Driving with roadmaps and dashboards: using information resources to structure the decision models in service organizations.

PubMed

Chorpita, Bruce F; Bernstein, Adam; Daleiden, Eric L

2008-03-01

This paper illustrates the application of design principles for tools that structure clinical decision-making. If the effort to implement evidence-based practices in community services organizations is to be effective, attention must be paid to the decision-making context in which such treatments are delivered. Clinical research trials commonly occur in an environment characterized by structured decision making and expert supports. Technology has great potential to serve mental health organizations by supporting these potentially important contextual features of the research environment, through organization and reporting of clinical data into interpretable information to support decisions and anchor decision-making procedures. This article describes one example of a behavioral health reporting system designed to facilitate clinical and administrative use of evidence-based practices. The design processes underlying this system-mapping of decision points and distillation of performance information at the individual, caseload, and organizational levels-can be implemented to support clinical practice in a wide variety of settings.

Development of a real-time clinical decision support system upon the web mvc-based architecture for prostate cancer treatment

PubMed Central

2011-01-01

Background A real-time clinical decision support system (RTCDSS) with interactive diagrams enables clinicians to instantly and efficiently track patients' clinical records (PCRs) and improve their quality of clinical care. We propose a RTCDSS to process online clinical informatics from multiple databases for clinical decision making in the treatment of prostate cancer based on Web Model-View-Controller (MVC) architecture, by which the system can easily be adapted to different diseases and applications. Methods We designed a framework upon the Web MVC-based architecture in which the reusable and extractable models can be conveniently adapted to other hospital information systems and which allows for efficient database integration. Then, we determined the clinical variables of the prostate cancer treatment based on participating clinicians' opinions and developed a computational model to determine the pretreatment parameters. Furthermore, the components of the RTCDSS integrated PCRs and decision factors for real-time analysis to provide evidence-based diagrams upon the clinician-oriented interface for visualization of treatment guidance and health risk assessment. Results The resulting system can improve quality of clinical treatment by allowing clinicians to concurrently analyze and evaluate the clinical markers of prostate cancer patients with instantaneous clinical data and evidence-based diagrams which can automatically identify pretreatment parameters. Moreover, the proposed RTCDSS can aid interactions between patients and clinicians. Conclusions Our proposed framework supports online clinical informatics, evaluates treatment risks, offers interactive guidance, and provides real-time reference for decision making in the treatment of prostate cancer. The developed clinician-oriented interface can assist clinicians in conveniently presenting evidence-based information to patients and can be readily adapted to an existing hospital information system and be easily applied in other chronic diseases. PMID:21385459

Development of a real-time clinical decision support system upon the Web MVC-based architecture for prostate cancer treatment.

PubMed

Lin, Hsueh-Chun; Wu, Hsi-Chin; Chang, Chih-Hung; Li, Tsai-Chung; Liang, Wen-Miin; Wang, Jong-Yi Wang

2011-03-08

A real-time clinical decision support system (RTCDSS) with interactive diagrams enables clinicians to instantly and efficiently track patients' clinical records (PCRs) and improve their quality of clinical care. We propose a RTCDSS to process online clinical informatics from multiple databases for clinical decision making in the treatment of prostate cancer based on Web Model-View-Controller (MVC) architecture, by which the system can easily be adapted to different diseases and applications. We designed a framework upon the Web MVC-based architecture in which the reusable and extractable models can be conveniently adapted to other hospital information systems and which allows for efficient database integration. Then, we determined the clinical variables of the prostate cancer treatment based on participating clinicians' opinions and developed a computational model to determine the pretreatment parameters. Furthermore, the components of the RTCDSS integrated PCRs and decision factors for real-time analysis to provide evidence-based diagrams upon the clinician-oriented interface for visualization of treatment guidance and health risk assessment. The resulting system can improve quality of clinical treatment by allowing clinicians to concurrently analyze and evaluate the clinical markers of prostate cancer patients with instantaneous clinical data and evidence-based diagrams which can automatically identify pretreatment parameters. Moreover, the proposed RTCDSS can aid interactions between patients and clinicians. Our proposed framework supports online clinical informatics, evaluates treatment risks, offers interactive guidance, and provides real-time reference for decision making in the treatment of prostate cancer. The developed clinician-oriented interface can assist clinicians in conveniently presenting evidence-based information to patients and can be readily adapted to an existing hospital information system and be easily applied in other chronic diseases.

Heuristics in Managing Complex Clinical Decision Tasks in Experts’ Decision Making

PubMed Central

Islam, Roosan; Weir, Charlene; Del Fiol, Guilherme

2016-01-01

Background Clinical decision support is a tool to help experts make optimal and efficient decisions. However, little is known about the high level of abstractions in the thinking process for the experts. Objective The objective of the study is to understand how clinicians manage complexity while dealing with complex clinical decision tasks. Method After approval from the Institutional Review Board (IRB), three clinical experts were interviewed the transcripts from these interviews were analyzed. Results We found five broad categories of strategies by experts for managing complex clinical decision tasks: decision conflict, mental projection, decision trade-offs, managing uncertainty and generating rule of thumb. Conclusion Complexity is created by decision conflicts, mental projection, limited options and treatment uncertainty. Experts cope with complexity in a variety of ways, including using efficient and fast decision strategies to simplify complex decision tasks, mentally simulating outcomes and focusing on only the most relevant information. Application Understanding complex decision making processes can help design allocation based on the complexity of task for clinical decision support design. PMID:27275019

Heuristics in Managing Complex Clinical Decision Tasks in Experts' Decision Making.

PubMed

Islam, Roosan; Weir, Charlene; Del Fiol, Guilherme

2014-09-01

Clinical decision support is a tool to help experts make optimal and efficient decisions. However, little is known about the high level of abstractions in the thinking process for the experts. The objective of the study is to understand how clinicians manage complexity while dealing with complex clinical decision tasks. After approval from the Institutional Review Board (IRB), three clinical experts were interviewed the transcripts from these interviews were analyzed. We found five broad categories of strategies by experts for managing complex clinical decision tasks: decision conflict, mental projection, decision trade-offs, managing uncertainty and generating rule of thumb. Complexity is created by decision conflicts, mental projection, limited options and treatment uncertainty. Experts cope with complexity in a variety of ways, including using efficient and fast decision strategies to simplify complex decision tasks, mentally simulating outcomes and focusing on only the most relevant information. Understanding complex decision making processes can help design allocation based on the complexity of task for clinical decision support design.

Knowledge bases, clinical decision support systems, and rapid learning in oncology.

PubMed

Yu, Peter Paul

2015-03-01

One of the most important benefits of health information technology is to assist the cognitive process of the human mind in the face of vast amounts of health data, limited time for decision making, and the complexity of the patient with cancer. Clinical decision support tools are frequently cited as a technologic solution to this problem, but to date useful clinical decision support systems (CDSS) have been limited in utility and implementation. This article describes three unique sources of health data that underlie fundamentally different types of knowledge bases which feed into CDSS. CDSS themselves comprise a variety of models which are discussed. The relationship of knowledge bases and CDSS to rapid learning health systems design is critical as CDSS are essential drivers of rapid learning in clinical care. Copyright © 2015 by American Society of Clinical Oncology.

Big-Data Based Decision-Support Systems to Improve Clinicians' Cognition.

PubMed

Roosan, Don; Samore, Matthew; Jones, Makoto; Livnat, Yarden; Clutter, Justin

2016-01-01

Complex clinical decision-making could be facilitated by using population health data to inform clinicians. In two previous studies, we interviewed 16 infectious disease experts to understand complex clinical reasoning. For this study, we focused on answers from the experts on how clinical reasoning can be supported by population-based Big-Data. We found cognitive strategies such as trajectory tracking, perspective taking, and metacognition has the potential to improve clinicians' cognition to deal with complex problems. These cognitive strategies could be supported by population health data, and all have important implications for the design of Big-Data based decision-support tools that could be embedded in electronic health records. Our findings provide directions for task allocation and design of decision-support applications for health care industry development of Big data based decision-support systems.

Big-Data Based Decision-Support Systems to Improve Clinicians’ Cognition

PubMed Central

Roosan, Don; Samore, Matthew; Jones, Makoto; Livnat, Yarden; Clutter, Justin

2016-01-01

Complex clinical decision-making could be facilitated by using population health data to inform clinicians. In two previous studies, we interviewed 16 infectious disease experts to understand complex clinical reasoning. For this study, we focused on answers from the experts on how clinical reasoning can be supported by population-based Big-Data. We found cognitive strategies such as trajectory tracking, perspective taking, and metacognition has the potential to improve clinicians’ cognition to deal with complex problems. These cognitive strategies could be supported by population health data, and all have important implications for the design of Big-Data based decision-support tools that could be embedded in electronic health records. Our findings provide directions for task allocation and design of decision-support applications for health care industry development of Big data based decision-support systems. PMID:27990498

An exploration of clinical decision making in mental health triage.

PubMed

Sands, Natisha

2009-08-01

Mental health (MH) triage is a specialist area of clinical nursing practice that involves complex decision making. The discussion in this article draws on the findings of a Ph.D. study that involved a statewide investigation of the scope of MH triage nursing practice in Victoria, Australia. Although the original Ph.D. study investigated a number of core practices in MH triage, the focus of the discussion in this article is specifically on the findings related to clinical decision making in MH triage, which have not previously been published. The study employed an exploratory descriptive research design that used mixed data collection methods including a survey questionnaire (n = 139) and semistructured interviews (n = 21). The study findings related to decision making revealed a lack of empirically tested evidence-based decision-making frameworks currently in use to support MH triage nursing practice. MH triage clinicians in Australia rely heavily on clinical experience to underpin decision making and have little of knowledge of theoretical models for practice, such as methodologies for rating urgency. A key recommendation arising from the study is the need to develop evidence-based decision-making frameworks such as clinical guidelines to inform and support MH triage clinical decision making.

Competency in health care management: a training model in epidemiologic methods for assessing and improving the quality of clinical practice through evidence-based decision making.

PubMed

Hudak, R P; Jacoby, I; Meyer, G S; Potter, A L; Hooper, T I; Krakauer, H

1997-01-01

This article describes a training model that focuses on health care management by applying epidemiologic methods to assess and improve the quality of clinical practice. The model's uniqueness is its focus on integrating clinical evidence-based decision making with fundamental principles of resource management to achieve attainable, cost-effective, high-quality health outcomes. The target students are current and prospective clinical and administrative executives who must optimize decision making at the clinical and managerial levels of health care organizations.

Development and evaluation of learning module on clinical decision-making in Prosthodontics.

PubMed

Deshpande, Saee; Lambade, Dipti; Chahande, Jayashree

2015-01-01

Best practice strategies for helping students learn the reasoning skills of problem solving and critical thinking (CT) remain a source of conjecture, particularly with regard to CT. The dental education literature is fundamentally devoid of research on the cognitive components of clinical decision-making. This study was aimed to develop and evaluate the impact of blended learning module on clinical decision-making skills of dental graduates for planning prosthodontics rehabilitation. An interactive teaching module consisting of didactic lectures on clinical decision-making and a computer-assisted case-based treatment planning software was developed Its impact on cognitive knowledge gain in clinical decision-making was evaluated using an assessment involving problem-based multiple choice questions and paper-based case scenarios. Mean test scores were: Pretest (17 ± 1), posttest 1 (21 ± 2) and posttest 2 (43 ± 3). Comparison of mean scores was done with one-way ANOVA test. There was overall significant difference in between mean scores at all the three points (P < 0.001). A pair-wise comparison of mean scores was done with Bonferroni test. The mean difference is significant at the 0.05 level. The pair-wise comparison shows that posttest 2 score is significantly higher than posttest 1 and posttest 1 is significantly higher than pretest that is, pretest 2 > posttest 1 > pretest. Blended teaching methods employing didactic lectures on the clinical decision-making as well as computer assisted case-based learning can be used to improve quality of clinical decision-making in prosthodontic rehabilitation for dental graduates.

Evidence-based medicine, clinical practice guidelines, and common sense in the management of osteoporosis.

PubMed

Lewiecki, E Michael; Binkley, Neil

2009-01-01

To evaluate the benefits and limitations of randomized controlled trials (RCTs), clinical practice guidelines (CPGs), and clinical judgment in the management of osteoporosis. A review was conducted of the English-language literature on the origins and applications of RCTs, CPGs, evidence-based medicine, and clinical judgment in the management of osteoporosis. Evidence-based medicine is use of the currently available best evidence in making clinical decisions for individual patients. CPGs are recommendations for making clinical decisions based on research evidence, sometimes with consideration of expert opinion, health care policy, and costs of care. The highest levels of medical evidence are usually thought to be RCTs and meta-analyses of high-quality RCTs. Although it is desirable and appropriate for clinicians to consider research evidence from RCTs and recommendations presented in CPGs in making clinical decisions, other factors-such as patient preference, comorbidities, affordability, and availability of care-are important for the actual implementation of evidence-based medicine. Decisions about who to treat, which drug to use, how best to monitor, and how long to treat require clinical skills in addition to knowledge of medical research. The necessity of integrating common sense and clinical judgment is highlighted by the fact that many patients treated for osteoporosis in clinical practice would not qualify for participation in the pivotal clinical trials that demonstrated efficacy and safety of the drugs used to treat them.

[A study on participation in clinical decision making by home healthcare nurses].

PubMed

Kim, Se Young

2010-12-01

This study was done to identify participation by home healthcare nurses in clinical decision making and factors influencing clinical decision making. A descriptive survey was used to collect data from 68 home healthcare nurses in 22 hospital-based home healthcare services in Korea. To investigate participation, the researcher developed 3 scenarios through interviews with 5 home healthcare nurses. A self-report questionnaire composed of tools for characteristics, factors of clinical decision making, and participation was used. Participation was relatively high, but significantly lower in the design phase (F=3.51, p=.032). Competency in clinical decision making (r=.45, p<.001), perception of the decision maker role (r=.47, p<.001), and perception of the utility of clinical practice guidelines (r=.25, p=.043) were significantly correlated with participation. Competency in clinical decision making (Odds ratio [OR]=41.79, p=.007) and perception of the decision maker role (OR=15.09, p=.007) were significant factors predicting participation in clinical decision making by home healthcare nurses. In order to encourage participation in clinical decision making, education programs should be provided to home healthcare nurses. Official clinical practice guidelines should be used to support home healthcare nurses' participation in clinical decision making in cases where they can identify and solve the patient health problems.

SANDS: a service-oriented architecture for clinical decision support in a National Health Information Network.

PubMed

Wright, Adam; Sittig, Dean F

2008-12-01

In this paper, we describe and evaluate a new distributed architecture for clinical decision support called SANDS (Service-oriented Architecture for NHIN Decision Support), which leverages current health information exchange efforts and is based on the principles of a service-oriented architecture. The architecture allows disparate clinical information systems and clinical decision support systems to be seamlessly integrated over a network according to a set of interfaces and protocols described in this paper. The architecture described is fully defined and developed, and six use cases have been developed and tested using a prototype electronic health record which links to one of the existing prototype National Health Information Networks (NHIN): drug interaction checking, syndromic surveillance, diagnostic decision support, inappropriate prescribing in older adults, information at the point of care and a simple personal health record. Some of these use cases utilize existing decision support systems, which are either commercially or freely available at present, and developed outside of the SANDS project, while other use cases are based on decision support systems developed specifically for the project. Open source code for many of these components is available, and an open source reference parser is also available for comparison and testing of other clinical information systems and clinical decision support systems that wish to implement the SANDS architecture. The SANDS architecture for decision support has several significant advantages over other architectures for clinical decision support. The most salient of these are:

A theory-based decision aid for patients with cancer: results of feasibility and acceptability testing of DecisionKEYS for cancer.

PubMed

Hollen, Patricia J; Gralla, Richard J; Jones, Randy A; Thomas, Christopher Y; Brenin, David R; Weiss, Geoffrey R; Schroen, Anneke T; Petroni, Gina R

2013-03-01

Appropriate utilization of treatment is a goal for all patients undergoing cancer treatment. Proper treatment maximizes benefit and limits exposure to unnecessary measures. This report describes findings of the feasibility and acceptability of implementing a short, clinic-based decision aid and presents an in-depth clinical profile of the participants. This descriptive study used a prospective, quantitative approach to obtain the feasibility and acceptability of a decision aid (DecisionKEYS for Balancing Choices) for use in clinical settings. It combined results of trials of patients with three different common malignancies. All groups used the same decision aid series. Participants included 80 patients with solid tumors (22 with newly diagnosed breast cancer, 19 with advanced prostate cancer, and 39 with advanced lung cancer) and their 80 supporters as well as their physicians and nurses, for a total of 160 participants and 10 health professionals. The decision aid was highly acceptable to patient and supporter participants in all diagnostic groups. It was feasible for use in clinic settings; the overall value was rated highly. Of six physicians, all found the interactive format with the help of the nurse as feasible and acceptable. Nurses also rated the decision aid favorably. This intervention provides the opportunity to enhance decision making about cancer treatment and warrants further study including larger and more diverse groups. Strengths of the study included a theoretical grounding, feasibility testing of a practical clinic-based intervention, and summative evaluation of acceptability of the intervention by patient and supporter pairs. Further research also is needed to test the effectiveness of the decision aid in diverse clinical settings and to determine if this intervention can decrease overall costs.

[The effects of case-based learning using video on clinical decision making and learning motivation in undergraduate nursing students].

PubMed

Yoo, Moon-Sook; Park, Jin-Hee; Lee, Si-Ra

2010-12-01

The purpose of this study was to examine the effects of case-base learning (CBL) using video on clinical decision-making and learning motivation. This research was conducted between June 2009 and April 2010 as a nonequivalent control group non-synchronized design. The study population was 44 third year nursing students who enrolled in a college of nursing, A University in Korea. The nursing students were divided into the CBL and the control group. The intervention was the CBL with three cases using video. The controls attended a traditional live lecture on the same topics. With questionnaires objective clinical decision-making, subjective clinical decision-making, and learning motivation were measured before the intervention, and 10 weeks after the intervention. Significant group differences were observed in clinical decision-making and learning motivation. The post-test scores of clinical decision-making in the CBL group were statistically higher than the control group. Learning motivation was also significantly higher in the CBL group than in the control group. These results indicate that CBL using video is effective in enhancing clinical decision-making and motivating students to learn by encouraging self-directed learning and creating more interest and curiosity in learning.

Enhancing clinical decision making: development of a contiguous definition and conceptual framework.

PubMed

Tiffen, Jennifer; Corbridge, Susan J; Slimmer, Lynda

2014-01-01

Clinical decision making is a term frequently used to describe the fundamental role of the nurse practitioner; however, other terms have been used interchangeably. The purpose of this article is to begin the process of developing a definition and framework of clinical decision making. The developed definition was "Clinical decision making is a contextual, continuous, and evolving process, where data are gathered, interpreted, and evaluated in order to select an evidence-based choice of action." A contiguous framework for clinical decision making specific for nurse practitioners is also proposed. Having a clear and unique understanding of clinical decision making will allow for consistent use of the term, which is relevant given the changing educational requirements for nurse practitioners and broadening scope of practice. Copyright © 2014 Elsevier Inc. All rights reserved.

Nurses' decision making in heart failure management based on heart failure certification status.

PubMed

Albert, Nancy M; Bena, James F; Buxbaum, Denise; Martensen, Linda; Morrison, Shannon L; Prasun, Marilyn A; Stamp, Kelly D

Research findings on the value of nurse certification were based on subjective perceptions or biased by correlations of certification status and global clinical factors. In heart failure, the value of certification is unknown. Examine the value of certification based nurses' decision-making. Cross-sectional study of nurses who completed heart failure clinical vignettes that reflected decision-making in clinical heart failure scenarios. Statistical tests included multivariable linear, logistic and proportional odds logistic regression models. Of nurses (N = 605), 29.1% were heart failure certified, 35.0% were certified in another specialty/job role and 35.9% were not certified. In multivariable modeling, nurses certified in heart failure (versus not heart failure certified) had higher clinical vignette scores (p = 0.002), reflecting higher evidence-based decision making; nurses with another specialty/role certification (versus no certification) did not (p = 0.62). Heart failure certification, but not in other specialty/job roles was associated with decisions that reflected delivery of high-quality care. Copyright © 2018 Elsevier Inc. All rights reserved.

Gathering Real World Evidence with Cluster Analysis for Clinical Decision Support.

PubMed

Xia, Eryu; Liu, Haifeng; Li, Jing; Mei, Jing; Li, Xuejun; Xu, Enliang; Li, Xiang; Hu, Gang; Xie, Guotong; Xu, Meilin

2017-01-01

Clinical decision support systems are information technology systems that assist clinical decision-making tasks, which have been shown to enhance clinical performance. Cluster analysis, which groups similar patients together, aims to separate patient cases into phenotypically heterogenous groups and defining therapeutically homogeneous patient subclasses. Useful as it is, the application of cluster analysis in clinical decision support systems is less reported. Here, we describe the usage of cluster analysis in clinical decision support systems, by first dividing patient cases into similar groups and then providing diagnosis or treatment suggestions based on the group profiles. This integration provides data for clinical decisions and compiles a wide range of clinical practices to inform the performance of individual clinicians. We also include an example usage of the system under the scenario of blood lipid management in type 2 diabetes. These efforts represent a step toward promoting patient-centered care and enabling precision medicine.

Lessons learned from implementing service-oriented clinical decision support at four sites: A qualitative study.

PubMed

Wright, Adam; Sittig, Dean F; Ash, Joan S; Erickson, Jessica L; Hickman, Trang T; Paterno, Marilyn; Gebhardt, Eric; McMullen, Carmit; Tsurikova, Ruslana; Dixon, Brian E; Fraser, Greg; Simonaitis, Linas; Sonnenberg, Frank A; Middleton, Blackford

2015-11-01

To identify challenges, lessons learned and best practices for service-oriented clinical decision support, based on the results of the Clinical Decision Support Consortium, a multi-site study which developed, implemented and evaluated clinical decision support services in a diverse range of electronic health records. Ethnographic investigation using the rapid assessment process, a procedure for agile qualitative data collection and analysis, including clinical observation, system demonstrations and analysis and 91 interviews. We identified challenges and lessons learned in eight dimensions: (1) hardware and software computing infrastructure, (2) clinical content, (3) human-computer interface, (4) people, (5) workflow and communication, (6) internal organizational policies, procedures, environment and culture, (7) external rules, regulations, and pressures and (8) system measurement and monitoring. Key challenges included performance issues (particularly related to data retrieval), differences in terminologies used across sites, workflow variability and the need for a legal framework. Based on the challenges and lessons learned, we identified eight best practices for developers and implementers of service-oriented clinical decision support: (1) optimize performance, or make asynchronous calls, (2) be liberal in what you accept (particularly for terminology), (3) foster clinical transparency, (4) develop a legal framework, (5) support a flexible front-end, (6) dedicate human resources, (7) support peer-to-peer communication, (8) improve standards. The Clinical Decision Support Consortium successfully developed a clinical decision support service and implemented it in four different electronic health records and four diverse clinical sites; however, the process was arduous. The lessons identified by the Consortium may be useful for other developers and implementers of clinical decision support services. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Semantic Clinical Guideline Documents

PubMed Central

Eriksson, Henrik; Tu, Samson W.; Musen, Mark

2005-01-01

Decision-support systems based on clinical practice guidelines can support physicians and other health-care personnel in the process of following best practice consistently. A knowledge-based approach to represent guidelines makes it possible to encode computer-interpretable guidelines in a formal manner, perform consistency checks, and use the guidelines directly in decision-support systems. Decision-support authors and guideline users require guidelines in human-readable formats in addition to computer-interpretable ones (e.g., for guideline review and quality assurance). We propose a new document-oriented information architecture that combines knowledge-representation models with electronic and paper documents. The approach integrates decision-support modes with standard document formats to create a combined clinical-guideline model that supports on-line viewing, printing, and decision support. PMID:16779037

Nurses' Clinical Decision Making on Adopting a Wound Clinical Decision Support System.

PubMed

Khong, Peck Chui Betty; Hoi, Shu Yin; Holroyd, Eleanor; Wang, Wenru

2015-07-01

Healthcare information technology systems are considered the ideal tool to inculcate evidence-based nursing practices. The wound clinical decision support system was built locally to support nurses to manage pressure ulcer wounds in their daily practice. However, its adoption rate is not optimal. The study's objective was to discover the concepts that informed the RNs' decisions to adopt the wound clinical decision support system as an evidence-based technology in their nursing practice. This was an exploratory, descriptive, and qualitative design using face-to-face interviews, individual interviews, and active participatory observation. A purposive, theoretical sample of 14 RNs was recruited from one of the largest public tertiary hospitals in Singapore after obtaining ethics approval. After consenting, the nurses were interviewed and observed separately. Recruitment stopped when data saturation was reached. All transcribed interview data underwent a concurrent thematic analysis, whereas observational data were content analyzed independently and subsequently triangulated with the interview data. Eight emerging themes were identified, namely, use of the wound clinical decision support system, beliefs in the wound clinical decision support system, influences of the workplace culture, extent of the benefits, professional control over nursing practices, use of knowledge, gut feelings, and emotions (fear, doubt, and frustration). These themes represented the nurses' mental outlook as they made decisions on adopting the wound clinical decision support system in light of the complexities of their roles and workloads. This research has provided insight on the nurses' thoughts regarding their decision to interact with the computer environment in a Singapore context. It captured the nurses' complex thoughts when deciding whether to adopt or reject information technology as they practice in a clinical setting.

Clinical decision making using teleradiology in urology.

PubMed

Lee, B R; Allaf, M; Moore, R; Bohlman, M; Wang, G M; Bishoff, J T; Jackman, S V; Cadeddu, J A; Jarrett, T W; Khazan, R; Kavoussi, L R

1999-01-01

Using a personal computer-based teleradiology system, we compared accuracy, confidence, and diagnostic ability in the interpretation of digitized radiographs to determine if teleradiology-imported studies convey sufficient information to make relevant clinical decisions involving urology. Variables of diagnostic accuracy, confidence, image quality, interpretation, and the impact of clinical decisions made after viewing digitized radiographs were compared with those of original radiographs. We evaluated 956 radiographs that included 94 IV pyelograms, four voiding cystourethrograms, and two nephrostograms. The radiographs were digitized and transferred over an Ethernet network to a remote personal computer-based viewing station. The digitized images were viewed by urologists and graded according to confidence in making a diagnosis, image quality, diagnostic difficulty, clinical management based on the image itself, and brief patient history. The hard-copy radiographs were then interpreted immediately afterward, and diagnostic decisions were reassessed. All analog radiographs were reviewed by an attending radiologist. Ninety-seven percent of the decisions made from the digitized radiographs did not change after reviewing conventional radiographs of the same case. When comparing the variables of clinical confidence, quality of the film on the teleradiology system versus analog films, and diagnostic difficulty, we found no statistical difference (p > .05) between the two techniques. Overall accuracy in interpreting the digitized images on the teleradiology system was 88% by urologists compared with that of the attending radiologist's interpretation of the analog radiographs. However, urologists detected findings on five (5%) analog radiographs that had been previously unreported by the radiologist. Viewing radiographs transmitted to a personal computer-based viewing station is an appropriate means of reviewing films with sufficient quality on which to base clinical decisions. Our focus was whether decisions made after viewing the transmitted radiographs would change after viewing the hard-copy images of the same case. In 97% of the cases, the decision did not change. In those cases in which management was altered, recommendation of further imaging studies was the most common factor.

Withdrawal of anticancer therapy in advanced disease: a systematic literature review.

PubMed

Clarke, G; Johnston, S; Corrie, P; Kuhn, I; Barclay, S

2015-11-11

Current guidelines set out when to start anticancer treatments, but not when to stop as the end of life approaches. Conventional cytotoxic agents are administered intravenously and have major life-threatening toxicities. Newer drugs include molecular targeted agents (MTAs), in particular, small molecule kinase-inhibitors (KIs), which are administered orally. These have fewer life-threatening toxicities, and are increasingly used to palliate advanced cancer, generally offering additional months of survival benefit. MTAs are substantially more expensive, between £2-8 K per month, and perceived as easier to start than stop. A systematic review of decision-making concerning the withdrawal of anticancer drugs towards the end of life within clinical practice, with a particular focus on MTAs. Nine electronic databases searched. PRISMA guidelines followed. Forty-two studies included. How are decisions made? Decision-making was shared and ongoing, including stopping, starting and trying different treatments. Oncologists often experienced 'professional role dissonance' between their self-perception as 'treaters', and talking about end of life care. Why are decisions made? Clinical factors: disease progression, worsening functional status, treatment side-effects. Non-clinical factors: physicians' personal experience, values, emotions. Some patients continued treatment to maintain 'hope', often reflecting limited understanding of palliative goals. When are decisions made? Limited evidence reveals patients' decisions based upon quality of life benefits. Clinicians found timing withdrawal particularly challenging. Who makes the decisions? Decisions were based within physician-patient interaction. Oncologists report that decisions around stopping chemotherapy treatment are challenging, with limited evidence-based guidance outside of clinical trial protocols. The increasing availability of oral MTAs is transforming the management of incurable cancer; blurring boundaries between active treatment and palliative care. No studies specifically addressing decision-making around stopping MTAs in clinical practice were identified. There is a need to develop an evidence base to support physicians and patients with decision-making around the withdrawal of these high cost treatments.

Implementation of a scalable, web-based, automated clinical decision support risk-prediction tool for chronic kidney disease using C-CDA and application programming interfaces.

PubMed

Samal, Lipika; D'Amore, John D; Bates, David W; Wright, Adam

2017-11-01

Clinical decision support tools for risk prediction are readily available, but typically require workflow interruptions and manual data entry so are rarely used. Due to new data interoperability standards for electronic health records (EHRs), other options are available. As a clinical case study, we sought to build a scalable, web-based system that would automate calculation of kidney failure risk and display clinical decision support to users in primary care practices. We developed a single-page application, web server, database, and application programming interface to calculate and display kidney failure risk. Data were extracted from the EHR using the Consolidated Clinical Document Architecture interoperability standard for Continuity of Care Documents (CCDs). EHR users were presented with a noninterruptive alert on the patient's summary screen and a hyperlink to details and recommendations provided through a web application. Clinic schedules and CCDs were retrieved using existing application programming interfaces to the EHR, and we provided a clinical decision support hyperlink to the EHR as a service. We debugged a series of terminology and technical issues. The application was validated with data from 255 patients and subsequently deployed to 10 primary care clinics where, over the course of 1 year, 569 533 CCD documents were processed. We validated the use of interoperable documents and open-source components to develop a low-cost tool for automated clinical decision support. Since Consolidated Clinical Document Architecture-based data extraction extends to any certified EHR, this demonstrates a successful modular approach to clinical decision support. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association.

Using Best Practices to Extract, Organize, and Reuse Embedded Decision Support Content Knowledge Rules from Mature Clinical Systems.

PubMed

DesAutels, Spencer J; Fox, Zachary E; Giuse, Dario A; Williams, Annette M; Kou, Qing-Hua; Weitkamp, Asli; Neal R, Patel; Bettinsoli Giuse, Nunzia

2016-01-01

Clinical decision support (CDS) knowledge, embedded over time in mature medical systems, presents an interesting and complex opportunity for information organization, maintenance, and reuse. To have a holistic view of all decision support requires an in-depth understanding of each clinical system as well as expert knowledge of the latest evidence. This approach to clinical decision support presents an opportunity to unify and externalize the knowledge within rules-based decision support. Driven by an institutional need to prioritize decision support content for migration to new clinical systems, the Center for Knowledge Management and Health Information Technology teams applied their unique expertise to extract content from individual systems, organize it through a single extensible schema, and present it for discovery and reuse through a newly created Clinical Support Knowledge Acquisition and Archival Tool (CS-KAAT). CS-KAAT can build and maintain the underlying knowledge infrastructure needed by clinical systems.

Clinical decision support provided within physician order entry systems: a systematic review of features effective for changing clinician behavior.

PubMed

Kawamoto, Kensaku; Lobach, David F

2003-01-01

Computerized physician order entry (CPOE) systems represent an important tool for providing clinical decision support. In undertaking this systematic review, our objective was to identify the features of CPOE-based clinical decision support systems (CDSSs) most effective at modifying clinician behavior. For this review, two independent reviewers systematically identified randomized controlled trials that evaluated the effectiveness of CPOE-based CDSSs in changing clinician behavior. Furthermore, each included study was assessed for the presence of 14 CDSS features. We screened 10,023 citations and included 11 studies. Of the 10 studies comparing a CPOE-based CDSS intervention against a non-CDSS control group, 7 reported a significant desired change in professional practice. Moreover, meta-regression analysis revealed that automatic provision of the decision support was strongly associated with improved professional practice (adjusted odds ratio, 23.72; 95% confidence interval, 1.75-infiniti). Thus, we conclude that automatic provision of decision support is a critical feature of successful CPOE-based CDSS interventions.

Designing Computerized Decision Support That Works for Clinicians and Families

PubMed Central

Fiks, Alexander G.

2011-01-01

Evidence-based decision-making is central to the practice of pediatrics. Clinical trials and other biomedical research provide a foundation for this process, and practice guidelines, drawing from their results, inform the optimal management of an increasing number of childhood health problems. However, many clinicians fail to adhere to guidelines. Clinical decision support delivered using health information technology, often in the form of electronic health records, provides a tool to deliver evidence-based information to the point of care and has the potential to overcome barriers to evidence-based practice. An increasing literature now informs how these systems should be designed and implemented to most effectively improve outcomes in pediatrics. Through the examples of computerized physician order entry, as well as the impact of alerts at the point of care on immunization rates, the delivery of evidence-based asthma care, and the follow-up of children with attention deficit hyperactivity disorder, the following review addresses strategies for success in using these tools. The following review argues that, as decision support evolves, the clinician should no longer be the sole target of information and alerts. Through the Internet and other technologies, families are increasingly seeking health information and gathering input to guide health decisions. By enlisting clinical decision support systems to deliver evidence-based information to both clinicians and families, help families express their preferences and goals, and connect families to the medical home, clinical decision support may ultimately be most effective in improving outcomes. PMID:21315295

Towards knowledge-based systems in clinical practice: development of an integrated clinical information and knowledge management support system.

PubMed

Kalogeropoulos, Dimitris A; Carson, Ewart R; Collinson, Paul O

2003-09-01

Given that clinicians presented with identical clinical information will act in different ways, there is a need to introduce into routine clinical practice methods and tools to support the scientific homogeneity and accountability of healthcare decisions and actions. The benefits expected from such action include an overall reduction in cost, improved quality of care, patient and public opinion satisfaction. Computer-based medical data processing has yielded methods and tools for managing the task away from the hospital management level and closer to the desired disease and patient management level. To this end, advanced applications of information and disease process modelling technologies have already demonstrated an ability to significantly augment clinical decision making as a by-product. The wide-spread acceptance of evidence-based medicine as the basis of cost-conscious and concurrently quality-wise accountable clinical practice suffices as evidence supporting this claim. Electronic libraries are one-step towards an online status of this key health-care delivery quality control environment. Nonetheless, to date, the underlying information and knowledge management technologies have failed to be integrated into any form of pragmatic or marketable online and real-time clinical decision making tool. One of the main obstacles that needs to be overcome is the development of systems that treat both information and knowledge as clinical objects with same modelling requirements. This paper describes the development of such a system in the form of an intelligent clinical information management system: a system which at the most fundamental level of clinical decision support facilitates both the organised acquisition of clinical information and knowledge and provides a test-bed for the development and evaluation of knowledge-based decision support functions.

[Treatment regulations and treatment limits: factors influencing clinical decision-making].

PubMed

Baberg, H T; Kielstein, R; de Zeeuw, J; Sass, H-M

2002-08-02

Providing or withholding of treatment is based on a variety of factors. We sought for criteria in clinical decision making and reviewed attitudes towards clinical intuition and the patient's will. 503 physicians (25.6 % females; mean age 36.3) in 49 departments at nine hospitals of the universities Bochum and Magdeburg filled in a validated questionnaire. The most important factors in the decision to carry out a therapy were "international standards" and "own experience". The decision to omit a therapy was mainly influenced by the "patient's wish". Physicians with a higher status judged their own experience higher than young physicians, who considered the experience of colleagues more important. "Severe accompanying illnesses" and "multimorbidity" were the most frequently named reasons to withdraw a therapy. Intuitive decision-making was rare, especially in young physicians, although these decisions were seldom risky and often successful. A patient's will plays a prominent role in clinical decision making, especially in decisions to withdraw or to withhold treatment. Cost containment and research interest have been called less important, a remarkable response from research-based university hospitals. Also remarkable is the recognition and importance of clinical intuition in situations of complex or missing information. This important aspect is rarely discussed in the literature or in medical education. The widely voiced concern that priorities in clinical care are guided by scientific interest, financial or technical possibilities could not be confirmed.

SANDS: A Service-Oriented Architecture for Clinical Decision Support in a National Health Information Network

PubMed Central

Wright, Adam; Sittig, Dean F.

2008-01-01

In this paper we describe and evaluate a new distributed architecture for clinical decision support called SANDS (Service-oriented Architecture for NHIN Decision Support), which leverages current health information exchange efforts and is based on the principles of a service-oriented architecture. The architecture allows disparate clinical information systems and clinical decision support systems to be seamlessly integrated over a network according to a set of interfaces and protocols described in this paper. The architecture described is fully defined and developed, and six use cases have been developed and tested using a prototype electronic health record which links to one of the existing prototype National Health Information Networks (NHIN): drug interaction checking, syndromic surveillance, diagnostic decision support, inappropriate prescribing in older adults, information at the point of care and a simple personal health record. Some of these use cases utilize existing decision support systems, which are either commercially or freely available at present, and developed outside of the SANDS project, while other use cases are based on decision support systems developed specifically for the project. Open source code for many of these components is available, and an open source reference parser is also available for comparison and testing of other clinical information systems and clinical decision support systems that wish to implement the SANDS architecture. PMID:18434256

Clinical-decision support based on medical literature: A complex network approach

NASA Astrophysics Data System (ADS)

Jiang, Jingchi; Zheng, Jichuan; Zhao, Chao; Su, Jia; Guan, Yi; Yu, Qiubin

2016-10-01

In making clinical decisions, clinicians often review medical literature to ensure the reliability of diagnosis, test, and treatment because the medical literature can answer clinical questions and assist clinicians making clinical decisions. Therefore, finding the appropriate literature is a critical problem for clinical-decision support (CDS). First, the present study employs search engines to retrieve relevant literature about patient records. However, the result of the traditional method is usually unsatisfactory. To improve the relevance of the retrieval result, a medical literature network (MLN) based on these retrieved papers is constructed. Then, we show that this MLN has small-world and scale-free properties of a complex network. According to the structural characteristics of the MLN, we adopt two methods to further identify the potential relevant literature in addition to the retrieved literature. By integrating these potential papers into the MLN, a more comprehensive MLN is built to answer the question of actual patient records. Furthermore, we propose a re-ranking model to sort all papers by relevance. We experimentally find that the re-ranking model can improve the normalized discounted cumulative gain of the results. As participants of the Text Retrieval Conference 2015, our clinical-decision method based on the MLN also yields higher scores than the medians in most topics and achieves the best scores for topics: #11 and #12. These research results indicate that our study can be used to effectively assist clinicians in making clinical decisions, and the MLN can facilitate the investigation of CDS.

A Computational Model of Reasoning from the Clinical Literature

PubMed Central

Rennels, Glenn D.

1986-01-01

This paper explores the premise that a formalized representation of empirical studies can play a central role in computer-based decision support. The specific motivations underlying this research include the following propositions: 1. Reasoning from experimental evidence contained in the clinical literature is central to the decisions physicians make in patient care. 2. A computational model, based upon a declarative representation for published reports of clinical studies, can drive a computer program that selectively tailors knowledge of the clinical literature as it is applied to a particular case. 3. The development of such a computational model is an important first step toward filling a void in computer-based decision support systems. Furthermore, the model may help us better understand the general principles of reasoning from experimental evidence both in medicine and other domains. Roundsman is a developmental computer system which draws upon structured representations of the clinical literature in order to critique plans for the management of primary breast cancer. Roundsman is able to produce patient-specific analyses of breast cancer management options based on the 24 clinical studies currently encoded in its knowledge base. The Roundsman system is a first step in exploring how the computer can help to bring a critical analysis of the relevant literature to the physician, structured around a particular patient and treatment decision.

Decision tools in health care: focus on the problem, not the solution.

PubMed

Liu, Joseph; Wyatt, Jeremy C; Altman, Douglas G

2006-01-20

Systematic reviews or randomised-controlled trials usually help to establish the effectiveness of drugs and other health technologies, but are rarely sufficient by themselves to ensure actual clinical use of the technology. The process from innovation to routine clinical use is complex. Numerous computerised decision support systems (DSS) have been developed, but many fail to be taken up into actual use. Some developers construct technologically advanced systems with little relevance to the real world. Others did not determine whether a clinical need exists. With NHS investing 5 billion pounds sterling in computer systems, also occurring in other countries, there is an urgent need to shift from a technology-driven approach to one that identifies and employs the most cost-effective method to manage knowledge, regardless of the technology. The generic term, 'decision tool' (DT), is therefore suggested to demonstrate that these aids, which seem different technically, are conceptually the same from a clinical viewpoint. Many computerised DSSs failed for various reasons, for example, they were not based on best available knowledge; there was insufficient emphasis on their need for high quality clinical data; their development was technology-led; or evaluation methods were misapplied. We argue that DSSs and other computer-based, paper-based and even mechanical decision aids are members of a wider family of decision tools. A DT is an active knowledge resource that uses patient data to generate case specific advice, which supports decision making about individual patients by health professionals, the patients themselves or others concerned about them. The identification of DTs as a consistent and important category of health technology should encourage the sharing of lessons between DT developers and users and reduce the frequency of decision tool projects focusing only on technology. The focus of evaluation should become more clinical, with the impact of computer-based DTs being evaluated against other computer, paper- or mechanical tools, to identify the most cost effective tool for each clinical problem. We suggested the generic term 'decision tool' to demonstrate that decision-making aids, such as computerised DSSs, paper algorithms, and reminders are conceptually the same, so the methods to evaluate them should be the same.

Clinical errors that can occur in the treatment decision-making process in psychotherapy.

PubMed

Park, Jake; Goode, Jonathan; Tompkins, Kelley A; Swift, Joshua K

2016-09-01

Clinical errors occur in the psychotherapy decision-making process whenever a less-than-optimal treatment or approach is chosen when working with clients. A less-than-optimal approach may be one that a client is unwilling to try or fully invest in based on his/her expectations and preferences, or one that may have little chance of success based on contraindications and/or limited research support. The doctor knows best and the independent choice models are two decision-making models that are frequently used within psychology, but both are associated with an increased likelihood of errors in the treatment decision-making process. In particular, these models fail to integrate all three components of the definition of evidence-based practice in psychology (American Psychological Association, 2006). In this article we describe both models and provide examples of clinical errors that can occur in each. We then introduce the shared decision-making model as an alternative that is less prone to clinical errors. PsycINFO Database Record (c) 2016 APA, all rights reserved

A clinical decision support system for diagnosis of Allergic Rhinitis based on intradermal skin tests.

PubMed

Jabez Christopher, J; Khanna Nehemiah, H; Kannan, A

2015-10-01

Allergic Rhinitis is a universal common disease, especially in populated cities and urban areas. Diagnosis and treatment of Allergic Rhinitis will improve the quality of life of allergic patients. Though skin tests remain the gold standard test for diagnosis of allergic disorders, clinical experts are required for accurate interpretation of test outcomes. This work presents a clinical decision support system (CDSS) to assist junior clinicians in the diagnosis of Allergic Rhinitis. Intradermal Skin tests were performed on patients who had plausible allergic symptoms. Based on patient׳s history, 40 clinically relevant allergens were tested. 872 patients who had allergic symptoms were considered for this study. The rule based classification approach and the clinical test results were used to develop and validate the CDSS. Clinical relevance of the CDSS was compared with the Score for Allergic Rhinitis (SFAR). Tests were conducted for junior clinicians to assess their diagnostic capability in the absence of an expert. The class based Association rule generation approach provides a concise set of rules that is further validated by clinical experts. The interpretations of the experts are considered as the gold standard. The CDSS diagnoses the presence or absence of rhinitis with an accuracy of 88.31%. The allergy specialist and the junior clinicians prefer the rule based approach for its comprehendible knowledge model. The Clinical Decision Support Systems with rule based classification approach assists junior doctors and clinicians in the diagnosis of Allergic Rhinitis to make reliable decisions based on the reports of intradermal skin tests. Copyright © 2015 Elsevier Ltd. All rights reserved.

A problem solving and decision making toolbox for approaching clinical problems and decisions.

PubMed

Margolis, C; Jotkowitz, A; Sitter, H

2004-08-01

In this paper, we begin by presenting three real patients and then review all the practical conceptual tools that have been suggested for systematically analyzing clinical problems. Each of these conceptual tools (e.g. Evidence-Based Medicine, Clinical Practice Guidelines, Decision Analysis) deals mainly with a different type or aspect of clinical problems. We suggest that all of these conceptual tools can be thought of as belonging in the clinician's toolbox for solving clinical problems and making clinical decisions. A heuristic for guiding the clinician in using the tools is proposed. The heuristic is then used to analyze management of the three patients presented at the outset. Copyright 2004 Birkhäuser Verlag, Basel

Efficacy of an evidence-based clinical decision support in primary care practices: a randomized clinical trial.

PubMed

McGinn, Thomas G; McCullagh, Lauren; Kannry, Joseph; Knaus, Megan; Sofianou, Anastasia; Wisnivesky, Juan P; Mann, Devin M

2013-09-23

There is consensus that incorporating clinical decision support into electronic health records will improve quality of care, contain costs, and reduce overtreatment, but this potential has yet to be demonstrated in clinical trials. To assess the influence of a customized evidence-based clinical decision support tool on the management of respiratory tract infections and on the effectiveness of integrating evidence at the point of care. In a randomized clinical trial, we implemented 2 well-validated integrated clinical prediction rules, namely, the Walsh rule for streptococcal pharyngitis and the Heckerling rule for pneumonia. INTERVENTIONS AND MAIN OUTCOMES AND MEASURES: The intervention group had access to the integrated clinical prediction rule tool and chose whether to complete risk score calculators, order medications, and generate progress notes to assist with complex decision making at the point of care. The intervention group completed the integrated clinical prediction rule tool in 57.5% of visits. Providers in the intervention group were significantly less likely to order antibiotics than the control group (age-adjusted relative risk, 0.74; 95% CI, 0.60-0.92). The absolute risk of the intervention was 9.2%, and the number needed to treat was 10.8. The intervention group was significantly less likely to order rapid streptococcal tests compared with the control group (relative risk, 0.75; 95% CI, 0.58-0.97; P= .03). The integrated clinical prediction rule process for integrating complex evidence-based clinical decision report tools is of relevant importance for national initiatives, such as Meaningful Use. TRIAL REGISTRATION clinicaltrials.gov Identifier: NCT01386047.

Cross-sectional study to examine evidence-based practice skills and behaviors of physical therapy graduates: is there a knowledge-to-practice gap?

PubMed

Manns, Patricia J; Norton, Amy V; Darrah, Johanna

2015-04-01

Curricula changes in physical therapist education programs in Canada emphasize evidence-based practice skills, including literature retrieval and evaluation. Do graduates use these skills in practice? The aim of this study was to evaluate the use of research information in the clinical decision making of therapists with different years of experience and evidence-based practice preparation. Perceptions about evidence-based practice were explored qualitatively. A cross-sectional study with 4 graduating cohorts was conducted. Eighty physical therapists representing 4 different graduating cohorts participated in interviews focused on 2 clinical scenarios. Participants had varying years of clinical experience (range=1-15 years) and academic knowledge of evidence-based practice skills. Therapists discussed the effectiveness of interventions related to the scenarios and identified the sources of information used to reach decisions. Participants also answered general questions related to evidence-based practice knowledge. Recent graduates demonstrated better knowledge of evidence-based practice skills compared with therapists with 6 to 15 years of clinical experience. However, all groups used clinical experience most frequently as their source of information for clinical decisions. Research evidence was infrequently included in decision making. This study used a convenience sample of therapists who agreed to volunteer for the study. The results suggest a knowledge-to-practice gap; graduates are not using the new skills to inform their practice. Tailoring academic evidence-based activities more to the time constraints of clinical practice may help students to be more successful in applying evidence in practice. Academic programs need to do more to create and nurture environments in both academic and clinical settings to ensure students practice using evidence-based practice skills across settings. © 2015 American Physical Therapy Association.

Evaluate the ability of clinical decision support systems (CDSSs) to improve clinical practice.

PubMed

Ajami, Sima; Amini, Fatemeh

2013-01-01

Prevalence of new diseases, medical science promotion and increase of referring to health care centers, provide a good situation for medical errors growth. Errors can involve medicines, surgery, diagnosis, equipment, or lab reports. Medical errors can occur anywhere in the health care system: In hospitals, clinics, surgery centers, doctors' offices, nursing homes, pharmacies, and patients' homes. According to the Institute of Medicine (IOM), 98,000 people die every year from preventable medical errors. In 2010 from all referred medical error records to Iran Legal Medicine Organization, 46/5% physician and medical team members were known as delinquent. One of new technologies that can reduce medical errors is clinical decision support systems (CDSSs). This study was unsystematic-review study. The literature was searched on evaluate the "ability of clinical decision support systems to improve clinical practice" with the help of library, books, conference proceedings, data bank, and also searches engines available at Google, Google scholar. For our searches, we employed the following keywords and their combinations: medical error, clinical decision support systems, Computer-Based Clinical Decision Support Systems, information technology, information system, health care quality, computer systems in the searching areas of title, keywords, abstract, and full text. In this study, more than 100 articles and reports were collected and 38 of them were selected based on their relevancy. The CDSSs are computer programs, designed for help to health care careers. These systems as a knowledge-based tool could help health care manager in analyze evaluation, improvement and selection of effective solutions in clinical decisions. Therefore, it has a main role in medical errors reduction. The aim of this study was to express ability of the CDSSs to improve

Patients' Values in Clinical Decision-Making.

PubMed

Faggion, Clovis Mariano; Pachur, Thorsten; Giannakopoulos, Nikolaos Nikitas

2017-09-01

Shared decision-making involves the participation of patient and dental practitioner. Well-informed decision-making requires that both parties understand important concepts that may influence the decision. This fourth article in a series of 4 aims to discuss the importance of patients' values when a clinical decision is made. We report on how to incorporate important concepts for well-informed, shared decision-making. Here, we present patient values as an important issue, in addition to previously established topics such as the risk of bias of a study, cost-effectiveness of treatment approaches, and a comparison of therapeutic benefit with potential side effects. We provide 2 clinical examples and suggestions for a decision tree, based on the available evidence. The information reported in this article may improve the relationship between patient and dental practitioner, resulting in more well-informed clinical decisions. Copyright © 2017 Elsevier Inc. All rights reserved.

[Value-based cancer care. From traditional evidence-based decision making to balanced decision making within frameworks of shared values].

PubMed

Palazzo, Salvatore; Filice, Aldo; Mastroianni, Candida; Biamonte, Rosalbino; Conforti, Serafino; Liguori, Virginia; Turano, Salvatore; De Simone, Rosanna; Rovito, Antonio; Manfredi, Caterina; Minardi, Stefano; Vilardo, Emmanuelle; Loizzo, Monica; Oriolo, Carmela

2016-04-01

Clinical decision making in oncology is based so far on the evidence of efficacy from high-quality clinical research. Data collection and analysis from experimental studies provide valuable insight into response rates and progression-free or overall survival. Data processing generates valuable information for medical professionals involved in cancer patient care, enabling them to make objective and unbiased choices. The increased attention of many scientific associations toward a more rational resource consumption in clinical decision making is mirrored in the Choosing Wisely campaign against the overuse or misuse of exams and procedures of little or no benefit for the patient. This cultural movement has been actively promoting care solutions based on the concept of "value". As a result, the value-based decision-making process for cancer care should not be dissociated from economic sustainability and from ethics of the affordability, also given the growing average cost of the most recent cancer drugs. In support of this orientation, the National Comprehensive Cancer Network (NCCN) has developed innovative and "complex" guidelines based on values, defined as "evidence blocks", with the aim of assisting the medical community in making overall sustainable choices.

Creating and sharing clinical decision support content with Web 2.0: Issues and examples.

PubMed

Wright, Adam; Bates, David W; Middleton, Blackford; Hongsermeier, Tonya; Kashyap, Vipul; Thomas, Sean M; Sittig, Dean F

2009-04-01

Clinical decision support is a powerful tool for improving healthcare quality and patient safety. However, developing a comprehensive package of decision support interventions is costly and difficult. If used well, Web 2.0 methods may make it easier and less costly to develop decision support. Web 2.0 is characterized by online communities, open sharing, interactivity and collaboration. Although most previous attempts at sharing clinical decision support content have worked outside of the Web 2.0 framework, several initiatives are beginning to use Web 2.0 to share and collaborate on decision support content. We present case studies of three efforts: the Clinfowiki, a world-accessible wiki for developing decision support content; Partners Healthcare eRooms, web-based tools for developing decision support within a single organization; and Epic Systems Corporation's Community Library, a repository for sharing decision support content for customers of a single clinical system vendor. We evaluate the potential of Web 2.0 technologies to enable collaborative development and sharing of clinical decision support systems through the lens of three case studies; analyzing technical, legal and organizational issues for developers, consumers and organizers of clinical decision support content in Web 2.0. We believe the case for Web 2.0 as a tool for collaborating on clinical decision support content appears strong, particularly for collaborative content development within an organization.

Using evidence-based algorithms to improve clinical decision making: the case of a first-time anterior shoulder dislocation.

PubMed

Federer, Andrew E; Taylor, Dean C; Mather, Richard C

2013-09-01

Decision making in health care has evolved substantially over the last century. Up until the late 1970s, medical decision making was predominantly intuitive and anecdotal. It was based on trial and error and involved high levels of problem solving. The 1980s gave way to empirical medicine, which was evidence based probabilistic, and involved pattern recognition and less problem solving. Although this represented a major advance in the quality of medical decision making, limitations existed. The advantages of the gold standard of the randomized controlled clinical trial (RCT) are well-known and this technique is irreplaceable in its ability to answer critical clinical questions. However, the RCT does have drawbacks. RCTs are expensive and can only capture a snapshot in time. As treatments change and new technologies emerge, new expensive clinical trials must be undertaken to reevaluate them. Furthermore, in order to best evaluate a single intervention, other factors must be controlled. In addition, the study population may not match that of another organization or provider. Although evidence-based medicine has provided powerful data for clinicians, effectively and efficiently tailoring it to the individual has not yet evolved. We are now in a period of transition from this evidence-based era to one dominated by the personalization and customization of care. It will be fueled by policy decisions to shift financial responsibility to the patient, creating a powerful and sophisticated consumer, unlike any patient we have known before. The challenge will be to apply medical evidence and personal preferences to medical decisions and deliver it efficiently in the increasingly busy clinical setting. In this article, we provide a robust review of the concepts of customized care and some of techniques to deliver it. We will illustrate this through a personalized decision model for the treatment decision after a first-time anterior shoulder dislocation.

A practical guide to assessing clinical decision-making skills using the key features approach.

PubMed

Farmer, Elizabeth A; Page, Gordon

2005-12-01

This paper in the series on professional assessment provides a practical guide to writing key features problems (KFPs). Key features problems test clinical decision-making skills in written or computer-based formats. They are based on the concept of critical steps or 'key features' in decision making and represent an advance on the older, less reliable patient management problem (PMP) formats. The practical steps in writing these problems are discussed and illustrated by examples. Steps include assembling problem-writing groups, selecting a suitable clinical scenario or problem and defining its key features, writing the questions, selecting question response formats, preparing scoring keys, reviewing item quality and item banking. The KFP format provides educators with a flexible approach to testing clinical decision-making skills with demonstrated validity and reliability when constructed according to the guidelines provided.

Using Best Practices to Extract, Organize, and Reuse Embedded Decision Support Content Knowledge Rules from Mature Clinical Systems

PubMed Central

DesAutels, Spencer J.; Fox, Zachary E.; Giuse, Dario A.; Williams, Annette M.; Kou, Qing-hua; Weitkamp, Asli; Neal R, Patel; Bettinsoli Giuse, Nunzia

2016-01-01

Clinical decision support (CDS) knowledge, embedded over time in mature medical systems, presents an interesting and complex opportunity for information organization, maintenance, and reuse. To have a holistic view of all decision support requires an in-depth understanding of each clinical system as well as expert knowledge of the latest evidence. This approach to clinical decision support presents an opportunity to unify and externalize the knowledge within rules-based decision support. Driven by an institutional need to prioritize decision support content for migration to new clinical systems, the Center for Knowledge Management and Health Information Technology teams applied their unique expertise to extract content from individual systems, organize it through a single extensible schema, and present it for discovery and reuse through a newly created Clinical Support Knowledge Acquisition and Archival Tool (CS-KAAT). CS-KAAT can build and maintain the underlying knowledge infrastructure needed by clinical systems. PMID:28269846

Use of Decision Models in the Development of Evidence-Based Clinical Preventive Services Recommendations: Methods of the U.S. Preventive Services Task Force.

PubMed

Owens, Douglas K; Whitlock, Evelyn P; Henderson, Jillian; Pignone, Michael P; Krist, Alex H; Bibbins-Domingo, Kirsten; Curry, Susan J; Davidson, Karina W; Ebell, Mark; Gillman, Matthew W; Grossman, David C; Kemper, Alex R; Kurth, Ann E; Maciosek, Michael; Siu, Albert L; LeFevre, Michael L

2016-10-04

The U.S. Preventive Services Task Force (USPSTF) develops evidence-based recommendations about preventive care based on comprehensive systematic reviews of the best available evidence. Decision models provide a complementary, quantitative approach to support the USPSTF as it deliberates about the evidence and develops recommendations for clinical and policy use. This article describes the rationale for using modeling, an approach to selecting topics for modeling, and how modeling may inform recommendations about clinical preventive services. Decision modeling is useful when clinical questions remain about how to target an empirically established clinical preventive service at the individual or program level or when complex determinations of magnitude of net benefit, overall or among important subpopulations, are required. Before deciding whether to use decision modeling, the USPSTF assesses whether the benefits and harms of the preventive service have been established empirically, assesses whether there are key issues about applicability or implementation that modeling could address, and then defines the decision problem and key questions to address through modeling. Decision analyses conducted for the USPSTF are expected to follow best practices for modeling. For chosen topics, the USPSTF assesses the strengths and limitations of the systematically reviewed evidence and the modeling analyses and integrates the results of each to make preventive service recommendations.

Decision-making theories and their usefulness to the midwifery profession both in terms of midwifery practice and the education of midwives.

PubMed

Jefford, Elaine; Fahy, Kathleen; Sundin, Deborah

2011-06-01

What are the strengths and limitations of existing Decision-Making Theories as a basis for guiding best practice clinical decision-making within a framework of midwifery philosophy? Each theory is compared in relation with how well they provide a teachable framework for midwifery clinical reasoning that is consistent with midwifery philosophy. Hypothetico-Deductive Theory, from which medical clinical reasoning is based; intuitive decision-making; Dual Processing Theory; The International Confederation of Midwives Clinical Decision-Making Framework; Australian Nursing and Midwifery Council Midwifery Practice Decisions Flowchart and Midwifery Practice. Best practice midwifery clinical Decision-Making Theory needs to give guidance about: (i) effective use of cognitive reasoning processes; (ii) how to include contextual and emotional factors; (iii) how to include the interests of the baby as an integral part of the woman; (iv) decision-making in partnership with woman; and (v) how to recognize/respond to clinical situations outside the midwife's legal/personal scope of practice. No existing Decision-Making Theory meets the needs of midwifery. Medical clinical reasoning has a good contribution to make in terms of cognitive reasoning processes. Two limitations of medical clinical reasoning are its reductionistic focus and privileging of reason to the exclusion of emotional and contextual factors. Hypothetico-deductive clinical reasoning is a necessary but insufficient condition for best practice clinical decision-making in midwifery. © 2011 Blackwell Publishing Asia Pty Ltd.

Applicability of randomized trials in radiation oncology to standard clinical practice.

PubMed

Apisarnthanarax, Smith; Swisher-McClure, Samuel; Chiu, Wing K; Kimple, Randall J; Harris, Stephen L; Morris, David E; Tepper, Joel E

2013-08-15

Randomized controlled trials (RCTs) are commonly used to inform clinical practice; however, it is unclear how generalizable RCT data are to patients in routine clinical practice. The authors of this report assessed the availability and applicability of randomized evidence guiding medical decisions in a cohort of patients who were evaluated for consideration of definitive management in a radiation oncology clinic. The medical records of consecutive, new patient consultations between January and March 2007 were reviewed. Patient medical decisions were classified as those with (Group 1) or without (Group 2) available, relevant level I evidence (phase 3 RCT) supporting recommended treatments. Group 1 medical decisions were further divided into 3 groups based on the extent of fulfilling eligibility criteria for each RCT: Group 1A included decisions that fulfilled all eligibility criteria; Group 1B, decisions that did not fulfill at least 1 minor eligibility criteria; or Group 1C, decisions that did not fulfill at least 1 major eligibility criteria. Patient and clinical characteristics were tested for correlations with the availability of evidence. Of the 393 evaluable patients, malignancies of the breast (30%), head and neck (18%), and genitourinary system (14%) were the most common presenting primary disease sites. Forty-seven percent of all medical decisions (n = 451) were made without available (36%) or applicable (11%) randomized evidence to inform clinical decision making. Primary tumor diagnosis was significantly associated with the availability of evidence (P < .0001). A significant proportion of medical decisions in an academic radiation oncology clinic were made without available or applicable level I evidence, underscoring the limitations of relying solely on RCTs for the development of evidence-based health care. Copyright © 2013 American Cancer Society.

Data-driven decision support for radiologists: re-using the National Lung Screening Trial dataset for pulmonary nodule management.

PubMed

Morrison, James J; Hostetter, Jason; Wang, Kenneth; Siegel, Eliot L

2015-02-01

Real-time mining of large research trial datasets enables development of case-based clinical decision support tools. Several applicable research datasets exist including the National Lung Screening Trial (NLST), a dataset unparalleled in size and scope for studying population-based lung cancer screening. Using these data, a clinical decision support tool was developed which matches patient demographics and lung nodule characteristics to a cohort of similar patients. The NLST dataset was converted into Structured Query Language (SQL) tables hosted on a web server, and a web-based JavaScript application was developed which performs real-time queries. JavaScript is used for both the server-side and client-side language, allowing for rapid development of a robust client interface and server-side data layer. Real-time data mining of user-specified patient cohorts achieved a rapid return of cohort cancer statistics and lung nodule distribution information. This system demonstrates the potential of individualized real-time data mining using large high-quality clinical trial datasets to drive evidence-based clinical decision-making.

Reflections in the clinical practice.

PubMed

Borrell-Carrió, F; Hernández-Clemente, J C

2014-03-01

The purpose of this article is to analyze some models of expert decision and their impact on the clinical practice. We have analyzed decision-making considering the cognitive aspects (explanatory models, perceptual skills, analysis of the variability of a phenomenon, creating habits and inertia of reasoning and declarative models based on criteria). We have added the importance of emotions in decision making within highly complex situations, such as those occurring within the clinical practice. The quality of the reflective act depends, among other factors, on the ability of metacognition (thinking about what we think). Finally, we propose an educational strategy based on having a task supervisor and rectification scenarios to improve the quality of medical decision making. Copyright © 2013 Elsevier España, S.L. All rights reserved.

Science and intuition: do both have a place in clinical decision making?

PubMed

Pearson, Helen

Intuition is widely used in clinical decision making yet its use is underestimated compared to scientific decision-making methods. Information processing is used within scientific decision making and is methodical and analytical, whereas intuition relies more on a practitioner's perception. Intuition is an unconscious process and may be referred to as a 'sixth sense', 'hunch' or 'gut feeling'. It is not underpinned by valid and reliable measures. Expert health professionals use a rapid, automatic process to recognise familiar problems instantly. Intuition could therefore involve pattern recognition, where experts draw on experiences, so could be perceived as a cognitive skill rather than a perception or knowing without knowing how. The NHS places great importance on evidence-based practice but intuition is seemingly becoming an acceptable way of thinking and knowing in clinical decision making. Recognising nursing as an art allows intuition to be used and the environment or situation to be interpreted to help inform decision making. Intuition can be used in conjunction with evidence-based practice and to achieve good outcomes and deserves to be acknowledged within clinical practice.

How updating textual clinical practice guidelines impacts clinical decision support systems: a case study with bladder cancer management.

PubMed

Bouaud, Jacques; Séroussi, Brigitte; Brizon, Ambre; Culty, Thibault; Mentré, France; Ravery, Vincent

2007-01-01

Guideline-based clinical decision support systems (CDSSs) can be effective in increasing physician compliance with recommendations. However, the ever growing pace at which medical knowledge is produced requires that clinical practice guidelines (CPGs) be updated regularly. It is therefore mandatory that CDSSs be revised accordingly. The French Association for Urology publishes CPGs on bladder cancer management every 2 years. We studied the impact of the 2004 revision of these guidelines, with respect to the 2002 version with a CDSS, UroDoc. We proposed a typology of knowledge base modifications resulting from the update of CPGs making the difference between practice, clinical conditions and recommendations refinement as opposed to new practice and new recommendations. The number of formalized recommendations increased from 577 in 2002 to 1,081 in 2004. We evaluated the two versions of UroDoc on a randomized sample of patient records. A single new practice that modifies a decision taken in 49% of all recorded decisions leads to a fall from 67% to 46% of the compliance rate of decisions.

The normalization heuristic: an untested hypothesis that may misguide medical decisions.

