount of residual bacteria, and cleansing ability after treatment. However, due to the limited evidence available, these results should be interpreted with caution. Consequently, more randomized control trials using standardized protocols are needed in order to provide more solid recommendations. Copyright © 2017 Elsevier Inc. All rights reserved.

MedTxting: Learning based and Knowledge Rich SMS-style Medical Text Contraction

PubMed Central

Liu, Feifan; Moosavinasab, Soheil; Houston, Thomas K.; Yu, Hong

2012-01-01

In mobile health (M-health), Short Message Service (SMS) has shown to improve disease related self-management and health service outcomes, leading to enhanced patient care. However, the hard limit on character size for each message limits the full value of exploring SMS communication in health care practices. To overcome this problem and improve the efficiency of clinical workflow, we developed an innovative system, MedTxting (available at http://medtxting.askhermes.org), which is a learning-based but knowledge-rich system that compresses medical texts in a SMS style. Evaluations on clinical questions and discharge summary narratives show that MedTxting can effectively compress medical texts with reasonable readability and noticeable size reduction. Findings in this work reveal potentials of MedTxting to the clinical settings, allowing for real-time and cost-effective communication, such as patient condition reporting, medication consulting, physicians connecting to share expertise to improve point of care. PMID:23304328

Health Promotion Board-Ministry of Health clinical practice guidelines: functional screening for older adults in the community.

PubMed

Thilagaratnam, S; Ding, Y Y; Au Eong, K G; Chiam, P C; Chow, Y L; Khoo, G; Lim, H B; Lim, H Y L; Lim, W S; Lim, W Y; Peh, K C; Phua, K T; Sitoh, Y Y; Tan, B Y; Wong, S F; Wong, W P; Yee, R

2010-06-01

The Health Promotion Board (HPB) and the Ministry of Health (MOH) publish clinical practice guidelines to provide doctors and patients in Singapore with evidence-based guidance on managing important medical conditions. This article reproduces the introduction and executive summary (with recommendations from the guidelines) from the HPB-MOH clinical practice guidelines on Functional Screening for Older Adults in the Community, for the information of readers of the Singapore Medical Journal. Chapters and page numbers mentioned in the reproduced extract refer to the full text of the guidelines, which are available from the Health Promotion Board website (http://www.hpb.gov.sg/uploadedFiles/HPB_Online/Publications/CPGFunctionalscreening.pdf). The recommendations should be used with reference to the full text of the guidelines. Following this article are multiple choice questions based on the full text of the guidelines.

Mobile Text Messaging to Improve Medication Adherence and Viral Load in a Vulnerable Canadian Population Living With Human Immunodeficiency Virus: A Repeated Measures Study

PubMed Central

King, Elizabeth; Kinvig, Karen; Steif, Jonathan; Qiu, Annie Q; Maan, Evelyn J; Albert, Arianne YK; Pick, Neora; Alimenti, Ariane; Kestler, Mary H; Money, Deborah M; Lester, Richard T

2017-01-01

Background Combination antiretroviral therapy (cART) as treatment for human immunodeficiency virus (HIV) infection is effective and available, but poor medication adherence limits benefits, particularly in vulnerable populations. In a Kenyan randomized controlled trial, a weekly text-messaging intervention (WelTel) improved cART adherence and HIV viral load (VL). Despite growing evidence for short message service (SMS) text-message interventions in HIV care, there is a paucity of data utilizing these interventions in marginalized or female cohorts. Objective This study was undertaken to assess whether the standardized WelTel SMS text-message intervention applied to a vulnerable, predominantly female, population improved cART adherence and VL. Methods We conducted a repeated measures study of the WelTel intervention in high-risk HIV-positive persons by measuring change in VL, CD4 count, and self-reported adherence 12 months before and 12 months after the WelTel intervention was introduced. Inclusion criteria included VL ≥200 copies/mL, indication for treatment, and meeting vulnerability criteria. Participants were given a mobile phone with unlimited texting (where required), and weekly check-in text messages were sent for one year from the WelTel computer platform. Clinical data were collected for control and intervention years. Participants were followed by a multidisciplinary team in a clinical setting. Outcomes were assessed using Wilcoxon signed ranks tests for change in CD4 and VL from control year to study end and mixed-effects logistic regressions for change in cART adherence and appointment attendance. A secondary analysis was conducted to assess the effect of response rate on the outcome by modeling final log10 VL by number of responses while controlling for mean log10 VL in the control year. Results Eighty-five participants enrolled in the study, but 5 withdrew (final N=80). Participants were predominantly female (90%, 72/80) with a variety of vulnerabilities. Mean VL decreased from 1098 copies/mL in the control year to 439 copies/mL at study end (P=.004). Adherence to cART significantly improved (OR 1.14, IQR 1.10-1.18; P<.001), whereas appointment attendance decreased slightly with the intervention (OR 0.81, IQR 0.67-0.99; P=.03). A response was received for 46.57% (1753/3764) of messages sent and 9.62% (362/3764) of text messages sent were replied to with a problem. An outcome analysis examining relationship between reply rate and VL did not meet statistical significance (P=.07), but may be worthy of investigating further in a larger study. Conclusions WelTel may be an effective tool for improving cART adherence and reducing VLs among high-risk, vulnerable HIV-positive persons. Trial Registration Clinicaltrials.gov NCT02603536; https://clinicaltrials.gov/ct2/show/NCT02603536 (Archived by WebCite at http://www.webcitation.org/6qK57zCwv) PMID:28572079

Overview of qualitative research.

PubMed

Grossoehme, Daniel H

2014-01-01

Qualitative research methods are a robust tool for chaplaincy research questions. Similar to much of chaplaincy clinical care, qualitative research generally works with written texts, often transcriptions of individual interviews or focus group conversations and seeks to understand the meaning of experience in a study sample. This article describes three common methodologies: ethnography, grounded theory, and phenomenology. Issues to consider relating to the study sample, design, and analysis are discussed. Enhancing the validity of the data, as well reliability and ethical issues in qualitative research are described. Qualitative research is an accessible way for chaplains to contribute new knowledge about the sacred dimension of people's lived experience.

Using sentiment analysis to review patient satisfaction data located on the internet.

PubMed

Hopper, Anthony M; Uriyo, Maria

2015-01-01

The purpose of this paper is to test the usefulness of sentiment analysis and time-to-next-complaint methods in quantifying text-based information located on the internet. As important, the authors demonstrate how managers can use time-to-next-complaint techniques to organize sentiment analysis derived data into useful information, which can be shared with doctors and other staff. The authors used sentiment analysis to review patient feedback for a select group of gynecologists in Virginia. The authors utilized time-to-next-complaint methods along with other techniques to organize this data into meaningful information. The authors demonstrated that sentiment analysis and time-to-next-complaint techniques might be useful tools for healthcare managers who are interested in transforming web-based text into meaningful, quantifiable information. This study has several limitations. For one thing, neither the data set nor the techniques the authors used to analyze it will account for biases that resulted from selection issues related to gender, income, and culture, as well as from other socio-demographic concerns. Additionally, the authors lacked key data concerning patient volumes for the targeted physicians. Finally, it may be difficult to convince doctors to consider web-based comments as truthful, thereby preventing healthcare managers from using data located on the internet. The report illustrates some of the ways in which healthcare administrators can utilize sentiment analysis, along with time-to-next-complaint techniques, to mine web-based, patient comments for meaningful information. The paper is one of the first to illustrate ways in which administrators at clinics and physicians' offices can utilize sentiment analysis and time-to-next-complaint methods to analyze web-based patient comments.

Qualitative analysis of programmatic initiatives to text patients with mobile devices in resource-limited health systems.

PubMed

Garg, Sachin K; Lyles, Courtney R; Ackerman, Sara; Handley, Margaret A; Schillinger, Dean; Gourley, Gato; Aulakh, Veenu; Sarkar, Urmimala

2016-02-06

Text messaging is an affordable, ubiquitous, and expanding mobile communication technology. However, safety net health systems in the United States that provide more care to uninsured and low-income patients may face additional financial and infrastructural challenges in utilizing this technology. Formative evaluations of texting implementation experiences are limited. We interviewed safety net health systems piloting texting initiatives to study facilitators and barriers to real-world implementation. We conducted telephone interviews with various stakeholders who volunteered from each of the eight California-based safety net systems that received external funding to pilot a texting-based program of their choosing to serve a primary care need. We developed a semi-structured interview guide based partly on the Consolidated Framework for Implementation Research (CFIR), which encompasses several domains: the intervention, individuals involved, contextual factors, and implementation process. We inductively and deductively (using CFIR) coded transcripts, and categorized themes into facilitators and barriers. We performed eight interviews (one interview per pilot site). Five sites had no prior texting experience. Sites applied texting for programs related to medication adherence and monitoring, appointment reminders, care coordination, and health education and promotion. No site texted patient-identifying health information, and most sites manually obtained informed consent from each participating patient. Facilitators of implementation included perceived enthusiasm from patients, staff and management belief that texting is patient-centered, and the early identification of potential barriers through peer collaboration among grantees. Navigating government regulations that protect patient privacy and guide the handling of protected health information emerged as a crucial barrier. A related technical challenge in five sites was the labor-intensive tracking and documenting of texting communications due to an inability to integrate texting platforms with electronic health records. Despite enthusiasm for the texting programs from the involved individuals and organizations, inadequate data management capabilities and unclear privacy and security regulations for mobile health technology slowed the initial implementation and limited the clinical use of texting in the safety net and scope of pilots. Future implementation work and research should investigate how different texting platform and intervention designs affect efficacy, as well as explore issues that may affect sustainability and the scalability.

Are large dinners associated with excess weight, and does eating a smaller dinner achieve greater weight loss? A systematic review and meta-analysis.

PubMed

Fong, Mackenzie; Caterson, Ian D; Madigan, Claire D

2017-10-01

There are suggestions that large evening meals are associated with greater BMI. This study reviewed systematically the association between evening energy intake and weight in adults and aimed to determine whether reducing evening intake achieves weight loss. Databases searched were MEDLINE, PubMed, Cinahl, Web of Science, Cochrane Library of Clinical Trials, EMBASE and SCOPUS. Eligible observational studies investigated the relationship between BMI and evening energy intake. Eligible intervention trials compared weight change between groups where the proportion of evening intake was manipulated. Evening intake was defined as energy consumed during a certain time - for example 18.00-21.00 hours - or self-defined meal slots - that is 'dinner'. The search yielded 121 full texts that were reviewed for eligibility by two independent reviewers. In all, ten observational studies and eight clinical trials were included in the systematic review with four and five included in the meta-analyses, respectively. Four observational studies showed a positive association between large evening intake and BMI, five showed no association and one showed an inverse relationship. The meta-analysis of observational studies showed a non-significant trend between BMI and evening intake (P=0·06). The meta-analysis of intervention trials showed no difference in weight change between small and large dinner groups (-0·89 kg; 95 % CI -2·52, 0·75, P=0·29). This analysis was limited by significant heterogeneity, and many trials had an unknown or high risk of bias. Recommendations to reduce evening intake for weight loss cannot be substantiated by clinical evidence, and more well-controlled intervention trials are needed.

Statistical approaches in published ophthalmic clinical science papers: a comparison to statistical practice two decades ago.

PubMed

Zhang, Harrison G; Ying, Gui-Shuang

2018-02-09

The aim of this study is to evaluate the current practice of statistical analysis of eye data in clinical science papers published in British Journal of Ophthalmology ( BJO ) and to determine whether the practice of statistical analysis has improved in the past two decades. All clinical science papers (n=125) published in BJO in January-June 2017 were reviewed for their statistical analysis approaches for analysing primary ocular measure. We compared our findings to the results from a previous paper that reviewed BJO papers in 1995. Of 112 papers eligible for analysis, half of the studies analysed the data at an individual level because of the nature of observation, 16 (14%) studies analysed data from one eye only, 36 (32%) studies analysed data from both eyes at ocular level, one study (1%) analysed the overall summary of ocular finding per individual and three (3%) studies used the paired comparison. Among studies with data available from both eyes, 50 (89%) of 56 papers in 2017 did not analyse data from both eyes or ignored the intereye correlation, as compared with in 60 (90%) of 67 papers in 1995 (P=0.96). Among studies that analysed data from both eyes at an ocular level, 33 (92%) of 36 studies completely ignored the intereye correlation in 2017, as compared with in 16 (89%) of 18 studies in 1995 (P=0.40). A majority of studies did not analyse the data properly when data from both eyes were available. The practice of statistical analysis did not improve in the past two decades. Collaborative efforts should be made in the vision research community to improve the practice of statistical analysis for ocular data. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Economic Evaluation of Hospital and Community Pharmacy Services.

PubMed

Gammie, Todd; Vogler, Sabine; Babar, Zaheer-Ud-Din

2017-01-01

To review the international body of literature from 2010 to 2015 concerning methods of economic evaluations used in hospital- and community-based studies of pharmacy services in publicly funded health systems worldwide, their clinical outcomes, and economic effectiveness. The literature search was undertaken between May 2, 2015, and September 4, 2015. Keywords included "health economics" and "evaluation" "assessment" or "appraisal," "methods," "hospital" or "community" or "residential care," "pharmacy" or "pharmacy services" and "cost minimisation analysis" or "cost utility analysis" or "cost effectiveness analysis" or "cost benefit analysis." The databases searched included MEDLINE, PubMed, Google Scholar, Science Direct, Springer Links, and Scopus, and journals searched included PLoS One, PLoS Medicine, Nature, Health Policy, Pharmacoeconomics, The European Journal of Health Economics, Expert Review of Pharmacoeconomics and Outcomes Research, and Journal of Health Economics. Studies were selected on the basis of study inclusion criteria. These criteria included full-text original research articles undertaking an economic evaluation of hospital- or community-based pharmacy services in peer-reviewed scientific journals and in English, in countries with a publicly funded health system published between 2010 and 2015. 14 articles were included in this review. Cost-utility analysis (CUA) was the most utilized measure. Cost-minimization analysis (CMA) was not used by any studies. The limited use of cost-benefit analyses (CBAs) is likely a result of technical challenges in quantifying the cost of clinical benefits, risks, and outcomes. Hospital pharmacy services provided clinical benefits including improvements in patient health outcomes and reductions in adverse medication use, and all studies were considered cost-effective due to meeting a cost-utility (per quality-adjusted life year) threshold or were cost saving. Community pharmacy services were considered cost-effective in 8 of 10 studies. Economic evaluations of hospital and community pharmacy services are becoming increasingly commonplace to enable an understanding of which health care services provide value for money and to inform policy makers as to which services will be cost-effective in light of limited health care resources.

Accuracy of pedicle screw placement comparing robot-assisted technology and the free-hand with fluoroscopy-guided method in spine surgery: An updated meta-analysis.

PubMed

Fan, Yong; Du, Jin Peng; Liu, Ji Jun; Zhang, Jia Nan; Qiao, Huan Huan; Liu, Shi Chang; Hao, Ding Jun

2018-06-01

A miniature spine-mounted robot has recently been introduced to further improve the accuracy of pedicle screw placement in spine surgery. However, the differences in accuracy between the robotic-assisted (RA) technique and the free-hand with fluoroscopy-guided (FH) method for pedicle screw placement are controversial. A meta-analysis was conducted to focus on this problem. Several randomized controlled trials (RCTs) and cohort studies involving RA and FH and published before January 2017 were searched for using the Cochrane Library, Ovid, Web of Science, PubMed, and EMBASE databases. A total of 55 papers were selected. After the full-text assessment, 45 clinical trials were excluded. The final meta-analysis included 10 articles. The accuracy of pedicle screw placement within the RA group was significantly greater than the accuracy within the FH group (odds ratio 95%, "perfect accuracy" confidence interval: 1.38-2.07, P < .01; odds ratio 95% "clinically acceptable" Confidence Interval: 1.17-2.08, P < .01). There are significant differences in accuracy between RA surgery and FH surgery. It was demonstrated that the RA technique is superior to the conventional method in terms of the accuracy of pedicle screw placement.

Tooth wear against ceramic crowns in posterior region: a systematic literature review

PubMed Central

Hmaidouch, Rim; Weigl, Paul

2013-01-01

The objective of this systematic review was to assess tooth wear against ceramic crowns in posterior region in vitro and in vivo. An electronic PubMed search was conducted to identify studies on tooth wear against ceramic crowns in posterior region. The selected studies were analyzed in regard to type of crowns, natural antagonist, measuring protocol and outcome. From a yield of 1 000 titles, 43 articles were selected for full-text analysis; finally, no in vitro and only five in vivo studies met the inclusion criteria. As there is heterogeneity in design, used measuring method, ceramics and analysis-form, a meta-analysis was not possible. Results of these studies are very controversial which makes a scientifically valid comparison impossible. This review indicated that some all-ceramic crowns are as wear friendly as metal-ceramic crowns. Up to now, it has been impossible to associate tooth wear with any specific causal agent. The role of ceramic surface treatment that might be responsible for the changing in rate of tooth wear seems undetermined as yet through clinical trials. The literature reveals that studies on this topic are subject to a substantial amount of bias. Therefore, additional clinical studies, properly designed to diminish bias, are warranted. PMID:24136675

Change detection of medical images using dictionary learning techniques and principal component analysis.

PubMed

Nika, Varvara; Babyn, Paul; Zhu, Hongmei

2014-07-01

Automatic change detection methods for identifying the changes of serial MR images taken at different times are of great interest to radiologists. The majority of existing change detection methods in medical imaging, and those of brain images in particular, include many preprocessing steps and rely mostly on statistical analysis of magnetic resonance imaging (MRI) scans. Although most methods utilize registration software, tissue classification remains a difficult and overwhelming task. Recently, dictionary learning techniques are being used in many areas of image processing, such as image surveillance, face recognition, remote sensing, and medical imaging. We present an improved version of the EigenBlockCD algorithm, named the EigenBlockCD-2. The EigenBlockCD-2 algorithm performs an initial global registration and identifies the changes between serial MR images of the brain. Blocks of pixels from a baseline scan are used to train local dictionaries to detect changes in the follow-up scan. We use PCA to reduce the dimensionality of the local dictionaries and the redundancy of data. Choosing the appropriate distance measure significantly affects the performance of our algorithm. We examine the differences between [Formula: see text] and [Formula: see text] norms as two possible similarity measures in the improved EigenBlockCD-2 algorithm. We show the advantages of the [Formula: see text] norm over the [Formula: see text] norm both theoretically and numerically. We also demonstrate the performance of the new EigenBlockCD-2 algorithm for detecting changes of MR images and compare our results with those provided in the recent literature. Experimental results with both simulated and real MRI scans show that our improved EigenBlockCD-2 algorithm outperforms the previous methods. It detects clinical changes while ignoring the changes due to the patient's position and other acquisition artifacts.

The Evaluation of a Temporal Reasoning System in Processing Clinical Discharge Summaries

PubMed Central

Zhou, Li; Parsons, Simon; Hripcsak, George

2008-01-01

Context TimeText is a temporal reasoning system designed to represent, extract, and reason about temporal information in clinical text. Objective To measure the accuracy of the TimeText for processing clinical discharge summaries. Design Six physicians with biomedical informatics training served as domain experts. Twenty discharge summaries were randomly selected for the evaluation. For each of the first 14 reports, 5 to 8 clinically important medical events were chosen. The temporal reasoning system generated temporal relations about the endpoints (start or finish) of pairs of medical events. Two experts (subjects) manually generated temporal relations for these medical events. The system and expert-generated results were assessed by four other experts (raters). All of the twenty discharge summaries were used to assess the system’s accuracy in answering time-oriented clinical questions. For each report, five to ten clinically plausible temporal questions about events were generated. Two experts generated answers to the questions to serve as the gold standard. We wrote queries to retrieve answers from system’s output. Measurements Correctness of generated temporal relations, recall of clinically important relations, and accuracy in answering temporal questions. Results The raters determined that 97% of subjects’ 295 generated temporal relations were correct and that 96.5% of the system’s 995 generated temporal relations were correct. The system captured 79% of 307 temporal relations determined to be clinically important by the subjects and raters. The system answered 84% of the temporal questions correctly. Conclusion The system encoded the majority of information identified by experts, and was able to answer simple temporal questions. PMID:17947618

[Text mining, a method for computer-assisted analysis of scientific texts, demonstrated by an analysis of author networks].

PubMed

Hahn, P; Dullweber, F; Unglaub, F; Spies, C K

2014-06-01

Searching for relevant publications is becoming more difficult with the increasing number of scientific articles. Text mining as a specific form of computer-based data analysis may be helpful in this context. Highlighting relations between authors and finding relevant publications concerning a specific subject using text analysis programs are illustrated graphically by 2 performed examples. © Georg Thieme Verlag KG Stuttgart · New York.

An evaluation of computer assisted clinical classification algorithms.

PubMed

Chute, C G; Yang, Y; Buntrock, J

1994-01-01

The Mayo Clinic has a long tradition of indexing patient records in high resolution and volume. Several algorithms have been developed which promise to help human coders in the classification process. We evaluate variations on code browsers and free text indexing systems with respect to their speed and error rates in our production environment. The more sophisticated indexing systems save measurable time in the coding process, but suffer from incompleteness which requires a back-up system or human verification. Expert Network does the best job of rank ordering clinical text, potentially enabling the creation of thresholds for the pass through of computer coded data without human review.

Integrated clinical workstations for image and text data capture, display, and teleconsultation.

PubMed

Dayhoff, R; Kuzmak, P M; Kirin, G

1994-01-01

The Department of Veterans Affairs (VA) DHCP Imaging System digitally records clinically significant diagnostic images selected by medical specialists in a variety of hospital departments, including radiology, cardiology, gastroenterology, pathology, dermatology, hematology, surgery, podiatry, dental clinic, and emergency room. These images, which include true color and gray scale images, scanned documents, and electrocardiogram waveforms, are stored on network file servers and displayed on workstations located throughout a medical center. All images are managed by the VA's hospital information system (HIS), allowing integrated displays of text and image data from all medical specialties. Two VA medical centers currently have DHCP Imaging Systems installed, and other installations are underway.

A Review of Evidence Presented in Support of Three Key Claims in the Validity Argument for the "TextEvaluator"® Text Analysis Tool. Research Report. ETS RR-16-12

ERIC Educational Resources Information Center

Sheehan, Kathleen M.

2016-01-01

The "TextEvaluator"® text analysis tool is a fully automated text complexity evaluation tool designed to help teachers and other educators select texts that are consistent with the text complexity guidelines specified in the Common Core State Standards (CCSS). This paper provides an overview of the TextEvaluator measurement approach and…

"It´s incredible how much I´ve had to fight." Negotiating medical uncertainty in clinical encounters.

PubMed

Lian, Olaug S; Robson, Catherine

2017-01-01

Clinical encounters related to medically unexplained physical symptoms (MUPS) are associated with high levels of conflict between patients and doctors. Collaborative difficulties are fused by the medical uncertainty that dominates these consultations. The main aim of this study is to explore the interactional dynamics of clinical encounters riddled by medical uncertainty, as experienced by people living with long-term medically unexplained fatigue in Norway. A qualitative thematic analysis of written texts from 256 study participants. We found that patients experience being met with disbelief, inappropriate psychological explanations, marginalisation of experiences, disrespectful treatment, lack of physical examination and damaging health advice. The main source of their discontent is not the lack of biomedical knowledge, but doctors who fail to communicate acknowledgement of patients' experiences, knowledge and autonomy. War metaphors are emblematic of how participants describe their medical encounters. The overarching storyline depicts experiences of being caught in a power struggle with doctors and health systems, fused by a lack of common conceptual ground. When physical symptoms cannot be detected, explained and managed by biomedical knowledge and technology, good doctor-patient partnerships are crucial. Without clearly acknowledging patients' perspectives and capabilities in clinical practice, such partnerships cannot be achieved.

Case-based lung image categorization and retrieval for interstitial lung diseases: clinical workflows.

PubMed

Depeursinge, Adrien; Vargas, Alejandro; Gaillard, Frédéric; Platon, Alexandra; Geissbuhler, Antoine; Poletti, Pierre-Alexandre; Müller, Henning

2012-01-01

Clinical workflows and user interfaces of image-based computer-aided diagnosis (CAD) for interstitial lung diseases in high-resolution computed tomography are introduced and discussed. Three use cases are implemented to assist students, radiologists, and physicians in the diagnosis workup of interstitial lung diseases. In a first step, the proposed system shows a three-dimensional map of categorized lung tissue patterns with quantification of the diseases based on texture analysis of the lung parenchyma. Then, based on the proportions of abnormal and normal lung tissue as well as clinical data of the patients, retrieval of similar cases is enabled using a multimodal distance aggregating content-based image retrieval (CBIR) and text-based information search. The global system leads to a hybrid detection-CBIR-based CAD, where detection-based and CBIR-based CAD show to be complementary both on the user's side and on the algorithmic side. The proposed approach is in accordance with the classical workflow of clinicians searching for similar cases in textbooks and personal collections. The developed system enables objective and customizable inter-case similarity assessment, and the performance measures obtained with a leave-one-patient-out cross-validation (LOPO CV) are representative of a clinical usage of the system.

Text-interpreter language for flexible generation of patient notes and instructions.

PubMed

Forker, T S

1992-01-01

An interpreted computer language has been developed along with a windowed user interface and multi-printer-support formatter to allow preparation of documentation of patient visits, including progress notes, prescriptions, excuses for work/school, outpatient laboratory requisitions, and patient instructions. Input is by trackball or mouse with little or no keyboard skill required. For clinical problems with specific protocols, the clinician can be prompted with problem-specific items of history, exam, and lab data to be gathered and documented. The language implements a number of text-related commands as well as branching logic and arithmetic commands. In addition to generating text, it is simple to implement arithmetic calculations such as weight-specific drug dosages; multiple branching decision-support protocols for paramedical personnel (or physicians); and calculation of clinical scores (e.g., coma or trauma scores) while simultaneously documenting the status of each component of the score. ASCII text files produced by the interpreter are available for computerized quality audit. Interpreter instructions are contained in text files users can customize with any text editor.

Circulating Tumor DNA Analysis in Patients With Cancer: American Society of Clinical Oncology and College of American Pathologists Joint Review.