PubMed

Aberegg, Scott K; O'Brien, James M

2009-06-01

Medical practice is increasingly informed by the evidence from randomized controlled trials. When such evidence is not available, clinical hypotheses based on pathophysiological reasoning and common sense guide clinical decision making. One commonly utilized general clinical hypothesis is the assumption that normalizing abnormal laboratory values and physiological parameters will lead to improved patient outcomes. We refer to the general use of this clinical hypothesis to guide medical therapeutics as the "normalization heuristic". In this paper, we operationally define this heuristic and discuss its limitations as a rule of thumb for clinical decision making. We review historical and contemporaneous examples of normalization practices as empirical evidence for the normalization heuristic and to highlight its frailty as a guide for clinical decision making.

The anatomy of decision support during inpatient care provider order entry (CPOE): Empirical observations from a decade of CPOE experience at Vanderbilt

PubMed Central

Miller, Randolph A.; Waitman, Lemuel R.; Chen, Sutin; Rosenbloom, S. Trent

2006-01-01

The authors describe a pragmatic approach to the introduction of clinical decision support at the point of care, based on a decade of experience in developing and evolving Vanderbilt’s inpatient “WizOrder” care provider order entry (CPOE) system. The inpatient care setting provides a unique opportunity to interject CPOE-based decision support features that restructure clinical workflows, deliver focused relevant educational materials, and influence how care is delivered to patients. From their empirical observations, the authors have developed a generic model for decision support within inpatient CPOE systems. They believe that the model’s utility extends beyond Vanderbilt, because it is based on characteristics of end-user workflows and on decision support considerations that are common to a variety of inpatient settings and CPOE systems. The specific approach to implementing a given clinical decision support feature within a CPOE system should involve evaluation along three axes: what type of intervention to create (for which the authors describe 4 general categories); when to introduce the intervention into the user’s workflow (for which the authors present 7 categories), and how disruptive, during use of the system, the intervention might be to end-users’ workflows (for which the authors describe 6 categories). Framing decision support in this manner may help both developers and clinical end-users plan future alterations to their systems when needs for new decision support features arise. PMID:16290243

Clinical intuition in the nursing process and decision-making-A mixed-studies review.

PubMed

Melin-Johansson, Christina; Palmqvist, Rebecca; Rönnberg, Linda

2017-12-01

To review what is characteristic of registered nurses' intuition in clinical settings, in relationships and in the nursing process. Intuition is a controversial concept and nurses believe that there are difficulties in how they should explain their nursing actions or decisions based on intuition. Much of the evidence from the body of research indicates that nurses value their intuition in a variety of clinical settings. More information on how nurses integrate intuition as a core element in daily clinical work would contribute to an improved understanding on how they go about this. Intuition deserves a place in evidence-based activities, where intuition is an important component associated with the nursing process. An integrative review strengthened with a mixed-studies review. Literature searches were conducted in the databases CINAHL, PubMed and PsycINFO, and literature published 1985-2016 were included. The findings in the studies were analysed with content analysis, and the synthesis process entailed a reasoning between the authors. After a quality assessment, 16 studies were included. The analysis and synthesis resulted in three categories. The characteristics of intuition in the nurse's daily clinical activities include application, assertiveness and experiences; in the relationships with patients' intuition include unique connections, mental and bodily responses, and personal qualities; and in the nursing process include support and guidance, component and clues in decision-making, and validating decisions. Intuition is more than simply a "gut feeling," and it is a process based on knowledge and care experience and has a place beside research-based evidence. Nurses integrate both analysis and synthesis of intuition alongside objective data when making decisions. They should rely on their intuition and use this knowledge in clinical practice as a support in decision-making, which increases the quality and safety of patient care. We find that intuition plays a key role in more or less all of the steps in the nursing process as a base for decision-making that supports safe patient care, and is a validated component of nursing clinical care expertise. © 2017 John Wiley & Sons Ltd.

How do small groups make decisions? : A theoretical framework to inform the implementation and study of clinical competency committees.

PubMed

Chahine, Saad; Cristancho, Sayra; Padgett, Jessica; Lingard, Lorelei

2017-06-01

In the competency-based medical education (CBME) approach, clinical competency committees are responsible for making decisions about trainees' competence. However, we currently lack a theoretical model for group decision-making to inform this emerging assessment phenomenon. This paper proposes an organizing framework to study and guide the decision-making processes of clinical competency committees.This is an explanatory, non-exhaustive review, tailored to identify relevant theoretical and evidence-based papers related to small group decision-making. The search was conducted using Google Scholar, Web of Science, MEDLINE, ERIC, and PsycINFO for relevant literature. Using a thematic analysis, two researchers (SC & JP) met four times between April-June 2016 to consolidate the literature included in this review.Three theoretical orientations towards group decision-making emerged from the review: schema, constructivist, and social influence. Schema orientations focus on how groups use algorithms for decision-making. Constructivist orientations focus on how groups construct their shared understanding. Social influence orientations focus on how individual members influence the group's perspective on a decision. Moderators of decision-making relevant to all orientations include: guidelines, stressors, authority, and leadership.Clinical competency committees are the mechanisms by which groups of clinicians will be in charge of interpreting multiple assessment data points and coming to a shared decision about trainee competence. The way in which these committees make decisions can have huge implications for trainee progression and, ultimately, patient care. Therefore, there is a pressing need to build the science of how such group decision-making works in practice. This synthesis suggests a preliminary organizing framework that can be used in the implementation and study of clinical competency committees.

Ethically-based clinical decision-making in physical therapy: process and issues.

PubMed

Finch, Elspeth; Geddes, E Lynne; Larin, Hélène

2005-01-01

The identification and consideration of relevant ethical issues in clinical decision-making, and the education of health care professionals (HCPs) in these skills are key factors in providing quality health care. This qualitative study explores the way in which physical therapists (PTs) integrate ethical issues into clinical practice decisions and identifies ethical themes used by PTs. A purposive sample of eight PTs was asked to describe a recent ethically-based clinical decision. Transcribed interviews were coded and themes identified related to the following categories: 1) the integration of ethical issues in the clinical decision-making process, 2) patient welfare, 3) professional ethos of the PT, and 4) health care economics and business practices. Participants readily described clinical situations involving ethical issues but rarely identified specific conflicting ethical issues in their description. Ethical dilemmas were more frequently resolved when there were fewer emotional sequelae associated with the dilemma, and the PT had a clear understanding of professional ethos, valued patient autonomy, and explored a variety of alternative actions before implementing one. HCP students need to develop a clear professional ethos and an increased understanding of the economic factors that will present ethical issues in practice.

Characteristics of knowledge content in a curated online evidence library.

PubMed

Varada, Sowmya; Lacson, Ronilda; Raja, Ali S; Ip, Ivan K; Schneider, Louise; Osterbur, David; Bain, Paul; Vetrano, Nicole; Cellini, Jacqueline; Mita, Carol; Coletti, Margaret; Whelan, Julia; Khorasani, Ramin

2018-05-01

To describe types of recommendations represented in a curated online evidence library, report on the quality of evidence-based recommendations pertaining to diagnostic imaging exams, and assess underlying knowledge representation. The evidence library is populated with clinical decision rules, professional society guidelines, and locally developed best practice guidelines. Individual recommendations were graded based on a standard methodology and compared using chi-square test. Strength of evidence ranged from grade 1 (systematic review) through grade 5 (recommendations based on expert opinion). Finally, variations in the underlying representation of these recommendations were identified. The library contains 546 individual imaging-related recommendations. Only 15% (16/106) of recommendations from clinical decision rules were grade 5 vs 83% (526/636) from professional society practice guidelines and local best practice guidelines that cited grade 5 studies (P < .0001). Minor head trauma, pulmonary embolism, and appendicitis were topic areas supported by the highest quality of evidence. Three main variations in underlying representations of recommendations were "single-decision," "branching," and "score-based." Most recommendations were grade 5, largely because studies to test and validate many recommendations were absent. Recommendation types vary in amount and complexity and, accordingly, the structure and syntax of statements they generate. However, they can be represented in single-decision, branching, and score-based representations. In a curated evidence library with graded imaging-based recommendations, evidence quality varied widely, with decision rules providing the highest-quality recommendations. The library may be helpful in highlighting evidence gaps, comparing recommendations from varied sources on similar clinical topics, and prioritizing imaging recommendations to inform clinical decision support implementation.

The Clinical Intuition Exploration Guide: A Decision-Making Tool for Counselors and Supervisors

ERIC Educational Resources Information Center

Jeffrey, Aaron

2012-01-01

Clinical intuition is a common experience among counselors, yet many do not know what to do with intuition when it occurs. This article reviews the role intuition plays in clinical work and presents the research-based Clinical Intuition Exploration Guide to help counselors navigate the decision-making process. The guide consists of self-reflection…

A predictive approach to selecting the size of a clinical trial, based on subjective clinical opinion.

PubMed

Spiegelhalter, D J; Freedman, L S

1986-01-01

The 'textbook' approach to determining sample size in a clinical trial has some fundamental weaknesses which we discuss. We describe a new predictive method which takes account of prior clinical opinion about the treatment difference. The method adopts the point of clinical equivalence (determined by interviewing the clinical participants) as the null hypothesis. Decision rules at the end of the study are based on whether the interval estimate of the treatment difference (classical or Bayesian) includes the null hypothesis. The prior distribution is used to predict the probabilities of making the decisions to use one or other treatment or to reserve final judgement. It is recommended that sample size be chosen to control the predicted probability of the last of these decisions. An example is given from a multi-centre trial of superficial bladder cancer.

Perceived Barriers and Facilitators of Using a Web-Based Interactive Decision Aid for Colorectal Cancer Screening in Community Practice Settings: Findings From Focus Groups With Primary Care Clinicians and Medical Office Staff

PubMed Central

2013-01-01

Background Information is lacking about the capacity of those working in community practice settings to utilize health information technology for colorectal cancer screening. Objective To address this gap we asked those working in community practice settings to share their perspectives about how the implementation of a Web-based patient-led decision aid might affect patient-clinician conversations about colorectal cancer screening and the day-to-day clinical workflow. Methods Five focus groups in five community practice settings were conducted with 8 physicians, 1 physician assistant, and 18 clinic staff. Focus groups were organized using a semistructured discussion guide designed to identify factors that mediate and impede the use of a Web-based decision aid intended to clarify patient preferences for colorectal cancer screening and to trigger shared decision making during the clinical encounter. Results All physicians, the physician assistant, and 8 of the 18 clinic staff were active participants in the focus groups. Clinician and staff participants from each setting reported a belief that the Web-based patient-led decision aid could be an informative and educational tool; in all but one setting participants reported a readiness to recommend the tool to patients. The exception related to clinicians from one clinic who described a preference for patients having fewer screening choices, noting that a colonoscopy was the preferred screening modality for patients in their clinic. Perceived barriers to utilizing the Web-based decision aid included patients’ lack of Internet access or low computer literacy, and potential impediments to the clinics’ daily workflow. Expanding patients’ use of an online decision aid that is both easy to access and understand and that is utilized by patients outside of the office visit was described as a potentially efficient means for soliciting patients’ screening preferences. Participants described that a system to link the online decision aid to a computerized reminder system could promote a better understanding of patients’ screening preferences, though some expressed concern that such a system could be difficult to keep up and running. Conclusions Community practice clinicians and staff perceived the Web-based decision aid technology as promising but raised questions as to how the technology and resultant information would be integrated into their daily practice workflow. Additional research investigating how to best implement online decision aids should be conducted prior to the widespread adoption of such technology so as to maximize the benefits of the technology while minimizing workflow disruptions. PMID:24351420

Shared decision-making – transferring research into practice: the Analytic Hierarchy Process (AHP)

PubMed Central

Dolan, James G.

2008-01-01

Objective To illustrate how the Analytic Hierarchy Process (AHP) can be used to promote shared decision-making and enhance clinician-patient communication. Methods Tutorial review. Results The AHP promotes shared decision making by creating a framework that is used to define the decision, summarize the information available, prioritize information needs, elicit preferences and values, and foster meaningful communication among decision stakeholders. Conclusions The AHP and related multi-criteria methods have the potential for improving the quality of clinical decisions and overcoming current barriers to implementing shared decision making in busy clinical settings. Further research is needed to determine the best way to implement these tools and to determine their effectiveness. Practice Implications Many clinical decisions involve preference-based trade-offs between competing risks and benefits. The AHP is a well-developed method that provides a practical approach for improving patient-provider communication, clinical decision-making, and the quality of patient care in these situations. PMID:18760559

Reducing Diagnostic Error with Computer-Based Clinical Decision Support

ERIC Educational Resources Information Center

Greenes, Robert A.

2009-01-01

Information technology approaches to delivering diagnostic clinical decision support (CDS) are the subject of the papers to follow in the proceedings. These will address the history of CDS and present day approaches (Miller), evaluation of diagnostic CDS methods (Friedman), and the role of clinical documentation in supporting diagnostic decision…

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…

Tools to Promote Shared Decision Making in Serious Illness: A Systematic Review.

PubMed

Austin, C Adrian; Mohottige, Dinushika; Sudore, Rebecca L; Smith, Alexander K; Hanson, Laura C

2015-07-01

Serious illness impairs function and threatens survival. Patients facing serious illness value shared decision making, yet few decision aids address the needs of this population. To perform a systematic review of evidence about decision aids and other exportable tools that promote shared decision making in serious illness, thereby (1) identifying tools relevant to the treatment decisions of seriously ill patients and their caregivers, (2) evaluating the quality of evidence for these tools, and (3) summarizing their effect on outcomes and accessibility for clinicians. We searched PubMed, CINAHL, and PsychInfo from January 1, 1995, through October 31, 2014, and identified additional studies from reference lists and other systematic reviews. Clinical trials with random or nonrandom controls were included if they tested print, video, or web-based tools for advance care planning (ACP) or decision aids for serious illness. We extracted data on the study population, design, results, and risk for bias using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) criteria. Each tool was evaluated for its effect on patient outcomes and accessibility. Seventeen randomized clinical trials tested decision tools in serious illness. Nearly all the trials were of moderate or high quality and showed that decision tools improve patient knowledge and awareness of treatment choices. The available tools address ACP, palliative care and goals of care communication, feeding options in dementia, lung transplant in cystic fibrosis, and truth telling in terminal cancer. Five randomized clinical trials provided further evidence that decision tools improve ACP documentation, clinical decisions, and treatment received. Clinicians can access and use evidence-based tools to engage seriously ill patients in shared decision making. This field of research is in an early stage; future research is needed to develop novel decision aids for other serious diagnoses and key decisions. Health care delivery organizations should prioritize the use of currently available tools that are evidence based and effective.

Lung Cancer Assistant: a hybrid clinical decision support application for lung cancer care.

PubMed

Sesen, M Berkan; Peake, Michael D; Banares-Alcantara, Rene; Tse, Donald; Kadir, Timor; Stanley, Roz; Gleeson, Fergus; Brady, Michael

2014-09-06

Multidisciplinary team (MDT) meetings are becoming the model of care for cancer patients worldwide. While MDTs have improved the quality of cancer care, the meetings impose substantial time pressure on the members, who generally attend several such MDTs. We describe Lung Cancer Assistant (LCA), a clinical decision support (CDS) prototype designed to assist the experts in the treatment selection decisions in the lung cancer MDTs. A novel feature of LCA is its ability to provide rule-based and probabilistic decision support within a single platform. The guideline-based CDS is based on clinical guideline rules, while the probabilistic CDS is based on a Bayesian network trained on the English Lung Cancer Audit Database (LUCADA). We assess rule-based and probabilistic recommendations based on their concordances with the treatments recorded in LUCADA. Our results reveal that the guideline rule-based recommendations perform well in simulating the recorded treatments with exact and partial concordance rates of 0.57 and 0.79, respectively. On the other hand, the exact and partial concordance rates achieved with probabilistic results are relatively poorer with 0.27 and 0.76. However, probabilistic decision support fulfils a complementary role in providing accurate survival estimations. Compared to recorded treatments, both CDS approaches promote higher resection rates and multimodality treatments.

Utility of bleb imaging with anterior segment optical coherence tomography in clinical decision-making after trabeculectomy.

PubMed

Singh, Mandeep; Aung, Tin; Aquino, Maria C; Chew, Paul T K

2009-08-01

To determine if imaging of blebs with anterior segment optical coherence tomography (ASOCT) affects clinical decision-making with regard to laser suture lysis (LSL) after trabeculectomy. In this prospective observational case series, we included patients with poorly controlled intraocular pressure (IOP) after standardized trabeculectomy from May to November 2006. One observer assessed IOP, anterior chamber depth and bleb formation, and recorded a decision of whether or not to undertake LSL based on clinical grounds. A second observer masked to clinical data recorded a decision of whether or not to perform LSL based on ASOCT assessment of scleral flap position, presence of a sub-flap space, patency of the internal ostium, and bleb wall thickening. We compared the 2 observers' decisions to determine how ASOCT influenced decision-making. Seven eyes of 7 patients were included. On the basis of clinical examination, LSL was recommended in all 7 (100.0%) cases due to presence of elevated IOP, deep anterior chambers and poorly formed blebs. Using ASOCT, LSL was recommended in 5/7 (71.4%) cases with apposed scleral flaps, absent sub-flap spaces, and absent bleb wall thickening. In 2/7 (28.7%) cases, LSL was not recommended based on ASOCT findings of an elevated scleral flap, a patent sub-flap space, and bleb wall thickening. All 7 patients had good IOP control and formed blebs at a mean of 8.4+/-2.6 months after trabeculectomy, with a mean IOP of 14.3+/-3.2 mm Hg with no medications. This small study suggests that ASOCT imaging may affect decision-making with regard to LSL by providing information not apparent on clinical examination.

Bayesian Decision Support for Adaptive Lung Treatments

NASA Astrophysics Data System (ADS)

McShan, Daniel; Luo, Yi; Schipper, Matt; TenHaken, Randall

2014-03-01

Purpose: A Bayesian Decision Network will be demonstrated to provide clinical decision support for adaptive lung response-driven treatment management based on evidence that physiologic metrics may correlate better with individual patient response than traditional (population-based) dose and volume-based metrics. Further, there is evidence that information obtained during the course of radiation therapy may further improve response predictions. Methods: Clinical factors were gathered for 58 patients including planned mean lung dose, and the bio-markers IL-8 and TGF-β1 obtained prior to treatment and two weeks into treatment along with complication outcomes for these patients. A Bayesian Decision Network was constructed using Netica 5.0.2 from Norsys linking these clinical factors to obtain a prediction of radiation induced lung disese (RILD) complication. A decision node was added to the network to provide a plan adaption recommendation based on the trade-off between the RILD prediction and complexity of replanning. A utility node provides the weighting cost between the competing factors. Results: The decision node predictions were optimized against the data for the 58 cases. With this decision network solution, one can consider the decision result for a new patient with specific findings to obtain a recommendation to adaptively modify the originally planned treatment course. Conclusions: A Bayesian approach allows handling and propagating probabilistic data in a logical and principled manner. Decision networks provide the further ability to provide utility-based trade-offs, reflecting non-medical but practical cost/benefit analysis. The network demonstrated illustrates the basic concept, but many other factors may affect these decisions and work on building better models are being designed and tested. Acknowledgement: Supported by NIH-P01-CA59827

Free and open source enabling technologies for patient-centric, guideline-based clinical decision support: a survey.

PubMed

Leong, T Y; Kaiser, K; Miksch, S

2007-01-01

Guideline-based clinical decision support is an emerging paradigm to help reduce error, lower cost, and improve quality in evidence-based medicine. The free and open source (FOS) approach is a promising alternative for delivering cost-effective information technology (IT) solutions in health care. In this paper, we survey the current FOS enabling technologies for patient-centric, guideline-based care, and discuss the current trends and future directions of their role in clinical decision support. We searched PubMed, major biomedical informatics websites, and the web in general for papers and links related to FOS health care IT systems. We also relied on our background and knowledge for specific subtopics. We focused on the functionalities of guideline modeling tools, and briefly examined the supporting technologies for terminology, data exchange and electronic health record (EHR) standards. To effectively support patient-centric, guideline-based care, the computerized guidelines and protocols need to be integrated with existing clinical information systems or EHRs. Technologies that enable such integration should be accessible, interoperable, and scalable. A plethora of FOS tools and techniques for supporting different knowledge management and quality assurance tasks involved are available. Many challenges, however, remain in their implementation. There are active and growing trends of deploying FOS enabling technologies for integrating clinical guidelines, protocols, and pathways into the main care processes. The continuing development and maturation of such technologies are likely to make increasingly significant contributions to patient-centric, guideline-based clinical decision support.

Patient-oriented Computerized Clinical Guidelines for Mobile Decision Support in Gestational Diabetes.

PubMed

García-Sáez, Gema; Rigla, Mercedes; Martínez-Sarriegui, Iñaki; Shalom, Erez; Peleg, Mor; Broens, Tom; Pons, Belén; Caballero-Ruíz, Estefanía; Gómez, Enrique J; Hernando, M Elena

2014-03-01

The risks associated with gestational diabetes (GD) can be reduced with an active treatment able to improve glycemic control. Advances in mobile health can provide new patient-centric models for GD to create personalized health care services, increase patient independence and improve patients' self-management capabilities, and potentially improve their treatment compliance. In these models, decision-support functions play an essential role. The telemedicine system MobiGuide provides personalized medical decision support for GD patients that is based on computerized clinical guidelines and adapted to a mobile environment. The patient's access to the system is supported by a smartphone-based application that enhances the efficiency and ease of use of the system. We formalized the GD guideline into a computer-interpretable guideline (CIG). We identified several workflows that provide decision-support functionalities to patients and 4 types of personalized advice to be delivered through a mobile application at home, which is a preliminary step to providing decision-support tools in a telemedicine system: (1) therapy, to help patients to comply with medical prescriptions; (2) monitoring, to help patients to comply with monitoring instructions; (3) clinical assessment, to inform patients about their health conditions; and (4) upcoming events, to deal with patients' personal context or special events. The whole process to specify patient-oriented decision support functionalities ensures that it is based on the knowledge contained in the GD clinical guideline and thus follows evidence-based recommendations but at the same time is patient-oriented, which could enhance clinical outcomes and patients' acceptance of the whole system. © 2014 Diabetes Technology Society.

Certainty, leaps of faith, and tradition: rethinking clinical interventions.

PubMed

Dzurec, L C

1998-12-01

Clinical decision making requires that clinicians think quickly and in ways that will foster optimal, safe client care. Tradition influences clinical decision making, enhancing efficiency of resulting nursing action; however, since many decisions must be based on data that are either uncertain, incomplete, or indirect, clinicians are readily ensnared in processes involving potentially faulty logic associated with tradition. The author addresses the tenacity of tradition and then focuses on three processes--consensus formation, the grounding of certainty in inductive reasoning, and affirming the consequent--that have affected clinical decision making. For some recipients of care, tradition has had a substantial and invalid influence on their ability to access care.

Clinical decision-making by midwives: managing case complexity.

PubMed

Cioffi, J; Markham, R

1997-02-01

In making clinical judgements, it is argued that midwives use 'shortcuts' or heuristics based on estimated probabilities to simplify the decision-making task. Midwives (n = 30) were given simulated patient assessment situations of high and low complexity and were required to think aloud. Analysis of verbal protocols showed that subjective probability judgements (heuristics) were used more frequently in the high than low complexity case and predominated in the last quarter of the assessment period for the high complexity case. 'Representativeness' was identified more frequently in the high than in the low case, but was the dominant heuristic in both. Reports completed after each simulation suggest that heuristics based on memory for particular conditions affect decisions. It is concluded that midwives use heuristics, derived mainly from their clinical experiences, in an attempt to save cognitive effort and to facilitate reasonably accurate decisions in the decision-making process.

Improving Emergency Department Triage Classification with Computerized Clinical Decision Support at a Pediatric Hospital

ERIC Educational Resources Information Center

Kunisch, Joseph Martin

2012-01-01

Background: The Emergency Severity Index (ESI) is an emergency department (ED) triage classification system based on estimated patient-specific resource utilization. Rules for a computerized clinical decision support (CDS) system based on a patient's chief complaint were developed and tested using a stochastic model for predicting ESI scores.…

Evidence-based clinical practice, [corrected] evidence-based medicine and the Cochrane collaboration.

PubMed

Gambrill, E

1999-03-01

Encouraging professionals in training and later to consider practice-related research findings when making important clinical decisions is an on-going concern. Evidenced-Based Medicine (EBM) and the Cochrane Collaboration (CC) provide a source of tools and ideas for doing so, as well as a roster of colleagues who share this interest. Evidenced-based medicine involves integrating clinical expertise with the best available external evidence from systematic research as well as considering the values and expectations of patients/clients. Advantage can be taken of educational formats developed in EBM, such as problem-based learning and critical-appraisal workshops in which participants learn how to ask key answerable questions related to important clinical practice questions (e.g., regarding effectiveness, accuracy of assessment measures, prediction, prevention, and quality of clinical practice guidelines) and to access and critically appraise related research. The Cochrane Collaboration is a world-wide network of centers that prepare, maintain, and disseminate high-quality systematic reviews on the efficacy of healthcare. These databases allow access to evidence related to clinical practice decisions. Forging reciprocal working relationships with those involved in EBM reciprocal and the CC should contribute to the pursuit of shared goals such as basing clinical decisions on the best-available evidence and involving clients as informed consumers.

Disciplined Decision Making in an Interdisciplinary Environment: Some Implications for Clinical Applications of Statistical Process Control.

ERIC Educational Resources Information Center

Hantula, Donald A.

1995-01-01

Clinical applications of statistical process control (SPC) in human service organizations are considered. SPC is seen as providing a standard set of criteria that serves as a common interface for data-based decision making, which may bring decision making under the control of established contingencies rather than the immediate contingencies of…

Developing genomic knowledge bases and databases to support clinical management: current perspectives.

PubMed

Huser, Vojtech; Sincan, Murat; Cimino, James J

2014-01-01

Personalized medicine, the ability to tailor diagnostic and treatment decisions for individual patients, is seen as the evolution of modern medicine. We characterize here the informatics resources available today or envisioned in the near future that can support clinical interpretation of genomic test results. We assume a clinical sequencing scenario (germline whole-exome sequencing) in which a clinical specialist, such as an endocrinologist, needs to tailor patient management decisions within his or her specialty (targeted findings) but relies on a genetic counselor to interpret off-target incidental findings. We characterize the genomic input data and list various types of knowledge bases that provide genomic knowledge for generating clinical decision support. We highlight the need for patient-level databases with detailed lifelong phenotype content in addition to genotype data and provide a list of recommendations for personalized medicine knowledge bases and databases. We conclude that no single knowledge base can currently support all aspects of personalized recommendations and that consolidation of several current resources into larger, more dynamic and collaborative knowledge bases may offer a future path forward.

Developing genomic knowledge bases and databases to support clinical management: current perspectives

PubMed Central

Huser, Vojtech; Sincan, Murat; Cimino, James J

2014-01-01

Personalized medicine, the ability to tailor diagnostic and treatment decisions for individual patients, is seen as the evolution of modern medicine. We characterize here the informatics resources available today or envisioned in the near future that can support clinical interpretation of genomic test results. We assume a clinical sequencing scenario (germline whole-exome sequencing) in which a clinical specialist, such as an endocrinologist, needs to tailor patient management decisions within his or her specialty (targeted findings) but relies on a genetic counselor to interpret off-target incidental findings. We characterize the genomic input data and list various types of knowledge bases that provide genomic knowledge for generating clinical decision support. We highlight the need for patient-level databases with detailed lifelong phenotype content in addition to genotype data and provide a list of recommendations for personalized medicine knowledge bases and databases. We conclude that no single knowledge base can currently support all aspects of personalized recommendations and that consolidation of several current resources into larger, more dynamic and collaborative knowledge bases may offer a future path forward. PMID:25276091

Mixture-based gatekeeping procedures in adaptive clinical trials.

PubMed

Kordzakhia, George; Dmitrienko, Alex; Ishida, Eiji

2018-01-01

Clinical trials with data-driven decision rules often pursue multiple clinical objectives such as the evaluation of several endpoints or several doses of an experimental treatment. These complex analysis strategies give rise to "multivariate" multiplicity problems with several components or sources of multiplicity. A general framework for defining gatekeeping procedures in clinical trials with adaptive multistage designs is proposed in this paper. The mixture method is applied to build a gatekeeping procedure at each stage and inferences at each decision point (interim or final analysis) are performed using the combination function approach. An advantage of utilizing the mixture method is that it enables powerful gatekeeping procedures applicable to a broad class of settings with complex logical relationships among the hypotheses of interest. Further, the combination function approach supports flexible data-driven decisions such as a decision to increase the sample size or remove a treatment arm. The paper concludes with a clinical trial example that illustrates the methodology by applying it to develop an adaptive two-stage design with a mixture-based gatekeeping procedure.

Health professionals' decision-making in wound management: a grounded theory.

PubMed

Gillespie, Brigid M; Chaboyer, Wendy; St John, Winsome; Morley, Nicola; Nieuwenhoven, Paul

2015-06-01

To develop a conceptual understanding of the decision-making processes used by healthcare professionals in wound care practice. With the global move towards using an evidence-base in standardizing wound care practices and the need to reduce hospital wound care costs, it is important to understand health professionals' decision-making in this important yet under-researched area. A grounded theory approach was used to explore clinical decision-making of healthcare professionals in wound care practice. Interviews were conducted with 20 multi-disciplinary participants from nursing, surgery, infection control and wound care who worked at a metropolitan hospital in Australia. Data were collected during 2012-2013. Constant comparative analysis underpinned by Strauss and Corbin's framework was used to identify clinical decision-making processes. The core category was 'balancing practice-based knowledge with evidence-based knowledge'. Participants' clinical practice and actions embedded the following processes: 'utilizing the best available information', 'using a consistent approach in wound assessment' and 'using a multidisciplinary approach'. The substantive theory explains how practice and evidence knowledge was balanced and the variation in use of intuitive practice-based knowledge versus evidence-based knowledge. Participants considered patients' needs and preferences, costs, outcomes, technologies, others' expertise and established practices. Participants' decision-making tended to be more heavily weighted towards intuitive practice-based processes. These findings offer a better understanding of the processes used by health professionals' in their decision-making in wound care. Such an understanding may inform the development of evidence-based interventions that lead to better patient outcomes. © 2014 John Wiley & Sons Ltd.

Digital technology and clinical decision making in depression treatment: Current findings and future opportunities.

PubMed

Hallgren, Kevin A; Bauer, Amy M; Atkins, David C

2017-06-01

Clinical decision making encompasses a broad set of processes that contribute to the effectiveness of depression treatments. There is emerging interest in using digital technologies to support effective and efficient clinical decision making. In this paper, we provide "snapshots" of research and current directions on ways that digital technologies can support clinical decision making in depression treatment. Practical facets of clinical decision making are reviewed, then research, design, and implementation opportunities where technology can potentially enhance clinical decision making are outlined. Discussions of these opportunities are organized around three established movements designed to enhance clinical decision making for depression treatment, including measurement-based care, integrated care, and personalized medicine. Research, design, and implementation efforts may support clinical decision making for depression by (1) improving tools to incorporate depression symptom data into existing electronic health record systems, (2) enhancing measurement of treatment fidelity and treatment processes, (3) harnessing smartphone and biosensor data to inform clinical decision making, (4) enhancing tools that support communication and care coordination between patients and providers and within provider teams, and (5) leveraging treatment and outcome data from electronic health record systems to support personalized depression treatment. The current climate of rapid changes in both healthcare and digital technologies facilitates an urgent need for research, design, and implementation of digital technologies that explicitly support clinical decision making. Ensuring that such tools are efficient, effective, and usable in frontline treatment settings will be essential for their success and will require engagement of stakeholders from multiple domains. © 2017 Wiley Periodicals, Inc.

Neighborhood graph and learning discriminative distance functions for clinical decision support.

PubMed

Tsymbal, Alexey; Zhou, Shaohua Kevin; Huber, Martin

2009-01-01

There are two essential reasons for the slow progress in the acceptance of clinical case retrieval and similarity search-based decision support systems; the especial complexity of clinical data making it difficult to define a meaningful and effective distance function on them and the lack of transparency and explanation ability in many existing clinical case retrieval decision support systems. In this paper, we try to address these two problems by introducing a novel technique for visualizing inter-patient similarity based on a node-link representation with neighborhood graphs and by considering two techniques for learning discriminative distance function that help to combine the power of strong "black box" learners with the transparency of case retrieval and nearest neighbor classification.

Decision-Making in Audiology: Balancing Evidence-Based Practice and Patient-Centered Care.

PubMed

Boisvert, Isabelle; Clemesha, Jennifer; Lundmark, Erik; Crome, Erica; Barr, Caitlin; McMahon, Catherine M

2017-01-01

Health-care service delivery models have evolved from a practitioner-centered approach toward a patient-centered ideal. Concurrently, increasing emphasis has been placed on the use of empirical evidence in decision-making to increase clinical accountability. The way in which clinicians use empirical evidence and client preferences to inform decision-making provides an insight into health-care delivery models utilized in clinical practice. The present study aimed to investigate the sources of information audiologists use when discussing rehabilitation choices with clients, and discuss the findings within the context of evidence-based practice and patient-centered care. To assess the changes that may have occurred over time, this study uses a questionnaire based on one of the few studies of decision-making behavior in audiologists, published in 1989. The present questionnaire was completed by 96 audiologists who attended the World Congress of Audiology in 2014. The responses were analyzed using qualitative and quantitative approaches. Results suggest that audiologists rank clinical test results and client preferences as the most important factors for decision-making. Discussion with colleagues or experts was also frequently reported as an important source influencing decision-making. Approximately 20% of audiologists mentioned utilizing research evidence to inform decision-making when no clear solution was available. Information shared at conferences was ranked low in terms of importance and reliability. This study highlights an increase in awareness of concepts associated with evidence-based practice and patient-centered care within audiology settings, consistent with current research-to-practice dissemination pathways. It also highlights that these pathways may not be sufficient for an effective clinical implementation of these practices.

Cancer patient decision making related to clinical trial participation: an integrative review with implications for patients' relational autonomy.

PubMed

Bell, Jennifer A H; Balneaves, Lynda G

2015-04-01

Oncology clinical trials are necessary for the improvement of patient care as they have the ability to confirm the efficacy and safety of novel cancer treatments and in so doing, contribute to a solid evidence base on which practitioners and patients can make informed treatment decisions. However, only 3-5 % of adult cancer patients enroll in clinical trials. Lack of participation compromises the success of clinical trials and squanders an opportunity for improving patient outcomes. This literature review summarizes the factors and contexts that influence cancer patient decision making related to clinical trial participation. An integrative review was undertaken within PubMed, CINAHL, and EMBASE databases for articles written between 1995 and 2012 and archived under relevant keywords. Articles selected were data-based, written in English, and limited to adult cancer patients. In the 51 articles reviewed, three main types of factors were identified that influence cancer patients' decision making about participation in clinical trials: personal, social, and system factors. Subthemes included patients' trust in their physician and the research process, undue influence within the patient-physician relationship, and systemic social inequalities. How these factors interact and influence patients' decision-making process and relational autonomy, however, is insufficiently understood. Future research is needed to further elucidate the sociopolitical barriers and facilitators of clinical trial participation and to enhance ethical practice within clinical trial enrolment. This research will inform targeted education and support interventions to foster patients' relational autonomy in the decision-making process and potentially improve clinical trial participation rates.

How shrinks think: decision making in psychiatry.

PubMed

Bhugra, Dinesh; Malliaris, Yanni; Gupta, Susham

2010-10-01

Psychiatrists use biopsychosocial models in identifying aetiological factors in assessing their patients and similar approaches in planning management. Models in decision making will be influenced by previous experience, training, age and gender, among other factors. Critical thinking and evidence base are both important components in the process of reaching clinical decisions. Expected outcome of treatment may be another factor. The way we think influences our decision making, clinical or otherwise. With patients expecting and taking larger roles in their own management, there needs to be a shift towards patient-centred care in decision making. Further exploration in how clinical decisions are made by psychiatrists is necessary. An understanding of the manner in which therapeutic alliances are formed between the clinician and the patient is necessary to understand decision making.

What can paper-based clinical information systems tell us about the design of computerized clinical information systems (CIS) in the ICU?

PubMed

Miller, A; Pilcher, D; Mercaldo, N; Leong, T; Scheinkestel, C; Schildcrout, J

2010-08-01

Screen designs in computerized clinical information systems (CIS) have been modeled on their paper predecessors. However, limited understanding about how paper forms support clinical work means that we risk repeating old mistakes and creating new opportunities for error and inefficiency as illustrated by problems associated with computerized provider order entry systems. This study was designed to elucidate principles underlying a successful ICU paper-based CIS. The research was guided by two exploratory hypotheses: (1) paper-based artefacts (charts, notes, equipment, order forms) are used differently by nurses, doctors and other healthcare professionals in different (formal and informal) conversation contexts and (2) different artefacts support different decision processes that are distributed across role-based conversations. All conversations undertaken at the bedsides of five patients were recorded with any supporting artefacts for five days per patient. Data was coded according to conversational role-holders, clinical decision process, conversational context and artefacts. 2133 data points were analyzed using Poisson logistic regression analyses. Results show significant interactions between artefacts used during different professional conversations in different contexts (chi(2)((df=16))=55.8, p<0.0001). The interaction between artefacts used during different professional conversations for different clinical decision processes was not statistically significant although all two-way interactions were statistically significant. Paper-based CIS have evolved to support complex interdisciplinary decision processes. The translation of two design principles - support interdisciplinary perspectives and integrate decision processes - from paper to computerized CIS may minimize the risks associated with computerization. 2010 Australian College of Critical Care Nurses Ltd. Published by Elsevier Ltd. All rights reserved.

Pharmacogenomic knowledge representation, reasoning and genome-based clinical decision support based on OWL 2 DL ontologies.

PubMed

Samwald, Matthias; Miñarro Giménez, Jose Antonio; Boyce, Richard D; Freimuth, Robert R; Adlassnig, Klaus-Peter; Dumontier, Michel

2015-02-22

Every year, hundreds of thousands of patients experience treatment failure or adverse drug reactions (ADRs), many of which could be prevented by pharmacogenomic testing. However, the primary knowledge needed for clinical pharmacogenomics is currently dispersed over disparate data structures and captured in unstructured or semi-structured formalizations. This is a source of potential ambiguity and complexity, making it difficult to create reliable information technology systems for enabling clinical pharmacogenomics. We developed Web Ontology Language (OWL) ontologies and automated reasoning methodologies to meet the following goals: 1) provide a simple and concise formalism for representing pharmacogenomic knowledge, 2) finde errors and insufficient definitions in pharmacogenomic knowledge bases, 3) automatically assign alleles and phenotypes to patients, 4) match patients to clinically appropriate pharmacogenomic guidelines and clinical decision support messages and 5) facilitate the detection of inconsistencies and overlaps between pharmacogenomic treatment guidelines from different sources. We evaluated different reasoning systems and test our approach with a large collection of publicly available genetic profiles. Our methodology proved to be a novel and useful choice for representing, analyzing and using pharmacogenomic data. The Genomic Clinical Decision Support (Genomic CDS) ontology represents 336 SNPs with 707 variants; 665 haplotypes related to 43 genes; 22 rules related to drug-response phenotypes; and 308 clinical decision support rules. OWL reasoning identified CDS rules with overlapping target populations but differing treatment recommendations. Only a modest number of clinical decision support rules were triggered for a collection of 943 public genetic profiles. We found significant performance differences across available OWL reasoners. The ontology-based framework we developed can be used to represent, organize and reason over the growing wealth of pharmacogenomic knowledge, as well as to identify errors, inconsistencies and insufficient definitions in source data sets or individual patient data. Our study highlights both advantages and potential practical issues with such an ontology-based approach.

Evidence-based dentistry: fundamentals for the dentist.

PubMed

Bauer, Janet; Chiappelli, Francesco; Spackman, Sue; Prolo, Paolo; Stevenson, Richard

2006-06-01

This article explains the fundamentals of evidence-based dentistry for the dentist. Evidence-based dentistry is a discipline whose primary participant is the translational researcher. Recent developments have emphasized the importance of this discipline (clinical and translational research) for improving health care. The process of evidence-based dentistry is the reciprocation of new and existing evidence between dentists and quantitative and qualitative researchers, facilitated by the translational researcher. The product of this reciprocation is the clinical practice guideline, or best evidence, that provides the patient options in choosing treatments or services. These options are quantified and qualified by decision, utility, and cost data. Using shared decision-making, the dentist and patient arrive at a mutual understanding of which option best meets an acceptable and preferred treatment course that is cost effective. This option becomes the clinical decision.

A pilot study of distributed knowledge management and clinical decision support in the cloud.

PubMed

Dixon, Brian E; Simonaitis, Linas; Goldberg, Howard S; Paterno, Marilyn D; Schaeffer, Molly; Hongsermeier, Tonya; Wright, Adam; Middleton, Blackford

2013-09-01

Implement and perform pilot testing of web-based clinical decision support services using a novel framework for creating and managing clinical knowledge in a distributed fashion using the cloud. The pilot sought to (1) develop and test connectivity to an external clinical decision support (CDS) service, (2) assess the exchange of data to and knowledge from the external CDS service, and (3) capture lessons to guide expansion to more practice sites and users. The Clinical Decision Support Consortium created a repository of shared CDS knowledge for managing hypertension, diabetes, and coronary artery disease in a community cloud hosted by Partners HealthCare. A limited data set for primary care patients at a separate health system was securely transmitted to a CDS rules engine hosted in the cloud. Preventive care reminders triggered by the limited data set were returned for display to clinician end users for review and display. During a pilot study, we (1) monitored connectivity and system performance, (2) studied the exchange of data and decision support reminders between the two health systems, and (3) captured lessons. During the six month pilot study, there were 1339 patient encounters in which information was successfully exchanged. Preventive care reminders were displayed during 57% of patient visits, most often reminding physicians to monitor blood pressure for hypertensive patients (29%) and order eye exams for patients with diabetes (28%). Lessons learned were grouped into five themes: performance, governance, semantic interoperability, ongoing adjustments, and usability. Remote, asynchronous cloud-based decision support performed reasonably well, although issues concerning governance, semantic interoperability, and usability remain key challenges for successful adoption and use of cloud-based CDS that will require collaboration between biomedical informatics and computer science disciplines. Decision support in the cloud is feasible and may be a reasonable path toward achieving better support of clinical decision-making across the widest range of health care providers. Published by Elsevier B.V.

A service oriented approach for guidelines-based clinical decision support using BPMN.

PubMed

Rodriguez-Loya, Salvador; Aziz, Ayesha; Chatwin, Chris

2014-01-01

Evidence-based medical practice requires that clinical guidelines need to be documented in such a way that they represent a clinical workflow in its most accessible form. In order to optimize clinical processes to improve clinical outcomes, we propose a Service Oriented Architecture (SOA) based approach for implementing clinical guidelines that can be accessed from an Electronic Health Record (EHR) application with a Web Services enabled communication mechanism with the Enterprise Service Bus. We have used Business Process Modelling Notation (BPMN) for modelling and presenting the clinical pathway in the form of a workflow. The aim of this study is to produce spontaneous alerts in the healthcare workflow in the diagnosis of Chronic Obstructive Pulmonary Disease (COPD). The use of BPMN as a tool to automate clinical guidelines has not been previously employed for providing Clinical Decision Support (CDS).

An analysis of nursing students' decision-making in teams during simulations of acute patient deterioration.

PubMed

Bucknall, Tracey K; Forbes, Helen; Phillips, Nicole M; Hewitt, Nicky A; Cooper, Simon; Bogossian, Fiona

2016-10-01

The aim of this study was to examine the decision-making of nursing students during team based simulations on patient deterioration to determine the sources of information, the types of decisions made and the influences underpinning their decisions. Missed, misinterpreted or mismanaged physiological signs of deterioration in hospitalized patients lead to costly serious adverse events. Not surprisingly, an increased focus on clinical education and graduate nurse work readiness has resulted. A descriptive exploratory design. Clinical simulation laboratories in three Australian universities were used to run team based simulations with a patient actor. A convenience sample of 97 final-year nursing students completed simulations, with three students forming a team. Four teams from each university were randomly selected for detailed analysis. Cued recall during video review of team based simulation exercises to elicit descriptions of individual and team based decision-making and reflections on performance were audio-recorded post simulation (2012) and transcribed. Students recalled 11 types of decisions, including: information seeking; patient assessment; diagnostic; intervention/treatment; evaluation; escalation; prediction; planning; collaboration; communication and reflective. Patient distress, uncertainty and a lack of knowledge were frequently recalled influences on decisions. Incomplete information, premature diagnosis and a failure to consider alternatives when caring for patients is likely to lead to poor quality decisions. All health professionals have a responsibility in recognizing and responding to clinical deterioration within their scope of practice. A typology of nursing students' decision-making in teams, in this context, highlights the importance of individual knowledge, leadership and communication. © 2016 John Wiley & Sons Ltd.

Launching a virtual decision lab: development and field-testing of a web-based patient decision support research platform.

PubMed

Hoffman, Aubri S; Llewellyn-Thomas, Hilary A; Tosteson, Anna N A; O'Connor, Annette M; Volk, Robert J; Tomek, Ivan M; Andrews, Steven B; Bartels, Stephen J

2014-12-12

Over 100 trials show that patient decision aids effectively improve patients' information comprehension and values-based decision making. However, gaps remain in our understanding of several fundamental and applied questions, particularly related to the design of interactive, personalized decision aids. This paper describes an interdisciplinary development process for, and early field testing of, a web-based patient decision support research platform, or virtual decision lab, to address these questions. An interdisciplinary stakeholder panel designed the web-based research platform with three components: a) an introduction to shared decision making, b) a web-based patient decision aid, and c) interactive data collection items. Iterative focus groups provided feedback on paper drafts and online prototypes. A field test assessed a) feasibility for using the research platform, in terms of recruitment, usage, and acceptability; and b) feasibility of using the web-based decision aid component, compared to performance of a videobooklet decision aid in clinical care. This interdisciplinary, theory-based, patient-centered design approach produced a prototype for field-testing in six months. Participants (n = 126) reported that: the decision aid component was easy to use (98%), information was clear (90%), the length was appropriate (100%), it was appropriately detailed (90%), and it held their interest (97%). They spent a mean of 36 minutes using the decision aid and 100% preferred using their home/library computer. Participants scored a mean of 75% correct on the Decision Quality, Knowledge Subscale, and 74 out of 100 on the Preparation for Decision Making Scale. Completing the web-based decision aid reduced mean Decisional Conflict scores from 31.1 to 19.5 (p < 0.01). Combining decision science and health informatics approaches facilitated rapid development of a web-based patient decision support research platform that was feasible for use in research studies in terms of recruitment, acceptability, and usage. Within this platform, the web-based decision aid component performed comparably with the videobooklet decision aid used in clinical practice. Future studies may use this interactive research platform to study patients' decision making processes in real-time, explore interdisciplinary approaches to designing web-based decision aids, and test strategies for tailoring decision support to meet patients' needs and preferences.

Clinical reasoning and population health: decision making for an emerging paradigm of health care.

PubMed

Edwards, Ian; Richardson, Barbara

2008-01-01

Chronic conditions now provide the major disease and disability burden facing humanity. This development has necessitated a reorientation in the practice skills of health care professions away from hospital-based inpatient and outpatient care toward community-based management of patients with chronic conditions. Part of this reorientation toward community-based management of chronic conditions involves practitioners' understanding and adoption of a concept of population health management based on appropriate theoretical models of health care. Drawing on recent studies of expertise in physiotherapy, this article proposes a clinical reasoning and decision-making framework to meet these challenges. The challenge of population and community-based management of chronic conditions also provides an opportunity for physiotherapists to further clarify a professional epistemology of practice that embraces the kinds of knowledge and clinical reasoning processes used in physiotherapy practice. Three case studies related to the management of chronic musculoskeletal pain in different populations are used to exemplify the range of epistemological perspectives that underpin community-based practice. They illustrate the link between conceptualizations of practice problems and knowledge sources that are used as a basis for clinical reasoning and decision making as practitioners are increasingly required to move between the clinic and the community.

When to trust our learners? Clinical teachers' perceptions of decision variables in the entrustment process.

PubMed

Duijn, Chantal C M A; Welink, Lisanne S; Bok, Harold G J; Ten Cate, Olle T J

2018-06-01

Clinical training programs increasingly use entrustable professional activities (EPAs) as focus of assessment. However, questions remain about which information should ground decisions to trust learners. This qualitative study aimed to identify decision variables in the workplace that clinical teachers find relevant in the elaboration of the entrustment decision processes. The findings can substantiate entrustment decision-making in the clinical workplace. Focus groups were conducted with medical and veterinary clinical teachers, using the structured consensus method of the Nominal Group Technique to generate decision variables. A ranking was made based on a relevance score assigned by the clinical teachers to the different decision variables. Field notes, audio recordings and flip chart lists were analyzed and subsequently translated and, as a form of axial coding, merged into one list, combining the decision variables that were similar in their meaning. A list of 11 and 17 decision variables were acknowledged as relevant by the medical and veterinary teacher groups, respectively. The focus groups yielded 21 unique decision variables that were considered relevant to inform readiness to perform a clinical task on a designated level of supervision. The decision variables consisted of skills, generic qualities, characteristics, previous performance or other information. We were able to group the decision variables into five categories: ability, humility, integrity, reliability and adequate exposure. To entrust a learner to perform a task at a specific level of supervision, a supervisor needs information to support such a judgement. This trust cannot be credited on a single case at a single moment of assessment, but requires different variables and multiple sources of information. This study provides an overview of decision variables giving evidence to justify the multifactorial process of making an entrustment decision.

Preferred information sources for clinical decision making: critical care nurses' perceptions of information accessibility and usefulness.

PubMed

Marshall, Andrea P; West, Sandra H; Aitken, Leanne M

2011-12-01

Variability in clinical practice may result from the use of diverse information sources to guide clinical decisions. In routine clinical practice, nurses privilege information from colleagues over more formal information sources. It is not clear whether similar information-seeking behaviour is exhibited when critical care nurses make decisions about a specific clinical practice, where extensive practice variability exists alongside a developing research base. This study explored the preferred sources of information intensive care nurses used and their perceptions of the accessibility and usefulness of this information for making decisions in clinically uncertain situations specific to enteral feeding practice. An instrumental case study design, incorporating concurrent verbal protocols, Q methodology and focus groups, was used to determine intensive care nurses' perspectives of information use in the resolution of clinical uncertainty. A preference for information from colleagues to support clinical decisions was observed. People as information sources were considered most useful and most accessible in the clinical setting. Text and electronic information sources were seen as less accessible, mainly because of the time required to access the information within the documents. When faced with clinical uncertainty, obtaining information from colleagues allows information to be quickly accessed and applied within the context of a specific clinical presentation. Seeking information from others also provides opportunities for shared decision-making and potential validation of clinical judgment, although differing views may exacerbate clinical uncertainty. The social exchange of clinical information may meet the needs of nurses working in a complex, time-pressured environment but the extent of the evidence base for information passed through verbal communication is unclear. The perceived usefulness and accessibility of information is premised on the ease of use and access and thus the variability in information may be contributing to clinical uncertainty. Copyright ©2011 Sigma Theta Tau International.

Objective consensus from decision trees.

PubMed

Putora, Paul Martin; Panje, Cedric M; Papachristofilou, Alexandros; Dal Pra, Alan; Hundsberger, Thomas; Plasswilm, Ludwig

2014-12-05

Consensus-based approaches provide an alternative to evidence-based decision making, especially in situations where high-level evidence is limited. Our aim was to demonstrate a novel source of information, objective consensus based on recommendations in decision tree format from multiple sources. Based on nine sample recommendations in decision tree format a representative analysis was performed. The most common (mode) recommendations for each eventuality (each permutation of parameters) were determined. The same procedure was applied to real clinical recommendations for primary radiotherapy for prostate cancer. Data was collected from 16 radiation oncology centres, converted into decision tree format and analyzed in order to determine the objective consensus. Based on information from multiple sources in decision tree format, treatment recommendations can be assessed for every parameter combination. An objective consensus can be determined by means of mode recommendations without compromise or confrontation among the parties. In the clinical example involving prostate cancer therapy, three parameters were used with two cut-off values each (Gleason score, PSA, T-stage) resulting in a total of 27 possible combinations per decision tree. Despite significant variations among the recommendations, a mode recommendation could be found for specific combinations of parameters. Recommendations represented as decision trees can serve as a basis for objective consensus among multiple parties.

Decision making in asthma exacerbation: a clinical judgement analysis

PubMed Central

Jenkins, John; Shields, Mike; Patterson, Chris; Kee, Frank

2007-01-01

Background Clinical decisions which impact directly on patient safety and quality of care are made during acute asthma attacks by individual doctors based on their knowledge and experience. Decisions include administration of systemic corticosteroids (CS) and oral antibiotics, and admission to hospital. Clinical judgement analysis provides a methodology for comparing decisions between practitioners with different training and experience, and improving decision making. Methods Stepwise linear regression was used to select clinical cues based on visual analogue scale assessments of the propensity of 62 clinicians to prescribe a short course of oral CS (decision 1), a course of antibiotics (decision 2), and/or admit to hospital (decision 3) for 60 “paper” patients. Results When compared by specialty, paediatricians' models for decision 1 were more likely to include level of alertness as a cue (54% vs 16%); for decision 2 they were more likely to include presence of crepitations (49% vs 16%) and less likely to include inhaled CS (8% vs 40%), respiratory rate (0% vs 24%) and air entry (70% vs 100%). When compared to other grades, the models derived for decision 3 by consultants/general practitioners were more likely to include wheeze severity as a cue (39% vs 6%). Conclusions Clinicians differed in their use of individual cues and the number included in their models. Patient safety and quality of care will benefit from clarification of decision‐making strategies as general learning points during medical training, in the development of guidelines and care pathways, and by clinicians developing self‐awareness of their own preferences. PMID:17428817

Creating Shareable Clinical Decision Support Rules for a Pharmacogenomics Clinical Guideline Using Structured Knowledge Representation.

PubMed

Linan, Margaret K; Sottara, Davide; Freimuth, Robert R

2015-01-01

Pharmacogenomics (PGx) guidelines contain drug-gene relationships, therapeutic and clinical recommendations from which clinical decision support (CDS) rules can be extracted, rendered and then delivered through clinical decision support systems (CDSS) to provide clinicians with just-in-time information at the point of care. Several tools exist that can be used to generate CDS rules that are based on computer interpretable guidelines (CIG), but none have been previously applied to the PGx domain. We utilized the Unified Modeling Language (UML), the Health Level 7 virtual medical record (HL7 vMR) model, and standard terminologies to represent the semantics and decision logic derived from a PGx guideline, which were then mapped to the Health eDecisions (HeD) schema. The modeling and extraction processes developed here demonstrate how structured knowledge representations can be used to support the creation of shareable CDS rules from PGx guidelines.

Application of evidence-based dentistry: from research to clinical periodontal practice.

PubMed

Kwok, Vivien; Caton, Jack G; Polson, Alan M; Hunter, Paul G

2012-06-01

Dentists need to make daily decisions regarding patient care, and these decisions should essentially be scientifically sound. Evidence-based dentistry is meant to empower clinicians to provide the most contemporary treatment. The benefits of applying the evidence-based method in clinical practice include application of the most updated treatment and stronger reasoning to justify the treatment. A vast amount of information is readily accessible with today's digital technology, and a standardized search protocol can be developed to ensure that a literature search is valid, specific and repeatable. It involves developing a preset question (population, intervention, comparison and outcome; PICO) and search protocol. It is usually used academically to perform commissioned reviews, but it can also be applied to answer simple clinical queries. The scientific evidence thus obtained can then be considered along with patient preferences and values, clinical patient circumstances and the practitioner's experience and judgment in order to make the treatment decision. This paper describes how clinicians can incorporate evidence-based methods into patient care and presents a clinical example to illustrate the process. © 2012 John Wiley & Sons A/S.

Use of declarative statements in creating and maintaining computer-interpretable knowledge bases for guideline-based care.

PubMed

Tu, Samson W; Hrabak, Karen M; Campbell, James R; Glasgow, Julie; Nyman, Mark A; McClure, Robert; McClay, James; Abarbanel, Robert; Mansfield, James G; Martins, Susana M; Goldstein, Mary K; Musen, Mark A

2006-01-01

Developing computer-interpretable clinical practice guidelines (CPGs) to provide decision support for guideline-based care is an extremely labor-intensive task. In the EON/ATHENA and SAGE projects, we formulated substantial portions of CPGs as computable statements that express declarative relationships between patient conditions and possible interventions. We developed query and expression languages that allow a decision-support system (DSS) to evaluate these statements in specific patient situations. A DSS can use these guideline statements in multiple ways, including: (1) as inputs for determining preferred alternatives in decision-making, and (2) as a way to provide targeted commentaries in the clinical information system. The use of these declarative statements significantly reduces the modeling expertise and effort required to create and maintain computer-interpretable knowledge bases for decision-support purpose. We discuss possible implications for sharing of such knowledge bases.

Artificial intelligence in cardiology.

PubMed

Bonderman, Diana

2017-12-01

Decision-making is complex in modern medicine and should ideally be based on available data, structured knowledge and proper interpretation in the context of an individual patient. Automated algorithms, also termed artificial intelligence that are able to extract meaningful patterns from data collections and build decisions upon identified patterns may be useful assistants in clinical decision-making processes. In this article, artificial intelligence-based studies in clinical cardiology are reviewed. The text also touches on the ethical issues and speculates on the future roles of automated algorithms versus clinicians in cardiology and medicine in general.

Unconscious race and class bias: its association with decision making by trauma and acute care surgeons.

PubMed

Haider, Adil H; Schneider, Eric B; Sriram, N; Dossick, Deborah S; Scott, Valerie K; Swoboda, Sandra M; Losonczy, Lia; Haut, Elliott R; Efron, David T; Pronovost, Peter J; Freischlag, Julie A; Lipsett, Pamela A; Cornwell, Edward E; MacKenzie, Ellen J; Cooper, Lisa A

2014-09-01

Recent studies have found that unconscious biases may influence physicians' clinical decision making. The objective of our study was to determine, using clinical vignettes, if unconscious race and class biases exist specifically among trauma/acute care surgeons and, if so, whether those biases impact surgeons' clinical decision making. A prospective Web-based survey was administered to active members of the Eastern Association for the Surgery of Trauma. Participants completed nine clinical vignettes, each with three trauma/acute care surgery management questions. Race Implicit Association Test (IAT) and social class IAT assessments were completed by each participant. Multivariable, ordered logistic regression analysis was then used to determine whether implicit biases reflected on the IAT tests were associated with vignette responses. In total, 248 members of the Eastern Association for the Surgery of Trauma participated. Of these, 79% explicitly stated that they had no race preferences and 55% stated they had no social class preferences. However, 73.5% of the participants had IAT scores demonstrating an unconscious preference toward white persons; 90.7% demonstrated an implicit preference toward upper social class persons. Only 2 of 27 vignette-based clinical decisions were associated with patient race or social class on univariate analyses. Multivariable analyses revealed no relationship between IAT scores and vignette-based clinical assessments. Unconscious preferences for white and upper-class persons are prevalent among trauma and acute care surgeons. In this study, these biases were not statistically significantly associated with clinical decision making. Further study of the factors that may prevent implicit biases from influencing patient management is warranted. Epidemiologic study, level II.

Knowledge of Fecal Calprotectin and Infliximab Trough Levels Alters Clinical Decision-making for IBD Outpatients on Maintenance Infliximab Therapy.

PubMed

Huang, Vivian W; Prosser, Connie; Kroeker, Karen I; Wang, Haili; Shalapay, Carol; Dhami, Neil; Fedorak, Darryl K; Halloran, Brendan; Dieleman, Levinus A; Goodman, Karen J; Fedorak, Richard N

2015-06-01

Infliximab is an effective therapy for inflammatory bowel disease (IBD). However, more than 50% of patients lose response. Empiric dose intensification is not effective for all patients because not all patients have objective disease activity or subtherapeutic drug level. The aim was to determine how an objective marker of disease activity or therapeutic drug monitoring affects clinical decisions regarding maintenance infliximab therapy in outpatients with IBD. Consecutive patients with IBD on maintenance infliximab therapy were invited to participate by providing preinfusion stool and blood samples. Fecal calprotectin (FCP) and infliximab trough levels (ITLs) were measured by enzyme linked immunosorbent assay. Three decisions were compared: (1) actual clinical decision, (2) algorithmic FCP or ITL decisions, and (3) expert panel decision based on (a) clinical data, (b) clinical data plus FCP, and (c) clinical data plus FCP plus ITL. In secondary analysis, Receiver-operating curves were used to assess the ability of FCP and ITL in predicting clinical disease activity or remission. A total of 36 sets of blood and stool were available for analysis; median FCP 191.5 μg/g, median ITLs 7.3 μg/mL. The actual clinical decision differed from the hypothetical decision in 47.2% (FCP algorithm); 69.4% (ITL algorithm); 25.0% (expert panel clinical decision); 44.4% (expert panel clinical plus FCP); 58.3% (expert panel clinical plus FCP plus ITL) cases. FCP predicted clinical relapse (area under the curve [AUC] = 0.417; 95% confidence interval [CI], 0.197-0.641) and subtherapeutic ITL (AUC = 0.774; 95% CI, 0.536-1.000). ITL predicted clinical remission (AUC = 0.498; 95% CI, 0.254-0.742) and objective remission (AUC = 0.773; 95% CI, 0.622-0.924). Using FCP and ITLs in addition to clinical data results in an increased number of decisions to optimize management in outpatients with IBD on stable maintenance infliximab therapy.

Web-based health services and clinical decision support.

PubMed

Jegelevicius, Darius; Marozas, Vaidotas; Lukosevicius, Arunas; Patasius, Martynas

2004-01-01

The purpose of this study was the development of a Web-based e-health service for comprehensive assistance and clinical decision support. The service structure consists of a Web server, a PHP-based Web interface linked to a clinical SQL database, Java applets for interactive manipulation and visualization of signals and a Matlab server linked with signal and data processing algorithms implemented by Matlab programs. The service ensures diagnostic signal- and image analysis-sbased clinical decision support. By using the discussed methodology, a pilot service for pathology specialists for automatic calculation of the proliferation index has been developed. Physicians use a simple Web interface for uploading the pictures under investigation to the server; subsequently a Java applet interface is used for outlining the region of interest and, after processing on the server, the requested proliferation index value is calculated. There is also an "expert corner", where experts can submit their index estimates and comments on particular images, which is especially important for system developers. These expert evaluations are used for optimization and verification of automatic analysis algorithms. Decision support trials have been conducted for ECG and ophthalmology ultrasonic investigations of intraocular tumor differentiation. Data mining algorithms have been applied and decision support trees constructed. These services are under implementation by a Web-based system too. The study has shown that the Web-based structure ensures more effective, flexible and accessible services compared with standalone programs and is very convenient for biomedical engineers and physicians, especially in the development phase.

A Knowledge-Modeling Approach to Integrate Multiple Clinical Practice Guidelines to Provide Evidence-Based Clinical Decision Support for Managing Comorbid Conditions.

PubMed

Abidi, Samina

2017-10-26

Clinical management of comorbidities is a challenge, especially in a clinical decision support setting, as it requires the safe and efficient reconciliation of multiple disease-specific clinical procedures to formulate a comorbid therapeutic plan that is both effective and safe for the patient. In this paper we pursue the integration of multiple disease-specific Clinical Practice Guidelines (CPG) in order to manage co-morbidities within a computerized Clinical Decision Support System (CDSS). We present a CPG integration framework-termed as COMET (Comorbidity Ontological Modeling & ExecuTion) that manifests a knowledge management approach to model, computerize and integrate multiple CPG to yield a comorbid CPG knowledge model that upon execution can provide evidence-based recommendations for handling comorbid patients. COMET exploits semantic web technologies to achieve (a) CPG knowledge synthesis to translate a paper-based CPG to disease-specific clinical pathways (CP) that include specialized co-morbidity management procedures based on input from domain experts; (b) CPG knowledge modeling to computerize the disease-specific CP using a Comorbidity CPG ontology; (c) CPG knowledge integration by aligning multiple ontologically-modeled CP to develop a unified comorbid CPG knowledge model; and (e) CPG knowledge execution using reasoning engines to derive CPG-mediated recommendations for managing patients with comorbidities. We present a web-accessible COMET CDSS that provides family physicians with CPG-mediated comorbidity decision support to manage Atrial Fibrillation and Chronic Heart Failure. We present our qualitative and quantitative analysis of the knowledge content and usability of COMET CDSS.

Diagnostic games: from adequate formalization of clinical experience to structure discovery.

PubMed

Shifrin, Michael A; Kasparova, Eva I

2008-01-01

A method of obtaining well-founded and reproducible results in clinical decision making is presented. It is based on "diagnostic games", a procedure of elicitation and formalization of experts' knowledge and experience. The use of this procedure allows formulating decision rules in the terms of an adequate language, that are both unambiguous and clinically clear.

Developing integrated clinical reasoning competencies in dental students using scaffolded case-based learning - empirical evidence.

PubMed

Postma, T C; White, J G

2016-08-01

This study provides empirical evidence of the development of integrated clinical reasoning in the discipline-based School of Dentistry, University of Pretoria, South Africa. Students were exposed to case-based learning in comprehensive patient care (CPC) in the preclinical year of study, scaffolded by means of the four-component instructional design model for complex learning. Progress test scores of third- to fifth-year dental students, who received case-based teaching and learning in the third year (2009-2011), were compared to the scores of preceding fourth- and fifth-year cohorts. These fourth- and fifth-year cohorts received content-based teaching concurrently with their clinical training in CPC. The progress test consisted of a complex case study and 32 MCQs on tracer conditions. Students had to gather the necessary information and had to make diagnostic and treatment-planning decisions. Preclinical students who participated in the case-based teaching and learning achieved similar scores compared to final-year students who received lecture-based teaching and learning. Final-year students who participated in the case-based learning made three more correct clinical decisions per student, compared to those who received content-based teaching. Students struggled more with treatment-planning than with diagnostic decisions. The scaffolded case-based learning appears to contribute to accurate clinical decisions when compared to lecture-based teaching. It is suggested that the development of integrated reasoning competencies starts as early as possible in a dental curriculum, perhaps even in the preclinical year of study. Treatment-planning should receive particular attention. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Using a Clinical Knowledge Base to Assess Comorbidity Interrelatedness Among Patients with Multiple Chronic Conditions.

PubMed

Zulman, Donna M; Martins, Susana B; Liu, Yan; Tu, Samson W; Hoffman, Brian B; Asch, Steven M; Goldstein, Mary K

2015-01-01

Decision support tools increasingly integrate clinical knowledge such as medication indications and contraindications with electronic health record (EHR) data to support clinical care and patient safety. The availability of this encoded information and patient data provides an opportunity to develop measures of clinical decision complexity that may be of value for quality improvement and research efforts. We investigated the feasibility of using encoded clinical knowledge and EHR data to develop a measure of comorbidity interrelatedness (the degree to which patients' co-occurring conditions interact to generate clinical complexity). Using a common clinical scenario-decisions about blood pressure medications in patients with hypertension-we quantified comorbidity interrelatedness by calculating the number of indications and contraindications to blood pressure medications that are generated by patients' comorbidities (e.g., diabetes, gout, depression). We examined properties of comorbidity interrelatedness using data from a decision support system for hypertension in the Veterans Affairs Health Care System.

Comprehensible knowledge model creation for cancer treatment decision making.

PubMed

Afzal, Muhammad; Hussain, Maqbool; Ali Khan, Wajahat; Ali, Taqdir; Lee, Sungyoung; Huh, Eui-Nam; Farooq Ahmad, Hafiz; Jamshed, Arif; Iqbal, Hassan; Irfan, Muhammad; Abbas Hydari, Manzar

2017-03-01

A wealth of clinical data exists in clinical documents in the form of electronic health records (EHRs). This data can be used for developing knowledge-based recommendation systems that can assist clinicians in clinical decision making and education. One of the big hurdles in developing such systems is the lack of automated mechanisms for knowledge acquisition to enable and educate clinicians in informed decision making. An automated knowledge acquisition methodology with a comprehensible knowledge model for cancer treatment (CKM-CT) is proposed. With the CKM-CT, clinical data are acquired automatically from documents. Quality of data is ensured by correcting errors and transforming various formats into a standard data format. Data preprocessing involves dimensionality reduction and missing value imputation. Predictive algorithm selection is performed on the basis of the ranking score of the weighted sum model. The knowledge builder prepares knowledge for knowledge-based services: clinical decisions and education support. Data is acquired from 13,788 head and neck cancer (HNC) documents for 3447 patients, including 1526 patients of the oral cavity site. In the data quality task, 160 staging values are corrected. In the preprocessing task, 20 attributes and 106 records are eliminated from the dataset. The Classification and Regression Trees (CRT) algorithm is selected and provides 69.0% classification accuracy in predicting HNC treatment plans, consisting of 11 decision paths that yield 11 decision rules. Our proposed methodology, CKM-CT, is helpful to find hidden knowledge in clinical documents. In CKM-CT, the prediction models are developed to assist and educate clinicians for informed decision making. The proposed methodology is generalizable to apply to data of other domains such as breast cancer with a similar objective to assist clinicians in decision making and education. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Benefit-Risk Analysis Approach to Capture Regulatory Decision-Making: Multiple Myeloma.

PubMed

Raju, G K; Gurumurthi, Karthik; Domike, Reuben; Kazandjian, Dickran; Landgren, Ola; Blumenthal, Gideon M; Farrell, Ann; Pazdur, Richard; Woodcock, Janet

2018-01-01

Drug regulators around the world make decisions about drug approvability based on qualitative benefit-risk analysis. In this work, a quantitative benefit-risk analysis approach captures regulatory decision-making about new drugs to treat multiple myeloma (MM). MM assessments have been based on endpoints such as time to progression (TTP), progression-free survival (PFS), and objective response rate (ORR) which are different than benefit-risk analysis based on overall survival (OS). Twenty-three FDA decisions on MM drugs submitted to FDA between 2003 and 2016 were identified and analyzed. The benefits and risks were quantified relative to comparators (typically the control arm of the clinical trial) to estimate whether the median benefit-risk was positive or negative. A sensitivity analysis was demonstrated using ixazomib to explore the magnitude of uncertainty. FDA approval decision outcomes were consistent and logical using this benefit-risk framework. © 2017 American Society for Clinical Pharmacology and Therapeutics.

Decision-Making in Audiology: Balancing Evidence-Based Practice and Patient-Centered Care

PubMed Central

Clemesha, Jennifer; Lundmark, Erik; Crome, Erica; Barr, Caitlin; McMahon, Catherine M.

2017-01-01

Health-care service delivery models have evolved from a practitioner-centered approach toward a patient-centered ideal. Concurrently, increasing emphasis has been placed on the use of empirical evidence in decision-making to increase clinical accountability. The way in which clinicians use empirical evidence and client preferences to inform decision-making provides an insight into health-care delivery models utilized in clinical practice. The present study aimed to investigate the sources of information audiologists use when discussing rehabilitation choices with clients, and discuss the findings within the context of evidence-based practice and patient-centered care. To assess the changes that may have occurred over time, this study uses a questionnaire based on one of the few studies of decision-making behavior in audiologists, published in 1989. The present questionnaire was completed by 96 audiologists who attended the World Congress of Audiology in 2014. The responses were analyzed using qualitative and quantitative approaches. Results suggest that audiologists rank clinical test results and client preferences as the most important factors for decision-making. Discussion with colleagues or experts was also frequently reported as an important source influencing decision-making. Approximately 20% of audiologists mentioned utilizing research evidence to inform decision-making when no clear solution was available. Information shared at conferences was ranked low in terms of importance and reliability. This study highlights an increase in awareness of concepts associated with evidence-based practice and patient-centered care within audiology settings, consistent with current research-to-practice dissemination pathways. It also highlights that these pathways may not be sufficient for an effective clinical implementation of these practices. PMID:28752808

Effects of Clinical Decision Topic on Patients' Involvement in and Satisfaction With Decisions and Their Subsequent Implementation.

PubMed

Freidl, Marion; Pesola, Francesca; Konrad, Jana; Puschner, Bernd; Kovacs, Attila Istvan; De Rosa, Corrado; Fiorillo, Andrea; Krogsgaard Bording, Malene; Kawohl, Wolfram; Rössler, Wulf; Nagy, Marietta; Munk-Jørgensen, Povl; Slade, Mike

2016-06-01

Clinical decision making is an important aspect of mental health care. Predictors of how patients experience decision making and whether decisions are implemented are underresearched. This study investigated the relationship between decision topic and involvement in the decision, satisfaction with it, and its subsequent implementation from both staff and patient perspectives. As part of the Clinical Decision Making and Outcome in Routine Care for People With Severe Mental Illness study, patients (N=588) and their providers (N=213) were recruited from community-based mental health services in six European countries. Both completed bimonthly assessments for one year using the Clinical Decision Making in Routine Care Scale to assess the decision topic and implementation; both also completed the Clinical Decision Making Involvement and Satisfaction Scale. Three categories of decision topics were determined: treatment (most frequently cited), social, and financial. The topic identified as most important remained stable over the follow-up. Patients were more likely to rate their involvement as active rather than passive for social decisions (odds ratio [OR]=5.7, p<.001) and financial decisions (OR=9.5, p<.001). They were more likely to report higher levels of satisfaction rather than lower levels for social decisions (OR=1.5, p=.01) and financial decisions (OR=1.7, p=.01). Social decisions were more likely to be partly implemented (OR=3.0, p<.001) or fully implemented (OR=1.7, p=.03) than not implemented. Patients reported poorer involvement, satisfaction, and implementation in regard to treatment-related decisions, compared with social and financial decisions. Clinicians may need to employ different interactional styles for different types of decisions to maximize satisfaction and decision implementation.

Clinical Decision-Making in Community Children's Mental Health: Using Innovative Methods to Compare Clinicians with and without Training in Evidence-Based Treatment

ERIC Educational Resources Information Center

Baker-Ericzén, Mary J.; Jenkins, Melissa M.; Park, Soojin; Garland, Ann F.

2015-01-01

Background: Mental health professionals' decision-making practice is an area of increasing interest and importance, especially in the pediatric research and clinical communities. Objective: The present study explored the role of prior training in evidence-based treatments (EBTs) on clinicians' assessment and treatment formulations using…

A practical approach to evidence-based dentistry: How to search for evidence to inform clinical decisions.

PubMed

Brignardello-Petersen, Romina; Carrasco-Labra, Alonso; Booth, H Austin; Glick, Michael; Guyatt, Gordon H; Azarpazhooh, Amir; Agoritsas, Thomas

2014-12-01

Knowing how to search for evidence that can inform clinical decisions is a fundamental skill for the practice of evidence-based dentistry. There are many available types of evidence-based resources, characterized by their degrees of coverage of preappraised or summarized evidence at varying levels of processing, from primary studies to systematic reviews and clinical guidelines. The practice of evidence-based dentistry requires familiarity with these resources. In this article, the authors describe the process of searching for evidence: defining the question, identifying the question's nature and main components, and selecting the study design that best addresses the question.

The Utility of the Frailty Index in Clinical Decision Making.

PubMed

Khatry, K; Peel, N M; Gray, L C; Hubbard, R E

2018-01-01

Using clinical vignettes, this study aimed to determine if a measure of patient frailty would impact management decisions made by geriatricians regarding commonly encountered clinical situations. Electronic surveys consisting of three vignettes derived from cases commonly seen in an acute inpatient ward were distributed to geriatricians. Vignettes included patients being considered for intensive care treatment, rehabilitation, or coronary artery bypass surgery. A frailty index was generated through Comprehensive electronic Geriatric Assessment. For each vignette, respondents were asked to make a recommendation for management, based on either a brief or detailed amount of clinical information and to reconsider their decision after the addition of the frailty index. The study suggests that quantification of frailty might aid the clinical judgment now employed daily to proceed with usual care, or to modify it based on the vulnerability of the person to whom it is aimed.

On implementing clinical decision support: achieving scalability and maintainability by combining business rules and ontologies.

PubMed

Kashyap, Vipul; Morales, Alfredo; Hongsermeier, Tonya

2006-01-01

We present an approach and architecture for implementing scalable and maintainable clinical decision support at the Partners HealthCare System. The architecture integrates a business rules engine that executes declarative if-then rules stored in a rule-base referencing objects and methods in a business object model. The rules engine executes object methods by invoking services implemented on the clinical data repository. Specialized inferences that support classification of data and instances into classes are identified and an approach to implement these inferences using an OWL based ontology engine is presented. Alternative representations of these specialized inferences as if-then rules or OWL axioms are explored and their impact on the scalability and maintenance of the system is presented. Architectural alternatives for integration of clinical decision support functionality with the invoking application and the underlying clinical data repository; and their associated trade-offs are discussed and presented.

Pilot study of a point-of-use decision support tool for cancer clinical trials eligibility.

PubMed

Breitfeld, P P; Weisburd, M; Overhage, J M; Sledge, G; Tierney, W M

1999-01-01

Many adults with cancer are not enrolled in clinical trials because caregivers do not have the time to match the patient's clinical findings with varying eligibility criteria associated with multiple trials for which the patient might be eligible. The authors developed a point-of-use portable decision support tool (DS-TRIEL) to automate this matching process. The support tool consists of a hand-held computer with a programmable relational database. A two-level hierarchic decision framework was used for the identification of eligible subjects for two open breast cancer clinical trials. The hand-held computer also provides protocol consent forms and schemas to further help the busy oncologist. This decision support tool and the decision framework on which it is based could be used for multiple trials and different cancer sites.

Pilot Study of a Point-of-use Decision Support Tool for Cancer Clinical Trials Eligibility

PubMed Central

Breitfeld, Philip P.; Weisburd, Marina; Overhage, J. Marc; Sledge, George; Tierney, William M.

1999-01-01

Many adults with cancer are not enrolled in clinical trials because caregivers do not have the time to match the patient's clinical findings with varying eligibility criteria associated with multiple trials for which the patient might be eligible. The authors developed a point-of-use portable decision support tool (DS-TRIEL) to automate this matching process. The support tool consists of a hand-held computer with a programmable relational database. A two-level hierarchic decision framework was used for the identification of eligible subjects for two open breast cancer clinical trials. The hand-held computer also provides protocol consent forms and schemas to further help the busy oncologist. This decision support tool and the decision framework on which it is based could be used for multiple trials and different cancer sites. PMID:10579605

mobilityRERC state of the science conference: Considerations for developing an evidence base for wheeled mobility and seating service delivery.

PubMed

Cohen, Laura; Greer, Nancy; Berliner, Elise; Sprigle, Stephen

2013-11-01

This article, developed as background content for discussion during the Mobility Rehabilitation Engineering Research Center State of the Science Conference, reviews research surrounding wheeled mobility and seating (WMS) service delivery, discusses the challenges of improving clinical decision-making, and discusses research approaches used to study and improve health services in other practice areas that might be leveraged to develop the evidence base for WMS. Narrative literature review. An overview of existing research found general agreement across models of WMS service delivery but little high quality evidence to support the recommended approaches and few studies of the relationship between service delivery steps and individual patient outcomes. The definition of successful clinical decision-making is different for different stakeholders. Clinical decision-making should incorporate the best available evidence along with patient values, preferences, circumstances, and clinical expertise. To advance the evidence base for WMS service delivery, alternatives to randomized controlled trials should be considered and reliable and valid outcome measures developed. Technological advances offer tremendous opportunities for individuals with complex rehabilitation technology needs. However, with ongoing scrutiny of WMS service delivery there is an increased need for evidence to support the clinical decision-making process and to support evidence-based coverage policies for WMS services and technologies. An evidence base for wheeled mobility and seating services is an important component of the clinical decision-making process. At present, there is little evidence regarding essential components of the wheeled mobility and seating evaluation or the relationship between the evaluation process and patient outcomes. Many factors can confound this relationship and present challenges to research in this area. All stakeholders (i.e. clinicians, rehabilitation technology suppliers, manufacturers, researchers, payers, policy makers, and wheelchair users) need to work together to develop and support an evidence base for wheeled mobility and seating service delivery.

Design, implementation, use, and preliminary evaluation of SEBASTIAN, a standards-based Web service for clinical decision support.

PubMed

Kawamoto, Kensaku; Lobach, David F

2005-01-01

Despite their demonstrated ability to improve care quality, clinical decision support systems are not widely used. In part, this limited use is due to the difficulty of sharing medical knowledge in a machine-executable format. To address this problem, we developed a decision support Web service known as SEBASTIAN. In SEBASTIAN, individual knowledge modules define the data requirements for assessing a patient, the conclusions that can be drawn using that data, and instructions on how to generate those conclusions. Using standards-based XML messages transmitted over HTTP, client decision support applications provide patient data to SEBASTIAN and receive patient-specific assessments and recommendations. SEBASTIAN has been used to implement four distinct decision support systems; an architectural overview is provided for one of these systems. Preliminary assessments indicate that SEBASTIAN fulfills all original design objectives, including the re-use of executable medical knowledge across diverse applications and care settings, the straightforward authoring of knowledge modules, and use of the framework to implement decision support applications with significant clinical utility.

In the teeth of the evidence: the curious case of evidence-based medicine.

PubMed

Davidoff, F

1999-03-01

For a very long time, evidence from research has contributed to clinical decision making. Over the past 50 years, however, the nature of clinical research evidence has drastically changed compared with previous eras: its standards are higher, the tools for assembling and analyzing it are more powerful, and the context in which it is used is less authoritarian. The consequence has been a shift in both the concept and the practice of clinical decision making known as evidence-based medicine. Evidence-based decisions, by definition, use the strongest available evidence, are often more quantitatively informed than decisions made in the traditional fashion; and sometimes run counter to expert opinion. The techniques of evidence-based medicine are also helpful in resolving conflicting opinions. Evidence-based medicine did not simply appear in vacuo; its roots extend back at least as far as the great French Encyclopedia of the 18th century, and the subsequent work of Pierre Louis in Paris in the early 19th century. The power of the evidence-based approach has been enhanced in recent years by the development of the techniques of systematic review and meta-analysis. While this approach has its critics, we would all want the best available evidence used in making decisions about our care if we got sick. It is only fair that the patients under our care receive nothing less.

Appropriate and inappropriate influences on outpatient discharge decision making in dermatology: a prospective qualitative study.

PubMed

Harun, N A; Finlay, A Y; Salek, M S; Piguet, V

2015-09-01

Outpatient discharge decision making in dermatology is poorly understood. To identify the influences on clinicians' thought processes when making discharge decisions in dermatology outpatient clinics. Forty clinicians from 11 National Health Service Trusts in England were interviewed. The interviews were audiorecorded, transcribed, coded and thematically analysed. The mean age of the clinicians was 48.8 years (range 33.0-67.0), 17 (43%) were men and 19 (48%) had > 20 years of clinical experience. One hundred and forty-eight influences were reported, with five main themes: (i) disease-based influences included type of diagnosis (100% of clinicians), guidelines (100%) and treatment needed (100%); (ii) clinician-based influences included the clinician's level of experience (100%), seniority (37%), emotional attitude (95%), 'gut feeling' (25%), personal attitude towards discharge (45%) and level of perception (100%); (iii) patient-based influences included patients' ability to cope with their disease (100%), wishes (70%), quality of life (32%), command of English (40%) and cultural background (25%); (iv) practice-based influences included good primary care (100%), secondary support structure (100%) and clinic capacity pressure (67%); (v) policy-based influences included pressure from hospital managers (57%) and an active discharge policy (7%). Fourteen (9%) influences were potentially inappropriate. This study has identified multiple factors influencing outpatient discharge decision making. This provides the basis for developing evidence-based training to improve discharge decision appropriateness. © 2015 British Association of Dermatologists.

Decision curve analysis assessing the clinical benefit of NMP22 in the detection of bladder cancer: secondary analysis of a prospective trial.

PubMed

Barbieri, Christopher E; Cha, Eugene K; Chromecki, Thomas F; Dunning, Allison; Lotan, Yair; Svatek, Robert S; Scherr, Douglas S; Karakiewicz, Pierre I; Sun, Maxine; Mazumdar, Madhu; Shariat, Shahrokh F

2012-03-01

• To employ decision curve analysis to determine the impact of nuclear matrix protein 22 (NMP22) on clinical decision making in the detection of bladder cancer using data from a prospective trial. • The study included 1303 patients at risk for bladder cancer who underwent cystoscopy, urine cytology and measurement of urinary NMP22 levels. • We constructed several prediction models to estimate risk of bladder cancer. The base model was generated using patient characteristics (age, gender, race, smoking and haematuria); cytology and NMP22 were added to the base model to determine effects on predictive accuracy. • Clinical net benefit was calculated by summing the benefits and subtracting the harms and weighting these by the threshold probability at which a patient or clinician would opt for cystoscopy. • In all, 72 patients were found to have bladder cancer (5.5%). In univariate analyses, NMP22 was the strongest predictor of bladder cancer presence (predictive accuracy 71.3%), followed by age (67.5%) and cytology (64.3%). • In multivariable prediction models, NMP22 improved the predictive accuracy of the base model by 8.2% (area under the curve 70.2-78.4%) and of the base model plus cytology by 4.2% (area under the curve 75.9-80.1%). • Decision curve analysis revealed that adding NMP22 to other models increased clinical benefit, particularly at higher threshold probabilities. • NMP22 is a strong, independent predictor of bladder cancer. • Addition of NMP22 improves the accuracy of standard predictors by a statistically and clinically significant margin. • Decision curve analysis suggests that integration of NMP22 into clinical decision making helps avoid unnecessary cystoscopies, with minimal increased risk of missing a cancer. © 2011 THE AUTHORS. BJU INTERNATIONAL © 2011 BJU INTERNATIONAL.

Connecting clinical and actuarial prediction with rule-based methods.

PubMed

Fokkema, Marjolein; Smits, Niels; Kelderman, Henk; Penninx, Brenda W J H

2015-06-01

Meta-analyses comparing the accuracy of clinical versus actuarial prediction have shown actuarial methods to outperform clinical methods, on average. However, actuarial methods are still not widely used in clinical practice, and there has been a call for the development of actuarial prediction methods for clinical practice. We argue that rule-based methods may be more useful than the linear main effect models usually employed in prediction studies, from a data and decision analytic as well as a practical perspective. In addition, decision rules derived with rule-based methods can be represented as fast and frugal trees, which, unlike main effects models, can be used in a sequential fashion, reducing the number of cues that have to be evaluated before making a prediction. We illustrate the usability of rule-based methods by applying RuleFit, an algorithm for deriving decision rules for classification and regression problems, to a dataset on prediction of the course of depressive and anxiety disorders from Penninx et al. (2011). The RuleFit algorithm provided a model consisting of 2 simple decision rules, requiring evaluation of only 2 to 4 cues. Predictive accuracy of the 2-rule model was very similar to that of a logistic regression model incorporating 20 predictor variables, originally applied to the dataset. In addition, the 2-rule model required, on average, evaluation of only 3 cues. Therefore, the RuleFit algorithm appears to be a promising method for creating decision tools that are less time consuming and easier to apply in psychological practice, and with accuracy comparable to traditional actuarial methods. (c) 2015 APA, all rights reserved).

Clinic-Based Mobile Health Decision Support to Enhance Adult Epilepsy Self-Management: An Intervention Mapping Approach.

PubMed

Shegog, Ross; Begley, Charles E

2017-01-01

Epilepsy is a neurological disorder involving recurrent seizures. It affects approximately 5 million people in the U.S. To optimize their quality of life people with epilepsy are encouraged to engage in self-management (S-M) behaviors. These include managing their treatment (e.g., adhering to anti-seizure medication and clinical visit schedules), managing their seizures (e.g., responding to seizure episodes), managing their safety (e.g., monitoring and avoiding environmental seizure triggers), and managing their co-morbid conditions (e.g., anxiety, depression). The clinic-based Management Information Decision Support Epilepsy Tool (MINDSET) is a decision-support system founded on theory and empirical evidence. It is designed to increase awareness by adult patients (≥18 years) and their health-care provider regarding the patient's epilepsy S-M behaviors, facilitate communication during the clinic visit to prioritize S-M goals and strategies commensurate with the patient's needs, and increase the patient's self-efficacy to achieve those goals. The purpose of this paper is to describe the application of intervention mapping (IM) to develop, implement, and formatively evaluate the clinic-based MINDSET prototype and in developing implementation and evaluation plans. Deliverables comprised a logic model of the problem (IM Step 1); matrices of program objectives (IM Step 2); a program planning document comprising scope, sequence, theory-based methods, and practical strategies (IM Step 3); a functional MINDSET program prototype (IM Step 4); plans for implementation (IM Step 5); and evaluation (IM Step 6). IM provided a logical and systematic approach to developing and evaluating clinic-based decision support toward epilepsy S-M.

Development and Validation of a Primary Care-Based Family Health History and Decision Support Program (MeTree)

PubMed Central

Orlando, Lori A.; Buchanan, Adam H.; Hahn, Susan E.; Christianson, Carol A.; Powell, Karen P.; Skinner, Celette Sugg; Chesnut, Blair; Blach, Colette; Due, Barbara; Ginsburg, Geoffrey S.; Henrich, Vincent C.

2016-01-01

INTRODUCTION Family health history is a strong predictor of disease risk. To reduce the morbidity and mortality of many chronic diseases, risk-stratified evidence-based guidelines strongly encourage the collection and synthesis of family health history to guide selection of primary prevention strategies. However, the collection and synthesis of such information is not well integrated into clinical practice. To address barriers to collection and use of family health histories, the Genomedical Connection developed and validated MeTree, a Web-based, patient-facing family health history collection and clinical decision support tool. MeTree is designed for integration into primary care practices as part of the genomic medicine model for primary care. METHODS We describe the guiding principles, operational characteristics, algorithm development, and coding used to develop MeTree. Validation was performed through stakeholder cognitive interviewing, a genetic counseling pilot program, and clinical practice pilot programs in 2 community-based primary care clinics. RESULTS Stakeholder feedback resulted in changes to MeTree’s interface and changes to the phrasing of clinical decision support documents. The pilot studies resulted in the identification and correction of coding errors and the reformatting of clinical decision support documents. MeTree’s strengths in comparison with other tools are its seamless integration into clinical practice and its provision of action-oriented recommendations guided by providers’ needs. LIMITATIONS The tool was validated in a small cohort. CONCLUSION MeTree can be integrated into primary care practices to help providers collect and synthesize family health history information from patients with the goal of improving adherence to risk-stratified evidence-based guidelines. PMID:24044145

Modifications and integration of the electronic tracking board in a pediatric emergency department.

PubMed

Dexheimer, Judith W; Kennebeck, Stephanie

2013-07-01

Electronic health records (EHRs) are used for data storage; provider, laboratory, and patient communication; clinical decision support; procedure and medication orders; and decision support alerts. Clinical decision support is part of any EHR and is designed to help providers make better decisions. The emergency department (ED) poses a unique environment to the use of EHRs and clinical decision support. Used effectively, computerized tracking boards can help improve flow, communication, and the dissemination of pertinent visit information between providers and other departments in a busy ED. We discuss the unique modifications and decisions made in the implementation of an EHR and computerized tracking board in a pediatric ED. We discuss the changing views based on provider roles, customization to the user interface including the layout and colors, decision support, tracking board best practices collected from other institutions and colleagues, and a case study of using reminders on the electronic tracking board to drive pain reassessments.

Evaluation of Internet-Based Clinical Decision Support Systems

PubMed Central

Thomas, Karl W; Dayton, Charles S

1999-01-01

Background Scientifically based clinical guidelines have become increasingly used to educate physicians and improve quality of care. While individual guidelines are potentially useful, repeated studies have shown that guidelines are ineffective in changing physician behavior. The Internet has evolved as a potentially useful tool for guideline education, dissemination, and implementation because of its open standards and its ability to provide concise, relevant clinical information at the location and time of need. Objective Our objective was to develop and test decision support systems (DSS) based on clinical guidelines which could be delivered over the Internet for two disease models: asthma and tuberculosis (TB) preventive therapy. Methods Using open standards of HTML and CGI, we developed an acute asthma severity assessment DSS and a preventative tuberculosis treatment DSS based on content from national guidelines that are recognized as standards of care. Both DSS's are published on the Internet and operate through a decision algorithm developed from the parent guidelines with clinical information provided by the user at the point of clinical care. We tested the effectiveness of each DSS in influencing physician decisions using clinical scenario testing. Results We first validated the asthma algorithm by comparing asthma experts' decisions with the decisions reached by nonpulmonary nurses using the computerized DSS. Using the DSS, nurses scored the same as experts (89% vs. 88%; p = NS). Using the same scenario test instrument, we next compared internal medicine residents using the DSS with residents using a printed version of the National Asthma Education Program-2 guidelines. Residents using the computerized DSS scored significantly better than residents using the paper-based guidelines (92% vs. 84%; p <0.002). We similarly compared residents using the computerized TB DSS to residents using a printed reference card; the residents using the computerized DSS scored significantly better (95.8% vs. 56.6% correct; p<0.001). Conclusions Previous work has shown that guidelines disseminated through traditional educational interventions have minimal impact on physician behavior. Although computerized DSS have been effective in altering physician behavior, many of these systems are not widely available. We have developed two clinical DSS's based on national guidelines and published them on the Internet. Both systems improved physician compliance with national guidelines when tested in clinical scenarios. By providing information that is coupled to relevant activity, we expect that these widely available DSS's will serve as effective educational tools to positively impact physician behavior. PMID:11720915

New decision criteria for selecting delta check methods based on the ratio of the delta difference to the width of the reference range can be generally applicable for each clinical chemistry test item.

PubMed

Park, Sang Hyuk; Kim, So-Young; Lee, Woochang; Chun, Sail; Min, Won-Ki

2012-09-01

Many laboratories use 4 delta check methods: delta difference, delta percent change, rate difference, and rate percent change. However, guidelines regarding decision criteria for selecting delta check methods have not yet been provided. We present new decision criteria for selecting delta check methods for each clinical chemistry test item. We collected 811,920 and 669,750 paired (present and previous) test results for 27 clinical chemistry test items from inpatients and outpatients, respectively. We devised new decision criteria for the selection of delta check methods based on the ratio of the delta difference to the width of the reference range (DD/RR). Delta check methods based on these criteria were compared with those based on the CV% of the absolute delta difference (ADD) as well as those reported in 2 previous studies. The delta check methods suggested by new decision criteria based on the DD/RR ratio corresponded well with those based on the CV% of the ADD except for only 2 items each in inpatients and outpatients. Delta check methods based on the DD/RR ratio also corresponded with those suggested in the 2 previous studies, except for 1 and 7 items in inpatients and outpatients, respectively. The DD/RR method appears to yield more feasible and intuitive selection criteria and can easily explain changes in the results by reflecting both the biological variation of the test item and the clinical characteristics of patients in each laboratory. We suggest this as a measure to determine delta check methods.

Evidence-based periodontal therapy: An overview

PubMed Central

Vijayalakshmi, R.; Anitha, V.; Ramakrishnan, T.; Sudhakar, Uma

2008-01-01

Dentists need to make clinical decisions based on limited scientific evidence. In clinical practice, a clinician must weigh a myriad of evidences every day. The goal of evidence-based dentistry is to help practitioners provide their patients with optimal care. This is achieved by integrating sound research evidence with personal clinical expertise and patient values to determine the best course of treatment. Periodontology has a rich background of research and scholarship. Therefore, efficient use of this wealth of research data needs to be a part of periodontal practice. Evidence-based periodontology aims to facilitate such an approach and it offers a bridge from science to clinical practice. The clinician must integrate the evidence with patient preference, scientific knowledge, and personal experience. Most important, it allows us to care for our patients. Therefore, evidence-based periodontology is a tool to support decision-making and integrating the best evidence available with clinical practice. PMID:20142947

Measurement-based care for refractory depression: a clinical decision support model for clinical research and practice.

PubMed

Trivedi, Madhukar H; Daly, Ella J

2007-05-01

Despite years of antidepressant drug development and patient and provider education, suboptimal medication dosing and duration of exposure resulting in incomplete remission of symptoms remains the norm in the treatment of depression. Additionally, since no one treatment is effective for all patients, optimal implementation focusing on the measurement of symptoms, side effects, and function is essential to determine effective sequential treatment approaches. There is a need for a paradigm shift in how clinical decision making is incorporated into clinical practice and for a move away from the trial-and-error approach that currently determines the "next best" treatment. This paper describes how our experience with the Texas Medication Algorithm Project (TMAP) and the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial has confirmed the need for easy-to-use clinical support systems to ensure fidelity to guidelines. To further enhance guideline fidelity, we have developed an electronic decision support system that provides critical feedback and guidance at the point of patient care. We believe that a measurement-based care (MBC) approach is essential to any decision support system, allowing physicians to individualize and adapt decisions about patient care based on symptom progress, tolerability of medication, and dose optimization. We also believe that successful integration of sequential algorithms with MBC into real-world clinics will facilitate change that will endure and improve patient outcomes. Although we use major depression to illustrate our approach, the issues addressed are applicable to other chronic psychiatric conditions including comorbid depression and substance use disorder as well as other medical illnesses.

Measurement-Based Care for Refractory Depression: A Clinical Decision Support Model for Clinical Research and Practice

PubMed Central

Trivedi, Madhukar H.; Daly, Ella J.

2009-01-01

Despite years of antidepressant drug development and patient and provider education, suboptimal medication dosing and duration of exposure resulting in incomplete remission of symptoms remains the norm in the treatment of depression. Additionally, since no one treatment is effective for all patients, optimal implementation focusing on the measurement of symptoms, side effects, and function is essential to determine effective sequential treatment approaches. There is a need for a paradigm shift in how clinical decision making is incorporated into clinical practice and for a move away from the trial-and-error approach that currently determines the “next best” treatment. This paper describes how our experience with the Texas Medication Algorithm Project (TMAP) and the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial has confirmed the need for easy-to-use clinical support systems to ensure fidelity to guidelines. To further enhance guideline fidelity, we have developed an electronic decision support system that provides critical feedback and guidance at the point of patient care. We believe that a measurement-based care (MBC) approach is essential to any decision support system, allowing physicians to individualize and adapt decisions about patient care based on symptom progress, tolerability of medication, and dose optimization. We also believe that successful integration of sequential algorithms with MBC into real-world clinics will facilitate change that will endure and improve patient outcomes. Although we use major depression to illustrate our approach, the issues addressed are applicable to other chronic psychiatric conditions including comorbid depression and substance use disorder as well as other medical illnesses. PMID:17320312

Assessing an AI knowledge-base for asymptomatic liver diseases.

PubMed

Babic, A; Mathiesen, U; Hedin, K; Bodemar, G; Wigertz, O

1998-01-01

Discovering not yet seen knowledge from clinical data is of importance in the field of asymptomatic liver diseases. Avoidance of liver biopsy which is used as the ultimate confirmation of diagnosis by making the decision based on relevant laboratory findings only, would be considered an essential support. The system based on Quinlan's ID3 algorithm was simple and efficient in extracting the sought knowledge. Basic principles of applying the AI systems are therefore described and complemented with medical evaluation. Some of the diagnostic rules were found to be useful as decision algorithms i.e. they could be directly applied in clinical work and made a part of the knowledge-base of the Liver Guide, an automated decision support system.

onlineDeCISion.org: a web-based decision aid for DCIS treatment.

PubMed

Ozanne, Elissa M; Schneider, Katharine H; Soeteman, Djøra; Stout, Natasha; Schrag, Deborah; Fordis, Michael; Punglia, Rinaa S

2015-11-01

Women diagnosed with DCIS face complex treatment decisions and often do so with inaccurate and incomplete understanding of the risks and benefits involved. Our objective was to create a tool to guide these decisions for both providers and patients. We developed a web-based decision aid designed to provide clinicians with tailored information about a patient’s recurrence risks and survival outcomes following different treatment strategies for DCIS. A theoretical framework, microsimulation model (Soeteman et al., J Natl Cancer 105:774–781, 2013) and best practices for web-based decision tools guided the development of the decision aid. The development process used semi-structured interviews and usability testing with key stakeholders, including a diverse group of multidisciplinary clinicians and a patient advocate. We developed onlineDeCISion.​org to include the following features that were rated as important by the stakeholders: (1) descriptions of each of the standard treatment options available; (2) visual projections of the likelihood of time-specific (10-year and lifetime) breast-preservation, recurrence, and survival outcomes; and (3) side-by-side comparisons of down-stream effects of each treatment choice. All clinicians reviewing the decision aid in usability testing were interested in using it in their clinical practice. The decision aid is available in a web-based format and is planned to be publicly available. To improve treatment decision making in patients with DCIS, we have developed a web-based decision aid onlineDeCISion.​org that conforms to best practices and that clinicians are interested in using in their clinics with patients to better inform treatment decisions.

Development of a computer-based clinical decision support tool for selecting appropriate rehabilitation interventions for injured workers.

PubMed

Gross, Douglas P; Zhang, Jing; Steenstra, Ivan; Barnsley, Susan; Haws, Calvin; Amell, Tyler; McIntosh, Greg; Cooper, Juliette; Zaiane, Osmar

2013-12-01

To develop a classification algorithm and accompanying computer-based clinical decision support tool to help categorize injured workers toward optimal rehabilitation interventions based on unique worker characteristics. Population-based historical cohort design. Data were extracted from a Canadian provincial workers' compensation database on all claimants undergoing work assessment between December 2009 and January 2011. Data were available on: (1) numerous personal, clinical, occupational, and social variables; (2) type of rehabilitation undertaken; and (3) outcomes following rehabilitation (receiving time loss benefits or undergoing repeat programs). Machine learning, concerned with the design of algorithms to discriminate between classes based on empirical data, was the foundation of our approach to build a classification system with multiple independent and dependent variables. The population included 8,611 unique claimants. Subjects were predominantly employed (85 %) males (64 %) with diagnoses of sprain/strain (44 %). Baseline clinician classification accuracy was high (ROC = 0.86) for selecting programs that lead to successful return-to-work. Classification performance for machine learning techniques outperformed the clinician baseline classification (ROC = 0.94). The final classifiers were multifactorial and included the variables: injury duration, occupation, job attachment status, work status, modified work availability, pain intensity rating, self-rated occupational disability, and 9 items from the SF-36 Health Survey. The use of machine learning classification techniques appears to have resulted in classification performance better than clinician decision-making. The final algorithm has been integrated into a computer-based clinical decision support tool that requires additional validation in a clinical sample.

Health economics in drug development: efficient research to inform healthcare funding decisions.

PubMed

Hall, Peter S; McCabe, Christopher; Brown, Julia M; Cameron, David A

2010-10-01

In order to decide whether a new treatment should be used in patients, a robust estimate of efficacy and toxicity is no longer sufficient. As a result of increasing healthcare costs across the globe healthcare payers and providers now seek estimates of cost-effectiveness as well. Most trials currently being designed still only consider the need for prospective efficacy and toxicity data during the development life-cycle of a new intervention. Hence the cost-effectiveness estimates are inevitably less precise than the clinical data on which they are based. Methods based on decision theory are being developed by health economists that can contribute to the design of clinical trials in such a way that they can more effectively lead to better informed drug funding decisions on the basis of cost-effectiveness in addition to clinical outcomes. There is an opportunity to apply these techniques prospectively in the design of future clinical trials. This article describes the problems encountered by those responsible for drug reimbursement decisions as a consequence of the current drug development pathway. The potential for decision theoretic methods to help overcome these problems is introduced and potential obstacles in implementation are highlighted. Copyright © 2010 Elsevier Ltd. All rights reserved.

Identification of design features to enhance utilization and acceptance of systems for Internet-based decision support at the point of care.

PubMed

Gadd, C S; Baskaran, P; Lobach, D F

1998-01-01

Extensive utilization of point-of-care decision support systems will be largely dependent on the development of user interaction capabilities that make them effective clinical tools in patient care settings. This research identified critical design features of point-of-care decision support systems that are preferred by physicians, through a multi-method formative evaluation of an evolving prototype of an Internet-based clinical decision support system. Clinicians used four versions of the system--each highlighting a different functionality. Surveys and qualitative evaluation methodologies assessed clinicians' perceptions regarding system usability and usefulness. Our analyses identified features that improve perceived usability, such as telegraphic representations of guideline-related information, facile navigation, and a forgiving, flexible interface. Users also preferred features that enhance usefulness and motivate use, such as an encounter documentation tool and the availability of physician instruction and patient education materials. In addition to identifying design features that are relevant to efforts to develop clinical systems for point-of-care decision support, this study demonstrates the value of combining quantitative and qualitative methods of formative evaluation with an iterative system development strategy to implement new information technology in complex clinical settings.

Emerging medical informatics with case-based reasoning for aiding clinical decision in multi-agent system.

PubMed

Shen, Ying; Colloc, Joël; Jacquet-Andrieu, Armelle; Lei, Kai

2015-08-01

This research aims to depict the methodological steps and tools about the combined operation of case-based reasoning (CBR) and multi-agent system (MAS) to expose the ontological application in the field of clinical decision support. The multi-agent architecture works for the consideration of the whole cycle of clinical decision-making adaptable to many medical aspects such as the diagnosis, prognosis, treatment, therapeutic monitoring of gastric cancer. In the multi-agent architecture, the ontological agent type employs the domain knowledge to ease the extraction of similar clinical cases and provide treatment suggestions to patients and physicians. Ontological agent is used for the extension of domain hierarchy and the interpretation of input requests. Case-based reasoning memorizes and restores experience data for solving similar problems, with the help of matching approach and defined interfaces of ontologies. A typical case is developed to illustrate the implementation of the knowledge acquisition and restitution of medical experts. Copyright © 2015 Elsevier Inc. All rights reserved.

A qualitative analysis of how advanced practice nurses use clinical decision support systems.

PubMed

Weber, Scott

2007-12-01

The purpose of this study was to generate a grounded theory that will reflect the experiences of advanced practice nurses (APNs) working as critical care nurse practitioners (NPs) and clinical nurse specialists (CNS) with computer-based decision-making systems. A study design using grounded theory qualitative research methods and convenience sampling was employed in this study. Twenty-three APNs (13 CNS and 10 NPs) were recruited from 16 critical care units located in six large urban medical centers in the U.S. Midwest. Single-structured in-depth interviews with open-ended audio-taped questions were conducted with each APN. Through this process, APNs defined what they consider to be relevant themes and patterns of clinical decision system use in their critical care practices, and they identified the interrelatedness of the conceptual categories that emerged from the results. Data were analyzed using the constant comparative analysis method of qualitative research. APN participants were predominantly female, white/non-Hispanic, had a history of access to the clinical decision system used in their critical care settings for an average of 14 months, and had attended a formal training program to learn how to use clinical decision systems. "Forecasting decision outcomes," which was defined as the voluntary process employed to forecast the outcomes of patient care decisions in critical care prior to actual decision making, was the core variable describing system use that emerged from the responses. This variable consisted of four user constructs or components: (a) users' perceptions of their initial system learning experience, (b) users' sense of how well they understand how system technology works, (c) users' understanding of how system inferences are created or derived, and (d) users' relative trust of system-derived data. Each of these categories was further described through the grounded theory research process, and the relationships between the categories were identified. The findings of this study suggest that the main reason critical care APNs choose to integrate clinical decision systems into their practices is to provide an objective, scientifically derived, technology-based backup for human forecasting of the outcomes of patient care decisions prior to their actual decision making. Implications for nursing, health care, and technology research are presented.

Relational Algebra in Spatial Decision Support Systems Ontologies.

PubMed

Diomidous, Marianna; Chardalias, Kostis; Koutonias, Panagiotis; Magnita, Adrianna; Andrianopoulos, Charalampos; Zimeras, Stelios; Mechili, Enkeleint Aggelos

2017-01-01

Decision Support Systems (DSS) is a powerful tool, for facilitates researchers to choose the correct decision based on their final results. Especially in medical cases where doctors could use these systems, to overcome the problem with the clinical misunderstanding. Based on these systems, queries must be constructed based on the particular questions that doctors must answer. In this work, combination between questions and queries would be presented via relational algebra.

Clinical decision-making described by Swedish prehospital emergency care nurse students - An exploratory study.

PubMed

Nilsson, Tomas; Lindström, Veronica

2016-07-01

The purpose of this study was to explore the PECN students' clinical decision-making during a seven-week clinical rotation in the ambulance services. Developing expertise in prehospital emergency care practices requires both theoretical and empirical learning. A prehospital emergency care nurse (PECN) is a Registered Nurse (RN) with one year of additional training in emergency care. There has been little investigation of how PECN students describe their decision-making during a clinical rotation. A qualitative study design was used, and 12 logbooks written by the Swedish PECN students were analysed using content analysis. The students wrote about 997 patient encounters - ambulance assignments during their clinical rotation. Four themes emerged as crucial for the students' decision-making: knowing the patient, the context-situation awareness in the ambulance service, collaboration, and evaluation. Based on the themes, students made decisions on how to respond to patients' illnesses. The PECN students used several variables in their decision-making. The decision- making was an on-going process during the whole ambulance assignment. The university has the responsibility to guide the students during their transition from an RN to a PECN. The findings of the study can support the educators and clinical supervisors in developing the programme of study for becoming a PECN. Copyright © 2015 Elsevier Ltd. All rights reserved.

Conceptual framework of knowledge management for ethical decision-making support in neonatal intensive care.

PubMed

Frize, Monique; Yang, Lan; Walker, Robin C; O'Connor, Annette M

2005-06-01

This research is built on the belief that artificial intelligence estimations need to be integrated into clinical social context to create value for health-care decisions. In sophisticated neonatal intensive care units (NICUs), decisions to continue or discontinue aggressive treatment are an integral part of clinical practice. High-quality evidence supports clinical decision-making, and a decision-aid tool based on specific outcome information for individual NICU patients will provide significant support for parents and caregivers in making difficult "ethical" treatment decisions. In our approach, information on a newborn patient's likely outcomes is integrated with the physician's interpretation and parents' perspectives into codified knowledge. Context-sensitive content adaptation delivers personalized and customized information to a variety of users, from physicians to parents. The system provides structuralized knowledge translation and exchange between all participants in the decision, facilitating collaborative decision-making that involves parents at every stage on whether to initiate, continue, limit, or terminate intensive care for their infant.

Echocardiography for Intraoperative Decision Making in Mitral Valve Surgery-A Pilot Simulation-Based Training Module.

PubMed

Morais, Rex Joseph; Ashokka, Balakrishnan; Paranjothy, Suresh; Siau, Chiang; Ti, Lian Kah

2017-10-01

Echocardiographic assessment of the repaired or replaced mitral valve intraoperatively involves making a high-impact joint decision with the surgeon, in a time-sensitive manner, in a dynamic clinical situation. These decisions have to take into account the degree of imperfection if any, the likelihood of obtaining a better result, the underlying condition of the patient, and the impact of a longer cardiopulmonary bypass period if the decision is made to reintervene. Traditional echocardiography teaching is limited in its ability to provide this training. The authors report the development and implementation of a training module simulating the dynamic clinical environment of a mitral valve surgery in progress and the critical echo-based intraoperative decision making involved in the assessment of the acceptability of the surgical result. Copyright © 2017 Elsevier Inc. All rights reserved.

The role of decision analytic modeling in the health economic assessment of spinal intervention.

PubMed

Edwards, Natalie C; Skelly, Andrea C; Ziewacz, John E; Cahill, Kevin; McGirt, Matthew J

2014-10-15

Narrative review. To review the common tenets, strengths, and weaknesses of decision modeling for health economic assessment and to review the use of decision modeling in the spine literature to date. For the majority of spinal interventions, well-designed prospective, randomized, pragmatic cost-effectiveness studies that address the specific decision-in-need are lacking. Decision analytic modeling allows for the estimation of cost-effectiveness based on data available to date. Given the rising demands for proven value in spine care, the use of decision analytic modeling is rapidly increasing by clinicians and policy makers. This narrative review discusses the general components of decision analytic models, how decision analytic models are populated and the trade-offs entailed, makes recommendations for how users of spine intervention decision models might go about appraising the models, and presents an overview of published spine economic models. A proper, integrated, clinical, and economic critical appraisal is necessary in the evaluation of the strength of evidence provided by a modeling evaluation. As is the case with clinical research, all options for collecting health economic or value data are not without their limitations and flaws. There is substantial heterogeneity across the 20 spine intervention health economic modeling studies summarized with respect to study design, models used, reporting, and general quality. There is sparse evidence for populating spine intervention models. Results mostly showed that interventions were cost-effective based on $100,000/quality-adjusted life-year threshold. Spine care providers, as partners with their health economic colleagues, have unique clinical expertise and perspectives that are critical to interpret the strengths and weaknesses of health economic models. Health economic models must be critically appraised for both clinical validity and economic quality before altering health care policy, payment strategies, or patient care decisions. 4.

Faculty Training in Evidence-Based Medicine: Improving Evidence Acquisition and Critical Appraisal

ERIC Educational Resources Information Center

Nicholson, Laura J.; Warde, Carole M.; Boker, John R.

2007-01-01

Introduction: Evidence-based medicine (EBM) integrates published clinical evidence with patient values and clinical expertise, the output of which is informed medical decision making. Key skills for evidence-based practice include acquisition and appraisal of clinical information. Faculty clinicians often lack expertise in these skills and are…

A multiple-scenario assessment of the effect of a continuous-care, guideline-based decision support system on clinicians' compliance to clinical guidelines.

PubMed

Shalom, Erez; Shahar, Yuval; Parmet, Yisrael; Lunenfeld, Eitan

2015-04-01

To quantify the effect of a new continuous-care guideline (GL)-application engine, the Picard decision support system (DSS) engine, on the correctness and completeness of clinicians' decisions relative to an established clinical GL, and to assess the clinicians' attitudes towards a specific DSS. Thirty-six clinicians, including residents at different training levels and board-certified specialists at an academic OB/GYN department that handles around 15,000 deliveries annually, agreed to evaluate our continuous-care guideline-based DSS and to perform a cross-over assessment of the effects of using our guideline-based DSS. We generated electronic patient records that realistically simulated the longitudinal course of six different clinical scenarios of the preeclampsia/eclampsia/toxemia (PET) GL, encompassing 60 different decision points in total. Each clinician managed three scenarios manually without the Picard DSS engine (Non-DSS mode) and three scenarios when assisted by the Picard DSS engine (DSS mode). The main measures in both modes were correctness and completeness of actions relative to the PET GL. Correctness was further decomposed into necessary and redundant actions, relative to the guideline and the actual patient data. At the end of the assessment, a questionnaire was administered to the clinicians to assess their perceptions regarding use of the DSS. With respect to completeness, the clinicians applied approximately 41% of the GL's recommended actions in the non-DSS mode. Completeness increased to the performance of approximately 93% of the guideline's recommended actions, when using the DSS mode. With respect to correctness, approximately 94.5% of the clinicians' decisions in the non-DSS mode were correct. However, these included 68% of the actions that were correct but redundant, given the patient's data (e.g., repeating tests that had been performed), and 27% of the actions, which were necessary in the context of the GL and of the given scenario. Only 5.5% of the decisions were definite errors. In the DSS mode, 94% of the clinicians' decisions were correct, which included 3% that were correct but redundant, and 91% of the actions that were correct and necessary in the context of the GL and of the given scenario. Only 6% of the DSS-mode decisions were erroneous. The DSS was assessed by the clinicians as potentially useful. Support from the GL-based DSS led to uniformity in the quality of the decisions, regardless of the particular clinician, any particular clinical scenario, any particular decision point, or any decision type within the scenarios. Using the DSS dramatically enhances completeness (i.e., performance of guideline-based recommendations) and seems to prevent the performance of most of the redundant actions, but does not seem to affect the rate of performance of incorrect actions. The redundancy rate is enhanced by similar recent findings in recent studies. Clinicians mostly find this support to be potentially useful for their daily practice. A continuous-care GL-based DSS, such as the Picard DSS engine, has the potential to prevent most errors of omission by ensuring uniformly high quality of clinical decision making (relative to a GL-based norm), due to the increased adherence (i.e., completeness) to the GL, and most of the errors of commission that increase therapy costs, by reducing the rate of redundant actions. However, to prevent clinical errors of commission, the DSS needs to be accompanied by additional modules, such as automated control of the quality of the physician's actual actions. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Systematic Analysis of the Decision Rules of Traditional Chinese Medicine

PubMed Central

Bin-Rong, Ma; Xi-Yuan, Jiang; Su-Ming, Liso; Huai-ning, Zhu; Xiu-ru, Lin

1981-01-01

Chinese traditional medicine has evolved over many centuries, and has accumulated a body of observed relationships between symptoms, signs and prognoses, and the efficacy of alternative treatments and prescriptions. With the assistance of a computer-based clinical data base for recording the diagnostic and therapeutic practice of skilled practitioners of Chinese traditional medicine, a systematic program is being conducted to identify and define the clinical decision-making rules that underlie current practice.

An IT Architecture for Systems Medicine.

PubMed

Ganzinger, Matthias; Gietzelt, Matthias; Karmen, Christian; Firnkorn, Daniel; Knaup, Petra

2015-01-01

Systems medicine aims to support treatment of complex diseases like cancer by integrating all available data for the disease. To provide such a decision support in clinical practice, a suitable IT architecture is necessary. We suggest a generic architecture comprised of the following three layers: data representation, decision support, and user interface. For the systems medicine research project "Clinically-applicable, omics-based assessment of survival, side effects, and targets in multiple myeloma" (CLIOMMICS) we developed a concrete instance of the generic architecture. We use i2b2 for representing the harmonized data. Since no deterministic model exists for multiple myeloma we use case-based reasoning for decision support. For clinical practice, visualizations of the results must be intuitive and clear. At the same time, they must communicate the uncertainty immanent in stochastic processes. Thus, we develop a specific user interface for systems medicine based on the web portal software Liferay.

Enabling Cross-Platform Clinical Decision Support through Web-Based Decision Support in Commercial Electronic Health Record Systems: Proposal and Evaluation of Initial Prototype Implementations

PubMed Central

Zhang, Mingyuan; Velasco, Ferdinand T.; Musser, R. Clayton; Kawamoto, Kensaku

2013-01-01

Enabling clinical decision support (CDS) across multiple electronic health record (EHR) systems has been a desired but largely unattained aim of clinical informatics, especially in commercial EHR systems. A potential opportunity for enabling such scalable CDS is to leverage vendor-supported, Web-based CDS development platforms along with vendor-supported application programming interfaces (APIs). Here, we propose a potential staged approach for enabling such scalable CDS, starting with the use of custom EHR APIs and moving towards standardized EHR APIs to facilitate interoperability. We analyzed three commercial EHR systems for their capabilities to support the proposed approach, and we implemented prototypes in all three systems. Based on these analyses and prototype implementations, we conclude that the approach proposed is feasible, already supported by several major commercial EHR vendors, and potentially capable of enabling cross-platform CDS at scale. PMID:24551426

Evidence-based decision-making as a practice-based learning skill: a pilot study.

PubMed

Falzer, Paul R; Garman, D Melissa

2012-03-01

As physicians are being trained to adapt their practices to the needs and experience of patients, initiatives to standardize care have been gaining momentum. The resulting conflict can be addressed through a practice-based learning and improvement (PBL) program that develops competency in using treatment guidelines as decision aids and incorporating patient-specific information into treatment recommendations. This article describes and tests a program that is consistent with the ACGME's multilevel competency-based approach, targets students at four levels of training, and features progressive learning objectives and assessments. The program was pilot-tested with 22 paid volunteer psychiatric residents and fellows. They were introduced to a schizophrenia treatment guideline and reviewed six case vignettes of varying complexity. PBL assessments were based on how treatment recommendations were influenced by clinical and patient-specific factors. The task permitted separate assessments of learning objectives all four training levels. Among the key findings at each level, most participants found the treatment guideline helpful in making treatment decisions. Recommendations were influenced by guideline-based assessment criteria and other clinical features. They were also influenced by patients' perceptions of their illness, patient-based progress assessments, and complications such as stressors and coping patterns. Recommendations were strongly influenced by incongruence between clinical facts and patient experience. Practical understanding of how patient experience joins with clinical knowledge can enhance the use of treatment guidelines as decision tools and enable clinicians to appreciate more fully how and why patients' perceptions of their illness should influence treatment recommendations. This PBL program can assist training facilities in preparing students to cope with contradictory demands to both standardize and adapt their practice. The program can be modified to accommodate various disorders and a range of clinical factors and patient-specific complications.

Proposed Clinical Decision Rules to Diagnose Acute Rhinosinusitis Among Adults in Primary Care.

PubMed

Ebell, Mark H; Hansen, Jens Georg

2017-07-01

To reduce inappropriate antibiotic prescribing, we sought to develop a clinical decision rule for the diagnosis of acute rhinosinusitis and acute bacterial rhinosinusitis. Multivariate analysis and classification and regression tree (CART) analysis were used to develop clinical decision rules for the diagnosis of acute rhinosinusitis, defined using 3 different reference standards (purulent antral puncture fluid or abnormal finding on a computed tomographic (CT) scan; for acute bacterial rhinosinusitis, we used a positive bacterial culture of antral fluid). Signs, symptoms, C-reactive protein (CRP), and reference standard tests were prospectively recorded in 175 Danish patients aged 18 to 65 years seeking care for suspected acute rhinosinusitis. For each reference standard, we developed 2 clinical decision rules: a point score based on a logistic regression model and an algorithm based on a CART model. We identified low-, moderate-, and high-risk groups for acute rhinosinusitis or acute bacterial rhinosinusitis for each clinical decision rule. The point scores each had between 5 and 6 predictors, and an area under the receiver operating characteristic curve (AUROCC) between 0.721 and 0.767. For positive bacterial culture as the reference standard, low-, moderate-, and high-risk groups had a 16%, 49%, and 73% likelihood of acute bacterial rhinosinusitis, respectively. CART models had an AUROCC ranging from 0.783 to 0.827. For positive bacterial culture as the reference standard, low-, moderate-, and high-risk groups had a likelihood of acute bacterial rhinosinusitis of 6%, 31%, and 59% respectively. We have developed a series of clinical decision rules integrating signs, symptoms, and CRP to diagnose acute rhinosinusitis and acute bacterial rhinosinusitis with good accuracy. They now require prospective validation and an assessment of their effect on clinical and process outcomes. © 2017 Annals of Family Medicine, Inc.

Strategies to facilitate shared decision-making about pediatric oncology clinical trial enrollment: A systematic review.

PubMed

Robertson, Eden G; Wakefield, Claire E; Signorelli, Christina; Cohn, Richard J; Patenaude, Andrea; Foster, Claire; Pettit, Tristan; Fardell, Joanna E

2018-07-01

We conducted a systematic review to identify the strategies that have been recommended in the literature to facilitate shared decision-making regarding enrolment in pediatric oncology clinical trials. We searched seven databases for peer-reviewed literature, published 1990-2017. Of 924 articles identified, 17 studies were eligible for the review. We assessed study quality using the 'Mixed-Methods Appraisal Tool'. We coded the results and discussions of papers line-by-line using nVivo software. We categorized strategies thematically. Five main themes emerged: 1) decision-making as a process, 2) individuality of the process; 3) information provision, 4) the role of communication, or 5) decision and psychosocial support. Families should have adequate time to make a decision. HCPs should elicit parents' and patients' preferences for level of information and decision involvement. Information should be clear and provided in multiple modalities. Articles also recommended providing training for healthcare professionals and access to psychosocial support for families. High quality, individually-tailored information, open communication and psychosocial support appear vital in supporting decision-making regarding enrollment in clinical trials. These data will usefully inform future decision-making interventions/tools to support families making clinical trial decisions. A solid evidence-base for effective strategies which facilitate shared decision-making is needed. Copyright © 2018 Elsevier B.V. All rights reserved.

A Data Model for Teleconsultation in Managing High-Risk Pregnancies: Design and Preliminary Evaluation

PubMed Central

Deldar, Kolsoum

2017-01-01

Background Teleconsultation is a guarantor for virtual supervision of clinical professors on clinical decisions made by medical residents in teaching hospitals. Type, format, volume, and quality of exchanged information have a great influence on the quality of remote clinical decisions or tele-decisions. Thus, it is necessary to develop a reliable and standard model for these clinical relationships. Objective The goal of this study was to design and evaluate a data model for teleconsultation in the management of high-risk pregnancies. Methods This study was implemented in three phases. In the first phase, a systematic review, a qualitative study, and a Delphi approach were done in selected teaching hospitals. Systematic extraction and localization of diagnostic items to develop the tele-decision clinical archetypes were performed as the second phase. Finally, the developed model was evaluated using predefined consultation scenarios. Results Our review study has shown that present medical consultations have no specific structure or template for patient information exchange. Furthermore, there are many challenges in the remote medical decision-making process, and some of them are related to the lack of the mentioned structure. The evaluation phase of our research has shown that data quality (P<.001), adequacy (P<.001), organization (P<.001), confidence (P<.001), and convenience (P<.001) had more scores in archetype-based consultation scenarios compared with routine-based ones. Conclusions Our archetype-based model could acquire better and higher scores in the data quality, adequacy, organization, confidence, and convenience dimensions than ones with routine scenarios. It is probable that the suggested archetype-based teleconsultation model may improve the quality of physician-physician remote medical consultations. PMID:29242181

Treatment algorithms and protocolized care.

PubMed

Morris, Alan H

2003-06-01

Excess information in complex ICU environments exceeds human decision-making limits and likely contributes to unnecessary variation in clinical care, increasing the likelihood of clinical errors. I reviewed recent critical care clinical trials searching for information about the impact of protocol use on clinically pertinent outcomes. Several recently published clinical trials illustrate the importance of distinguishing efficacy and effectiveness trials. One of these trials illustrates the danger of conducting effectiveness trials before the efficacy of an intervention is established. The trials also illustrate the importance of distinguishing guidelines and inadequately explicit protocols from adequately explicit protocols. Only adequately explicit protocols contain enough detail to lead different clinicians to the same decision when faced with the same clinical scenario. Differences between guidelines and protocols are important. Guidelines lack detail and provide general guidance that requires clinicians to fill in many gaps. Computerized or paper-based protocols are detailed and, when used for complex clinical ICU problems, can generate patient-specific, evidence-based therapy instructions that can be carried out by different clinicians with almost no interclinician variability. Individualization of patient therapy can be preserved by these protocols when they are driven by individual patient data. Explicit decision-support tools (eg, guidelines and protocols) have favorable effects on clinician and patient outcomes and can reduce the variation in clinical practice. Guidelines and protocols that aid ICU decision makers should be more widely distributed.

Effects of additional team-based learning on students' clinical reasoning skills: a pilot study.

PubMed

Jost, Meike; Brüstle, Peter; Giesler, Marianne; Rijntjes, Michel; Brich, Jochen

2017-07-14

In the field of Neurology good clinical reasoning skills are essential for successful diagnosing and treatment. Team-based learning (TBL), an active learning and small group instructional strategy, is a promising method for fostering these skills. The aim of this pilot study was to examine the effects of a supplementary TBL-class on students' clinical decision-making skills. Fourth- and fifth-year medical students participated in this pilot study (static-group comparison design). The non-treatment group (n = 15) did not receive any additional training beyond regular teaching in the neurology course. The treatment group (n = 11) took part in a supplementary TBL-class optimized for teaching clinical reasoning in addition to the regular teaching in the neurology course. Clinical decision making skills were assessed using a key-feature problem examination. Factual and conceptual knowledge was assessed by a multiple-choice question examination. The TBL-group performed significantly better than the non-TBL-group (p = 0.026) in the key-feature problem examination. No significant differences between the results of the multiple-choice question examination of both groups were found. In this pilot study participants of a supplementary TBL-class significantly improved clinical decision-making skills, indicating that TBL may be an appropriate method for teaching clinical decision making in neurology. Further research is needed for replication in larger groups and other clinical fields.

Analysis of Nursing Clinical Decision Support Requests and Strategic Plan in a Large Academic Health System.

PubMed

Whalen, Kimberly; Bavuso, Karen; Bouyer-Ferullo, Sharon; Goldsmith, Denise; Fairbanks, Amanda; Gesner, Emily; Lagor, Charles; Collins, Sarah

2016-01-01

To understand requests for nursing Clinical Decision Support (CDS) interventions at a large integrated health system undergoing vendor-based EHR implementation. In addition, to establish a process to guide both short-term implementation and long-term strategic goals to meet nursing CDS needs. We conducted an environmental scan to understand current state of nursing CDS over three months. The environmental scan consisted of a literature review and an analysis of CDS requests received from across our health system. We identified existing high priority CDS and paper-based tools used in nursing practice at our health system that guide decision-making. A total of 46 nursing CDS requests were received. Fifty-six percent (n=26) were specific to a clinical specialty; 22 percent (n=10) were focused on facilitating clinical consults in the inpatient setting. "Risk Assessments/Risk Reduction/Promotion of Healthy Habits" (n=23) was the most requested High Priority Category received for nursing CDS. A continuum of types of nursing CDS needs emerged using the Data-Information-Knowledge-Wisdom Conceptual Framework: 1) facilitating data capture, 2) meeting information needs, 3) guiding knowledge-based decision making, and 4) exposing analytics for wisdom-based clinical interpretation by the nurse. Identifying and prioritizing paper-based tools that can be modified into electronic CDS is a challenge. CDS strategy is an evolving process that relies on close collaboration and engagement with clinical sites for short-term implementation and should be incorporated into a long-term strategic plan that can be optimized and achieved overtime. The Data-Information-Knowledge-Wisdom Conceptual Framework in conjunction with the High Priority Categories established may be a useful tool to guide a strategic approach for meeting short-term nursing CDS needs and aligning with the organizational strategic plan.

[Which research is needed to support clinical decision-making on integrative medicine? Can comparative effectiveness research close the gap?].

PubMed

Witt, Claudia M; Huang, Wen-jing; Lao, Lixing; Berman, Brian M

2013-08-01

In clinical research on complementary and integrative medicine, experts and scientists have often pursued a research agenda in spite of an incomplete understanding of the needs of end users. Consequently, the majority of previous clinical trials have mainly assessed the efficacy of interventions. Scant data is available on their effectiveness. Comparative effectiveness research (CER) promises to support decision makers by generating evidence that compares the benefits and harms of best care options. This evidence, more generalizable than evidence generated by traditional randomized clinical trials (RCTs), is better suited to inform real-world care decisions. An emphasis on CER supports the development of the evidence base for clinical and policy decision-making. Whereas in most areas of complementary and integrative medicine data on CER is scarce, available acupuncture research already contributes to CER evidence. This paper will introduce CER and make suggestions for future research.

Clinical genomics information management software linking cancer genome sequence and clinical decisions.

PubMed

Watt, Stuart; Jiao, Wei; Brown, Andrew M K; Petrocelli, Teresa; Tran, Ben; Zhang, Tong; McPherson, John D; Kamel-Reid, Suzanne; Bedard, Philippe L; Onetto, Nicole; Hudson, Thomas J; Dancey, Janet; Siu, Lillian L; Stein, Lincoln; Ferretti, Vincent

2013-09-01

Using sequencing information to guide clinical decision-making requires coordination of a diverse set of people and activities. In clinical genomics, the process typically includes sample acquisition, template preparation, genome data generation, analysis to identify and confirm variant alleles, interpretation of clinical significance, and reporting to clinicians. We describe a software application developed within a clinical genomics study, to support this entire process. The software application tracks patients, samples, genomic results, decisions and reports across the cohort, monitors progress and sends reminders, and works alongside an electronic data capture system for the trial's clinical and genomic data. It incorporates systems to read, store, analyze and consolidate sequencing results from multiple technologies, and provides a curated knowledge base of tumor mutation frequency (from the COSMIC database) annotated with clinical significance and drug sensitivity to generate reports for clinicians. By supporting the entire process, the application provides deep support for clinical decision making, enabling the generation of relevant guidance in reports for verification by an expert panel prior to forwarding to the treating physician. Copyright © 2013 Elsevier Inc. All rights reserved.