PubMed

Merker, Jason D; Oxnard, Geoffrey R; Compton, Carolyn; Diehn, Maximilian; Hurley, Patricia; Lazar, Alexander J; Lindeman, Neal; Lockwood, Christina M; Rai, Alex J; Schilsky, Richard L; Tsimberidou, Apostolia M; Vasalos, Patricia; Billman, Brooke L; Oliver, Thomas K; Bruinooge, Suanna S; Hayes, Daniel F; Turner, Nicholas C

2018-06-01

Purpose Clinical use of analytical tests to assess genomic variants in circulating tumor DNA (ctDNA) is increasing. This joint review from ASCO and the College of American Pathologists summarizes current information about clinical ctDNA assays and provides a framework for future research. Methods An Expert Panel conducted a literature review on the use of ctDNA assays for solid tumors, including pre-analytical variables, analytical validity, interpretation and reporting, and clinical validity and utility. Results The literature search identified 1,338 references. Of those, 390, plus 31 references supplied by the Expert Panel, were selected for full-text review. There were 77 articles selected for inclusion. Conclusion The evidence indicates that testing for ctDNA is optimally performed on plasma collected in cell stabilization or EDTA tubes, with EDTA tubes processed within 6 hours of collection. Some ctDNA assays have demonstrated clinical validity and utility with certain types of advanced cancer; however, there is insufficient evidence of clinical validity and utility for the majority of ctDNA assays in advanced cancer. Evidence shows discordance between the results of ctDNA assays and genotyping tumor specimens and supports tumor tissue genotyping to confirm undetected results from ctDNA tests. There is no evidence of clinical utility and little evidence of clinical validity of ctDNA assays in early-stage cancer, treatment monitoring, or residual disease detection. There is no evidence of clinical validity and clinical utility to suggest that ctDNA assays are useful for cancer screening, outside of a clinical trial. Given the rapid pace of research, re-evaluation of the literature will shortly be required, along with the development of tools and guidance for clinical practice.

Automated ancillary cancer history classification for mesothelioma patients from free-text clinical reports

PubMed Central

Wilson, Richard A.; Chapman, Wendy W.; DeFries, Shawn J.; Becich, Michael J.; Chapman, Brian E.

2010-01-01

Background: Clinical records are often unstructured, free-text documents that create information extraction challenges and costs. Healthcare delivery and research organizations, such as the National Mesothelioma Virtual Bank, require the aggregation of both structured and unstructured data types. Natural language processing offers techniques for automatically extracting information from unstructured, free-text documents. Methods: Five hundred and eight history and physical reports from mesothelioma patients were split into development (208) and test sets (300). A reference standard was developed and each report was annotated by experts with regard to the patient’s personal history of ancillary cancer and family history of any cancer. The Hx application was developed to process reports, extract relevant features, perform reference resolution and classify them with regard to cancer history. Two methods, Dynamic-Window and ConText, for extracting information were evaluated. Hx’s classification responses using each of the two methods were measured against the reference standard. The average Cohen’s weighted kappa served as the human benchmark in evaluating the system. Results: Hx had a high overall accuracy, with each method, scoring 96.2%. F-measures using the Dynamic-Window and ConText methods were 91.8% and 91.6%, which were comparable to the human benchmark of 92.8%. For the personal history classification, Dynamic-Window scored highest with 89.2% and for the family history classification, ConText scored highest with 97.6%, in which both methods were comparable to the human benchmark of 88.3% and 97.2%, respectively. Conclusion: We evaluated an automated application’s performance in classifying a mesothelioma patient’s personal and family history of cancer from clinical reports. To do so, the Hx application must process reports, identify cancer concepts, distinguish the known mesothelioma from ancillary cancers, recognize negation, perform reference resolution and determine the experiencer. Results indicated that both information extraction methods tested were dependant on the domain-specific lexicon and negation extraction. We showed that the more general method, ConText, performed as well as our task-specific method. Although Dynamic- Window could be modified to retrieve other concepts, ConText is more robust and performs better on inconclusive concepts. Hx could greatly improve and expedite the process of extracting data from free-text, clinical records for a variety of research or healthcare delivery organizations. PMID:21031012

An Experiment Comparing Lexical and Statistical Methods for Extracting MeSH Terms from Clinical Free Text

PubMed Central

Cooper, Gregory F.; Miller, Randolph A.

1998-01-01

Abstract Objective: A primary goal of the University of Pittsburgh's 1990-94 UMLS-sponsored effort was to develop and evaluate PostDoc (a lexical indexing system) and Pindex (a statistical indexing system) comparatively, and then in combination as a hybrid system. Each system takes as input a portion of the free text from a narrative part of a patient's electronic medical record and returns a list of suggested MeSH terms to use in formulating a Medline search that includes concepts in the text. This paper describes the systems and reports an evaluation. The intent is for this evaluation to serve as a step toward the eventual realization of systems that assist healthcare personnel in using the electronic medical record to construct patient-specific searches of Medline. Design: The authors tested the performances of PostDoc, Pindex, and a hybrid system, using text taken from randomly selected clinical records, which were stratified to include six radiology reports, six pathology reports, and six discharge summaries. They identified concepts in the clinical records that might conceivably be used in performing a patient-specific Medline search. Each system was given the free text of each record as an input. The extent to which a system-derived list of MeSH terms captured the relevant concepts in these documents was determined based on blinded assessments by the authors. Results: PostDoc output a mean of approximately 19 MeSH terms per report, which included about 40% of the relevant report concepts. Pindex output a mean of approximately 57 terms per report and captured about 45% of the relevant report concepts. A hybrid system captured approximately 66% of the relevant concepts and output about 71 terms per report. Conclusion: The outputs of PostDoc and Pindex are complementary in capturing MeSH terms from clinical free text. The results suggest possible approaches to reduce the number of terms output while maintaining the percentage of terms captured, including the use of UMLS semantic types to constrain the output list to contain only clinically relevant MeSH terms. PMID:9452986

Use of mobile phones and text messaging to decrease the turnaround time for early infant HIV diagnosis and notification in rural Zambia: an observational study.

PubMed

Sutcliffe, Catherine G; Thuma, Philip E; van Dijk, Janneke H; Sinywimaanzi, Kathy; Mweetwa, Sydney; Hamahuwa, Mutinta; Moss, William J

2017-03-08

Early infant diagnosis of HIV infection is challenging in rural sub-Saharan Africa as blood samples are sent to central laboratories for HIV DNA testing, leading to delays in diagnosis and treatment initiation. Simple technologies to rapidly deliver results to clinics and notify mothers of test results would decrease many of these delays. The feasibility of using mobile phones to contact mothers was evaluated. In addition, the first two years of implementation of a national short message service (SMS) reporting system to deliver test results from the laboratory to the clinic were evaluated. The study was conducted in Macha, Zambia from 2013 to 2015 among mothers of HIV-exposed infants. Mothers were interviewed about mobile phone use and willingness to be contacted directly or through their rural health center. Mothers were contacted according to their preferred method of communication when test results were available. Mothers of positive infants were asked to return to the clinic as soon as possible. Dates of sample collection, delivery of test results to the clinic and notification of mothers were documented in addition to test results. Four hundred nineteen mothers and infants were enrolled. Only 30% of mothers had ever used a mobile phone. 96% of mobile phone owners were reached by study staff and 98% of mothers without mobile phones were contacted through their rural health center. Turnaround times for mothers of positive infants were approximately 2 weeks shorter than for mothers of negative infants. Delivery of test results by the national SMS system improved from 2013 to 2014, with increases in the availability of texted results (38 vs. 91%) and arrival of the texted result prior to the hardcopy report (27 vs. 83%). Texted results arriving at the clinic before the hardcopy were received a median of 19 days earlier. Four discrepancies between texted and hardcopy results were identified out of 340 tests. Mobile phone and text messaging technology has the potential to improve early infant diagnosis but challenges to widespread implementation need to be addressed, including low mobile phone ownership, use and coverage in rural areas.

Presentation approaches for enhancing interpretability of patient-reported outcomes (PROs) in meta-analysis: a protocol for a systematic survey of Cochrane reviews.

PubMed

Devji, Tahira; Johnston, Bradley C; Patrick, Donald L; Bhandari, Mohit; Thabane, Lehana; Guyatt, Gordon H

2017-09-27

Meta-analyses of clinical trials often provide sufficient information for decision-makers to evaluate whether chance can explain apparent differences between interventions. Interpretation of the magnitude and importance of treatment effects beyond statistical significance can, however, be challenging, particularly for patient-reported outcomes (PROs) measured using questionnaires with which clinicians have limited familiarity. The objectives of our study are to systematically evaluate Cochrane systematic review authors' approaches to calculation, reporting and interpretation of pooled estimates of patient-reported outcome measures (PROMs) in meta-analyses. We will conduct a methodological survey of a random sample of Cochrane systematic reviews published from 1 January 2015 to 1 April 2017 that report at least one statistically significant pooled result for at least one PRO in the abstract. Author pairs will independently review all titles, abstracts and full texts identified by the literature search, and they will extract data using a standardised data extraction form. We will extract the following: year of publication, number of included trials, number of included participants, clinical area, type of intervention(s) and control(s), type of meta-analysis and use of the Grading of Recommendations, Assessment, Development and Evaluation approach to rate the quality of evidence, as well as information regarding the characteristics of PROMs, calculation and presentation of PROM effect estimates and interpretation of PROM effect estimates. We will document and summarise the methods used for the analysis, reporting and interpretation of each summary effect measure. We will summarise categorical variables with frequencies and percentages and continuous outcomes as means and/or medians and associated measures of dispersion. Ethics approval for this study is not required. We will disseminate the results of this review in peer-reviewed publications and conference presentations. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Variability in Objective Refraction for Persons with Down Syndrome.

PubMed

Marsack, Jason D; Ravikumar, Ayeswarya; Benoit, Julia S; Anderson, Heather A

2017-05-01

Down syndrome (DS) is associated with ocular and cognitive sequelae, which both have the potential to influence clinical measures of refractive error. This study compares variability of autorefraction among subjects with and without DS. Grand Seiko autorefraction was performed on 139 subjects with DS (age: 8-55, mean: 25 ± 9 yrs) and 138 controls (age: 7-59, mean: 25 ± 10 yrs). Subjects with three refraction measures per eye (DS: 113, control: 136) were included for analysis. Each refraction was converted to power vector notation (M, J0, J45) and a difference in each component (ΔM, ΔJ0, ΔJ45) was calculated for each refraction pairing. From these quantities, average dioptric strength ((Equation is included in full-text article.): square root of the sum of the squares of M, J0, and J45) and average dioptric difference ((Equation is included in full-text article.): square root of the sum of the squares of ΔM, ΔJ0, and ΔJ45) were calculated. The DS group exhibited a greater median (Equation is included in full-text article.)(1Q: 1.38D M: 2.38D 3Q: 3.41D) than control eyes (1Q: 0.47D M: 0.96D 3Q: 2.75D) (P < .001). Likewise, the DS group exhibited a greater median (Equation is included in full-text article.)in refraction (1Q: 0.27D M: 0.42D 3Q: 0.78D) than control eyes (1Q: 0.11D M: 0.15D 3Q: 0.23D) (P < .001) with 97.1% of control eyes exhibiting (Equation is included in full-text article.)≤0.50D, compared to 59.3% of DS eyes. An effect of (Equation is included in full-text article.)on (Equation is included in full-text article.)was not detected (P = .3009) nor was a significant interaction between (Equation is included in full-text article.)and group detected (P = .49). In the current study, comparing three autorefraction readings, median total dioptric difference with autorefraction in DS was 2.8 times the levels observed in controls, indicating greater potential uncertainty in objective measures of refraction for this population. The analysis demonstrates that J45 is highly contributory to the observed variability.

Physician satisfaction with a critical care clinical information system using a multimethod evaluation of usability.

PubMed

Hudson, Darren; Kushniruk, Andre; Borycki, Elizabeth; Zuege, Danny J

2018-04-01

Physician satisfaction with electronic medical records has often been poor. Usability has frequently been identified as a source for decreased satisfaction. While surveys can identify many issues, and are logistically easier to administer, they may miss issues identified using other methods This study sought to understand the level of physician satisfaction and usability issues associated with a critical care clinical information system (eCritical Alberta) implemented throughout the province of Alberta, Canada. All critical care attending physicians using the system were invited to participate in an online survey. Questions included components of the User Acceptance of Information Technology and Usability Questionnaire as well as free text feedback on system components. Physicians were also invited to participate in a think aloud test using simulated scenarios. The transcribed think aloud text and questionnaire were subjected to textual analysis. 82% of all eligible physicians completed the on-line survey (n = 61). Eight physicians were invited and seven completed the think aloud test. Overall satisfaction with the system was moderate. Usability was identified as a significant factor contributing to satisfaction. The major usability factors identified were system response time and layout. The think aloud component identified additional factors beyond those identified in the on-line survey. This study found a modestly high level of physician satisfaction with a province-wide clinical critical care information system. Usability continues to be a significant factor in physician satisfaction. Using multiple methods of evaluation can capture the benefits of a large sample size and deeper understanding of the issues. Copyright © 2018 Elsevier B.V. All rights reserved.

Normalization of relative and incomplete temporal expressions in clinical narratives.

PubMed

Sun, Weiyi; Rumshisky, Anna; Uzuner, Ozlem

2015-09-01

To improve the normalization of relative and incomplete temporal expressions (RI-TIMEXes) in clinical narratives. We analyzed the RI-TIMEXes in temporally annotated corpora and propose two hypotheses regarding the normalization of RI-TIMEXes in the clinical narrative domain: the anchor point hypothesis and the anchor relation hypothesis. We annotated the RI-TIMEXes in three corpora to study the characteristics of RI-TMEXes in different domains. This informed the design of our RI-TIMEX normalization system for the clinical domain, which consists of an anchor point classifier, an anchor relation classifier, and a rule-based RI-TIMEX text span parser. We experimented with different feature sets and performed an error analysis for each system component. The annotation confirmed the hypotheses that we can simplify the RI-TIMEXes normalization task using two multi-label classifiers. Our system achieves anchor point classification, anchor relation classification, and rule-based parsing accuracy of 74.68%, 87.71%, and 57.2% (82.09% under relaxed matching criteria), respectively, on the held-out test set of the 2012 i2b2 temporal relation challenge. Experiments with feature sets reveal some interesting findings, such as: the verbal tense feature does not inform the anchor relation classification in clinical narratives as much as the tokens near the RI-TIMEX. Error analysis showed that underrepresented anchor point and anchor relation classes are difficult to detect. We formulate the RI-TIMEX normalization problem as a pair of multi-label classification problems. Considering only RI-TIMEX extraction and normalization, the system achieves statistically significant improvement over the RI-TIMEX results of the best systems in the 2012 i2b2 challenge. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Does restoration of focal lumbar lordosis for single level degenerative spondylolisthesis result in better patient-reported clinical outcomes? A systematic literature review.

PubMed

Rhee, Chanseok; Visintini, Sarah; Dunning, Cynthia E; Oxner, William M; Glennie, R Andrew

2017-10-01

It is controversial whether the surgical restoration of sagittal balance and spinopelvic angulation in a single level lumbar degenerative spondylolisthesis results in clinical improvements. The purpose of this study to systematically review the available literature to determine whether the surgical correction of malalignment in lumbar degenerative spondylolisthesis correlates with improvements in patient-reported clinical outcomes. Literature searches were performed via Ovid Medline, Embase, CENTRAL and Web of Science using search terms "lumbar," "degenerative/spondylolisthesis" and "surgery/surgical/surgeries/fusion". This resulted in 844 articles and after reviewing the abstracts and full-texts, 13 articles were included for summary and final analysis. There were two Level II articles, four Level III articles and five Level IV articles. Most commonly used patient-reported outcome measures (PROMs) were Oswestery disability index (ODI) and visual analogue scale (VAS). Four articles were included for the final statistical analysis. There was no statistically significant difference between the patient groups who achieved successful surgical correction of malalignment and those who did not for either ODI (mean difference -0.94, CI -8.89-7.00) or VAS (mean difference 1.57, CI -3.16-6.30). Two studies assessed the efficacy of manual reduction of lumbar degenerative spondylolisthesis and their clinical outcomes after the operation, and there was no statistically significant improvement. Overall, the restoration of focal lumbar lordosis and restoration of sagittal balance for single-level lumbar degenerative spondylolisthesis does not seem to yield clinical improvements but well-powered studies on this specific topic is lacking in the current literature. Future well-powered studies are needed for a more definitive conclusion. Copyright © 2017 Elsevier Ltd. All rights reserved.

Exploration of contextual factors in a successful quality improvement collaborative in English ambulance services: cross-sectional survey.

PubMed

Phung, Viet-Hai; Essam, Nadya; Asghar, Zahid; Spaight, Anne; Siriwardena, Aloysius N

2016-02-01

Clinical leadership and organizational culture are important contextual factors for quality improvement (QI) but the relationship between these and with organizational change is complex and poorly understood. We aimed to explore the relationship between clinical leadership, culture of innovation and clinical engagement in QI within a national ambulance QI Collaborative (QIC). We used a self-administered online questionnaire survey sent to front-line clinicians in all 12 English ambulance services. We conducted a cross-sectional analysis of quantitative data and qualitative analysis of free-text responses. There were 2743 (12% of 22 117) responses from 11 of the 12 participating ambulance services. In the 3% of responders that were directly involved with the QIC, leadership behaviour was significantly higher than for those not directly involved. QIC involvement made no significant difference to responders' perceptions of the culture of innovation in their organization, which was generally considered poor. Although uptake of QI methods was low overall, QIC members were significantly more likely to use QI methods, which were also significantly associated with leadership behaviour. Despite a limited organizational culture of innovation, clinical leadership and use of QI methods in ambulance services generally, the QIC achieved its aims to significantly improve pre-hospital care for acute myocardial infarction and stroke. We postulate that this was mediated through an improvement subculture, linked to the QIC, which facilitated large-scale improvement by stimulating leadership and QI methods. Further research is needed to understand success factors for QI in complex health care environments. © 2016 The Authors. Journal of Evaluation in Clinical Practice published by John Wiley & Sons, Ltd.

[Educative strategy evaluation to improve critical reading skills on clinical research texts in second year gyneco-obstetrics residents].

PubMed

Carranza Lira, Sebastián; Arce Herrera, Rosa María; González González, Patricia

2007-11-01

The educative models and strategies to achieve a significant learning have a wide variety. The development of clinical aptitude for clinical research papers lecture has an important place to maintain the physician actualized and for resident formation. To evaluate the degree of development of the aptitude for the reading of clinical research articles in 2nd grade residents of the gynecology and obstetrics speciality alter an educative strategy. In 16 2nd year gynecology and obstetrics residents, a previously validated instrument was applied for the evaluation of critical lecture of clinical research articles in general medicine previous and after and educative strategy. Statistical analysis was with Kruskal-Wallis analysis of variance. Also Wilcoxon test was used to assess the differences between baseline and final results. The median of age was 27 (24-31) years, gender 56.3% women and 43.8% men. A statistically significant increase in global score was observed after the educative strategy. After it only there was a significant increase in the indicator to interpret. After evaluating the domain degrees according to the indicator to interpret, in baseline evaluation it predominated the very low level and at the final evaluation the very low and low levels. In the indicator to judge at baseline the majority were in the very low level, and at the end in very low and low levels. According to the indicator to propose at baseline all were in the level expected by hazard, and at the end a minimal proportion was at very low level. These results traduce a discrete improvement in critical lecture process, which makes to consider the educative strategy that was used, since the objective to improve critical lecture capacity was not achieved.

A Concept–Wide Association Study of Clinical Notes to Discover New Predictors of Kidney Failure

PubMed Central

Betensky, Rebecca A.; Wright, Adam; Curhan, Gary C.; Bates, David W.; Waikar, Sushrut S.

2016-01-01

Background and objectives Identifying predictors of kidney disease progression is critical toward the development of strategies to prevent kidney failure. Clinical notes provide a unique opportunity for big data approaches to identify novel risk factors for disease. Design, setting, participants, & measurements We used natural language processing tools to extract concepts from the preceding year’s clinical notes among patients newly referred to a tertiary care center’s outpatient nephrology clinics and retrospectively evaluated these concepts as predictors for the subsequent development of ESRD using proportional subdistribution hazards (competing risk) regression. The primary outcome was time to ESRD, accounting for a competing risk of death. We identified predictors from univariate and multivariate (adjusting for Tangri linear predictor) models using a 5% threshold for false discovery rate (q value <0.05). We included all patients seen by an adult outpatient nephrologist between January 1, 2004 and June 18, 2014 and excluded patients seen only by transplant nephrology, with preexisting ESRD, with fewer than five clinical notes, with no follow-up, or with no baseline creatinine values. Results Among the 4013 patients selected in the final study cohort, we identified 960 concepts in the unadjusted analysis and 885 concepts in the adjusted analysis. Novel predictors identified included high–dose ascorbic acid (adjusted hazard ratio, 5.48; 95% confidence interval, 2.80 to 10.70; q<0.001) and fast food (adjusted hazard ratio, 4.34; 95% confidence interval, 2.55 to 7.40; q<0.001). Conclusions Novel predictors of human disease may be identified using an unbiased approach to analyze text from the electronic health record. PMID:27927892

TextHunter – A User Friendly Tool for Extracting Generic Concepts from Free Text in Clinical Research

PubMed Central

Jackson MSc, Richard G.; Ball, Michael; Patel, Rashmi; Hayes, Richard D.; Dobson, Richard J.B.; Stewart, Robert

2014-01-01

Observational research using data from electronic health records (EHR) is a rapidly growing area, which promises both increased sample size and data richness - therefore unprecedented study power. However, in many medical domains, large amounts of potentially valuable data are contained within the free text clinical narrative. Manually reviewing free text to obtain desired information is an inefficient use of researcher time and skill. Previous work has demonstrated the feasibility of applying Natural Language Processing (NLP) to extract information. However, in real world research environments, the demand for NLP skills outweighs supply, creating a bottleneck in the secondary exploitation of the EHR. To address this, we present TextHunter, a tool for the creation of training data, construction of concept extraction machine learning models and their application to documents. Using confidence thresholds to ensure high precision (>90%), we achieved recall measurements as high as 99% in real world use cases. PMID:25954379

Can Aidi injection restore cellular immunity and improve clinical efficacy in non-small-cell lung cancer patients treated with platinum-based chemotherapy? A meta-analysis of 17 randomized controlled trials following the PRISMA guidelines.

PubMed

Xiao, Zheng; Wang, Chengqiong; Sun, Yongping; Li, Nana; Li, Jing; Chen, Ling; Yao, Xingsheng; Ding, Jie; Ma, Hu

2016-11-01

Aidi injection is an adjuvant chemotherapy drug commonly used in China. Can Aidi injection restore the cellular immunity and improve the clinical efficacy in non-small-cell lung cancer (NSCLC) patients treated with platinum-based chemotherapy? There is a lack of strong evidence to prove it. To further reveal it, we systematically evaluated all related studies. We collected all studies about the clinical efficacy and cellular immunity of Aidi injection plus platinum-based chemotherapy for NSCLC in Medline, Embase, Web of Science, China national knowledge infrastructure database (CNKI), Chinese Scientific Journals Full-Text Database (VIP), Wanfang, China biological medicine database (CBM) (established to June 2015), Cochrane Central Register of Controlled Trials (CCRCT) (June 2015), Chinese clinical trial registry, and US-clinical trials (June 2015). We evaluated their quality according to the Cochrane evaluation handbook of randomized controlled trials (RCTs) (5.1.0), extracted data following the patient intervention control group outcomes principles and synthesized the data by meta-analysis. Seventeen (RCTs) with 1390 NSCLC patients were included, with general methodological quality in most trials. The merged relative risk (RR) values and their 95% CI of meta-analysis for objective response rate (ORR) and disease control rate (DCR) were as follows: 1.26 (1.12, 1.42) and 1.11(1.04, 1.17). The merged standardized mean difference (SMD) values and their 95% CI of meta-analysis for the percentage of CD3T cells, CD4T cells, CD8T cells, natural killer (NK) cells, and CD4/CD8 T cell ratio were as follows: 1.41, (0.89, 1.92), 1.59, (1.07, 2.11), 0.85, (0.38, 1.33), 1.64 (0.89, 2.39) and 0.91, (0.58, 1.24). Compared with platinum-based chemotherapy alone, all differences were statistically significant. These results might be overestimated or underestimated. Aidi injection plus platinum-based chemotherapy can improve the clinical efficacy of patients with NSCLC. Aidi injection could significantly restore the cellular immunity damaged by platinum-based chemotherapy. It may be an important tumor immune modulator and protector for patients with NSCLC treated with chemotherapy.

A comparison of three clustering methods for finding subgroups in MRI, SMS or clinical data: SPSS TwoStep Cluster analysis, Latent Gold and SNOB.

PubMed

Kent, Peter; Jensen, Rikke K; Kongsted, Alice

2014-10-02

There are various methodological approaches to identifying clinically important subgroups and one method is to identify clusters of characteristics that differentiate people in cross-sectional and/or longitudinal data using Cluster Analysis (CA) or Latent Class Analysis (LCA). There is a scarcity of head-to-head comparisons that can inform the choice of which clustering method might be suitable for particular clinical datasets and research questions. Therefore, the aim of this study was to perform a head-to-head comparison of three commonly available methods (SPSS TwoStep CA, Latent Gold LCA and SNOB LCA). The performance of these three methods was compared: (i) quantitatively using the number of subgroups detected, the classification probability of individuals into subgroups, the reproducibility of results, and (ii) qualitatively using subjective judgments about each program's ease of use and interpretability of the presentation of results.We analysed five real datasets of varying complexity in a secondary analysis of data from other research projects. Three datasets contained only MRI findings (n = 2,060 to 20,810 vertebral disc levels), one dataset contained only pain intensity data collected for 52 weeks by text (SMS) messaging (n = 1,121 people), and the last dataset contained a range of clinical variables measured in low back pain patients (n = 543 people). Four artificial datasets (n = 1,000 each) containing subgroups of varying complexity were also analysed testing the ability of these clustering methods to detect subgroups and correctly classify individuals when subgroup membership was known. The results from the real clinical datasets indicated that the number of subgroups detected varied, the certainty of classifying individuals into those subgroups varied, the findings had perfect reproducibility, some programs were easier to use and the interpretability of the presentation of their findings also varied. The results from the artificial datasets indicated that all three clustering methods showed a near-perfect ability to detect known subgroups and correctly classify individuals into those subgroups. Our subjective judgement was that Latent Gold offered the best balance of sensitivity to subgroups, ease of use and presentation of results with these datasets but we recognise that different clustering methods may suit other types of data and clinical research questions.

Integrating mobile-phone based assessment for psychosis into people's everyday lives and clinical care: a qualitative study.

PubMed

Palmier-Claus, Jasper E; Rogers, Anne; Ainsworth, John; Machin, Matt; Barrowclough, Christine; Laverty, Louise; Barkus, Emma; Kapur, Shitij; Wykes, Til; Lewis, Shôn W

2013-01-23

Over the past decade policy makers have emphasised the importance of healthcare technology in the management of long-term conditions. Mobile-phone based assessment may be one method of facilitating clinically- and cost-effective intervention, and increasing the autonomy and independence of service users. Recently, text-message and smartphone interfaces have been developed for the real-time assessment of symptoms in individuals with schizophrenia. Little is currently understood about patients' perceptions of these systems, and how they might be implemented into their everyday routine and clinical care. 24 community based individuals with non-affective psychosis completed a randomised repeated-measure cross-over design study, where they filled in self-report questions about their symptoms via text-messages on their own phone, or via a purpose designed software application for Android smartphones, for six days. Qualitative interviews were conducted in order to explore participants' perceptions and experiences of the devices, and thematic analysis was used to analyse the data. Three themes emerged from the data: i) the appeal of usability and familiarity, ii) acceptability, validity and integration into domestic routines, and iii) perceived impact on clinical care. Although participants generally found the technology non-stigmatising and well integrated into their everyday activities, the repetitiveness of the questions was identified as a likely barrier to long-term adoption. Potential benefits to the quality of care received were seen in terms of assisting clinicians, faster and more efficient data exchange, and aiding patient-clinician communication. However, patients often failed to see the relevance of the systems to their personal situations, and emphasised the threat to the person centred element of their care. The feedback presented in this paper suggests that patients are conscious of the benefits that mobile-phone based assessment could bring to clinical care, and that the technology can be successfully integrated into everyday routine. However, it also suggests that it is important to demonstrate to patients the personal, as well as theoretical, benefits of the technology. In the future it will be important to establish whether clinical practitioners are able to use this technology as part of a personalised mental health regime.