Using family paradigms to improve evidence-based practice.

PubMed

Hidecker, Mary Jo Cooley; Jones, Rebecca S; Imig, David R; Villarruel, Francisco A

2009-08-01

Evidence-based practice (EBP) describes clinical decision making using research, clinical experience, and client values. For family-centered practices, the client's family is integral to this process. This article proposes that using family paradigms, a family science framework, may help elicit and understand client/family values within family-centered EBP. This article describes the family paradigms framework: 4 classic paradigms of "closed," "random," "open," and "synchronous." Its applicability to family-centered EBP is proposed using augmentative and alternative communication examples. A family-centered approach to EBP requires families to be an integral part of clinical decision making, but some families may need assistance in enumerating their views and values. Family paradigms (which consider how a family uses its resources of time, space, energy, and material in the pursuit of its goals of control, affect, meaning, and content) may be a way to elicit family values and preferences relevant to clinical decisions. Family and client values can be incorporated throughout the EBP steps. Considering family paradigms may increase awareness and understanding of how families' views of their goals and resources affect clinical decisions. Further research is needed into both the processes and effectiveness of using family paradigms to conduct family-centered EBP.

An Environment for Guideline-based Decision Support Systems for Outpatients Monitoring.

PubMed

Zini, Elisa M; Lanzola, Giordano; Bossi, Paolo; Quaglini, Silvana

2017-08-11

We propose an architecture for monitoring outpatients that relies on mobile technologies for acquiring data. The goal is to better control the onset of possible side effects between the scheduled visits at the clinic. We analyze the architectural components required to ensure a high level of abstraction from data. Clinical practice guidelines were formalized with Alium, an authoring tool based on the PROforma language, using SNOMED-CT as a terminology standard. The Alium engine is accessible through a set of APIs that may be leveraged for implementing an application based on standard web technologies to be used by doctors at the clinic. Data sent by patients using mobile devices need to be complemented with those already available in the Electronic Health Record to generate personalized recommendations. Thus a middleware pursuing data abstraction is required. To comply with current standards, we adopted the HL7 Virtual Medical Record for Clinical Decision Support Logical Model, Release 2. The developed architecture for monitoring outpatients includes: (1) a guideline-based Decision Support System accessible through a web application that helps the doctors with prevention, diagnosis and treatment of therapy side effects; (2) an application for mobile devices, which allows patients to regularly send data to the clinic. In order to tailor the monitoring procedures to the specific patient, the Decision Support System also helps physicians with the configuration of the mobile application, suggesting the data to be collected and the associated collection frequency that may change over time, according to the individual patient's conditions. A proof of concept has been developed with a system for monitoring the side effects of chemo-radiotherapy in head and neck cancer patients. Our environment introduces two main innovation elements with respect to similar works available in the literature. First, in order to meet the specific patients' needs, in our work the Decision Support System also helps the physicians in properly configuring the mobile application. Then the Decision Support System is also continuously fed by patient-reported outcomes.

Classifying clinical decision making: a unifying approach.

PubMed

Buckingham, C D; Adams, A

2000-10-01

This is the first of two linked papers exploring decision making in nursing which integrate research evidence from different clinical and academic disciplines. Currently there are many decision-making theories, each with their own distinctive concepts and terminology, and there is a tendency for separate disciplines to view their own decision-making processes as unique. Identifying good nursing decisions and where improvements can be made is therefore problematic, and this can undermine clinical and organizational effectiveness, as well as nurses' professional status. Within the unifying framework of psychological classification, the overall aim of the two papers is to clarify and compare terms, concepts and processes identified in a diversity of decision-making theories, and to demonstrate their underlying similarities. It is argued that the range of explanations used across disciplines can usefully be re-conceptualized as classification behaviour. This paper explores problems arising from multiple theories of decision making being applied to separate clinical disciplines. Attention is given to detrimental effects on nursing practice within the context of multidisciplinary health-care organizations and the changing role of nurses. The different theories are outlined and difficulties in applying them to nursing decisions highlighted. An alternative approach based on a general model of classification is then presented in detail to introduce its terminology and the unifying framework for interpreting all types of decisions. The classification model is used to provide the context for relating alternative philosophical approaches and to define decision-making activities common to all clinical domains. This may benefit nurses by improving multidisciplinary collaboration and weakening clinical elitism.

An integrative model for in-silico clinical-genomics discovery science.

PubMed

Lussier, Yves A; Sarkar, Indra Nell; Cantor, Michael

2002-01-01

Human Genome discovery research has set the pace for Post-Genomic Discovery Research. While post-genomic fields focused at the molecular level are intensively pursued, little effort is being deployed in the later stages of molecular medicine discovery research, such as clinical-genomics. The objective of this study is to demonstrate the relevance and significance of integrating mainstream clinical informatics decision support systems to current bioinformatics genomic discovery science. This paper is a feasibility study of an original model enabling novel "in-silico" clinical-genomic discovery science and that demonstrates its feasibility. This model is designed to mediate queries among clinical and genomic knowledge bases with relevant bioinformatic analytic tools (e.g. gene clustering). Briefly, trait-disease-gene relationships were successfully illustrated using QMR, OMIM, SNOMED-RT, GeneCluster and TreeView. The analyses were visualized as two-dimensional dendrograms of clinical observations clustered around genes. To our knowledge, this is the first study using knowledge bases of clinical decision support systems for genomic discovery. Although this study is a proof of principle, it provides a framework for the development of clinical decision-support-system driven, high-throughput clinical-genomic technologies which could potentially unveil significant high-level functions of genes.

Helping Health Care Providers and Clinical Scientists Understand Apparently Irrational Policy Decisions.

PubMed

Demeter, Sandor J

2016-12-21

Health care providers (HCP) and clinical scientists (CS) are generally most comfortable using evidence-based rational decision-making models. They become very frustrated when policymakers make decisions that, on the surface, seem irrational and unreasonable. However, such decisions usually make sense when analysed properly. The goal of this paper to provide a basic theoretical understanding of major policy models, to illustrate which models are most prevalent in publicly funded health care systems, and to propose a policy analysis framework to better understand the elements that drive policy decision-making. The proposed policy framework will also assist HCP and CS achieve greater success with their own proposals.

[The historical background and present development of evidence-based healthcare and clinical nursing].

PubMed

Tsai, Jung-Mei

2014-12-01

Evidence-based healthcare (EBHC) emphasizes the integration of the best research evidence with patient values, specialist suggestions, and clinical circumstances during the process of clinical decision-making. EBHC is a recognized core competency in modern healthcare. Nursing is a professional discipline of empirical science that thrives in an environment marked by advances in knowledge and technology in medicine as well as in nursing. Clinical nurses must elevate their skills and professional qualifications, provide efficient and quality health services, and promote their proficiency in EBHC. The Institute of Medicine in the United States indicates that evidence-based research results often fail to disseminate efficiently to clinical decision makers. This problem highlights the importance of better promoting the evidence-based healthcare fundamentals and competencies to frontline clinical nurses. This article describes the historical background and present development of evidence-based healthcare from the perspective of modern clinical nursing in light of the importance of evidence-based healthcare in clinical nursing; describes the factors associated with evidence-based healthcare promotion; and suggests strategies and policies that may improve the promotion and application of EBHC in clinical settings. The authors hope that this paper provides a reference for efforts to improve clinical nursing in the realms of EBHC training, promotion, and application.

Comparing wavefront-optimized, wavefront-guided and topography-guided laser vision correction: clinical outcomes using an objective decision tree.

PubMed

Stonecipher, Karl; Parrish, Joseph; Stonecipher, Megan

2018-05-18

This review is intended to update and educate the reader on the currently available options for laser vision correction, more specifically, laser-assisted in-situ keratomileusis (LASIK). In addition, some related clinical outcomes data from over 1000 cases performed over a 1-year are presented to highlight some differences between the various treatment profiles currently available including the rapidity of visual recovery. The cases in question were performed on the basis of a decision tree to segregate patients on the basis of anatomical, topographic and aberrometry findings; the decision tree was formulated based on the data available in some of the reviewed articles. Numerous recent studies reported in the literature provide data related to the risks and benefits of LASIK; alternatives to a laser refractive procedure are also discussed. The results from these studies have been used to prepare a decision tree to assist the surgeon in choosing the best option for the patient based on the data from several standard preoperative diagnostic tests. The data presented here should aid surgeons in understanding the effects of currently available LASIK treatment profiles. Surgeons should also be able to appreciate how the findings were used to create a decision tree to help choose the most appropriate treatment profile for patients. Finally, the retrospective evaluation of clinical outcomes based on the decision tree should provide surgeons with a realistic expectation for their own outcomes should they adopt such a decision tree in their own practice.

Adjuvant chemotherapy decisions in clinical practice for early-stage node-negative, estrogen receptor-positive, HER2-negative breast cancer: challenges and considerations.

PubMed

Nagaraj, Gayathri; Ma, Cynthia X

2013-03-01

Decisions regarding adjuvant chemotherapy for patients with estrogen receptor (ER)-positive, HER2-negative, lymph node-negative breast cancer have traditionally relied on clinical and pathologic parameters. However, the molecular heterogeneity and the complex tumor genome demand more sophisticated approaches to the problem. Several multigene-based assays have been developed to better prognosticate the risk of recurrence and death and predict benefit of therapy in this patient population. Oncologists are often faced with the challenge of incorporating these various complex genome-based biomarkers along with the traditional biomarkers in clinical decision-making. The NCCN Clinical Practice Guidelines in Oncology for Breast Cancer are helpful in providing a general recommendation. However, uncertainty remains in the absence of definitive data for various clinical scenarios. This case report describes a postmenopausal woman with stage I breast cancer that is low-grade and ER-rich, and has an intermediate Oncotype DX recurrence score of 28.

Clinical decision support for personalized medicine: an opportunity for pharmacist-physician collaboration.

PubMed

Barlow, Jane F

2012-06-01

Pharmacogenomics has significant potential to improve the efficacy and safety of medication therapy, but it requires new expertise and adds a new layer of complexity for all healthcare professionals. Pharmacists and pharmacy management systems can play a leading role in providing clinical decision support for the use and interpretation of pharmacogenomic tests. To serve this role effectively, pharmacists will need to expand their expertise in the emerging field of clinical pharmacogenomics. Pharmacy-based clinical programs can expedite the use of pharmacogenomic testing, help physicians interpret the test results and identify future medication risks associated with the patient's phenotype. Over time, some of these functions can be embedded in clinical decision support systems as part of the broader automation of the healthcare system.

[Modeling in value-based medicine].

PubMed

Neubauer, A S; Hirneiss, C; Kampik, A

2010-03-01

Modeling plays an important role in value-based medicine (VBM). It allows decision support by predicting potential clinical and economic consequences, frequently combining different sources of evidence. Based on relevant publications and examples focusing on ophthalmology the key economic modeling methods are explained and definitions are given. The most frequently applied model types are decision trees, Markov models, and discrete event simulation (DES) models. Model validation includes besides verifying internal validity comparison with other models (external validity) and ideally validation of its predictive properties. The existing uncertainty with any modeling should be clearly stated. This is true for economic modeling in VBM as well as when using disease risk models to support clinical decisions. In economic modeling uni- and multivariate sensitivity analyses are usually applied; the key concepts here are tornado plots and cost-effectiveness acceptability curves. Given the existing uncertainty, modeling helps to make better informed decisions than without this additional information.

Understanding clinical work practices for cross-boundary decision support in e-health.

PubMed

Tawfik, Hissam; Anya, Obinna; Nagar, Atulya K

2012-07-01

One of the major concerns of research in integrated healthcare information systems is to enable decision support among clinicians across boundaries of organizations and regional workgroups. A necessary precursor, however, is to facilitate the construction of appropriate awareness of local clinical practices, including a clinician's actual cognitive capabilities, peculiar workplace circumstances, and specific patient-centered needs based on real-world clinical contexts across work settings. In this paper, a user-centered study aimed to investigate clinical practices across three different geographical areas-the U.K., the UAE and Nigeria-is presented. The findings indicate that differences in clinical practices among clinicians are associated with differences in local work contexts across work settings, but are moderated by adherence to best practice guidelines and the need for patient-centered care. The study further reveals that an awareness especially of the ontological, stereotypical, and situated practices plays a crucial role in adapting knowledge for cross-boundary decision support. The paper then outlines a set of design guidelines for the development of enterprise information systems for e-health. Based on the guidelines, the paper proposes the conceptual design of CaDHealth, a practice-centered framework for making sense of clinical practices across work settings for effective cross-boundary e-health decision support.

Effects of reflection on clinical decision-making of intensive care unit nurses.

PubMed

Razieh, Shahrokhi; Somayeh, Ghafari; Fariba, Haghani

2018-07-01

Nurses are one of the most influential factors in overcoming the main challenges faced by health systems throughout the world. Every health system should, hence, empower nurses in clinical judgment and decision-making skills. This study evaluated the effects of implementing Tanner's reflection method on clinical decision-making of nurses working in an intensive care unit (ICU). This study used an experimental, pretest, posttest design. The setting was the intensive care unit of Amin Hospital Isfahan, Iran. The convenience sample included 60 nurses working in the ICU of Amin Hospital (Isfahan, Iran). This clinical trial was performed on 60 nurses working in the ICU of Amin Hospital (Isfahan, Iran). The nurses were selected by census sampling and randomly allocated to either the case or the control group. Data were collected using a questionnaire containing demographic characteristics and the clinical decision-making scale developed by Laurie and Salantera (NDMI-14). The questionnaire was completed before and one week after the intervention. The data were analyzed using SPSS 21.0. The two groups were not significantly different in terms of the level and mean scores of clinical decision-making before the intervention (P = 0.786). Based on the results of independent t-test, the mean score of clinical decision-making one week after the intervention was significantly higher in the case group than in the control group (P = 0.009; t = -2.69). The results of Mann Whitney test showed that one week after the intervention, the nurses' level of clinical decision-making in the case group rose to the next level (P = 0.001). Reflection could improve the clinical decision-making of ICU nurses. It is, thus, recommended to incorporate this method into the nursing curriculum and care practices. Copyright © 2018. Published by Elsevier Ltd.

Knowledge Translation and Barriers to Imaging Optimization in the Emergency Department: A Research Agenda.

PubMed

Probst, Marc A; Dayan, Peter S; Raja, Ali S; Slovis, Benjamin H; Yadav, Kabir; Lam, Samuel H; Shapiro, Jason S; Farris, Coreen; Babcock, Charlene I; Griffey, Richard T; Robey, Thomas E; Fortin, Emily M; Johnson, Jamlik O; Chong, Suzanne T; Davenport, Moira; Grigat, Daniel W; Lang, Eddy L

2015-12-01

Researchers have attempted to optimize imaging utilization by describing which clinical variables are more predictive of acute disease and, conversely, what combination of variables can obviate the need for imaging. These results are then used to develop evidence-based clinical pathways, clinical decision instruments, and clinical practice guidelines. Despite the validation of these results in subsequent studies, with some demonstrating improved outcomes, their actual use is often limited. This article outlines a research agenda to promote the dissemination and implementation (also known as knowledge translation) of evidence-based interventions for emergency department (ED) imaging, i.e., clinical pathways, clinical decision instruments, and clinical practice guidelines. We convened a multidisciplinary group of stakeholders and held online and telephone discussions over a 6-month period culminating in an in-person meeting at the 2015 Academic Emergency Medicine consensus conference. We identified the following four overarching research questions: 1) what determinants (barriers and facilitators) influence emergency physicians' use of evidence-based interventions when ordering imaging in the ED; 2) what implementation strategies at the institutional level can improve the use of evidence-based interventions for ED imaging; 3) what interventions at the health care policy level can facilitate the adoption of evidence-based interventions for ED imaging; and 4) how can health information technology, including electronic health records, clinical decision support, and health information exchanges, be used to increase awareness, use, and adherence to evidence-based interventions for ED imaging? Advancing research that addresses these questions will provide valuable information as to how we can use evidence-based interventions to optimize imaging utilization and ultimately improve patient care. © 2015 by the Society for Academic Emergency Medicine.

[Why controlled studies may lead to misleading and unconfirmed therapeutic concepts--a critical view of evidence-based medicine].

PubMed

Flachskampf, F A

2002-03-01

The concept of evidence-based medicine has gathered widespread support during recent years. While this concept has clear merits in compiling and qualifying up-to-date information for clinical decisions, it should be viewed with caution as the sole valid knowledge source for clinical decision-making. The limitations of such an approach are particularly striking when reviewing two key developments in modern cardiology, fibrinolysis and acute percutaneous intervention in acute myocardial infarction. In both cases, early studies and meta-analyses showed no benefit for these therapeutic interventions over earlier treatment. Only after further refinement (mainly in dosage, time window, concomitant heparin therapy for fibrinolysis, and the introduction of stents and IIb/IIIa inhibitors for acute intervention) did these therapies become universally acknowledged. It is therefore crucial to understand that especially for physicians actively participating in the development of a clinical field clinical decisions cannot be exclusively based on published evidence. Another important problem to consider is the time gap between the emergence of new therapies and the publication and reception by the medical audience, in particular in rapidly evolving fields as cardiology. While it is clear that clinical decision-making must be backed by solid knowledge of the published evidence, in particular the specialist involved in-depth in the field may use not yet proven therapeutic concepts and measures to the patient's advantage.

Intuition: A Concept Analysis.

PubMed

Chilcote, Deborah R

2017-01-01

The purpose of this article is to conceptually examine intuition; identify the importance of intuition in nursing education, clinical practice, and patient care; encourage acceptance of the use of intuition; and add to the body of nursing knowledge. Nurses often report using intuition when making clinical decisions. Intuition is a rapid, unconscious process based in global knowledge that views the patient holistically while synthesizing information to improve patient outcomes. However, with the advent of evidence-based practice (EBP), the use of intuition has become undervalued in nursing. Walker and Avant's framework was used to analyze intuition. A literature search from 1987 to 2014 was conducted using the following keywords: intuition, intuition and nursing, clinical decision making, clinical decision making and intuition, patient outcomes, EBP, and analytical thinking. The use of intuition is reported by nurses, but is not legitimized within the nursing profession. Defining attributes of intuition are an unconscious, holistic knowledge gathered without using an analytical process and knowledge derived through synthesis, not analysis. Consequences include verification of intuition through an analytical process and translating that knowledge into a course of action. This article supports the use of intuition in nursing by offering clarity to the concept, adds to the nursing knowledge base, encourages a holistic view of the patient during clinical decision making, and encourages nurse educators to promote the use of intuition. © 2016 Wiley Periodicals, Inc.

Clinical Assistant Diagnosis for Electronic Medical Record Based on Convolutional Neural Network.

PubMed

Yang, Zhongliang; Huang, Yongfeng; Jiang, Yiran; Sun, Yuxi; Zhang, Yu-Jin; Luo, Pengcheng

2018-04-20

Automatically extracting useful information from electronic medical records along with conducting disease diagnoses is a promising task for both clinical decision support(CDS) and neural language processing(NLP). Most of the existing systems are based on artificially constructed knowledge bases, and then auxiliary diagnosis is done by rule matching. In this study, we present a clinical intelligent decision approach based on Convolutional Neural Networks(CNN), which can automatically extract high-level semantic information of electronic medical records and then perform automatic diagnosis without artificial construction of rules or knowledge bases. We use collected 18,590 copies of the real-world clinical electronic medical records to train and test the proposed model. Experimental results show that the proposed model can achieve 98.67% accuracy and 96.02% recall, which strongly supports that using convolutional neural network to automatically learn high-level semantic features of electronic medical records and then conduct assist diagnosis is feasible and effective.

Clinical Decision-Making in Community Children's Mental Health: Using Innovative Methods to Compare Clinicians With and Without Training in Evidence-Based Treatment.

PubMed

Baker-Ericzén, Mary J; Jenkins, Melissa M; Park, Soojin; Garland, Ann F

2015-02-01

Mental health professionals' decision-making practice is an area of increasing interest and importance, especially in the pediatric research and clinical communities. The present study explored the role of prior training in evidence-based treatments on clinicians' assessment and treatment formulations using case vignettes. Specifically, study aims included using the Naturalistic Decision Making (NDM) cognitive theory to 1) examine potential associations between EBT training and decision-making processes (novice versus expert type), and 2) explore how client and family contextual information affects clinical decision-making. Forty-eight clinicians across two groups (EBT trained=14, Not EBT trained=34) participated. Clinicians were comparable on professional experience, demographics, and discipline. The quasi-experimental design used an analog "think aloud" method where clinicians read case vignettes about a child with disruptive behavior problems and verbalized case conceptualization and treatment planning out-loud. Responses were coded according to NDM theory. MANOVA results were significant for EBT training status such that EBT trained clinicians' displayed cognitive processes more closely aligned with "expert" decision-makers and non-EBT trained clinicians' decision processes were more similar to "novice" decision-makers, following NDM theory. Non-EBT trained clinicians assigned significantly more diagnoses, provided less detailed treatment plans and discussed fewer EBTs. Parent/family contextual information also appeared to influence decision-making. This study offers a preliminary investigation of the possible broader impacts of EBT training and potential associations with development of expert decision-making skills. Targeting clinicians' decision-making may be an important avenue to pursue within dissemination-implementation efforts in mental health practice.

Implementing pharmacogenomics decision support across seven European countries: The Ubiquitous Pharmacogenomics (U-PGx) project.

PubMed

Blagec, Kathrin; Koopmann, Rudolf; Crommentuijn-van Rhenen, Mandy; Holsappel, Inge; van der Wouden, Cathelijne H; Konta, Lidija; Xu, Hong; Steinberger, Daniela; Just, Enrico; Swen, Jesse J; Guchelaar, Henk-Jan; Samwald, Matthias

2018-02-09

Clinical pharmacogenomics (PGx) has the potential to make pharmacotherapy safer and more effective by utilizing genetic patient data for drug dosing and selection. However, widespread adoption of PGx depends on its successful integration into routine clinical care through clinical decision support tools, which is often hampered by insufficient or fragmented infrastructures. This paper describes the setup and implementation of a unique multimodal, multilingual clinical decision support intervention consisting of digital, paper-, and mobile-based tools that are deployed across implementation sites in seven European countries participating in the Ubiquitous PGx (U-PGx) project. © The Author(s) 2018. Published by Oxford University Press on behalf of the American Medical Informatics Association.

Protocol-based care: the standardisation of decision-making?

PubMed

Rycroft-Malone, Jo; Fontenla, Marina; Seers, Kate; Bick, Debra

2009-05-01

To explore how protocol-based care affects clinical decision-making. In the context of evidence-based practice, protocol-based care is a mechanism for facilitating the standardisation of care and streamlining decision-making through rationalising the information with which to make judgements and ultimately decisions. However, whether protocol-based care does, in the reality of practice, standardise decision-making is unknown. This paper reports on a study that explored the impact of protocol-based care on nurses' decision-making. Theoretically informed by realistic evaluation and the promoting action on research implementation in health services framework, a case study design using ethnographic methods was used. Two sites were purposively sampled; a diabetic and endocrine unit and a cardiac medical unit. Within each site, data collection included observation, postobservation semi-structured interviews with staff and patients, field notes, feedback sessions and document review. Data were inductively and thematically analysed. Decisions made by nurses in both sites were varied according to many different and interacting factors. While several standardised care approaches were available for use, in reality, a variety of information sources informed decision-making. The primary approach to knowledge exchange and acquisition was person-to-person; decision-making was a social activity. Rarely were standardised care approaches obviously referred to; nurses described following a mental flowchart, not necessarily linked to a particular guideline or protocol. When standardised care approaches were used, it was reported that they were used flexibly and particularised. While the logic of protocol-based care is algorithmic, in the reality of clinical practice, other sources of information supported nurses' decision-making process. This has significant implications for the political goal of standardisation. The successful implementation and judicious use of tools such as protocols and guidelines will likely be dependant on approaches that facilitate the development of nurses' decision-making processes in parallel to paying attention to the influence of context.

Predictors for reimbursement of oncology drugs in Belgium between 2002 and 2013.

PubMed

Pauwels, Kim; Huys, Isabelle; De Nys, Katelijne; Casteels, Minne; Simoens, Steven

2015-01-01

Price setting and reimbursement decisions regarding drugs are competence of individual member states in Europe. These decisions involve important trade-offs between social, ethical, clinical and economic criteria. The aim of this study was to investigate the relative importance of criteria for reimbursement of oncology drugs in Belgium. Reimbursement dossiers on oncology drugs for which reimbursement was applied between 2002 and 2013 were consulted. Multivariate logistic regression was performed. Results showed that clinical evidence and presence of alternative treatments have a significant impact on the reimbursement decisions. Evidence-based medicine still plays a role in Belgian reimbursement decision-making. In order to allow transition towards value-based medicine and avoid spending money on products with limited incremental benefit, therapeutic need at patient level need to be taken into account.

Involving clinical librarians at the point of care: results of a controlled intervention.

PubMed

Aitken, Elizabeth M; Powelson, Susan E; Reaume, Renée D; Ghali, William A

2011-12-01

To measure the effect of including a clinical librarian in the health care team on medical residents and clinical clerks. In 2009, medical residents and clinical clerks were preassigned to one of two patient care teams (intervention and control). Each team had a month-long rotation on the general medicine teaching unit. The clinical librarian joined the intervention team for morning intake, clinical rounding, or an afternoon patient list review, providing immediate literature searches, formal group instruction, informal bedside teaching, and/or individual mentoring for use of preappraised resources and evidence-based medicine search techniques. Both intervention and control teams completed pre and post surveys comparing their confidence levels and awareness of resources as well as their self-reported use of evidence for making patient care decisions. The nonintervention team was surveyed as the control group. The clinical librarian intervention had a significant positive effect on medical trainees' self-reported ability to independently locate and evaluate evidence resources to support patient care decisions. Notably, 30 of 34 (88%) reported having changed a treatment plan based on skills taught by the clinical librarian, and 27 of 34 (79%) changed a treatment plan based on the librarian's mediated search support. Clinical librarians on the care team led to positive effects on self-reported provider attitudes, provider information retrieval tendencies, and, notably, clinical decision making. Future research should evaluate economic effects of widespread implementation of on-site clinical librarians.

Medical Problem-Solving: A Critique of the Literature.

ERIC Educational Resources Information Center

McGuire, Christine H.

1985-01-01

Prescriptive, decision-analysis of medical problem-solving has been based on decision theory that involves calculation and manipulation of complex probability and utility values to arrive at optimal decisions that will maximize patient benefits. The studies offer a methodology for improving clinical judgment. (Author/MLW)

Assessing School Readiness for a Practice Arrangement Using Decision Tree Methodology.

ERIC Educational Resources Information Center

Barger, Sara E.

1998-01-01

Questions in a decision-tree address mission, faculty interest, administrative support, and practice plan as a way of assessing arrangements for nursing faculty's clinical practice. Decisions should be based on congruence between the human resource allocation and the reward systems. (SK)

Assessing clinical reasoning (ASCLIRE): Instrument development and validation.

PubMed

Kunina-Habenicht, Olga; Hautz, Wolf E; Knigge, Michel; Spies, Claudia; Ahlers, Olaf

2015-12-01

Clinical reasoning is an essential competency in medical education. This study aimed at developing and validating a test to assess diagnostic accuracy, collected information, and diagnostic decision time in clinical reasoning. A norm-referenced computer-based test for the assessment of clinical reasoning (ASCLIRE) was developed, integrating the entire clinical decision process. In a cross-sectional study participants were asked to choose as many diagnostic measures as they deemed necessary to diagnose the underlying disease of six different cases with acute or sub-acute dyspnea and provide a diagnosis. 283 students and 20 content experts participated. In addition to diagnostic accuracy, respective decision time and number of used relevant diagnostic measures were documented as distinct performance indicators. The empirical structure of the test was investigated using a structural equation modeling approach. Experts showed higher accuracy rates and lower decision times than students. In a cross-sectional comparison, the diagnostic accuracy of students improved with the year of study. Wrong diagnoses provided by our sample were comparable to wrong diagnoses in practice. We found an excellent fit for a model with three latent factors-diagnostic accuracy, decision time, and choice of relevant diagnostic information-with diagnostic accuracy showing no significant correlation with decision time. ASCLIRE considers decision time as an important performance indicator beneath diagnostic accuracy and provides evidence that clinical reasoning is a complex ability comprising diagnostic accuracy, decision time, and choice of relevant diagnostic information as three partly correlated but still distinct aspects.

Clinical, information and business process modeling to promote development of safe and flexible software.

PubMed

Liaw, Siaw-Teng; Deveny, Elizabeth; Morrison, Iain; Lewis, Bryn

2006-09-01

Using a factorial vignette survey and modeling methodology, we developed clinical and information models - incorporating evidence base, key concepts, relevant terms, decision-making and workflow needed to practice safely and effectively - to guide the development of an integrated rule-based knowledge module to support prescribing decisions in asthma. We identified workflows, decision-making factors, factor use, and clinician information requirements. The Unified Modeling Language (UML) and public domain software and knowledge engineering tools (e.g. Protégé) were used, with the Australian GP Data Model as the starting point for expressing information needs. A Web Services service-oriented architecture approach was adopted within which to express functional needs, and clinical processes and workflows were expressed in the Business Process Execution Language (BPEL). This formal analysis and modeling methodology to define and capture the process and logic of prescribing best practice in a reference implementation is fundamental to tackling deficiencies in prescribing decision support software.

“Smart Forms” in an Electronic Medical Record: Documentation-based Clinical Decision Support to Improve Disease Management

PubMed Central

Schnipper, Jeffrey L.; Linder, Jeffrey A.; Palchuk, Matvey B.; Einbinder, Jonathan S.; Li, Qi; Postilnik, Anatoly; Middleton, Blackford

2008-01-01

Clinical decision support systems (CDSS) integrated within Electronic Medical Records (EMR) hold the promise of improving healthcare quality. To date the effectiveness of CDSS has been less than expected, especially concerning the ambulatory management of chronic diseases. This is due, in part, to the fact that clinicians do not use CDSS fully. Barriers to clinicians' use of CDSS have included lack of integration into workflow, software usability issues, and relevance of the content to the patient at hand. At Partners HealthCare, we are developing “Smart Forms” to facilitate documentation-based clinical decision support. Rather than being interruptive in nature, the Smart Form enables writing a multi-problem visit note while capturing coded information and providing sophisticated decision support in the form of tailored recommendations for care. The current version of the Smart Form is designed around two chronic diseases: coronary artery disease and diabetes mellitus. The Smart Form has potential to improve the care of patients with both acute and chronic conditions. PMID:18436911

"Smart Forms" in an Electronic Medical Record: documentation-based clinical decision support to improve disease management.

PubMed

Schnipper, Jeffrey L; Linder, Jeffrey A; Palchuk, Matvey B; Einbinder, Jonathan S; Li, Qi; Postilnik, Anatoly; Middleton, Blackford

2008-01-01

Clinical decision support systems (CDSS) integrated within Electronic Medical Records (EMR) hold the promise of improving healthcare quality. To date the effectiveness of CDSS has been less than expected, especially concerning the ambulatory management of chronic diseases. This is due, in part, to the fact that clinicians do not use CDSS fully. Barriers to clinicians' use of CDSS have included lack of integration into workflow, software usability issues, and relevance of the content to the patient at hand. At Partners HealthCare, we are developing "Smart Forms" to facilitate documentation-based clinical decision support. Rather than being interruptive in nature, the Smart Form enables writing a multi-problem visit note while capturing coded information and providing sophisticated decision support in the form of tailored recommendations for care. The current version of the Smart Form is designed around two chronic diseases: coronary artery disease and diabetes mellitus. The Smart Form has potential to improve the care of patients with both acute and chronic conditions.

Neonatal physical therapy. Part I: clinical competencies and neonatal intensive care unit clinical training models.

PubMed

Sweeney, Jane K; Heriza, Carolyn B; Blanchard, Yvette

2009-01-01

To describe clinical training models, delineate clinical competencies, and outline a clinical decision-making algorithm for neonatal physical therapy. In these updated practice guidelines, advanced clinical training models, including precepted practicum and residency or fellowship training, are presented to guide practitioners in organizing mentored, competency-based preparation for neonatal care. Clinical competencies in neonatal physical therapy are outlined with advanced clinical proficiencies and knowledge areas specific to each role. An algorithm for decision making on examination, evaluation, intervention, and re-examination processes provides a framework for clinical reasoning. Because of advanced-level competency requirements and the continuous examination, evaluation, and modification of procedures during each patient contact, the intensive care unit is a restricted practice area for physical therapist assistants, physical therapist generalists, and physical therapy students. Accountable, ethical physical therapy for neonates requires advanced, competency-based training with a preceptor in the pediatric subspecialty of neonatology.

Identification of design features to enhance utilization and acceptance of systems for Internet-based decision support at the point of care.

PubMed Central

Gadd, C. S.; Baskaran, P.; Lobach, D. F.

1998-01-01

Extensive utilization of point-of-care decision support systems will be largely dependent on the development of user interaction capabilities that make them effective clinical tools in patient care settings. This research identified critical design features of point-of-care decision support systems that are preferred by physicians, through a multi-method formative evaluation of an evolving prototype of an Internet-based clinical decision support system. Clinicians used four versions of the system--each highlighting a different functionality. Surveys and qualitative evaluation methodologies assessed clinicians' perceptions regarding system usability and usefulness. Our analyses identified features that improve perceived usability, such as telegraphic representations of guideline-related information, facile navigation, and a forgiving, flexible interface. Users also preferred features that enhance usefulness and motivate use, such as an encounter documentation tool and the availability of physician instruction and patient education materials. In addition to identifying design features that are relevant to efforts to develop clinical systems for point-of-care decision support, this study demonstrates the value of combining quantitative and qualitative methods of formative evaluation with an iterative system development strategy to implement new information technology in complex clinical settings. Images Figure 1 PMID:9929188

An Exploration of the Relationship between Clinical Decision-Making Ability and Educational Preparation among New Graduate Nurses

ERIC Educational Resources Information Center

Blount, Kamilah V.

2013-01-01

This study examined the impact of accelerated nursing direct entry master's programs on the development of clinical decision-making skills of new graduate nurses that completed the Performance Based Development System (PBDS) assessment during the study period of 2008-2012 at a healthcare organization. Healthcare today is practiced in a…

Facilitating Adoption of News Tool to Develop Clinical Decision Making

ERIC Educational Resources Information Center

Brown, Robin T.

2017-01-01

This scholarly project was a non-experimental, pre/post-test design to (a) facilitate the voluntary adoption of the National Early Warning Score (NEWS), and (b) develop clinical decision making (CDM) in one cohort of junior level nursing students participating in a simulation lab. NEWS is an evidence-based predictive scoring tool developed by the…

Fuzzy-Arden-Syntax-based, Vendor-agnostic, Scalable Clinical Decision Support and Monitoring Platform.

PubMed

Adlassnig, Klaus-Peter; Fehre, Karsten; Rappelsberger, Andrea

2015-01-01

This study's objective is to develop and use a scalable genuine technology platform for clinical decision support based on Arden Syntax, which was extended by fuzzy set theory and fuzzy logic. Arden Syntax is a widely recognized formal language for representing clinical and scientific knowledge in an executable format, and is maintained by Health Level Seven (HL7) International and approved by the American National Standards Institute (ANSI). Fuzzy set theory and logic permit the representation of knowledge and automated reasoning under linguistic and propositional uncertainty. These forms of uncertainty are a common feature of patients' medical data, the body of medical knowledge, and deductive clinical reasoning.

The ethics of end-of-life decisions in the elderly: deliberations from the ECOPE study.

PubMed

Reiter-Theil, Stella

2003-06-01

Is age a factor underlying clinical decision-making? Should age be a criterion in the allocation of health care resources? Is it correct to criticize this approach as 'ageism'? What role does 'paternalism' play? These questions are the focus of this chapter which takes an interdisciplinary perspective of clinical ethics in order to provide an ethical evaluation of the situation of the elderly in health care. First, the text of the chapter is based on the descriptive level referring to (a) clinical ethics consultation, (b) the ECOPE study on 'Ethical Conditions of Passive Euthanasia' focusing on decision-making, and studies about age as a factor in clinical decisions, such as the American SUPPORT study. Second, at the normative level, ethical deliberations are discussed for and against age as a criterion for allocating health care resources. Finally, it is suggested that the differences in evidence to be found about the role of age as a factor in clinical decision-making may be due to the different national health policies as well as to the insufficient awareness of ethical principles violated by covert 'ageist' attitudes.

Construction of a Clinical Decision Support System for Undergoing Surgery Based on Domain Ontology and Rules Reasoning

PubMed Central

Bau, Cho-Tsan; Huang, Chung-Yi

2014-01-01

Abstract Objective: To construct a clinical decision support system (CDSS) for undergoing surgery based on domain ontology and rules reasoning in the setting of hospitalized diabetic patients. Materials and Methods: The ontology was created with a modified ontology development method, including specification and conceptualization, formalization, implementation, and evaluation and maintenance. The Protégé–Web Ontology Language editor was used to implement the ontology. Embedded clinical knowledge was elicited to complement the domain ontology with formal concept analysis. The decision rules were translated into JENA format, which JENA can use to infer recommendations based on patient clinical situations. Results: The ontology includes 31 classes and 13 properties, plus 38 JENA rules that were built to generate recommendations. The evaluation studies confirmed the correctness of the ontology, acceptance of recommendations, satisfaction with the system, and usefulness of the ontology for glycemic management of diabetic patients undergoing surgery, especially for domain experts. Conclusions: The contribution of this research is to set up an evidence-based hybrid ontology and an evaluation method for CDSS. The system can help clinicians to achieve inpatient glycemic control in diabetic patients undergoing surgery while avoiding hypoglycemia. PMID:24730353

Construction of a clinical decision support system for undergoing surgery based on domain ontology and rules reasoning.

PubMed

Bau, Cho-Tsan; Chen, Rung-Ching; Huang, Chung-Yi

2014-05-01

To construct a clinical decision support system (CDSS) for undergoing surgery based on domain ontology and rules reasoning in the setting of hospitalized diabetic patients. The ontology was created with a modified ontology development method, including specification and conceptualization, formalization, implementation, and evaluation and maintenance. The Protégé-Web Ontology Language editor was used to implement the ontology. Embedded clinical knowledge was elicited to complement the domain ontology with formal concept analysis. The decision rules were translated into JENA format, which JENA can use to infer recommendations based on patient clinical situations. The ontology includes 31 classes and 13 properties, plus 38 JENA rules that were built to generate recommendations. The evaluation studies confirmed the correctness of the ontology, acceptance of recommendations, satisfaction with the system, and usefulness of the ontology for glycemic management of diabetic patients undergoing surgery, especially for domain experts. The contribution of this research is to set up an evidence-based hybrid ontology and an evaluation method for CDSS. The system can help clinicians to achieve inpatient glycemic control in diabetic patients undergoing surgery while avoiding hypoglycemia.

Value-based decision making under uncertainty in hoarding and obsessive-compulsive disorders

PubMed Central

Pushkarskaya, Helen; Tolin, David; Ruderman, Lital; Henick, Daniel; Kelly, J. MacLaren; Pittenger, Christopher; Levy, Ifat

2017-01-01

Difficulties in decision making are a core impairment in a range of disease states. For instance, both obsessive-compulsive disorder (OCD) and hoarding disorder (HD) are associated with indecisiveness, inefficient planning, and enhanced uncertainty intolerance, even in contexts unrelated to their core symptomology. We examined decision-making patterns in 19 individuals with OCD, 19 individuals with HD, 19 individuals with comorbid OCD and HD, and 57 individuals from the general population, using a well-validated choice task grounded in behavioral economic theory. Our results suggest that difficulties in decision making in individuals with OCD (with or without comorbid HD) are linked to reduced fidelity of value-based decision making (i.e. increase in inconsistent choices). In contrast, we find that performance of individuals with HD on our laboratory task is largely intact. Overall, these results support our hypothesis that decision-making impairments in OCD and HD, which can appear quite similar clinically, have importantly different underpinnings. Systematic investigation of different aspects of decision making, under varying conditions, may shed new light on commonalities between and distinctions among clinical syndromes. PMID:28864119

Weighing Clinical Evidence Using Patient Preferences: An Application of Probabilistic Multi-Criteria Decision Analysis.

PubMed

Broekhuizen, Henk; IJzerman, Maarten J; Hauber, A Brett; Groothuis-Oudshoorn, Catharina G M

2017-03-01

The need for patient engagement has been recognized by regulatory agencies, but there is no consensus about how to operationalize this. One approach is the formal elicitation and use of patient preferences for weighing clinical outcomes. The aim of this study was to demonstrate how patient preferences can be used to weigh clinical outcomes when both preferences and clinical outcomes are uncertain by applying a probabilistic value-based multi-criteria decision analysis (MCDA) method. Probability distributions were used to model random variation and parameter uncertainty in preferences, and parameter uncertainty in clinical outcomes. The posterior value distributions and rank probabilities for each treatment were obtained using Monte-Carlo simulations. The probability of achieving the first rank is the probability that a treatment represents the highest value to patients. We illustrated our methodology for a simplified case on six HIV treatments. Preferences were modeled with normal distributions and clinical outcomes were modeled with beta distributions. The treatment value distributions showed the rank order of treatments according to patients and illustrate the remaining decision uncertainty. This study demonstrated how patient preference data can be used to weigh clinical evidence using MCDA. The model takes into account uncertainty in preferences and clinical outcomes. The model can support decision makers during the aggregation step of the MCDA process and provides a first step toward preference-based personalized medicine, yet requires further testing regarding its appropriate use in real-world settings.

Understanding clinical and non-clinical decisions under uncertainty: a scenario-based survey.

PubMed

Simianu, Vlad V; Grounds, Margaret A; Joslyn, Susan L; LeClerc, Jared E; Ehlers, Anne P; Agrawal, Nidhi; Alfonso-Cristancho, Rafael; Flaxman, Abraham D; Flum, David R

2016-12-01

Prospect theory suggests that when faced with an uncertain outcome, people display loss aversion by preferring to risk a greater loss rather than incurring certain, lesser cost. Providing probability information improves decision making towards the economically optimal choice in these situations. Clinicians frequently make decisions when the outcome is uncertain, and loss aversion may influence choices. This study explores the extent to which prospect theory, loss aversion, and probability information in a non-clinical domain explains clinical decision making under uncertainty. Four hundred sixty two participants (n = 117 non-medical undergraduates, n = 113 medical students, n = 117 resident trainees, and n = 115 medical/surgical faculty) completed a three-part online task. First, participants completed an iced-road salting task using temperature forecasts with or without explicit probability information. Second, participants chose between less or more risk-averse ("defensive medicine") decisions in standardized scenarios. Last, participants chose between recommending therapy with certain outcomes or risking additional years gained or lost. In the road salting task, the mean expected value for decisions made by clinicians was better than for non-clinicians(-$1,022 vs -$1,061; <0.001). Probability information improved decision making for all participants, but non-clinicians improved more (mean improvement of $64 versus $33; p = 0.027). Mean defensive decisions decreased across training level (medical students 2.1 ± 0.9, residents 1.6 ± 0.8, faculty1.6 ± 1.1; p-trend < 0.001) and prospect-theory-concordant decisions increased (25.4%, 33.9%, and 40.7%;p-trend = 0.016). There was no relationship identified between road salting choices with defensive medicine and prospect-theory-concordant decisions. All participants made more economically-rational decisions when provided explicit probability information in a non-clinical domain. However, choices in the non-clinical domain were not related to prospect-theory concordant decision making and risk aversion tendencies in the clinical domain. Recognizing this discordance may be important when applying prospect theory to interventions aimed at improving clinical care.

Many faces of rationality: Implications of the great rationality debate for clinical decision-making.

PubMed

Djulbegovic, Benjamin; Elqayam, Shira

2017-10-01

Given that more than 30% of healthcare costs are wasted on inappropriate care, suboptimal care is increasingly connected to the quality of medical decisions. It has been argued that personal decisions are the leading cause of death, and 80% of healthcare expenditures result from physicians' decisions. Therefore, improving healthcare necessitates improving medical decisions, ie, making decisions (more) rational. Drawing on writings from The Great Rationality Debate from the fields of philosophy, economics, and psychology, we identify core ingredients of rationality commonly encountered across various theoretical models. Rationality is typically classified under umbrella of normative (addressing the question how people "should" or "ought to" make their decisions) and descriptive theories of decision-making (which portray how people actually make their decisions). Normative theories of rational thought of relevance to medicine include epistemic theories that direct practice of evidence-based medicine and expected utility theory, which provides the basis for widely used clinical decision analyses. Descriptive theories of rationality of direct relevance to medical decision-making include bounded rationality, argumentative theory of reasoning, adaptive rationality, dual processing model of rationality, regret-based rationality, pragmatic/substantive rationality, and meta-rationality. For the first time, we provide a review of wide range of theories and models of rationality. We showed that what is "rational" behaviour under one rationality theory may be irrational under the other theory. We also showed that context is of paramount importance to rationality and that no one model of rationality can possibly fit all contexts. We suggest that in context-poor situations, such as policy decision-making, normative theories based on expected utility informed by best research evidence may provide the optimal approach to medical decision-making, whereas in the context-rich circumstances other types of rationality, informed by human cognitive architecture and driven by intuition and emotions such as the aim to minimize regret, may provide better solution to the problem at hand. The choice of theory under which we operate is important as it determines both policy and our individual decision-making. © 2017 The Authors Journal of Evaluation in Clinical Practice Published by John Wiley & Sons Ltd.

Electronic Risk Assessment System as an Appropriate Tool for the Prevention of Cancer: a Qualitative Study.

PubMed

Javan Amoli, Amir Hossein; Maserat, Elham; Safdari, Reza; Zali, Mohammad Reza

2015-01-01

Decision making modalities for screening for many cancer conditions and different stages have become increasingly complex. Computer-based risk assessment systems facilitate scheduling and decision making and support the delivery of cancer screening services. The aim of this article was to survey electronic risk assessment system as an appropriate tool for the prevention of cancer. A qualitative design was used involving 21 face-to-face interviews. Interviewing involved asking questions and getting answers from exclusive managers of cancer screening. Of the participants 6 were female and 15 were male, and ages ranged from 32 to 78 years. The study was based on a grounded theory approach and the tool was a semi- structured interview. Researchers studied 5 dimensions, comprising electronic guideline standards of colorectal cancer screening, work flow of clinical and genetic activities, pathways of colorectal cancer screening and functionality of computer based guidelines and barriers. Electronic guideline standards of colorectal cancer screening were described in the s3 categories of content standard, telecommunications and technical standards and nomenclature and classification standards. According to the participations' views, workflow and genetic pathways of colorectal cancer screening were identified. The study demonstrated an effective role of computer-guided consultation for screening management. Electronic based systems facilitate real-time decision making during a clinical interaction. Electronic pathways have been applied for clinical and genetic decision support, workflow management, update recommendation and resource estimates. A suitable technical and clinical infrastructure is an integral part of clinical practice guidline of screening. As a conclusion, it is recommended to consider the necessity of architecture assessment and also integration standards.

Picture Exchange Communication System (PECS) or Sign Language: An Evidence-Based Decision-Making Example

ERIC Educational Resources Information Center

Spencer, Trina D.; Petersen, Douglas B.; Gillam, Sandra L.

2008-01-01

Evidence-based practice (EBP) refers to clinical decisions as a result of the careful integration of research evidence and student needs. Legal mandates such as No Child Left Behind require teachers to employ evidence-based practices in their classrooms, yet teachers receive little guidance regarding how to determine which practices are…

Making reasonable decisions: a qualitative study of medical decision making in the care of patients with a clinically significant haemoglobin disorder.

PubMed

Crowther, Helen J; Kerridge, Ian

2015-10-01

Therapies utilized in patients with clinically significant haemoglobin disorders appear to vary between clinicians and units. This study aimed to investigate the processes of evidence implementation and medical decision making in the care of such patients in NSW, Australia. Using semi-structured interviews, 11 haematologists discussed their medical decision-making processes with particular attention paid to the use of published evidence. Transcripts were thematically analysed by a single investigator on a line-by-line basis. Decision making surrounding the care of patients with significant haemoglobin disorders varied and was deeply contextual. Three main determinants of clinical decision making were identified - factors relating to the patient and to their illness, factors specific to the clinician and the institution in which they were practising and factors related to the notion of evidence and to utility and role of evidence-based medicine in clinical practice. Clinicians pay considerable attention to medical decision making and evidence incorporation and attempt to tailor these to particular patient contexts. However, the patient context is often inferred and when discordant with the clinician's own contexture can lead to discomfort with decision recommendations. Clinicians strive to improve comfort through the use of experience and trustworthy evidence. © 2015 John Wiley & Sons, Ltd.

Evidence-based medicine and patient choice: the case of heart failure care.

PubMed

Sanders, Tom; Harrison, Stephen; Checkland, Kath

2008-04-01

The implementation of evidence-based medicine and policies aimed at increasing user involvement in health care decisions are central planks of contemporary English health policy. Yet they are potentially in conflict. Our aim was to explore how clinicians working in the field of heart failure resolve this conflict. Qualitative semi-structured interviews were carried out with health professionals who were currently caring for patients with heart failure, and observations were conducted at one dedicated heart failure clinic in northern England. While clinicians acknowledged that patients' ideas and preferences should be an important part of treatment decisions, the widespread acceptance of an evidence-based clinical protocol for heart failure among the clinic doctors significantly influenced the content and style of the consultation. Evidence-based medicine was used to buttress professional authority and seemed to provide an additional barrier to the adoption of patient-centred clinical practice.

Which research is needed to support clinical decision-making on integrative medicine?- Can comparative effectiveness research close the gap?

PubMed

Witt, Claudia M; Huang, Wen-jing; Lao, Lixing; Bm, Berman

2012-10-01

In clinical research on complementary and integrative medicine, experts and scientists have often pursued a research agenda in spite of an incomplete understanding of the needs of end users. Consequently, the majority of previous clinical trials have mainly assessed the efficacy of interventions. Scant data is available on their effectiveness. Comparative effectiveness research (CER) promises to support decision makers by generating evidence that compares the benefits and harms of the best care options. This evidence, more generalizable than the evidence generated by traditional randomized controlled trials (RCTs), is better suited to inform real-world care decisions. An emphasis on CER supports the development of the evidence base for clinical and policy decision-making. Whereas in most areas of complementary and integrative medicine data on comparative effectiveness is scarce, available acupuncture research already contributes to CER evidence. This paper will introduce CER and make suggestions for future research.

Effort-Based Decision-Making Paradigms for Clinical Trials in Schizophrenia: Part 2—External Validity and Correlates

PubMed Central

Reddy, L. Felice; Barch, Deanna M.; Buchanan, Robert W.; Dunayevich, Eduardo; Gold, James M.; Marder, Steven R.; Wynn, Jonathan K.; Young, Jared W.; Green, Michael F.

2015-01-01

Effort-based decision making has strong conceptual links to the motivational disturbances that define a key subdomain of negative symptoms. However, the extent to which effort-based decision-making performance relates to negative symptoms, and other clinical and functionally important variables has yet to be systematically investigated. In 94 clinically stable outpatients with schizophrenia, we examined the external validity of 5 effort-based paradigms, including the Effort Expenditure for Rewards, Balloon Effort, Grip Strength Effort, Deck Choice Effort, and Perceptual Effort tasks. These tasks covered 3 types of effort: physical, cognitive, and perceptual. Correlations between effort related performance and 6 classes of variables were examined, including: (1) negative symptoms, (2) clinically rated motivation and community role functioning, (3) self-reported motivational traits, (4) neurocognition, (5) other psychiatric symptoms and clinical/demographic characteristics, and (6) subjective valuation of monetary rewards. Effort paradigms showed small to medium relationships to clinical ratings of negative symptoms, motivation, and functioning, with the pattern more consistent for some measures than others. They also showed small to medium relations with neurocognitive functioning, but were generally unrelated to other psychiatric symptoms, self-reported traits, antipsychotic medications, side effects, and subjective valuation of money. There were relatively strong interrelationships among the effort measures. In conjunction with findings from a companion psychometric article, all the paradigms warrant further consideration and development, and 2 show the strongest potential for clinical trial use at this juncture. PMID:26209546

The use of video-based patient education for shared decision-making in the treatment of prostate cancer.

PubMed

Gomella, L G; Albertsen, P C; Benson, M C; Forman, J D; Soloway, M S

2000-08-01

Increased consumerism, patient empowerment, and autonomy are creating a health care revolution. In recent years, the public has become better informed and more sophisticated. An extraordinary amount of treatment advice from books, the media, and the Internet is available to patients today, although much of it is confusing or conflicting. Consequently, the traditional, paternalistic doctor-patient relationship is yielding to a more consumerist one. The new dynamic is based on a participatory ethic and a change in the balance of power. This shared decision-making creates a true partnership between professionals and patients, in which each contributes equally to decisions about treatment or care. Evidence suggests that in diseases such as prostate cancer, where there may be a number of appropriate treatment options for a particular patient, shared decision-making may lead to improved clinical and quality-of-life outcomes. This article explores the evolving relationship between the physician and patient, the pros and cons of shared decision-making, and the use of video technology in the clinical setting. The authors review the use of medical decision aids, including a video-based educational program called CHOICES, in the treatment of prostate cancer and other diseases.

Development of an evidence-based decision pathway for vestibular schwannoma treatment options.

PubMed

Linkov, Faina; Valappil, Benita; McAfee, Jacob; Goughnour, Sharon L; Hildrew, Douglas M; McCall, Andrew A; Linkov, Igor; Hirsch, Barry; Snyderman, Carl

To integrate multiple sources of clinical information with patient feedback to build evidence-based decision support model to facilitate treatment selection for patients suffering from vestibular schwannomas (VS). This was a mixed methods study utilizing focus group and survey methodology to solicit feedback on factors important for making treatment decisions among patients. Two 90-minute focus groups were conducted by an experienced facilitator. Previously diagnosed VS patients were recruited by clinical investigators at the University of Pittsburgh Medical Center (UPMC). Classical content analysis was used for focus group data analysis. Providers were recruited from practices within the UPMC system and were surveyed using Delphi methods. This information can provide a basis for multi-criteria decision analysis (MCDA) framework to develop a treatment decision support system for patients with VS. Eight themes were derived from these data (focus group + surveys): doctor/health care system, side effects, effectiveness of treatment, anxiety, mortality, family/other people, quality of life, and post-operative symptoms. These data, as well as feedback from physicians were utilized in building a multi-criteria decision model. The study illustrated steps involved in the development of a decision support model that integrates evidence-based data and patient values to select treatment alternatives. Studies focusing on the actual development of the decision support technology for this group of patients are needed, as decisions are highly multifactorial. Such tools have the potential to improve decision making for complex medical problems with alternate treatment pathways. Copyright © 2016 Elsevier Inc. All rights reserved.

Variation in clinical decision-making for induction of labour: a qualitative study.

PubMed

Nippita, Tanya A; Porter, Maree; Seeho, Sean K; Morris, Jonathan M; Roberts, Christine L

2017-09-22

Unexplained variation in induction of labour (IOL) rates exist between hospitals, even after accounting for casemix and hospital differences. We aimed to explore factors that influence clinical decision-making for IOL that may be contributing to the variation in IOL rates between hospitals. We undertook a qualitative study involving semi-structured, audio-recorded interviews with obstetricians and midwives. Using purposive sampling, participants known to have diverse opinions on IOL were selected from ten Australian maternity hospitals (based on differences in hospital IOL rate, size, location and case-mix complexities). Transcripts were indexed, coded, and analysed using the Framework Approach to identify main themes and subthemes. Forty-five participants were interviewed (21 midwives, 24 obstetric medical staff). Variations in decision-making for IOL were based on the obstetrician's perception of medical risk in the pregnancy (influenced by the obstetrician's personality and knowledge), their care relationship with the woman, how they involved the woman in decision-making, and resource availability. The role of a 'gatekeeper' in the procedural aspects of arranging an IOL also influenced decision-making. There was wide variation in the clinical decision-making practices of obstetricians and less accountability for decision-making in hospitals with a high IOL rate, with the converse occurring in hospitals with low IOL rates. Improved communication, standardised risk assessment and accountability for IOL offer potential for reducing variation in hospital IOL rates.

Evidence - based medicine/practice in sports physical therapy.

PubMed

Manske, Robert C; Lehecka, B J

2012-10-01

A push for the use of evidence-based medicine and evidence-based practice patterns has permeated most health care disciplines. The use of evidence-based practice in sports physical therapy may improve health care quality, reduce medical errors, help balance known benefits and risks, challenge views based on beliefs rather than evidence, and help to integrate patient preferences into decision-making. In this era of health care utilization sports physical therapists are expected to integrate clinical experience with conscientious, explicit, and judicious use of research evidence in order to make clearly informed decisions in order to help maximize and optimize patient well-being. One of the more common reasons for not using evidence in clinical practice is the perceived lack of skills and knowledge when searching for or appraising research. This clinical commentary was developed to educate the readership on what constitutes evidence-based practice, and strategies used to seek evidence in the daily clinical practice of sports physical therapy.

Transforming clinical practice guidelines and clinical pathways into fast-and-frugal decision trees to improve clinical care strategies.

PubMed

Djulbegovic, Benjamin; Hozo, Iztok; Dale, William

2018-02-27

Contemporary delivery of health care is inappropriate in many ways, largely due to suboptimal Q5 decision-making. A typical approach to improve practitioners' decision-making is to develop evidence-based clinical practice guidelines (CPG) by guidelines panels, who are instructed to use their judgments to derive practice recommendations. However, mechanisms for the formulation of guideline judgments remains a "black-box" operation-a process with defined inputs and outputs but without sufficient knowledge of its internal workings. Increased explicitness and transparency in the process can be achieved by implementing CPG as clinical pathways (CPs) (also known as clinical algorithms or flow-charts). However, clinical recommendations thus derived are typically ad hoc and developed by experts in a theory-free environment. As any recommendation can be right (true positive or negative), or wrong (false positive or negative), the lack of theoretical structure precludes the quantitative assessment of the management strategies recommended by CPGs/CPs. To realize the full potential of CPGs/CPs, they need to be placed on more solid theoretical grounds. We believe this potential can be best realized by converting CPGs/CPs within the heuristic theory of decision-making, often implemented as fast-and-frugal (FFT) decision trees. This is possible because FFT heuristic strategy of decision-making can be linked to signal detection theory, evidence accumulation theory, and a threshold model of decision-making, which, in turn, allows quantitative analysis of the accuracy of clinical management strategies. Fast-and-frugal provides a simple and transparent, yet solid and robust, methodological framework connecting decision science to clinical care, a sorely needed missing link between CPGs/CPs and patient outcomes. We therefore advocate that all guidelines panels express their recommendations as CPs, which in turn should be converted into FFTs to guide clinical care. © 2018 John Wiley & Sons, Ltd.

SynopSIS: integrating physician sign-out with the electronic medical record.

PubMed

Sarkar, Urmimala; Carter, Jonathan T; Omachi, Theodore A; Vidyarthi, Arpana R; Cucina, Russell; Bokser, Seth; van Eaton, Erik; Blum, Michael

2007-09-01

Safe delivery of care depends on effective communication among all health care providers, especially during transfers of care. The traditional medical chart does not adequately support such communication. We designed a patient-tracking tool that enhances provider communication and supports clinical decision making. To develop a problem-based patient-tracking tool, called Sign-out, Information Retrieval, and Summary (SynopSIS), in order to support patient tracking, transfers of care (ie, sign-outs), and daily rounds. Tertiary-care, university-based teaching hospital. SynopSIS compiles and organizes information from the electronic medical record to support hospital discharge and disposition decisions, daily provider decisions, and overnight or cross-coverage decisions. It reflects the provider's patient-care and daily work-flow needs. We plan to use Web-based surveys, audits of daily use, and interdisciplinary focus groups to evaluate SynopSIS's impact on communication between providers, quality of sign-out, patient continuity of care, and rounding efficiency. We expect SynopSIS to improve care by facilitating communication between care teams, standardizing sign-out, and automating daily review of clinical and laboratory trends. SynopSIS redesigns the clinical chart to better serve provider and patient needs. (c) 2007 Society of Hospital Medicine.

Information systems: the key to evidence-based health practice.

PubMed Central

Rodrigues, R. J.

2000-01-01

Increasing prominence is being given to the use of best current evidence in clinical practice and health services and programme management decision-making. The role of information in evidence-based practice (EBP) is discussed, together with questions of how advanced information systems and technology (IS&T) can contribute to the establishment of a broader perspective for EBP. The author examines the development, validation and use of a variety of sources of evidence and knowledge that go beyond the well-established paradigm of research, clinical trials, and systematic literature review. Opportunities and challenges in the implementation and use of IS&T and knowledge management tools are examined for six application areas: reference databases, contextual data, clinical data repositories, administrative data repositories, decision support software, and Internet-based interactive health information and communication. Computerized and telecommunications applications that support EBP follow a hierarchy in which systems, tasks and complexity range from reference retrieval and the processing of relatively routine transactions, to complex "data mining" and rule-driven decision support systems. PMID:11143195

Modelling and Decision Support of Clinical Pathways

NASA Astrophysics Data System (ADS)

Gabriel, Roland; Lux, Thomas

The German health care market is under a rapid rate of change, forcing especially hospitals to provide high-quality services at low costs. Appropriate measures for more effective and efficient service provision are process orientation and decision support by information technology of clinical pathway of a patient. The essential requirements are adequate modelling of clinical pathways as well as usage of adequate systems, which are capable of assisting the complete path of a patient within a hospital, and preferably also outside of it, in a digital way. To fulfil these specifications the authors present a suitable concept, which meets the challenges of well-structured clinical pathways as well as rather poorly structured diagnostic and therapeutic decisions, by interplay of process-oriented and knowledge-based hospital information systems.

Clinical Decision-Making in Community Children’s Mental Health: Using Innovative Methods to Compare Clinicians With and Without Training in Evidence-Based Treatment

PubMed Central

Baker-Ericzén, Mary J.; Jenkins, Melissa M.; Park, Soojin; Garland, Ann F.

2014-01-01

Background Mental health professionals’ decision-making practice is an area of increasing interest and importance, especially in the pediatric research and clinical communities. Objective The present study explored the role of prior training in evidence-based treatments on clinicians’ assessment and treatment formulations using case vignettes. Specifically, study aims included using the Naturalistic Decision Making (NDM) cognitive theory to 1) examine potential associations between EBT training and decision-making processes (novice versus expert type), and 2) explore how client and family contextual information affects clinical decision-making. Methods Forty-eight clinicians across two groups (EBT trained=14, Not EBT trained=34) participated. Clinicians were comparable on professional experience, demographics, and discipline. The quasi-experimental design used an analog “think aloud” method where clinicians read case vignettes about a child with disruptive behavior problems and verbalized case conceptualization and treatment planning out-loud. Responses were coded according to NDM theory. Results MANOVA results were significant for EBT training status such that EBT trained clinicians’ displayed cognitive processes more closely aligned with “expert” decision-makers and non-EBT trained clinicians’ decision processes were more similar to “novice” decision-makers, following NDM theory. Non-EBT trained clinicians assigned significantly more diagnoses, provided less detailed treatment plans and discussed fewer EBTs. Parent/family contextual information also appeared to influence decision-making. Conclusion This study offers a preliminary investigation of the possible broader impacts of EBT training and potential associations with development of expert decision-making skills. Targeting clinicians’ decision-making may be an important avenue to pursue within dissemination-implementation efforts in mental health practice. PMID:25892901

Prognostic Factors and Decision Tree for Long-term Survival in Metastatic Uveal Melanoma.

PubMed

Lorenzo, Daniel; Ochoa, María; Piulats, Josep Maria; Gutiérrez, Cristina; Arias, Luis; Català, Jaum; Grau, María; Peñafiel, Judith; Cobos, Estefanía; Garcia-Bru, Pere; Rubio, Marcos Javier; Padrón-Pérez, Noel; Dias, Bruno; Pera, Joan; Caminal, Josep Maria

2017-12-04

The purpose of this study was to demonstrate the existence of a bimodal survival pattern in metastatic uveal melanoma. Secondary aims were to identify the characteristics and prognostic factors associated with long-term survival and to develop a clinical decision tree. The medical records of 99 metastatic uveal melanoma patients were retrospectively reviewed. Patients were classified as either short (≤ 12 months) or long-term survivors (> 12 months) based on a graphical interpretation of the survival curve after diagnosis of the first metastatic lesion. Ophthalmic and oncological characteristics were assessed in both groups. Of the 99 patients, 62 (62.6%) were classified as short-term survivors, and 37 (37.4%) as long-term survivors. The multivariate analysis identified the following predictors of long-term survival: age ≤ 65 years (p=0.012) and unaltered serum lactate dehydrogenase levels (p=0.018); additionally, the size (smaller vs. larger) of the largest liver metastasis showed a trend towards significance (p=0.063). Based on the variables significantly associated with long-term survival, we developed a decision tree to facilitate clinical decision-making. The findings of this study demonstrate the existence of a bimodal survival pattern in patients with metastatic uveal melanoma. The presence of certain clinical characteristics at diagnosis of distant disease is associated with long-term survival. A decision tree was developed to facilitate clinical decision-making and to counsel patients about the expected course of disease.

Evaluation and diagnosis of low back pain.

PubMed

Manusov, Eron G

2012-09-01

The diagnosis of low back pain is complicated by the varying presentations and complex nature of pain and the nonstandardized approach by physicians to clinical decision making. Only a few physicians use evidence-based guidelines to assist with clinical decision making. This article reviews a systematic approach to the evaluation and diagnosis of low back pain. Copyright © 2012 Elsevier Inc. All rights reserved.

Application of a diagnosis-based clinical decision guide in patients with low back pain.