DataToText: A Consumer-Oriented Approach to Data Analysis

ERIC Educational Resources Information Center

Kenny, David A.

2010-01-01

DataToText is a project developed where the user communicates the relevant information for an analysis and DataToText computer routine produces text output that describes in words, tables, and figures the results from the analyses. Two extended examples are given, one an example of a moderator analysis and the other an example of a dyadic data…

Designing an Exploratory Text Analysis Tool for Humanities and Social Sciences Research

ERIC Educational Resources Information Center

Shrikumar, Aditi

2013-01-01

This dissertation presents a new tool for exploratory text analysis that attempts to improve the experience of navigating and exploring text and its metadata. The design of the tool was motivated by the unmet need for text analysis tools in the humanities and social sciences. In these fields, it is common for scholars to have hundreds or thousands…

History of neurologic examination books

PubMed Central

2015-01-01

The objective of this study was to create an annotated list of textbooks dedicated to teaching the neurologic examination. Monographs focused primarily on the complete neurologic examination published prior to 1960 were reviewed. This analysis was limited to books with the word “examination” in the title, with exceptions for the texts of Robert Wartenberg and Gordon Holmes. Ten manuals met the criteria. Works dedicated primarily to the neurologic examination without a major emphasis on disease description or treatment first appeared in the early 1900s. Georg Monrad-Krohn's “Blue Book of Neurology” (“Blue Bible”) was the earliest success. These treatises served the important purpose of educating trainees on proper neurologic examination technique. They could make a reputation and be profitable for the author (Monrad-Krohn), highlight how neurology was practiced at individual institutions (McKendree, Denny-Brown, Holmes, DeJong, Mayo Clinic authors), and honor retiring mentors (Mayo Clinic authors). PMID:25829645

Prolonged Infusion Piperacillin-Tazobactam Decreases Mortality and Improves Outcomes in Severely Ill Patients: Results of a Systematic Review and Meta-Analysis.

PubMed

Rhodes, Nathaniel J; Liu, Jiajun; O'Donnell, J Nicholas; Dulhunty, Joel M; Abdul-Aziz, Mohd H; Berko, Patsy Y; Nadler, Barbara; Lipman, Jeffery; Roberts, Jason A

2018-02-01

Piperacillin-tazobactam is a commonly used antibiotic in critically ill patients; however, controversy exists as to whether mortality in serious infections can be decreased through administration by prolonged infusion compared with intermittent infusion. The purpose of this systematic review and meta-analysis was to describe the impact of prolonged infusion piperacillin-tazobactam schemes on clinical endpoints in severely ill patients. We conducted a systematic literature review and meta-analysis searching MEDLINE, Cumulative Index to Nursing and Allied Health Literature, and the Cochrane Library from inception to April 1, 2017, for studies. Mortality rates were compared between severely ill patients receiving piperacillin-tazobactam via prolonged infusion or intermittent infusion. Included studies must have reported severity of illness scores, which were transformed into average study-level mortality probabilities. Two investigators independently screened titles, abstracts, and full texts of studies meeting inclusion criteria for this systematic review and meta-analysis. Variables included author name, publication year, study design, demographics, total daily dose(s), average estimated creatinine clearance, type of prolonged infusion, prevalence of combination therapy, severity of illness scores, infectious sources, all-cause mortality, clinical cure, microbiological cure, and hospital and ICU length of stay. The review identified 18 studies including 3,401 patients who received piperacillin-tazobactam, 56.7% via prolonged infusion. Across all studies, the majority of patients had an identified primary infectious source. Receipt of prolonged infusion was associated with a 1.46-fold lower odds of mortality (95% CI, 1.20-1.77) in the pooled analysis. Patients receiving prolonged infusion had a 1.77-fold higher odds of clinical cure (95% CI, 1.24-2.54) and a 1.22-fold higher odds of microbiological cure (95% CI, 0.84-1.77). Subanalyses were conducted according to high (≥ 20%) and low (< 20%) average study-level mortality probabilities. In studies reporting higher mortality probabilities, effect sizes were variable but similar to the pooled results. Receipt of prolonged infusion of piperacillin-tazobactam was associated with reduced mortality and improved clinical cure rates across diverse cohorts of severely ill patients.

Comparing Mobile Health Strategies to Improve Medication Adherence for Veterans With Coronary Heart Disease (Mobile4Meds): Protocol for a Mixed-Methods Study.

PubMed

Park, Linda G; Collins, Eileen G; Shim, Janet K; Whooley, Mary A

2017-07-18

Adherence to antiplatelet medications is critical to prevent life threatening complications (ie, stent thrombosis) after percutaneous coronary interventions (PCIs), yet rates of nonadherence range from 21-57% by 12 months. Mobile interventions delivered via text messaging or mobile apps represent a practical and inexpensive strategy to promote behavior change and enhance medication adherence. The Mobile4Meds study seeks to determine whether text messaging or a mobile app, compared with an educational website control provided to all Veterans, can improve adherence to antiplatelet therapy among patients following acute coronary syndrome (ACS) or PCI. The three aims of the study are to: (1) determine preferences for content and frequency of text messaging to promote medication adherence through focus groups; (2) identify the most patient-centered app that promotes adherence, through a content analysis of all commercially available apps for medication adherence and focus groups centered on usability; and (3) compare adherence to antiplatelet medications in Veterans after ACS/PCI via a randomized clinical trial (RCT). We will utilize a mixed-methods design that uses focus groups to achieve the first and second aims (N=32). Patients will be followed for 12 months after being randomly assigned to one of three arms: (1) customized text messaging, (2) mobile app, or (3) website-control groups (N=225). Medication adherence will be measured with electronic monitoring devices, pharmacy records, and self-reports. Enrollment for the focus groups is currently in progress. We expect to enroll patients for the RCT in the beginning of 2018. Determining the efficacy of mobile technology using a Veteran-designed protocol to promote medication adherence will have a significant impact on Veteran health and public health, particularly for individuals with chronic diseases that require strict medication adherence. ClinicalTrials.gov NCT03022669. ©Linda G Park, Eileen G Collins, Janet K Shim, Mary A Whooley. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 18.07.2017.

Detection of pneumonia using free-text radiology reports in the BioSense system.

PubMed

Asatryan, Armenak; Benoit, Stephen; Ma, Haobo; English, Roseanne; Elkin, Peter; Tokars, Jerome

2011-01-01

Near real-time disease detection using electronic data sources is a public health priority. Detecting pneumonia is particularly important because it is the manifesting disease of several bioterrorism agents as well as a complication of influenza, including avian and novel H1N1 strains. Text radiology reports are available earlier than physician diagnoses and so could be integral to rapid detection of pneumonia. We performed a pilot study to determine which keywords present in text radiology reports are most highly associated with pneumonia diagnosis. Electronic radiology text reports from 11 hospitals from February 1, 2006 through December 31, 2007 were used. We created a computerized algorithm that searched for selected keywords ("airspace disease", "consolidation", "density", "infiltrate", "opacity", and "pneumonia"), differentiated between clinical history and radiographic findings, and accounted for negations and double negations; this algorithm was tested on a sample of 350 radiology reports. We used the algorithm to study 189,246 chest radiographs, searching for the keywords and determining their association with a final International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) diagnosis of pneumonia. Performance of the search algorithm in finding keywords, and association of the keywords with a pneumonia diagnosis. In the sample of 350 radiographs, the search algorithm was highly successful in identifying the selected keywords (sensitivity 98.5%, specificity 100%). Analysis of the 189,246 radiographs showed that the keyword "pneumonia" was the strongest predictor of an ICD-9-CM diagnosis of pneumonia (adjusted odds ratio 11.8) while "density" was the weakest (adjusted odds ratio 1.5). In general, the most highly associated keyword present in the report, regardless of whether a less highly associated keyword was also present, was the best predictor of a diagnosis of pneumonia. Empirical methods may assist in finding radiology report keywords that are most highly predictive of a pneumonia diagnosis. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Automated Methods to Extract Patient New Information from Clinical Notes in Electronic Health Record Systems

ERIC Educational Resources Information Center

Zhang, Rui

2013-01-01

The widespread adoption of Electronic Health Record (EHR) has resulted in rapid text proliferation within clinical care. Clinicians' use of copying and pasting functions in EHR systems further compounds this by creating a large amount of redundant clinical information in clinical documents. A mixture of redundant information (especially outdated…

The full spectrum of ethical issues in the care of patients with ALS: a systematic qualitative review.

PubMed

Seitzer, F; Kahrass, H; Neitzke, G; Strech, D

2016-02-01

Dealing systematically with ethical issues in amyotrophic lateral sclerosis (ALS) care requires an unbiased awareness of all the relevant ethical issues. The aim of the study was to determine systematically and transparently the full spectrum of ethical issues in ALS care. We conducted a systematic review in Medline and Google Books (restricted to English and German literature published between 1993 and 2014). We applied qualitative text analysis and normative analysis to categorise the spectrum of ethical issues in ALS care. The literature review retrieved 56 references that together mentioned a spectrum of 103 ethical issues in ALS care. The spectrum was structured into six major categories that consist of first and second-order categories of ethical issues. The systematically derived spectrum of ethical issues in ALS care presented in this paper raises awareness and understanding of the complexity of ethical issues in ALS care. It also offers a basis for the systematic development of informational and training materials for health professionals, patients and their relatives, and society as a whole. Finally, it supports a rational and fair selection of all those ethical issues that should be addressed in health policies, position papers and clinical practice guidelines. Further research is needed to identify ways to systematically select the most relevant ethical issues not only in the clinical environment, but also for the development of clinical practice guidelines.

Barriers to Retrieving Patient Information from Electronic Health Record Data: Failure Analysis from the TREC Medical Records Track

PubMed Central

Edinger, Tracy; Cohen, Aaron M.; Bedrick, Steven; Ambert, Kyle; Hersh, William

2012-01-01

Objective: Secondary use of electronic health record (EHR) data relies on the ability to retrieve accurate and complete information about desired patient populations. The Text Retrieval Conference (TREC) 2011 Medical Records Track was a challenge evaluation allowing comparison of systems and algorithms to retrieve patients eligible for clinical studies from a corpus of de-identified medical records, grouped by patient visit. Participants retrieved cohorts of patients relevant to 35 different clinical topics, and visits were judged for relevance to each topic. This study identified the most common barriers to identifying specific clinic populations in the test collection. Methods: Using the runs from track participants and judged visits, we analyzed the five non-relevant visits most often retrieved and the five relevant visits most often overlooked. Categories were developed iteratively to group the reasons for incorrect retrieval for each of the 35 topics. Results: Reasons fell into nine categories for non-relevant visits and five categories for relevant visits. Non-relevant visits were most often retrieved because they contained a non-relevant reference to the topic terms. Relevant visits were most often infrequently retrieved because they used a synonym for a topic term. Conclusions: This failure analysis provides insight into areas for future improvement in EHR-based retrieval with techniques such as more widespread and complete use of standardized terminology in retrieval and data entry systems. PMID:23304287

Barriers to retrieving patient information from electronic health record data: failure analysis from the TREC Medical Records Track.

PubMed

Edinger, Tracy; Cohen, Aaron M; Bedrick, Steven; Ambert, Kyle; Hersh, William

2012-01-01

Secondary use of electronic health record (EHR) data relies on the ability to retrieve accurate and complete information about desired patient populations. The Text Retrieval Conference (TREC) 2011 Medical Records Track was a challenge evaluation allowing comparison of systems and algorithms to retrieve patients eligible for clinical studies from a corpus of de-identified medical records, grouped by patient visit. Participants retrieved cohorts of patients relevant to 35 different clinical topics, and visits were judged for relevance to each topic. This study identified the most common barriers to identifying specific clinic populations in the test collection. Using the runs from track participants and judged visits, we analyzed the five non-relevant visits most often retrieved and the five relevant visits most often overlooked. Categories were developed iteratively to group the reasons for incorrect retrieval for each of the 35 topics. Reasons fell into nine categories for non-relevant visits and five categories for relevant visits. Non-relevant visits were most often retrieved because they contained a non-relevant reference to the topic terms. Relevant visits were most often infrequently retrieved because they used a synonym for a topic term. This failure analysis provides insight into areas for future improvement in EHR-based retrieval with techniques such as more widespread and complete use of standardized terminology in retrieval and data entry systems.

[Research applications in digital radiology. Big data and co].

PubMed

Müller, H; Hanbury, A

2016-02-01

Medical imaging produces increasingly complex images (e.g. thinner slices and higher resolution) with more protocols, so that image reading has also become much more complex. More information needs to be processed and usually the number of radiologists available for these tasks has not increased to the same extent. The objective of this article is to present current research results from projects on the use of image data for clinical decision support. An infrastructure that can allow large volumes of data to be accessed is presented. In this way the best performing tools can be identified without the medical data having to leave secure servers. The text presents the results of the VISCERAL and Khresmoi EU-funded projects, which allow the analysis of previous cases from institutional archives to support decision-making and for process automation. The results also represent a secure evaluation environment for medical image analysis. This allows the use of data extracted from past cases to solve information needs occurring when diagnosing new cases. The presented research prototypes allow direct extraction of knowledge from the visual data of the images and to use this for decision support or process automation. Real clinical use has not been tested but several subjective user tests showed the effectiveness and efficiency of the process. The future in radiology will clearly depend on better use of the important knowledge in clinical image archives to automate processes and aid decision-making via big data analysis. This can help concentrate the work of radiologists towards the most important parts of diagnostics.

Dental Students' Perceived Value of Peer-Mentoring Clinical Leadership Experiences.

PubMed

Sheridan, Rachel A; Hammaker, Daniel J; de Peralta, Tracy L; Fitzgerald, Mark

2016-03-01

This pilot study compared second- and fourth-year dental students' perceived values of newly implemented clinical leadership experiences (CLEs) at one U.S. dental school during the 2012-13 academic year. In the CLEs, fourth-year (D4) students mentored second-year (D2) dental students during faculty-supervised patient treatment. The two cohorts' perceived value of the experiences was measured with questionnaires consisting of five-point Likert scale questions and open text responses. Out of a total of 114 D2 and 109 D4 students, 46 D2 students and 35 D4 students participated (response rates of 40.4% and 32.1%, respectively). While responses from both cohorts showed they highly valued the CLEs, the D2s perceived greater value: 4.07 (0.53) v. 3.51 (0.95), p<0.003. Both cohorts reported feeling that D4s were prepared to mentor D2s, that the CLEs had educational benefits, and that the CLEs increased their comfort with peer communication. Theme analysis of open text questions revealed that the respondents perceived the D4s were more accessible than faculty and provided guidance and individual attention; the CLEs increased student comfort; the CLEs reinforced D4 skills, knowledge, and confidence; and the CLEs provided management, leadership, and collaborative work experience. Theme analysis also highlighted student concerns about a lack of program structure. Overall, the majority of both groups valued CLEs in their dental education. Particular advantages they perceived were increased comfort, guidance, and attention. Further program development should address student concerns. These results suggest that similar programs should be considered and/or expanded in other dental schools' curricula.

How does preclinical laboratory training impact physical examination skills during the first clinical year? A retrospective analysis of routinely collected objective structured clinical examination scores among the first two matriculating classes of a reformed curriculum in one Polish medical school.

PubMed

Świerszcz, Jolanta; Stalmach-Przygoda, Agata; Kuźma, Marcin; Jabłoński, Konrad; Cegielny, Tomasz; Skrzypek, Agnieszka; Wieczorek-Surdacka, Ewa; Kruszelnicka, Olga; Chmura, Kaja; Chyrchel, Bernadeta; Surdacki, Andrzej; Nowakowski, Michał

2017-09-01

As a result of a curriculum reform launched in 2012 at our institution, preclinical training was shortened to 2 years instead of the traditional 3 years, creating additional incentives to optimise teaching methods. In accordance with the new curriculum, a semester-long preclinical module of clinical skills (CS) laboratory training takes place in the second year of study, while an introductory clinical course (ie, brief introductory clerkships) is scheduled for the Fall semester of the third year. Objective structured clinical examinations (OSCEs) are carried out at the conclusion of both the preclinical module and the introductory clinical course. Our aim was to compare the scores at physical examination stations between the first and second matriculating classes of a newly reformed curriculum on preclinical second-year OSCEs and early clinical third-year OSCEs. Analysis of routinely collected data. One Polish medical school. Complete OSCE records for 462 second-year students and 445 third-year students. OSCE scores by matriculation year. In comparison to the first class of the newly reformed curriculum, significantly higher (ie, better) OSCE scores were observed for those students who matriculated in 2013, a year after implementing the reformed curriculum. This finding was consistent for both second-year and third-year cohorts. Additionally, the magnitude of the improvement in median third-year OSCE scores was proportional to the corresponding advancement in preceding second-year preclinical OSCE scores for each of two different sets of physical examination tasks. In contrast, no significant difference was noted between the academic years in the ability to interpret laboratory data or ECG - tasks which had not been included in the second-year preclinical training. Our results suggest the importance of preclinical training in a CS laboratory to improve students' competence in physical examination at the completion of introductory clinical clerkships during the first clinical year. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

A Randomized Clinical Trial of the Collaborative Assessment and Management of Suicidality vs. Enhanced Care as Usual for Suicidal Soldiers

DTIC Science & Technology

2016-04-01

are those of the author(s) and should not be construed as an official Department of the Army position, policy or decision unless so designated by...paragraph) describes the subject, purpose and scope of the research. This study is designed to investigate the effectiveness of a novel clinical... tests of significance shall be applied to all data whenever possible. Figures and graphs referenced in the text may be embedded in the text or

Childrearing style in families of anxiety-disordered children: between-family and within-family differences.

PubMed

Lindhout, Ingeborg E; Markus, Monica Th; Borst, Sophie R; Hoogendijk, Thea H G; Dingemans, Peter M A J; Boer, Frits

2009-06-01

This study examined whether (1) parents of anxiety-disordered (AD) children differed from those of non-clinical controls in their childrearing style, and whether (2) the child-rearing style of parents towards AD children is different from that towards their siblings. A clinical sample of 25 AD children, age range 8-13 years, was compared with 25 siblings and a non-clinical control group (n = 25). Childrearing was assessed by means of parental self-report, child report and through an expressed emotion interview measure. AD children perceived more parental rejection than non-clinical control children or the AD children's siblings. High-expressed emotion was scored significantly more often towards AD children than non-clinical control children, or their siblings. On [Symbol: see text]care' and [Symbol: see text]control' parental self-report showed some differences regarding AD children on the one hand and non-clinical control children or siblings of AD children on the other. These results suggest that the rearing of AD children differs significantly both from the rearing of their siblings and that of non-clinical control children.

Challenges to evaluating complex interventions: a content analysis of published papers

PubMed Central

2013-01-01

Background There is continuing interest among practitioners, policymakers and researchers in the evaluation of complex interventions stemming from the need to further develop the evidence base on the effectiveness of healthcare and public health interventions, and an awareness that evaluation becomes more challenging if interventions are complex. We undertook an analysis of published journal articles in order to identify aspects of complexity described by writers, the fields in which complex interventions are being evaluated and the challenges experienced in design, implementation and evaluation. This paper outlines the findings of this documentary analysis. Methods The PubMed electronic database was searched for the ten year period, January 2002 to December 2011, using the term “complex intervention*” in the title and/or abstract of a paper. We extracted text from papers to a table and carried out a thematic analysis to identify authors’ descriptions of challenges faced in developing, implementing and evaluating complex interventions. Results The search resulted in a sample of 221 papers of which full text of 216 was obtained and 207 were included in the analysis. The 207 papers broadly cover clinical, public health and methodological topics. Challenges described included the content and standardisation of interventions, the impact of the people involved (staff and patients), the organisational context of implementation, the development of outcome measures, and evaluation. Conclusions Our analysis of these papers suggests that more detailed reporting of information on outcomes, context and intervention is required for complex interventions. Future revisions to reporting guidelines for both primary and secondary research may need to take aspects of complexity into account to enhance their value to both researchers and users of research. PMID:23758638

Developing content for a mHealth intervention to promote postpartum retention in prevention of mother-to-child HIV transmission programs and early infant diagnosis of HIV: a qualitative study.

PubMed

Odeny, Thomas A; Newman, Maya; Bukusi, Elizabeth A; McClelland, R Scott; Cohen, Craig R; Camlin, Carol S

2014-01-01

Maternal attendance at postnatal clinic visits and timely diagnosis of infant HIV infection are important steps for prevention of mother-to-child transmission (PMTCT) of HIV. We aimed to use theory-informed methods to develop text messages targeted at facilitating these steps. We conducted five focus group discussions with health workers and women attending antenatal, postnatal, and PMTCT clinics to explore aspects of women's engagement in postnatal HIV care and infant testing. Discussion topics were informed by constructs of the Health Belief Model (HBM) and prior empirical research. Qualitative data were coded and analyzed according to the construct of the HBM to which they related. Themes were extracted and used to draft intervention messages. We carried out two stages of further messaging development: messages were presented in a follow-up focus group in order to develop optimal phrasing in local languages. We then further refined the messages, pretested them in individual cognitive interviews with selected health workers, and finalized the messages for the intervention. Findings indicated that brief, personalized, caring, polite, encouraging, and educational text messages would facilitate women bringing their children to clinic after delivery, suggesting that text messages may serve as an important "cue to action." Participants emphasized that messages should not mention HIV due to fear of HIV testing and disclosure. Participants also noted that text messages could capitalize on women's motivation to attend clinic for childhood immunizations. Applying a multi-stage content development approach to crafting text messages--informed by behavioral theory--resulted in message content that was consistent across different focus groups. This approach could help answer "why" and "how" text messaging may be a useful tool to support maternal and child health. We are evaluating the effect of these messages on improving postpartum PMTCT retention and infant HIV testing in a randomized trial.

Natural language processing to extract symptoms of severe mental illness from clinical text: the Clinical Record Interactive Search Comprehensive Data Extraction (CRIS-CODE) project

PubMed Central

Jayatilleke, Nishamali; Kolliakou, Anna; Ball, Michael; Gorrell, Genevieve; Roberts, Angus; Stewart, Robert

2017-01-01

Objectives We sought to use natural language processing to develop a suite of language models to capture key symptoms of severe mental illness (SMI) from clinical text, to facilitate the secondary use of mental healthcare data in research. Design Development and validation of information extraction applications for ascertaining symptoms of SMI in routine mental health records using the Clinical Record Interactive Search (CRIS) data resource; description of their distribution in a corpus of discharge summaries. Setting Electronic records from a large mental healthcare provider serving a geographic catchment of 1.2 million residents in four boroughs of south London, UK. Participants The distribution of derived symptoms was described in 23 128 discharge summaries from 7962 patients who had received an SMI diagnosis, and 13 496 discharge summaries from 7575 patients who had received a non-SMI diagnosis. Outcome measures Fifty SMI symptoms were identified by a team of psychiatrists for extraction based on salience and linguistic consistency in records, broadly categorised under positive, negative, disorganisation, manic and catatonic subgroups. Text models for each symptom were generated using the TextHunter tool and the CRIS database. Results We extracted data for 46 symptoms with a median F1 score of 0.88. Four symptom models performed poorly and were excluded. From the corpus of discharge summaries, it was possible to extract symptomatology in 87% of patients with SMI and 60% of patients with non-SMI diagnosis. Conclusions This work demonstrates the possibility of automatically extracting a broad range of SMI symptoms from English text discharge summaries for patients with an SMI diagnosis. Descriptive data also indicated that most symptoms cut across diagnoses, rather than being restricted to particular groups. PMID:28096249

Visualizing complex processes using a cognitive-mapping tool to support the learning of clinical reasoning.

PubMed

Wu, Bian; Wang, Minhong; Grotzer, Tina A; Liu, Jun; Johnson, Janice M

2016-08-22

Practical experience with clinical cases has played an important role in supporting the learning of clinical reasoning. However, learning through practical experience involves complex processes difficult to be captured by students. This study aimed to examine the effects of a computer-based cognitive-mapping approach that helps students to externalize the reasoning process and the knowledge underlying the reasoning process when they work with clinical cases. A comparison between the cognitive-mapping approach and the verbal-text approach was made by analyzing their effects on learning outcomes. Fifty-two third-year or higher students from two medical schools participated in the study. Students in the experimental group used the computer-base cognitive-mapping approach, while the control group used the verbal-text approach, to make sense of their thinking and actions when they worked with four simulated cases over 4 weeks. For each case, students in both groups reported their reasoning process (involving data capture, hypotheses formulation, and reasoning with justifications) and the underlying knowledge (involving identified concepts and the relationships between the concepts) using the given approach. The learning products (cognitive maps or verbal text) revealed that students in the cognitive-mapping group outperformed those in the verbal-text group in the reasoning process, but not in making sense of the knowledge underlying the reasoning process. No significant differences were found in a knowledge posttest between the two groups. The computer-based cognitive-mapping approach has shown a promising advantage over the verbal-text approach in improving students' reasoning performance. Further studies are needed to examine the effects of the cognitive-mapping approach in improving the construction of subject-matter knowledge on the basis of practical experience.

Integrating query of relational and textual data in clinical databases: a case study.

PubMed

Fisk, John M; Mutalik, Pradeep; Levin, Forrest W; Erdos, Joseph; Taylor, Caroline; Nadkarni, Prakash

2003-01-01

The authors designed and implemented a clinical data mart composed of an integrated information retrieval (IR) and relational database management system (RDBMS). Using commodity software, which supports interactive, attribute-centric text and relational searches, the mart houses 2.8 million documents that span a five-year period and supports basic IR features such as Boolean searches, stemming, and proximity and fuzzy searching. Results are relevance-ranked using either "total documents per patient" or "report type weighting." Non-curated medical text has a significant degree of malformation with respect to spelling and punctuation, which creates difficulties for text indexing and searching. Presently, the IR facilities of RDBMS packages lack the features necessary to handle such malformed text adequately. A robust IR+RDBMS system can be developed, but it requires integrating RDBMSs with third-party IR software. RDBMS vendors need to make their IR offerings more accessible to non-programmers.

In silico analysis of the anti-hypertensive drugs impact on myocardial oxygen balance.

PubMed

Guala, A; Leone, D; Milan, A; Ridolfi, L

2017-06-01

Hypertension is a very common pathology, and its clinical treatment largely relies on different drugs. Some of these drugs exhibit specific protective functions in addition to those resulting from blood pressure reduction. In this work, we study the impact of commonly used anti-hypertensive drugs (RAAS, [Formula: see text] and calcium channel blockers) on myocardial oxygen supply-consumption balance, which plays a crucial role in type 2 myocardial infarction. To this aim, 42 wash-out hypertensive patients were selected, a number of measured data were used to set a validated multi-scale cardiovascular model to subject-specific conditions, and the administration of different drugs was suitably simulated. Our results ascribe the well-known major cardioprotective efficiency of [Formula: see text] blockers compared to other drugs to a positive change of myocardial oxygen balance due to the concomitant: (1) reduction in aortic systolic, diastolic and pulse pressures, (2) decrease in left ventricular work, diastolic cavity pressure and oxygen consumption, (3) increase in coronary flow and (4) ejection efficiency improvement. RAAS blockers share several positive outcomes with [Formula: see text] blockers, although to a reduced extent. In contrast, calcium channel blockers seem to induce some potentially negative effects on the myocardial oxygen balance.

Exploration of contextual factors in a successful quality improvement collaborative in English ambulance services: cross‐sectional survey

PubMed Central

Phung, Viet‐Hai; Essam, Nadya; Asghar, Zahid; Spaight, Anne

2015-01-01

Abstract Rationale, aims and objectives Clinical leadership and organizational culture are important contextual factors for quality improvement (QI) but the relationship between these and with organizational change is complex and poorly understood. We aimed to explore the relationship between clinical leadership, culture of innovation and clinical engagement in QI within a national ambulance QI Collaborative (QIC). Methods We used a self‐administered online questionnaire survey sent to front‐line clinicians in all 12 English ambulance services. We conducted a cross‐sectional analysis of quantitative data and qualitative analysis of free‐text responses. Results There were 2743 (12% of 22 117) responses from 11 of the 12 participating ambulance services. In the 3% of responders that were directly involved with the QIC, leadership behaviour was significantly higher than for those not directly involved. QIC involvement made no significant difference to responders' perceptions of the culture of innovation in their organization, which was generally considered poor. Although uptake of QI methods was low overall, QIC members were significantly more likely to use QI methods, which were also significantly associated with leadership behaviour. Conclusions Despite a limited organizational culture of innovation, clinical leadership and use of QI methods in ambulance services generally, the QIC achieved its aims to significantly improve pre‐hospital care for acute myocardial infarction and stroke. We postulate that this was mediated through an improvement subculture, linked to the QIC, which facilitated large‐scale improvement by stimulating leadership and QI methods. Further research is needed to understand success factors for QI in complex health care environments. PMID:26303398

Integrated clinical workstations for image and text data capture, display, and teleconsultation.

PubMed Central

Dayhoff, R.; Kuzmak, P. M.; Kirin, G.

1994-01-01

The Department of Veterans Affairs (VA) DHCP Imaging System digitally records clinically significant diagnostic images selected by medical specialists in a variety of hospital departments, including radiology, cardiology, gastroenterology, pathology, dermatology, hematology, surgery, podiatry, dental clinic, and emergency room. These images, which include true color and gray scale images, scanned documents, and electrocardiogram waveforms, are stored on network file servers and displayed on workstations located throughout a medical center. All images are managed by the VA's hospital information system (HIS), allowing integrated displays of text and image data from all medical specialties. Two VA medical centers currently have DHCP Imaging Systems installed, and other installations are underway. PMID:7949899

WITH: a system to write clinical trials using XML and RDBMS.

PubMed Central

Fazi, Paola; Luzi, Daniela; Manco, Mariarosaria; Ricci, Fabrizio L.; Toffoli, Giovanni; Vignetti, Marco

2002-01-01

The paper illustrates the system WITH (Write on Internet clinical Trials in Haematology) which supports the writing of a clinical trial (CT) document. The requirements of this system have been defined analysing the writing process of a CT and then modelling the content of its sections together with their logical and temporal relationships. The system WITH allows: a) editing the document text; b) re-using the text; and c) facilitating the cooperation and the collaborative writing. It is based on XML mark-up language, and on a RDBMS. This choice guarantees: a) process standardisation; b) process management; c) efficient delivery of information-based tasks; and d) explicit focus on process design. PMID:12463823

ContextD: an algorithm to identify contextual properties of medical terms in a Dutch clinical corpus.

PubMed

Afzal, Zubair; Pons, Ewoud; Kang, Ning; Sturkenboom, Miriam C J M; Schuemie, Martijn J; Kors, Jan A

2014-11-29

In order to extract meaningful information from electronic medical records, such as signs and symptoms, diagnoses, and treatments, it is important to take into account the contextual properties of the identified information: negation, temporality, and experiencer. Most work on automatic identification of these contextual properties has been done on English clinical text. This study presents ContextD, an adaptation of the English ConText algorithm to the Dutch language, and a Dutch clinical corpus. We created a Dutch clinical corpus containing four types of anonymized clinical documents: entries from general practitioners, specialists' letters, radiology reports, and discharge letters. Using a Dutch list of medical terms extracted from the Unified Medical Language System, we identified medical terms in the corpus with exact matching. The identified terms were annotated for negation, temporality, and experiencer properties. To adapt the ConText algorithm, we translated English trigger terms to Dutch and added several general and document specific enhancements, such as negation rules for general practitioners' entries and a regular expression based temporality module. The ContextD algorithm utilized 41 unique triggers to identify the contextual properties in the clinical corpus. For the negation property, the algorithm obtained an F-score from 87% to 93% for the different document types. For the experiencer property, the F-score was 99% to 100%. For the historical and hypothetical values of the temporality property, F-scores ranged from 26% to 54% and from 13% to 44%, respectively. The ContextD showed good performance in identifying negation and experiencer property values across all Dutch clinical document types. Accurate identification of the temporality property proved to be difficult and requires further work. The anonymized and annotated Dutch clinical corpus can serve as a useful resource for further algorithm development.

Clinical Natural Language Processing in languages other than English: opportunities and challenges.

PubMed

Névéol, Aurélie; Dalianis, Hercules; Velupillai, Sumithra; Savova, Guergana; Zweigenbaum, Pierre

2018-03-30

Natural language processing applied to clinical text or aimed at a clinical outcome has been thriving in recent years. This paper offers the first broad overview of clinical Natural Language Processing (NLP) for languages other than English. Recent studies are summarized to offer insights and outline opportunities in this area. We envision three groups of intended readers: (1) NLP researchers leveraging experience gained in other languages, (2) NLP researchers faced with establishing clinical text processing in a language other than English, and (3) clinical informatics researchers and practitioners looking for resources in their languages in order to apply NLP techniques and tools to clinical practice and/or investigation. We review work in clinical NLP in languages other than English. We classify these studies into three groups: (i) studies describing the development of new NLP systems or components de novo, (ii) studies describing the adaptation of NLP architectures developed for English to another language, and (iii) studies focusing on a particular clinical application. We show the advantages and drawbacks of each method, and highlight the appropriate application context. Finally, we identify major challenges and opportunities that will affect the impact of NLP on clinical practice and public health studies in a context that encompasses English as well as other languages.

Valx: A system for extracting and structuring numeric lab test comparison statements from text

PubMed Central

Hao, Tianyong; Liu, Hongfang; Weng, Chunhua

2017-01-01

Objectives To develop an automated method for extracting and structuring numeric lab test comparison statements from text and evaluate the method using clinical trial eligibility criteria text. Methods Leveraging semantic knowledge from the Unified Medical Language System (UMLS) and domain knowledge acquired from the Internet, Valx takes 7 steps to extract and normalize numeric lab test expressions: 1) text preprocessing, 2) numeric, unit, and comparison operator extraction, 3) variable identification using hybrid knowledge, 4) variable - numeric association, 5) context-based association filtering, 6) measurement unit normalization, and 7) heuristic rule-based comparison statements verification. Our reference standard was the consensus-based annotation among three raters for all comparison statements for two variables, i.e., HbA1c and glucose, identified from all of Type 1 and Type 2 diabetes trials in ClinicalTrials.gov. Results The precision, recall, and F-measure for structuring HbA1c comparison statements were 99.6%, 98.1%, 98.8% for Type 1 diabetes trials, and 98.8%, 96.9%, 97.8% for Type 2 Diabetes trials, respectively. The precision, recall, and F-measure for structuring glucose comparison statements were 97.3%, 94.8%, 96.1% for Type 1 diabetes trials, and 92.3%, 92.3%, 92.3% for Type 2 diabetes trials, respectively. Conclusions Valx is effective at extracting and structuring free-text lab test comparison statements in clinical trial summaries. Future studies are warranted to test its generalizability beyond eligibility criteria text. The open-source Valx enables its further evaluation and continued improvement among the collaborative scientific community. PMID:26940748

Valx: A System for Extracting and Structuring Numeric Lab Test Comparison Statements from Text.

PubMed

Hao, Tianyong; Liu, Hongfang; Weng, Chunhua

2016-05-17

To develop an automated method for extracting and structuring numeric lab test comparison statements from text and evaluate the method using clinical trial eligibility criteria text. Leveraging semantic knowledge from the Unified Medical Language System (UMLS) and domain knowledge acquired from the Internet, Valx takes seven steps to extract and normalize numeric lab test expressions: 1) text preprocessing, 2) numeric, unit, and comparison operator extraction, 3) variable identification using hybrid knowledge, 4) variable - numeric association, 5) context-based association filtering, 6) measurement unit normalization, and 7) heuristic rule-based comparison statements verification. Our reference standard was the consensus-based annotation among three raters for all comparison statements for two variables, i.e., HbA1c and glucose, identified from all of Type 1 and Type 2 diabetes trials in ClinicalTrials.gov. The precision, recall, and F-measure for structuring HbA1c comparison statements were 99.6%, 98.1%, 98.8% for Type 1 diabetes trials, and 98.8%, 96.9%, 97.8% for Type 2 diabetes trials, respectively. The precision, recall, and F-measure for structuring glucose comparison statements were 97.3%, 94.8%, 96.1% for Type 1 diabetes trials, and 92.3%, 92.3%, 92.3% for Type 2 diabetes trials, respectively. Valx is effective at extracting and structuring free-text lab test comparison statements in clinical trial summaries. Future studies are warranted to test its generalizability beyond eligibility criteria text. The open-source Valx enables its further evaluation and continued improvement among the collaborative scientific community.

Added Value of Selected Images Embedded Into Radiology Reports to Referring Clinicians

PubMed Central

Iyer, Veena R.; Hahn, Peter F.; Blaszkowsky, Lawrence S.; Thayer, Sarah P.; Halpern, Elkan F.; Harisinghani, Mukesh G.

2011-01-01

Purpose The aim of this study was to evaluate the added utility of embedding images for findings described in radiology text reports to referring clinicians. Methods Thirty-five cases referred for abdominal CT scans in 2007 and 2008 were included. Referring physicians were asked to view text-only reports, followed by the same reports with pertinent images embedded. For each pair of reports, a questionnaire was administered. A 5-point, Likert-type scale was used to assess if the clinical query was satisfactorily answered by the text-only report. A “yes-or-no” question was used to assess whether the report with images answered the clinical query better; a positive answer to this question generated “yes-or-no” queries to examine whether the report with images helped in making a more confident decision on management, whether it reduced time spent in forming the plan, and whether it altered management. The questionnaire asked whether a radiologist would be contacted with queries on reading the text-only report and the report with images. Results In 32 of 35 cases, the text-only reports satisfactorily answered the clinical queries. In these 32 cases, the reports with attached images helped in making more confident management decisions and reduced time in planning management. Attached images altered management in 2 cases. Radiologists would have been consulted for clarifications in 21 and 10 cases on reading the text-only reports and the reports with embedded images, respectively. Conclusions Providing relevant images with reports saves time, increases physicians' confidence in deciding treatment plans, and can alter management. PMID:20193926

Adaptation and uptake evaluation of an SMS text message smoking cessation programme (MiQuit) for use in antenatal care

PubMed Central

Naughton, Felix; Cooper, Sue; Bowker, Katharine; Campbell, Katarzyna; Sutton, Stephen; Leonardi-Bee, Jo; Sloan, Melanie; Coleman, Tim

2015-01-01

Objectives To adapt a tailored short message service (SMS) text message smoking cessation intervention (MiQuit) for use without active health professional endorsement in routine antenatal care settings, to estimate ‘real-world’ uptake and test the feasibility of its use. Design Single-site service evaluation. Setting A Nottinghamshire (UK) antenatal clinic. Participants Pregnant women accessing the antenatal clinic (N=1750) over 6 months. Intervention A single-sheet A5 leaflet provided in the women's maternity notes folder describing the MiQuit text service. Similar materials were left on clinic desks and noticeboards. Outcome measures MiQuit activation requests and system interactions were logged for two time frames: 6 months (strict) and 8 months (extended). Local hospital data were used to estimate the denominator of pregnant smokers exposed to the materials. Results During the strict and extended time frames, 13 and 25 activation requests were received, representing 3% (95% CI 2% to 5%) and 4% (95% CI 3% to 6%) of estimated smokers, respectively. Only 11 (44%) of the 25 requesting activation sent a correctly formatted initiation text. Of those activating MiQuit, and invited to complete tailoring questions (used to tailor support), 6 (67%) completed all 12 questions by text or website and 5 (56%) texted a quit date to the system. Of the 11 activating MiQuit, 5 (45%, 95% CI 21% to 72%) stopped the programme prematurely. Conclusions A low-intensity, cheap cessation intervention promoted at very low cost, resulted in a small but potentially impactful uptake rate by pregnant smokers. PMID:26493459

Using text mining techniques to extract phenotypic information from the PhenoCHF corpus

PubMed Central

2015-01-01

Background Phenotypic information locked away in unstructured narrative text presents significant barriers to information accessibility, both for clinical practitioners and for computerised applications used for clinical research purposes. Text mining (TM) techniques have previously been applied successfully to extract different types of information from text in the biomedical domain. They have the potential to be extended to allow the extraction of information relating to phenotypes from free text. Methods To stimulate the development of TM systems that are able to extract phenotypic information from text, we have created a new corpus (PhenoCHF) that is annotated by domain experts with several types of phenotypic information relating to congestive heart failure. To ensure that systems developed using the corpus are robust to multiple text types, it integrates text from heterogeneous sources, i.e., electronic health records (EHRs) and scientific articles from the literature. We have developed several different phenotype extraction methods to demonstrate the utility of the corpus, and tested these methods on a further corpus, i.e., ShARe/CLEF 2013. Results Evaluation of our automated methods showed that PhenoCHF can facilitate the training of reliable phenotype extraction systems, which are robust to variations in text type. These results have been reinforced by evaluating our trained systems on the ShARe/CLEF corpus, which contains clinical records of various types. Like other studies within the biomedical domain, we found that solutions based on conditional random fields produced the best results, when coupled with a rich feature set. Conclusions PhenoCHF is the first annotated corpus aimed at encoding detailed phenotypic information. The unique heterogeneous composition of the corpus has been shown to be advantageous in the training of systems that can accurately extract phenotypic information from a range of different text types. Although the scope of our annotation is currently limited to a single disease, the promising results achieved can stimulate further work into the extraction of phenotypic information for other diseases. The PhenoCHF annotation guidelines and annotations are publicly available at https://code.google.com/p/phenochf-corpus. PMID:26099853

Using text mining techniques to extract phenotypic information from the PhenoCHF corpus.

PubMed

Alnazzawi, Noha; Thompson, Paul; Batista-Navarro, Riza; Ananiadou, Sophia

2015-01-01

Phenotypic information locked away in unstructured narrative text presents significant barriers to information accessibility, both for clinical practitioners and for computerised applications used for clinical research purposes. Text mining (TM) techniques have previously been applied successfully to extract different types of information from text in the biomedical domain. They have the potential to be extended to allow the extraction of information relating to phenotypes from free text. To stimulate the development of TM systems that are able to extract phenotypic information from text, we have created a new corpus (PhenoCHF) that is annotated by domain experts with several types of phenotypic information relating to congestive heart failure. To ensure that systems developed using the corpus are robust to multiple text types, it integrates text from heterogeneous sources, i.e., electronic health records (EHRs) and scientific articles from the literature. We have developed several different phenotype extraction methods to demonstrate the utility of the corpus, and tested these methods on a further corpus, i.e., ShARe/CLEF 2013. Evaluation of our automated methods showed that PhenoCHF can facilitate the training of reliable phenotype extraction systems, which are robust to variations in text type. These results have been reinforced by evaluating our trained systems on the ShARe/CLEF corpus, which contains clinical records of various types. Like other studies within the biomedical domain, we found that solutions based on conditional random fields produced the best results, when coupled with a rich feature set. PhenoCHF is the first annotated corpus aimed at encoding detailed phenotypic information. The unique heterogeneous composition of the corpus has been shown to be advantageous in the training of systems that can accurately extract phenotypic information from a range of different text types. Although the scope of our annotation is currently limited to a single disease, the promising results achieved can stimulate further work into the extraction of phenotypic information for other diseases. The PhenoCHF annotation guidelines and annotations are publicly available at https://code.google.com/p/phenochf-corpus.

Literature mining, gene-set enrichment and pathway analysis for target identification in Behçet's disease.

PubMed

Wilson, Paul; Larminie, Christopher; Smith, Rona

2016-01-01

To use literature mining to catalogue Behçet's associated genes, and advanced computational methods to improve the understanding of the pathways and signalling mechanisms that lead to the typical clinical characteristics of Behçet's patients. To extend this technique to identify potential treatment targets for further experimental validation. Text mining methods combined with gene enrichment tools, pathway analysis and causal analysis algorithms. This approach identified 247 human genes associated with Behçet's disease and the resulting disease map, comprising 644 nodes and 19220 edges, captured important details of the relationships between these genes and their associated pathways, as described in diverse data repositories. Pathway analysis has identified how Behçet's associated genes are likely to participate in innate and adaptive immune responses. Causal analysis algorithms have identified a number of potential therapeutic strategies for further investigation. Computational methods have captured pertinent features of the prominent disease characteristics presented in Behçet's disease and have highlighted NOD2, ICOS and IL18 signalling as potential therapeutic strategies.

Semantic Classification of Diseases in Discharge Summaries Using a Context-aware Rule-based Classifier

PubMed Central

Solt, Illés; Tikk, Domonkos; Gál, Viktor; Kardkovács, Zsolt T.

2009-01-01

Objective Automated and disease-specific classification of textual clinical discharge summaries is of great importance in human life science, as it helps physicians to make medical studies by providing statistically relevant data for analysis. This can be further facilitated if, at the labeling of discharge summaries, semantic labels are also extracted from text, such as whether a given disease is present, absent, questionable in a patient, or is unmentioned in the document. The authors present a classification technique that successfully solves the semantic classification task. Design The authors introduce a context-aware rule-based semantic classification technique for use on clinical discharge summaries. The classification is performed in subsequent steps. First, some misleading parts are removed from the text; then the text is partitioned into positive, negative, and uncertain context segments, then a sequence of binary classifiers is applied to assign the appropriate semantic labels. Measurement For evaluation the authors used the documents of the i2b2 Obesity Challenge and adopted its evaluation measures: F1-macro and F1-micro for measurements. Results On the two subtasks of the Obesity Challenge (textual and intuitive classification) the system performed very well, and achieved a F1-macro = 0.80 for the textual and F1-macro = 0.67 for the intuitive tasks, and obtained second place at the textual and first place at the intuitive subtasks of the challenge. Conclusions The authors show in the paper that a simple rule-based classifier can tackle the semantic classification task more successfully than machine learning techniques, if the training data are limited and some semantic labels are very sparse. PMID:19390101

Longitudinal Neuroimaging Hippocampal Markers for Diagnosing Alzheimer's Disease.

PubMed

Platero, Carlos; Lin, Lin; Tobar, M Carmen

2018-05-21

Hippocampal atrophy measures from magnetic resonance imaging (MRI) are powerful tools for monitoring Alzheimer's disease (AD) progression. In this paper, we introduce a longitudinal image analysis framework based on robust registration and simultaneous hippocampal segmentation and longitudinal marker classification of brain MRI of an arbitrary number of time points. The framework comprises two innovative parts: a longitudinal segmentation and a longitudinal classification step. The results show that both steps of the longitudinal pipeline improved the reliability and the accuracy of the discrimination between clinical groups. We introduce a novel approach to the joint segmentation of the hippocampus across multiple time points; this approach is based on graph cuts of longitudinal MRI scans with constraints on hippocampal atrophy and supported by atlases. Furthermore, we use linear mixed effect (LME) modeling for differential diagnosis between clinical groups. The classifiers are trained from the average residue between the longitudinal marker of the subjects and the LME model. In our experiments, we analyzed MRI-derived longitudinal hippocampal markers from two publicly available datasets (Alzheimer's Disease Neuroimaging Initiative, ADNI and Minimal Interval Resonance Imaging in Alzheimer's Disease, MIRIAD). In test/retest reliability experiments, the proposed method yielded lower volume errors and significantly higher dice overlaps than the cross-sectional approach (volume errors: 1.55% vs 0.8%; dice overlaps: 0.945 vs 0.975). To diagnose AD, the discrimination ability of our proposal gave an area under the receiver operating characteristic (ROC) curve (AUC) [Formula: see text] 0.947 for the control vs AD, AUC [Formula: see text] 0.720 for mild cognitive impairment (MCI) vs AD, and AUC [Formula: see text] 0.805 for the control vs MCI.

Clinical Reasoning Terms Included in Clinical Problem Solving Exercises?

PubMed Central

Musgrove, John L.; Morris, Jason; Estrada, Carlos A.; Kraemer, Ryan R.

2016-01-01

Background Published clinical problem solving exercises have emerged as a common tool to illustrate aspects of the clinical reasoning process. The specific clinical reasoning terms mentioned in such exercises is unknown. Objective We identified which clinical reasoning terms are mentioned in published clinical problem solving exercises and compared them to clinical reasoning terms given high priority by clinician educators. Methods A convenience sample of clinician educators prioritized a list of clinical reasoning terms (whether to include, weight percentage of top 20 terms). The authors then electronically searched the terms in the text of published reports of 4 internal medicine journals between January 2010 and May 2013. Results The top 5 clinical reasoning terms ranked by educators were dual-process thinking (weight percentage = 24%), problem representation (12%), illness scripts (9%), hypothesis generation (7%), and problem categorization (7%). The top clinical reasoning terms mentioned in the text of 79 published reports were context specificity (n = 20, 25%), bias (n = 13, 17%), dual-process thinking (n = 11, 14%), illness scripts (n = 11, 14%), and problem representation (n = 10, 13%). Context specificity and bias were not ranked highly by educators. Conclusions Some core concepts of modern clinical reasoning theory ranked highly by educators are mentioned explicitly in published clinical problem solving exercises. However, some highly ranked terms were not used, and some terms used were not ranked by the clinician educators. Effort to teach clinical reasoning to trainees may benefit from a common nomenclature of clinical reasoning terms. PMID:27168884

Clinical Reasoning Terms Included in Clinical Problem Solving Exercises?

PubMed

Musgrove, John L; Morris, Jason; Estrada, Carlos A; Kraemer, Ryan R

2016-05-01

Background Published clinical problem solving exercises have emerged as a common tool to illustrate aspects of the clinical reasoning process. The specific clinical reasoning terms mentioned in such exercises is unknown. Objective We identified which clinical reasoning terms are mentioned in published clinical problem solving exercises and compared them to clinical reasoning terms given high priority by clinician educators. Methods A convenience sample of clinician educators prioritized a list of clinical reasoning terms (whether to include, weight percentage of top 20 terms). The authors then electronically searched the terms in the text of published reports of 4 internal medicine journals between January 2010 and May 2013. Results The top 5 clinical reasoning terms ranked by educators were dual-process thinking (weight percentage = 24%), problem representation (12%), illness scripts (9%), hypothesis generation (7%), and problem categorization (7%). The top clinical reasoning terms mentioned in the text of 79 published reports were context specificity (n = 20, 25%), bias (n = 13, 17%), dual-process thinking (n = 11, 14%), illness scripts (n = 11, 14%), and problem representation (n = 10, 13%). Context specificity and bias were not ranked highly by educators. Conclusions Some core concepts of modern clinical reasoning theory ranked highly by educators are mentioned explicitly in published clinical problem solving exercises. However, some highly ranked terms were not used, and some terms used were not ranked by the clinician educators. Effort to teach clinical reasoning to trainees may benefit from a common nomenclature of clinical reasoning terms.

The Impact of Youth-Friendly Structures of Care on Retention Among HIV-Infected Youth

PubMed Central

Yehia, Baligh R.; Gaur, Aditya H.; Rutstein, Richard; Gebo, Kelly; Keruly, Jeanne C.; Moore, Richard D.; Nijhawan, Ank E.; Agwu, Allison L.

2016-01-01

Abstract Limited data exist on how structures of care impact retention among youth living with HIV (YLHIV). We describe the availability of youth-friendly structures of care within HIV Research Network (HIVRN) clinics and examine their association with retention in HIV care. Data from 680 15- to 24-year-old YLHIV receiving care at 7 adult and 5 pediatric clinics in 2011 were included in the analysis. The primary outcome was retention in care, defined as completing ≥2 primary HIV care visits ≥90 days apart in a 12-month period. Sites were surveyed to assess the availability of clinic structures defined a priori as ‘youth-friendly’. Univariate and multivariable logistic regression models assessed structures associated with retention in care. Among 680 YLHIV, 85% were retained. Nearly half (48%) of the 680 YLHIV attended clinics with youth-friendly waiting areas, 36% attended clinics with evening hours, 73% attended clinics with adolescent health-trained providers, 87% could email or text message providers, and 73% could schedule a routine appointment within 2 weeks. Adjusting for demographic and clinical factors, YLHIV were more likely to be retained in care at clinics with a youth-friendly waiting area (AOR 2.47, 95% CI [1.11–5.52]), evening clinic hours (AOR 1.94; 95% CI [1.13–3.33]), and providers with adolescent health training (AOR 1.98; 95% CI [1.01–3.86]). Youth-friendly structures of care impact retention in care among YLHIV. Further investigations are needed to determine how to effectively implement youth-friendly strategies across clinical settings where YLHIV receive care. PMID:26983056

Ubiquitous testing using tablets: its impact on medical student perceptions of and engagement in learning.

PubMed

Kim, Kyong-Jee; Hwang, Jee-Young

2016-03-01

Ubiquitous testing has the potential to affect medical education by enhancing the authenticity of the assessment using multimedia items. This study explored medical students' experience with ubiquitous testing and its impact on student learning. A cohort (n=48) of third-year students at a medical school in South Korea participated in this study. The students were divided into two groups and were given different versions of 10 content-matched items: one in text version (the text group) and the other in multimedia version (the multimedia group). Multimedia items were delivered using tablets. Item response analyses were performed to compare item characteristics between the two versions. Additionally, focus group interviews were held to investigate the students' experiences of ubiquitous testing. The mean test score was significantly higher in the text group. Item difficulty and discrimination did not differ between text and multimedia items. The participants generally showed positive responses on ubiquitous testing. Still, they felt that the lectures that they had taken in preclinical years did not prepare them enough for this type of assessment and clinical encounters during clerkships were more helpful. To be better prepared, the participants felt that they needed to engage more actively in learning in clinical clerkships and have more access to multimedia learning resources. Ubiquitous testing can positively affect student learning by reinforcing the importance of being able to understand and apply knowledge in clinical contexts, which drives students to engage more actively in learning in clinical settings.