PubMed

Murphy, Donald R; Hurwitz, Eric L

2011-10-21

Low back pain (LBP) is common and costly. Development of accurate and efficacious methods of diagnosis and treatment has been identified as a research priority. A diagnosis-based clinical decision guide (DBCDG; previously referred to as a diagnosis-based clinical decision rule) has been proposed which attempts to provide the clinician with a systematic, evidence-based means to apply the biopsychosocial model of care. The approach is based on three questions of diagnosis. The purpose of this study is to present the prevalence of findings using the DBCDG in consecutive patients with LBP. Demographic, diagnostic and baseline outcome measure data were gathered on a cohort of LBP patients examined by one of three examiners trained in the application of the DBCDG. Data were gathered on 264 patients. Signs of visceral disease or potentially serious illness were found in 2.7%. Centralization signs were found in 41%, lumbar and sacroiliac segmental signs in 23% and 27%, respectively and radicular signs were found in 24%. Clinically relevant myofascial signs were diagnosed in 10%. Dynamic instability was diagnosed in 63%, fear beliefs in 40%, central pain hypersensitivity in 5%, passive coping in 3% and depression in 3%. The DBCDG can be applied in a busy private practice environment. Further studies are needed to investigate clinically relevant means to identify central pain hypersensitivity, poor coping and depression, correlations and patterns among the diagnostic components of the DBCDG as well as inter-examiner reliability and efficacy of treatment based on the DBCDG.

Newly graduated nurses' use of knowledge sources in clinical decision-making: an ethnographic study.

PubMed

Voldbjerg, Siri Lygum; Grønkjaer, Mette; Wiechula, Rick; Sørensen, Erik Elgaard

2017-05-01

To explore which knowledge sources newly graduated nurses' use in clinical decision-making and why and how they are used. In spite of an increased educational focus on skills and competencies within evidence-based practice, newly graduated nurses' ability to use components within evidence-based practice with a conscious and reflective use of research evidence has been described as being poor. To understand why, it is relevant to explore which other knowledge sources are used. This may shed light on why research evidence is sparsely used and ultimately inform approaches to strengthen the knowledgebase used in clinical decision-making. Ethnographic study using participant-observation and individual semistructured interviews of nine Danish newly graduated nurses in medical and surgical hospital settings. Newly graduates use of knowledge sources was described within three main structures: 'other', 'oneself' and 'gut feeling'. Educational preparation, transition into clinical practice and the culture of the setting influenced the knowledge sources used. The sources ranged from overt easily articulated knowledge sources to covert sources that were difficult to articulate. The limited articulation of certain sources inhibited the critical reflection on the reasoning behind decisions. Reflection is a prerequisite for an evidence-based practice where decisions should be transparent in order to consider if other evidentiary sources could be used. Although there is a complexity and variety to knowledge sources used, there is an imbalance with the experienced nurse playing a key role, functioning both as predominant source and a role model as to which sources are valued and used in clinical decision-making. If newly graduates are to be supported in an articulate and reflective use of a variety of sources, they have to be allocated to experienced nurses who model a reflective, articulate and balanced use of knowledge sources. © 2016 John Wiley & Sons Ltd.

[Development and clinical evaluation of an anesthesia information management system].

PubMed

Feng, Jing-yi; Chen, Hua; Zhu, Sheng-mei

2010-09-21

To study the design, implementation and clinical evaluation of an anesthesia information management system. To record, process and store peri-operative patient data automatically, all kinds of bedside monitoring equipments are connected into the system based on information integrating technology; after a statistical analysis of those patient data by data mining technology, patient status can be evaluated automatically based on risk prediction standard and decision support system, and then anesthetist could perform reasonable and safe clinical processes; with clinical processes electronically recorded, standard record tables could be generated, and clinical workflow is optimized, as well. With the system, kinds of patient data could be collected, stored, analyzed and archived, kinds of anesthesia documents could be generated, and patient status could be evaluated to support clinic decision. The anesthesia information management system is useful for improving anesthesia quality, decreasing risk of patient and clinician, and aiding to provide clinical proof.

A peer review process as part of the implementation of clinical pathways in radiation oncology: Does it improve compliance?

PubMed

Gebhardt, Brian J; Heron, Dwight E; Beriwal, Sushil

Clinical pathways are patient management plans that standardize evidence-based practices to ensure high-quality and cost-effective medical care. Implementation of a pathway is a collaborative process in our network, requiring the active involvement of physicians. This approach promotes acceptance of pathway recommendations, although a peer review process is necessary to ensure compliance and to capture and approve off-pathway selections. We investigated the peer review process and factors associated with time to completion of peer review. Our cancer center implemented radiation oncology pathways for every disease site throughout a large, integrated network. Recommendations are written based upon national guidelines, published literature, and institutional experience with evidence evaluated hierarchically in order of efficacy, toxicity, and then cost. Physicians enter decisions into an online, menu-driven decision support tool that integrates with medical records. Data were collected from the support tool and included the rate of on- and off-pathway selections, peer review decisions performed by disease site directors, and time to complete peer review. A total of 6965 treatment decisions were entered in 2015, and 605 (8.7%) were made off-pathway and were subject to peer review. The median time to peer review decision was 2 days (interquartile range, 0.2-6.8). Factors associated with time to peer review decision >48 hours on univariate analysis include disease site (P < .0001) with a trend toward significance (P = .066) for radiation therapy modality. There was no difference between recurrent and non-recurrent disease (P = .267). Multivariable analysis revealed disease site was associated with time to peer review (P < .001), with lymphoma and skin/sarcoma most strongly influencing decision time >48 hours. Clinical pathways are an integral tool for standardizing evidence-based care throughout our large, integrated network, with 91.3% of all treatment decisions being made as per pathway. The peer review process was feasible, with <1% selections ultimately rejected, suggesting that awareness of peer review of treatment decisions encourages compliance with clinical pathway recommendations. Copyright © 2017 American Society for Radiation Oncology. Published by Elsevier Inc. All rights reserved.

Clinical use of patient decision-making aids for stone patients.

PubMed

Lim, Amy H; Streeper, Necole M; Best, Sara L; Penniston, Kristina L; Nakada, Stephen Y

2017-08-01

Patient decision-making aids (PDMAs) help patients make informed healthcare decisions and improve patient satisfaction. The utility of PDMAs for patients considering treatments for urolithiasis has not yet been published. We report our experience using PDMAs developed at our institution in the outpatient clinical setting in patients considering a variety of treatment options for stones. Patients with radiographically confirmed urolithiasis were given PDMAs regarding treatment options for their stone(s) based on their clinical profile. We assessed patients' satisfaction, involvedness, and feeling of making a more informed decision with utilization of the PDMAs using a Likert Scale Questionnaire. Information was also collected regarding previous stone passage, history and type of surgical intervention for urolithiasis, and level of education. Patients (n = 43; 18 males, 23 females and two unknown) 53 +/- 14years old were included. Patients reported that they understood the advantages and disadvantages outlined in the PDMAs (97%), that the PDMAs helped them make a more informed decision (83%) and felt more involved in the decision making process (88%). Patients reported that the aids were presented in a balanced manner and used up-to-date scientific information (100%, 84% respectively). Finally, a majority of the patients prefer an expert's opinion when making a treatment decision (98%) with 73% of patients preferring to form their own opinion based on available information. Previous stone surgery was associated with patients feeling more involved with the decision making process (p = 0.0465). PDMAs have a promising role in shared decision-making in the setting of treatment options for nephrolithiasis.

Forensic issues in medical evaluation: competency and end-of-life issues.

PubMed

Soliman, Sherif; Hall, Ryan C W

2015-01-01

Decision-making capacity is a common reason for psychiatric consultation that is likely to become more common as the population ages. Capacity assessments are frequently compromised by misconceptions, such as the belief that incapacity is permanent or that patients with dementia categorically lack capacity. This chapter will review the conceptual framework of decision-making capacity and discuss its application to medical decision-making. We will review selected developments in capacity assessment and recommend an approach to assessing decision-making capacity. We will discuss the unique challenges posed by end-of-life care, including determining capacity, identifying surrogate decision-makers, and working with surrogate decision-makers. We will discuss clinical and legal approaches to incapacity, including advance directives, surrogate decision-makers, and guardians. We will discuss the legal standards based on which surrogates make medical decisions and outline options for resolving disagreements between clinical staff and surrogate decision-makers. We will offer recommendations for approaching decision-making capacity assessments. © 2015 S. Karger AG, Basel.

System for selecting relevant information for decision support.

PubMed

Kalina, Jan; Seidl, Libor; Zvára, Karel; Grünfeldová, Hana; Slovák, Dalibor; Zvárová, Jana

2013-01-01

We implemented a prototype of a decision support system called SIR which has a form of a web-based classification service for diagnostic decision support. The system has the ability to select the most relevant variables and to learn a classification rule, which is guaranteed to be suitable also for high-dimensional measurements. The classification system can be useful for clinicians in primary care to support their decision-making tasks with relevant information extracted from any available clinical study. The implemented prototype was tested on a sample of patients in a cardiological study and performs an information extraction from a high-dimensional set containing both clinical and gene expression data.

CorRECTreatment: A Web-based Decision Support Tool for Rectal Cancer Treatment that Uses the Analytic Hierarchy Process and Decision Tree

PubMed Central

Karakülah, G.; Dicle, O.; Sökmen, S.; Çelikoğlu, C.C.

2015-01-01

Summary Background The selection of appropriate rectal cancer treatment is a complex multi-criteria decision making process, in which clinical decision support systems might be used to assist and enrich physicians’ decision making. Objective The objective of the study was to develop a web-based clinical decision support tool for physicians in the selection of potentially beneficial treatment options for patients with rectal cancer. Methods The updated decision model contained 8 and 10 criteria in the first and second steps respectively. The decision support model, developed in our previous study by combining the Analytic Hierarchy Process (AHP) method which determines the priority of criteria and decision tree that formed using these priorities, was updated and applied to 388 patients data collected retrospectively. Later, a web-based decision support tool named corRECTreatment was developed. The compatibility of the treatment recommendations by the expert opinion and the decision support tool was examined for its consistency. Two surgeons were requested to recommend a treatment and an overall survival value for the treatment among 20 different cases that we selected and turned into a scenario among the most common and rare treatment options in the patient data set. Results In the AHP analyses of the criteria, it was found that the matrices, generated for both decision steps, were consistent (consistency ratio<0.1). Depending on the decisions of experts, the consistency value for the most frequent cases was found to be 80% for the first decision step and 100% for the second decision step. Similarly, for rare cases consistency was 50% for the first decision step and 80% for the second decision step. Conclusions The decision model and corRECTreatment, developed by applying these on real patient data, are expected to provide potential users with decision support in rectal cancer treatment processes and facilitate them in making projections about treatment options. PMID:25848413

CorRECTreatment: a web-based decision support tool for rectal cancer treatment that uses the analytic hierarchy process and decision tree.

PubMed

Suner, A; Karakülah, G; Dicle, O; Sökmen, S; Çelikoğlu, C C

2015-01-01

The selection of appropriate rectal cancer treatment is a complex multi-criteria decision making process, in which clinical decision support systems might be used to assist and enrich physicians' decision making. The objective of the study was to develop a web-based clinical decision support tool for physicians in the selection of potentially beneficial treatment options for patients with rectal cancer. The updated decision model contained 8 and 10 criteria in the first and second steps respectively. The decision support model, developed in our previous study by combining the Analytic Hierarchy Process (AHP) method which determines the priority of criteria and decision tree that formed using these priorities, was updated and applied to 388 patients data collected retrospectively. Later, a web-based decision support tool named corRECTreatment was developed. The compatibility of the treatment recommendations by the expert opinion and the decision support tool was examined for its consistency. Two surgeons were requested to recommend a treatment and an overall survival value for the treatment among 20 different cases that we selected and turned into a scenario among the most common and rare treatment options in the patient data set. In the AHP analyses of the criteria, it was found that the matrices, generated for both decision steps, were consistent (consistency ratio<0.1). Depending on the decisions of experts, the consistency value for the most frequent cases was found to be 80% for the first decision step and 100% for the second decision step. Similarly, for rare cases consistency was 50% for the first decision step and 80% for the second decision step. The decision model and corRECTreatment, developed by applying these on real patient data, are expected to provide potential users with decision support in rectal cancer treatment processes and facilitate them in making projections about treatment options.

Mobile Clinical Decision Support System for Acid-base Balance Diagnosis and Treatment Recommendation.

PubMed

Mandzuka, Mensur; Begic, Edin; Boskovic, Dusanka; Begic, Zijo; Masic, Izet

2017-06-01

This paper presents mobile application implementing a decision support system for acid-base disorder diagnosis and treatment recommendation. The application was developed using the official integrated development environment for the Android platform (to maximize availability and minimize investments in specialized hardware) called Android Studio. The application identifies disorder, based on the blood gas analysis, evaluates whether the disorder has been compensated, and based on additional input related to electrolyte imbalance, provides recommendations for treatment. The application is a tool in the hands of the user, which provides assistance during acid-base disorders treatment. The application will assist the physician in clinical practice and is focused on the treatment in intensive care.

Basic physiological systems indicator's informative assessment for children and adolescents obesity diagnosis tasks

NASA Astrophysics Data System (ADS)

Marukhina, O. V.; Berestneva, O. G.; Emelyanova, Yu A.; Romanchukov, S. V.; Petrova, L.; Lombardo, C.; Kozlova, N. V.

2018-05-01

The healthcare computerization creates opportunities to the clinical decision support system development. In the course of diagnosis, doctor manipulates a considerable amount of data and makes a decision in the context of uncertainty basing upon the first-hand experience and knowledge. The situation is exacerbated by the fact that the knowledge scope in medicine is incrementally growing, but the decision-making time does not increase. The amount of medical malpractice is growing and it leads to various negative effects, even the mortality rate increase. IT-solution's development for clinical purposes is one of the most promising and efficient ways to prevent these effects. That is why the efforts of many IT specialists are directed to the doctor's heuristics simulating software or expert-based medical decision-making algorithms development. Thus, the objective of this study is to develop techniques and approaches for the body physiological system's informative value assessment index for the obesity degree evaluation based on the diagnostic findings.

Shared decision making as part of value based care: New U.S. policies challenge our readiness.

PubMed

Spatz, Erica S; Elwyn, Glyn; Moulton, Benjamin W; Volk, Robert J; Frosch, Dominick L

2017-06-01

Shared decision making in the United States is increasingly being recognized as part of value-based care. During the last decade, several state and federal initiatives have linked shared decision making with reimbursement and increased protection from litigation. Additionally, private and public foundations are increasingly funding studies to identify best practices for moving shared decision making from the research world into clinical practice. These shifts offer opportunities and challenges for ensuring effective implementation. Copyright © 2017. Published by Elsevier GmbH.

Design and Development of a Sharable Clinical Decision Support System Based on a Semantic Web Service Framework.

PubMed

Zhang, Yi-Fan; Gou, Ling; Tian, Yu; Li, Tian-Chang; Zhang, Mao; Li, Jing-Song

2016-05-01

Clinical decision support (CDS) systems provide clinicians and other health care stakeholders with patient-specific assessments or recommendations to aid in the clinical decision-making process. Despite their demonstrated potential for improving health care quality, the widespread availability of CDS systems has been limited mainly by the difficulty and cost of sharing CDS knowledge among heterogeneous healthcare information systems. The purpose of this study was to design and develop a sharable clinical decision support (S-CDS) system that meets this challenge. The fundamental knowledge base consists of independent and reusable knowledge modules (KMs) to meet core CDS needs, wherein each KM is semantically well defined based on the standard information model, terminologies, and representation formalisms. A semantic web service framework was developed to identify, access, and leverage these KMs across diverse CDS applications and care settings. The S-CDS system has been validated in two distinct client CDS applications. Model-level evaluation results confirmed coherent knowledge representation. Application-level evaluation results reached an overall accuracy of 98.66 % and a completeness of 96.98 %. The evaluation results demonstrated the technical feasibility and application prospect of our approach. Compared with other CDS engineering efforts, our approach facilitates system development and implementation and improves system maintainability, scalability and efficiency, which contribute to the widespread adoption of effective CDS within the healthcare domain.

Assessing the Clinical Impact of Risk Prediction Models With Decision Curves: Guidance for Correct Interpretation and Appropriate Use

PubMed Central

Brown, Marshall D.; Zhu, Kehao; Janes, Holly

2016-01-01

The decision curve is a graphical summary recently proposed for assessing the potential clinical impact of risk prediction biomarkers or risk models for recommending treatment or intervention. It was applied recently in an article in Journal of Clinical Oncology to measure the impact of using a genomic risk model for deciding on adjuvant radiation therapy for prostate cancer treated with radical prostatectomy. We illustrate the use of decision curves for evaluating clinical- and biomarker-based models for predicting a man’s risk of prostate cancer, which could be used to guide the decision to biopsy. Decision curves are grounded in a decision-theoretical framework that accounts for both the benefits of intervention and the costs of intervention to a patient who cannot benefit. Decision curves are thus an improvement over purely mathematical measures of performance such as the area under the receiver operating characteristic curve. However, there are challenges in using and interpreting decision curves appropriately. We caution that decision curves cannot be used to identify the optimal risk threshold for recommending intervention. We discuss the use of decision curves for miscalibrated risk models. Finally, we emphasize that a decision curve shows the performance of a risk model in a population in which every patient has the same expected benefit and cost of intervention. If every patient has a personal benefit and cost, then the curves are not useful. If subpopulations have different benefits and costs, subpopulation-specific decision curves should be used. As a companion to this article, we released an R software package called DecisionCurve for making decision curves and related graphics. PMID:27247223

The use of the Dutch Self-Sufficiency Matrix (SSM-D) to inform allocation decisions to public mental health care for homeless people.

PubMed

Lauriks, Steve; de Wit, Matty A S; Buster, Marcel C A; Fassaert, Thijs J L; van Wifferen, Ron; Klazinga, Niek S

2014-10-01

The current study set out to develop a decision support tool based on the Self-Sufficiency Matrix (Dutch version; SSM-D) for the clinical decision to allocate homeless people to the public mental health care system at the central access point of public mental health care in Amsterdam, The Netherlands. Logistic regression and receiver operating characteristic-curve analyses were used to model professional decisions and establish four decision categories based on SSM-D scores from half of the research population (Total n = 612). The model and decision categories were found to be accurate and reliable in predicting professional decisions in the second half of the population. Results indicate that the decision support tool based on the SSM-D is useful and feasible. The method to develop the SSM-D as a decision support tool could be applied to decision-making processes in other systems and services where the SSM-D has been implemented, to further increase the utility of the instrument.

Analysis of Nursing Clinical Decision Support Requests and Strategic Plan in a Large Academic Health System

PubMed Central

Bavuso, Karen; Bouyer-Ferullo, Sharon; Goldsmith, Denise; Fairbanks, Amanda; Gesner, Emily; Lagor, Charles; Collins, Sarah

2016-01-01

Summary Objectives To understand requests for nursing Clinical Decision Support (CDS) interventions at a large integrated health system undergoing vendor-based EHR implementation. In addition, to establish a process to guide both short-term implementation and long-term strategic goals to meet nursing CDS needs. Materials and Methods We conducted an environmental scan to understand current state of nursing CDS over three months. The environmental scan consisted of a literature review and an analysis of CDS requests received from across our health system. We identified existing high priority CDS and paper-based tools used in nursing practice at our health system that guide decision-making. Results A total of 46 nursing CDS requests were received. Fifty-six percent (n=26) were specific to a clinical specialty; 22 percent (n=10) were focused on facilitating clinical consults in the inpatient setting. “Risk Assessments/Risk Reduction/Promotion of Healthy Habits” (n=23) was the most requested High Priority Category received for nursing CDS. A continuum of types of nursing CDS needs emerged using the Data-Information-Knowledge-Wisdom Conceptual Framework: 1) facilitating data capture, 2) meeting information needs, 3) guiding knowledge-based decision making, and 4) exposing analytics for wisdom-based clinical interpretation by the nurse. Conclusion Identifying and prioritizing paper-based tools that can be modified into electronic CDS is a challenge. CDS strategy is an evolving process that relies on close collaboration and engagement with clinical sites for short-term implementation and should be incorporated into a long-term strategic plan that can be optimized and achieved overtime. The Data-Information-Knowledge-Wisdom Conceptual Framework in conjunction with the High Priority Categories established may be a useful tool to guide a strategic approach for meeting short-term nursing CDS needs and aligning with the organizational strategic plan. PMID:27437036

Clinical and Research Perspectives on Nonspeech Oral Motor Treatments and Evidence-Based Practice

ERIC Educational Resources Information Center

Muttiah, Nimisha; Georges, Katie; Brackenbury, Tim

2011-01-01

Purpose: Evidence-based practice (EBP) involves the incorporation of research evidence, clinical expertise, and client values in clinical decision making. One case in which these factors conflict is the use of nonspeech oral motor treatments (NSOMTs) for children with developmental speech sound disorders. Critical reviews of the research evidence…

Improving Decision Making about Genetic Testing in the Clinic: An Overview of Effective Knowledge Translation Interventions.

PubMed

Légaré, France; Robitaille, Hubert; Gane, Claire; Hébert, Jessica; Labrecque, Michel; Rousseau, François

2016-01-01

Knowledge translation (KT) interventions are attempts to change behavior in keeping with scientific evidence. While genetic tests are increasingly available to healthcare consumers in the clinic, evidence about their benefits is unclear and decisions about genetic testing are thus difficult for all parties. We sought to identify KT interventions that involved decisions about genetic testing in the clinical context and to assess their effectiveness for improving decision making in terms of behavior change, increased knowledge and wellbeing. We searched for trials assessing KT interventions in the context of genetic testing up to March 2014 in all systematic reviews (n = 153) published by two Cochrane review groups: Effective Practice and Organisation of Care (EPOC) and Consumers and Communication. We retrieved 2473 unique trials of which we retained only 28 (1%). Two EPOC reviews yielded two trials of KT interventions: audit and feedback (n = 1) and educational outreach (n = 1). Both targeted health professionals and the KT intervention they assessed was found to be effective. Four Consumers and Communication reviews yielded 26 trials: decision aids (n = 15), communication of DNA-based disease risk estimates (n = 7), personalized risk communication (n = 3) and mobile phone messaging (n = 1). Among these, 25 trials targeted only health consumers or patients and the KT interventions were found to be effective in four trials, partly effective in seven, and ineffective in four. Lastly, only one trial targeted both physicians and patients and was found to be effective. More research on the effectiveness of KT interventions regarding genetic testing in the clinical context may contribute to patients making informed value-based decisions and drawing the maximum benefit from clinical applications of genetic and genomic innovations.

Computerized Clinical Decision Support: Contributions from 2015

PubMed Central

Bouaud, J.

2016-01-01

Summary Objective To summarize recent research and select the best papers published in 2015 in the field of computerized clinical decision support for the Decision Support section of the IMIA yearbook. Method A literature review was performed by searching two bibliographic databases for papers related to clinical decision support systems (CDSSs) and computerized provider order entry (CPOE) systems. The aim was to identify a list of candidate best papers from the retrieved papers that were then peer-reviewed by external reviewers. A consensus meeting between the two section editors and the IMIA editorial team was finally conducted to conclude in the best paper selection. Results Among the 974 retrieved papers, the entire review process resulted in the selection of four best papers. One paper reports on a CDSS routinely applied in pediatrics for more than 10 years, relying on adaptations of the Arden Syntax. Another paper assessed the acceptability and feasibility of an important CPOE evaluation tool in hospitals outside the US where it was developed. The third paper is a systematic, qualitative review, concerning usability flaws of medication-related alerting functions, providing an important evidence-based, methodological contribution in the domain of CDSS design and development in general. Lastly, the fourth paper describes a study quantifying the effect of a complex, continuous-care, guideline-based CDSS on the correctness and completeness of clinicians’ decisions. Conclusions While there are notable examples of routinely used decision support systems, this 2015 review on CDSSs and CPOE systems still shows that, despite methodological contributions, theoretical frameworks, and prototype developments, these technologies are not yet widely spread (at least with their full functionalities) in routine clinical practice. Further research, testing, evaluation, and training are still needed for these tools to be adopted in clinical practice and, ultimately, illustrate the benefits that they promise. PMID:27830247

[The role of research-based evidence in health system policy decision-making].

PubMed

Patiño, Daniel; Lavis, John N; Moat, Kaelan

2013-01-01

Different models may be used for explaining how research-based evidence is used in healthcare system policy-making. It is argued that models arising from a clinical setting (i.e. evidence-based policy-making model) could be useful regarding some types of healthcare system decision-making. However, such models are "silent" concerning the influence of political contextual factors on healthcare policy-making and are thus inconsistent with decision-making regarding the modification of healthcare system arrangements. Other political science-based models would seem to be more useful for understanding that research is just one factor affecting decision-making and that different types of research-based evidence can be used instrumentally, conceptual or strategically during different policy-making stages.

A medical informatics perspective on clinical decision support systems. Findings from the yearbook 2013 section on decision support.

PubMed

Bouaud, J; Lamy, J-B

2013-01-01

To summarize excellent research and to select best papers published in 2012 in the field of computer-based decision support in healthcare. A bibliographic search focused on clinical decision support systems (CDSSs) and computer provider order entry was performed, followed by a double-blind literature review. The review process yielded six papers, illustrating various aspects of clinical decision support. The first paper is a systematic review of CDSS intervention trials in real settings, and considers different types of possible outcomes. It emphasizes the heterogeneity of studies and confirms that CDSSs can improve process measures but that evidence lacks for other types of outcomes, especially clinical or economic. Four other papers tackle the safety of drug prescribing and show that CDSSs can be efficient in reducing prescription errors. The sixth paper exemplifies the growing role of ontological resources which can be used for several applications including decision support. CDSS research has to be continuously developed and assessed. The wide variety of systems and of interventions limits the understanding of factors of success of CDSS implementations. A standardization in the characterization of CDSSs and of intervention trial reporting will help to overcome this obstacle.

Healthy participants in phase I clinical trials: the quality of their decision to take part.

PubMed

Rabin, Cheryl; Tabak, Nili

2006-08-01

This study was set out to test the quality of the decision-making process of healthy volunteers in clinical trials. Researchers fear that the decision to volunteer for clinical trials is taken inadequately and that the signature on the consent forms, meant to affirm that consent was 'informed', is actually insubstantial. The study design was quasi-experimental, using a convenience quota sample. Over a period of a year, candidates were approached during their screening process for a proposed clinical trial, after concluding the required 'Informed Consent' procedure. In all, 100 participants in phase I trials filled out questionnaires based ultimately on the Janis and Mann model of vigilant information processing, during their stay in the research centre. Only 35% of the participants reached a 'quality decision'. There is a definite correlation between information processing and quality decision-making. However, many of the healthy research volunteers (58%) do not seek out information nor check alternatives before making a decision. Full disclosure is essential to a valid informed consent procedure but not sufficient; emphasis must be put on having the information understood and assimilated. Research nurses play a central role in achieving this objective.

Factors associated with clinical inertia: an integrative review

PubMed Central

Aujoulat, Isabelle; Jacquemin, Patricia; Rietzschel, Ernst; Scheen, André; Tréfois, Patrick; Wens, Johan; Darras, Elisabeth; Hermans, Michel P

2014-01-01

Failure to initiate or intensify therapy according to evidence-based guidelines is increasingly being acknowledged as a phenomenon that contributes to inadequate management of chronic conditions, and is referred to as clinical inertia. However, the number and complexity of factors associated with the clinical reasoning that underlies the decision-making processes in medicine calls for a critical examination of the consistency of the concept. Indeed, in the absence of information on and justification of treatment decisions that were made, clinical inertia may be only apparent, and actually reflect good clinical practice. This integrative review seeks to address the factors generally associated with clinical inaction, in order to better delineate the concept of true clinical inertia. PMID:24868181

Eliciting societal preferences of reimbursement decision criteria for anti cancer drugs in South Korea.

PubMed

Kwon, Sun-Hong; Park, Sun-Kyeong; Byun, Ji-Hye; Lee, Eui-Kyung

2017-08-01

In order to look beyond the cost-effectiveness analysis, this study used a multi-criteria decision analysis (MCDA), which reflects societal values with regard to reimbursement decisions. This study aims to elicit societal preferences of the reimbursement decision criteria for anti cancer drugs from public and healthcare professionals. Eight criteria were defined based on a literature review and focus group sessions: disease severity, disease population size, pediatrics targets, unmet needs, innovation, clinical benefits, cost-effectiveness, and budget impacts. Using quota sampling and purposive sampling, 300 participants from the Korean public and 30 healthcare professionals were selected for the survey. Preferences were elicited using an analytic hierarchy process. Both groups rated clinical benefits the highest, followed by cost-effectiveness and disease severity, but differed with regard to disease population size and unmet needs. Innovation was the least preferred criteria. Clinical benefits and other social values should be reflected appropriately with cost-effectiveness in healthcare coverage. MCDA can be used to assess decision priorities for complicated health policy decisions, including reimbursement decisions. It is a promising method for making logical and transparent drug reimbursement decisions that consider a broad range of factors, which are perceived as important by relevant stakeholders.

What is a medical decision? A taxonomy based on physician statements in hospital encounters: a qualitative study

PubMed Central

Ofstad, Eirik H; Frich, Jan C; Schei, Edvin; Frankel, Richard M; Gulbrandsen, Pål

2016-01-01

Objective The medical literature lacks a comprehensive taxonomy of decisions made by physicians in medical encounters. Such a taxonomy might be useful in understanding the physician-centred, patient-centred and shared decision-making in clinical settings. We aimed to identify and classify all decisions emerging in conversations between patients and physicians. Design Qualitative study of video recorded patient–physician encounters. Participants and setting 380 patients in consultations with 59 physicians from 17 clinical specialties and three different settings (emergency room, ward round, outpatient clinic) in a Norwegian teaching hospital. A randomised sample of 30 encounters from internal medicine was used to identify and classify decisions, a maximum variation sample of 20 encounters was used for reliability assessments, and the remaining encounters were analysed to test for applicability across specialties. Results On the basis of physician statements in our material, we developed a taxonomy of clinical decisions—the Decision Identification and Classification Taxonomy for Use in Medicine (DICTUM). We categorised decisions into 10 mutually exclusive categories: gathering additional information, evaluating test results, defining problem, drug-related, therapeutic procedure-related, legal and insurance-related, contact-related, advice and precaution, treatment goal, and deferment. Four-coder inter-rater reliability using Krippendorff's α was 0.79. Conclusions DICTUM represents a precise, detailed and comprehensive taxonomy of medical decisions communicated within patient–physician encounters. Compared to previous normative frameworks, the taxonomy is descriptive, substantially broader and offers new categories to the variety of clinical decisions. The taxonomy could prove helpful in studies on the quality of medical work, use of time and resources, and understanding of why, when and how patients are or are not involved in decisions. PMID:26868946

Simulation as a preoperative planning approach in advanced heart failure patients. A retrospective clinical analysis.

PubMed

Capoccia, Massimo; Marconi, Silvia; Singh, Sanjeet Avtaar; Pisanelli, Domenico M; De Lazzari, Claudio

2018-05-02

Modelling and simulation may become clinically applicable tools for detailed evaluation of the cardiovascular system and clinical decision-making to guide therapeutic intervention. Models based on pressure-volume relationship and zero-dimensional representation of the cardiovascular system may be a suitable choice given their simplicity and versatility. This approach has great potential for application in heart failure where the impact of left ventricular assist devices has played a significant role as a bridge to transplant and more recently as a long-term solution for non eligible candidates. We sought to investigate the value of simulation in the context of three heart failure patients with a view to predict or guide further management. CARDIOSIM © was the software used for this purpose. The study was based on retrospective analysis of haemodynamic data previously discussed at a multidisciplinary meeting. The outcome of the simulations addressed the value of a more quantitative approach in the clinical decision process. Although previous experience, co-morbidities and the risk of potentially fatal complications play a role in clinical decision-making, patient-specific modelling may become a daily approach for selection and optimisation of device-based treatment for heart failure patients. Willingness to adopt this integrated approach may be the key to further progress.

Comparing and using assessments of the value of information to clinical decision-making.

PubMed Central

Urquhart, C J; Hepworth, J B

1996-01-01

This paper discusses the Value project, which assessed the value to clinical decision-making of information supplied by National Health Service (NHS) library and information services. The project not only showed how health libraries in the United Kingdom help clinicians in decision-making but also provided quality assurance guidelines for these libraries to help make their information services more effective. The paper reviews methods and results used in previous studies of the value of health libraries, noting that methodological differences appear to affect the results. The paper also discusses aspects of user involvement, categories of clinical decision-making, the value of information to present and future clinical decisions, and the combination of quantitative and qualitative assessments of value, as applied to the Value project and the studies reviewed. The Value project also demonstrated that the value placed on information depends in part on the career stage of the physician. The paper outlines the structure of the quality assurance tool kit, which is based on the findings and methods used in the Value project. PMID:8913550

Clinical decision support for whole genome sequence information leveraging a service-oriented architecture: a prototype.

PubMed

Welch, Brandon M; Rodriguez-Loya, Salvador; Eilbeck, Karen; Kawamoto, Kensaku

2014-01-01

Whole genome sequence (WGS) information could soon be routinely available to clinicians to support the personalized care of their patients. At such time, clinical decision support (CDS) integrated into the clinical workflow will likely be necessary to support genome-guided clinical care. Nevertheless, developing CDS capabilities for WGS information presents many unique challenges that need to be overcome for such approaches to be effective. In this manuscript, we describe the development of a prototype CDS system that is capable of providing genome-guided CDS at the point of care and within the clinical workflow. To demonstrate the functionality of this prototype, we implemented a clinical scenario of a hypothetical patient at high risk for Lynch Syndrome based on his genomic information. We demonstrate that this system can effectively use service-oriented architecture principles and standards-based components to deliver point of care CDS for WGS information in real-time.

Using the Situated Clinical Decision-Making framework to guide analysis of nurses' clinical decision-making.

PubMed

Gillespie, Mary

2010-11-01

Nurses' clinical decision-making is a complex process that holds potential to influence the quality of care provided and patient outcomes. The evolution of nurses' decision-making that occurs with experience has been well documented. In addition, literature includes numerous strategies and approaches purported to support development of nurses' clinical decision-making. There has been, however, significantly less attention given to the process of assessing nurses' clinical decision-making and novice clinical educators are often challenged with knowing how to best support nurses and nursing students in developing their clinical decision-making capacity. The Situated Clinical Decision-Making framework is presented for use by clinical educators: it provides a structured approach to analyzing nursing students' and novice nurses' decision-making in clinical nursing practice, assists educators in identifying specific issues within nurses' clinical decision-making, and guides selection of relevant strategies to support development of clinical decision-making. A series of questions is offered as a guide for clinical educators when assessing nurses' clinical decision-making. The discussion presents key considerations related to analysis of various decision-making components, including common sources of challenge and errors that may occur within nurses' clinical decision-making. An exemplar illustrates use of the framework and guiding questions. Implications of this approach for selection of strategies that support development of clinical decision-making are highlighted. Copyright © 2010 Elsevier Ltd. All rights reserved.

Medication-related clinical decision support in computerized provider order entry systems: a review.

PubMed

Kuperman, Gilad J; Bobb, Anne; Payne, Thomas H; Avery, Anthony J; Gandhi, Tejal K; Burns, Gerard; Classen, David C; Bates, David W

2007-01-01

While medications can improve patients' health, the process of prescribing them is complex and error prone, and medication errors cause many preventable injuries. Computer provider order entry (CPOE) with clinical decision support (CDS), can improve patient safety and lower medication-related costs. To realize the medication-related benefits of CDS within CPOE, one must overcome significant challenges. Healthcare organizations implementing CPOE must understand what classes of CDS their CPOE systems can support, assure that clinical knowledge underlying their CDS systems is reasonable, and appropriately represent electronic patient data. These issues often influence to what extent an institution will succeed with its CPOE implementation and achieve its desired goals. Medication-related decision support is probably best introduced into healthcare organizations in two stages, basic and advanced. Basic decision support includes drug-allergy checking, basic dosing guidance, formulary decision support, duplicate therapy checking, and drug-drug interaction checking. Advanced decision support includes dosing support for renal insufficiency and geriatric patients, guidance for medication-related laboratory testing, drug-pregnancy checking, and drug-disease contraindication checking. In this paper, the authors outline some of the challenges associated with both basic and advanced decision support and discuss how those challenges might be addressed. The authors conclude with summary recommendations for delivering effective medication-related clinical decision support addressed to healthcare organizations, application and knowledge base vendors, policy makers, and researchers.

Evidence-based algorithm for heparin dosing before cardiopulmonary bypass. Part 1: Development of the algorithm.

PubMed

McKinney, Mark C; Riley, Jeffrey B

2007-12-01

The incidence of heparin resistance during adult cardiac surgery with cardiopulmonary bypass has been reported at 15%-20%. The consistent use of a clinical decision-making algorithm may increase the consistency of patient care and likely reduce the total required heparin dose and other problems associated with heparin dosing. After a directed survey of practicing perfusionists regarding treatment of heparin resistance and a literature search for high-level evidence regarding the diagnosis and treatment of heparin resistance, an evidence-based decision-making algorithm was constructed. The face validity of the algorithm decisive steps and logic was confirmed by a second survey of practicing perfusionists. The algorithm begins with review of the patient history to identify predictors for heparin resistance. The definition for heparin resistance contained in the algorithm is an activated clotting time < 450 seconds with > 450 IU/kg heparin loading dose. Based on the literature, the treatment for heparin resistance used in the algorithm is anti-thrombin III supplement. The algorithm seems to be valid and is supported by high-level evidence and clinician opinion. The next step is a human randomized clinical trial to test the clinical procedure guideline algorithm vs. current standard clinical practice.

How we developed and piloted an electronic key features examination for the internal medicine clerkship based on a US national curriculum.

PubMed

Bronander, Kirk A; Lang, Valerie J; Nixon, L James; Harrell, Heather E; Kovach, Regina; Hingle, Susan; Berman, Norman

2015-01-01

Key features examinations (KFEs) have been used to assess clinical decision making in medical education, yet there are no reports of an online KFE-based on a national curriculum for the internal medicine clerkship. What we did: The authors developed and pilot tested an electronic KFE based on the US Clerkship Directors in Internal Medicine core curriculum. Teams, with expert oversight and peer review, developed key features (KFs) and cases. The exam was pilot tested at eight medical schools with 162 third and fourth year medical students, of whom 96 (59.3%) responded to a survey. While most students reported that the exam was more difficult than a multiple choice question exam, 61 (83.3%) students agreed that it reflected problems seen in clinical practice and 51 (69.9%) students reported that it more accurately assessed the ability to make clinical decisions. The development of an electronic KFs exam is a time-intensive process. A team approach offers built-in peer review and accountability. Students, although not familiar with this format in the US, recognized it as authentically assessing clinical decision-making for problems commonly seen in the clerkship.

New technology continues to invade healthcare. What are the strategic implications/outcomes?

PubMed

Smith, Coy

2004-01-01

Healthcare technology continues to advance and be implemented in healthcare organizations. Nurse executives must strategically evaluate the effectiveness of each proposed system or device using a strategic planning process. Clinical information systems, computer-chip-based clinical monitoring devices, advanced Web-based applications with remote, wireless communication devices, clinical decision support software--all compete for capital and registered nurse salary dollars. The concept of clinical transformation is developed with new models of care delivery being supported by technology rather than driving care delivery. Senior nursing leadership's role in clinical transformation and healthcare technology implementation is developed. Proposed standards, expert group action, business and consumer groups, and legislation are reviewed as strategic drivers in the development of an electronic health record and healthcare technology. A matrix of advancing technology and strategic decision-making parameters are outlined.

Bladder cancer treatment response assessment with radiomic, clinical, and radiologist semantic features

NASA Astrophysics Data System (ADS)

Gordon, Marshall N.; Cha, Kenny H.; Hadjiiski, Lubomir M.; Chan, Heang-Ping; Cohan, Richard H.; Caoili, Elaine M.; Paramagul, Chintana; Alva, Ajjai; Weizer, Alon Z.

2018-02-01

We are developing a decision support system for assisting clinicians in assessment of response to neoadjuvant chemotherapy for bladder cancer. Accurate treatment response assessment is crucial for identifying responders and improving quality of life for non-responders. An objective machine learning decision support system may help reduce variability and inaccuracy in treatment response assessment. We developed a predictive model to assess the likelihood that a patient will respond based on image and clinical features. With IRB approval, we retrospectively collected a data set of pre- and post- treatment CT scans along with clinical information from surgical pathology from 98 patients. A linear discriminant analysis (LDA) classifier was used to predict the likelihood that a patient would respond to treatment based on radiomic features extracted from CT urography (CTU), a radiologist's semantic feature, and a clinical feature extracted from surgical and pathology reports. The classification accuracy was evaluated using the area under the ROC curve (AUC) with a leave-one-case-out cross validation. The classification accuracy was compared for the systems based on radiomic features, clinical feature, and radiologist's semantic feature. For the system based on only radiomic features the AUC was 0.75. With the addition of clinical information from examination under anesthesia (EUA) the AUC was improved to 0.78. Our study demonstrated the potential of designing a decision support system to assist in treatment response assessment. The combination of clinical features, radiologist semantic features and CTU radiomic features improved the performance of the classifier and the accuracy of treatment response assessment.

Effort-Based Decision-Making Paradigms for Clinical Trials in Schizophrenia: Part 2—External Validity and Correlates.

PubMed

Horan, William P; Reddy, L Felice; Barch, Deanna M; Buchanan, Robert W; Dunayevich, Eduardo; Gold, James M; Marder, Steven R; Wynn, Jonathan K; Young, Jared W; Green, Michael F

2015-09-01

Effort-based decision making has strong conceptual links to the motivational disturbances that define a key subdomain of negative symptoms. However, the extent to which effort-based decision-making performance relates to negative symptoms, and other clinical and functionally important variables has yet to be systematically investigated. In 94 clinically stable outpatients with schizophrenia, we examined the external validity of 5 effort-based paradigms, including the Effort Expenditure for Rewards, Balloon Effort, Grip Strength Effort, Deck Choice Effort, and Perceptual Effort tasks. These tasks covered 3 types of effort: physical, cognitive, and perceptual. Correlations between effort related performance and 6 classes of variables were examined, including: (1) negative symptoms, (2) clinically rated motivation and community role functioning, (3) self-reported motivational traits, (4) neurocognition, (5) other psychiatric symptoms and clinical/demographic characteristics, and (6) subjective valuation of monetary rewards. Effort paradigms showed small to medium relationships to clinical ratings of negative symptoms, motivation, and functioning, with the pattern more consistent for some measures than others. They also showed small to medium relations with neurocognitive functioning, but were generally unrelated to other psychiatric symptoms, self-reported traits, antipsychotic medications, side effects, and subjective valuation of money. There were relatively strong interrelationships among the effort measures. In conjunction with findings from a companion psychometric article, all the paradigms warrant further consideration and development, and 2 show the strongest potential for clinical trial use at this juncture. © The Author 2015. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

OrderRex: clinical order decision support and outcome predictions by data-mining electronic medical records

PubMed Central

Chen, Jonathan H; Podchiyska, Tanya

2016-01-01

Objective: To answer a “grand challenge” in clinical decision support, the authors produced a recommender system that automatically data-mines inpatient decision support from electronic medical records (EMR), analogous to Netflix or Amazon.com’s product recommender. Materials and Methods: EMR data were extracted from 1 year of hospitalizations (>18K patients with >5.4M structured items including clinical orders, lab results, and diagnosis codes). Association statistics were counted for the ∼1.5K most common items to drive an order recommender. The authors assessed the recommender’s ability to predict hospital admission orders and outcomes based on initial encounter data from separate validation patients. Results: Compared to a reference benchmark of using the overall most common orders, the recommender using temporal relationships improves precision at 10 recommendations from 33% to 38% (P < 10−10) for hospital admission orders. Relative risk-based association methods improve inverse frequency weighted recall from 4% to 16% (P < 10−16). The framework yields a prediction receiver operating characteristic area under curve (c-statistic) of 0.84 for 30 day mortality, 0.84 for 1 week need for ICU life support, 0.80 for 1 week hospital discharge, and 0.68 for 30-day readmission. Discussion: Recommender results quantitatively improve on reference benchmarks and qualitatively appear clinically reasonable. The method assumes that aggregate decision making converges appropriately, but ongoing evaluation is necessary to discern common behaviors from “correct” ones. Conclusions: Collaborative filtering recommender algorithms generate clinical decision support that is predictive of real practice patterns and clinical outcomes. Incorporating temporal relationships improves accuracy. Different evaluation metrics satisfy different goals (predicting likely events vs. “interesting” suggestions). PMID:26198303

Constructing diagnostic likelihood: clinical decisions using subjective versus statistical probability.

PubMed

Kinnear, John; Jackson, Ruth

2017-07-01

Although physicians are highly trained in the application of evidence-based medicine, and are assumed to make rational decisions, there is evidence that their decision making is prone to biases. One of the biases that has been shown to affect accuracy of judgements is that of representativeness and base-rate neglect, where the saliency of a person's features leads to overestimation of their likelihood of belonging to a group. This results in the substitution of 'subjective' probability for statistical probability. This study examines clinicians' propensity to make estimations of subjective probability when presented with clinical information that is considered typical of a medical condition. The strength of the representativeness bias is tested by presenting choices in textual and graphic form. Understanding of statistical probability is also tested by omitting all clinical information. For the questions that included clinical information, 46.7% and 45.5% of clinicians made judgements of statistical probability, respectively. Where the question omitted clinical information, 79.9% of clinicians made a judgement consistent with statistical probability. There was a statistically significant difference in responses to the questions with and without representativeness information (χ2 (1, n=254)=54.45, p<0.0001). Physicians are strongly influenced by a representativeness bias, leading to base-rate neglect, even though they understand the application of statistical probability. One of the causes for this representativeness bias may be the way clinical medicine is taught where stereotypic presentations are emphasised in diagnostic decision making. 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/.

Impact of computer-based treatment planning software on clinical judgment of dental students for planning prosthodontic rehabilitation

PubMed Central

Deshpande, Saee; Chahande, Jayashree

2014-01-01

Purpose Successful prosthodontic rehabilitation involves making many interrelated clinical decisions which have an impact on each other. Self-directed computer-based training has been shown to be a very useful tool to develop synthetic and analytical problem-solving skills among students. Thus, a computer-based case study and treatment planning (CSTP) software program was developed which would allow students to work through the process of comprehensive, multidisciplinary treatment planning for patients in a structured and logical manner. The present study was aimed at assessing the effect of this CSTP software on the clinical judgment of dental students while planning prosthodontic rehabilitation and to assess the students’ perceptions about using the program for its intended use. Methods A CSTP software program was developed and validated. The impact of this program on the clinical decision making skills of dental graduates was evaluated by real life patient encounters, using a modified and validated mini-CEX. Students’ perceptions about the program were obtained by a pre-validated feedback questionnaire. Results The faculty assessment scores of clinical judgment improved significantly after the use of this program. The majority of students felt it was an informative, useful, and innovative way of learning and they strongly felt that they had learnt the logical progression of planning, the insight into decision making, and the need for flexibility in treatment planning after using this program. Conclusion CSTP software was well received by the students. There was significant improvement in students’ clinical judgment after using this program. It should thus be envisaged fundamentally as an adjunct to conventional teaching techniques to improve students’ decision making skills and confidence. PMID:25170288

An evaluation of learning clinical decision-making for early rehabilitation in the ICU via interactive education with audience response system.

PubMed

Toonstra, Amy L; Nelliot, Archana; Aronson Friedman, Lisa; Zanni, Jennifer M; Hodgson, Carol; Needham, Dale M

2017-06-01

Knowledge-related barriers to safely implement early rehabilitation programs in intensive care units (ICUs) may be overcome via targeted education. The purpose of this study was to evaluate the effectiveness of an interactive educational session on short-term knowledge of clinical decision-making for safe rehabilitation of patients in ICUs. A case-based teaching approach, drawing from published safety recommendations for initiation of rehabilitation in ICUs, was used with a multidisciplinary audience. An audience response system was incorporated to promote interaction and evaluate knowledge before vs. after the educational session. Up to 175 audience members, of 271 in attendance (129 (48%) physical therapists, 51 (19%) occupational therapists, 31 (11%) nursing, 14 (5%) physician, 46 (17%) other), completed both the pre- and post-test questions for each of the six unique patient cases. In four of six patient cases, there was a significant (p< 0.001) increase in identifying the correct answer regarding initiation of rehabilitation activities. This learning effect was similar irrespective of participants' years of experience and clinical discipline. An interactive, case-based, educational session may be effective for increasing short-term knowledge, and identifying knowledge gaps, regarding clinical decision-making for safe rehabilitation of patients in ICUs. Implications for Rehabilitation Lack of knowledge regarding the safety considerations for early rehabilitation of ICU patients is a barrier to implementing early rehabilitation. Interactive educational formats, such as the use of audience response systems, offer a new method of teaching and instantly assessing learning of clinically important information. In a small study, we have shown that an interactive, case-based educational format may be used to effectively teach clinical decision-making for the safe rehabilitation of ICU patients to a diverse audience of clinicians.

Effort-Based Decision Making in Schizophrenia: Evaluation of Paradigms to Measure Motivational Deficits

PubMed Central

Green, Michael F.; Horan, William P.

2015-01-01

Effort-based decision making requires one to decide how much effort to expend for a certain amount of reward. As the amount of reward goes up most people are willing to exert more effort. This relationship between reward level and effort expenditure can be measured in specialized performance-based tasks that have only recently been applied to schizophrenia. Such tasks provide a way to measure objectively motivational deficits in schizophrenia, which now are only assessed with clinical interviews of negative symptoms. The articles in this theme provide reviews of the relevant animal and human literatures (first 2 articles), and then a psychometric evaluation of 5 effort-based decision making paradigms (last 2 articles). This theme section is intended to stimulate interest in this emerging area among basic scientists developing paradigms for preclinical studies, human experimentalists trying to disentangle factors that contribute to performance on effort-based tasks, and investigators looking for objective endpoints for clinical trials of negative symptoms in schizophrenia. PMID:26108868

Fertility preservation and cancer: Challenges for adolescent and young adult patients

PubMed Central

Benedict, Catherine; Thom, Bridgette; Kelvin, Joanne

2016-01-01

Purpose of review With increasing survival rates, fertility is an important quality of life concern for many young cancer patients. There is a critical need for improvements in clinical care to ensure patients are well informed about infertility risks and fertility preservation (FP) options and to support them in their reproductive decision-making prior to treatment. Recent findings A number of barriers prevent fertility from being adequately addressed in the clinical context. Providers’ and patients’ incomplete or inaccurate understanding of infertility risks exacerbate patients’ reproductive concerns. For female patients in particular, making decisions about FP before treatment often leads to decision conflict, reducing the likelihood of making informed, values-based decisions, and post-treatment regret and distress. Recent empirically-based interventions to improve provider training around fertility issues and to support patient decision-making about FP show promise. Summary Providers should be knowledgeable about the infertility risks associated with cancer therapies and proactively address fertility with all patients who might one day wish to have a child. Comprehensive counseling should also include related issues such as contraceptive use and health implications of early menopause, regardless of desire for future children. Although the negative psychosocial impact of cancer-related infertility is now well accepted, limited work has been done to explore how to improve clinical management of fertility issues in the context of cancer care. Evidence-based interventions should be developed to address barriers and provide psychosocial and decision-making support to patients who are concerned about their fertility and interested in FP options. PMID:26730794

Multidisciplinary decision-making on chemotherapy for colorectal cancer: an age-based comparison.

PubMed

Hamaker, Marije E; van Rixtel, Bert; Thunnissen, Peter; Oberndorff, Ardi H; Smakman, Niels; Ten Bokkel Huinink, Daan

2015-05-01

With the ageing of society, optimising decision-making for older patients with cancer becomes increasingly important. A first step is awareness of current clinical practice. We analysed how treatment decisions regarding chemotherapy for older and younger patients with colorectal cancer are currently being made by the multidisciplinary team, the oncologist and the patient. A total of 316 patients with colorectal cancer (median age 68.3 years), discussed at the multidisciplinary gastrointestinal oncology team meetings between 2010 and 2013, were reviewed to select patients for whom guidelines recommended chemotherapy. Multidisciplinary decision-making and subsequent clinical course were extracted from medical files. The multidisciplinary team recommended chemotherapy in 97% of younger patients treated with curative intent, compared to 65% of older patients; 86% of younger patients and 42% of older patients subsequently received chemotherapy. In a palliative setting, the multidisciplinary team recommended chemotherapy in 98% of younger and 69% of older patients and 81% and 45%, respectively, subsequently received this treatment. In addition to comorbidity and the patient's physical condition, chronological age was an important reason for withholding chemotherapy. When older patients did receive chemotherapy, reduced intensity regimens were often effectuated. Multidisciplinary decision-making regarding chemotherapy for older patients with colorectal cancer is still frequently based on clinical impressions, preconceptions or chronological age alone. Rather, treatment decisions should be made after thorough evaluation of the patient's health status across multiple domains, either by a geriatrician or within the oncology team itself. Given the preference-sensitive nature of chemotherapy decisions in the elderly, shared decision-making should be strived for whenever possible. Copyright © 2015 Elsevier Inc. All rights reserved.

A critical comparison of clinical decision instruments for computed tomographic scanning in mild closed traumatic brain injury in adolescents and adults.

PubMed

Stein, Sherman C; Fabbri, Andrea; Servadei, Franco; Glick, Henry A

2009-02-01

A number of clinical decision aids have been introduced to limit unnecessary computed tomographic scans in patients with mild traumatic brain injury. These aids differ in the risk factors they use to recommend a scan. We compare the instruments according to their sensitivity and specificity and recommend ones based on incremental benefit of correctly classifying patients as having surgical, nonsurgical, or no intracranial lesions. We performed a secondary analysis of prospectively collected database from 7,955 patients aged 10 years or older with mild traumatic brain injury to compare sensitivity and specificity of 6 common clinical decision strategies: the Canadian CT Head Rule, the Neurotraumatology Committee of the World Federation of Neurosurgical Societies, the New Orleans, the National Emergency X-Radiography Utilization Study II (NEXUS-II), the National Institute of Clinical Excellence guideline, and the Scandinavian Neurotrauma Committee guideline. Excluded from the database were patients for whom the history of trauma was unclear, the initial Glasgow Coma Scale score was less than 14, the injury was penetrating, vital signs were unstable, or who refused diagnostic tests. Patients revisiting the emergency department within 7 days were counted only once. The percentage of scans that would have been required by applying each of the 6 aids were Canadian CT head rule (high risk only) 53%, Canadian (medium & high risk) 56%, the Neurotraumatology Committee of the World Federation of Neurosurgical Societies 56%, New Orleans 69%, NEXUS-II 56%, National Institute of Clinical Excellence 71%, and the Scandinavian 50%. The 6 decision aids' sensitivities for surgical hematomas could not be distinguished statistically (P>.05). Sensitivity was 100% (95% confidence interval [CI] 96% to 100%) for NEXUS-II, 98.1% (95% CI 93% to 100%) for National Institute of Clinical Excellence, and 99.1% (95% CI 94% to 100%) for the other 4 clinical decision instruments. Sensitivity for any intracranial lesion ranged from 95.7% (95% CI 93% to 97%) (Scandinavian) to 100% (95% CI 98% to 100%) (National Institute of Clinical Excellence). In contrast, specificities varied between 30.9% (95% CI 30% to 32%) (National Institute of Clinical Excellence) and 52.9% (95% CI 52% to 54) (Scandinavian). NEXUS-II and the Scandinavian clinical decision aids displayed the best combination of sensitivity and specificity in this patient population. However, we cannot demonstrate that the higher sensitivity of NEXUS-II for surgical hematomas is statistically significant. Therefore, choosing which of the 2 clinical decision instruments to use must be based on decisionmakers' attitudes toward risk.

Clinical decision support systems in child and adolescent psychiatry: a systematic review.

PubMed

Koposov, Roman; Fossum, Sturla; Frodl, Thomas; Nytrø, Øystein; Leventhal, Bennett; Sourander, Andre; Quaglini, Silvana; Molteni, Massimo; de la Iglesia Vayá, María; Prokosch, Hans-Ulrich; Barbarini, Nicola; Milham, Michael Peter; Castellanos, Francisco Xavier; Skokauskas, Norbert

2017-11-01

Psychiatric disorders are amongst the most prevalent and impairing conditions in childhood and adolescence. Unfortunately, it is well known that general practitioners (GPs) and other frontline health providers (i.e., child protection workers, public health nurses, and pediatricians) are not adequately trained to address these ubiquitous problems (Braddick et al. Child and Adolescent mental health in Europe: infrastructures, policy and programmes, European Communities, 2009; Levav et al. Eur Child Adolesc Psychiatry 13:395-401, 2004). Advances in technology may offer a solution to this problem with clinical decision support systems (CDSS) that are designed to help professionals make sound clinical decisions in real time. This paper offers a systematic review of currently available CDSS for child and adolescent mental health disorders prepared according to the PRISMA-Protocols (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols). Applying strict eligibility criteria, the identified studies (n = 5048) were screened. Ten studies, describing eight original clinical decision support systems for child and adolescent psychiatric disorders, fulfilled inclusion criteria. Based on this systematic review, there appears to be a need for a new, readily available CDSS for child neuropsychiatric disorder which promotes evidence-based, best practices, while enabling consideration of national variation in practices by leveraging data-reuse to generate predictions regarding treatment outcome, addressing a broader cluster of clinical disorders, and targeting frontline practice environments.

Decision curve analysis for assessing the usefulness of tests for making decisions to treat: an application to tests for prodromal psychosis.

PubMed

Pulleyblank, Ryan; Chuma, Jefter; Gilbody, Simon M; Thompson, Carl

2013-09-01

For a test to be considered useful for making treatment decisions, it is necessary that making treatment decisions based on the results of the test be a preferable strategy to making treatment decisions without the test. Decision curve analysis is a framework for assessing when a test would be expected to be useful, which integrates evidence of a test's performance characteristics (sensitivity and specificity), condition prevalence among at-risk patients, and patient preferences for treatment. We describe decision curve analysis generally and illustrate its potential through an application to tests for prodromal psychosis. Clinical psychosis is often preceded by a prodromal phase, but not all those with prodromal symptoms proceed to develop full psychosis. Patients identified as at risk for developing psychosis may be considered for proactive treatment to mitigate development of clinically defined psychosis. Tests exist to help identify those at-risk patients most likely to develop psychosis, but it is uncertain when these tests would be considered useful for making proactive treatment decisions. We apply decision curve analysis to results from a systematic review of studies investigating clinical tests for predicting the development of psychosis in at-risk populations, and present resulting decision curves that illustrate when the tests may be expected to be useful for making proactive treatment decisions.

[Evidence-based aspects of clinical mastitis treatment].

PubMed

Mansion-de Vries, E M; Hoedemaker, M; Krömker, V

2015-01-01

Mastitis is one of the most common and expensive diseases in dairy cattle. The decision to treat clinical mastitis is usually made without any knowledge of the etiology, and can therefore only be evidence-based to a limited extent. Evidence-based medicine relies essentially on a combination of one's own clinical competence and scientific findings. In mastitis therapy, those insights depend mostly on pathogen-specific factors. Therefore, in evidence-based therapeutic decision making the pathogen identification should serve as a basis for the consideration of scientifically validated therapeutic concepts. The present paper considers evidence-based treatment of clinical mastitis based on a literature review. The authors conclude that an anti-inflammatory treatment using an NSAID should be conducted regardless of the pathogen. However, the choice of an antibiotic therapy depends on the mastitis causative pathogen, clinical symptoms and the animal itself. In principle, a local antibiotic treatment should be chosen for mild and moderate mastitis. It should be noted, that the benefit of an antibiotic therapy for coliform infections is questionable. With knowledge concerning the pathogen, it appears entirely reasonable to refrain from an antibiotic therapy. For severe (i.   e. feverish) mastitis, a parenteral antibiotic therapy should be selected. An extension of the antibiotic therapy beyond the manufacturer's information is only reasonable for streptococcal infections. It is important to make the decision on a prolonged antibiotic therapy only with the knowledge of the mastitis-causative pathogen. In terms of the therapy of a staphylococcus or streptococcus infection, a narrow-spectrum antibiotic from the penicillin family should be adopted when selecting the active agents.

Development of a digital clinical pathway for emergency medicine: Lessons from usability testing and implementation failure.

PubMed

Gutenstein, Marc; Pickering, John W; Than, Martin

2018-06-01

Clinical pathways are used to support the management of patients in emergency departments. An existing document-based clinical pathway was used as the foundation on which to design and build a digital clinical pathway for acute chest pain, with the aim of improving clinical calculations, clinician decision-making, documentation, and data collection. Established principles of decision support system design were used to build an application within the existing electronic health record, before testing with a multidisciplinary team of doctors using a think-aloud protocol. Technical authoring was successful, however, usability testing revealed that the user experience and the flexibility of workflow within the application were critical barriers to implementation. Emergency medicine and acute care decision support systems face particular challenges to existing models of linear workflow that should be deliberately addressed in digital pathway design. We make key recommendations regarding digital pathway design in emergency medicine.

Mobile Clinical Decision Support System for Acid-base Balance Diagnosis and Treatment Recommendation

PubMed Central

Mandzuka, Mensur; Begic, Edin; Boskovic, Dusanka; Begic, Zijo; Masic, Izet

2017-01-01

Introduction: This paper presents mobile application implementing a decision support system for acid-base disorder diagnosis and treatment recommendation. Material and methods: The application was developed using the official integrated development environment for the Android platform (to maximize availability and minimize investments in specialized hardware) called Android Studio. Results: The application identifies disorder, based on the blood gas analysis, evaluates whether the disorder has been compensated, and based on additional input related to electrolyte imbalance, provides recommendations for treatment. Conclusion: The application is a tool in the hands of the user, which provides assistance during acid-base disorders treatment. The application will assist the physician in clinical practice and is focused on the treatment in intensive care. PMID:28883678

Advance care planning for patients with amyotrophic lateral sclerosis.

PubMed

Levi, Benjamin H; Simmons, Zachary; Hanna, Courtney; Brothers, Allyson; Lehman, Erik; Farace, Elana; Bain, Megan; Stewart, Renee; Green, Michael J

2017-08-01

To determine whether an advance care planning (ACP) decision-aid could improve communication about end-of-life treatment wishes between patients with amyotrophic lateral sclerosis (ALS) and their clinicians. Forty-four patients with ALS (>21, English-speaking, without dementia) engaged in ACP using an interactive computer based decision-aid. Before participants completed the intervention, and again three months later, their clinicians reviewed three clinical vignettes, and made treatment decisions (n = 18) for patients. After patients indicated their agreement with the team's decisions, concordance was calculated. The mean concordance between patient wishes and the clinical team decisions was significantly higher post-intervention (post = 91.9%, 95% CI = 87.8, 96.1, vs. pre = 52.4%, 95% CI = 41.9, 62.9; p <0.001). Clinical team members reported greater confidence that their decisions accurately represented each patient's wishes post-intervention (mean = 6.5) compared to pre-intervention (mean = 3.3, 1 = low, 10 = high, p <0.001). Patients reported high satisfaction (mean = 26.4, SD = 3.2; 6 = low, 30 = high) and low decisional conflict (mean = 28.8, SD = 8.2; 20 = low, 80 = high) with decisions about end-of-life care, and high satisfaction with the decision-aid (mean = 52.7, SD = 5.7, 20 = low, 60 = high). Patient knowledge regarding ACP increased post-intervention (pre = 47.8% correct responses vs. post = 66.3%; p <0.001) without adversely affecting patient anxiety or self-determination. A computer based ACP decision-aid can significantly improve clinicians' understanding of ALS patients' wishes with regard to end-of-life medical care.

Informing clinical policy decision-making practices in ambulance services.

PubMed

Muecke, Sandy; Curac, Nada; Binks, Darryn

2013-12-01

This study aims to identify the processes and frameworks that support an evidence-based approach to clinical policy decision-making practices in ambulance services. This literature review focused on: (i) the setting (pre-hospital); and (ii) the process of evidence translation, for studies published after the year 2000. Searches of Medline, CINAHL and Google were undertaken. Reference lists of eligible publications were searched for relevant articles. A total of 954 articles were identified. Of these, 20 full text articles were assessed for eligibility and seven full text articles met the inclusion criteria. Three provided detailed descriptions of the evidence-based practice processes used to inform ambulance service protocol or guideline development or review. There is little published literature that describes the processes involved, and frameworks required, to inform clinical policy decision making within ambulance services. This review found that processes were iterative and involved collaborations across many internal and external stakeholders. In several jurisdictions, these were coordinated by a dedicated team. Success appears dependent on committed leadership and purposive human and structural resources. Although time consuming, structured processes have been developed in some jurisdictions to assist decision-making processes. Further insight is likely to be obtained from literature published by those from other disciplines. © 2013 The Authors. International Journal of Evidence-Based Healthcare © 2013 The Joanna Briggs Institute.

Scalable software architectures for decision support.

PubMed

Musen, M A

1999-12-01

Interest in decision-support programs for clinical medicine soared in the 1970s. Since that time, workers in medical informatics have been particularly attracted to rule-based systems as a means of providing clinical decision support. Although developers have built many successful applications using production rules, they also have discovered that creation and maintenance of large rule bases is quite problematic. In the 1980s, several groups of investigators began to explore alternative programming abstractions that can be used to build decision-support systems. As a result, the notions of "generic tasks" and of reusable problem-solving methods became extremely influential. By the 1990s, academic centers were experimenting with architectures for intelligent systems based on two classes of reusable components: (1) problem-solving methods--domain-independent algorithms for automating stereotypical tasks--and (2) domain ontologies that captured the essential concepts (and relationships among those concepts) in particular application areas. This paper highlights how developers can construct large, maintainable decision-support systems using these kinds of building blocks. The creation of domain ontologies and problem-solving methods is the fundamental end product of basic research in medical informatics. Consequently, these concepts need more attention by our scientific community.