Tell me what's wrong with me: a discourse analysis approach to the concept of patient autonomy.

PubMed Central

Nessa, J; Malterud, K

1998-01-01

BACKGROUND: Patient autonomy has gradually replaced physician paternalism as an ethical ideal. However, in a medical context, the principle of individual autonomy has different meanings. More knowledge is needed about what is and should be an appropriate understanding of the concept of patient autonomy in clinical practice. AIM: To challenge the traditional concept of patient autonomy by applying a discourse analysis to the issue. METHOD: A qualitative case study approach with material from one consultation. The discourse is interpreted according to pragmatic and text-linguistic principles and provides the basis of a theoretical discussion of different concepts of patient autonomy. RESULTS: The consultation transcript illustrates how the patient's wishes can be respected in real life. The patient, her husband and the doctor are all involved in the discourse dynamics, governed by the subject matter, namely her mental illness. CONCLUSION: We suggest a dynamic and dialogue-based conception of autonomy as adequate for clinical purposes. These perspectives, based on mutual understanding, take communication between patient and doctor as their starting point. According to this approach, autonomy requires a genuine dialogue, an interpersonal mode of being which we choose to call "authentic interaction". PMID:9873980

Graph-based layout analysis for PDF documents

NASA Astrophysics Data System (ADS)

Xu, Canhui; Tang, Zhi; Tao, Xin; Li, Yun; Shi, Cao

2013-03-01

To increase the flexibility and enrich the reading experience of e-book on small portable screens, a graph based method is proposed to perform layout analysis on Portable Document Format (PDF) documents. Digital born document has its inherent advantages like representing texts and fractional images in explicit form, which can be straightforwardly exploited. To integrate traditional image-based document analysis and the inherent meta-data provided by PDF parser, the page primitives including text, image and path elements are processed to produce text and non text layer for respective analysis. Graph-based method is developed in superpixel representation level, and page text elements corresponding to vertices are used to construct an undirected graph. Euclidean distance between adjacent vertices is applied in a top-down manner to cut the graph tree formed by Kruskal's algorithm. And edge orientation is then used in a bottom-up manner to extract text lines from each sub tree. On the other hand, non-textual objects are segmented by connected component analysis. For each segmented text and non-text composite, a 13-dimensional feature vector is extracted for labelling purpose. The experimental results on selected pages from PDF books are presented.

Value of XML in the implementation of clinical practice guidelines--the issue of content retrieval and presentation.

PubMed

Hoelzer, S; Schweiger, R K; Boettcher, H A; Tafazzoli, A G; Dudeck, J

2001-01-01

The purpose of guidelines in clinical practice is to improve the effectiveness and efficiency of clinical care. It is known that nationally or internationally produced guidelines which, in particular, do not involve medical processes at the time of consultation, do not take local factors into account, and have no consistent implementation strategy, have limited impact in changing either the behaviour of physicians, or patterns of care. The literature provides evidence for the effectiveness of computerization of CPGs for increasing compliance and improving patient outcomes. Probably the most effective concepts are knowledge-based functions for decision support or monitoring that are integrated in clinical information systems. This approach is mostly restricted by the effort required for development and maintenance of the information systems and the limited number of implemented medical rules. Most of the guidelines are text-based, and are primarily published in medical journals and posted on the internet. However, internet-published guidelines have little impact on the behaviour of physicians. It can be difficult and time-consuming to browse the internet to find (a) the correct guidelines to an existing diagnosis and (b) and adequate recommendation for a specific clinical problem. Our objective is to provide a web-based guideline service that takes as input clinical data on a particular patient and returns as output a customizable set of recommendations regarding diagnosis and treatment. Information in healthcare is to a very large extent transmitted and stored as unstructured or slightly structured text such as discharge letters, reports, forms, etc. The same applies for facilities containing medical information resources for clinical purposes and research such as text books, articles, guidelines, etc. Physicians are used to obtaining information from text-based sources. Since most guidelines are text-based, it would be practical to use a document-based solution that preserves the original cohesiveness. The lack of structure limits the automatic identification and extraction of the information contained in these resources. For this reason, we have chosen a document-based approach using eXtensible Markup Language (XML) with its schema definition and related technologies. XML empowers the applications for in-context searching. In addition it allows the same content to be represented in different ways. Our XML reference clinical data model for guidelines has been realized with the XML schema definition. The schema is used for structuring new text-based guidelines and updating existing documents. It is also used to establish search strategies on the document base. We hypothesize that enabling the physicians to query the available CPGs easily, and to get access to selected and specific information at the point of care will foster increased use. Based on current evidence we are confident that it will have substantial impact on the care provided, and will improve health outcomes.

Fitting Higgs data with nonlinear effective theory.

PubMed

Buchalla, G; Catà, O; Celis, A; Krause, C

2016-01-01

In a recent paper we showed that the electroweak chiral Lagrangian at leading order is equivalent to the conventional [Formula: see text] formalism used by ATLAS and CMS to test Higgs anomalous couplings. Here we apply this fact to fit the latest Higgs data. The new aspect of our analysis is a systematic interpretation of the fit parameters within an EFT. Concentrating on the processes of Higgs production and decay that have been measured so far, six parameters turn out to be relevant: [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text]. A global Bayesian fit is then performed with the result [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text]. Additionally, we show how this leading-order parametrization can be generalized to next-to-leading order, thus improving the [Formula: see text] formalism systematically. The differences with a linear EFT analysis including operators of dimension six are also discussed. One of the main conclusions of our analysis is that since the conventional [Formula: see text] formalism can be properly justified within a QFT framework, it should continue to play a central role in analyzing and interpreting Higgs data.

What Pauline Doesn't Know: Using Guided Fiction Writing to Educate Health Professionals about Cultural Competence.

PubMed

Saffran, Lise

2017-01-07

Research linking reading literary fiction to empathy supports health humanities programs in which reflective writing accompanies close readings of texts, both to explore principles of storytelling (narrative arc and concrete language) and to promote an examination of biases in care. Little attention has been paid to the possible contribution of guided fiction-writing in health humanities curricula toward enhancing cultural competence among health professionals, both clinical and community-based. Through an analysis of the short story "Pie Dance" by Molly Giles, juxtaposed with descriptions of specific writing exercises, this paper explains how the demands of writing fiction promote cultural competency.

Research MethodologyOverview of Qualitative Research

PubMed Central

GROSSOEHME, DANIEL H.

2015-01-01

Qualitative research methods are a robust tool for chaplaincy research questions. Similar to much of chaplaincy clinical care, qualitative research generally works with written texts, often transcriptions of individual interviews or focus group conversations and seeks to understand the meaning of experience in a study sample. This article describes three common methodologies: ethnography, grounded theory, and phenomenology. Issues to consider relating to the study sample, design, and analysis are discussed. Enhancing the validity of the data, as well reliability and ethical issues in qualitative research are described. Qualitative research is an accessible way for chaplains to contribute new knowledge about the sacred dimension of people's lived experience. PMID:24926897

Mobile Technology Boosts the Effectiveness of Psychotherapy and Behavioral Interventions: A Meta-analysis

PubMed Central

Lindhiem, Oliver; Bennett, Charles B.; Rosen, Dana; Silk, Jennifer

2015-01-01

We conducted a meta-analysis on the effects of mobile technology on treatment outcome for psychotherapy and other behavioral interventions. Our search of the literature resulted in 26 empirical articles describing 25 clinical trials testing the benefits of smartphone applications, PDAs, or text messaging systems either to supplement treatment or substitute for direct contact with a clinician. Overall, mobile technology use was associated with superior treatment outcome across all study designs and control conditions, ES = .34, p < .0001. For the subset of 10 studies that looked specifically at the added benefit of mobile technology using a rigorous “Treatment” versus “Treatment + Mobile” design, effect sizes were only slightly more modest (ES = .27) and still significant (p < .05). Overall, the results support the role of mobile technology for the delivery of psychotherapy and other behavioral interventions. PMID:26187164

How novice, skilled and advanced clinical researchers include variables in a case report form for clinical research: a qualitative study.

PubMed

Chu, Hongling; Zeng, Lin; Fetters, Micheal D; Li, Nan; Tao, Liyuan; Shi, Yanyan; Zhang, Hua; Wang, Xiaoxiao; Li, Fengwei; Zhao, Yiming

2017-09-18

Despite varying degrees in research training, most academic clinicians are expected to conduct clinical research. The objective of this research was to understand how clinical researchers of different skill levels include variables in a case report form for their clinical research. The setting for this research was a major academic institution in Beijing, China. The target population was clinical researchers with three levels of experience, namely, limited clinical research experience, clinicians with rich clinical research experience and clinical research experts. Using a qualitative approach, we conducted 13 individual interviews (face to face) and one group interview (n=4) with clinical researchers from June to September 2016. Based on maximum variation sampling to identify researchers with three levels of research experience: eight clinicians with limited clinical research experience, five clinicians with rich clinical research experience and four clinical research experts. These 17 researchers had diverse hospital-based medical specialties and or specialisation in clinical research. Our analysis yields a typology of three processes developing a case report form that varies according to research experience level. Novice clinician researchers often have an incomplete protocol or none at all, and conduct data collection and publication based on a general framework. Experienced clinician researchers include variables in the case report form based on previous experience with attention to including domains or items at risk for omission and by eliminating unnecessary variables. Expert researchers consider comprehensively in advance data collection and implementation needs and plan accordingly. These results illustrate increasing levels of sophistication in research planning that increase sophistication in selection for variables in the case report form. These findings suggest that novice and intermediate-level researchers could benefit by emulating the comprehensive planning procedures such as those used by expert clinical researchers. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Measurement properties of self-report physical activity assessment tools in stroke: a protocol for a systematic review

PubMed Central

Martins, Júlia Caetano; Aguiar, Larissa Tavares; Nadeau, Sylvie; Scianni, Aline Alvim; Teixeira-Salmela, Luci Fuscaldi; Faria, Christina Danielli Coelho de Morais

2017-01-01

Introduction Self-report physical activity assessment tools are commonly used for the evaluation of physical activity levels in individuals with stroke. A great variety of these tools have been developed and widely used in recent years, which justify the need to examine their measurement properties and clinical utility. Therefore, the main objectives of this systematic review are to examine the measurement properties and clinical utility of self-report measures of physical activity and discuss the strengths and limitations of the identified tools. Methods and analysis A systematic review of studies that investigated the measurement properties and/or clinical utility of self-report physical activity assessment tools in stroke will be conducted. Electronic searches will be performed in five databases: Medical Literature Analysis and Retrieval System Online (MEDLINE) (PubMed), Excerpta Medica Database (EMBASE), Physiotherapy Evidence Database (PEDro), Literatura Latino-Americana e do Caribe em Ciências da Saúde (LILACS) and Scientific Electronic Library Online (SciELO), followed by hand searches of the reference lists of the included studies. Two independent reviewers will screen all retrieve titles, abstracts, and full texts, according to the inclusion criteria and will also extract the data. A third reviewer will be referred to solve any disagreement. A descriptive summary of the included studies will contain the design, participants, as well as the characteristics, measurement properties, and clinical utility of the self-report tools. The methodological quality of the studies will be evaluated using the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) checklist and the clinical utility of the identified tools will be assessed considering predefined criteria. This systematic review will follow the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) statement. Discussion This systematic review will provide an extensive review of the measurement properties and clinical utility of self-report physical activity assessment tools used in individuals with stroke, which would benefit clinicians and researchers. Trial registration number PROSPERO CRD42016037146. PMID:28193848

Malignant transformation of actinic cheilitis: A systematic review of observational studies.

PubMed

Dancyger, Alex; Heard, Victoria; Huang, Baikai; Suley, Cameron; Tang, Dorothy; Ariyawardana, Anura

2018-06-04

The aim of the present systematic review was to determine the malignant transformation rate of actinic cheilitis (AC). A comprehensive literature search was conducted using Medline/PubMed, Cumulative Index of Nursing and Allied Health Literature, Scopus, OvidSP, and Google Scholar. The inclusion criteria comprised of observational human studies involving the malignant transformation of AC and publications in English. Studies included in this review were clinical follow-up, cohort, retrospective, or prospective investigations. The search yielded 1126 articles, and after exclusion, 34 full-text articles were eligible for full-text analysis. Only one article met the inclusion criteria. Based on the included article, it was determined that the malignant transformation rate of AC to squamous cell carcinoma (SCC) was 3.07%. Excluded articles focused on the clinicopathological characteristics and treatment efficacies of AC, and no malignant transformation rate was assessed. There is a need for more clinical studies on the malignant transformation of AC, as lip cancer is a public health concern. High-risk populations, including those living in tropical regions, have excessive exposure to UV radiation, and have older aged males, fair-skinned people, and smokers should be identified to prevent AC and its malignant change. Health practitioners should facilitate early intervention to prevent the progression of AC to SCC of the lip. © 2018 John Wiley & Sons Australia, Ltd.

Medical subdomain classification of clinical notes using a machine learning-based natural language processing approach.

PubMed

Weng, Wei-Hung; Wagholikar, Kavishwar B; McCray, Alexa T; Szolovits, Peter; Chueh, Henry C

2017-12-01

The medical subdomain of a clinical note, such as cardiology or neurology, is useful content-derived metadata for developing machine learning downstream applications. To classify the medical subdomain of a note accurately, we have constructed a machine learning-based natural language processing (NLP) pipeline and developed medical subdomain classifiers based on the content of the note. We constructed the pipeline using the clinical NLP system, clinical Text Analysis and Knowledge Extraction System (cTAKES), the Unified Medical Language System (UMLS) Metathesaurus, Semantic Network, and learning algorithms to extract features from two datasets - clinical notes from Integrating Data for Analysis, Anonymization, and Sharing (iDASH) data repository (n = 431) and Massachusetts General Hospital (MGH) (n = 91,237), and built medical subdomain classifiers with different combinations of data representation methods and supervised learning algorithms. We evaluated the performance of classifiers and their portability across the two datasets. The convolutional recurrent neural network with neural word embeddings trained-medical subdomain classifier yielded the best performance measurement on iDASH and MGH datasets with area under receiver operating characteristic curve (AUC) of 0.975 and 0.991, and F1 scores of 0.845 and 0.870, respectively. Considering better clinical interpretability, linear support vector machine-trained medical subdomain classifier using hybrid bag-of-words and clinically relevant UMLS concepts as the feature representation, with term frequency-inverse document frequency (tf-idf)-weighting, outperformed other shallow learning classifiers on iDASH and MGH datasets with AUC of 0.957 and 0.964, and F1 scores of 0.932 and 0.934 respectively. We trained classifiers on one dataset, applied to the other dataset and yielded the threshold of F1 score of 0.7 in classifiers for half of the medical subdomains we studied. Our study shows that a supervised learning-based NLP approach is useful to develop medical subdomain classifiers. The deep learning algorithm with distributed word representation yields better performance yet shallow learning algorithms with the word and concept representation achieves comparable performance with better clinical interpretability. Portable classifiers may also be used across datasets from different institutions.

De-identifying an EHR database - anonymity, correctness and readability of the medical record.

PubMed

Pantazos, Kostas; Lauesen, Soren; Lippert, Soren

2011-01-01

Electronic health records (EHR) contain a large amount of structured data and free text. Exploring and sharing clinical data can improve healthcare and facilitate the development of medical software. However, revealing confidential information is against ethical principles and laws. We de-identified a Danish EHR database with 437,164 patients. The goal was to generate a version with real medical records, but related to artificial persons. We developed a de-identification algorithm that uses lists of named entities, simple language analysis, and special rules. Our algorithm consists of 3 steps: collect lists of identifiers from the database and external resources, define a replacement for each identifier, and replace identifiers in structured data and free text. Some patient records could not be safely de-identified, so the de-identified database has 323,122 patient records with an acceptable degree of anonymity, readability and correctness (F-measure of 95%). The algorithm has to be adjusted for each culture, language and database.

Systematic review for geo-authentic Lonicerae Japonicae Flos.

PubMed

Yang, Xingyue; Liu, Yali; Hou, Aijuan; Yang, Yang; Tian, Xin; He, Liyun

2017-06-01

In traditional Chinese medicine, Lonicerae Japonicae Flos is commonly used as anti-inflammatory, antiviral, and antipyretic herbal medicine, and geo-authentic herbs are believed to present the highest quality among all samples from different regions. To discuss the current situation and trend of geo-authentic Lonicerae Japonicae Flos, we searched Chinese Biomedicine Literature Database, Chinese Journal Full-text Database, Chinese Scientific Journal Full-text Database, Cochrane Central Register of Controlled Trials, Wanfang, and PubMed. We investigated all studies up to November 2015 pertaining to quality assessment, discrimination, pharmacological effects, planting or processing, or ecological system of geo-authentic Lonicerae Japonicae Flos. Sixty-five studies mainly discussing about chemical fingerprint, component analysis, planting and processing, discrimination between varieties, ecological system, pharmacological effects, and safety were systematically reviewed. By analyzing these studies, we found that the key points of geo-authentic Lonicerae Japonicae Flos research were quality and application. Further studies should focus on improving the quality by selecting the more superior of all varieties and evaluating clinical effectiveness.

OpenCyto: An Open Source Infrastructure for Scalable, Robust, Reproducible, and Automated, End-to-End Flow Cytometry Data Analysis

PubMed Central

Finak, Greg; Frelinger, Jacob; Jiang, Wenxin; Newell, Evan W.; Ramey, John; Davis, Mark M.; Kalams, Spyros A.; De Rosa, Stephen C.; Gottardo, Raphael

2014-01-01

Flow cytometry is used increasingly in clinical research for cancer, immunology and vaccines. Technological advances in cytometry instrumentation are increasing the size and dimensionality of data sets, posing a challenge for traditional data management and analysis. Automated analysis methods, despite a general consensus of their importance to the future of the field, have been slow to gain widespread adoption. Here we present OpenCyto, a new BioConductor infrastructure and data analysis framework designed to lower the barrier of entry to automated flow data analysis algorithms by addressing key areas that we believe have held back wider adoption of automated approaches. OpenCyto supports end-to-end data analysis that is robust and reproducible while generating results that are easy to interpret. We have improved the existing, widely used core BioConductor flow cytometry infrastructure by allowing analysis to scale in a memory efficient manner to the large flow data sets that arise in clinical trials, and integrating domain-specific knowledge as part of the pipeline through the hierarchical relationships among cell populations. Pipelines are defined through a text-based csv file, limiting the need to write data-specific code, and are data agnostic to simplify repetitive analysis for core facilities. We demonstrate how to analyze two large cytometry data sets: an intracellular cytokine staining (ICS) data set from a published HIV vaccine trial focused on detecting rare, antigen-specific T-cell populations, where we identify a new subset of CD8 T-cells with a vaccine-regimen specific response that could not be identified through manual analysis, and a CyTOF T-cell phenotyping data set where a large staining panel and many cell populations are a challenge for traditional analysis. The substantial improvements to the core BioConductor flow cytometry packages give OpenCyto the potential for wide adoption. It can rapidly leverage new developments in computational cytometry and facilitate reproducible analysis in a unified environment. PMID:25167361

OpenCyto: an open source infrastructure for scalable, robust, reproducible, and automated, end-to-end flow cytometry data analysis.

PubMed

Finak, Greg; Frelinger, Jacob; Jiang, Wenxin; Newell, Evan W; Ramey, John; Davis, Mark M; Kalams, Spyros A; De Rosa, Stephen C; Gottardo, Raphael

2014-08-01

Flow cytometry is used increasingly in clinical research for cancer, immunology and vaccines. Technological advances in cytometry instrumentation are increasing the size and dimensionality of data sets, posing a challenge for traditional data management and analysis. Automated analysis methods, despite a general consensus of their importance to the future of the field, have been slow to gain widespread adoption. Here we present OpenCyto, a new BioConductor infrastructure and data analysis framework designed to lower the barrier of entry to automated flow data analysis algorithms by addressing key areas that we believe have held back wider adoption of automated approaches. OpenCyto supports end-to-end data analysis that is robust and reproducible while generating results that are easy to interpret. We have improved the existing, widely used core BioConductor flow cytometry infrastructure by allowing analysis to scale in a memory efficient manner to the large flow data sets that arise in clinical trials, and integrating domain-specific knowledge as part of the pipeline through the hierarchical relationships among cell populations. Pipelines are defined through a text-based csv file, limiting the need to write data-specific code, and are data agnostic to simplify repetitive analysis for core facilities. We demonstrate how to analyze two large cytometry data sets: an intracellular cytokine staining (ICS) data set from a published HIV vaccine trial focused on detecting rare, antigen-specific T-cell populations, where we identify a new subset of CD8 T-cells with a vaccine-regimen specific response that could not be identified through manual analysis, and a CyTOF T-cell phenotyping data set where a large staining panel and many cell populations are a challenge for traditional analysis. The substantial improvements to the core BioConductor flow cytometry packages give OpenCyto the potential for wide adoption. It can rapidly leverage new developments in computational cytometry and facilitate reproducible analysis in a unified environment.

Text Analysis of Chemistry Thesis and Dissertation Titles

ERIC Educational Resources Information Center

Scalfani, Vincent F.

2017-01-01

Programmatic text analysis can be used to understand patterns and reveal trends in data that would otherwise be difficult or impossible to uncover with manual coding methods. This work uses programmatic text analysis, specifically term frequency counts, to study nearly 10,000 chemistry thesis and dissertation titles from 1911-2015. The thesis and…

Intertextual Content Analysis: An Approach for Analysing Text-Related Discussions with Regard to Movability in Reading and How Text Content Is Handled

ERIC Educational Resources Information Center

Hallesson, Yvonne; Visén, Pia

2018-01-01

Reading and discussing texts as a means for learning subject content are regular features within educational contexts. This paper presents an approach for intertextual content analysis (ICA) of such text-related discussions revealing what the participants make of the text. Thus, in contrast to many other approaches for analysing conversation that…

Working with Data: Discovering Knowledge through Mining and Analysis; Systematic Knowledge Management and Knowledge Discovery; Text Mining; Methodological Approach in Discovering User Search Patterns through Web Log Analysis; Knowledge Discovery in Databases Using Formal Concept Analysis; Knowledge Discovery with a Little Perspective.

ERIC Educational Resources Information Center

Qin, Jian; Jurisica, Igor; Liddy, Elizabeth D.; Jansen, Bernard J; Spink, Amanda; Priss, Uta; Norton, Melanie J.

2000-01-01

These six articles discuss knowledge discovery in databases (KDD). Topics include data mining; knowledge management systems; applications of knowledge discovery; text and Web mining; text mining and information retrieval; user search patterns through Web log analysis; concept analysis; data collection; and data structure inconsistency. (LRW)

Assessing semantic similarity of texts - Methods and algorithms

NASA Astrophysics Data System (ADS)

Rozeva, Anna; Zerkova, Silvia

2017-12-01

Assessing the semantic similarity of texts is an important part of different text-related applications like educational systems, information retrieval, text summarization, etc. This task is performed by sophisticated analysis, which implements text-mining techniques. Text mining involves several pre-processing steps, which provide for obtaining structured representative model of the documents in a corpus by means of extracting and selecting the features, characterizing their content. Generally the model is vector-based and enables further analysis with knowledge discovery approaches. Algorithms and measures are used for assessing texts at syntactical and semantic level. An important text-mining method and similarity measure is latent semantic analysis (LSA). It provides for reducing the dimensionality of the document vector space and better capturing the text semantics. The mathematical background of LSA for deriving the meaning of the words in a given text by exploring their co-occurrence is examined. The algorithm for obtaining the vector representation of words and their corresponding latent concepts in a reduced multidimensional space as well as similarity calculation are presented.

Compiling standardized information from clinical practice: using content analysis and ICF Linking Rules in a goal-oriented youth rehabilitation program.

PubMed

Lustenberger, Nadia A; Prodinger, Birgit; Dorjbal, Delgerjargal; Rubinelli, Sara; Schmitt, Klaus; Scheel-Sailer, Anke

2017-09-23

To illustrate how routinely written narrative admission and discharge reports of a rehabilitation program for eight youths with chronic neurological health conditions can be transformed to the International Classification of Functioning, Disability and Health. First, a qualitative content analysis was conducted by building meaningful units with text segments assigned of the reports to the five elements of the Rehab-Cycle ® : goal; assessment; assignment; intervention; evaluation. Second, the meaningful units were then linked to the ICF using the refined ICF Linking Rules. With the first step of transformation, the emphasis of the narrative reports changed to a process oriented interdisciplinary layout, revealing three thematic blocks of goals: mobility, self-care, mental, and social functions. The linked 95 unique ICF codes could be grouped in clinically meaningful goal-centered ICF codes. Between the two independent linkers, the agreement rate was improved after complementing the rules with additional agreements. The ICF Linking Rules can be used to compile standardized health information from narrative reports if prior structured. The process requires time and expertise. To implement the ICF into common practice, the findings provide the starting point for reporting rehabilitation that builds upon existing practice and adheres to international standards. Implications for Rehabilitation This study provides evidence that routinely collected health information from rehabilitation practice can be transformed to the International Classification of Functioning, Disability and Health by using the "ICF Linking Rules", however, this requires time and expertise. The Rehab-Cycle ® , including assessments, assignments, goal setting, interventions and goal evaluation, serves as feasible framework for structuring this rehabilitation program and ensures that the complexity of local practice is appropriately reflected. The refined "ICF Linking Rules" lead to a standardized transformation process of narrative text and thus a higher quality with increased transparency. As a next step, the resulting format of goal codes supplemented by goal-clarifying codes could be validated to strengthen the implementation of the International Classification of Functioning, Disability and Health into rehabilitation routine by respecting the variety of clinical practice.

Metabolite signatures of exercise training in human skeletal muscle relate to mitochondrial remodelling and cardiometabolic fitness.

PubMed

Huffman, Kim M; Koves, Timothy R; Hubal, Monica J; Abouassi, Hiba; Beri, Nina; Bateman, Lori A; Stevens, Robert D; Ilkayeva, Olga R; Hoffman, Eric P; Muoio, Deborah M; Kraus, William E

2014-11-01

Targeted metabolomic and transcriptomic approaches were used to evaluate the relationship between skeletal muscle metabolite signatures, gene expression profiles and clinical outcomes in response to various exercise training interventions. We hypothesised that changes in mitochondrial metabolic intermediates would predict improvements in clinical risk factors, thereby offering novel insights into potential mechanisms. Subjects at risk of metabolic disease were randomised to 6 months of inactivity or one of five aerobic and/or resistance training programmes (n = 112). Pre/post-intervention assessments included cardiorespiratory fitness ([Formula: see text]), serum triacylglycerols (TGs) and insulin sensitivity (SI). In this secondary analysis, muscle biopsy specimens were used for targeted mass spectrometry-based analysis of metabolic intermediates and measurement of mRNA expression of genes involved in metabolism. Exercise regimens with the largest energy expenditure produced robust increases in muscle concentrations of even-chain acylcarnitines (median 37-488%), which correlated positively with increased expression of genes involved in muscle uptake and oxidation of fatty acids. Along with free carnitine, the aforementioned acylcarnitine metabolites were related to improvements in [Formula: see text], TGs and SI (R = 0.20-0.31, p < 0.05). Muscle concentrations of the tricarboxylic acid cycle intermediates succinate and succinylcarnitine (R = 0.39 and 0.24, p < 0.05) emerged as the strongest correlates of SI. The metabolic signatures of exercise-trained skeletal muscle reflected reprogramming of mitochondrial function and intermediary metabolism and correlated with changes in cardiometabolic fitness. Succinate metabolism and the succinate dehydrogenase complex emerged as a potential regulatory node that intersects with whole-body insulin sensitivity. This study identifies new avenues for mechanistic research aimed at understanding the health benefits of physical activity. Trial registration ClinicalTrials.gov NCT00200993 and NCT00275145 Funding This work was supported by the National Heart, Lung, and Blood Institute (National Institutes of Health), National Institute on Aging (National Institutes of Health) and National Institute of Arthritis and Musculoskeletal and Skin Diseases (National Institutes of Health).

Clinical Information Systems as the Backbone of a Complex Information Logistics Process: Findings from the Clinical Information Systems Perspective for 2016.

PubMed

Hackl, W O; Ganslandt, T

2017-08-01

Objective: To summarize recent research and to propose a selection of best papers published in 2016 in the field of Clinical Information Systems (CIS). Method: The query used to retrieve the articles for the CIS section of the 2016 edition of the IMIA Yearbook of Medical Informatics was reused. It again aimed at identifying relevant publications in the field of CIS from PubMed and Web of Science and comprised search terms from the Medical Subject Headings (MeSH) catalog as well as additional free text search terms. The retrieved articles were categorized in a multi-pass review carried out by the two section editors. The final selection of candidate papers was then peer-reviewed by Yearbook editors and external reviewers. Based on the review results, the best papers were then chosen at the selection meeting with the IMIA Yearbook editorial board. Text mining, term co-occurrence mapping, and topic modelling techniques were used to get an overview on the content of the retrieved articles. Results: The query was carried out in mid-January 2017, yielding a consolidated result set of 2,190 articles published in 921 different journals. Out of them, 14 papers were nominated as candidate best papers and three of them were finally selected as the best papers of the CIS field. The content analysis of the articles revealed the broad spectrum of topics covered by CIS research. Conclusions: The CIS field is multi-dimensional and complex. It is hard to draw a well-defined outline between CIS and other domains or other sections of the IMIA Yearbook. The trends observed in the previous years are progressing. Clinical information systems are more than just sociotechnical systems for data collection, processing, exchange, presentation, and archiving. They are the backbone of a complex, trans-institutional information logistics process. Georg Thieme Verlag KG Stuttgart.

Patient representatives' views on patient information in clinical cancer trials.

PubMed

Dellson, Pia; Nilbert, Mef; Carlsson, Christina

2016-02-01

Patient enrolment into clinical trials is based on oral information and informed consent, which includes an information sheet and a consent certificate. The written information should be complete, but at the same time risks being so complex that it may be questioned if a fully informed consent is possible to provide. We explored patient representatives' views and perceptions on the written trial information used in clinical cancer trials. Written patient information leaflets used in four clinical trials for colorectal cancer were used for the study. The trials included phase I-III trials, randomized and non-randomized trials that evaluated chemotherapy/targeted therapy in the neoadjuvant, adjuvant and palliative settings. Data were collected through focus groups and were analysed using inductive content analysis. Two major themes emerged: emotional responses and cognitive responses. Subthemes related to the former included individual preferences and perceptions of effect, while subthemes related to the latter were comprehensibility and layout. Based on these observations the patient representatives provided suggestions for improvement, which largely included development of future simplified and more attractive informed consent forms. The emotional and cognitive responses to written patient information reported by patient representatives provides a basis for revised formats in future trials and add to the body of information that support use of plain language, structured text and illustrations to improve the informed consent process and thereby patient enrolment into clinical trials.

Text messaging reminders for influenza vaccine in primary care: protocol for a cluster randomised controlled trial (TXT4FLUJAB).

PubMed

Herrett, Emily; van Staa, Tjeerd; Free, Caroline; Smeeth, Liam

2014-05-02

The UK government recommends that at least 75% of people aged under 64 with certain conditions receive an annual influenza vaccination. Primary care practices often fall short of this target and strategies to increase vaccine uptake are required. Text messaging reminders are already used in 30% of practices to remind patients about vaccination, but there has been no trial addressing their effectiveness in increasing influenza vaccine uptake in the UK. The aims of the study are (1) to develop the methodology for conducting cluster randomised trials of text messaging interventions utilising routine electronic health records and (2) to assess the effectiveness of using a text messaging influenza vaccine reminder in achieving an increase in influenza vaccine uptake in patients aged 18-64 with chronic conditions, compared with standard care. This cluster randomised trial will recruit general practices across three settings in English primary care (Clinical Practice Research Datalink, ResearchOne and London iPLATO text messaging software users) and randomise them to either standard care or a text messaging campaign to eligible patients. Flu vaccine uptake will be ascertained using routinely collected, anonymised electronic patient records. This protocol outlines the proposed study design and analysis methods. This study will determine the effectiveness of text messaging vaccine reminders in primary care in increasing influenza vaccine uptake, and will strengthen the methodology for using electronic health records in cluster randomised trials of text messaging interventions. This trial was approved by the Surrey Borders Ethics Committee (13/LO/0872). The trial results will be disseminated at national conferences and published in a peer-reviewed medical journal. The results will also be distributed to the Primary Care Research Network and to all participating general practices. This study is registered at controlled-trials.com ISRCTN48840025, July 2013.

Analysis of the Precision of Variable Flip Angle T1 Mapping with Emphasis on the Noise Propagated from RF Transmit Field Maps.

PubMed

Lee, Yoojin; Callaghan, Martina F; Nagy, Zoltan

2017-01-01

In magnetic resonance imaging, precise measurements of longitudinal relaxation time ( T 1 ) is crucial to acquire useful information that is applicable to numerous clinical and neuroscience applications. In this work, we investigated the precision of T 1 relaxation time as measured using the variable flip angle method with emphasis on the noise propagated from radiofrequency transmit field ([Formula: see text]) measurements. The analytical solution for T 1 precision was derived by standard error propagation methods incorporating the noise from the three input sources: two spoiled gradient echo (SPGR) images and a [Formula: see text] map. Repeated in vivo experiments were performed to estimate the total variance in T 1 maps and we compared these experimentally obtained values with the theoretical predictions to validate the established theoretical framework. Both the analytical and experimental results showed that variance in the [Formula: see text] map propagated comparable noise levels into the T 1 maps as either of the two SPGR images. Improving precision of the [Formula: see text] measurements significantly reduced the variance in the estimated T 1 map. The variance estimated from the repeatedly measured in vivo T 1 maps agreed well with the theoretically-calculated variance in T 1 estimates, thus validating the analytical framework for realistic in vivo experiments. We concluded that for T 1 mapping experiments, the error propagated from the [Formula: see text] map must be considered. Optimizing the SPGR signals while neglecting to improve the precision of the [Formula: see text] map may result in grossly overestimating the precision of the estimated T 1 values.

Individual Profiling Using Text Analysis

DTIC Science & Technology

2016-04-15

Mining a Text for Errors. . . . on Knowledge discovery in data mining , pages 624–628, 2005. [12] Michal Kosinski, David Stillwell, and Thore Graepel...AFRL-AFOSR-UK-TR-2016-0011 Individual Profiling using Text Analysis 140333 Mark Stevenson UNIVERSITY OF SHEFFIELD, DEPARTMENT OF PSYCHOLOGY Final...REPORT TYPE      Final 3.  DATES COVERED (From - To)      15 Sep 2014 to 14 Sep 2015 4.  TITLE AND SUBTITLE Individual Profiling using Text Analysis

Semantic Annotation of Complex Text Structures in Problem Reports

NASA Technical Reports Server (NTRS)

Malin, Jane T.; Throop, David R.; Fleming, Land D.

2011-01-01

Text analysis is important for effective information retrieval from databases where the critical information is embedded in text fields. Aerospace safety depends on effective retrieval of relevant and related problem reports for the purpose of trend analysis. The complex text syntax in problem descriptions has limited statistical text mining of problem reports. The presentation describes an intelligent tagging approach that applies syntactic and then semantic analysis to overcome this problem. The tags identify types of problems and equipment that are embedded in the text descriptions. The power of these tags is illustrated in a faceted searching and browsing interface for problem report trending that combines automatically generated tags with database code fields and temporal information.

Benefits of off-campus education for students in the health sciences: a text-mining analysis.

PubMed

Nakagawa, Kazumasa; Asakawa, Yasuyoshi; Yamada, Keiko; Ushikubo, Mitsuko; Yoshida, Tohru; Yamaguchi, Haruyasu

2012-08-28

In Japan, few community-based approaches have been adopted in health-care professional education, and the appropriate content for such approaches has not been clarified. In establishing community-based education for health-care professionals, clarification of its learning effects is required. A community-based educational program was started in 2009 in the health sciences course at Gunma University, and one of the main elements in this program is conducting classes outside school. The purpose of this study was to investigate using text-analysis methods how the off-campus program affects students. In all, 116 self-assessment worksheets submitted by students after participating in the off-campus classes were decomposed into words. The extracted words were carefully selected from the perspective of contained meaning or content. With the selected terms, the relations to each word were analyzed by means of cluster analysis. Cluster analysis was used to select and divide 32 extracted words into four clusters: cluster 1-"actually/direct," "learn/watch/hear," "how," "experience/participation," "local residents," "atmosphere in community-based clinical care settings," "favorable," "communication/conversation," and "study"; cluster 2-"work of staff member" and "role"; cluster 3-"interaction/communication," "understanding," "feel," "significant/important/necessity," and "think"; and cluster 4-"community," "confusing," "enjoyable," "proactive," "knowledge," "academic knowledge," and "class." The students who participated in the program achieved different types of learning through the off-campus classes. They also had a positive impression of the community-based experience and interaction with the local residents, which is considered a favorable outcome. Off-campus programs could be a useful educational approach for students in health sciences.

Acceptance of dying: a discourse analysis of palliative care literature.

PubMed

Zimmermann, Camilla

2012-07-01

The subject of death denial in the West has been examined extensively in the sociological literature. However, there has not been a similar examination of its "opposite", the acceptance of death. In this study, I use the qualitative method of discourse analysis to examine the use of the term "acceptance" of dying in the palliative care literature from 1970 to 2001. A Medline search was performed by combining the text words "accept or acceptance" with the subject headings "terminal care or palliative care or hospice care", and restricting the search to English language articles in clinical journals discussing acceptance of death in adults. The 40 articles were coded and analysed using a critical discourse analysis method. This paper focuses on the theme of acceptance as integral to palliative care, which had subthemes of acceptance as a goal of care, personal acceptance of healthcare workers, and acceptance as a facilitator of care. For patients and families, death acceptance is a goal that they can be helped to attain; for palliative care staff, acceptance of dying is a personal quality that is a precondition for effective practice. Acceptance not only facilitates the dying process for the patient and family, but also renders care easier. The analysis investigates the intertextuality of these themes with each other and with previous texts. From a Foucauldian perspective, I suggest that the discourse on acceptance of dying represents a productive power, which disciplines patients through apparent psychological and spiritual gratification, and encourages participation in a certain way to die. Copyright © 2012 Elsevier Ltd. All rights reserved.

A systematic review of different substance injection and dry needling for treatment of temporomandibular myofascial pain.

PubMed

Machado, E; Machado, P; Wandscher, V F; Marchionatti, A M E; Zanatta, F B; Kaizer, O B

2018-05-22

Temporomandibular myofascial pain presents a major challenge in the diagnosis of temporomandibular disorders (TMD). Due to the characteristics of this condition, intramuscular injection procedures are often needed for adequate control of symptoms and treatment. Thus, the aim of this systematic review was to evaluate the effectiveness of dry needling and injection with different substances in temporomandibular myofascial pain. Electronic databases PubMed, EMBASE, CENTRAL/Cochrane, Lilacs, Scopus, Web of Science and CAPES Catalog of Dissertations and Theses were searched for randomized clinical trials until January 2018. Manual search was performed in relevant journals and in the references/citations of the included studies. The selection of studies was carried out by two independent reviewers according to eligibility criteria. From 7128 eligible studies, 137 were selected for full-text analysis and 18 were included. Due to the heterogeneity of the primary studies it was not possible to perform a meta-analysis. The narrative analysis of the results showed that most of the studies had methodological limitations and biases that compromised the quality of the findings. Dry needling and local anaesthesic injections seem promising, but there is a need to conduct further randomized clinical trials, with larger samples and longer follow-up times, to evaluate the real effectiveness of the technique and evaluated substances. Copyright © 2018 International Association of Oral and Maxillofacial Surgeons. Published by Elsevier Ltd. All rights reserved.

Does the instrument used for the implant site preparation influence the bone-implant interface? A systematic review of clinical and animal studies.

PubMed

Tretto, P H W; Fabris, V; Cericato, G O; Sarkis-Onofre, R; Bacchi, A

2018-04-24

This systematic review evaluates the influence of the instrument used for the implant site preparation on the bone-implant interface. Any type of clinical or animal study were searched for in MEDLINE/PubMed, ISI Web of Science, and SciVerse Scopus. Two independent reviewers screened titles/abstracts of articles and the full-text of potentially eligible studies. Comparisons of bone to implant contact and crestal bone loss were estimated using pairwise meta-analysis. Twenty-nine studies met the inclusion criteria. The instruments identified in the articles were conventional drills (CDs), osteotome (OT), piezoelectric device (PD), Er:YAG LASER (LS) and osseodensification drills (ODs). The meta-analysis on bone to implant contact suggested no difference between CDs and other techniques and the meta-analysis on crestal bone loss suggested no difference between CDs and PD. The survival of implants in sites prepared with CDs vs. OT or PD presented no significant differences. The use of PD provided lower inflammatory response and earlier bone formation when compared to CDs. ODs provided significant biomechanical improvement in comparison to CDs. LS did not provide any relevant improvement in comparison to CDs or PD. The influence of the instrument used for implant site preparation depended on the property evaluated. Copyright © 2018 International Association of Oral and Maxillofacial Surgeons. Published by Elsevier Ltd. All rights reserved.

[Failure mode and effects analysis on computerized drug prescriptions].

PubMed

Paredes-Atenciano, J A; Roldán-Aviña, J P; González-García, Mercedes; Blanco-Sánchez, M C; Pinto-Melero, M A; Pérez-Ramírez, C; Calvo Rubio-Burgos, Miguel; Osuna-Navarro, F J; Jurado-Carmona, A M

2015-01-01

To identify and analyze errors in drug prescriptions of patients treated in a "high resolution" hospital by applying a Failure mode and effects analysis (FMEA).Material and methods A multidisciplinary group of medical specialties and nursing analyzed medical records where drug prescriptions were held in free text format. An FMEA was developed in which the risk priority index (RPI) was obtained from a cross-sectional observational study using an audit of the medical records, carried out in 2 phases: 1) Pre-intervention testing, and (2) evaluation of improvement actions after the first analysis. An audit sample size of 679 medical records from a total of 2,096 patients was calculated using stratified sampling and random selection of clinical events. Prescription errors decreased by 22.2% in the second phase. FMEA showed a greater RPI in "unspecified route of administration" and "dosage unspecified", with no significant decreases observed in the second phase, although it did detect, "incorrect dosing time", "contraindication due to drug allergy", "wrong patient" or "duplicate prescription", which resulted in the improvement of prescriptions. Drug prescription errors have been identified and analyzed by FMEA methodology, improving the clinical safety of these prescriptions. This tool allows updates of electronic prescribing to be monitored. To avoid such errors would require the mandatory completion of all sections of a prescription. Copyright © 2014 SECA. Published by Elsevier Espana. All rights reserved.

Cinnamon in glycaemic control: Systematic review and meta analysis.

PubMed

Akilen, Rajadurai; Tsiami, Amalia; Devendra, Devasenan; Robinson, Nicola

2012-10-01

Cinnamon seems to be highly bioactive, appearing to mimic the effect of insulin through increased glucose uptake in adipocytes and skeletal muscles. This systematic review and Meta analysis examined the effect of cinnamon on glycaemic control in patients with Type 2 Diabetes mellitus. A systematic literature search was conducted from the earliest possible date through to 01 August 2011. Search terms included free text terms, MeSH and Medline medical index terms such as: "cinnamon", "cinnamomum", "cinnamomum cassia", "cinnamomum zeylanicum", "type 2 diabetes mellitus". Each was crossed with the term "diabetes mellitus". In addition, references of key articles were hand searched. A total of 6 clinical trials met the strict inclusion criteria and considered a total of 435 patients; follow up between 40 days-4 months, doses ranging from 1 g to 6 g per day. Meta-analysis of RCTs showed a significant decrease in mean HbA1c [0.09%; 95% CI was 0.04-0.14] and mean FPG [0.84 mmol/l; 95% CI was 0.66-1.02]. Use of cinnamon showed a beneficial effect on glycaemic control (both HbA1c and FPG) and the short term (<4 months) effects of the use of cinnamon on glycaemic control looks promising. Copyright © 2012 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.

Smartphones in nursing education.

PubMed

Phillippi, Julia C; Wyatt, Tami H

2011-08-01

Smartphones are a new technology similar to PDAs but with expanded functions and greater Internet access. This article explores the potential uses and issues surrounding the use of smartphones in nursing education. While the functions of smartphones, such as sending text messages, viewing videos, and access to the Internet, may seem purely recreational, they can be used within the nursing curriculum to engage students and reinforce learning at any time or location. Smartphones can be used for quick access to educational materials and guidelines during clinical, class, or clinical conference. Students can review instructional videos prior to performing skills and readily reach their clinical instructor via text message. Downloadable applications, subscriptions, and reference materials expand the smartphone functions even further. Common concerns about requiring smartphones in nursing education include cost, disease transmission, and equipment interference; however, there are many ways to overcome these barriers and provide students with constant access to current clinical evidence.

Systematic drug repositioning through mining adverse event data in ClinicalTrials.gov.

PubMed

Su, Eric Wen; Sanger, Todd M

2017-01-01

Drug repositioning (i.e., drug repurposing) is the process of discovering new uses for marketed drugs. Historically, such discoveries were serendipitous. However, the rapid growth in electronic clinical data and text mining tools makes it feasible to systematically identify drugs with the potential to be repurposed. Described here is a novel method of drug repositioning by mining ClinicalTrials.gov. The text mining tools I2E (Linguamatics) and PolyAnalyst (Megaputer) were utilized. An I2E query extracts "Serious Adverse Events" (SAE) data from randomized trials in ClinicalTrials.gov. Through a statistical algorithm, a PolyAnalyst workflow ranks the drugs where the treatment arm has fewer predefined SAEs than the control arm, indicating that potentially the drug is reducing the level of SAE. Hypotheses could then be generated for the new use of these drugs based on the predefined SAE that is indicative of disease (for example, cancer).

Orthodontic trial outcomes: Plentiful, inconsistent, and in need of uniformity? A scoping review.

PubMed

Tsichlaki, Aliki; O'Brien, Kevin; Johal, Ama; Fleming, Padhraig S

2018-06-01

The selection of appropriate outcomes that matter to both patients and operators is increasingly appreciated, with core outcome sets in clinical trials gaining in popularity. The first step in core outcome set development is the generation of a list of possible important outcomes based on a scoping literature review. Moreover, outcome heterogeneity is known to detract from the findings of systematic reviews and meta-analyses. The aim of this study was to identify the range of outcome domains and specific outcome measures in contemporary orthodontic research. Multiple electronic databases were searched from December 31, 2012, to December 31, 2016, to identify clinical trials of orthodontic interventions, with no language restrictions. Abstracts, eligible full texts, and reference lists were screened, and all reported primary and nonprimary outcomes and methods of measurement were recorded. The search identified 1267 abstracts, of which 189 full-text articles were retrieved, and 164 studies were included in the analysis. A total of 54 outcomes were identified and categorized into 14 outcome domains. The most frequently measured outcomes were patient-reported pain, periodontal health, tooth angulation/inclination changes, and treatment duration, followed by rate of tooth movement and skeletal changes. Outcomes that followed the overall course of treatment were assessed in only 14 studies. Patient perspectives are increasingly being accounted for in orthodontic trials; however, there is little consistency in outcome selection among them. The identified list of outcomes will be used to inform a ranking exercise with service users and providers to establish an agreed core outcome set for future orthodontic clinical trials. Copyright © 2018 American Association of Orthodontists. Published by Elsevier Inc. All rights reserved.

Cognitive Pathways: Analysis of Students' Written Texts for Science Understanding

ERIC Educational Resources Information Center

Grimberg, Bruna Irene; Hand, Brian

2009-01-01

The purpose of this study was to reconstruct writers' reasoning process as reflected in their written texts. The codes resulting from the text analysis were related to cognitive operations, ranging from simple to more sophisticated ones. The sequence of the cognitive operations as the text unfolded represents the writer's cognitive pathway at the…

Text Information Extraction System (TIES) | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

TIES is a service based software system for acquiring, deidentifying, and processing clinical text reports using natural language processing, and also for querying, sharing and using this data to foster tissue and image based research, within and between institutions.

Preventing Risky Drinking in Veterans Treated with Prescription Opioids

DTIC Science & Technology

2017-04-01

assessment, brief intervention, monitoring, and extended prevention services delivered through a combination of clinical visits, telephone calls, and text ...tailored text messages and brief monthly telephone contacts. Veterans who continue to drink at risky levels are instead placed in a track that provides...tailored text messages and more frequent telephone calls. In addition to monitoring, these calls provide further prevention/BI services to help the

Preventing Risky Drinking in Veterans Treated with Prescription Opioids

DTIC Science & Technology

2016-04-01

intervention, monitoring, and extended prevention services delivered through a combination of clinical visits, telephone calls, and text messages. We...Veterans who reduce alcohol use to non-hazardous levels during this one-month period continue in a monitoring track, consisting of tailored text ...messages and brief monthly telephone contacts. Veterans who continue to drink at risky levels are instead placed in a track that provides tailored text

SU110. Meaning-Making, Self-identity, and Ambivalence Around Antipsychotics in First-Episode Psychosis

PubMed Central

Berkhout, Susan; Zaheer, Juveria

2017-01-01

Abstract Background: An issue throughout all areas of medicine, nonadherence to medications is particularly challenging in first-episode psychosis (FEP), where discontinuation of medications has been found to be one of the most reliable predictors of relapse after symptom remission (Haddad et al, 2014; Alvarez-Jimenez et al, 2012). And while medication factors and patient expectancies are frequently employed to understand challenges surrounding adherence, there are limits to their explanatory power. Methods: Utilizing ethnographic methodologies, we collected and analyzed narratives of FEP clinic users in order to explore relationships between experiences of illness, contacts with the mental health system, and medication nonadherence. Data were composed of text materials relating to early intervention and first-episode psychosis and antipsychotic medications, longitudinal key informant interviews, and participant observation in a FEP clinic setting in Toronto, Canada. An interpretive thematic analysis of interview transcripts, field notes, and texts was subsequently undertaken, and emerging themes developed iteratively through multiple readings of the texts; the use of multiple coders, member checks, and the range of data sources enabled triangulation of the established themes. Results: The imperative to consistently ingest or inject psychiatric medications can, at times, clash with the lived experience of those struggling to reorient a sense of self in the aftermath of a psychotic illness. Frictions exist between subjective meanings attached to experiences of psychosis and their biomedical framing, leading to ruptures in the clinical setting that are dramatized around medication use. Conclusion: This pilot study demonstrates that a much broader scope of subjective and intersubjective experience is salient to issues surrounding medication use in first-episode psychosis. Moreover, meanings attached to medications are continually shifting, imbued with ambivalence, and overdetermined. As such, limiting analyses of antipsychotic adherence to medication-centric factors and cross-sectional methodologies fail to encapsulate the breadth of relevant meanings and experiences to medications and their mutable nature. These findings offer insights that may further facilitate engagement of individuals around medications and within first-episode services more broadly.

Methotrexate for the Treatment of Pediatric Crohn's Disease: A Systematic Review and Meta-analysis.

PubMed

Colman, Ruben J; Lawton, Rachel C; Dubinsky, Marla C; Rubin, David T

2018-04-23

Methotrexate (MTX) is an immunomodulator used for the treatment of pediatric inflammatory bowel disease (IBD). There are currently no RCTs that assess the treatment efficacy of methotrexate within the pediatric IBD patient population. This systematic review and meta-analysis assesses the efficacy of MTX therapy among the existing pediatric literature. A systematic literature search was performed using MEDLINE and the Cochrane library from inception until March 2016. Synonyms for 'pediatric', 'methotrexate' and 'IBD' were utilized as both free text and MESH search terms. The studies included contained clinical remission (CR) rates for MTX treatment of pediatric IBD patients 18 yrs old, as mono- or combination therapy. Case studies with <10 patients were excluded. Quality assessment was performed with the Newcastle-Ottawa Scale. Meta-analysis calculated pooled CR rates. A random-effects meta-analysis with forest plots was performed using R. Fourteen (11 monotherapy, 1 combination therapy, 2 both; n = 886 patients) observational studies were eligible out of 202 studies. No interventional studies were identified. The pooled achieved CR rate for pediatric CD patients on monotherapy within 3-6 months was 57.7% (95% CI 48.2-66.6%), (P =0.22; I2 = 29.8%). The CR was 37.1% (95% CI 29.5-45.5%), (P = 0.20; I2 = 37.4%) for maintenance therapy at 12 months. Sub-analysis could not identify CR differences between MTX administration types, thiopurine exposure. This meta-analysis demonstrated that, over 50% of pediatric Crohn's disease patients induced with methotrexate achieved clinical remission, while 12-month remission rate was only 37%. Prospective controlled interventional trials should assess treatment efficacy among patient subgroups. 10.1093/ibd/izy078_video1izy078.video15774883936001.

The association between prostatitis and prostate cancer. Systematic review and meta-analysis.

PubMed

Perletti, Gianpaolo; Monti, Elena; Magri, Vittorio; Cai, Tommaso; Cleves, Anne; Trinchieri, Alberto; Montanari, Emanuele

2017-12-31

The main outcome of this review was the association between a history of clinical chronic prostatitis (NIH category II or III) and a histologically confirmed diagnosis of prostate cancer. Crude odds ratios and 95% confidence intervals (CI) were calculated to analyze dichotomous data. For analysis of pooled data we adopted a random-effects model and the inverse variance weighing method. Heterogeneity was assessed by calculating the I2 value. Out of 2794 screened records, we retrieved 16 full-text articles written in English, reporting the data of 15 case-control studies, involving 422.943 patients. Pooled analysis resulted in a significant crude odds ratio of 1.83 (95% CI: 1.43 to 2.35; P < 0.00001). The total set of data showed considerable heterogeneity (I2 = 91%). Both the Egger's test and the Begg's test for funnel plot asymmetry did not reach statistical significance. The 'trim and fill' method applied to the funnel plot imputed 3 missing studies and the resulting adjusted estimate of the odds ratio was 2.12 (95% CI: 1.38 to 3.22). According to GRADE criteria, the overall quality of the meta-analysis data is low, mainly due to the presence of bias, confounders and extreme effect size outliers. Five among the included studies reported data assessed in 8015 African-American subjects. Pooled analysis resulted in a non-significant crude odds ratio of 1.59 (95% CI: 0.71 to 3.57; P = 0.26), and considerable heterogeneity (I2 = 90%). Meta-analysis of 15 case-control studies shows that a history of clinical chronic prostatitis can significantly increase the odds for prostate cancer in the general population, whereas such association in African-American individuals remains uncertain.