[Evidence-based Risk and Benefit Communication for Shared Decision Making].

PubMed

Nakayama, Takeo

2018-01-01

　Evidence-based medicine (EBM) can be defined as "the integration of the best research evidence with clinical expertise and a patient's unique values and circumstances". However, even with the best research evidence, many uncertainties can make clinical decisions difficult. As the social requirement of respecting patient values and preferences has been increasingly recognized, shared decision making (SDM) and consensus development between patients and clinicians have attracted attention. SDM is a process by which patients and clinicians make decisions and arrive at a consensus through interactive conversations and communications. During the process of SDM, patients and clinicians share information with each other on the goals they hope to achieve and responsibilities in meeting those goals. From the clinician's standpoint, information regarding the benefits and risks of potential treatment options based on current evidence and professional experience is provided to patients. From the patient's standpoint, information on personal values, preferences, and social roles is provided to clinicians. SDM is a sort of "wisdom" in the context of making autonomous decisions in uncertain, difficult situations through interactions and cooperation between patients and clinicians. Joint development of EBM and SDM will help facilitate patient-clinician relationships and improve the quality of healthcare.

Factors influencing nurses' decision-making process on leaving in the peripheral intravascular catheter after 96 hours: a longitudinal study.

PubMed

Palese, Alvisa; Cassone, Andrea; Kulla, Annamaria; Dorigo, Sabrina; Magee, Jesse; Artico, Marco; Camero, Francesco; Cassin, Catia; Cialdella, Sandra; Floridia, Giuseppe; Nadlišek, Boris; Palcic, Annamaria; Valle, Giulia; Sclauzero, Paola

2011-01-01

The clinical and research debate on the peripheral intravascular (PIV) catheter length of stay in situ is ongoing. The principal aim of this study was to explore the factors behind a nurse's decision to leave a PIV in place for more than 96 hours. The study focused on 7 northern Italian hospitals in 2009. A consequent sample of 269 PIV catheters was included. Direct observation and interviews were adopted. The time of the expected PIV replacement was fixed at 96 hours after its positioning, in accordance with the international guideline. Several factors were taken into account in regard to replacement of the PIV catheters by nurses, ranging from analysis based on their own clinical experience with PIV complications and analysis of the patient's clinical situation to the critical analysis of their own work situation. This clinical decision-making process is valuable: leaving the PIV in place for more than 96 hours is a complex decision and not simply a guideline violation.

Privacy-preserving clinical decision support system using Gaussian kernel-based classification.

PubMed

Rahulamathavan, Yogachandran; Veluru, Suresh; Phan, Raphael C-W; Chambers, Jonathon A; Rajarajan, Muttukrishnan

2014-01-01

A clinical decision support system forms a critical capability to link health observations with health knowledge to influence choices by clinicians for improved healthcare. Recent trends toward remote outsourcing can be exploited to provide efficient and accurate clinical decision support in healthcare. In this scenario, clinicians can use the health knowledge located in remote servers via the Internet to diagnose their patients. However, the fact that these servers are third party and therefore potentially not fully trusted raises possible privacy concerns. In this paper, we propose a novel privacy-preserving protocol for a clinical decision support system where the patients' data always remain in an encrypted form during the diagnosis process. Hence, the server involved in the diagnosis process is not able to learn any extra knowledge about the patient's data and results. Our experimental results on popular medical datasets from UCI-database demonstrate that the accuracy of the proposed protocol is up to 97.21% and the privacy of patient data is not compromised.

SU-E-J-04: A Data-Driven, Response-Based, Multi-Criteria Decision Support System for Personalized Lung Radiation Treatment Planning

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

Luo, Y; McShan, D; Schipper, M

2014-06-01

Purpose: To develop a decision support tool to predict a patient's potential overall survival (OS) and radiation induced toxicity (RIT) based on clinical factors and responses during the course of radiotherapy, and suggest appropriate radiation dose adjustments to improve therapeutic effect. Methods: Important relationships between a patient's basic information and their clinical features before and during the radiation treatment are identified from historical clinical data by using statistical learning and data mining approaches. During each treatment period, a data analysis (DA) module predicts radiotherapy features such as time to local progression (TTLP), time to distant metastases (TTDM), radiation toxicity tomore » different organs, etc., under possible future treatment plans based on patient specifics or responses. An information fusion (IF) module estimates intervals for a patient's OS and the probabilities of RIT from a treatment plan by integrating the outcomes of module DA. A decision making (DM) module calculates “satisfaction” with the predicted radiation outcome based on trade-offs between OS and RIT, and finds the best treatment plan for the next time period via multi-criteria optimization. Results: Using physical and biological data from 130 lung cancer patients as our test bed, we were able to train and implement the 3 modules of our decision support tool. Examples demonstrate how it can help predict a new patient's potential OS and RIT with different radiation dose plans along with how these combinations change with dose, thus presenting a range of satisfaction/utility for use in individualized decision support. Conclusion: Although the decision support tool is currently developed from a small patient sample size, it shows the potential for the improvement of each patient's satisfaction in personalized radiation therapy. The radiation treatment outcome prediction and decision making model needs to be evaluated with more patients and demonstrated for use in radiation treatments for other cancers. P01-CA59827;R01CA142840.« less

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 Conceptual Framework for Decision-making Support in Uncertainty- and Risk-based Diagnosis of Rare Clinical Cases by Specialist Physicians.

PubMed

Santos, Adriano A; Moura, J Antão B; de Araújo, Joseana Macêdo Fechine Régis

2015-01-01

Mitigating uncertainty and risks faced by specialist physicians in analysis of rare clinical cases is something desired by anyone who needs health services. The number of clinical cases never seen by these experts, with little documentation, may introduce errors in decision-making. Such errors negatively affect well-being of patients, increase procedure costs, rework, health insurance premiums, and impair the reputation of specialists and medical systems involved. In this context, IT and Clinical Decision Support Systems (CDSS) play a fundamental role, supporting decision-making process, making it more efficient and effective, reducing a number of avoidable medical errors and enhancing quality of treatment given to patients. An investigation has been initiated to look into characteristics and solution requirements of this problem, model it, propose a general solution in terms of a conceptual risk-based, automated framework to support rare-case medical diagnostics and validate it by means of case studies. A preliminary validation study of the proposed framework has been carried out by interviews conducted with experts who are practicing professionals, academics, and researchers in health care. This paper summarizes the investigation and its positive results. These results motivate continuation of research towards development of the conceptual framework and of a software tool that implements the proposed model.

Using decision analysis to assess comparative clinical efficacy of surgical treatment of unstable ankle fractures.

PubMed

Michelson, James D

2013-11-01

The development of a robust treatment algorithm for ankle fractures based on well-established stability criteria has been shown to be prognostic with respect to treatment and outcomes. In parallel with the development of improved understanding of the biomechanical rationale of ankle fracture treatment has been an increased emphasis on assessing the effectiveness of medical and surgical interventions. The purpose of this study was to investigate the use of using decision analysis in the assessment of the cost effectiveness of operative treatment of ankle fractures based on the existing clinical data in the literature. Using the data obtained from a previous structured review of the ankle fracture literature, decision analysis trees were constructed using standard software. The decision nodes for the trees were based on ankle fracture stability criteria previously published. The outcomes were assessed by calculated Quality-Adjusted Life Years (QALYs) assigned to achieving normal ankle function, developing posttraumatic arthritis, or sustaining a postoperative infection. Sensitivity analysis was undertaken by varying the patient's age, incidence of arthritis, and incidence or infection. Decision analysis trees captured the essential aspects of clinical decision making in ankle fracture treatment in a clinically useful manner. In general, stable fractures yielded better outcomes with nonoperative treatment, whereas unstable fractures had better outcomes with surgery. These were consistent results over a wide range of postoperative infection rates. Varying the age of the patient did not qualitatively change the results. Between the ages of 30 and 80 years, surgery yielded higher expected QALYs than nonoperative care for unstable fractures, and generated lower QALYs than nonoperative care for stable fractures. Using local cost estimates for operative and nonoperative treatment, the incremental cost of surgery for unstable fractures was less than $40,000 per QALY (the usual cutoff for the determination of cost effectiveness) for patients aged up to 90 years. Decision analysis is a useful methodology in developing treatment guidelines. Numerous previous studies have indicated superior clinical outcomes when unstable ankle fractures underwent operative reduction and stabilization. What has been lacking was an examination of the cost effectiveness of such an approach, particularly in older patients who have fewer expected years of life. In light of the evidence for satisfactory outcomes for surgery of severe ankle fractures in older people, the justification for operative intervention is an obvious question that can be asked in the current increasingly cost-conscious environment. Using a decision-tree decision analysis structured around the stability-based ankle fracture classification system, in conjunction with a relatively simple cost effectiveness analysis, this study was able to demonstrate that surgical treatment of unstable ankle fractures in elderly patients is in fact cost effective. The clinical implication of the present analysis is that these existing treatment protocols for ankle fracture treatment are also cost effective when quality of life outcome measures are taken into account. Economic Level II. See Instructions for Authors for a complete description of levels of evidence.

DXplain: a Web-based diagnostic decision support system for medical students.

PubMed

London, S

1998-01-01

DXplain is a diagnostic decision support program, with a new World Wide Web interface, designed to help medical students and physicians formulate differential diagnoses based on clinical findings. It covers over 2000 diseases and 5000 clinical manifestations. DXplain suggests possible diagnoses, and provides brief descriptions of every disease in the database. Not all diseases are included, nor does DXplain take into account preexisting conditions or the chronological sequence of clinical manifestations. Despite these limitations, it is a useful educational tool, particularly for problem-based learning (PBL) cases and for students in clinical rotations, as it fills a niche not adequately covered by MEDLINE or medical texts. The system is relatively self-explanatory, requiring little or no end-user training. Medical libraries offering, or planning to offer, their users access to Web-based materials and resources may find this system a valuable addition to their electronic collections. Should it prove popular with the local users, provision of access may also establish or enhance the library's image as a partner in medical education.

Applying Kane's Validity Framework to a Simulation Based Assessment of Clinical Competence

ERIC Educational Resources Information Center

Tavares, Walter; Brydges, Ryan; Myre, Paul; Prpic, Jason; Turner, Linda; Yelle, Richard; Huiskamp, Maud

2018-01-01

Assessment of clinical competence is complex and inference based. Trustworthy and defensible assessment processes must have favourable evidence of validity, particularly where decisions are considered high stakes. We aimed to organize, collect and interpret validity evidence for a high stakes simulation based assessment strategy for certifying…

Knowledge of and Attitudes Toward Evidence-Based Guidelines for and Against Clinical Preventive Services: Results from a National Survey.

PubMed

Lantz, Paula M; Evans, W Douglas; Mead, Holly; Alvarez, Carmen; Stewart, Lisa

2016-03-01

Both the underuse and overuse of clinical preventive services relative to evidence-based guidelines are a public health concern. Informed consumers are an important foundation of many components of the Affordable Care Act, including coverage mandates for proven clinical preventive services recommended by the US Preventive Services Task Force. Across sociodemographic groups, however, knowledge of and positive attitudes toward evidence-based guidelines for preventive care are extremely low. Given the demonstrated low levels of consumers' knowledge of and trust in guidelines, coupled with their strong preference for involvement in preventive care decisions, better education and decision-making support for evidence-based preventive services are greatly needed. Both the underuse and overuse of clinical preventive services are a serious public health problem. The goal of our study was to produce population-based national data that could assist in the design of communication strategies to increase knowledge of and positive attitudes toward evidence-based guidelines for clinical preventive services (including the US Preventive Services Task Force, USPSTF) and to reduce uncertainty among patients when guidelines change or are controversial. In late 2013 we implemented an Internet-based survey of a nationally representative sample of 2,529 adults via KnowledgePanel, a probability-based survey panel of approximately 60,000 adults, statistically representative of the US noninstitutionalized population. African Americans, Hispanics, and those with less than a high school education were oversampled. We then conducted descriptive statistics and multivariable logistic regression analysis to identify the prevalence of and sociodemographic characteristics associated with key knowledge and attitudinal variables. While 36.4% of adults reported knowing that the Affordable Care Act requires insurance companies to cover proven preventive services without cost sharing, only 7.7% had heard of the USPSTF. Approximately 1 in 3 (32.6%) reported trusting that a government task force would make fair guidelines for preventive services, and 38.2% believed that the government uses guidelines to ration health care. Most of the respondents endorsed the notion that research/scientific evidence and expert medical opinion are important for the creation of guidelines and that clinicians should follow guidelines based on evidence. But when presented with patient vignettes in which a physician made a guideline-based recommendation against a cancer-screening test, less than 10% believed that this recommendation alone, without further dialogue and/or the patient's own research, was sufficient to make such a decision. Given these demonstrated low levels of knowledge and mistrust regarding guidelines, coupled with a strong preference for shared decision making, better consumer education and decision supports for evidence-based guidelines for clinical preventive services are greatly needed. © 2016 Milbank Memorial Fund.

Genders of patients and clinicians and their effect on shared decision making: a participant-level meta-analysis.

PubMed

Wyatt, Kirk D; Branda, Megan E; Inselman, Jonathan W; Ting, Henry H; Hess, Erik P; Montori, Victor M; LeBlanc, Annie

2014-09-02

Gender differences in communication styles between clinicians and patients have been postulated to impact patient care, but the extent to which the gender dyad structure impacts outcomes in shared decision making remains unclear. Participant-level meta-analysis of 775 clinical encounters within 7 randomized trials where decision aids, shared decision making tools, were used at the point of care. Outcomes analysed include decisional conflict scale scores, satisfaction with the clinical encounter, concordance between stated decision and action taken, and degree of patient engagement by the clinician using the OPTION scale. An estimated minimal important difference was used to determine if nonsignificant results could be explained by low power. We did not find a statistically significant interaction between clinician/patient gender mix and arm for decisional conflict, satisfaction with the clinical encounter or patient engagement. A borderline significant interaction (p = 0.05) was observed for one outcome: concordance between stated decision and action taken, where encounters with female clinician/male patient showed increased concordance in the decision aid arm compared to control (8% more concordant encounters). All other gender dyads showed decreased concordance with decision aid use (6% fewer concordant encounters for same-gender, 16% fewer concordant encounters for male clinician/female patient). In this participant-level meta-analysis of 7 randomized trials, decision aids used at the point of care demonstrated comparable efficacy across gender dyads. Purported barriers to shared decision making based on gender were not detected when tested for a minimum detected difference. ClinicalTrials.gov NCT00888537, NCT01077037, NCT01029288, NCT00388050, NCT00578981, NCT00949611, NCT00217061.

How should treatment costs impact on physician's decisions?

PubMed

Neymark, N

1999-01-01

This article first discusses at what level of clinical decision making cost considerations may be most pertinent and important. It is argued that cost assessments will be of most relevance and value at an intermediate level of clinical decision making i.e. at a level where so-called policy decisions are made. These are decisions such as which drugs to include in a hospital formulary or which standard treatment 'protocols' to choose for particular types of patients. The personal encounter between individual patients and physicians will take place within the framework of available treatment options determined by these policy decisions, which must necessarily be based on a prior assessment of the expected costs and benefits of treatments. The article goes on to give a brief introduction to the various methods of economic evaluation that have been developed in order to provide the decision makers with the means to make policy decisions on the basis of the most reliable and pertinent information possible.

Is it the time to rethink clinical decision-making strategies? From a single clinical outcome evaluation to a Clinical Multi-criteria Decision Assessment (CMDA).

PubMed

Migliore, Alberto; Integlia, Davide; Bizzi, Emanuele; Piaggio, Tomaso

2015-10-01

There are plenty of different clinical, organizational and economic parameters to consider in order having a complete assessment of the total impact of a pharmaceutical treatment. In the attempt to follow, a holistic approach aimed to provide an evaluation embracing all clinical parameters in order to choose the best treatments, it is necessary to compare and weight multiple criteria. Therefore, a change is required: we need to move from a decision-making context based on the assessment of one single criteria towards a transparent and systematic framework enabling decision makers to assess all relevant parameters simultaneously in order to choose the best treatment to use. In order to apply the MCDA methodology to clinical decision making the best pharmaceutical treatment (or medical devices) to use to treat a specific pathology, we suggest a specific application of the Multiple Criteria Decision Analysis for the purpose, like a Clinical Multi-criteria Decision Assessment CMDA. In CMDA, results from both meta-analysis and observational studies are used by a clinical consensus after attributing weights to specific domains and related parameters. The decision will result from a related comparison of all consequences (i.e., efficacy, safety, adherence, administration route) existing behind the choice to use a specific pharmacological treatment. The match will yield a score (in absolute value) that link each parameter with a specific intervention, and then a final score for each treatment. The higher is the final score; the most appropriate is the intervention to treat disease considering all criteria (domain an parameters). The results will allow the physician to evaluate the best clinical treatment for his patients considering at the same time all relevant criteria such as clinical effectiveness for all parameters and administration route. The use of CMDA model will yield a clear and complete indication of the best pharmaceutical treatment to use for patients, helping physicians to choose drugs with a complete set of information, imputed in the model. Copyright © 2015 Elsevier Ltd. All rights reserved.

Systematic Review of Medical Informatics-Supported Medication Decision Making.

PubMed

Melton, Brittany L

2017-01-01

This systematic review sought to assess the applications and implications of current medical informatics-based decision support systems related to medication prescribing and use. Studies published between January 2006 and July 2016 which were indexed in PubMed and written in English were reviewed, and 39 studies were ultimately included. Most of the studies looked at computerized provider order entry or clinical decision support systems. Most studies examined decision support systems as a means of reducing errors or risk, particularly associated with medication prescribing, whereas a few studies evaluated the impact medical informatics-based decision support systems have on workflow or operations efficiency. Most studies identified benefits associated with decision support systems, but some indicate there is room for improvement.

An HL7-CDA wrapper for facilitating semantic interoperability to rule-based Clinical Decision Support Systems.

PubMed

Sáez, Carlos; Bresó, Adrián; Vicente, Javier; Robles, Montserrat; García-Gómez, Juan Miguel

2013-03-01

The success of Clinical Decision Support Systems (CDSS) greatly depends on its capability of being integrated in Health Information Systems (HIS). Several proposals have been published up to date to permit CDSS gathering patient data from HIS. Some base the CDSS data input on the HL7 reference model, however, they are tailored to specific CDSS or clinical guidelines technologies, or do not focus on standardizing the CDSS resultant knowledge. We propose a solution for facilitating semantic interoperability to rule-based CDSS focusing on standardized input and output documents conforming an HL7-CDA wrapper. We define the HL7-CDA restrictions in a HL7-CDA implementation guide. Patient data and rule inference results are mapped respectively to and from the CDSS by means of a binding method based on an XML binding file. As an independent clinical document, the results of a CDSS can present clinical and legal validity. The proposed solution is being applied in a CDSS for providing patient-specific recommendations for the care management of outpatients with diabetes mellitus. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Automated Detection of Glaucoma From Topographic Features of the Optic Nerve Head in Color Fundus Photographs.

PubMed

Chakrabarty, Lipi; Joshi, Gopal Datt; Chakravarty, Arunava; Raman, Ganesh V; Krishnadas, S R; Sivaswamy, Jayanthi

2016-07-01

To describe and evaluate the performance of an automated CAD system for detection of glaucoma from color fundus photographs. Color fundus photographs of 2252 eyes from 1126 subjects were collected from 2 centers: Aravind Eye Hospital, Madurai and Coimbatore, India. The images of 1926 eyes (963 subjects) were used to train an automated image analysis-based system, which was developed to provide a decision on a given fundus image. A total of 163 subjects were clinically examined by 2 ophthalmologists independently and their diagnostic decisions were recorded. The consensus decision was defined to be the clinical reference (gold standard). Fundus images of eyes with disagreement in diagnosis were excluded from the study. The fundus images of the remaining 314 eyes (157 subjects) were presented to 4 graders and their diagnostic decisions on the same were collected. The performance of the system was evaluated on the 314 images, using the reference standard. The sensitivity and specificity of the system and 4 independent graders were determined against the clinical reference standard. The system achieved an area under receiver operating characteristic curve of 0.792 with a sensitivity of 0.716 and specificity of 0.717 at a selected threshold for the detection of glaucoma. The agreement with the clinical reference standard as determined by Cohen κ is 0.45 for the proposed system. This is comparable to that of the image-based decisions of 4 ophthalmologists. An automated system was presented for glaucoma detection from color fundus photographs. The overall evaluation results indicated that the presented system was comparable in performance to glaucoma classification by a manual grader solely based on fundus image examination.

Financial Concerns About Participation in Clinical Trials Among Patients With Cancer.

PubMed

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

2016-02-10

The decision to enroll in a clinical trial is complex given the uncertain risks and benefits of new approaches. Many patients also have financial concerns. We sought to characterize the association between financial concerns and the quality of decision making about clinical trials. We conducted a secondary data analysis of a randomized trial of a Web-based educational tool (Preparatory Education About Clinical Trials) designed to improve the preparation of patients with cancer for making decisions about clinical trial enrollment. Patients completed a baseline questionnaire that included three questions related to financial concerns (five-point Likert scales): "How much of a burden on you is the cost of your medical care?," "I'm afraid that my health insurance won't pay for a clinical trial," and "I'm worried that I wouldn't be able to afford the costs of treatment on a clinical trial." Results were summed, with higher scores indicating greater concerns. We used multiple linear regressions to measure the association between concerns and self-reported measures of self-efficacy, preparation for decision making, distress, and decisional conflict in separate models, controlling for sociodemographic characteristics. One thousand two hundred eleven patients completed at least one financial concern question. Of these, 27% were 65 years or older, 58% were female, and 24% had a high school education or less. Greater financial concern was associated with lower self-efficacy and preparation for decision making, as well as with greater decisional conflict and distress, even after adjustment for age, race, sex, education, employment, and hospital location (P < .001 for all models). Financial concerns are associated with several psychological constructs that may negatively influence decision quality regarding clinical trials. Greater attention to patients' financial needs and concerns may reduce distress and improve patient decision making. © 2015 by American Society of Clinical Oncology.

Development and impact of computerised decision support systems for clinical management of depression: A systematic review.

PubMed

Triñanes, Yolanda; Atienza, Gerardo; Louro-González, Arturo; de-las-Heras-Liñero, Elena; Alvarez-Ariza, María; Palao, Diego J

2015-01-01

One of the proposals for improving clinical practice is to introduce computerised decision support systems (CDSS) and integrate these with electronic medical records. Accordingly, this study sought to systematically review evidence on the effectiveness of CDSS in the management of depression. A search was performed in Medline, EMBASE and PsycInfo, in order to do this. The quality of quantitative studies was assessed using the SIGN method, and qualitative studies using the CASPe checklist. Seven studies were identified (3 randomised clinical trials, 3 non-randomised trials, and one qualitative study). The CDSS assessed incorporated content drawn from guidelines and other evidence-based products. In general, the CDSS had a positive impact on different aspects, such as the screening and diagnosis, treatment, improvement in depressive symptoms and quality of life, and referral of patients. The use of CDSS could thus serve to optimise care of depression in various scenarios by providing recommendations based on the best evidence available and facilitating decision-making in clinical practice. Copyright © 2014 SEP y SEPB. Published by Elsevier España. All rights reserved.

Medicine Based Evidence for Individualized Decision Making: Case Study of Systemic Lupus Erythematosus.

PubMed

Wivel, Ashley E; Lapane, Kate; Kleoudis, Christi; Singer, Burton H; Horwitz, Ralph I

2017-11-01

To guide management decisions for an index patient, evidence is required from comparisons between approximate matches to the profile of the index case, where some matches contain responses to treatment and others act as controls. We describe a method for constructing clinically relevant histories/profiles using data collected but unreported from 2 recent phase 3 randomized controlled trials assessing belimumab in subjects with clinically active and serologically positive systemic lupus erythematosus. Outcome was the Systemic lupus erythematosus Responder Index (SRI) measured at 52 weeks. Among 1175 subjects, we constructed an algorithm utilizing 11 trajectory variables including 4 biological, 2 clinical, and 5 social/behavioral. Across all biological and social/behavioral variables, the proportion of responders based on the SRI whose value indicated clinical worsening or no improvement ranged from 27.5% to 42.3%. Kappa values suggested poor agreement, indicating that each biological and patient-reported outcome provides different information than gleaned from the SRI. The richly detailed patient profiles needed to guide decision-making in clinical practice are sharply at odds with the limited information utilized in conventional randomized controlled trial analyses. Copyright © 2017 Elsevier Inc. All rights reserved.

From guideline modeling to guideline execution: defining guideline-based decision-support services.

PubMed Central

Tu, S. W.; Musen, M. A.

2000-01-01

We describe our task-based approach to defining the guideline-based decision-support services that the EON system provides. We categorize uses of guidelines in patient-specific decision support into a set of generic tasks--making of decisions, specification of work to be performed, interpretation of data, setting of goals, and issuance of alert and reminders--that can be solved using various techniques. Our model includes constructs required for representing the knowledge used by these techniques. These constructs form a toolkit from which developers can select modeling solutions for guideline task. Based on the tasks and the guideline model, we define a guideline-execution architecture and a model of interactions between a decision-support server and clients that invoke services provided by the server. These services use generic interfaces derived from guideline tasks and their associated modeling constructs. We describe two implementations of these decision-support services and discuss how this work can be generalized. We argue that a well-defined specification of guideline-based decision-support services will facilitate sharing of tools that implement computable clinical guidelines. PMID:11080007

Patient, physician and presentational influences on clinical decision making for breast cancer: results from a factorial experiment.

PubMed

McKinlay, J B; Burns, R B; Durante, R; Feldman, H A; Freund, K M; Harrow, B S; Irish, J T; Kasten, L E; Moskowitz, M A

1997-02-01

This study examines the influence of six patient characteristics (age, race, socioeconomic status, comorbidities, mobility and presentational style) and two physician characteristics (medical specialty and years of clinical experience) on physicians' clinical decision making behaviour in the evaluation treatment of an unknown and known breast cancer. Physicians' variability and certainty associated with diagnostic and treatment behaviour were also examined. Separate analyses explored the influence of these non-medical factors on physicians' cognitive processes. Using a fractional factorial design, 128 practising physicians were shown two videotaped scenarios and asked about possible diagnoses and medical recommendations. Results showed that physicians displayed considerable variability in response to several patient-based factors. Physician characteristics also emerged as important predictors of clinical behaviour, thus confirming the complexity of the medical decision-making process.

Evaluating a Clinical Decision Support Interface for End-of-Life Nurse Care.

PubMed

Febretti, Alessandro; Stifter, Janet; Keenan, Gail M; Lopez, Karen D; Johnson, Andrew; Wilkie, Diana J

2014-01-01

Clinical Decision Support Systems (CDSS) are tools that assist healthcare personnel in the decision-making process for patient care. Although CDSSs have been successfully deployed in the clinical setting to assist physicians, few CDSS have been targeted at professional nurses, the largest group of health providers. We present our experience in designing and testing a CDSS interface embedded within a nurse care planning and documentation tool. We developed four prototypes based on different CDSS feature designs, and tested them in simulated end-of-life patient handoff sessions with a group of 40 nurse clinicians. We show how our prototypes directed nurses towards an optimal care decision that was rarely performed in unassisted practice. We also discuss the effect of CDSS layout and interface navigation in a nurse's acceptance of suggested actions. These findings provide insights into effective nursing CDSS design that are generalizable to care scenarios different than end-of-life.

Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: methods of a decision-maker-researcher partnership systematic review.

PubMed

Haynes, R Brian; Wilczynski, Nancy L

2010-02-05

Computerized clinical decision support systems are information technology-based systems designed to improve clinical decision-making. As with any healthcare intervention with claims to improve process of care or patient outcomes, decision support systems should be rigorously evaluated before widespread dissemination into clinical practice. Engaging healthcare providers and managers in the review process may facilitate knowledge translation and uptake. The objective of this research was to form a partnership of healthcare providers, managers, and researchers to review randomized controlled trials assessing the effects of computerized decision support for six clinical application areas: primary preventive care, therapeutic drug monitoring and dosing, drug prescribing, chronic disease management, diagnostic test ordering and interpretation, and acute care management; and to identify study characteristics that predict benefit. The review was undertaken by the Health Information Research Unit, McMaster University, in partnership with Hamilton Health Sciences, the Hamilton, Niagara, Haldimand, and Brant Local Health Integration Network, and pertinent healthcare service teams. Following agreement on information needs and interests with decision-makers, our earlier systematic review was updated by searching Medline, EMBASE, EBM Review databases, and Inspec, and reviewing reference lists through 6 January 2010. Data extraction items were expanded according to input from decision-makers. Authors of primary studies were contacted to confirm data and to provide additional information. Eligible trials were organized according to clinical area of application. We included randomized controlled trials that evaluated the effect on practitioner performance or patient outcomes of patient care provided with a computerized clinical decision support system compared with patient care without such a system. Data will be summarized using descriptive summary measures, including proportions for categorical variables and means for continuous variables. Univariable and multivariable logistic regression models will be used to investigate associations between outcomes of interest and study specific covariates. When reporting results from individual studies, we will cite the measures of association and p-values reported in the studies. If appropriate for groups of studies with similar features, we will conduct meta-analyses. A decision-maker-researcher partnership provides a model for systematic reviews that may foster knowledge translation and uptake.

Effect of clinical decision rules, patient cost and malpractice information on clinician brain CT image ordering: a randomized controlled trial.

PubMed

Gimbel, Ronald W; Pirrallo, Ronald G; Lowe, Steven C; Wright, David W; Zhang, Lu; Woo, Min-Jae; Fontelo, Paul; Liu, Fang; Connor, Zachary

2018-03-12

The frequency of head computed tomography (CT) imaging for mild head trauma patients has raised safety and cost concerns. Validated clinical decision rules exist in the published literature and on-line sources to guide medical image ordering but are often not used by emergency department (ED) clinicians. Using simulation, we explored whether the presentation of a clinical decision rule (i.e. Canadian CT Head Rule - CCHR), findings from malpractice cases related to clinicians not ordering CT imaging in mild head trauma cases, and estimated patient out-of-pocket cost might influence clinician brain CT ordering. Understanding what type and how information may influence clinical decision making in the ordering advanced medical imaging is important in shaping the optimal design and implementation of related clinical decision support systems. Multi-center, double-blinded simulation-based randomized controlled trial. Following standardized clinical vignette presentation, clinicians made an initial imaging decision for the patient. This was followed by additional information on decision support rules, malpractice outcome review, and patient cost; each with opportunity to modify their initial order. The malpractice and cost information differed by assigned group to test the any temporal relationship. The simulation closed with a second vignette and an imaging decision. One hundred sixteen of the 167 participants (66.9%) initially ordered a brain CT scan. After CCHR presentation, the number of clinicians ordering a CT dropped to 76 (45.8%), representing a 21.1% reduction in CT ordering (P = 0.002). This reduction in CT ordering was maintained, in comparison to initial imaging orders, when presented with malpractice review information (p = 0.002) and patient cost information (p = 0.002). About 57% of clinicians changed their order during study, while 43% never modified their imaging order. This study suggests that ED clinician brain CT imaging decisions may be influenced by clinical decision support rules, patient out-of-pocket cost information and findings from malpractice case review. NCT03449862 , February 27, 2018, Retrospectively registered.

Knowledge as a Service at the Point of Care.

PubMed

Shellum, Jane L; Freimuth, Robert R; Peters, Steve G; Nishimura, Rick A; Chaudhry, Rajeev; Demuth, Steve J; Knopp, Amy L; Miksch, Timothy A; Milliner, Dawn S

2016-01-01

An electronic health record (EHR) can assist the delivery of high-quality patient care, in part by providing the capability for a broad range of clinical decision support, including contextual references (e.g., Infobuttons), alerts and reminders, order sets, and dashboards. All of these decision support tools are based on clinical knowledge; unfortunately, the mechanisms for managing rules, order sets, Infobuttons, and dashboards are often unrelated, making it difficult to coordinate the application of clinical knowledge to various components of the clinical workflow. Additional complexity is encountered when updating enterprise-wide knowledge bases and delivering the content through multiple modalities to different consumers. We present the experience of Mayo Clinic as a case study to examine the requirements and implementation challenges related to knowledge management across a large, multi-site medical center. The lessons learned through the development of our knowledge management and delivery platform will help inform the future development of interoperable knowledge resources.

Knowledge as a Service at the Point of Care

PubMed Central

Shellum, Jane L.; Freimuth, Robert R.; Peters, Steve G.; Nishimura, Rick A.; Chaudhry, Rajeev; Demuth, Steve J.; Knopp, Amy L.; Miksch, Timothy A.; Milliner, Dawn S.

2016-01-01

An electronic health record (EHR) can assist the delivery of high-quality patient care, in part by providing the capability for a broad range of clinical decision support, including contextual references (e.g., Infobuttons), alerts and reminders, order sets, and dashboards. All of these decision support tools are based on clinical knowledge; unfortunately, the mechanisms for managing rules, order sets, Infobuttons, and dashboards are often unrelated, making it difficult to coordinate the application of clinical knowledge to various components of the clinical workflow. Additional complexity is encountered when updating enterprise-wide knowledge bases and delivering the content through multiple modalities to different consumers. We present the experience of Mayo Clinic as a case study to examine the requirements and implementation challenges related to knowledge management across a large, multi-site medical center. The lessons learned through the development of our knowledge management and delivery platform will help inform the future development of interoperable knowledge resources. PMID:28269911

A First Step towards a Clinical Decision Support System for Post-traumatic Stress Disorders.

PubMed

Ma, Sisi; Galatzer-Levy, Isaac R; Wang, Xuya; Fenyö, David; Shalev, Arieh Y

2016-01-01

PTSD is distressful and debilitating, following a non-remitting course in about 10% to 20% of trauma survivors. Numerous risk indicators of PTSD have been identified, but individual level prediction remains elusive. As an effort to bridge the gap between scientific discovery and practical application, we designed and implemented a clinical decision support pipeline to provide clinically relevant recommendation for trauma survivors. To meet the specific challenge of early prediction, this work uses data obtained within ten days of a traumatic event. The pipeline creates personalized predictive model for each individual, and computes quality metrics for each predictive model. Clinical recommendations are made based on both the prediction of the model and its quality, thus avoiding making potentially detrimental recommendations based on insufficient information or suboptimal model. The current pipeline outperforms the acute stress disorder, a commonly used clinical risk factor for PTSD development, both in terms of sensitivity and specificity.

Preclinical Bioavailability Strategy for Decisions on Clinical Drug Formulation Development: An In Depth Analysis.

PubMed

Van den Bergh, An; Van Hemelryck, Sandy; Bevernage, Jan; Van Peer, Achiel; Brewster, Marcus; Mackie, Claire; Mannaert, Erik

2018-06-11

The aim of the presented retrospective analysis was to verify whether a previously proposed Janssen Biopharmaceutical Classification System (BCS)-like decision tree, based on preclinical bioavailability data of a solution and suspension formulation, would facilitate informed decision making on the clinical formulation development strategy. In addition, the predictive value of (in vitro) selection criteria, such as solubility, human permeability, and/or a clinical dose number (Do), were evaluated, potentially reducing additional supporting formulation bioavailability studies in animals. The absolute ( F abs,sol ) and relative ( F rel, susp/sol ) bioavailability of an oral solution and suspension, respectively, in rat or dog and the anticipated BCS classification were analyzed for 89 Janssen compounds with 28 of these having F rel,susp/sol and F abs,sol in both rat and dog at doses around 10 and 5 mg/kg, respectively. The bioavailability outcomes in the dog aligned well with a BCS-like classification based upon the solubility of the active pharmaceutical ingredient (API) in biorelevant media, while the alignment was less clear for the bioavailability data in the rat. A retrospective analysis on the clinically tested formulations for a set of 12 Janssen compounds confirmed that the previously proposed animal bioavailability-based decision tree facilitated decisions on the oral formulation type, with the dog as the most discriminative species. Furthermore, the analysis showed that based on a Do for a standard human dose of 100 mg in aqueous and/or biorelevant media, a similar formulation type would have been selected compared to the one suggested by the animal data. However, the concept of a Do did not distinguish between solubility enhancing or enabling formulations and does not consider the API permeability, and hence, it produces the risk of slow and potentially incomplete oral absorption of an API with poor intestinal permeability. In cases where clinical dose estimations are available early in development, the preclinical bioavailability studies and dose number calculations, used to guide formulation selection, may be performed at more relevant doses instead of the proposed standard human dose. It should be noted, however, that unlike in late development, there is uncertainty on the clinical dose estimated in the early clinical phases because that dose is usually only based on in vitro and/or in vivo animal pharmacology models, or early clinical biomarker information. Therefore, formulation strategies may be adjusted based on emerging data supporting clinical doses. In summary, combined early information on in vitro-assessed API solubility and permeability, preclinical suspension/solution bioavailability data in relation to the intravenous clearance, and metabolic pathways of the API can strengthen formulation decisions. However, these data may not always fully distinguish between conventional (e.g., to be taken with food), enhancing, and enabling formulations. Therefore, to avoid overinvestment in complex and expensive enabling technologies, it is useful to evaluate a conventional and solubility (and/or permeability) enhancing formulation under fasted and fed conditions, as part of a first-in-human study or in a subsequent early human bioavailability study, for compounds with high Do, a low animal F rel,susp/sol , or low F abs,sol caused by precipitation of the solubilized API.

The role (or not) of economic evaluation at the micro level: can Bourdieu's theory provide a way forward for clinical decision-making?

PubMed

Lessard, Chantale; Contandriopoulos, André-Pierre; Beaulieu, Marie-Dominique

2010-06-01

Despite increasing interest in health economic evaluation, investigations have shown limited use by micro (clinical) level decision-makers. A considerable amount of health decisions take place daily at the point of the clinical encounter; especially in primary care. Since every decision has an opportunity cost, ignoring economic information in family physicians' (FPs) decision-making may have a broad impact on health care efficiency. Knowledge translation of economic evaluation is often based on taken-for-granted assumptions about actors' interests and interactions, neglecting much of the complexity of social reality. Health economics literature frequently assumes a rational and linear decision-making process. Clinical decision-making is in fact a complex social, dynamic, multifaceted process, involving relationships and contextual embeddedness. FPs are embedded in complex social networks that have a significant impact on skills, attitudes, knowledge, practices, and on the information being used. Because of their socially constructed nature, understanding preferences, professional culture, practices, and knowledge translation requires serious attention to social reality. There has been little exploration by health economists of whether the problem may be more fundamental and reside in a misunderstanding of the process of decision-making. There is a need to enhance our understanding of the role of economic evaluation in decision-making from a disciplinary perspective different than health economics. This paper argues for a different conceptualization of the role of economic evaluation in FPs' decision-making, and proposes Bourdieu's sociological theory as a research framework. Bourdieu's theory of practice illustrates how the context-sensitive nature of practice must be understood as a socially constituted practical knowledge. The proposed approach could substantially contribute to a more complex understanding of the role of economic evaluation in FPs' decision-making. Copyright 2010 Elsevier Ltd. All rights reserved.

Modular Architecture for Integrated Model-Based Decision Support.

PubMed

Gaebel, Jan; Schreiber, Erik; Oeser, Alexander; Oeltze-Jafra, Steffen

2018-01-01

Model-based decision support systems promise to be a valuable addition to oncological treatments and the implementation of personalized therapies. For the integration and sharing of decision models, the involved systems must be able to communicate with each other. In this paper, we propose a modularized architecture of dedicated systems for the integration of probabilistic decision models into existing hospital environments. These systems interconnect via web services and provide model sharing and processing capabilities for clinical information systems. Along the lines of IHE integration profiles from other disciplines and the meaningful reuse of routinely recorded patient data, our approach aims for the seamless integration of decision models into hospital infrastructure and the physicians' daily work.

Medical and pharmacy coverage decision making at the population level.

PubMed

Mohr, Penny E; Tunis, Sean R

2014-06-01

Medicare is one of the largest health care payers in the United States. As a result, its decisions about coverage have profound implications for patient access to care. In this commentary, the authors describe how Medicare used evidence on heterogeneity of treatment effects to make population-based decisions on health care coverage for implantable cardiac defibrillators. This case is discussed in the context of the rapidly expanding availability of comparative effectiveness research. While there is a potential tension between population-based and patient-centered decision making, the expanded diversity of populations and settings included in comparative effectiveness research can provide useful information for making more discerning and informed policy and clinical decisions.

Surrogate decision making and intellectual virtue.

PubMed

Bock, Gregory L

2014-01-01

Patients can be harmed by a religiously motivated surrogate decision maker whose decisions are contrary to the standard of care; therefore, surrogate decision making should be held to a high standard. Stewart Eskew and Christopher Meyers proposed a two-part rule for deciding which religiously based decisions to honor: (1) a secular reason condition and (2) a rationality condition. The second condition is based on a coherence theory of rationality, which they claim is accessible, generous, and culturally sensitive. In this article, I will propose strengthening the rationality condition by grounding it in a theory of intellectual virtue, which is both rigorous and culturally sensitive. Copyright 2014 The Journal of Clinical Ethics. All rights reserved.

What is a medical decision? A taxonomy based on physician statements in hospital encounters: a qualitative study.

PubMed

Ofstad, Eirik H; Frich, Jan C; Schei, Edvin; Frankel, Richard M; Gulbrandsen, Pål

2016-02-11

The medical literature lacks a comprehensive taxonomy of decisions made by physicians in medical encounters. Such a taxonomy might be useful in understanding the physician-centred, patient-centred and shared decision-making in clinical settings. We aimed to identify and classify all decisions emerging in conversations between patients and physicians. Qualitative study of video recorded patient-physician encounters. 380 patients in consultations with 59 physicians from 17 clinical specialties and three different settings (emergency room, ward round, outpatient clinic) in a Norwegian teaching hospital. A randomised sample of 30 encounters from internal medicine was used to identify and classify decisions, a maximum variation sample of 20 encounters was used for reliability assessments, and the remaining encounters were analysed to test for applicability across specialties. On the basis of physician statements in our material, we developed a taxonomy of clinical decisions--the Decision Identification and Classification Taxonomy for Use in Medicine (DICTUM). We categorised decisions into 10 mutually exclusive categories: gathering additional information, evaluating test results, defining problem, drug-related, therapeutic procedure-related, legal and insurance-related, contact-related, advice and precaution, treatment goal, and deferment. Four-coder inter-rater reliability using Krippendorff's α was 0.79. DICTUM represents a precise, detailed and comprehensive taxonomy of medical decisions communicated within patient-physician encounters. Compared to previous normative frameworks, the taxonomy is descriptive, substantially broader and offers new categories to the variety of clinical decisions. The taxonomy could prove helpful in studies on the quality of medical work, use of time and resources, and understanding of why, when and how patients are or are not involved in decisions. 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/

A decision-support system for the analysis of clinical practice patterns.

PubMed

Balas, E A; Li, Z R; Mitchell, J A; Spencer, D C; Brent, E; Ewigman, B G

1994-01-01

Several studies documented substantial variation in medical practice patterns, but physicians often do not have adequate information on the cumulative clinical and financial effects of their decisions. The purpose of developing an expert system for the analysis of clinical practice patterns was to assist providers in analyzing and improving the process and outcome of patient care. The developed QFES (Quality Feedback Expert System) helps users in the definition and evaluation of measurable quality improvement objectives. Based on objectives and actual clinical data, several measures can be calculated (utilization of procedures, annualized cost effect of using a particular procedure, and expected utilization based on peer-comparison and case-mix adjustment). The quality management rules help to detect important discrepancies among members of the selected provider group and compare performance with objectives. The system incorporates a variety of data and knowledge bases: (i) clinical data on actual practice patterns, (ii) frames of quality parameters derived from clinical practice guidelines, and (iii) rules of quality management for data analysis. An analysis of practice patterns of 12 family physicians in the management of urinary tract infections illustrates the use of the system.

Do online prognostication tools represent a valid alternative to genomic profiling in the context of adjuvant treatment of early breast cancer? A systematic review of the literature.

PubMed

El Hage Chehade, Hiba; Wazir, Umar; Mokbel, Kinan; Kasem, Abdul; Mokbel, Kefah

2018-01-01

Decision-making regarding adjuvant chemotherapy has been based on clinical and pathological features. However, such decisions are seldom consistent. Web-based predictive models have been developed using data from cancer registries to help determine the need for adjuvant therapy. More recently, with the recognition of the heterogenous nature of breast cancer, genomic assays have been developed to aid in the therapeutic decision-making. We have carried out a comprehensive literature review regarding online prognostication tools and genomic assays to assess whether online tools could be used as valid alternatives to genomic profiling in decision-making regarding adjuvant therapy in early breast cancer. Breast cancer has been recently recognized as a heterogenous disease based on variations in molecular characteristics. Online tools are valuable in guiding adjuvant treatment, especially in resource constrained countries. However, in the era of personalized therapy, molecular profiling appears to be superior in predicting clinical outcome and guiding therapy. Copyright © 2017 Elsevier Inc. All rights reserved.

Assessing Clinical Reasoning (ASCLIRE): Instrument Development and Validation

ERIC Educational Resources Information Center

Kunina-Habenicht, Olga; Hautz, Wolf E.; Knigge, Michel; Spies, Claudia; Ahlers, Olaf

2015-01-01

Clinical reasoning is an essential competency in medical education. This study aimed at developing and validating a test to assess diagnostic accuracy, collected information, and diagnostic decision time in clinical reasoning. A norm-referenced computer-based test for the assessment of clinical reasoning (ASCLIRE) was developed, integrating the…

Can Classification Tree Analyses Help Improve Decision Making About Treatments for Depression and Anxiety Disorders? A Preliminary Investigation

PubMed Central

Rhodes, Louisa; Naumann, Ulrike M.

2011-01-01

Objective: To identify how decisions about treatment are being made in secondary services for anxiety disorders and depression and, specifically, whether it was possible to predict the decisions to refer for evidence-based treatments. Method: Post hoc classification tree analysis was performed using a sample from an audit on implementation of the National Institute for Health and Clinical Excellence Guidelines for Depression and Anxiety Disorders. The audit was of 5 teams offering secondary care services; they included psychiatrists, psychologists, community psychiatric nurses, social workers, dual-diagnosis workers, and vocational workers. The patient sample included all of those with a primary problem of depression (n = 56) or an anxiety disorder (n = 16) who were offered treatment from February 16 to April 3, 2009. The outcome variable was whether or not evidence-based treatments were offered, and the predictor variables were presenting problem, risk, comorbid problem, social problems, and previous psychiatric history. Results: Treatment decisions could be more accurately predicted for anxiety disorders (93% correct) than for depression (55%). For anxiety disorders, the presence or absence of social problems was a good predictor for whether evidence-based or non–evidence-based treatments were offered; 44% (4/9) of those with social problems vs 100% (6/6) of those without social problems were offered evidence-based treatments. For depression, patients’ risk rating had the largest impact on treatment decisions, although no one variable could be identified as individually predictive of all treatment decisions. Conclusions: Treatment decisions were generally consistent for anxiety disorders but more idiosyncratic for depression, making the development of a decision-making model very difficult for depression. The lack of clarity of some terms in the clinical guidelines and the more complex nature of depression could be factors contributing to this difficulty. Further research is needed to understand the complex nature of decision making with depressed patients. PMID:22295255

A web-based personalized risk communication and decision-making tool for women with dense breasts: Design and methods of a randomized controlled trial within an integrated health care system.

PubMed

Knerr, Sarah; Wernli, Karen J; Leppig, Kathleen; Ehrlich, Kelly; Graham, Amanda L; Farrell, David; Evans, Chalanda; Luta, George; Schwartz, Marc D; O'Neill, Suzanne C

2017-05-01

Mammographic breast density is one of the strongest risk factors for breast cancer after age and family history. Mandatory breast density disclosure policies are increasing nationally without clear guidance on how to communicate density status to women. Coupling density disclosure with personalized risk counseling and decision support through a web-based tool may be an effective way to allow women to make informed, values-consistent risk management decisions without increasing distress. This paper describes the design and methods of Engaged, a prospective, randomized controlled trial examining the effect of online personalized risk counseling and decision support on risk management decisions in women with dense breasts and increased breast cancer risk. The trial is embedded in a large integrated health care system in the Pacific Northwest. A total of 1250 female health plan members aged 40-69 with a recent negative screening mammogram who are at increased risk for interval cancer based on their 5-year breast cancer risk and BI-RADS® breast density will be randomly assigned to access either a personalized web-based counseling and decision support tool or standard educational content. Primary outcomes will be assessed using electronic health record data (i.e., chemoprevention and breast MRI utilization) and telephone surveys (i.e., distress) at baseline, six weeks, and twelve months. Engaged will provide evidence about whether a web-based personalized risk counseling and decision support tool is an effective method for communicating with women about breast density and risk management. An effective intervention could be disseminated with minimal clinical burden to align with density disclosure mandates. Clinical Trials Registration Number:NCT03029286. Copyright © 2017 Elsevier Inc. All rights reserved.

Racial, gender, and socioeconomic status bias in senior medical student clinical decision-making: a national survey.

PubMed

Williams, Robert L; Romney, Crystal; Kano, Miria; Wright, Randy; Skipper, Betty; Getrich, Christina M; Sussman, Andrew L; Zyzanski, Stephen J

2015-06-01

Research suggests stereotyping by clinicians as one contributor to racial and gender-based health disparities. It is necessary to understand the origins of such biases before interventions can be developed to eliminate them. As a first step toward this understanding, we tested for the presence of bias in senior medical students. The purpose of the study was to determine whether bias based on race, gender, or socioeconomic status influenced clinical decision-making among medical students. We surveyed seniors at 84 medical schools, who were required to choose between two clinically equivalent management options for a set of cardiac patient vignettes. We examined variations in student recommendations based on patient race, gender, and socioeconomic status. The study included senior medical students. We investigated the percentage of students selecting cardiac procedural options for vignette patients, analyzed by patient race, gender, and socioeconomic status. Among 4,603 returned surveys, we found no evidence in the overall sample supporting racial or gender bias in student clinical decision-making. Students were slightly more likely to recommend cardiac procedural options for black (43.9 %) vs. white (42 %, p = .03) patients; there was no difference by patient gender. Patient socioeconomic status was the strongest predictor of student recommendations, with patients described as having the highest socioeconomic status most likely to receive procedural care recommendations (50.3 % vs. 43.2 % for those in the lowest socioeconomic status group, p < .001). Analysis by subgroup, however, showed significant regional geographic variation in the influence of patient race and gender on decision-making. Multilevel analysis showed that white female patients were least likely to receive procedural recommendations. In the sample as a whole, we found no evidence of racial or gender bias in student clinical decision-making. However, we did find evidence of bias with regard to the influence of patient socioeconomic status, geographic variations, and the influence of interactions between patient race and gender on student recommendations.

Expert System Shells for Rapid Clinical Decision Support Module Development: An ESTA Demonstration of a Simple Rule-Based System for the Diagnosis of Vaginal Discharge

PubMed Central

2012-01-01

Objectives This study demonstrates the feasibility of using expert system shells for rapid clinical decision support module development. Methods A readily available expert system shell was used to build a simple rule-based system for the crude diagnosis of vaginal discharge. Pictures and 'canned text explanations' are extensively used throughout the program to enhance its intuitiveness and educational dimension. All the steps involved in developing the system are documented. Results The system runs under Microsoft Windows and is available as a free download at http://healthcybermap.org/vagdisch.zip (the distribution archive includes both the program's executable and the commented knowledge base source as a text document). The limitations of the demonstration system, such as the lack of provisions for assessing uncertainty or various degrees of severity of a sign or symptom, are discussed in detail. Ways of improving the system, such as porting it to the Web and packaging it as an app for smartphones and tablets, are also presented. Conclusions An easy-to-use expert system shell enables clinicians to rapidly become their own 'knowledge engineers' and develop concise evidence-based decision support modules of simple to moderate complexity, targeting clinical practitioners, medical and nursing students, as well as patients, their lay carers and the general public (where appropriate). In the spirit of the social Web, it is hoped that an online repository can be created to peer review, share and re-use knowledge base modules covering various clinical problems and algorithms, as a service to the clinical community. PMID:23346475

Acute care clinical pharmacy practice: unit- versus service-based models.

PubMed

Haas, Curtis E; Eckel, Stephen; Arif, Sally; Beringer, Paul M; Blake, Elizabeth W; Lardieri, Allison B; Lobo, Bob L; Mercer, Jessica M; Moye, Pamela; Orlando, Patricia L; Wargo, Kurt

2012-02-01

This commentary from the 2010 Task Force on Acute Care Practice Model of the American College of Clinical Pharmacy was developed to compare and contrast the "unit-based" and "service-based" orientation of the clinical pharmacist within an acute care pharmacy practice model and to offer an informed opinion concerning which should be preferred. The clinical pharmacy practice model must facilitate patient-centered care and therefore must position the pharmacist to be an active member of the interprofessional team focused on providing high-quality pharmaceutical care to the patient. Although both models may have advantages and disadvantages, the most important distinction pertains to the patient care role of the clinical pharmacist. The unit-based pharmacist is often in a position of reacting to an established order or decision and frequently is focused on task-oriented clinical services. By definition, the service-based clinical pharmacist functions as a member of the interprofessional team. As a team member, the pharmacist proactively contributes to the decision-making process and the development of patient-centered care plans. The service-based orientation of the pharmacist is consistent with both the practice vision embraced by ACCP and its definition of clinical pharmacy. The task force strongly recommends that institutions pursue a service-based pharmacy practice model to optimally deploy their clinical pharmacists. Those who elect to adopt this recommendation will face challenges in overcoming several resource, technologic, regulatory, and accreditation barriers. However, such challenges must be confronted if clinical pharmacists are to contribute fully to achieving optimal patient outcomes. © 2012 Pharmacotherapy Publications, Inc.

Structured assessment of mental capacity to make financial decisions in Chinese older persons with mild cognitive impairment and mild Alzheimer disease.

PubMed

Lui, Victor W C; Lam, Linda C W; Chau, Rachel C M; Fung, Ada W T; Wong, Billy M L; Leung, Grace T Y; Leung, K F; Chiu, Helen F K; Karlawish, Jason H T; Appelbaum, Paul S

2013-06-01

Previous studies suggested that patients with mild cognitive impairment (MCI) or dementia can have impaired and declining financial skills and abilities. The purpose of this study is to test a clinically applicable method, based on the contemporary legal standard, to examine directly the mental capacity to make financial decisions and its component decision-making abilities among patients with MCI and early dementia. A total of 90 patients with mild Alzheimer disease (AD), 92 participants with MCI, and 93 cognitively normal control participants were recruited for this study. Their mental capacity to make everyday financial decisions was assessed by clinician ratings and the Chinese version of the Assessment of Capacity for Everyday Decision-Making (ACED). Based on the clinician ratings, only 53.5% were found to be mentally competent in the AD group, compared with 94.6% in the MCI group. However, participants with MCI had mild but significant impairment in understanding, appreciating, and reasoning abilities as measured by the ACED. The ACED provided a reliable and clinically applicable structured framework for assessment of mental capacity to make financial decisions.

Implementation science: a role for parallel dual processing models of reasoning?

PubMed Central

Sladek, Ruth M; Phillips, Paddy A; Bond, Malcolm J

2006-01-01

Background A better theoretical base for understanding professional behaviour change is needed to support evidence-based changes in medical practice. Traditionally strategies to encourage changes in clinical practices have been guided empirically, without explicit consideration of underlying theoretical rationales for such strategies. This paper considers a theoretical framework for reasoning from within psychology for identifying individual differences in cognitive processing between doctors that could moderate the decision to incorporate new evidence into their clinical decision-making. Discussion Parallel dual processing models of reasoning posit two cognitive modes of information processing that are in constant operation as humans reason. One mode has been described as experiential, fast and heuristic; the other as rational, conscious and rule based. Within such models, the uptake of new research evidence can be represented by the latter mode; it is reflective, explicit and intentional. On the other hand, well practiced clinical judgments can be positioned in the experiential mode, being automatic, reflexive and swift. Research suggests that individual differences between people in both cognitive capacity (e.g., intelligence) and cognitive processing (e.g., thinking styles) influence how both reasoning modes interact. This being so, it is proposed that these same differences between doctors may moderate the uptake of new research evidence. Such dispositional characteristics have largely been ignored in research investigating effective strategies in implementing research evidence. Whilst medical decision-making occurs in a complex social environment with multiple influences and decision makers, it remains true that an individual doctor's judgment still retains a key position in terms of diagnostic and treatment decisions for individual patients. This paper argues therefore, that individual differences between doctors in terms of reasoning are important considerations in any discussion relating to changing clinical practice. Summary It is imperative that change strategies in healthcare consider relevant theoretical frameworks from other disciplines such as psychology. Generic dual processing models of reasoning are proposed as potentially useful in identifying factors within doctors that may moderate their individual uptake of evidence into clinical decision-making. Such factors can then inform strategies to change practice. PMID:16725023

Implementation science: a role for parallel dual processing models of reasoning?

PubMed

Sladek, Ruth M; Phillips, Paddy A; Bond, Malcolm J

2006-05-25

A better theoretical base for understanding professional behaviour change is needed to support evidence-based changes in medical practice. Traditionally strategies to encourage changes in clinical practices have been guided empirically, without explicit consideration of underlying theoretical rationales for such strategies. This paper considers a theoretical framework for reasoning from within psychology for identifying individual differences in cognitive processing between doctors that could moderate the decision to incorporate new evidence into their clinical decision-making. Parallel dual processing models of reasoning posit two cognitive modes of information processing that are in constant operation as humans reason. One mode has been described as experiential, fast and heuristic; the other as rational, conscious and rule based. Within such models, the uptake of new research evidence can be represented by the latter mode; it is reflective, explicit and intentional. On the other hand, well practiced clinical judgments can be positioned in the experiential mode, being automatic, reflexive and swift. Research suggests that individual differences between people in both cognitive capacity (e.g., intelligence) and cognitive processing (e.g., thinking styles) influence how both reasoning modes interact. This being so, it is proposed that these same differences between doctors may moderate the uptake of new research evidence. Such dispositional characteristics have largely been ignored in research investigating effective strategies in implementing research evidence. Whilst medical decision-making occurs in a complex social environment with multiple influences and decision makers, it remains true that an individual doctor's judgment still retains a key position in terms of diagnostic and treatment decisions for individual patients. This paper argues therefore, that individual differences between doctors in terms of reasoning are important considerations in any discussion relating to changing clinical practice. It is imperative that change strategies in healthcare consider relevant theoretical frameworks from other disciplines such as psychology. Generic dual processing models of reasoning are proposed as potentially useful in identifying factors within doctors that may moderate their individual uptake of evidence into clinical decision-making. Such factors can then inform strategies to change practice.

Contemporary evidence-based practice in Canadian emergency medical services: a vision for integrating evidence into clinical and policy decision-making.

PubMed

Jensen, Jan L; Travers, Andrew H

2017-05-01

Nationally, emphasis on the importance of evidence-based practice (EBP) in emergency medicine and emergency medical services (EMS) has continuously increased. However, meaningful incorporation of effective and sustainable EBP into clinical and administrative decision-making remains a challenge. We propose a vision for EBP in EMS: Canadian EMS clinicians and leaders will understand and use the best available evidence for clinical and administrative decision-making, to improve patient health outcomes, the capability and quality of EMS systems of care, and safety of patients and EMS professionals. This vision can be implemented with the use of a structure, process, system, and outcome taxonomy to identify current barriers to true EBP, to recognize the opportunities that exist, and propose corresponding recommended strategies for local EMS agencies and at the national level. Framing local and national discussions with this approach will be useful for developing a cohesive and collaborative Canadian EBP strategy.

Hydra: A web-based system for cardiovascular analysis, diagnosis and treatment.

PubMed

Novo, J; Hermida, A; Ortega, M; Barreira, N; Penedo, M G; López, J E; Calvo, C

2017-02-01

Cardiovascular (CV) risk stratification is a highly complex process involving an extensive set of clinical trials to support the clinical decision-making process. There are many clinical conditions (e.g. diabetes, obesity, stress, etc.) that can lead to the early diagnosis or establishment of cardiovascular disease. In order to determine all these clinical conditions, a complete set of clinical patient analyses is typically performed, including a physical examination, blood analysis, electrocardiogram, blood pressure (BP) analysis, etc. This article presents a web-based system, called Hydra, which integrates a full and detailed set of services and functionalities for clinical decision support in order to help and improve the work of clinicians in cardiovascular patient diagnosis, risk assessment, treatment and monitoring over time. Hydra integrates a number of different services: a service for inputting all the information gathered by specialists (physical examination, habits, BP, blood analysis, electrocardiogram, etc.); a tool to automatically determine the CV risk stratification, including well-known standard risk stratification tables; and, finally, various tools to incorporate, analyze and graphically present the records of the ambulatory BP monitoring that provides BP analysis over a given period of time (24 or 48 hours). In addition, the platform presents a set of reports derived from all the information gathered from the patient in order to support physicians in their clinical decisions. Hydra was tested and validated in a real domain. In particular, internal medicine specialists at the Hypertension Unit of the Santiago de Compostela University Hospital (CHUS) validated the platform and used it in different clinical studies to demonstrate its utility. It was observed that the platform increased productivity and accuracy in the assessment of patient data yielding a cost reduction in clinical practice. This paper proposes a complete platform that includes different services for cardiovascular clinical decision support. It was also run as a web-based application to facilitate its use by clinicians, who can access the platform from any remote computer with Internet access. Hydra also includes different automated methods to facilitate the physicians' work and avoid potential errors in the analysis of patient data. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

The capacity of people with a 'mental disability' to make a health care decision.

PubMed

Wong, J G; Clare, C H; Holland, A J; Watson, P C; Gunn, M

2000-03-01

Based on the developing clinical and legal literature, and using the framework adopted in draft legislation, capacity to make a valid decision about a clinically required blood test was investigated in three groups of people with a 'mental disability' (i.e. mental illness (chronic schizophrenia), 'learning disability' ('mental retardation', or intellectual or developmental disability), or, dementia) and a fourth, comparison group. The three 'mental disability' groups (N = 20 in the 'learning disability' group, N = 21 in each of the other two groups) were recruited through the relevant local clinical services; and through a phlebotomy clinic for the 'general population' comparison group (N = 20). The decision-making task was progressively simplified by presenting the relevant information as separate elements and modifying the assessment of capacity so that responding became gradually less dependent on expressive verbal ability. Compared with the 'general population' group, capacity to make the particular decision was significantly more impaired in the 'learning disability' and 'dementia' groups. Importantly, however, it was not more impaired among the 'mental illness' group. All the groups benefited as the decision-making task was simplified, but at different stages. In each of the 'mental disability' groups, one participant benefited only when responding did not require any expensive verbal ability. Consistent with current views, capacity reflected an interaction between the decision-maker and the demands of the decision-making task. The findings have implications for the way in which decisions about health care interventions are sought from people with a 'mental disability'. The methodology may be extended to assess capacity to make other legally-significant decisions.

Clinical decision making in the recognition of dying: a qualitative interview study.

PubMed

Taylor, Paul; Dowding, Dawn; Johnson, Miriam

2017-01-25

Recognising dying is an essential clinical skill for general and palliative care professionals alike. Despite the high importance, both identification and good clinical care of the dying patient remains extremely difficult and often controversial in clinical practice. This study aimed to answer the question: "What factors influence medical and nursing staff when recognising dying in end-stage cancer and heart failure patients?" This study used a descriptive approach to decision-making theory. Participants were purposively sampled for profession (doctor or nurse), specialty (cardiology or oncology) and grade (senior vs junior). Recruitment continued until data saturation was reached. Semi-structured interviews were conducted with NHS medical and nursing staff in an NHS Trust which contained cancer and cardiology tertiary referral centres. An interview schedule was designed, based on decision-making literature. Interviews were audio-recorded and transcribed and analysed using thematic framework. Data were managed with Atlas.ti. Saturation was achieved with 19 participants (7 seniors; 8 intermediate level staff; 4 juniors). There were 11 oncologists (6 doctors, 5 nurses) and 8 cardiologists (3 doctors, 5 nurses). Six themes were generated: information used; decision processes; modifying factors; implementation; reflecting on decisions and related decisions. The decision process described was time-dependent, ongoing and iterative, and relies heavily on intuition. This study supports the need to recognise the strengths and weaknesses of expertise and intuition as part of the decision process, and of placing the recognition of dying in a time-dependent context. Clinicians should also be prepared to accept and convey the uncertainty surrounding these decisions, both in practice and in communication with patients and carers.

Using computerised decision support to improve compliance of cancer multidisciplinary meetings with evidence-based guidance

PubMed Central

Patkar, Vivek; Acosta, Dionisio; Davidson, Tim; Jones, Alison; Fox, John

2012-01-01

Objectives The cancer multidisciplinary team (MDT) meeting (MDM) is regarded as the best platform to reduce unwarranted variation in cancer care through evidence-compliant management. However, MDMs are often overburdened with many different agendas and hence struggle to achieve their full potential. The authors developed an interactive clinical decision support system called MATE (Multidisciplinary meeting Assistant and Treatment sElector) to facilitate explicit evidence-based decision making in the breast MDMs. Design Audit study and a questionnaire survey. Setting Breast multidisciplinary unit in a large secondary care teaching hospital. Participants All members of the breast MDT at the Royal Free Hospital, London, were consulted during the process of MATE development and implementation. The emphasis was on acknowledging the clinical needs and practical constraints of the MDT and fitting the system around the team's workflow rather than the other way around. Delegates, who attended MATE workshop at the England Cancer Networks' Development Programme conference in March 2010, participated in the questionnaire survey. Outcome measures The measures included evidence-compliant care, measured by adherence to clinical practice guidelines, and promoting research, measured by the patient identification rate for ongoing clinical trials. Results MATE identified 61% more patients who were potentially eligible for recruitment into clinical trials than the MDT, and MATE recommendations demonstrated better concordance with clinical practice guideline than MDT recommendations (97% of MATE vs 93.2% of MDT; N=984). MATE is in routine use in breast MDMs at the Royal Free Hospital, London, and wider evaluations are being considered. Conclusions Sophisticated decision support systems can enhance the conduct of MDMs in a way that is acceptable to and valued by the clinical team. Further rigorous evaluations are required to examine cost-effectiveness and measure the impact on patient outcomes. The decision support technology used in MATE is generic and if found useful can be applied across medicine. PMID:22734113

A computerized handheld decision-support system to improve pulmonary embolism diagnosis: a randomized trial.