CRIE: An automated analyzer for Chinese texts.

PubMed

Sung, Yao-Ting; Chang, Tao-Hsing; Lin, Wei-Chun; Hsieh, Kuan-Sheng; Chang, Kuo-En

2016-12-01

Textual analysis has been applied to various fields, such as discourse analysis, corpus studies, text leveling, and automated essay evaluation. Several tools have been developed for analyzing texts written in alphabetic languages such as English and Spanish. However, currently there is no tool available for analyzing Chinese-language texts. This article introduces a tool for the automated analysis of simplified and traditional Chinese texts, called the Chinese Readability Index Explorer (CRIE). Composed of four subsystems and incorporating 82 multilevel linguistic features, CRIE is able to conduct the major tasks of segmentation, syntactic parsing, and feature extraction. Furthermore, the integration of linguistic features with machine learning models enables CRIE to provide leveling and diagnostic information for texts in language arts, texts for learning Chinese as a foreign language, and texts with domain knowledge. The usage and validation of the functions provided by CRIE are also introduced.

A Stylistic Analysis of Complexity in William Faulkner's "A Rose for Emily"

ERIC Educational Resources Information Center

Abdurrahman, Israa' Burhanuddin

2016-01-01

Applying a stylistic analysis on certain texts refers to the identification of patterns of usage in writing. However, such an analysis is not restricted just to the description of the formal characteristics of texts, but it also tries to elucidate their functional importance for the interpretation of the text. This paper highlights complexity as a…

Aesthetic Analysis of Media Texts in the Classroom at the Student Audience

ERIC Educational Resources Information Center

Fedorov, Alexander

2015-01-01

Aesthetic analysis of media texts, ie the analysis of art concept of the media texts of different types and genres, is closely related to the aesthetic (artistic) theory of media (Aesthetical Approach, Media as Popular Arts Approach, Discriminatory Approach). Aesthetic theory of media literacy education has been very popular in the 1960s…

Mobile phone messaging for illicit drug and alcohol dependence: A systematic review of the literature.

PubMed

Tofighi, Babak; Nicholson, Joseph M; McNeely, Jennifer; Muench, Frederick; Lee, Joshua D

2017-07-01

Mobile phone use has increased dramatically and concurrent with rapid developments in mobile phone-based health interventions. The integration of text messaging interventions promises to optimise the delivery of care for persons with substance dependence with minimal disruption to clinical workflows. We conducted a systematic review to assess the acceptability, feasibility and clinical impact of text messaging interventions for persons with illicit drug and alcohol dependence. Studies were required to evaluate the use of text messaging as an intervention for persons who met Diagnostic and Statistical Manual of Mental Disorders, 4th edition criterion for a diagnosis of illicit drug and/or alcohol dependence. Authors searched for articles published to date in MEDLINE (pubmed.gov), the Cochrane Library, EMBASE, CINAHL, Google Scholar and PsychINFO. Eleven articles met the search criteria for this review and support the acceptability and feasibility of text messaging interventions for addressing illicit drug and alcohol dependence. Most studies demonstrated improved clinical outcomes, medication adherence and engagement with peer support groups. Text messaging interventions also intervened on multiple therapeutic targets such as appointment attendance, motivation, self-efficacy, relapse prevention and social support. Suggestions for future research are described, including intervention design features, clinician contact, privacy measures and integration of behaviour change theories. Text messaging interventions offer a feasible platform to address a range of substances (i.e. alcohol, methamphetamine, heroin and alcohol), and there is increasing evidence supporting further larger-scale studies. [Tofighi B, Nicholson JM, McNeely J, Muench F, Lee JD. Mobile phone messaging for illicit drug and alcohol dependence: A systematic review of the literature. Drug Alcohol Rev 2017;36:477-491]. © 2017 Australasian Professional Society on Alcohol and other Drugs.

Impact of Prominent Themes in Clinician-Patient Conversations on Caregiver’s Perceived Quality of Communication with Paediatric Dental Visits

PubMed Central

Bridges, Susan Margaret; McGrath, Colman Patrick; Yiu, Cynthia Kar Yung; Zayts, Olga A.; Au, Terry Kit Fong

2017-01-01

Patients’ perceived satisfaction is a key performance index of the quality health care service. Good communication has been found to increase patient’s perceived satisfaction. The purpose of this study was to examine the impact of the prominent themes arising from clinician-patient conversations on the caregiver’s perceived quality of communication during paediatric dental visits. 162 video recordings of clinical dental consultations for 62 cases attending the Paediatric Dentistry Clinic of The Prince Philip Dental Hospital in Hong Kong were captured and transcribed. The patients’ demographic information and the caregiver’s perceived quality of communication with the clinicians were recorded using the 16-item Dental Patient Feedback on Consultation skills questionnaires. Visual text analytics (Leximancer™) indicated five prominent themes ‘disease / treatment’, ‘treatment procedure related instructions’, ‘preparation for examination’, ‘positive reinforcement / reassurance’, and ‘family / social history’ from the clinician-patient conversation of the recorded videos, with 60.2% of the total variance in concept words in this study explained through principal components analysis. Significant variation in perceived quality of communication was noted in five variables regarding the prominent theme ‘Positive reinforcement / reassurance’: ‘number of related words’ (p = 0.002), ‘number of related utterances’ (p = 0.001), ‘percentage of the related words in total number of words’ (p = 0.005), ‘percentage of the related utterances in total number of utterances’ (p = 0.035) and ‘percentage of time spent in total time duration’ (p = 0.023). Clinicians were perceived to be more patient-centered and empathetic if a larger proportion of their conversation showed positive reinforcement and reassurance via using related key words. Care-giver’s involvement, such as clinicians’ mention of the parent, was also seen as critical to perceptions of quality clinical experience. The study reveals the potential of the application of visual text analytics software in clinical consultations with implications for professional development regarding clinicians’ communication skills for improving patients’ clinical experiences and treatment satisfaction. PMID:28046044

Example of monitoring measurements in a virtual eye clinic using 'big data'.

PubMed

Jones, Lee; Bryan, Susan R; Miranda, Marco A; Crabb, David P; Kotecha, Aachal

2017-10-26

To assess the equivalence of measurement outcomes between patients attending a standard glaucoma care service, where patients see an ophthalmologist in a face-to-face setting, and a glaucoma monitoring service (GMS). The average mean deviation (MD) measurement on the visual field (VF) test for 250 patients attending a GMS were compared with a 'big data' repository of patients attending a standard glaucoma care service (reference database). In addition, the speed of VF progression between GMS patients and reference database patients was compared. Reference database patients were used to create expected outcomes that GMS patients could be compared with. For GMS patients falling outside of the expected limits, further analysis was carried out on the clinical management decisions for these patients. The average MD of patients in the GMS ranged from +1.6 dB to -18.9 dB between two consecutive appointments at the clinic. In the first analysis, 12 (4.8%; 95% CI 2.5% to 8.2%) GMS patients scored outside the 90% expected values based on the reference database. In the second analysis, 1.9% (95% CI 0.4% to 5.4%) GMS patients had VF changes outside of the expected 90% limits. Using 'big data' collected in the standard glaucoma care service, we found that patients attending a GMS have equivalent outcomes on the VF test. Our findings provide support for the implementation of virtual healthcare delivery in the hospital eye service. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

"Relinquish the reins": persuasion and consensus in the discourse of pregnancy and childbirth advice literature.

PubMed

Rodgers, Ornaith

2015-03-01

Popular pregnancy and childbirth advice books constitute an important source of information for pregnant women. These texts shape women's perceptions of pregnancy, childbirth and the medical care they will receive during this time. This article reports on a study of the enactment of power relations between pregnant women and their medical caregivers in the discourse of pregnancy and childbirth advice literature and its implications for practice. The study focuses on the discursive positioning of women in relation to medical personnel through a critical discourse analysis of two popular advice books, one in English and one in French. The article suggests that through the use of a number of key discursive strategies, pregnant women are constructed as under the control of the medical institution in these texts. However, this control is not achieved by an overt oppressive discourse, instead it is achieved through persuasion and consensus by generating the consent of pregnant women to comply with medical norms. The medical institution is represented in these texts as a dominant force while women are constructed as powerless recipients of medical care. Medical professionals should firstly consider whether the power relations represented in these texts correspond to those enacted in clinics and delivery rooms. Secondly, caregivers should be cautious about recommending popular pregnancy and childbirth advice books to women as the relationship between pregnant women and their caregivers may be undermined by the negative power asymmetry enacted in these texts. Copyright © 2014 Australian College of Midwives. Published by Elsevier Ltd. All rights reserved.

Application of Synchronous Text-Based Dialogue Systems in Mental Health Interventions: Systematic Review

PubMed Central

Milne, David N

2017-01-01

Background Synchronous written conversations (or “chats”) are becoming increasingly popular as Web-based mental health interventions. Therefore, it is of utmost importance to evaluate and summarize the quality of these interventions. Objective The aim of this study was to review the current evidence for the feasibility and effectiveness of online one-on-one mental health interventions that use text-based synchronous chat. Methods A systematic search was conducted of the databases relevant to this area of research (Medical Literature Analysis and Retrieval System Online [MEDLINE], PsycINFO, Central, Scopus, EMBASE, Web of Science, IEEE, and ACM). There were no specific selection criteria relating to the participant group. Studies were included if they reported interventions with individual text-based synchronous conversations (ie, chat or text messaging) and a psychological outcome measure. Results A total of 24 articles were included in this review. Interventions included a wide range of mental health targets (eg, anxiety, distress, depression, eating disorders, and addiction) and intervention design. Overall, compared with the waitlist (WL) condition, studies showed significant and sustained improvements in mental health outcomes following synchronous text-based intervention, and post treatment improvement equivalent but not superior to treatment as usual (TAU) (eg, face-to-face and telephone counseling). Conclusions Feasibility studies indicate substantial innovation in this area of mental health intervention with studies utilizing trained volunteers and chatbot technologies to deliver interventions. While studies of efficacy show positive post-intervention gains, further research is needed to determine whether time requirements for this mode of intervention are feasible in clinical practice. PMID:28784594

Chest Wall Kinematics Using Triangular Cosserat Point Elements in Healthy and Neuromuscular Subjects.

PubMed

Solav, Dana; Meric, Henri; Rubin, M B; Pradon, Didier; Lofaso, Frédéric; Wolf, Alon

2017-08-01

Optoelectronic plethysmography (OEP) is a noninvasive method for assessing lung volume variations and the contributions of different anatomical compartments of the chest wall (CW) through measurements of the motion of markers attached to the CW surface. The present study proposes a new method for analyzing the local CW kinematics from OEP measurements based on the kinematics of triangular Cosserat point elements (TCPEs). 52 reflective markers were placed on the anterior CW to create a mesh of 78 triangles according to an anatomical model. Each triangle was characterized by a TCPE and its kinematics was described using four time-variant scalar TCPE parameters. The total CW volume ([Formula: see text]) and the contributions of its six compartments were also estimated, using the same markers. The method was evaluated using measurements of ten healthy subjects, nine patients with Pompe disease, and ten patients with Duchenne muscular dystrophy (DMD), during spontaneous breathing (SB) and vital capacity maneuvers (VC) in the supine position. TCPE parameters and compartmental volumes were compared with [Formula: see text] by computing the phase angles [Formula: see text] (for SB) and the correlation r (for VC) between them. Analysis of [Formula: see text] and r of the outward translation parameter [Formula: see text] of each TCPE revealed that for healthy subjects it provided similar results to those obtained by compartmental volumes, whereas for the neuromuscular patients the TCPE method was capable of detecting local asynchronous and paradoxical movements also in cases where they were undistinguished by volumes. Therefore, the TCPE approach provides additional information to OEP that may enhance its clinical evaluation capabilities.

A meta-analysis of clinical electro-oculography values.

PubMed

Constable, Paul A; Ngo, David; Quinn, Stephen; Thompson, Dorothy A

2017-12-01

The aim of the meta-analysis was to derive a range of mean normal clinical electrooculogram (EOG) values from a systematic review of published EOG studies that followed the guidelines of the ISCEV standard for clinical electro-oculography. A systematic literature review was performed using four relevant databases limited to peer-reviewed articles in English between 1967 and February 2017. Studies reporting clinical EOG or FO normal values were included when the report used a standard 30° horizontal saccade, a retinal luminance of between 100 and 250 cd m -2 , and had > 10 subjects in their normative values. The search identified 1145 articles after duplicates were removed with subsequent screening of the abstracts excluding a further 1098, resulting in 47 full-text articles that were then assessed by the author (PC) with a final nine articles meeting the inclusion criteria. An overall effect estimate using inverse variance-weighted meta-analysis was performed to estimate the mean values for the light peak/dark trough ratio (LP:DT ratio) (dilated and undilated), the time to the LP, the amplitude of the LP, dark trough (DT) and the fast oscillation (FO) peak-to-trough ratio from the included studies. The mean dilated LP:DT ratio was 2.35 (95% CI 2.28-2.42); undilated LP:DT ratio was 2.37 (95% CI 2.28-2.45); LP amplitude was 835 (95% CI 631-1039) µV and the mean time to the LP being 8.2 (95% CI 7.7-8.7) min. The mean DT amplitude was 358 (95% CI 292-424) µV, and the mean FO peak-to-trough ratio was 1.13 (95% CI 1.11-1.16). The results of the LP/DT ratio are drawn from studies with a mean ± standard deviation (SD) age of 34.08 ± 12.93 years for dilated and 33.65 ± 12.28 years for undilated LP/DT ratios. The meta-analysis of EOG studies has generated a reference range of normal mean values for clinicians to refer to when using the ISCEV clinical EOG. It provides a potential method to generate similar data sets from published normal values in related visual electrophysiology tests.

Physical examination tests of the shoulder: a systematic review and meta-analysis of diagnostic test performance.

PubMed

Gismervik, Sigmund Ø; Drogset, Jon O; Granviken, Fredrik; Rø, Magne; Leivseth, Gunnar

2017-01-25

Physical examination tests of the shoulder (PETS) are clinical examination maneuvers designed to aid the assessment of shoulder complaints. Despite more than 180 PETS described in the literature, evidence of their validity and usefulness in diagnosing the shoulder is questioned. This meta-analysis aims to use diagnostic odds ratio (DOR) to evaluate how much PETS shift overall probability and to rank the test performance of single PETS in order to aid the clinician's choice of which tests to use. This study adheres to the principles outlined in the Cochrane guidelines and the PRISMA statement. A fixed effect model was used to assess the overall diagnostic validity of PETS by pooling DOR for different PETS with similar biomechanical rationale when possible. Single PETS were assessed and ranked by DOR. Clinical performance was assessed by sensitivity, specificity, accuracy and likelihood ratio. Six thousand nine-hundred abstracts and 202 full-text articles were assessed for eligibility; 20 articles were eligible and data from 11 articles could be included in the meta-analysis. All PETS for SLAP (superior labral anterior posterior) lesions pooled gave a DOR of 1.38 [1.13, 1.69]. The Supraspinatus test for any full thickness rotator cuff tear obtained the highest DOR of 9.24 (sensitivity was 0.74, specificity 0.77). Compression-Rotation test obtained the highest DOR (6.36) among single PETS for SLAP lesions (sensitivity 0.43, specificity 0.89) and Hawkins test obtained the highest DOR (2.86) for impingement syndrome (sensitivity 0.58, specificity 0.67). No single PETS showed superior clinical test performance. The clinical performance of single PETS is limited. However, when the different PETS for SLAP lesions were pooled, we found a statistical significant change in post-test probability indicating an overall statistical validity. We suggest that clinicians choose their PETS among those with the highest pooled DOR and to assess validity to their own specific clinical settings, review the inclusion criteria of the included primary studies. We further propose that future studies on the validity of PETS use randomized research designs rather than the accuracy design relying less on well-established gold standard reference tests and efficient treatment options.

CER Hub: An informatics platform for conducting comparative effectiveness research using multi-institutional, heterogeneous, electronic clinical data.

PubMed

Hazlehurst, Brian L; Kurtz, Stephen E; Masica, Andrew; Stevens, Victor J; McBurnie, Mary Ann; Puro, Jon E; Vijayadeva, Vinutha; Au, David H; Brannon, Elissa D; Sittig, Dean F

2015-10-01

Comparative effectiveness research (CER) requires the capture and analysis of data from disparate sources, often from a variety of institutions with diverse electronic health record (EHR) implementations. In this paper we describe the CER Hub, a web-based informatics platform for developing and conducting research studies that combine comprehensive electronic clinical data from multiple health care organizations. The CER Hub platform implements a data processing pipeline that employs informatics standards for data representation and web-based tools for developing study-specific data processing applications, providing standardized access to the patient-centric electronic health record (EHR) across organizations. The CER Hub is being used to conduct two CER studies utilizing data from six geographically distributed and demographically diverse health systems. These foundational studies address the effectiveness of medications for controlling asthma and the effectiveness of smoking cessation services delivered in primary care. The CER Hub includes four key capabilities: the ability to process and analyze both free-text and coded clinical data in the EHR; a data processing environment supported by distributed data and study governance processes; a clinical data-interchange format for facilitating standardized extraction of clinical data from EHRs; and a library of shareable clinical data processing applications. CER requires coordinated and scalable methods for extracting, aggregating, and analyzing complex, multi-institutional clinical data. By offering a range of informatics tools integrated into a framework for conducting studies using EHR data, the CER Hub provides a solution to the challenges of multi-institutional research using electronic medical record data. Copyright © 2015. Published by Elsevier Ireland Ltd.

Ubiquitous testing using tablets: its impact on medical student perceptions of and engagement in learning

PubMed Central

Kim, Kyong-Jee; Hwang, Jee-Young

2016-01-01

Purpose: Ubiquitous testing has the potential to affect medical education by enhancing the authenticity of the assessment using multimedia items. This study explored medical students’ experience with ubiquitous testing and its impact on student learning. Methods: A cohort (n=48) of third-year students at a medical school in South Korea participated in this study. The students were divided into two groups and were given different versions of 10 content-matched items: one in text version (the text group) and the other in multimedia version (the multimedia group). Multimedia items were delivered using tablets. Item response analyses were performed to compare item characteristics between the two versions. Additionally, focus group interviews were held to investigate the students’ experiences of ubiquitous testing. Results: The mean test score was significantly higher in the text group. Item difficulty and discrimination did not differ between text and multimedia items. The participants generally showed positive responses on ubiquitous testing. Still, they felt that the lectures that they had taken in preclinical years did not prepare them enough for this type of assessment and clinical encounters during clerkships were more helpful. To be better prepared, the participants felt that they needed to engage more actively in learning in clinical clerkships and have more access to multimedia learning resources. Conclusion: Ubiquitous testing can positively affect student learning by reinforcing the importance of being able to understand and apply knowledge in clinical contexts, which drives students to engage more actively in learning in clinical settings. PMID:26838569

Improving Reading Comprehension Using Digital Text: A Meta-Analysis of Interventions

ERIC Educational Resources Information Center

Berkeley, Sheri; Kurz, Leigh Ann; Boykin, Andrea; Evmenova, Anya S.

2015-01-01

Much is known about how to improve students' comprehension when reading printed text; less is known about outcomes when reading digital text. The purpose of this meta-analysis was to analyze research on the impact of digital text interventions. A comprehensive literature search resulted in 27 group intervention studies with 16,513 participants.…

A Network Text Analysis of David Ayer's "Fury"

ERIC Educational Resources Information Center

Hunter, Starling David; Smith, Susan

2015-01-01

Network Text Analysis (NTA) involves the creation of networks of words and/or concepts from linguistic data. Its key insight is that the position of words and concepts in a text network provides vital clues to the central and underlying themes of the text as a whole. Recent research has relied on inductive approaches to identify these themes. In…

Patient reminder systems and asthma medication adherence: a systematic review.

PubMed

Tran, Nancy; Coffman, Janet M; Sumino, Kaharu; Cabana, Michael D

2014-06-01

One of the most common reasons for medication non-adherence for asthma patients is forgetfulness. Daily medication reminder system interventions in the form of text messages, automated phone calls and audiovisual reminder devices can potentially address this problem. The aim of this review was to assess the effectiveness of reminder systems on patient daily asthma medication adherence. We conducted a systematic review of the literature to identify randomized controlled trials (RCTs) which assessed the effect of reminder systems on daily asthma medication adherence. We searched all English-language articles in Pub Med (MEDLINE), CINAHL, EMBASE, PsychINFO and the Cochrane Library through May 2013. We abstracted data on the year of study publication, location, inclusion and exclusion criteria, patient characteristics, reminder system characteristics, effect on patient adherence rate and other outcomes measured. Descriptive statistics were used to summarize the characteristics and results of the studies. Five RCTs and one pragmatic RCT were included in the analysis. Median follow-up time was 16 weeks. All of the six studies suggested that the reminder system intervention was associated with greater levels of participant asthma medication adherence compared to those participants in the control group. None of the studies documented a change in asthma-related quality of life or clinical asthma outcomes. All studies in our analysis suggest that reminder systems increase patient medication adherence, but none documented improved clinical outcomes. Further studies with longer intervention durations are needed to assess effects on clinical outcomes, as well as the sustainability of effects on patient adherence.

Clinical case in digital technology for nursing students' learning: An integrative review.

PubMed

Hara, Cristina Yuri Nakata; Aredes, Natália Del Angelo; Fonseca, Luciana Mara Monti; Silveira, Renata Cristina de Campos Pereira; Camargo, Rosangela Andrade Aukar; de Goes, Fernanda Santos Nogueira

2016-03-01

This review aimed to analyze the available evidences in literature about clinical case studies inserted in digital technologies for nursing education, characterizing the technology resources and cognitive, procedural and attitudinal learnings. Integrative review of literature with the following steps: development of the research problem, data collection, data extraction and critic evaluation, data analysis and interpretation and presentation of results. The research question was: how does the clinical case study inserted in educational digital technology collaborate for cognitive, attitudinal and procedural learning of nursing students? data bases LILACS, PUBMED, CINAHL and Scopus. the search resulted in 437 studies: 136 from LILACS, 122 from PUBMED, 104 from Scopus and 75 from CINAHL. Of these, 143 did not meet the including criteria, 93 were duplicated and four studies were unavailable. After analyzing all abstracts based on inclusion and exclusion criteria, there were selected 197 studies and after full text analysis the final sample resulted in 21 primary studies. Case study use in educational digital technologies allowed the students to build different types of learning: cognitive learning (n 16 studies), attitudinal learning (n=12 studies) and procedural learning (n=8 studies). It is possible to conclude that case studies can collaborate with the students to develop different learnings which can be built integrate, continuous, informative and formative, aiming integral formation and aligned to policies of formation in nursing, both national and international. Copyright © 2015 Elsevier Ltd. All rights reserved.

The role of mutation analysis of the APC gene in the management of FAP patients. A controversial issue.

PubMed

Dodaro, Concetta; Grifasi, Carlo; Florio, Jole; Santangelo, Michele L; Duraturo, Francesca; De Rosa, Marina; Izzo, Paola; Renda, Andrea

A correlation between the location of mutation in the adenomatous polyposis coli (APC) gene and clinical manifestations of familial adenomatous polyposis (FAP) has repeatedly been reported. Some Authors suggest the use of mutational analysis as a guide to select the best surgical option in FAP patients. However, data coming from studies on large series have raised questions on this issue. The aim of this study is to discuss the role of the genetic tests in the management of FAP. A literature review was performed considering only peer-reviewed articles published between 1991-2015. All the studies examined the role of genetic as a guide for surgical management of FAP. Of 363 articles identified, 21 were selected for full-text review. We found different positions with regard the use of genetic tests to determine surgical management of FAP. In particular, while consistent correlations between the APC mutation site and FAP phenotype were observed in large series, 8 studies reported a wide variation of genotypephenotype correlation in patients with the same mutation and they recommended that decisions regarding surgical strategy should be based not only on genotype but also on the clinical factors and the will of the patient who must be fully informed. The decision on the type and the timing of surgery should be based on the assessment of many factors and genotype assessment should be used in combination with clinical data. Disease severity, Familial adenomatous polyposis, Genetic tests, Genotype-phenotype correlations, Surgical management.

Extracting similar terms from multiple EMR-based semantic embeddings to support chart reviews.

PubMed

Cheng Ye, M S; Fabbri, Daniel

2018-05-21

Word embeddings project semantically similar terms into nearby points in a vector space. When trained on clinical text, these embeddings can be leveraged to improve keyword search and text highlighting. In this paper, we present methods to refine the selection process of similar terms from multiple EMR-based word embeddings, and evaluate their performance quantitatively and qualitatively across multiple chart review tasks. Word embeddings were trained on each clinical note type in an EMR. These embeddings were then combined, weighted, and truncated to select a refined set of similar terms to be used in keyword search and text highlighting. To evaluate their quality, we measured the similar terms' information retrieval (IR) performance using precision-at-K (P@5, P@10). Additionally a user study evaluated users' search term preferences, while a timing study measured the time to answer a question from a clinical chart. The refined terms outperformed the baseline method's information retrieval performance (e.g., increasing the average P@5 from 0.48 to 0.60). Additionally, the refined terms were preferred by most users, and reduced the average time to answer a question. Clinical information can be more quickly retrieved and synthesized when using semantically similar term from multiple embeddings. Copyright © 2018. Published by Elsevier Inc.

STANLEY (Sandia Text ANaLysis Extensible librarY) Ver. 1.1

DOE Office of Scientific and Technical Information (OSTI.GOV)

BENZ, ZACHARY; APODACA, VINCENT; BASILICO, JUSTIN

2009-11-10

Reusable, extensible text analysis library. This library forms the basis for the automated generation of cognitive models from text for Sandia's Cognition program. It also is the basis for the suite of underlying, related applications.

Designing a Culturally Appropriate Visually Enhanced Low-Text Mobile Health App Promoting Physical Activity for Latinos: A Qualitative Study.