PubMed

Roy, Pierre-Marie; Durieux, Pierre; Gillaizeau, Florence; Legall, Catherine; Armand-Perroux, Aurore; Martino, Ludovic; Hachelaf, Mohamed; Dubart, Alain-Eric; Schmidt, Jeannot; Cristiano, Mirko; Chretien, Jean-Marie; Perrier, Arnaud; Meyer, Guy

2009-11-17

Testing for pulmonary embolism often differs from that recommended by evidence-based guidelines. To assess the effectiveness of a handheld clinical decision-support system to improve the diagnostic work-up of suspected pulmonary embolism among patients in the emergency department. Cluster randomized trial. Assignment was by random-number table, providers were not blinded, and outcome assessment was automated. (ClinicalTrials.gov registration number: NCT00188032). 20 emergency departments in France. 1103 and 1768 consecutive outpatients with suspected pulmonary embolism. After a preintervention period involving 20 centers and 1103 patients, in which providers grew accustomed to inputting clinical data into handheld devices and investigators assessed baseline testing, emergency departments were randomly assigned to activation of a decision-support system on the devices (10 centers, 753 patients) or posters and pocket cards that showed validated diagnostic strategies (10 centers, 1015 patients). Appropriateness of diagnostic work-up, defined as any sequence of tests that yielded a posttest probability less than 5% or greater than 85% (primary outcome) or as strict adherence to guideline recommendations (secondary outcome); number of tests per patient (secondary outcome). The proportion of patients who received appropriate diagnostic work-ups was greater during the trial than in the preintervention period in both groups, but the increase was greater in the computer-based guidelines group (adjusted mean difference in increase, 19.3 percentage points favoring computer-based guidelines [95% CI, 2.9 to 35.6 percentage points]; P = 0.023). Among patients with appropriate work-ups, those in the computer-based guidelines group received slightly fewer tests than did patients in the paper guidelines group (mean tests per patient, 1.76 [SD, 0.98] vs. 2.25 [SD, 1.04]; P < 0.001). The study was not designed to show a difference in the clinical outcomes of patients during follow-up. A handheld decision-support system improved diagnostic decision making for patients with suspected pulmonary embolism in the emergency department.

Integration of evidence-based knowledge management in microsystems: a tele-ICU experience.

PubMed

Rincon, Teresa A

2012-01-01

The Institute of Medicine's proposed 6 aims to improve health care are timely, safe, effective, efficient, equitable, and patient-centered care. Unfortunately, it also asserts that improvements in these 6 dimensions cannot be achieved within the existing framework of care systems. These systems are based on unrealistic expectations on human cognition and vigilance, and demonstrate a lack of dependence on computerized systems to support care processes and put information at the point of use. Knowledge-based care and evidence-based clinical decision-making need to replace the unscientific care that is being delivered in health care. Building care practices on evidence within an information technology platform is needed to support sound clinical decision-making and to influence organizational adoption of evidence-based practice in health care. Despite medical advances and evidence-based recommendations for treatment of severe sepsis, it remains a significant cause of mortality and morbidity in the world. It is a complex disease state that has proven difficult to define, diagnose, and treat. Supporting bedside teams with real-time knowledge and expertise to target early identification of severe sepsis and compliance to Surviving Sepsis Campaign, evidence-based practice bundles are important to improving outcomes. Using a centralized, remote team of expert nurses and an open-source software application to advance clinical decision-making and execution of the severe sepsis bundle will be examined.

"In the physio we trust": A qualitative study on patients' preferences for physiotherapy.

PubMed

Bernhardsson, Susanne; Larsson, Maria E H; Johansson, Kajsa; Öberg, Birgitta

2017-07-01

Patients' preferences should be integrated in evidence-based practice. This study aimed to explore patients' preferences for physiotherapy treatment and participation in decision making. A qualitative study set in an urban physiotherapy clinic in Gothenburg, Sweden. Individual, semi-structured interviews were conducted with 20 individuals who sought physiotherapy for musculoskeletal disorders. The interviews were recorded, transcribed, and analyzed with qualitative content analysis. An overarching theme, embracing six categories, was conceptualized: Trust in the physiotherapist fosters active engagement in therapy. The participants preferred active treatment strategies such as exercise and advice for self-management, allowing them to actively engage in their therapy. Some preferred passive treatments. Key influencers on treatment preferences were previous experiences and media. All participants wanted to be involved in the clinical decision making, but to varying extents. Some expressed a preference for an active role and wanting to share decisions while others were content with a passive role. Expectations for a professional management were reflected in trust and confidence in physiotherapists' skills and competence, expectations for good outcomes, and believing that treatment methods should be evidence-based. Trust in the physiotherapist's competence, as well as a desire to participate in clinical decision making, fosters active engagement in physiotherapy.

A Paradigm Shift toward Evidence-Based Clinical Practice: Developing a Performance Assessment

ERIC Educational Resources Information Center

Wentworth, Nancy; Erickson, Lynnette B.; Lawrence, Barbara; Popham, J. Aaron; Korth, Byran

2009-01-01

The Clinical Practice Assessment System (CPAS), developed in response to teacher preparation program accreditation requirements, represents a paradigm shift of one university toward data-based decision-making in teacher education programs. The new assessment system is a scale aligned with INTASC Standards, which allows for observation and…

75 FR 70677 - Agency Information Collection Activities: Proposed Collection; Comment Request

Federal Register 2010, 2011, 2012, 2013, 2014

2010-11-18

... research and through the promotion of improvements in clinical and health system practices, including the... publicly accessible Web-based database of evidence-based clinical practice guidelines meeting explicit... encouraging the use of evidence to make informed health care decisions. The NGC is a vehicle for such...

Value-Based Reimbursement: Impact of Curtailing Physician Autonomy in Medical Decision Making.

PubMed

Gupta, Dipti; Karst, Ingolf; Mendelson, Ellen B

2016-02-01

In this article, we define value in the context of reimbursement and explore the effect of shifting reimbursement paradigms on the decision-making autonomy of a women's imaging radiologist. The current metrics used for value-based reimbursement such as report turnaround time are surrogate measures that do not measure value directly. The true measure of a physician's value in medicine is accomplishment of better health outcomes, which, in breast imaging, are best achieved with a physician-patient relationship. Complying with evidence-based medicine, which includes data-driven best clinical practices, a physician's clinical expertise, and the patient's values, will improve our science and preserve the art of medicine.

Why do we do as we do? Factors influencing clinical reasoning and decision-making among physiotherapists in an acute setting.

PubMed

Holdar, Ulrika; Wallin, Lars; Heiwe, Susanne

2013-12-01

Despite the current movement for health-care to become more informed by evidence, knowledge on effective implementation of evidence-based practice is scarce. To improve research application among physiotherapists, the process of implementation and clinical reasoning needs to be scrutinized. The aim of this study was to identify various experiences of factors that influence the physiotherapist's clinical reasoning in specialist care. A phenomenographic approach was chosen. Eleven physiotherapists at two acute care hospitals in nn. Data was obtained by observations and interviews. Phenomenographic data analysis identified various experiences of clinical decision-making. The Ethical Review Board of the nn approved the study. The observations and the interviews enabled identification of various experiences that influenced clinical decision-making. The physiotherapists' clinical reasoning was perceived to be constrained by contextual factors. The physiotherapists collected current information on the patient by using written and verbal information exchange and used this to generate an inner picture of the patient. By creating hypotheses that were accepted or rejected, they made decisions in advance of their interventions. The decisions were influenced by the individual characteristics of the physiotherapist, his/her knowledge and patient perceptions. Clinical reasoning is a complex and constantly evolving process. Contextual factors such as economy and politics are not easily changed, but factors such as the patient and the physiotherapist as a person are more tangible. Copyright © 2013 John Wiley & Sons, Ltd.

Building the Evidence Base for Decision-making in Cancer Genomic Medicine Using Comparative Effectiveness Research

PubMed Central

Goddard, Katrina A.B.; Knaus, William A.; Whitlock, Evelyn; Lyman, Gary H.; Feigelson, Heather Spencer; Schully, Sheri D.; Ramsey, Scott; Tunis, Sean; Freedman, Andrew N.; Khoury, Muin J.; Veenstra, David L.

2013-01-01

Background The clinical utility is uncertain for many cancer genomic applications. Comparative effectiveness research (CER) can provide evidence to clarify this uncertainty. Objectives To identify approaches to help stakeholders make evidence-based decisions, and to describe potential challenges and opportunities using CER to produce evidence-based guidance. Methods We identified general CER approaches for genomic applications through literature review, the authors’ experiences, and lessons learned from a recent, seven-site CER initiative in cancer genomic medicine. Case studies illustrate the use of CER approaches. Results Evidence generation and synthesis approaches include comparative observational and randomized trials, patient reported outcomes, decision modeling, and economic analysis. We identified significant challenges to conducting CER in cancer genomics: the rapid pace of innovation, the lack of regulation, the limited evidence for clinical utility, and the beliefs that genomic tests could have personal utility without having clinical utility. Opportunities to capitalize on CER methods in cancer genomics include improvements in the conduct of evidence synthesis, stakeholder engagement, increasing the number of comparative studies, and developing approaches to inform clinical guidelines and research prioritization. Conclusions CER offers a variety of methodological approaches to address stakeholders’ needs. Innovative approaches are needed to ensure an effective translation of genomic discoveries. PMID:22516979

Application of best practice approaches for designing decision support tools: The preparatory education about clinical trials (PRE-ACT) study

PubMed Central

Fleisher, Linda; Ruggieri, Dominique G.; Miller, Suzanne M.; Manne, Sharon; Albrecht, Terrance; Buzaglo, Joanne; Collins, Michael A.; Katz, Michael; Kinzy, Tyler G.; Liu, Tasnuva; Manning, Cheri; Charap, Ellen Specker; Millard, Jennifer; Miller, Dawn M.; Poole, David; Raivitch, Stephanie; Roach, Nancy; Ross, Eric A.; Meropol, Neal J.

2014-01-01

Objective This article describes the rigorous development process and initial feedback of the PRE-ACT (Preparatory Education About Clinical Trials) web-based- intervention designed to improve preparation for decision making in cancer clinical trials. Methods The multi-step process included stakeholder input, formative research, user testing and feedback. Diverse teams (researchers, advocates and developers) participated including content refinement, identification of actors, and development of video scripts. Patient feedback was provided in the final production period and through a vanguard group (N = 100) from the randomized trial. Results Patients/advocates confirmed barriers to cancer clinical trial participation, including lack of awareness and knowledge, fear of side effects, logistical concerns, and mistrust. Patients indicated they liked the tool’s user-friendly nature, the organized and comprehensive presentation of the subject matter, and the clarity of the videos. Conclusion The development process serves as an example of operationalizing best practice approaches and highlights the value of a multi-disciplinary team to develop a theory-based, sophisticated tool that patients found useful in their decision making process. Practice implications Best practice approaches can be addressed and are important to ensure evidence-based tools that are of value to patients and supports the usefulness of a process map in the development of e-health tools. PMID:24813474

Analyzing the effectiveness of teaching and factors in clinical decision-making.

PubMed

Hsieh, Ming-Chen; Lee, Ming-Shinn; Chen, Tsung-Ying; Tsai, Tsuen-Chiuan; Pai, Yi-Fong; Sheu, Min-Muh

2017-01-01

The aim of this study is to prepare junior physicians, clinical education should focus on the teaching of clinical decision-making. This research is designed to explore teaching of clinical decision-making and to analyze the benefits of an "Analogy guide clinical decision-making" as a learning intervention for junior doctors. This study had a "quasi-experimental design" and was conducted in a medical center in eastern Taiwan. Participants and Program Description: Thirty junior doctors and three clinical teachers were involved in the study. The experimental group (15) received 1 h of instruction from the "Analogy guide for teaching clinical decision-making" every day for 3 months. Program Evaluation: A "Clinical decision-making self-evaluation form" was used as the assessment tool to evaluate participant learning efficiency before and after the teaching program. Semi-structured qualitative research interviews were also conducted. We found using the analogy guide for teaching clinical decision-making could help enhance junior doctors' self-confidence. Important factors influencing clinical decision-making included workload, decision-making, and past experience. Clinical teaching using the analogy guide for clinical decision-making may be a helpful tool for training and can contribute to a more comprehensive understanding of decision-making.

Lessons from the Johns Hopkins Multi-Disciplinary Venous Thromboembolism (VTE) Prevention Collaborative

PubMed Central

Streiff, Michael B; Carolan, Howard T; Hobson, Deborah B; Kraus, Peggy S; Holzmueller, Christine G; Demski, Renee; Lau, Brandyn D; Biscup-Horn, Paula; Pronovost, Peter J

2012-01-01

Problem Venous thromboembolism (VTE) is a common cause of potentially preventable mortality, morbidity, and increased medical costs. Risk-appropriate prophylaxis can prevent most VTE events, but only a small fraction of patients at risk receive this treatment. Design Prospective quality improvement programme. Setting Johns Hopkins Hospital, Baltimore, Maryland, USA. Strategies for change A multidisciplinary team established a VTE Prevention Collaborative in 2005. The collaborative applied the four step TRIP (translating research into practice) model to develop and implement a mandatory clinical decision support tool for VTE risk stratification and risk-appropriate VTE prophylaxis for all hospitalised adult patients. Initially, paper based VTE order sets were implemented, which were then converted into 16 specialty-specific, mandatory, computerised, clinical decision support modules. Key measures for improvement VTE risk stratification within 24 hours of hospital admission and provision of risk-appropriate, evidence based VTE prophylaxis. Effects of change The VTE team was able to increase VTE risk assessment and ordering of risk-appropriate prophylaxis with paper based order sets to a limited extent, but achieved higher compliance with a computerised clinical decision support tool and the data feedback which it enabled. Risk-appropriate VTE prophylaxis increased from 26% to 80% for surgical patients and from 25% to 92% for medical patients in 2011. Lessons learnt A computerised clinical decision support tool can increase VTE risk stratification and risk-appropriate VTE prophylaxis among hospitalised adult patients admitted to a large urban academic medical centre. It is important to ensure the tool is part of the clinician’s normal workflow, is mandatory (computerised forcing function), and offers the requisite modules needed for every clinical specialty. PMID:22718994

An Assessment of Direct Restorative Material Use in Posterior Teeth by American and Canadian Pediatric Dentists: III. Preferred Level of Participation in Decision-making.

PubMed

Varughese, Rae E; Andrews, Paul; Sigal, Michael J; Azarpazhooh, Amir

2016-11-15

The purpose of this study was to assess Canadian and American pediatric dentists' preferred level of participation in clinical decision-making. A web-based survey was used to collect the opinions of all active Royal College of Dentists of Canada members and American Academy of Pediatric Dentistry members on the use of direct restorative materials in posterior teeth (n equals 4,648; 19.3 percent response rate). The main survey also included a domain to elicit participants' preferred role in clinical decision-making, ranging from an active role (the dentist takes the primary role in decision-making while considering patients/caregivers opinions) to a passive role (the dentist prefers to have the patient guide the decision-making). Bivariate and multivariate analyses for the preferred role and its predictor were performed (two-tailed P<0.05). Fifty-eight percent of participants preferred an active role. The passive role was chosen three times more by those who worked in a hospital-based setting (odds ratio [OR] equals 3.15, 95 percent confidence interval [CI] equals 1.13 to 8.79) or a university-based setting versus a combined setting (OR equals 3.61, 95 percent CI equals 1.11 to 11.77). The majority of participants preferred an active role in decision-making, a role that may not be consistent with a patient-centered practice that emphasizes patient autonomy in decision-making.

Teaching clinical reasoning and decision-making skills to nursing students: Design, development, and usability evaluation of a serious game.

PubMed

Johnsen, Hege Mari; Fossum, Mariann; Vivekananda-Schmidt, Pirashanthie; Fruhling, Ann; Slettebø, Åshild

2016-10-01

Serious games (SGs) are a type of simulation technology that may provide nursing students with the opportunity to practice their clinical reasoning and decision-making skills in a safe and authentic environment. Despite the growing number of SGs developed for healthcare professionals, few SGs are video based or address the domain of home health care. This paper aims to describe the design, development, and usability evaluation of a video based SG for teaching clinical reasoning and decision-making skills to nursing students who care for patients with chronic obstructive pulmonary disease (COPD) in home healthcare settings. A prototype SG was developed. A unified framework of usability called TURF (Task, User, Representation, and Function) and SG theory were employed to ensure a user-centered design. The educational content was based on the clinical decision-making model, Bloom's taxonomy, and a Bachelor of Nursing curriculum. A purposeful sample of six participants evaluated the SG prototype in a usability laboratory. Cognitive walkthrough evaluations, a questionnaire, and individual interviews were used for the usability evaluation. The data were analyzed using qualitative deductive content analysis based on the TURF framework elements and related usability heuristics. The SG was perceived as being realistic, clinically relevant, and at an adequate level of complexity for the intended users. Usability issues regarding functionality and the user-computer interface design were identified. However, the SG was perceived as being easy to learn, and participants suggested that the SG could serve as a supplement to traditional training in laboratory and clinical settings. Using video based scenarios with an authentic COPD patient and a home healthcare registered nurse as actors contributed to increased realism. Using different theoretical approaches in the SG design was considered an advantage of the design process. The SG was perceived as being useful, usable, and satisfying. The achievement of the desired functionality and the minimization of user-computer interface issues emphasize the importance of conducting a usability evaluation during the SG development process. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

[Evidence-based medicine - the current self-reflection of an individualised approach to medicine as an action science].

PubMed

Behrens, Johann

2010-01-01

Evidence-based Medicine (EbM) is the ongoing self-reflection of an individualised approach to medicine in terms of a science that originates from and focuses on clinical decision-making (pragmatic science="Handlungswissenschaft"). EbM is particularly suitable for self-reflecting individualised medicine on the basis of decision-oriented pragmatic science because it consistently distinguishes between external evidence (i.e., other subjects' experience gained through "qualitative" and "quantitative" scientific methods) and internal evidence, i.e., the individual user's, or patient's, own experience manifesting and developing in the individual contact between therapist and patient. Therefore, internal evidence is completely different from the individual clinical experience, expertise, and conviction which therapists contribute to the encounter with clients. A deeper understanding of internal evidence as a result of this encounter has emerged only in the past 15 years. However, it is an integral part of the logic of evidence-based professional decision-making. Scientifically justified beneficial and effective treatment in the individual case cannot be deduced from external evidence but can only be gathered from internal evidence for which the best external evidence available has been utilised. In the past 15 years nursing science has not only carved out the decision-oriented scientific core of evidence-based practice but has also tried to increase the validity of studies on external evidence by employing a combination of 'qualitative' social science studies and clinical epidemiological methods. Copyright © 2010. Published by Elsevier GmbH.

A dashboard-based system for supporting diabetes care.

PubMed

Dagliati, Arianna; Sacchi, Lucia; Tibollo, Valentina; Cogni, Giulia; Teliti, Marsida; Martinez-Millana, Antonio; Traver, Vicente; Segagni, Daniele; Posada, Jorge; Ottaviano, Manuel; Fico, Giuseppe; Arredondo, Maria Teresa; De Cata, Pasquale; Chiovato, Luca; Bellazzi, Riccardo

2018-05-01

To describe the development, as part of the European Union MOSAIC (Models and Simulation Techniques for Discovering Diabetes Influence Factors) project, of a dashboard-based system for the management of type 2 diabetes and assess its impact on clinical practice. The MOSAIC dashboard system is based on predictive modeling, longitudinal data analytics, and the reuse and integration of data from hospitals and public health repositories. Data are merged into an i2b2 data warehouse, which feeds a set of advanced temporal analytic models, including temporal abstractions, care-flow mining, drug exposure pattern detection, and risk-prediction models for type 2 diabetes complications. The dashboard has 2 components, designed for (1) clinical decision support during follow-up consultations and (2) outcome assessment on populations of interest. To assess the impact of the clinical decision support component, a pre-post study was conducted considering visit duration, number of screening examinations, and lifestyle interventions. A pilot sample of 700 Italian patients was investigated. Judgments on the outcome assessment component were obtained via focus groups with clinicians and health care managers. The use of the decision support component in clinical activities produced a reduction in visit duration (P ≪ .01) and an increase in the number of screening exams for complications (P < .01). We also observed a relevant, although nonstatistically significant, increase in the proportion of patients receiving lifestyle interventions (from 69% to 77%). Regarding the outcome assessment component, focus groups highlighted the system's capability of identifying and understanding the characteristics of patient subgroups treated at the center. Our study demonstrates that decision support tools based on the integration of multiple-source data and visual and predictive analytics do improve the management of a chronic disease such as type 2 diabetes by enacting a successful implementation of the learning health care system cycle.

Assessing decision quality in patient-centred care requires a preference-sensitive measure

PubMed Central

Kaltoft, Mette; Cunich, Michelle; Salkeld, Glenn; Dowie, Jack

2014-01-01

A theory-based instrument for measuring the quality of decisions made using any form of decision technology, including both decision-aided and unaided clinical consultations is required to enable person- and patient-centred care and to respond positively to individual heterogeneity in the value aspects of decision making. Current instruments using the term ‘decision quality’ have adopted a decision- and thus condition-specific approach. We argue that patient-centred care requires decision quality to be regarded as both preference-sensitive across multiple relevant criteria and generic across all conditions and decisions. MyDecisionQuality is grounded in prescriptive multi criteria decision analysis and employs a simple expected value algorithm to calculate a score for the quality of a decision that combines, in the clinical case, the patient’s individual preferences for eight quality criteria (expressed as importance weights) and their ratings of the decision just taken on each of these criteria (expressed as performance rates). It thus provides an index of decision quality that encompasses both these aspects. It also provides patients with help in prioritizing quality criteria for future decision making by calculating, for each criterion, the Incremental Value of Perfect Rating, that is, the increase in their decision quality score that would result if their performance rating on the criterion had been 100%, weightings unchanged. MyDecisionQuality, which is a web-based generic and preference-sensitive instrument, can constitute a key patient-reported measure of the quality of the decision-making process. It can provide the basis for future decision improvement, especially when the clinician (or other stakeholders) completes the equivalent instrument and the extent and nature of concordance and discordance can be established. Apart from its role in decision preparation and evaluation, it can also provide real time and relevant documentation for the patient’s record. PMID:24335587

A computerized clinical decision support system as a means of implementing depression guidelines.

PubMed

Trivedi, Madhukar H; Kern, Janet K; Grannemann, Bruce D; Altshuler, Kenneth Z; Sunderajan, Prabha

2004-08-01

The authors describe the history and current use of computerized systems for implementing treatment guidelines in general medicine as well as the development, testing, and early use of a computerized decision support system for depression treatment among "real-world" clinical settings in Texas. In 1999 health care experts from Europe and the United States met to confront the well-documented challenges of implementing treatment guidelines and to identify strategies for improvement. They suggested the integration of guidelines into computer systems that is incorporated into clinical workflow. Several studies have demonstrated improvements in physicians' adherence to guidelines when such guidelines are provided in a computerized format. Although computerized decision support systems are being used in many areas of medicine and have demonstrated improved patient outcomes, their use in psychiatric illness is limited. The authors designed and developed a computerized decision support system for the treatment of major depressive disorder by using evidence-based guidelines, transferring the knowledge gained from the Texas Medication Algorithm Project (TMAP). This computerized decision support system (CompTMAP) provides support in diagnosis, treatment, follow-up, and preventive care and can be incorporated into the clinical setting. CompTMAP has gone through extensive testing to ensure accuracy and reliability. Physician surveys have indicated a positive response to CompTMAP, although the sample was insufficient for statistical testing. CompTMAP is part of a new era of comprehensive computerized decision support systems that take advantage of advances in automation and provide more complete clinical support to physicians in clinical practice.

Impact of electronic clinical decision support on adherence to guideline-recommended treatment for hyperlipidaemia, atrial fibrillation and heart failure: protocol for a cluster randomised trial

PubMed Central

Kessler, Maya Elizabeth; Cook, David A; Kor, Daryl Jon; McKie, Paul M; Pencille, Laurie J; Scheitel, Marianne R; Chaudhry, Rajeev

2017-01-01

Introduction Clinical practice guidelines facilitate optimal clinical practice. Point of care access, interpretation and application of such guidelines, however, is inconsistent. Informatics-based tools may help clinicians apply guidelines more consistently. We have developed a novel clinical decision support tool that presents guideline-relevant information and actionable items to clinicians at the point of care. We aim to test whether this tool improves the management of hyperlipidaemia, atrial fibrillation and heart failure by primary care clinicians. Methods/analysis Clinician care teams were cluster randomised to receive access to the clinical decision support tool or passive access to institutional guidelines on 16 May 2016. The trial began on 1 June 2016 when access to the tool was granted to the intervention clinicians. The trial will be run for 6 months to ensure a sufficient number of patient encounters to achieve 80% power to detect a twofold increase in the primary outcome at the 0.05 level of significance. The primary outcome measure will be the percentage of guideline-based recommendations acted on by clinicians for hyperlipidaemia, atrial fibrillation and heart failure. We hypothesise care teams with access to the clinical decision support tool will act on recommendations at a higher rate than care teams in the standard of care arm. Ethics and dissemination The Mayo Clinic Institutional Review Board approved all study procedures. Informed consent was obtained from clinicians. A waiver of informed consent and of Health Insurance Portability and Accountability Act (HIPAA) authorisation for patients managed by clinicians in the study was granted. In addition to publication, results will be disseminated via meetings and newsletters. Trial registration number NCT02742545. PMID:29208620

Workshop on using natural language processing applications for enhancing clinical decision making: an executive summary

PubMed Central

Pai, Vinay M; Rodgers, Mary; Conroy, Richard; Luo, James; Zhou, Ruixia; Seto, Belinda

2014-01-01

In April 2012, the National Institutes of Health organized a two-day workshop entitled ‘Natural Language Processing: State of the Art, Future Directions and Applications for Enhancing Clinical Decision-Making’ (NLP-CDS). This report is a summary of the discussions during the second day of the workshop. Collectively, the workshop presenters and participants emphasized the need for unstructured clinical notes to be included in the decision making workflow and the need for individualized longitudinal data tracking. The workshop also discussed the need to: (1) combine evidence-based literature and patient records with machine-learning and prediction models; (2) provide trusted and reproducible clinical advice; (3) prioritize evidence and test results; and (4) engage healthcare professionals, caregivers, and patients. The overall consensus of the NLP-CDS workshop was that there are promising opportunities for NLP and CDS to deliver cognitive support for healthcare professionals, caregivers, and patients. PMID:23921193

Gatekeepers for Pragmatic Clinical Trials

PubMed Central

Whicher, Danielle M.; Miller, Jennifer E.; Dunham, Kelly M.; Joffe, Steven

2015-01-01

To successfully implement a pragmatic clinical trial, investigators need access to numerous resources, including financial support, institutional infrastructure (e.g., clinics, facilities, staff), eligible patients, and patient data. Gatekeepers are people or entities who have the ability to allow or deny access to the resources required to support the conduct of clinical research. Based on this definition, gatekeepers relevant to the United States clinical research enterprise include research sponsors, regulatory agencies, payers, health system and other organizational leadership, research team leadership, human research protections programs, advocacy and community groups, and clinicians. This manuscript provides a framework to help guide gatekeepers’ decision-making related to the use of resources for pragmatic clinical trials. These include (1) concern for the interests of individuals, groups, and communities affected by the gatekeepers’ decisions, including protection from harm and maximization of benefits, (2) advancement of organizational mission and values, and (3) stewardship of financial, human, and other organizational resources. Separate from these ethical considerations, gatekeepers’ actions will be guided by relevant federal, state, and local regulations. This framework also suggests that to further enhance the legitimacy of their decision-making, gatekeepers should adopt transparent processes that engage relevant stakeholders when feasible and appropriate. We apply this framework to the set of gatekeepers responsible for making decisions about resources necessary for pragmatic clinical trials in the United States, describing the relevance of the criteria in different situations and pointing out where conflicts among the criteria and relevant regulations may affect decision-making. Recognition of the complex set of considerations that should inform decision-making will guide gatekeepers in making justifiable choices regarding the use of limited and valuable resources. PMID:26374683

Clinical reasoning in nursing, a think-aloud study using virtual patients - a base for an innovative assessment.

PubMed

Forsberg, Elenita; Ziegert, Kristina; Hult, Håkan; Fors, Uno

2014-04-01

In health-care education, it is important to assess the competencies that are essential for the professional role. To develop clinical reasoning skills is crucial for nursing practice and therefore an important learning outcome in nursing education programmes. Virtual patients (VPs) are interactive computer simulations of real-life clinical scenarios and have been suggested for use not only for learning, but also for assessment of clinical reasoning. The aim of this study was to investigate how experienced paediatric nurses reason regarding complex VP cases and how they make clinical decisions. The study was also aimed to give information about possible issues that should be assessed in clinical reasoning exams for post-graduate students in diploma specialist paediatric nursing education. The information from this study is believed to be of high value when developing scoring and grading models for a VP-based examination for the specialist diploma in paediatric nursing education. Using the think-aloud method, data were collected from 30 RNs working in Swedish paediatric departments, and child or school health-care centres. Content analysis was used to analyse the data. The results indicate that experienced nurses try to consolidate their hypotheses by seeing a pattern and judging the value of signs, symptoms, physical examinations, laboratory tests and radiology. They show high specific competence but earlier experience of similar cases was also of importance for the decision making. The nurses thought it was an innovative assessment focusing on clinical reasoning and clinical decision making. They thought it was an enjoyable way to be assessed and that all three main issues could be assessed using VPs. In conclusion, VPs seem to be a possible model for assessing the clinical reasoning process and clinical decision making, but how to score and grade such exams needs further research. © 2013.

Logic Learning Machine and standard supervised methods for Hodgkin's lymphoma prognosis using gene expression data and clinical variables.

PubMed

Parodi, Stefano; Manneschi, Chiara; Verda, Damiano; Ferrari, Enrico; Muselli, Marco

2018-03-01

This study evaluates the performance of a set of machine learning techniques in predicting the prognosis of Hodgkin's lymphoma using clinical factors and gene expression data. Analysed samples from 130 Hodgkin's lymphoma patients included a small set of clinical variables and more than 54,000 gene features. Machine learning classifiers included three black-box algorithms ( k-nearest neighbour, Artificial Neural Network, and Support Vector Machine) and two methods based on intelligible rules (Decision Tree and the innovative Logic Learning Machine method). Support Vector Machine clearly outperformed any of the other methods. Among the two rule-based algorithms, Logic Learning Machine performed better and identified a set of simple intelligible rules based on a combination of clinical variables and gene expressions. Decision Tree identified a non-coding gene ( XIST) involved in the early phases of X chromosome inactivation that was overexpressed in females and in non-relapsed patients. XIST expression might be responsible for the better prognosis of female Hodgkin's lymphoma patients.

Clinical utility of gene expression profiling data for clinical decision-making regarding adjuvant therapy in early stage, node-negative breast cancer: a case report.

PubMed

Schuster, Steven R; Pockaj, Barbara A; Bothe, Mary R; David, Paru S; Northfelt, Donald W

2012-09-10

Breast cancer is the most common malignancy among women in the United States with the second highest incidence of cancer-related death following lung cancer. The decision-making process regarding adjuvant therapy is a time intensive dialogue between the patient and her oncologist. There are multiple tools that help individualize the treatment options for a patient. Population-based analysis with Adjuvant! Online and genomic profiling with Oncotype DX are two commonly used tools in patients with early stage, node-negative breast cancer. This case report illustrates a situation in which the population-based prognostic and predictive information differed dramatically from that obtained from genomic profiling and affected the patient's decision. In light of this case, we discuss the benefits and limitations of these tools.

Family physicians' beliefs about genetic contributions to racial/ethnic and gender differences in health and clinical decision-making.

PubMed

Warshauer-Baker, Esther; Bonham, Vence L; Jenkins, Jean; Stevens, Nancy; Page, Zintesia; Odunlami, Adebola; McBride, Colleen M

2008-01-01

Greater attention towards genetics as a contributor to group health differences may lead to inappropriate use of race/ethnicity and gender as genetic heuristics and exacerbate health disparities. As part of a web-based survey, 1,035 family physicians (FPs) rated the contribution of genetics and environment to racial/ethnic and gender differences in health outcomes, and the importance of race/ethnicity and gender in their clinical decision-making. FPs attributed racial/ethnic and gender differences in health outcomes equally to environment and genetics. These beliefs were not associated with rated importance of race/ethnicity or gender in clinical decision-making. FPs appreciate the complexity of genetic and environmental influences on health differences by race/ethnicity and gender. Copyright 2008 S. Karger AG, Basel.

Method Development for Clinical Comprehensive Evaluation of Pediatric Drugs Based on Multi-Criteria Decision Analysis: Application to Inhaled Corticosteroids for Children with Asthma.

PubMed

Yu, Yuncui; Jia, Lulu; Meng, Yao; Hu, Lihua; Liu, Yiwei; Nie, Xiaolu; Zhang, Meng; Zhang, Xuan; Han, Sheng; Peng, Xiaoxia; Wang, Xiaoling

2018-04-01

Establishing a comprehensive clinical evaluation system is critical in enacting national drug policy and promoting rational drug use. In China, the 'Clinical Comprehensive Evaluation System for Pediatric Drugs' (CCES-P) project, which aims to compare drugs based on clinical efficacy and cost effectiveness to help decision makers, was recently proposed; therefore, a systematic and objective method is required to guide the process. An evidence-based multi-criteria decision analysis model that involved an analytic hierarchy process (AHP) was developed, consisting of nine steps: (1) select the drugs to be reviewed; (2) establish the evaluation criterion system; (3) determine the criterion weight based on the AHP; (4) construct the evidence body for each drug under evaluation; (5) select comparative measures and calculate the original utility score; (6) place a common utility scale and calculate the standardized utility score; (7) calculate the comprehensive utility score; (8) rank the drugs; and (9) perform a sensitivity analysis. The model was applied to the evaluation of three different inhaled corticosteroids (ICSs) used for asthma management in children (a total of 16 drugs with different dosage forms and strengths or different manufacturers). By applying the drug analysis model, the 16 ICSs under review were successfully scored and evaluated. Budesonide suspension for inhalation (drug ID number: 7) ranked the highest, with comprehensive utility score of 80.23, followed by fluticasone propionate inhaled aerosol (drug ID number: 16), with a score of 79.59, and budesonide inhalation powder (drug ID number: 6), with a score of 78.98. In the sensitivity analysis, the ranking of the top five and lowest five drugs remains unchanged, suggesting this model is generally robust. An evidence-based drug evaluation model based on AHP was successfully developed. The model incorporates sufficient utility and flexibility for aiding the decision-making process, and can be a useful tool for the CCES-P.

Watson will see you now: a supercomputer to help clinicians make informed treatment decisions.

PubMed

Doyle-Lindrud, Susan

2015-02-01

IBM has collaborated with several cancer care providers to develop and train the IBM supercomputer Watson to help clinicians make informed treatment decisions. When a patient is seen in clinic, the oncologist can input all of the clinical information into the computer system. Watson will then review all of the data and recommend treatment options based on the latest evidence and guidelines. Once the oncologist makes the treatment decision, this information can be sent directly to the insurance company for approval. Watson has the ability to standardize care and accelerate the approval process, a benefit to the healthcare provider and the patient.

[Decisions in case of "problematic" cost-effectiveness ratios based on the example of a clinical trial in rehabilitation care].

PubMed

Leidl, R; Jacobi, E; Knab, J; Schweikert, B

2006-04-01

Economic assessment of an additional psychological intervention in the rehabilitation of patients with chronic low-back pain and evaluation of results by decision makers. Piggy-back cost-utility analysis of a randomised clinical trial, including a bootstrap analysis. Costs were measured by using the cost accounting systems of the rehabilitation clinics and by surveying patients. Health-related quality of life was measured using the EQ-5D. Implications of different representations of the decision problem and corresponding decision rules concerning the cost-effectiveness plane are discussed. As compared with the 126 patients of the control arm, the 98 patients in the intervention arm gained 3.5 days in perfect health on average as well as 1219 euro cost saving. However, because of the uncertainty involved, the results of a bootstrap analysis cover all quadrants of the cost-effectiveness plane. Using maximum willingness-to-pay per effect unit gained, decision rules can be defined for parts of the cost-effectiveness plane. These have to be aggregated in a further valuation step. Study results show that decisions on stochastic economic evaluation results may require an additional valuation step aggregating the various parts of the cost-effectiveness plane.

Making cognitive decision support work: Facilitating adoption, knowledge and behavior change through QI.

PubMed

Weir, Charlene; Brunker, Cherie; Butler, Jorie; Supiano, Mark A

2017-07-01

This paper evaluates the role of facilitation in the successful implementation of Computerized Decision Support (CDS). Facilitation processes include education, specialized computerized decision support, and work process reengineering. These techniques, as well as modeling and feedback enhance self-efficacy, which we propose is one of the factors that mediate the effectiveness of any CDS. In this study, outpatient clinics implemented quality improvement (QI) projects focused on improving geriatric care. Quality Improvement is the systematic process of improving quality through continuous measurement and targeted actions. The program, entitled "Advancing Geriatric Education through Quality Improvement" (AGE QI), consisted of a 6-month, QI based, intervention: (1) 2h didactic session, (2) 1h QI planning session, (3) computerized decision support design and implementation, (4) QI facilitation activities, (5) outcome feedback, and (6) 20h of CME. Specifically, we examined the impact of the QI based program on clinician's perceived self-efficacy in caring for older adults and the relationship of implementation support and facilitation on perceived success. The intervention was implemented at 3 institutions, 27 community healthcare system clinics, and 134 providers. This study reports the results of pre/post surveys for the forty-nine clinicians who completed the full CME program. Self-efficacy ratings for specific clinical behaviors related to care of older adults were assessed using a Likert based instrument. Self-ratings of efficacy improved across the following domains (depression, falls, end-of-life, functional status and medication management) and specifically in QI targeted domains and were associated with overall clinic improvements. Published by Elsevier Inc.

Evaluation of a Shared Decision-Making Intervention on the Utilization of Evidence-Based Psychotherapy in a VA Outpatient PTSD Clinic.

PubMed

Hessinger, Jonathan D; London, Melissa J; Baer, Sheila M

2017-03-13

The Veterans Health Administration (VHA) has continued to emphasize the availability, access, and utilization of high quality mental health care particularly in the treatment of posttraumatic stress disorder (PTSD). While dissemination and availability of evidence-based psychotherapies (EBPs) have only increased, treatment engagement and utilization have continued to be oft-noted challenges. Administrators, researchers, and individual clinicians have continued to develop and explore novel systemic and individualized interventions to address these issues. Pilot studies utilizing shared decision-making models to aid in veteran treatment selection have demonstrated the impact this approach may have on selection of and engagement in EBPs for PTSD. Based on these promising studies, a Department of Veterans Affairs (VA) outpatient PTSD clinic began to implement a shared-decision making intervention as part of a clinic redesign. In seeking to evaluate the impact of this intervention, archival clinical data from 1,056 veterans were reviewed by the authors for rates of treatment selection, EBP initiation, session attendance, and EBP completion. Time elapsed from consult until EBP initiation was also computed by the authors. These variables were then compared on the basis of whether the veteran received the shared-decision making intervention. Veterans who received the intervention were more likely to select and thus initiate an EBP for PTSD sooner than veterans who did not receive this intervention. Veterans, whether receiving the intervention or not, did not differ in therapy session attendance and completion. Implications of these findings and directions for future study are further discussed. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

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.

Evolutionary and Neural Computing Based Decision Support System for Disease Diagnosis from Clinical Data Sets in Medical Practice.

PubMed

Sudha, M

2017-09-27

As a recent trend, various computational intelligence and machine learning approaches have been used for mining inferences hidden in the large clinical databases to assist the clinician in strategic decision making. In any target data the irrelevant information may be detrimental, causing confusion for the mining algorithm and degrades the prediction outcome. To address this issue, this study attempts to identify an intelligent approach to assist disease diagnostic procedure using an optimal set of attributes instead of all attributes present in the clinical data set. In this proposed Application Specific Intelligent Computing (ASIC) decision support system, a rough set based genetic algorithm is employed in pre-processing phase and a back propagation neural network is applied in training and testing phase. ASIC has two phases, the first phase handles outliers, noisy data, and missing values to obtain a qualitative target data to generate appropriate attribute reduct sets from the input data using rough computing based genetic algorithm centred on a relative fitness function measure. The succeeding phase of this system involves both training and testing of back propagation neural network classifier on the selected reducts. The model performance is evaluated with widely adopted existing classifiers. The proposed ASIC system for clinical decision support has been tested with breast cancer, fertility diagnosis and heart disease data set from the University of California at Irvine (UCI) machine learning repository. The proposed system outperformed the existing approaches attaining the accuracy rate of 95.33%, 97.61%, and 93.04% for breast cancer, fertility issue and heart disease diagnosis.

A novel computer based expert decision making model for prostate cancer disease management.

PubMed

Richman, Martin B; Forman, Ernest H; Bayazit, Yildirim; Einstein, Douglas B; Resnick, Martin I; Stovsky, Mark D

2005-12-01

We propose a strategic, computer based, prostate cancer decision making model based on the analytic hierarchy process. We developed a model that improves physician-patient joint decision making and enhances the treatment selection process by making this critical decision rational and evidence based. Two groups (patient and physician-expert) completed a clinical study comparing an initial disease management choice with the highest ranked option generated by the computer model. Participants made pairwise comparisons to derive priorities for the objectives and subobjectives related to the disease management decision. The weighted comparisons were then applied to treatment options to yield prioritized rank lists that reflect the likelihood that a given alternative will achieve the participant treatment goal. Aggregate data were evaluated by inconsistency ratio analysis and sensitivity analysis, which assessed the influence of individual objectives and subobjectives on the final rank list of treatment options. Inconsistency ratios less than 0.05 were reliably generated, indicating that judgments made within the model were mathematically rational. The aggregate prioritized list of treatment options was tabulated for the patient and physician groups with similar outcomes for the 2 groups. Analysis of the major defining objectives in the treatment selection decision demonstrated the same rank order for the patient and physician groups with cure, survival and quality of life being more important than controlling cancer, preventing major complications of treatment, preventing blood transfusion complications and limiting treatment cost. Analysis of subobjectives, including quality of life and sexual dysfunction, produced similar priority rankings for the patient and physician groups. Concordance between initial treatment choice and the highest weighted model option differed between the groups with the patient group having 59% concordance and the physician group having only 42% concordance. This study successfully validated the usefulness of a computer based prostate cancer management decision making model to produce individualized, rational, clinically appropriate disease management decisions without physician bias.

Analyzing the "CareGap": assessing gaps in adherence to clinical guidelines in adult soft tissue sarcoma.

PubMed

Waks, Zeev; Goldbraich, Esther; Farkash, Ariel; Torresani, Michele; Bertulli, Rossella; Restifo, Nicola; Locatelli, Paolo; Casali, Paolo; Carmeli, Boaz

2013-01-01

Clinical decision support systems (CDSSs) are gaining popularity as tools that assist physicians in optimizing medical care. These systems typically comply with evidence-based medicine and are designed with input from domain experts. Nonetheless, deviations from CDSS recommendations are abundant across a broad spectrum of disorders, raising the question as to why this phenomenon exists. Here, we analyze this gap in adherence to a clinical guidelines-based CDSS by examining the physician treatment decisions for 1329 adult soft tissue sarcoma patients in northern Italy using patient-specific parameters. Dubbing this analysis "CareGap", we find that deviations correlate strongly with certain disease features such as local versus metastatic clinical presentation. We also notice that deviations from the guideline-based CDSS suggestions occur more frequently for patients with shorter survival time. Such observations can direct physicians' attention to distinct patient cohorts that are prone to higher deviation levels from clinical practice guidelines. This illustrates the value of CareGap analysis in assessing quality of care for subsets of patients within a larger pathology.

A programmable rules engine to provide clinical decision support using HTML forms.

PubMed

Heusinkveld, J; Geissbuhler, A; Sheshelidze, D; Miller, R

1999-01-01

The authors have developed a simple method for specifying rules to be applied to information on HTML forms. This approach allows clinical experts, who lack the programming expertise needed to write CGI scripts, to construct and maintain domain-specific knowledge and ordering capabilities within WizOrder, the order-entry and decision support system used at Vanderbilt Hospital. The clinical knowledge base maintainers use HTML editors to create forms and spreadsheet programs for rule entry. A test environment has been developed which uses Netscape to display forms; the production environment displays forms using an embedded browser.

An Evidence-Based Practice Model across the Academic and Clinical Settings

ERIC Educational Resources Information Center

Wolter, Julie A.; Corbin-Lewis, Kim; Self, Trisha; Elsweiler, Anne

2011-01-01

This tutorial is designed to provide academic communication sciences and disorders (CSD) programs, at both the undergraduate and graduate levels, with a comprehensive instructional model on evidence-based practice (EBP). The model was designed to help students view EBP as an ongoing process needed in all clinical decision making. The three facets…

Treating childhood pneumonia in hard-to-reach areas: a model-based comparison of mobile clinics and community-based care.

PubMed

Pitt, Catherine; Roberts, Bayard; Checchi, Francesco

2012-01-10

Where hard-to-access populations (such as those living in insecure areas) lack access to basic health services, relief agencies, donors, and ministries of health face a dilemma in selecting the most effective intervention strategy. This paper uses a decision mathematical model to estimate the relative effectiveness of two alternative strategies, mobile clinics and fixed community-based health services, for antibiotic treatment of childhood pneumonia, the world's leading cause of child mortality. A "Markov cycle tree" cohort model was developed in Excel with Visual Basic to compare the number of deaths from pneumonia in children aged 1 to 59 months expected under three scenarios: 1) No curative services available, 2) Curative services provided by a highly-skilled but intermittent mobile clinic, and 3) Curative services provided by a low-skilled community health post. Parameter values were informed by literature and expert interviews. Probabilistic sensitivity analyses were conducted for several plausible scenarios. We estimated median pneumonia-specific under-5 mortality rates of 0.51 (95% credible interval: 0.49 to 0.541) deaths per 10,000 child-days without treatment, 0.45 (95% CI: 0.43 to 0.48) with weekly mobile clinics, and 0.31 (95% CI: 0.29 to 0.32) with CHWs in fixed health posts. Sensitivity analyses found the fixed strategy superior, except when mobile clinics visited communities daily, where rates of care-seeking were substantially higher at mobile clinics than fixed posts, or where several variables simultaneously differed substantially from our baseline assumptions. Current evidence does not support the hypothesis that mobile clinics are more effective than CHWs. A CHW strategy therefore warrants consideration in high-mortality, hard-to-access areas. Uncertainty remains, and parameter values may vary across contexts, but the model allows preliminary findings to be updated as new or context-specific evidence becomes available. Decision analytic modelling can guide needed field-based research efforts in hard-to-access areas and offer evidence-based insights for decision-makers.

Use of case-based reasoning to enhance intensive management of patients on insulin pump therapy.

PubMed

Schwartz, Frank L; Shubrook, Jay H; Marling, Cynthia R

2008-07-01

This study was conducted to develop case-based decision support software to improve glucose control in patients with type 1 diabetes mellitus (T1DM) on insulin pump therapy. While the benefits of good glucose control are well known, achieving and maintaining good glucose control remains a difficult task. Case-based decision support software may assist by recalling past problems in glucose control and their associated therapeutic adjustments. Twenty patients with T1DM on insulin pumps were enrolled in a 6-week study. Subjects performed self-glucose monitoring and provided daily logs via the Internet, tracking insulin dosages, work, sleep, exercise, meals, stress, illness, menstrual cycles, infusion set changes, pump problems, hypoglycemic episodes, and other events. Subjects wore a continuous glucose monitoring system at weeks 1, 3, and 6. Clinical data were interpreted by physicians, who explained the relationship between life events and observed glucose patterns as well as treatment rationales to knowledge engineers. Knowledge engineers built a prototypical system that contained cases of problems in glucose control together with their associated solutions. Twelve patients completed the study. Fifty cases of clinical problems and solutions were developed and stored in a case base. The prototypical system detected 12 distinct types of clinical problems. It displayed the stored problems that are most similar to the problems detected, and offered learned solutions as decision support to the physician. This software can screen large volumes of clinical data and glucose levels from patients with T1DM, identify clinical problems, and offer solutions. It has potential application in managing all forms of diabetes.

The management of patients with early Parkinson's disease.

PubMed

Rascol, O; Payoux, P; Ferreira, J; Brefel-Courbon, C

2002-10-01

A major problem in the management of early Parkinson's disease is to choose the first medication to prescribe. This decision should rely on the level of available clinical evidence, largely based, at least for efficacy, on the results of randomised clinical trials. Safety and costs are also crucial to consider. Other factors like for example pathophysiological concepts, individual experience, marketing pressure, socio-economical environment, patients needs and expectations have, however, also their own influence. Levodopa is efficacious and cheap, but induces long-term motor complications. The early use of dopamine agonists is more and more frequently promoted, because large prospective L-dopa-controlled trials demonstrated that this strategy reduces the risk of such long-term complications. Integrating individual clinical expertise to the best available external clinical evidence (evidence-based medicine) is the best strategy in making decisions about the care of individual patients. Copyright 2002 Elsevier Science Ltd.

Guidelines for hypertension treatment: applications for primary care practice--a review of the JNC VI report.

PubMed

Alexander, L M

1998-01-01

The Joint National Committee's report on the Prevention, Detection, Evaluation, and Treatment of High Blood Pressure was released in November 1997. With its release, an increased emphasis on "treating the patient, not just the number" has taken place. The report provides a comprehensive review of recent clinical evidence that helps guide clinical decision making in the care of the hypertensive patient. A new disease classification system entitled "risk stratification" is introduced and takes into account comorbid conditions that are present for many hypertensive individuals. This risk stratification is then linked to treatment strategies and provides a concise decision analysis framework to aid in clinical decision making. Community-based prevention strategies are also highlighted and should raise the awareness of clinicians to adopt these recommendations and integrate them more aggressively into daily practice. Increased emphasis on patient compliance to improve overall hypertension control rates is also presented. Maximum efficacy through once-daily dosing and fixed-dose combinations are reviewed in the report. The JNC report is a comprehensive resource for clinicians in primary care practice. Its evidenced-based approach is a wonderful teaching tool for those clinicians who also serve as clinical educators in primary care.

Cystic echinococcosis of the liver: A primer for hepatologists

PubMed Central

Rinaldi, Francesca; Brunetti, Enrico; Neumayr, Andreas; Maestri, Marcello; Goblirsch, Samuel; Tamarozzi, Francesca

2014-01-01

Cystic echinococcosis (CE) is a complex, chronic and neglected disease with a worldwide distribution. The liver is the most frequent location of parasitic cysts. In humans, its clinical spectrum ranges from asymptomatic infection to severe, potentially fatal disease. Four approaches exist in the clinical management of CE: surgery, percutaneous techniques and drug treatment for active cysts, and the ”watch and wait” approach for inactive cysts. Allocation of patients to these treatments should be based on cyst stage, size and location, available clinical expertise, and comorbidities. However, clinical decision algorithms, efficacy, relapse rates, and costs have never been properly evaluated. This paper reviews recent advances in classification and diagnosis and the currently available evidence for clinical decision-making in cystic echinococcosis of the liver. PMID:24868323

OrderRex: clinical order decision support and outcome predictions by data-mining electronic medical records.

PubMed

Chen, Jonathan H; Podchiyska, Tanya; Altman, Russ B

2016-03-01

To answer a "grand challenge" in clinical decision support, the authors produced a recommender system that automatically data-mines inpatient decision support from electronic medical records (EMR), analogous to Netflix or Amazon.com's product recommender. EMR data were extracted from 1 year of hospitalizations (>18K patients with >5.4M structured items including clinical orders, lab results, and diagnosis codes). Association statistics were counted for the ∼1.5K most common items to drive an order recommender. The authors assessed the recommender's ability to predict hospital admission orders and outcomes based on initial encounter data from separate validation patients. Compared to a reference benchmark of using the overall most common orders, the recommender using temporal relationships improves precision at 10 recommendations from 33% to 38% (P < 10(-10)) for hospital admission orders. Relative risk-based association methods improve inverse frequency weighted recall from 4% to 16% (P < 10(-16)). The framework yields a prediction receiver operating characteristic area under curve (c-statistic) of 0.84 for 30 day mortality, 0.84 for 1 week need for ICU life support, 0.80 for 1 week hospital discharge, and 0.68 for 30-day readmission. Recommender results quantitatively improve on reference benchmarks and qualitatively appear clinically reasonable. The method assumes that aggregate decision making converges appropriately, but ongoing evaluation is necessary to discern common behaviors from "correct" ones. Collaborative filtering recommender algorithms generate clinical decision support that is predictive of real practice patterns and clinical outcomes. Incorporating temporal relationships improves accuracy. Different evaluation metrics satisfy different goals (predicting likely events vs. "interesting" suggestions). Published by Oxford University Press on behalf of the American Medical Informatics Association 2015. This work is written by US Government employees and is in the public domain in the US.

Teaching metacognition in clinical decision-making using a novel mnemonic checklist: an exploratory study

PubMed Central

Chew, Keng Sheng; Durning, Steven J; van Merriënboer, Jeroen JG

2016-01-01

INTRODUCTION Metacognition is a cognitive debiasing strategy that clinicians can use to deliberately detach themselves from the immediate context of a clinical decision, which allows them to reflect upon the thinking process. However, cognitive debiasing strategies are often most needed when the clinician cannot afford the time to use them. A mnemonic checklist known as TWED (T = threat, W = what else, E = evidence and D = dispositional factors) was recently created to facilitate metacognition. This study explores the hypothesis that the TWED checklist improves the ability of medical students to make better clinical decisions. METHODS Two groups of final-year medical students from Universiti Sains Malaysia, Malaysia, were recruited to participate in this quasi-experimental study. The intervention group (n = 21) received educational intervention that introduced the TWED checklist, while the control group (n = 19) received a tutorial on basic electrocardiography. Post-intervention, both groups received a similar assessment on clinical decision-making based on five case scenarios. RESULTS The mean score of the intervention group was significantly higher than that of the control group (18.50 ± 4.45 marks vs. 12.50 ± 2.84 marks, p < 0.001). In three of the five case scenarios, students in the intervention group obtained higher scores than those in the control group. CONCLUSION The results of this study support the use of the TWED checklist to facilitate metacognition in clinical decision-making. PMID:26778635

Decision Making in Health and Medicine

NASA Astrophysics Data System (ADS)

Hunink, Myriam; Glasziou, Paul; Siegel, Joanna; Weeks, Jane; Pliskin, Joseph; Elstein, Arthur; Weinstein, Milton C.

2001-11-01

Decision making in health care means navigating through a complex and tangled web of diagnostic and therapeutic uncertainties, patient preferences and values, and costs. In addition, medical therapies may include side effects, surgery may lead to undesirable complications, and diagnostic technologies may produce inconclusive results. In many clinical and health policy decisions it is necessary to counterbalance benefits and risks, and to trade off competing objectives such as maximizing life expectancy vs optimizing quality of life vs minimizing the required resources. This textbook plots a clear course through these complex and conflicting variables. It clearly explains and illustrates tools for integrating quantitative evidence-based data and subjective outcome values in making clinical and health policy decisions. An accompanying CD-ROM features solutions to the exercises, PowerPoint® presentations of the illustrations, and sample models and tables.

Guidelines and Value-Based Decision Making: An Evolving Role for Payers.

PubMed

McCauley, Janet L

2015-01-01

Payers use evidence-based guidelines to promote effective health diagnoses and treatments for their members and to ensure that members are not subject to harmful or wasteful care. Payer guidelines inform coverage, but the content of these guidelines relies on the same evidentiary base as clinical treatment guidelines. Recent strategies to foster value through benefit design and alternative reimbursement methodologies illustrate emerging applications for evidence-based guidelines. The current focus on cost effectiveness within health technology assessment, comparative effectiveness research in collaboration with payers, and transparency around payer evidence assessment could better align payers' interests in evidence-based care with those of other stakeholders. The move to value in health care will depend upon credible clinical evidence to enable informed decision making. ©2015 by the North Carolina Institute of Medicine and The Duke Endowment. All rights reserved.

Development and evaluation of online evidence based guideline bank system.

PubMed

Park, Myonghwa

2006-01-01

The purpose of this study was to develop and evaluate the online evidence-based nursing practice guideline bank system to support the best evidence-based decision in the clinical and community practice settings. The main homepage consisted of seven modules for introduction of site, EBN, guideline bank, guideline development, guideline review, related sites, and community. The major contents in the guidelines were purpose, developer, intended audience, method of development, target population, testing, knowledge components, and evaluation. Electronic versions of the guidelines were displayed by XML, PDF, and PDA versions. The system usability were evaluated by general users, guideline developers, and guideline reviewers on the web and the results showed high scores of satisfaction. This online evidence-based guideline bank system could support nurses' best and cost-effective clinical decision using the sharable standardized guidelines with education module of evidence based nursing.

Influence of patients' socioeconomic status on clinical management decisions: a qualitative study.

PubMed

Bernheim, Susannah M; Ross, Joseph S; Krumholz, Harlan M; Bradley, Elizabeth H

2008-01-01

Little is known about how patients' socioeconomic status (SES) influences physicians' clinical management decisions, although this information may have important implications for understanding inequities in health care quality. We investigated physician perspectives on how patients' SES influences care. The study consisted of in-depth semistructured interviews with primary care physicians in Connecticut. Investigators coded interviews line by line and refined the coding structure and interview guide based on successive interviews. Recurrent themes emerged through iterative analysis of codes and tagged quotations. We interviewed 18 physicians from varied practice settings, 6 female, 9 from minority racial backgrounds, and 3 of Hispanic ethnicity. Four themes emerged from our interviews: (1) physicians held conflicting views about the effect of patient SES on clinical management, (2) physicians believed that changes in clinical management based on the patient's SES were made in the patient's interest, (3) physicians varied in the degree to which they thought changes in clinical management influenced patient outcomes, and (4) physicians faced personal and financial strains when caring for patients of low SES. Physicians indicated that patient SES did affect their clinical management decisions. As a result, physicians commonly undertook changes to their management plan in an effort to enhance patient outcomes, but they experienced numerous strains when trying to balance what they believed was feasible for the patient with what they perceived as established standards of care.

Cost-effectiveness in Clostridium difficile treatment decision-making

PubMed Central

Nuijten, Mark JC; Keller, Josbert J; Visser, Caroline E; Redekop, Ken; Claassen, Eric; Speelman, Peter; Pronk, Marja H

2015-01-01

AIM: To develop a framework for the clinical and health economic assessment for management of Clostridium difficile infection (CDI). METHODS: CDI has vast economic consequences emphasizing the need for innovative and cost effective solutions, which were aim of this study. A guidance model was developed for coverage decisions and guideline development in CDI. The model included pharmacotherapy with oral metronidazole or oral vancomycin, which is the mainstay for pharmacological treatment of CDI and is recommended by most treatment guidelines. RESULTS: A design for a patient-based cost-effectiveness model was developed, which can be used to estimate the cost-effectiveness of current and future treatment strategies in CDI. Patient-based outcomes were extrapolated to the population by including factors like, e.g., person-to-person transmission, isolation precautions and closing and cleaning wards of hospitals. CONCLUSION: The proposed framework for a population-based CDI model may be used for clinical and health economic assessments of CDI guidelines and coverage decisions for emerging treatments for CDI. PMID:26601096

Cost-effectiveness in Clostridium difficile treatment decision-making.

PubMed

Nuijten, Mark Jc; Keller, Josbert J; Visser, Caroline E; Redekop, Ken; Claassen, Eric; Speelman, Peter; Pronk, Marja H

2015-11-16

To develop a framework for the clinical and health economic assessment for management of Clostridium difficile infection (CDI). CDI has vast economic consequences emphasizing the need for innovative and cost effective solutions, which were aim of this study. A guidance model was developed for coverage decisions and guideline development in CDI. The model included pharmacotherapy with oral metronidazole or oral vancomycin, which is the mainstay for pharmacological treatment of CDI and is recommended by most treatment guidelines. A design for a patient-based cost-effectiveness model was developed, which can be used to estimate the cost-effectiveness of current and future treatment strategies in CDI. Patient-based outcomes were extrapolated to the population by including factors like, e.g., person-to-person transmission, isolation precautions and closing and cleaning wards of hospitals. The proposed framework for a population-based CDI model may be used for clinical and health economic assessments of CDI guidelines and coverage decisions for emerging treatments for CDI.

External Validation of a Decision Tool To Guide Post-Operative Management of Patients with Secondary Peritonitis.

PubMed

Atema, Jasper J; Ram, Kim; Schultz, Marcus J; Boermeester, Marja A

Timely identification of patients in need of an intervention for abdominal sepsis after initial surgical management of secondary peritonitis is vital but complex. The aim of this study was to validate a decision tool for this purpose and to evaluate its potential to guide post-operative management. A prospective cohort study was conducted on consecutive adult patients undergoing surgery for secondary peritonitis in a single hospital. Assessments using the decision tool, based on one intra-operative and five post-operative variables, were performed on the second and third post-operative days and when the patients' clinical status deteriorated. Scores were compared with the clinical reference standard of persistent sepsis based on the clinical course or findings at imaging or surgery. Additionally, the potential of the decision tool to guide management in terms of diagnostic imaging in three previously defined score categories (low, intermediate, and high) was evaluated. A total of 161 assessments were performed in 69 patients. The majority of cases of secondary peritonitis (68%) were caused by perforation of the gastrointestinal tract. Post-operative persistent sepsis occurred in 28 patients. The discriminative capacity of the decision tool score was fair (area under the curve of the receiver operating characteristic = 0.79). The incidence rate differed significantly between the three score categories (p < 0.001). The negative predictive value of a decision tool score categorized as low probability was 89% (95% confidence interval [CI] 82-94) and 65% (95% CI 47-79) for an intermediate score. Diagnostic imaging was performed more frequently when there was an intermediate score than when the score was categorized as low (46% vs. 24%; p < 0.001). In patients operated on for secondary peritonitis, the decision tool score predicts with fair accuracy whether persistent sepsis is present.

Mammography Decision Aid Reduces Decisional Conflict for Women in Their Forties Considering Screening.

PubMed

Eden, Karen B; Scariati, Paula; Klein, Krystal; Watson, Lindsey; Remiker, Mark; Hribar, Michelle; Forro, Vanessa; Michaels, LeAnn; Nelson, Heidi D

2015-12-01

Clinical guidelines recommend a personalized approach to mammography screening for women in their forties; however, methods to do so are lacking. An evidence-based mammography screening decision aid was developed as an electronic mobile application and evaluated in a before-after study. The decision aid (Mammopad) included modules on breast cancer, mammography, risk assessment, and priority setting about screening. Women aged 40-49 years who were patients of rural primary care clinics, had no major risk factors for breast cancer, and no mammography during the previous year were invited to use the decision aid. Twenty women participated in pretesting of the decision aid and 75 additional women completed the before-after study. The primary outcome was decisional conflict measured before and after using Mammopad. Secondary outcomes included decision self-efficacy and intention to begin or continue mammography screening. Differences comparing measures before versus after use were determined using Wilcoxon signed rank tests. After using Mammopad, women reported reduced decisional conflict based on mean Decisional Conflict Scale scores overall (46.33 versus 8.33; Z = -7.225; p < 0.001) and on all subscales (p < 0.001). Women also reported increased mean Decision Self-Efficacy Scale scores (79.67 versus 95.73; Z = 6.816, p < 0.001). Although 19% of women changed their screening intentions, this was not statistically significant. Women reported less conflict about their decisions for mammography screening, and felt more confident to make decisions after using Mammopad. This approach may help guide women through the decision making process to determine personalized screening choices that are appropriate for them.

[Upon scientific accuracy scheme at clinical specialties].

PubMed

Ortega Calvo, M

2006-11-01

Will be medical specialties like sciences in the future? Yes, progressively they will. Accuracy in clinical specialties will be dissimilar in the future because formal-logic mathematics, quantum physics advances and relativity theory utilities. Evidence based medicine is now helping to clinical specialties on scientific accuracy by the way of decision theory.

Semantics-based plausible reasoning to extend the knowledge coverage of medical knowledge bases for improved clinical decision support.

PubMed

Mohammadhassanzadeh, Hossein; Van Woensel, William; Abidi, Samina Raza; Abidi, Syed Sibte Raza

2017-01-01

Capturing complete medical knowledge is challenging-often due to incomplete patient Electronic Health Records (EHR), but also because of valuable, tacit medical knowledge hidden away in physicians' experiences. To extend the coverage of incomplete medical knowledge-based systems beyond their deductive closure, and thus enhance their decision-support capabilities, we argue that innovative, multi-strategy reasoning approaches should be applied. In particular, plausible reasoning mechanisms apply patterns from human thought processes, such as generalization, similarity and interpolation, based on attributional, hierarchical, and relational knowledge. Plausible reasoning mechanisms include inductive reasoning , which generalizes the commonalities among the data to induce new rules, and analogical reasoning , which is guided by data similarities to infer new facts. By further leveraging rich, biomedical Semantic Web ontologies to represent medical knowledge, both known and tentative, we increase the accuracy and expressivity of plausible reasoning, and cope with issues such as data heterogeneity, inconsistency and interoperability. In this paper, we present a Semantic Web-based, multi-strategy reasoning approach, which integrates deductive and plausible reasoning and exploits Semantic Web technology to solve complex clinical decision support queries. We evaluated our system using a real-world medical dataset of patients with hepatitis, from which we randomly removed different percentages of data (5%, 10%, 15%, and 20%) to reflect scenarios with increasing amounts of incomplete medical knowledge. To increase the reliability of the results, we generated 5 independent datasets for each percentage of missing values, which resulted in 20 experimental datasets (in addition to the original dataset). The results show that plausibly inferred knowledge extends the coverage of the knowledge base by, on average, 2%, 7%, 12%, and 16% for datasets with, respectively, 5%, 10%, 15%, and 20% of missing values. This expansion in the KB coverage allowed solving complex disease diagnostic queries that were previously unresolvable, without losing the correctness of the answers. However, compared to deductive reasoning, data-intensive plausible reasoning mechanisms yield a significant performance overhead. We observed that plausible reasoning approaches, by generating tentative inferences and leveraging domain knowledge of experts, allow us to extend the coverage of medical knowledge bases, resulting in improved clinical decision support. Second, by leveraging OWL ontological knowledge, we are able to increase the expressivity and accuracy of plausible reasoning methods. Third, our approach is applicable to clinical decision support systems for a range of chronic diseases.