PubMed

Bender, Melinda S; Martinez, Suzanna; Kennedy, Christine

2016-07-01

Rapid proliferation of smartphone ownership and use among Latinos offers a unique opportunity to employ innovative visually enhanced low-text (VELT) mobile health applications (mHealth app) to promote health behavior change for Latinos at risk for lifestyle-related diseases. Using focus groups and in-depth interviews with 16 promotores and 5 health care providers recruited from California clinics, this qualitative study explored perceptions of visuals for a VELT mHealth app promoting physical activity (PA) and limiting sedentary behavior (SB) for Latinos. In this Phase 1 study, participants endorsed visuals portraying PA guidelines and recommended visuals depicting family and socially oriented PA. Overall, participants supported a VELT mHealth app as an alternative to text-based education. Findings will inform the future Phase 2 study development of a culturally appropriate VELT mHealth app to promote PA for Latinos, improve health literacy, and provide an alternative to traditional clinic text-based health education materials. © The Author(s) 2015.

Integrating Query of Relational and Textual Data in Clinical Databases: A Case Study

PubMed Central

Fisk, John M.; Mutalik, Pradeep; Levin, Forrest W.; Erdos, Joseph; Taylor, Caroline; Nadkarni, Prakash

2003-01-01

Objectives: The authors designed and implemented a clinical data mart composed of an integrated information retrieval (IR) and relational database management system (RDBMS). Design: Using commodity software, which supports interactive, attribute-centric text and relational searches, the mart houses 2.8 million documents that span a five-year period and supports basic IR features such as Boolean searches, stemming, and proximity and fuzzy searching. Measurements: Results are relevance-ranked using either “total documents per patient” or “report type weighting.” Results: Non-curated medical text has a significant degree of malformation with respect to spelling and punctuation, which creates difficulties for text indexing and searching. Presently, the IR facilities of RDBMS packages lack the features necessary to handle such malformed text adequately. Conclusion: A robust IR+RDBMS system can be developed, but it requires integrating RDBMSs with third-party IR software. RDBMS vendors need to make their IR offerings more accessible to non-programmers. PMID:12509355

Towards Phenotyping of Clinical Trial Eligibility Criteria.

PubMed

Löbe, Matthias; Stäubert, Sebastian; Goldberg, Colleen; Haffner, Ivonne; Winter, Alfred

2018-01-01

Medical plaintext documents contain important facts about patients, but they are rarely available for structured queries. The provision of structured information from natural language texts in addition to the existing structured data can significantly speed up the search for fulfilled inclusion criteria and thus improve the recruitment rate. This work is aimed at supporting clinical trial recruitment with text mining techniques to identify suitable subjects in hospitals. Based on the inclusion/exclusion criteria of 5 sample studies and a text corpus consisting of 212 doctor's letters and medical follow-up documentation from a university cancer center, a prototype was developed and technically evaluated using NLP procedures (UIMA) for the extraction of facts from medical free texts. It was found that although the extracted entities are not always correct (precision between 23% and 96%), they provide a decisive indication as to which patient file should be read preferentially. The prototype presented here demonstrates the technical feasibility. In order to find available, lucrative phenotypes, an in-depth evaluation is required.

The Clinical Model in Rehabilitation and Alternatives.

ERIC Educational Resources Information Center

Woods, Diane E., Ed.; And Others

This book is a compilation of responses and reactions to a position paper by Dr. Joseph Stubbins entitled "The Clinical Model in Rehabilitation and Alternatives." The text of the position paper is presented along with a brief summary of the main points he made in it pertaining to the clinical model and the systems model. Also included in the…

Development and prospective evaluation of an automated software system for quality control of quantitative 99mTc-MAG3 renal studies.

PubMed

Folks, Russell D; Garcia, Ernest V; Taylor, Andrew T

2007-03-01

Quantitative nuclear renography has numerous potential sources of error. We previously reported the initial development of a computer software module for comprehensively addressing the issue of quality control (QC) in the analysis of radionuclide renal images. The objective of this study was to prospectively test the QC software. The QC software works in conjunction with standard quantitative renal image analysis using a renal quantification program. The software saves a text file that summarizes QC findings as possible errors in user-entered values, calculated values that may be unreliable because of the patient's clinical condition, and problems relating to acquisition or processing. To test the QC software, a technologist not involved in software development processed 83 consecutive nontransplant clinical studies. The QC findings of the software were then tabulated. QC events were defined as technical (study descriptors that were out of range or were entered and then changed, unusually sized or positioned regions of interest, or missing frames in the dynamic image set) or clinical (calculated functional values judged to be erroneous or unreliable). Technical QC events were identified in 36 (43%) of 83 studies. Clinical QC events were identified in 37 (45%) of 83 studies. Specific QC events included starting the camera after the bolus had reached the kidney, dose infiltration, oversubtraction of background activity, and missing frames in the dynamic image set. QC software has been developed to automatically verify user input, monitor calculation of renal functional parameters, summarize QC findings, and flag potentially unreliable values for the nuclear medicine physician. Incorporation of automated QC features into commercial or local renal software can reduce errors and improve technologist performance and should improve the efficiency and accuracy of image interpretation.

Initial Outcomes From a 4-Week Follow-Up Study of the Text4baby Program in the Military Women’s Population: Randomized Controlled Trial

PubMed Central

Wallace Bihm, Jasmine; Szekely, Daniel; Nielsen, Peter; Murray, Elizabeth; Abroms, Lorien; Snider, Jeremy

2014-01-01

Background The use of mobile phone technologies for health promotion and disease prevention has advanced rapidly in recent years. Text4baby is a theory-based mobile health (mHealth) program in which text messages are delivered to pregnant women and new mothers to improve their health care beliefs and behaviors and improve health status and clinical outcomes. Recent evaluations of Text4baby have found that it improves targeted health attitudes and beliefs, but effects on behavior have not yet been determined. Objective In this study, investigators aimed to evaluate Text4baby in the military women’s population. Methods Investigators conducted a randomized controlled trial at Madigan Army Medical Center in Tacoma, Washington, from December 2011 through September 2013. All participants were pregnant women first presenting for care at Madigan. Investigators conducted a baseline assessment using a 24-item, self-administered online survey of attitudes and behaviors related to Text4baby message content. Participants were randomized to Text4baby plus usual care (intervention) or usual care alone (control). Investigators analyzed treatment effects of Text4baby on short-term targeted outcomes 4 weeks post enrollment. Results For this study, 943 patients were randomized and completed a baseline assessment. The average patient age was 28 years and nearly 70% self-identified as Caucasian. 48.7% of enrollees (459/943) completed the first follow-up assessment. Higher rates of single and working/in-school patients dropped out of the intervention arm of the study, and we adjusted for this finding in subsequent models. However, while investigators were unable to re-survey these participants, only 1.9% of Text4baby enrollees (18/943) dropped the service during the study period. Adjusted and unadjusted logistic generalized estimating equation models were developed to assess intervention effects on measured outcomes. In the model adjusting for age, marital status, having had a previous baby, and race/ethnicity, there was a significant effect of Text4baby intervention exposure on increased agreement with belief in the importance of taking prenatal vitamins (OR 1.91, 95% CI 1.08-3.34, P=.024). All of these attitudes had been targeted by at least one text message during the 4-week evaluation period examined in this study. In unadjusted models, there was a significant effect of intervention exposure on belief in the importance of visiting a health care provider to be a healthy new mother (OR 1.52, 95% CI 1.01-2.31, P=.046) and in the health risks of alcohol during pregnancy (OR 2.06, 95% CI 1.00-4.31, P=.05). No behavioral effects of the intervention were observed in this analysis. Conclusions Text4baby is a promising program that offers lessons for future mHealth activities. This large-scale study demonstrated initial effects of the program on attitudes and beliefs targeted by the messages received by women during the study period. Results confirm previous findings from Text4baby studies and other mHealth research. Future analyses will examine dosage effects of the intervention on behaviors and clinical outcomes. PMID:24846909

The Effects of Text Structure Instruction on Expository Reading Comprehension: A Meta-Analysis

ERIC Educational Resources Information Center

Hebert, Michael; Bohaty, Janet J.; Nelson, J. Ron; Brown, Jessica

2016-01-01

In this meta-analysis of 45 studies involving students in Grades 2-12, the authors present evidence on the effects of text structure instruction on the expository reading comprehension of students. The meta-analysis was deigned to answer 2 sets of questions. The first set of questions examined the effectiveness of text structure instruction on…

Graphic Warning Labels Elicit Affective and Thoughtful Responses from Smokers: Results of a Randomized Clinical Trial.

PubMed

Evans, Abigail T; Peters, Ellen; Strasser, Andrew A; Emery, Lydia F; Sheerin, Kaitlin M; Romer, Daniel

2015-01-01

Observational research suggests that placing graphic images on cigarette warning labels can reduce smoking rates, but field studies lack experimental control. Our primary objective was to determine the psychological processes set in motion by naturalistic exposure to graphic vs. text-only warnings in a randomized clinical trial involving exposure to modified cigarette packs over a 4-week period. Theories of graphic-warning impact were tested by examining affect toward smoking, credibility of warning information, risk perceptions, quit intentions, warning label memory, and smoking risk knowledge. Adults who smoked between 5 and 40 cigarettes daily (N = 293; mean age = 33.7), did not have a contra-indicated medical condition, and did not intend to quit were recruited from Philadelphia, PA and Columbus, OH. Smokers were randomly assigned to receive their own brand of cigarettes for four weeks in one of three warning conditions: text only, graphic images plus text, or graphic images with elaborated text. Data from 244 participants who completed the trial were analyzed in structural-equation models. The presence of graphic images (compared to text-only) caused more negative affect toward smoking, a process that indirectly influenced risk perceptions and quit intentions (e.g., image->negative affect->risk perception->quit intention). Negative affect from graphic images also enhanced warning credibility including through increased scrutiny of the warnings, a process that also indirectly affected risk perceptions and quit intentions (e.g., image->negative affect->risk scrutiny->warning credibility->risk perception->quit intention). Unexpectedly, elaborated text reduced warning credibility. Finally, graphic warnings increased warning-information recall and indirectly increased smoking-risk knowledge at the end of the trial and one month later. In the first naturalistic clinical trial conducted, graphic warning labels are more effective than text-only warnings in encouraging smokers to consider quitting and in educating them about smoking's risks. Negative affective reactions to smoking, thinking about risks, and perceptions of credibility are mediators of their impact. Clinicaltrials.gov NCT01782053.

Retrieving clinical evidence: a comparison of PubMed and Google Scholar for quick clinical searches.

PubMed

Shariff, Salimah Z; Bejaimal, Shayna Ad; Sontrop, Jessica M; Iansavichus, Arthur V; Haynes, R Brian; Weir, Matthew A; Garg, Amit X

2013-08-15

Physicians frequently search PubMed for information to guide patient care. More recently, Google Scholar has gained popularity as another freely accessible bibliographic database. To compare the performance of searches in PubMed and Google Scholar. We surveyed nephrologists (kidney specialists) and provided each with a unique clinical question derived from 100 renal therapy systematic reviews. Each physician provided the search terms they would type into a bibliographic database to locate evidence to answer the clinical question. We executed each of these searches in PubMed and Google Scholar and compared results for the first 40 records retrieved (equivalent to 2 default search pages in PubMed). We evaluated the recall (proportion of relevant articles found) and precision (ratio of relevant to nonrelevant articles) of the searches performed in PubMed and Google Scholar. Primary studies included in the systematic reviews served as the reference standard for relevant articles. We further documented whether relevant articles were available as free full-texts. Compared with PubMed, the average search in Google Scholar retrieved twice as many relevant articles (PubMed: 11%; Google Scholar: 22%; P<.001). Precision was similar in both databases (PubMed: 6%; Google Scholar: 8%; P=.07). Google Scholar provided significantly greater access to free full-text publications (PubMed: 5%; Google Scholar: 14%; P<.001). For quick clinical searches, Google Scholar returns twice as many relevant articles as PubMed and provides greater access to free full-text articles.

Sentiment analysis of Arabic tweets using text mining techniques

NASA Astrophysics Data System (ADS)

Al-Horaibi, Lamia; Khan, Muhammad Badruddin

2016-07-01

Sentiment analysis has become a flourishing field of text mining and natural language processing. Sentiment analysis aims to determine whether the text is written to express positive, negative, or neutral emotions about a certain domain. Most sentiment analysis researchers focus on English texts, with very limited resources available for other complex languages, such as Arabic. In this study, the target was to develop an initial model that performs satisfactorily and measures Arabic Twitter sentiment by using machine learning approach, Naïve Bayes and Decision Tree for classification algorithms. The datasets used contains more than 2,000 Arabic tweets collected from Twitter. We performed several experiments to check the performance of the two algorithms classifiers using different combinations of text-processing functions. We found that available facilities for Arabic text processing need to be made from scratch or improved to develop accurate classifiers. The small functionalities developed by us in a Python language environment helped improve the results and proved that sentiment analysis in the Arabic domain needs lot of work on the lexicon side.

Autism: Clinical and Research Issues.

ERIC Educational Resources Information Center

Accardo, Pasquale J., Ed.; Magnusen, Christy, Ed.; Capute, Arnold J., Ed.

This text examines the characteristics that define autism: impairments in communication; abnormal social development; and clinically significant odd behaviors. Specific chapters include: (1) Neural Mechanisms in Autism (Andrew W. Zimmerman and Barry Gordon); (2) Epidemiology of Autism and Other Pervasive Developmental Disorders: Current…

Extracting genetic alteration information for personalized cancer therapy from ClinicalTrials.gov

PubMed Central

Xu, Jun; Lee, Hee-Jin; Zeng, Jia; Wu, Yonghui; Zhang, Yaoyun; Huang, Liang-Chin; Johnson, Amber; Holla, Vijaykumar; Bailey, Ann M; Cohen, Trevor; Meric-Bernstam, Funda; Bernstam, Elmer V

2016-01-01

Objective: Clinical trials investigating drugs that target specific genetic alterations in tumors are important for promoting personalized cancer therapy. The goal of this project is to create a knowledge base of cancer treatment trials with annotations about genetic alterations from ClinicalTrials.gov. Methods: We developed a semi-automatic framework that combines advanced text-processing techniques with manual review to curate genetic alteration information in cancer trials. The framework consists of a document classification system to identify cancer treatment trials from ClinicalTrials.gov and an information extraction system to extract gene and alteration pairs from the Title and Eligibility Criteria sections of clinical trials. By applying the framework to trials at ClinicalTrials.gov, we created a knowledge base of cancer treatment trials with genetic alteration annotations. We then evaluated each component of the framework against manually reviewed sets of clinical trials and generated descriptive statistics of the knowledge base. Results and Discussion: The automated cancer treatment trial identification system achieved a high precision of 0.9944. Together with the manual review process, it identified 20 193 cancer treatment trials from ClinicalTrials.gov. The automated gene-alteration extraction system achieved a precision of 0.8300 and a recall of 0.6803. After validation by manual review, we generated a knowledge base of 2024 cancer trials that are labeled with specific genetic alteration information. Analysis of the knowledge base revealed the trend of increased use of targeted therapy for cancer, as well as top frequent gene-alteration pairs of interest. We expect this knowledge base to be a valuable resource for physicians and patients who are seeking information about personalized cancer therapy. PMID:27013523

Extracting genetic alteration information for personalized cancer therapy from ClinicalTrials.gov.

PubMed

Xu, Jun; Lee, Hee-Jin; Zeng, Jia; Wu, Yonghui; Zhang, Yaoyun; Huang, Liang-Chin; Johnson, Amber; Holla, Vijaykumar; Bailey, Ann M; Cohen, Trevor; Meric-Bernstam, Funda; Bernstam, Elmer V; Xu, Hua

2016-07-01

Clinical trials investigating drugs that target specific genetic alterations in tumors are important for promoting personalized cancer therapy. The goal of this project is to create a knowledge base of cancer treatment trials with annotations about genetic alterations from ClinicalTrials.gov. We developed a semi-automatic framework that combines advanced text-processing techniques with manual review to curate genetic alteration information in cancer trials. The framework consists of a document classification system to identify cancer treatment trials from ClinicalTrials.gov and an information extraction system to extract gene and alteration pairs from the Title and Eligibility Criteria sections of clinical trials. By applying the framework to trials at ClinicalTrials.gov, we created a knowledge base of cancer treatment trials with genetic alteration annotations. We then evaluated each component of the framework against manually reviewed sets of clinical trials and generated descriptive statistics of the knowledge base. The automated cancer treatment trial identification system achieved a high precision of 0.9944. Together with the manual review process, it identified 20 193 cancer treatment trials from ClinicalTrials.gov. The automated gene-alteration extraction system achieved a precision of 0.8300 and a recall of 0.6803. After validation by manual review, we generated a knowledge base of 2024 cancer trials that are labeled with specific genetic alteration information. Analysis of the knowledge base revealed the trend of increased use of targeted therapy for cancer, as well as top frequent gene-alteration pairs of interest. We expect this knowledge base to be a valuable resource for physicians and patients who are seeking information about personalized cancer therapy. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Improving health outcomes for young people with long term conditions: The role of digital communication in current and future patient-clinician communication for NHS providers of specialist clinical services for young people - LYNC study protocol.

PubMed

Griffiths, Frances E; Atherton, Helen; Barker, Jack R; Cave, Jonathan Ak; Dennick, Kathryn; Dowdall, Peter; Fraser, Joe; Huxley, Caroline; Kim, Sung-Wook; Madan, Jason J; Matharu, Harjit; Musumadi, Luhanga; Palmer, Tom M; Paul, Moli; Sankaranarayanan, Sailesh; Slowther, Anne-Marie; Sujan, Mark A; Sutcliffe, Paul A; Sturt, Jackie

2015-01-01

Young people living with long term conditions are vulnerable to health service disengagement. This endangers their long term health. Studies report requests for digital forms of communication - email, text, social media - with their health care team. Digital clinical communication is troublesome for the UK NHS. In this article we aim to present the research protocol for evaluating the impacts and outcomes of digital clinical communications for young people living with long term conditions and provide critical analysis of their use, monitoring and evaluation by NHS providers (LYNC study: Long term conditions, Young people, Networked Communications). The research involves: (a) patient and public involvement activities with 16-24 year olds with and without long term health conditions; (b) six literature reviews; (c) case studies - the main empirical part of the study - and (d) synthesis and a consensus meeting. Case studies use a mixed methods design. Interviews and non-participant observation of practitioners and patients communicating in up to 20 specialist clinical settings will be combined with data, aggregated at the case level (non-identifiable patient data) on a range of clinical outcomes meaningful within the case and across cases. We will describe the use of digital clinical communication from the perspective of patients, clinical staff, support staff and managers, interviewing up to 15 young people and 15 staff per case study. Outcome data includes emergency admissions, A&E attendance and DNA (did not attend) rates. Case studies will be analysed to understand impacts of digital clinical communication on patient health outcomes, health care costs and consumption, ethics and patient safety.

Measuring clinical trial transparency: an empirical analysis of newly approved drugs and large pharmaceutical companies.

PubMed

Miller, Jennifer E; Wilenzick, Marc; Ritcey, Nolan; Ross, Joseph S; Mello, Michelle M

2017-12-05

To define a series of clinical trial transparency measures and apply them to large pharmaceutical and biotechnology companies and their 2014 FDA-approved drugs. Cross-sectional descriptive analysis of all clinical trials supporting 2014 Food and Drugs Administration (FDA)-approved new drug applications (NDAs) for novel drugs sponsored by large companies. Data from over 45 sources, including Drugs@FDA.gov, ClinicalTrials.gov, corporate and international registries; PubMed, Google Scholar, EMBASE, corporate press releases, Securities and Exchange Commission (SEC) filings and personal communications with drug manufacturers. Trial registration, results reporting, clinical study report (CSR) synopsis sharing, biomedical journal publication, and FDA Amendments Acts (FDAAA) compliance, analysed on the drug level. The FDA approved 19 novel new drugs, sponsored by 11 large companies, involving 553 trials, in 2014. We analysed 505 relevant trials. Per drug, a median of 100% (IQR 86%-100%) of trials in patients were registered, 71% (IQR 57%-100%) reported results or shared a CSR synopsis, 80% (70%-100%) were published and 96% (80%-100%) were publicly available in some form by 13 months after FDA approval. Disclosure rates were lower at FDA approval (65%) and improved significantly by 6 months post FDA approval. Per drug, a median of 100% (IQR 75%-100%) of FDAAA-applicable trials were compliant. Half of reviewed drugs had publicly disclosed results for all trials in patients in our sample. One trial was uniquely registered in a corporate registry, and not ClinicalTrials.gov; 0 trials were uniquely registered in international registries. Among large pharmaceutical companies and new drugs, clinical trial transparency is high based on several standards, although opportunities for improvement remain. Transparency is markedly higher for trials in patients than among all trials supporting drug approval, including trials in healthy volunteers. Ongoing efforts to publicly track companies' transparency records and recognise exemplary companies may encourage further progress. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Evaluating the Effectiveness of Text Messaging and Phone Call Reminders to Minimize No Show at Pediatric Outpatient Clinics in Pakistan: Protocol for a Mixed-Methods Study.

PubMed

Saeed, Sana; Somani, Noureen; Sharif, Fatima; Kazi, Abdul Momin

2018-04-10

Missing health care appointments without canceling in advance results in a no show, a vacant appointment slot that cannot be offered to others. No show can be reduced by reminding patients about their appointment in advance. In this regard, mobile health (mHealth) strategy is to use text messaging (short message service, SMS), which is available on all cellular phones, including cheap low-end handsets. Nonattendance for appointments in health care results in wasted resources and disturbs the planned work schedules. The purpose of this study is to evaluate the efficacy of the current text messaging (SMS) and call-based reminder system and further explore how to improve the attendance at the pediatric outpatient clinics. The primary objectives are to (1) determine the efficacy of the current clinic appointment reminder service at pediatric outpatient clinics at Aga Khan University Hospital, (2) assess the mobile phone access and usage among caregivers visiting pediatrics consultant clinics, and (3) explore the perception and barriers of parents regarding the current clinic appointment reminder service at the pediatric outpatient clinics at Aga Khan University Hospital. The study uses a mixed-method design that consists of 3 components: (1) retrospective study (component A) which aims to determine the efficacy of text messaging (SMS) and phone call-based reminder service on patient's clinic attendance during January to June 2017 (N=58,517); (2) quantitative (component B) in which a baseline survey will be conducted to assess the mobile phone access and usage among parents/caregivers of children visiting pediatrics consultant clinics (n=300); and (3) qualitative (component C) includes in-depth interviews and focus group discussion with parents/caregivers of children visiting the pediatric consultancy clinic and with health care providers and administrative staff. Main constructs will be to explore perceptions and barriers related to existing clinic appointment reminder service. Ethics approval has been obtained from the Ethical Review Committee, Aga Khan University, Pakistan (4770-Ped-ERC-17). Results will be disseminated to pediatric quality public health and mHealth communities through scientific meetings and through publications, nationally and internationally. This study will provide insight regarding efficacy of using mHealth-based reminder services for patient's appointments in low- and middle-income countries setup. The finding of this study will be used to recommend further enhanced mHealth-based solutions to improve patient appointments and decrease no show. ©Sana Saeed, Noureen Somani, Fatima Sharif, Abdul Momin Kazi. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 10.04.2018.

Relating interesting quantitative time series patterns with text events and text features

NASA Astrophysics Data System (ADS)

Wanner, Franz; Schreck, Tobias; Jentner, Wolfgang; Sharalieva, Lyubka; Keim, Daniel A.

2013-12-01

In many application areas, the key to successful data analysis is the integrated analysis of heterogeneous data. One example is the financial domain, where time-dependent and highly frequent quantitative data (e.g., trading volume and price information) and textual data (e.g., economic and political news reports) need to be considered jointly. Data analysis tools need to support an integrated analysis, which allows studying the relationships between textual news documents and quantitative properties of the stock market price series. In this paper, we describe a workflow and tool that allows a flexible formation of hypotheses about text features and their combinations, which reflect quantitative phenomena observed in stock data. To support such an analysis, we combine the analysis steps of frequent quantitative and text-oriented data using an existing a-priori method. First, based on heuristics we extract interesting intervals and patterns in large time series data. The visual analysis supports the analyst in exploring parameter combinations and their results. The identified time series patterns are then input for the second analysis step, in which all identified intervals of interest are analyzed for frequent patterns co-occurring with financial news. An a-priori method supports the discovery of such sequential temporal patterns. Then, various text features like the degree of sentence nesting, noun phrase complexity, the vocabulary richness, etc. are extracted from the news to obtain meta patterns. Meta patterns are defined by a specific combination of text features which significantly differ from the text features of the remaining news data. Our approach combines a portfolio of visualization and analysis techniques, including time-, cluster- and sequence visualization and analysis functionality. We provide two case studies, showing the effectiveness of our combined quantitative and textual analysis work flow. The workflow can also be generalized to other application domains such as data analysis of smart grids, cyber physical systems or the security of critical infrastructure, where the data consists of a combination of quantitative and textual time series data.

[The Helsinki Declaration: relativism and vulnerability].

PubMed

Diniz, D; Corrêa, M

2001-01-01

The Helsinki Declaration is a crucial ethical landmark for clinical research involving human beings. Since the Declaration was issued, a series of revisions and modifications have been introduced into the original text, but they have not altered its humanist approach or its international force for regulating clinical research. A proposal for an extensive revision of the Declaration's underlying ethical principles has been debated for the past four years. If the proposal is approved, international clinical research involving human beings will be modified, further increasing the vulnerability of certain social groups. This article discusses the historical process involved in passing the Helsinki Declaration and the most recent debate on the new draft. The article analyzes the new text's social implications for underdeveloped countries, arguing for a political approach to the vulnerability concept.

Natural language processing to extract symptoms of severe mental illness from clinical text: the Clinical Record Interactive Search Comprehensive Data Extraction (CRIS-CODE) project.

PubMed

Jackson, Richard G; Patel, Rashmi; Jayatilleke, Nishamali; Kolliakou, Anna; Ball, Michael; Gorrell, Genevieve; Roberts, Angus; Dobson, Richard J; Stewart, Robert

2017-01-17

We sought to use natural language processing to develop a suite of language models to capture key symptoms of severe mental illness (SMI) from clinical text, to facilitate the secondary use of mental healthcare data in research. Development and validation of information extraction applications for ascertaining symptoms of SMI in routine mental health records using the Clinical Record Interactive Search (CRIS) data resource; description of their distribution in a corpus of discharge summaries. Electronic records from a large mental healthcare provider serving a geographic catchment of 1.2 million residents in four boroughs of south London, UK. The distribution of derived symptoms was described in 23 128 discharge summaries from 7962 patients who had received an SMI diagnosis, and 13 496 discharge summaries from 7575 patients who had received a non-SMI diagnosis. Fifty SMI symptoms were identified by a team of psychiatrists for extraction based on salience and linguistic consistency in records, broadly categorised under positive, negative, disorganisation, manic and catatonic subgroups. Text models for each symptom were generated using the TextHunter tool and the CRIS database. We extracted data for 46 symptoms with a median F1 score of 0.88. Four symptom models performed poorly and were excluded. From the corpus of discharge summaries, it was possible to extract symptomatology in 87% of patients with SMI and 60% of patients with non-SMI diagnosis. This work demonstrates the possibility of automatically extracting a broad range of SMI symptoms from English text discharge summaries for patients with an SMI diagnosis. Descriptive data also indicated that most symptoms cut across diagnoses, rather than being restricted to particular groups. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.