When is rational to order a diagnostic test, or prescribe treatment: the threshold model as an explanation of practice variation.

PubMed

Djulbegovic, Benjamin; van den Ende, Jef; Hamm, Robert M; Mayrhofer, Thomas; Hozo, Iztok; Pauker, Stephen G

2015-05-01

The threshold model represents an important advance in the field of medical decision-making. It is a linchpin between evidence (which exists on the continuum of credibility) and decision-making (which is a categorical exercise - we decide to act or not act). The threshold concept is closely related to the question of rational decision-making. When should the physician act, that is order a diagnostic test, or prescribe treatment? The threshold model embodies the decision theoretic rationality that says the most rational decision is to prescribe treatment when the expected treatment benefit outweighs its expected harms. However, the well-documented large variation in the way physicians order diagnostic tests or decide to administer treatments is consistent with a notion that physicians' individual action thresholds vary. We present a narrative review summarizing the existing literature on physicians' use of a threshold strategy for decision-making. We found that the observed variation in decision action thresholds is partially due to the way people integrate benefits and harms. That is, explanation of variation in clinical practice can be reduced to a consideration of thresholds. Limited evidence suggests that non-expected utility threshold (non-EUT) models, such as regret-based and dual-processing models, may explain current medical practice better. However, inclusion of costs and recognition of risk attitudes towards uncertain treatment effects and comorbidities may improve the explanatory and predictive value of the EUT-based threshold models. The decision when to act is closely related to the question of rational choice. We conclude that the medical community has not yet fully defined criteria for rational clinical decision-making. The traditional notion of rationality rooted in EUT may need to be supplemented by reflective rationality, which strives to integrate all aspects of medical practice - medical, humanistic and socio-economic - within a coherent reasoning system. © 2015 Stichting European Society for Clinical Investigation Journal Foundation.

Modeling the Innovation-Decision Process: Dissemination and Adoption of a Motivational Interviewing Preparatory Procedure in Addiction Outpatient Clinics

PubMed Central

Walitzer, Kimberly S.; Dermen, Kurt H.; Barrick, Christopher; Shyhalla, Kathleen

2015-01-01

Widespread adoption of empirically-supported treatment innovations has the potential to improve effectiveness of treatment received by individuals with substance use disorders. However, the process of disseminating such innovations has been complex, slow, and difficult. We empirically describe the dissemination and adoption of a treatment innovation – an alcohol-treatment preparatory therapeutic procedure based on motivational interviewing (MI) – in the context of Rogers’ (2003) five stages of innovation-decision process (knowledge, persuasion, decision, implementation and confirmation). To this end, 145 randomly-chosen outpatient addiction treatment clinics in New York State received an onsite visit from a project trainer delivering one of three randomly-assigned dissemination intensities: a 15-minute, a half-day or a full-day presentation. Across these clinics, 141 primary administrators and 837 clinicians completed questionnaires assessing aspects of five innovation-decision stages. At each clinic, questionnaire administration occurred immediately pre- and post-dissemination, as well as one and six months after dissemination. Consistent with Rogers’ theory, earlier stages of the innovation-decision process predicted later stages. As hypothesized, dissemination intensity predicted clinicians’ post-dissemination knowledge. Clinician baseline characteristics (including gender, pre-dissemination knowledge regarding the MI preparatory technique, education, case load, beliefs regarding the nature of alcohol problems, and beliefs and behavior with regard to therapeutic style) predicted knowledge and persuasion stage variables. One baseline clinic characteristic (i.e., clinic mean beliefs and behavior regarding an MI-consistent therapeutic style) predicted implementation stage variables. Findings suggest that dissemination strategies should accommodate clinician and clinic characteristics. PMID:25934460

A Serious Game for Teaching Nursing Students Clinical Reasoning and Decision-Making Skills.

PubMed

Johnsen, Hege Mari; Fossum, Mariann; Vivekananda-Schmidt, Pirashanthie; Fruhling, Ann; Slettebø, Åshild

2016-01-01

The aim of this study was to design and pilot-test a serious game for teaching nursing students clinical reasoning and decision-making skills in caring for patients with chronic obstructive pulmonary disease. A video-based serious game prototype was developed. A purposeful sample of six participants tested and evaluated the prototype. Usability issues were identified regarding functionality and user-computer interface. However, overall the serious game was perceived to be useful, usable and likable to use.

Data warehousing: toward knowledge management.

PubMed

Shams, K; Farishta, M

2001-02-01

With rapid changes taking place in the practice and delivery of health care, decision support systems have assumed an increasingly important role. More and more health care institutions are deploying data warehouse applications as decision support tools for strategic decision making. By making the right information available at the right time to the right decision makers in the right manner, data warehouses empower employees to become knowledge workers with the ability to make the right decisions and solve problems, creating strategic leverage for the organization. Health care management must plan and implement data warehousing strategy using a best practice approach. Through the power of data warehousing, health care management can negotiate bettermanaged care contracts based on the ability to provide accurate data on case mix and resource utilization. Management can also save millions of dollars through the implementation of clinical pathways in better resource utilization and changing physician behavior to best practices based on evidence-based medicine.

Clinical Ethics Consultants are not “Ethics” Experts—But They do Have Expertise 1

PubMed Central

Rasmussen, Lisa M.

2016-01-01

The attempt to critique the profession of clinical ethics consultation by establishing the impossibility of ethics expertise has been a red herring. Decisions made in clinical ethics cases are almost never based purely on moral judgments. Instead, they are all-things-considered judgments that involve determining how to balance other values as well. A standard of justified decision-making in this context would enable us to identify experts who could achieve these standards more often than others, and thus provide a basis for expertise in clinical ethics consultation. This expertise relies in part on what Richard Zaner calls the “expert knowledge of ethical phenomena” (1988, 8). PMID:27302970

Evaluation of a decision support system for pressure ulcer prevention and management: preliminary findings.

PubMed

Zielstorff, R D; Estey, G; Vickery, A; Hamilton, G; Fitzmaurice, J B; Barnett, G O

1997-01-01

A decision support system for prevention and management of pressure ulcers was developed based on AHCPR guidelines and other sources. The system was implemented for 21 weeks on a 20-bed clinical care unit. Fifteen nurses on that unit volunteered as subjects of the intervention to see whether use of the system would have a positive effect on their knowledge about pressure ulcers and on their decision-making skills related to this topic. A similar care unit was used as a control. In addition, the system was evaluated by experts for its instructional adequacy, and by end users for their satisfaction with the system. Preliminary results show no effect on knowledge about pressure ulcers and no effect on clinical decision making skills. The system was rated positively for instructional adequacy, and positively for user satisfaction. User interviews related to satisfaction supplemented the quantitative findings. A discussion of the issues of conducting experiments like this in today's clinical environment is included.

Enabling personalized cancer medicine decisions: The challenging pharmacological approach of PBPK models for nanomedicine and pharmacogenomics (Review).

PubMed

Vizirianakis, Ioannis S; Mystridis, George A; Avgoustakis, Konstantinos; Fatouros, Dimitrios G; Spanakis, Marios

2016-04-01

The existing tumor heterogeneity and the complexity of cancer cell biology critically demand powerful translational tools with which to support interdisciplinary efforts aiming to advance personalized cancer medicine decisions in drug development and clinical practice. The development of physiologically based pharmacokinetic (PBPK) models to predict the effects of drugs in the body facilitates the clinical translation of genomic knowledge and the implementation of in vivo pharmacology experience with pharmacogenomics. Such a direction unequivocally empowers our capacity to also make personalized drug dosage scheme decisions for drugs, including molecularly targeted agents and innovative nanoformulations, i.e. in establishing pharmacotyping in prescription. In this way, the applicability of PBPK models to guide individualized cancer therapeutic decisions of broad clinical utility in nanomedicine in real-time and in a cost-affordable manner will be discussed. The latter will be presented by emphasizing the need for combined efforts within the scientific borderlines of genomics with nanotechnology to ensure major benefits and productivity for nanomedicine and personalized medicine interventions.

A review of clinical decision making: models and current research.

PubMed

Banning, Maggi

2008-01-01

The aim of this paper was to review the current literature clinical decision-making models and the educational application of models to clinical practice. This was achieved by exploring the function and related research of the three available models of clinical decision making: information-processing model, the intuitive-humanist model and the clinical decision-making model. Clinical decision making is a unique process that involves the interplay between knowledge of pre-existing pathological conditions, explicit patient information, nursing care and experiential learning. Historically, two models of clinical decision making are recognized from the literature; the information-processing model and the intuitive-humanist model. The usefulness and application of both models has been examined in relation the provision of nursing care and care related outcomes. More recently a third model of clinical decision making has been proposed. This new multidimensional model contains elements of the information-processing model but also examines patient specific elements that are necessary for cue and pattern recognition. Literature review. Evaluation of the literature generated from MEDLINE, CINAHL, OVID, PUBMED and EBESCO systems and the Internet from 1980 to November 2005. The characteristics of the three models of decision making were identified and the related research discussed. Three approaches to clinical decision making were identified, each having its own attributes and uses. The most recent addition to the clinical decision making is a theoretical, multidimensional model which was developed through an evaluation of current literature and the assessment of a limited number of research studies that focused on the clinical decision-making skills of inexperienced nurses in pseudoclinical settings. The components of this model and the relative merits to clinical practice are discussed. It is proposed that clinical decision making improves as the nurse gains experience of nursing patients within a specific speciality and with experience, nurses gain a sense of saliency in relation to decision making. Experienced nurses may use all three forms of clinical decision making both independently and concurrently to solve nursing-related problems. It is suggested that O'Neill's clinical decision-making model could be tested by educators and experienced nurses to assess the efficacy of this hybrid approach to decision making.

Evidence-based medicine in primary care: qualitative study of family physicians.

PubMed

Tracy, C Shawn; Dantas, Guilherme Coelho; Upshur, Ross E G

2003-05-09

The objectives of this study were: a) to examine physician attitudes to and experience of the practice of evidence-based medicine (EBM) in primary care; b) to investigate the influence of patient preferences on clinical decision-making; and c) to explore the role of intuition in family practice. Qualitative analysis of semi-structured interviews of 15 family physicians purposively selected from respondents to a national survey on EBM mailed to a random sample of Canadian family physicians. Participants mainly welcomed the promotion of EBM in the primary care setting. A significant number of barriers and limitations to the implementation of EBM were identified. EBM is perceived by some physicians as a devaluation of the 'art of medicine' and a threat to their professional/clinical autonomy. Issues regarding the trustworthiness and credibility of evidence were of great concern, especially with respect to the influence of the pharmaceutical industry. Attempts to become more evidence-based often result in the experience of conflicts. Patient factors exert a powerful influence on clinical decision-making and can serve as trumps to research evidence. A widespread belief that intuition plays a vital role in primary care reinforced views that research evidence must be considered alongside other factors such as patient preferences and the clinical judgement and experience of the physician. Primary care physicians are increasingly keen to consider research evidence in clinical decision-making, but there are significant concerns about the current model of EBM. Our findings support the proposed revisions to EBM wherein greater emphasis is placed on clinical expertise and patient preferences, both of which remain powerful influences on physician behaviour.

IBM's Health Analytics and Clinical Decision Support.

PubMed

Kohn, M S; Sun, J; Knoop, S; Shabo, A; Carmeli, B; Sow, D; Syed-Mahmood, T; Rapp, W

2014-08-15

This survey explores the role of big data and health analytics developed by IBM in supporting the transformation of healthcare by augmenting evidence-based decision-making. Some problems in healthcare and strategies for change are described. It is argued that change requires better decisions, which, in turn, require better use of the many kinds of healthcare information. Analytic resources that address each of the information challenges are described. Examples of the role of each of the resources are given. There are powerful analytic tools that utilize the various kinds of big data in healthcare to help clinicians make more personalized, evidenced-based decisions. Such resources can extract relevant information and provide insights that clinicians can use to make evidence-supported decisions. There are early suggestions that these resources have clinical value. As with all analytic tools, they are limited by the amount and quality of data. Big data is an inevitable part of the future of healthcare. There is a compelling need to manage and use big data to make better decisions to support the transformation of healthcare to the personalized, evidence-supported model of the future. Cognitive computing resources are necessary to manage the challenges in employing big data in healthcare. Such tools have been and are being developed. The analytic resources, themselves, do not drive, but support healthcare transformation.

Enhancing emotion-based learning in decision-making under uncertainty.

PubMed

Alarcón, David; Amián, Josué G; Sánchez-Medina, José A

2015-01-01

The Iowa Gambling Task (IGT) is widely used to study decision-making differences between several clinical and healthy populations. Unlike the healthy participants, clinical participants have difficulty choosing between advantageous options, which yield long-term benefits, and disadvantageous options, which give high immediate rewards but lead to negative profits. However, recent studies have found that healthy participants avoid the options with a higher frequency of losses regardless of whether or not they are profitable in the long run. The aim of this study was to control for the confounding effect of the frequency of losses between options to improve the performance of healthy participants on the IGT. Eighty healthy participants were randomly assigned to the original IGT or a modified version of the IGT that diminished the gap in the frequency of losses between options. The participants who used the modified IGT version learned to make better decisions based on long-term profit, as indicated by an earlier ability to discriminate good from bad options, and took less time to make their choices. This research represents an advance in the study of decision making under uncertainty by showing that emotion-based learning is improved by controlling for the loss-frequency bias effect.

Development and implementation of a mobile device-based pediatric electronic decision support tool as part of a national practice standardization project.

PubMed

McCulloh, Russell J; Fouquet, Sarah D; Herigon, Joshua; Biondi, Eric A; Kennedy, Brandan; Kerns, Ellen; DePorre, Adrienne; Markham, Jessica L; Chan, Y Raymond; Nelson, Krista; Newland, Jason G

2018-06-07

Implementing evidence-based practices requires a multi-faceted approach. Electronic clinical decision support (ECDS) tools may encourage evidence-based practice adoption. However, data regarding the role of mobile ECDS tools in pediatrics is scant. Our objective is to describe the development, distribution, and usage patterns of a smartphone-based ECDS tool within a national practice standardization project. We developed a smartphone-based ECDS tool for use in the American Academy of Pediatrics, Value in Inpatient Pediatrics Network project entitled "Reducing Excessive Variation in the Infant Sepsis Evaluation (REVISE)." The mobile application (app), PedsGuide, was developed using evidence-based recommendations created by an interdisciplinary panel. App workflow and content were aligned with clinical benchmarks; app interface was adjusted after usability heuristic review. Usage patterns were measured using Google Analytics. Overall, 3805 users across the United States downloaded PedsGuide from December 1, 2016, to July 31, 2017, leading to 14 256 use sessions (average 3.75 sessions per user). Users engaged in 60 442 screen views, including 37 424 (61.8%) screen views that displayed content related to the REVISE clinical practice benchmarks, including hospital admission appropriateness (26.8%), length of hospitalization (14.6%), and diagnostic testing recommendations (17.0%). Median user touch depth was 5 [IQR 5]. We observed rapid dissemination and in-depth engagement with PedsGuide, demonstrating feasibility for using smartphone-based ECDS tools within national practice improvement projects. ECDS tools may prove valuable in future national practice standardization initiatives. Work should next focus on developing robust analytics to determine ECDS tools' impact on medical decision making, clinical practice, and health outcomes.

Using statistical process control to make data-based clinical decisions.

PubMed

Pfadt, A; Wheeler, D J

1995-01-01

Applied behavior analysis is based on an investigation of variability due to interrelationships among antecedents, behavior, and consequences. This permits testable hypotheses about the causes of behavior as well as for the course of treatment to be evaluated empirically. Such information provides corrective feedback for making data-based clinical decisions. This paper considers how a different approach to the analysis of variability based on the writings of Walter Shewart and W. Edwards Deming in the area of industrial quality control helps to achieve similar objectives. Statistical process control (SPC) was developed to implement a process of continual product improvement while achieving compliance with production standards and other requirements for promoting customer satisfaction. SPC involves the use of simple statistical tools, such as histograms and control charts, as well as problem-solving techniques, such as flow charts, cause-and-effect diagrams, and Pareto charts, to implement Deming's management philosophy. These data-analytic procedures can be incorporated into a human service organization to help to achieve its stated objectives in a manner that leads to continuous improvement in the functioning of the clients who are its customers. Examples are provided to illustrate how SPC procedures can be used to analyze behavioral data. Issues related to the application of these tools for making data-based clinical decisions and for creating an organizational climate that promotes their routine use in applied settings are also considered.

A Toolbox to Improve Algorithms for Insulin-Dosing Decision Support

PubMed Central

Donsa, K.; Plank, J.; Schaupp, L.; Mader, J. K.; Truskaller, T.; Tschapeller, B.; Höll, B.; Spat, S.; Pieber, T. R.

2014-01-01

Summary Background Standardized insulin order sets for subcutaneous basal-bolus insulin therapy are recommended by clinical guidelines for the inpatient management of diabetes. The algorithm based GlucoTab system electronically assists health care personnel by supporting clinical workflow and providing insulin-dose suggestions. Objective To develop a toolbox for improving clinical decision-support algorithms. Methods The toolbox has three main components. 1) Data preparation: Data from several heterogeneous sources is extracted, cleaned and stored in a uniform data format. 2) Simulation: The effects of algorithm modifications are estimated by simulating treatment workflows based on real data from clinical trials. 3) Analysis: Algorithm performance is measured, analyzed and simulated by using data from three clinical trials with a total of 166 patients. Results Use of the toolbox led to algorithm improvements as well as the detection of potential individualized subgroup-specific algorithms. Conclusion These results are a first step towards individualized algorithm modifications for specific patient subgroups. PMID:25024768

A Swarm Optimization approach for clinical knowledge mining.

PubMed

Christopher, J Jabez; Nehemiah, H Khanna; Kannan, A

2015-10-01

Rule-based classification is a typical data mining task that is being used in several medical diagnosis and decision support systems. The rules stored in the rule base have an impact on classification efficiency. Rule sets that are extracted with data mining tools and techniques are optimized using heuristic or meta-heuristic approaches in order to improve the quality of the rule base. In this work, a meta-heuristic approach called Wind-driven Swarm Optimization (WSO) is used. The uniqueness of this work lies in the biological inspiration that underlies the algorithm. WSO uses Jval, a new metric, to evaluate the efficiency of a rule-based classifier. Rules are extracted from decision trees. WSO is used to obtain different permutations and combinations of rules whereby the optimal ruleset that satisfies the requirement of the developer is used for predicting the test data. The performance of various extensions of decision trees, namely, RIPPER, PART, FURIA and Decision Tables are analyzed. The efficiency of WSO is also compared with the traditional Particle Swarm Optimization. Experiments were carried out with six benchmark medical datasets. The traditional C4.5 algorithm yields 62.89% accuracy with 43 rules for liver disorders dataset where as WSO yields 64.60% with 19 rules. For Heart disease dataset, C4.5 is 68.64% accurate with 98 rules where as WSO is 77.8% accurate with 34 rules. The normalized standard deviation for accuracy of PSO and WSO are 0.5921 and 0.5846 respectively. WSO provides accurate and concise rulesets. PSO yields results similar to that of WSO but the novelty of WSO lies in its biological motivation and it is customization for rule base optimization. The trade-off between the prediction accuracy and the size of the rule base is optimized during the design and development of rule-based clinical decision support system. The efficiency of a decision support system relies on the content of the rule base and classification accuracy. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Modeling paradigms for medical diagnostic decision support: a survey and future directions.

PubMed

Wagholikar, Kavishwar B; Sundararajan, Vijayraghavan; Deshpande, Ashok W

2012-10-01

Use of computer based decision tools to aid clinical decision making, has been a primary goal of research in biomedical informatics. Research in the last five decades has led to the development of Medical Decision Support (MDS) applications using a variety of modeling techniques, for a diverse range of medical decision problems. This paper surveys literature on modeling techniques for diagnostic decision support, with a focus on decision accuracy. Trends and shortcomings of research in this area are discussed and future directions are provided. The authors suggest that-(i) Improvement in the accuracy of MDS application may be possible by modeling of vague and temporal data, research on inference algorithms, integration of patient information from diverse sources and improvement in gene profiling algorithms; (ii) MDS research would be facilitated by public release of de-identified medical datasets, and development of opensource data-mining tool kits; (iii) Comparative evaluations of different modeling techniques are required to understand characteristics of the techniques, which can guide developers in choice of technique for a particular medical decision problem; and (iv) Evaluations of MDS applications in clinical setting are necessary to foster physicians' utilization of these decision aids.

Evidence-based Management: From Theory to Practice in Health Care

PubMed Central

Walshe, Kieran; Rundall, Thomas G.

2001-01-01

The rise of evidence-based clinical practice in health care has caused some people to start questioning how health care managers and policymakers make decisions, and what role evidence plays in the process. Though managers and policymakers have been quick to encourage clinicians to adopt an evidence-based approach, they have been slower to apply the same ideas to their own practice. Yet, there is evidence that the same problems (of the underuse of effective interventions and the overuse of ineffective ones) are as widespread in health care management as they are in clinical practice. Because there are important differences between the culture, research base, and decision-making processes of clinicians and managers, the ideas of evidence-based practice, while relevant, need to be translated for management rather than simply transferred. The experience of the Center for Health Management Research (CHMR) is used to explore how to bring managers and researchers together and promote the use of evidence in managerial decision-making. However, health care funders, health care organizations, research funders, and academic centers need wider and more concerted action to promote the development of evidence-based managerial practice. PMID:11565163

Determining the psychometric properties of the Enhancing Decision-making Assessment in Midwifery (EDAM) measure in a cross cultural context.

PubMed

Jefford, Elaine; Jomeen, Julie; Martin, Colin R

2016-04-28

The ability to act on and justify clinical decisions as autonomous accountable midwifery practitioners, is encompassed within many international regulatory frameworks, yet decision-making within midwifery is poorly defined. Decision-making theories from medicine and nursing may have something to offer, but fail to take into consideration midwifery context and philosophy and the decisional autonomy of women. Using an underpinning qualitative methodology, a decision-making framework was developed, which identified Good Clinical Reasoning and Good Midwifery Practice as two conditions necessary to facilitate optimal midwifery decision-making during 2nd stage labour. This study aims to confirm the robustness of the framework and describe the development of Enhancing Decision-making Assessment in Midwifery (EDAM) as a measurement tool through testing of its factor structure, validity and reliability. A cross-sectional design for instrument development and a 2 (country; Australia/UK) x 2 (Decision-making; optimal/sub-optimal) between-subjects design for instrument evaluation using exploratory and confirmatory factor analysis, internal consistency and known-groups validity. Two 'expert' maternity panels, based in Australia and the UK, comprising of 42 participants assessed 16 midwifery real care episode vignettes using the empirically derived 26 item framework. Each item was answered on a 5 point likert scale based on the level of agreement to which the participant felt each item was present in each of the vignettes. Participants were then asked to rate the overall decision-making (optimal/sub-optimal). Post factor analysis the framework was reduced to a 19 item EDAM measure, and confirmed as two distinct scales of 'Clinical Reasoning' (CR) and 'Midwifery Practice' (MP). The CR scale comprised of two subscales; 'the clinical reasoning process' and 'integration and intervention'. The MP scale also comprised two subscales; women's relationship with the midwife' and 'general midwifery practice'. EDAM would generally appear to be a robust, valid and reliable psychometric instrument for measuring midwifery decision-making, which performs consistently across differing international contexts. The 'women's relationship with midwife' subscale marginally failed to meet the threshold for determining good instrument reliability, which may be due to its brevity. Further research using larger samples and in a wider international context to confirm the veracity of the instrument's measurement properties and its wider global utility, would be advantageous.

Evidence, research, knowledge: a call for conceptual clarity.

PubMed

Scott-Findlay, Shannon; Pollock, Carolee

2004-01-01

To dispel some of the conceptual confusion in the field of evidence-based practice that has resulted from the overlapping use of the terms research, evidence, and knowledge. Theoretical discussion. Often the terms research and knowledge are used as synonyms for evidence, but the overlap is never complete. The term evidence has long been understood to mean the findings of research. Recent attempts to broaden the definition of evidence to include clinical experience and experiential knowledge have been misguided. Broadening our understanding of the basis for clinical decision making and conceptualizing evidence are quite different tasks. Other factors (not other forms of evidence) do shape the clinical decision-making process, but they are not evidence. We might better term them knowledge. Confusing evidence with these other factors has hindered research and the improvement of clinical decision making in health care. We argue that this confusion results from the use of the term evidence when we really mean either research findings or knowledge. In this article, we have argued for specificity in the use of the term evidence. We urge the restriction of the term evidence to research findings, and while we acknowledge the importance of other influences on the clinical decision-making process, we insist that they are not evidence. The time has come to value personal experience and experiential knowledge for what they are-we should not have to disguise them as types of evidence for them to be deemed of any value. Being specific to language, the goal is to improve clinical decision making by increasing practitioners' reliance on research findings (evidence) while acknowledging (and valuing) the important part played by other forms of knowledge in the decision-making process. The distinctions are important.

Evidence-based medicine: what has happened in the past 50 years?

PubMed

Mellis, Craig

2015-01-01

Although the phrase 'evidence-based medicine' (EBM) was used for the first time in the medical literature less than 25 years ago, the history of EBM goes back for centuries. What is remarkable is how popular and how globally accepted the EBM movement has become in such a short time. Many famous, past clinicians have played major roles in the disciplines that preceded EBM, particularly 'clinical epidemiology'. It soon became clear to the early EBM champions that 'evidence' was only part of the clinical decision-making process. Consequently, both clinical expertise and the patient's values and preferences were rapidly incorporated into the concept we now know as 'EBM'. The current need for high-quality, easily accessible 'evidence-based summaries' for busy clinicians is now apparent, as traditional EBM requires both considerable time and skill. Consequently, there is a progressive move away from the primary literature (such as randomised controlled trials) to systematic reviews and other 'evidence-based summaries'. The future of EBM will almost certainly involve widespread utilisation of 'clinical (computer)-based decision support systems'. © 2014 The Author. Journal of Paediatrics and Child Health © 2014 Paediatrics and Child Health Division (Royal Australasian College of Physicians).

A diagnosis-based clinical decision rule for spinal pain part 2: review of the literature

PubMed Central

Murphy, Donald R; Hurwitz, Eric L; Nelson, Craig F

2008-01-01

Background Spinal pain is a common and often disabling problem. The research on various treatments for spinal pain has, for the most part, suggested that while several interventions have demonstrated mild to moderate short-term benefit, no single treatment has a major impact on either pain or disability. There is great need for more accurate diagnosis in patients with spinal pain. In a previous paper, the theoretical model of a diagnosis-based clinical decision rule was presented. The approach is designed to provide the clinician with a strategy for arriving at a specific working diagnosis from which treatment decisions can be made. It is based on three questions of diagnosis. In the current paper, the literature on the reliability and validity of the assessment procedures that are included in the diagnosis-based clinical decision rule is presented. Methods The databases of Medline, Cinahl, Embase and MANTIS were searched for studies that evaluated the reliability and validity of clinic-based diagnostic procedures for patients with spinal pain that have relevance for questions 2 (which investigates characteristics of the pain source) and 3 (which investigates perpetuating factors of the pain experience). In addition, the reference list of identified papers and authors' libraries were searched. Results A total of 1769 articles were retrieved, of which 138 were deemed relevant. Fifty-one studies related to reliability and 76 related to validity. One study evaluated both reliability and validity. Conclusion Regarding some aspects of the DBCDR, there are a number of studies that allow the clinician to have a reasonable degree of confidence in his or her findings. This is particularly true for centralization signs, neurodynamic signs and psychological perpetuating factors. There are other aspects of the DBCDR in which a lesser degree of confidence is warranted, and in which further research is needed. PMID:18694490

Considering Information Up-to-Dateness to Increase the Accuracy of Therapy Decision Support Systems.

PubMed

Gaebel, Jan; Cypko, Mario A; Oeltze-Jafra, Steffen

2017-01-01

During the diagnostic process a lot of information is generated. All this information is assessed when making a final diagnosis and planning the therapy. While some patient information is stable, e.g., gender, others may become outdated, e.g., tumor size derived from CT data. Quantifying this information up-to-dateness and deriving consequences are difficult. Especially for the implementation in clinical decision support systems, this has not been studied. When information entities tend to become outdated, in practice, clinicians intuitively reduce their impact when making decisions. Therefore, in a system's calculations their impact should be reduced as well. We propose a method of decreasing the certainty of information entities based on their up-to-dateness. The method is tested in a decision support system for TNM staging based on Bayesian networks. We compared the actual N-state in records of 39 patients to the N-state calculated with and without decreasing data certainty. The results under decreased certainty correlated better with the actual states (r=0.958, p=0.008). We conclude that the up-to-dateness must be considered when processing clinical information to enhance decision making and ensure more patient safety.

The Use of Biomarkers in Prostate Cancer Screening and Treatment

PubMed Central

Alford, Ashley V.; Brito, Joseph M.; Yadav, Kamlesh K.; Yadav, Shalini S.; Tewari, Ashutosh K.; Renzulli, Joseph

2017-01-01

Prostate cancer screening and diagnosis has been guided by prostate-specific antigen levels for the past 25 years, but with the most recent US Preventive Services Task Force screening recommendations, as well as concerns regarding overdiagnosis and overtreatment, a new wave of prostate cancer biomarkers has recently emerged. These assays allow the testing of urine, serum, or prostate tissue for molecular signs of prostate cancer, and provide information regarding both diagnosis and prognosis. In this review, we discuss 12 commercially available biomarker assays approved for the diagnosis and treatment of prostate cancer. The results of clinical validation studies and clinical decision-making studies are presented. This information is designed to assist urologists in making clinical decisions with respect to ordering and interpreting these tests for different patients. There are numerous fluid and biopsy-based genomic tests available for prostate cancer patients that provide the physician and patient with different information about risk of future disease and treatment outcomes. It is important that providers be able to recommend the appropriate test for each individual patient; this decision is based on tissue availability and prognostic information desired. Future studies will continue to emphasize the important role of genomic biomarkers in making individualized treatment decisions for prostate cancer patients. PMID:29472826

Clinical decision support systems: data quality management and governance.

PubMed

Liaw, Siaw-Teng

2013-01-01

This chapter examines data quality management (DQM) and information governance (IG) of electronic decision support (EDS) systems so that they are safe and fit for use by clinicians and patients and their carers. This is consistent with the ISO definition of data quality as being fit for purpose. The scope of DQM & IG should range from data creation and collection in clinical settings, through cleaning and, where obtained from multiple sources, linkage, storage, use by the EDS logic engine and algorithms, knowledge base and guidance provided, to curation and presentation. It must also include protocols and mechanisms to monitor the safety of EDS, which will feedback into DQM & IG activities. Ultimately, DQM & IG must be integrated across the data cycle to ensure that the EDS systems provide guidance that leads to safe and effective clinical decisions and care.

Clinical evidence supporting pharmacogenomic biomarker testing provided in US Food and Drug Administration drug labels.

PubMed

Wang, Bo; Canestaro, William J; Choudhry, Niteesh K

2014-12-01

Genetic biomarkers that predict a drug's efficacy or likelihood of toxicity are assuming increasingly important roles in the personalization of pharmacotherapy, but concern exists that evidence that links use of some biomarkers to clinical benefit is insufficient. Nevertheless, information about the use of biomarkers appears in the labels of many prescription drugs, which may add confusion to the clinical decision-making process. To evaluate the evidence that supports pharmacogenomic biomarker testing in drug labels and how frequently testing is recommended. Publicly available US Food and Drug Administration databases. We identified drug labels that described the use of a biomarker and evaluated whether the label contained or referenced convincing evidence of its clinical validity (ie, the ability to predict phenotype) and clinical utility (ie, the ability to improve clinical outcomes) using guidelines published by the Evaluation of Genomic Applications in Practice and Prevention Working Group. We graded the completeness of the citation of supporting studies and determined whether the label recommended incorporation of biomarker test results in therapeutic decision making. Of the 119 drug-biomarker combinations, only 43 (36.1%) had labels that provided convincing clinical validity evidence, whereas 18 (15.1%) provided convincing evidence of clinical utility. Sixty-one labels (51.3%) made recommendations about how clinical decisions should be based on the results of a biomarker test; 36 (30.3%) of these contained convincing clinical utility data. A full description of supporting studies was included in 13 labels (10.9%). Fewer than one-sixth of drug labels contained or referenced convincing evidence of clinical utility of biomarker testing, whereas more than half made recommendations based on biomarker test results. It may be premature to include biomarker testing recommendations in drug labels when convincing data that link testing to patient outcomes do not exist.

Adolescent postabortion groups: risk reduction in a school-based health clinic.

PubMed

Daly, Joan Ziegler; Ziegler, Robert; Goldstein, Donna J

2004-10-01

A short-term postabortion group for adolescents was developed. Three groups were conducted in an adolescent mental health clinic within an urban high school-based health clinic. The clinical group experiences offered the adolescents an opportunity to integrate the experience of pregnancy and the abortion decision into their lives. At follow up, adolescents who participated in th postabortion counseling group indicated that they chose and used a method of birth control, did not repeat an unplanned pregnancy, and remained in high school.

Physician styles of decision-making for a complex condition: Type 2 diabetes with co-morbid mental illness.

PubMed

Trachtenberg, Felicia L; Pober, David M; Welch, Lisa C; McKinlay, John B

Variation in physician decisions may reflect personal styles of decision-making, as opposed to singular clinical actions and these styles may be applied differently depending on patient complexity. The objective of this study is to examine clusters of physician decision-making for type 2 diabetes, overall and in the presence of a mental health co-morbidity. This randomized balanced factorial experiment presented video vignettes of a "patient" with diagnosed, but uncontrolled type 2 diabetes. "Patients" were systematically varied by age, sex, race and co-morbidity (depression, schizophrenia with normal or bizarre affect, eczema as control). Two hundred and fifty-six primary care physicians, balanced by gender and experience level, completed a structured interview about clinical management. Cluster analysis identified 3 styles of diabetes management. "Minimalists" (n=84) performed fewer exams or tests compared to "middle of the road" physicians (n=84). "Interventionists" (n=88) suggested more medications and referrals. A second cluster analysis, without control for co-morbidities, identified an additional cluster of "information seekers" (n=15) who requested more additional information and referrals. Physicians ranking schizophrenia higher than diabetes on their problem list were more likely "minimalists" and none were "interventionists" or "information seekers". Variations in clinical management encompass multiple clinical actions and physicians subtly shift these decision-making styles depending on patient co-morbidities. Physicians' practice styles may help explain persistent differences in patient care. Training and continuing education efforts to encourage physicians to implement evidence-based clinical practice should account for general styles of decision-making and for how physicians process complicating comorbidities.

School-Based Clinics: A Guide for Advocates. Developing Policy Statements, Educating Decision Makers, Enlisting Local Support.

ERIC Educational Resources Information Center

Center for Population Options, Washington, DC.

School-based clinics (SBCs) are comprehensive primary health care facilities located within or on the grounds of middle, junior, or senior high schools. Varying in size and organizational structure, SBCs have emerged as an effective model for advancing adolescent health. They have gained attention because of their potential for treating problems…

A Bridging Opportunities Work-frame to develop mobile applications for clinical decision making

PubMed Central

van Rooij, Tibor; Rix, Serena; Moore, James B; Marsh, Sharon

2015-01-01

Background: Mobile applications (apps) providing clinical decision support (CDS) may show the greatest promise when created by and for frontline clinicians. Our aim was to create a generic model enabling healthcare providers to direct the development of CDS apps. Methods: We combined Change Management with a three-tier information technology architecture to stimulate CDS app development. Results: A Bridging Opportunities Work-frame model was developed. A test case was used to successfully develop an app. Conclusion: Healthcare providers can re-use this globally applicable model to actively create and manage regional decision support applications to translate evidence-based medicine in the use of emerging medication or novel treatment regimens. PMID:28031883

An architecture for a continuous, user-driven, and data-driven application of clinical guidelines and its evaluation.

PubMed

Shalom, Erez; Shahar, Yuval; Lunenfeld, Eitan

2016-02-01

Design, implement, and evaluate a new architecture for realistic continuous guideline (GL)-based decision support, based on a series of requirements that we have identified, such as support for continuous care, for multiple task types, and for data-driven and user-driven modes. We designed and implemented a new continuous GL-based support architecture, PICARD, which accesses a temporal reasoning engine, and provides several different types of application interfaces. We present the new architecture in detail in the current paper. To evaluate the architecture, we first performed a technical evaluation of the PICARD architecture, using 19 simulated scenarios in the preeclampsia/toxemia domain. We then performed a functional evaluation with the help of two domain experts, by generating patient records that simulate 60 decision points from six clinical guideline-based scenarios, lasting from two days to four weeks. Finally, 36 clinicians made manual decisions in half of the scenarios, and had access to the automated GL-based support in the other half. The measures used in all three experiments were correctness and completeness of the decisions relative to the GL. Mean correctness and completeness in the technical evaluation were 1±0.0 and 0.96±0.03 respectively. The functional evaluation produced only several minor comments from the two experts, mostly regarding the output's style; otherwise the system's recommendations were validated. In the clinically oriented evaluation, the 36 clinicians applied manually approximately 41% of the GL's recommended actions. Completeness increased to approximately 93% when using PICARD. Manual correctness was approximately 94.5%, and remained similar when using PICARD; but while 68% of the manual decisions included correct but redundant actions, only 3% of the actions included in decisions made when using PICARD were redundant. The PICARD architecture is technically feasible and is functionally valid, and addresses the realistic continuous GL-based application requirements that we have defined; in particular, the requirement for care over significant time frames. The use of the PICARD architecture in the domain we examined resulted in enhanced completeness and in reduction of redundancies, and is potentially beneficial for general GL-based management of chronic patients. Copyright © 2015 Elsevier Inc. All rights reserved.

Definition of drug-resistant epilepsy: is it evidence based?

PubMed

Wiebe, Samuel

2013-05-01

Clinical case definitions are the cornerstone of clinical communication and of clinical and epidemiologic research. The ramifications of establishing a case definition are extensive, including potentially large changes in epidemiologic estimates of frequency, and decisions for clinical management. Yet, defining a condition entails numerous challenges such as defining the scope and purpose, incorporating the strongest evidence base with clinical expertise, accounting for patients' values, and considering impact on care. The clinical case definition of drug-resistant epilepsy, in addition, must address what constitutes an adequate intervention for an individual drug, what are the outcomes of relevance, what period of observation is sufficient to determine success or failure, how many medications should be tried, whether seizure frequency should play a role, and what is the role of side effects and tolerability. On the other hand, the principles of evidence-based medicine (EBM) aim at providing a systematic approach to incorporating the best available evidence into the process of clinical decision for individual patients. The case definition of drug-resistant epilepsy proposed by the the International League Against Epilepsy (ILAE) in 2009 is evaluated in terms of the principles of EBM as well as the stated goals of the authors of the definition. Wiley Periodicals, Inc. © 2013 International League Against Epilepsy.

[Physician perspectives on the impact of patient preferences and the role of next-of-kin of patients in evidence-based decision-making: A qualitative interview study from oncology].

PubMed

Salloch, Sabine; Otte, Ina C; Reinacher-Schick, Anke; Vollmann, Jochen

2018-04-01

The impact of patient preferences in evidence-based medicine is a complex issue which touches on theoretical questions as well as medical practice in the clinical context. The interaction between evidence-based recommendations and value-related patient preferences in clinical practice is, however, highly complex and requires not only medical knowledge but social, psychological and communicative competencies on the side of the physician. The multi-layered process of oncology physicians' clinical decision-making was explored in 14 semi-structured interviews with respect to a first diagnosis of a pancreatic adenocarcinoma. A case vignette was used and the Q method ("card sorting") was applied to analyze the influence of different factors (such as evidence, patient preferences and the role of relatives) on physicians' deliberations. Content analysis (Mayring) was performed. The results show that the participating oncologists consider patient preferences as an important guidance which, however, is limited on certain occasions where the physicians assume a leadership role in decision-making. From the interviewees' perspectives, the preferences of the patients' relatives are likewise of high importance because debilitating oncologic treatments can only be carried out if patients have both social and psychological support. There is a need for an ongoing reflection of the physicians' own values and due consideration of the patients' social role within the context of shared decision-making. Copyright © 2018. Published by Elsevier GmbH.

Developing guidelines in low-income and middle-income countries: lessons from Kenya

PubMed Central

English, Mike; Irimu, Grace; Nyamai, Rachel; Were, Fred; Garner, Paul; Opiyo, Newton

2017-01-01

There are few examples of sustained nationally organised, evidence-informed clinical guidelines development processes in Sub-Saharan Africa. We describe the evolution of efforts from 2005 to 2015 to support evidence-informed decision making to guide admission hospital care practices in Kenya. The approach to conduct reviews, present evidence, and structure and promote transparency of consensus-based procedures for making recommendations improved over four distinct rounds of policy making. Efforts to engage important voices extended from government and academia initially to include multiple professional associations, regulators and practitioners. More than 100 people have been engaged in the decision-making process; an increasing number outside the research team has contributed to the conduct of systematic reviews, and 31 clinical policy recommendations has been developed. Recommendations were incorporated into clinical guideline booklets that have been widely disseminated with a popular knowledge and skills training course. Both helped translate evidence into practice. We contend that these efforts have helped improve the use of evidence to inform policy. The systematic reviews, Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approaches and evidence to decision-making process are well understood by clinicians, and the process has helped create a broad community engaged in evidence translation together with a social or professional norm to use evidence in paediatric care in Kenya. Specific sustained efforts should be made to support capacity and evidence-based decision making in other African settings and clinical disciplines. PMID:28584069

Validation workflow for a clinical Bayesian network model in multidisciplinary decision making in head and neck oncology treatment.

PubMed

Cypko, Mario A; Stoehr, Matthaeus; Kozniewski, Marcin; Druzdzel, Marek J; Dietz, Andreas; Berliner, Leonard; Lemke, Heinz U

2017-11-01

Oncological treatment is being increasingly complex, and therefore, decision making in multidisciplinary teams is becoming the key activity in the clinical pathways. The increased complexity is related to the number and variability of possible treatment decisions that may be relevant to a patient. In this paper, we describe validation of a multidisciplinary cancer treatment decision in the clinical domain of head and neck oncology. Probabilistic graphical models and corresponding inference algorithms, in the form of Bayesian networks, can support complex decision-making processes by providing a mathematically reproducible and transparent advice. The quality of BN-based advice depends on the quality of the model. Therefore, it is vital to validate the model before it is applied in practice. For an example BN subnetwork of laryngeal cancer with 303 variables, we evaluated 66 patient records. To validate the model on this dataset, a validation workflow was applied in combination with quantitative and qualitative analyses. In the subsequent analyses, we observed four sources of imprecise predictions: incorrect data, incomplete patient data, outvoting relevant observations, and incorrect model. Finally, the four problems were solved by modifying the data and the model. The presented validation effort is related to the model complexity. For simpler models, the validation workflow is the same, although it may require fewer validation methods. The validation success is related to the model's well-founded knowledge base. The remaining laryngeal cancer model may disclose additional sources of imprecise predictions.

When craft and science collide: Improving therapeutic practices through evidence-based innovations.

PubMed

Justice, Laura M

2010-04-01

Evidence-based practice (EBP) is a model of clinical decision-making that is increasingly being advocated for use in the field of speech-language pathology. With the increased emphasis on scientific evidence as a form of knowledge important to EBP, clinicians may wonder whether their craft-based knowledge (i.e., knowledge derived from theory and practice), remains a legitimate form of knowledge for use in clinician decisions. This article describes forms of knowledge that may be used to address clinical questions, to include both craft and science. Additionally, the steps used when engaging in EBP are described so that clinicians understand when and how craft comes into play. The major premise addressed within this article is that craft is a legitimate form of knowledge and that engagement in EBP requires one to employ craft-based knowledge.

Variation, certainty, evidence, and change in dental education: employing evidence-based dentistry in dental education.

PubMed

Marinho, V C; Richards, D; Niederman, R

2001-05-01

Variation in health care, and more particularly in dental care, was recently chronicled in a Readers Digest investigative report. The conclusions of this report are consistent with sound scientific studies conducted in various areas of health care, including dental care, which demonstrate substantial variation in the care provided to patients. This variation in care parallels the certainty with which clinicians and faculty members often articulate strongly held, but very different opinions. Using a case-based dental scenario, we present systematic evidence-based methods for accessing dental health care information, evaluating this information for validity and importance, and using this information to make informed curricular and clinical decisions. We also discuss barriers inhibiting these systematic approaches to evidence-based clinical decision making and methods for effectively promoting behavior change in health care professionals.

High-Value Consults: A Curriculum to Promote Point-of-Care, Evidence-Based Recommendations.

PubMed

Nandiwada, Deepa Rani; Kohli, Amar; McNamara, Megan; Smith, Kenneth J; Zimmer, Shanta; McNeil, Melissa; Spagnoletti, Carla; Rubio, Doris; Berlacher, Kathryn

2017-10-01

In an era when value-based care is paramount, teaching trainees to explicitly communicate the evidence behind recommendations fosters high-value care (HVC) in the consultation process. To implement an HVC consult curriculum highlighting the need for clear consult questions, evidence-based recommendations to improve consult teaching, clinical decision-making, and the educational value of consults. A pilot curriculum was implemented for residents on cardiology consult electives utilizing faculty and fellows as evidence-based medicine (EBM) coaches. The curriculum included an online module, an EBM teaching point template, EBM presentations on rounds, and "coach" feedback on notes. A total of 15 residents and 4 fellows on cardiology consults participated, and 87% (13 of 15) of residents on consults felt the curriculum was educationally valuable. A total of 80% (72 of 90) of residents on general medicine rotations responded to the survey, and 25 of 72 residents (35%) had a consult with the EBM template. General medicine teams felt the EBM teaching points affected clinical decision-making (48%, 12 of 25) and favored dissemination of the curriculum (90%, 72 of 80). Checklist-guided chart review showed a 22% improvement in evidence-based summaries behind recommendations (7 of 36 precurriculum to 70 of 146 charts postcurriculum, P  = .015). The HVC consult curriculum during a cardiology elective was perceived by residents to influence clinical decision-making and evidence-based recommendations, and was found to be educationally valuable on both parties in the consult process.

The relationship between patient data and pooled clinical management decisions.

PubMed

Ludbrook, G I; O'Loughlin, E J; Corcoran, T B; Grant, C

2013-01-01

A strong relationship between patient data and preoperative clinical decisions could potentially be used to support clinical decisions in preoperative management. The aim of this exploratory study was to determine the relationship between key patient data and pooled clinical opinions on management. In a previous study, panels of anaesthetists compared the quality of computer-assisted patient health assessments with outpatient consultations and made decisions on the need for preoperative tests, no preoperative outpatient assessment, possible postoperative intensive care unit/high dependency unit requirements and aspiration prophylaxis. In the current study, the relationship between patient data and these decisions was examined using binomial logistic regression analysis. Backward stepwise regression was used to identify independent predictors of each decision (at P >0.15), which were then incorporated into a predictive model. The number of factors related to each decision varied: blood picture (four factors), biochemistry (six factors), coagulation studies (three factors), electrocardiography (eight factors), chest X-ray (seven factors), preoperative outpatient assessment (17 factors), intensive care unit requirement (eight factors) and aspiration prophylaxis (one factor). The factor types also varied, but included surgical complexity, age, gender, number of medications or comorbidities, body mass index, hypertension, central nervous system condition, heart disease, sleep apnoea, smoking, persistent pain and stroke. Models based on these relationships usually demonstrated good sensitivity and specificity, with receiver operating characteristics in the following areas under curve: blood picture (0.75), biochemistry (0.86), coagulation studies (0.71), electrocardiography (0.90), chest X-ray (0.85), outpatient assessment (0.85), postoperative intensive care unit requirement (0.88) and aspiration prophylaxis (0.85). These initial results suggest modelling of patient data may have utility supporting clinicians' preoperative decisions.

A programmable rules engine to provide clinical decision support using HTML forms.

PubMed Central

Heusinkveld, J.; Geissbuhler, A.; Sheshelidze, D.; Miller, R.

1999-01-01

The authors have developed a simple method for specifying rules to be applied to information on HTML forms. This approach allows clinical experts, who lack the programming expertise needed to write CGI scripts, to construct and maintain domain-specific knowledge and ordering capabilities within WizOrder, the order-entry and decision support system used at Vanderbilt Hospital. The clinical knowledge base maintainers use HTML editors to create forms and spreadsheet programs for rule entry. A test environment has been developed which uses Netscape to display forms; the production environment displays forms using an embedded browser. Images Figure 1 PMID:10566470

The future in clinical genetics: affective forecasting biases in patient and clinician decision making.

PubMed

Peters, S A; Laham, S M; Pachter, N; Winship, I M

2014-04-01

When clinicians facilitate and patients make decisions about predictive genetic testing, they often base their choices on the predicted emotional consequences of positive and negative test results. Research from psychology and decision making suggests that such predictions may often be biased. Work on affective forecasting-predicting one's future emotional states-shows that people tend to overestimate the impact of (especially negative) emotional events on their well-being; a phenomenon termed the impact bias. In this article, we review the causes and consequences of the impact bias in medical decision making, with a focus on applying such findings to predictive testing in clinical genetics. We also recommend strategies for reducing the impact bias and consider the ethical and practical implications of doing so. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

An Evidence-Based Medicine Approach to Antihyperglycemic Therapy in Diabetes Mellitus to Overcome Overtreatment.

PubMed

Makam, Anil N; Nguyen, Oanh K

2017-01-10

Overtreatment is pervasive in medicine and leads to potential patient harms and excessive costs in health care. Although evidence-based medicine is often derided as practice by rote algorithmic medicine, the appropriate application of key evidence-based medicine principles in clinical decision making is fundamental to preventing overtreatment and promoting high-value, individualized patient-centered care. Specifically, this article discusses the importance of (1) using absolute rather than relative estimates of benefits to inform treatment decisions; (2) considering the time horizon to benefit of treatments; (3) balancing potential harms and benefits; and (4) using shared decision making by physicians to incorporate the patient's values and preferences into treatment decisions. Here, we illustrate the application of these principles to considering the decision of whether or not to recommend intensive glycemic control to patients to minimize microvascular and cardiovascular complications in type 2 diabetes mellitus. Through this lens, this example will illustrate how an evidence-based medicine approach can be used to individualize glycemic goals and prevent overtreatment, and can serve as a template for applying evidence-based medicine to inform treatment decisions for other conditions to optimize health and individualize patient care. © 2017 American Heart Association, Inc.

The Evolution of an Interprofessional Shared Decision-Making Research Program: Reflective Case Study of an Emerging Paradigm

PubMed Central

Menear, Matthew; Stacey, Dawn; Brière, Nathalie; Légaré, France

2016-01-01

Introduction: Healthcare research increasingly focuses on interprofessional collaboration and on shared decision making, but knowledge gaps remain about effective strategies for implementing interprofessional collaboration and shared decision-making together in clinical practice. We used Kuhn’s theory of scientific revolutions to reflect on how an integrated interprofessional shared decision-making approach was developed and implemented over time. Methods: In 2007, an interdisciplinary team initiated a new research program to promote the implementation of an interprofessional shared decision-making approach in clinical settings. For this reflective case study, two new team members analyzed the team’s four projects, six research publications, one unpublished and two published protocols and organized them into recognizable phases according to Kuhn’s theory. Results: The merging of two young disciplines led to challenges characteristic of emerging paradigms. Implementation of interprofessional shared-decision making was hindered by a lack of conceptual clarity, a dearth of theories and models, little methodological guidance, and insufficient evaluation instruments. The team developed a new model, identified new tools, and engaged knowledge users in a theory-based approach to implementation. However, several unresolved challenges remain. Discussion: This reflective case study sheds light on the evolution of interdisciplinary team science. It offers new approaches to implementing emerging knowledge in the clinical context. PMID:28435417

The Evolution of an Interprofessional Shared Decision-Making Research Program: Reflective Case Study of an Emerging Paradigm.

PubMed

Dogba, Maman Joyce; Menear, Matthew; Stacey, Dawn; Brière, Nathalie; Légaré, France

2016-07-19

Healthcare research increasingly focuses on interprofessional collaboration and on shared decision making, but knowledge gaps remain about effective strategies for implementing interprofessional collaboration and shared decision-making together in clinical practice. We used Kuhn's theory of scientific revolutions to reflect on how an integrated interprofessional shared decision-making approach was developed and implemented over time. In 2007, an interdisciplinary team initiated a new research program to promote the implementation of an interprofessional shared decision-making approach in clinical settings. For this reflective case study, two new team members analyzed the team's four projects, six research publications, one unpublished and two published protocols and organized them into recognizable phases according to Kuhn's theory. The merging of two young disciplines led to challenges characteristic of emerging paradigms. Implementation of interprofessional shared-decision making was hindered by a lack of conceptual clarity, a dearth of theories and models, little methodological guidance, and insufficient evaluation instruments. The team developed a new model, identified new tools, and engaged knowledge users in a theory-based approach to implementation. However, several unresolved challenges remain. This reflective case study sheds light on the evolution of interdisciplinary team science. It offers new approaches to implementing emerging knowledge in the clinical context.

The design and implementation of an Interactive Computerised Decision Support Framework (ICDSF) as a strategy to improve nursing students' clinical reasoning skills.

PubMed

Hoffman, Kerry; Dempsey, Jennifer; Levett-Jones, Tracy; Noble, Danielle; Hickey, Noelene; Jeong, Sarah; Hunter, Sharyn; Norton, Carol

2011-08-01

This paper describes the conceptual design and testing of an Interactive Computerised Decision Support Framework (ICDSF) which was constructed to enable student nurses to "think like a nurse." The ICDSF was based on a model of clinical reasoning. Teaching student nurses to reason clinically is important as poor clinical reasoning skills can lead to "failure-to rescue" of deteriorating patients. The framework of the ICDSF was based on nursing concepts to encourage deep learning and transferability of knowledge. The principles of active student participation, situated cognition to solve problems, authenticity, and cognitive rehearsal were used to develop the ICDSF. The ICDSF was designed in such a way that students moved through it in a step-wise fashion and were required to achieve competency at each step before proceeding to the next. The quality of the ICDSF was evaluated using a questionairre survey, students' written comments and student assessment measures on a pilot and the ICDSF. Overall students were highly satisfied with the clinical scenarios of the ICDSF and believed they were an interesting and useful way to engage in authentic clinical learning. They also believed the ICDSF was useful in developing cognitive skills such as clinical reasoning, problem-solving and decision-making. Some reported issues were the need for good technical support and the lack of face to face contact when using e-learning. Some students also believed the ICDSF was less useful than actual clinical placements. Copyright © 2010 Elsevier Ltd. All rights reserved.

Decaying relevance of clinical data towards future decisions in data-driven inpatient clinical order sets.

PubMed

Chen, Jonathan H; Alagappan, Muthuraman; Goldstein, Mary K; Asch, Steven M; Altman, Russ B

2017-06-01

Determine how varying longitudinal historical training data can impact prediction of future clinical decisions. Estimate the "decay rate" of clinical data source relevance. We trained a clinical order recommender system, analogous to Netflix or Amazon's "Customers who bought A also bought B..." product recommenders, based on a tertiary academic hospital's structured electronic health record data. We used this system to predict future (2013) admission orders based on different subsets of historical training data (2009 through 2012), relative to existing human-authored order sets. Predicting future (2013) inpatient orders is more accurate with models trained on just one month of recent (2012) data than with 12 months of older (2009) data (ROC AUC 0.91 vs. 0.88, precision 27% vs. 22%, recall 52% vs. 43%, all P<10 -10 ). Algorithmically learned models from even the older (2009) data was still more effective than existing human-authored order sets (ROC AUC 0.81, precision 16% recall 35%). Training with more longitudinal data (2009-2012) was no better than using only the most recent (2012) data, unless applying a decaying weighting scheme with a "half-life" of data relevance about 4 months. Clinical practice patterns (automatically) learned from electronic health record data can vary substantially across years. Gold standards for clinical decision support are elusive moving targets, reinforcing the need for automated methods that can adapt to evolving information. Prioritizing small amounts of recent data is more effective than using larger amounts of older data towards future clinical predictions. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Beyond evidence-based nursing: tools for practice.

PubMed

Jutel, Annemarie

2008-05-01

This commentary shares my views of evidence-based nursing as a framework for practice, pointing out its limitations and identifying a wider base of appraisal tools required for making good clinical decisions. As the principles of evidence-based nursing take an increasingly greater hold on nursing education, policy and management, it is important to consider the range of other decision-making tools which are subordinated by this approach. This article summarizes nursing's simultaneous reliance on and critique of evidence-based practice (EBP) in a context of inadequate critical reasoning. It then provides an exemplar of the limitations of evidence-based practice and offers an alternative view of important precepts of decision-making. I identify means by which nurses can develop skills to engage in informed and robust critique of practices and their underpinning rationale. Nurses need to be able to locate and assess useful and reliable information for decision-making. This skill is based on a range of tools which include, but also go beyond EBP including: information literacy, humanities, social sciences, public health, statistics, marketing, ethics and much more. This essay prompts nursing managers to reflect upon whether a flurried enthusiasm to adopt EBP neglects other important decision-making skills which provide an even stronger foundation for robust nursing decisions.

From Learning to Decision-Making: A Cross-Sectional Survey of a Clinical Pharmacist-Steered Journal Club

PubMed Central

Ismail, Sherine; Al Khansa, Sara; Aseeri, Mohammed; Alhamdan, Hani; Quadri, K. H. Mujtaba

2017-01-01

Journal clubs have been traditionally incorporated into academic training programs to enhance competency in the interpretation of literature. We designed a structured journal club (JC) to improve skills in the interpretation of literature; however, we were not aware of how learners (interns, residents, clinical pharmacists, etc.) would perceive it. We aimed to assess the perception of learners at different levels of pharmacy training. A cross-sectional design was used. A self-administered online survey was emailed to JC attendees from 2010–2014 at King Abdulaziz Medical City, Jeddah, Saudi Arabia. The survey questions included: introduction sessions, topic selection, JC layout, interaction with the moderator, and decision-making skills by clinical pharmacists. The response rate was 58/89 (65%); 52/54 (96%) respondents believed that JC adds to their knowledge in interpreting literature. Topic selection met the core curriculum requirements for credentials exams for 16/36 (44.4%), while 16/22 (73%) presenters had good to excellent interaction with the moderator. JC facilitated decision-making for 10/12 (83%) of clinical pharmacists. The results suggest that clinical pharmacist-steered JC may serve as an effective tool to empower learners at different levels of pharmacy practice, with evidence-based principles for interpretation of literature and guide informed decision-making. PMID:28970415

An evidence-based shared decision making programme on the prevention of myocardial infarction in type 2 diabetes: protocol of a randomised-controlled trial.

PubMed

Buhse, Susanne; Heller, Tabitha; Kasper, Jürgen; Mühlhauser, Ingrid; Müller, Ulrich Alfons; Lehmann, Thomas; Lenz, Matthias

2013-10-19

Lack of patient involvement in decision making has been suggested as one reason for limited treatment success. Concepts such as shared decision making may contribute to high quality healthcare by supporting patients to make informed decisions together with their physicians.A multi-component shared decision making programme on the prevention of heart attack in type 2 diabetes has been developed. It aims at improving the quality of decision-making by providing evidence-based patient information, enhancing patients' knowledge, and supporting them to actively participate in decision-making. In this study the efficacy of the programme is evaluated in the setting of a diabetes clinic. A single blinded randomised-controlled trial is conducted to compare the shared decision making programme with a control-intervention. The intervention consists of an evidence-based patient decision aid on the prevention of myocardial infarction and a corresponding counselling module provided by diabetes educators. Similar in duration and structure, the control-intervention targets nutrition, sports, and stress coping. A total of 154 patients between 40 and 69 years of age with type 2 diabetes and no previous diagnosis of ischaemic heart disease or stroke are enrolled and allocated either to the intervention or the control-intervention. Primary outcome measure is the patients' knowledge on benefits and harms of heart attack prevention captured by a standardised knowledge test. Key secondary outcome measure is the achievement of treatment goals prioritised by the individual patient. Treatment goals refer to statin taking, HbA1c-, blood pressure levels and smoking status. Outcomes are assessed directly after the counselling and at 6 months follow-up. Analyses will be carried out on intention-to-treat basis. Concurrent qualitative methods are used to explore intervention fidelity and to gain insight into implementation processes. Interventions to facilitate evidence-based shared decision making represent an innovative approach in diabetes care. The results of this study will provide information on the efficacy of such a concept in the setting of a diabetes clinic in Germany. ISRCTN84636255.

The utility of observational studies in clinical decision making: lessons learned from statin trials.

PubMed

Foody, JoAnne M; Mendys, Phillip M; Liu, Larry Z; Simpson, Ross J

2010-05-01

Contemporary clinical decision making is well supported by a wide variety of information sources, including clinical practice guidelines, position papers, and insights from randomized controlled trials (RCTs). Much of our fundamental understanding of cardiovascular risk factors is based on multiple observations from major epidemiologic studies, such as The Seven Country Studies and the US-based Framingham Heart Study. These studies provided the framework for the development of clinical practice guidelines, including the National Cholesterol Education Program Adult Treatment Panel series. The objective of this article is to highlight the value of observational studies as a complement to clinical trial data for clinical decision making in real-world practice. Although RCTs are still the benchmark for assessing clinical efficacy and safety of a specific therapeutic approach, they may be of limited utility to practitioners who must then adapt the lessons learned from the trial into the patient care environment. The use of well-structured observational studies can improve our understanding of the translation of clinical trials into clinical practice, as demonstrated here with the example of statins. Although such studies have their own limitations, improved techniques for design and analysis have reduced the impact of bias and confounders. The introduction of the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines has provided more uniformity for such studies. When used together with RCTs, observational studies can enhance our understanding of effectiveness and utility in real-world clinical practice. In the examples of statin observational studies, the results suggest that relative effectiveness of different statins and potential impact of switching statins should be carefully considered in treating individual patients by practicing physicians.

Knowledge translation of the American College of Emergency Physicians' clinical policy on syncope using computerized clinical decision support.

PubMed

Melnick, Edward R; Genes, Nicholas G; Chawla, Neal K; Akerman, Meredith; Baumlin, Kevin M; Jagoda, Andy

2010-06-01

To influence physician practice behavior after implementation of a computerized clinical decision support system (CDSS) based upon the recommendations from the 2007 ACEP Clinical Policy on Syncope. This was a pre-post intervention with a prospective cohort and retrospective controls. We conducted a medical chart review of consecutive adult patients with syncope. A computerized CDSS prompting physicians to explain their decision-making regarding imaging and admission in syncope patients based upon ACEP Clinical Policy recommendations was embedded into the emergency department information system (EDIS). The medical records of 410 consecutive adult patients presenting with syncope were reviewed prior to implementation, and 301 records were reviewed after implementation. Primary outcomes were physician practice behavior demonstrated by admission rate and rate of head computed tomography (CT) imaging before and after implementation. There was a significant difference in admission rate pre- and post-intervention (68.1% vs. 60.5% respectively, p = 0.036). There was no significant difference in the head CT imaging rate pre- and post-intervention (39.8% vs. 43.2%, p = 0.358). There were seven physicians who saw ten or more patients during the pre- and post-intervention. Subset analysis of these seven physicians' practice behavior revealed a slight significant difference in the admission rate pre- and post-intervention (74.3% vs. 63.9%, p = 0.0495) and no significant difference in the head CT scan rate pre- and post-intervention (42.9% vs. 45.4%, p = 0.660). The introduction of an evidence-based CDSS based upon ACEP Clinical Policy recommendations on syncope correlated with a change in physician practice behavior in an urban academic emergency department. This change suggests emergency medicine clinical practice guideline recommendations can be incorporated into the physician workflow of an EDIS to enhance the quality of practice.

Empowering occupational therapists to become evidence-based work rehabilitation practitioners.

PubMed

Vachon, Brigitte; Durand, Marie-José; LeBlanc, Jeannette

2010-01-01

Occupational therapists (OTs) engage in continuing education to integrate best available knowledge and skills into their practice. However, many barriers influence the degree to which they are currently able to integrate research evidence into their clinical decision making process. The specific objectives were to explore the clinical decision-making processes they used, and to describe the empowerment process they developed to become evidence-based practitioners. Eight OTs, who had attended a four-day workshop on evidence-based work rehabilitation, were recruited to participate to a reflective practice group. A collaborative research methodology was used. The group was convened for 12 meetings and held during a 15-month period. The data collected was analyzed using the grounded theory method. The results revealed the different decision-making modes used by OTs: defensive, repressed, cautious, autonomous intuitive and autonomous thoughtful. These modes influenced utilization of evidence and determined the stances taken toward practice change. Reflective learning facilitated their utilization of an evidence-based practice model through a three-level empowerment process: deliberateness, client-centeredness and system mindedness. During the course of this study, participants learned to become evidence-based practitioners. This process had an impact on how they viewed their clients, their practice and the work rehabilitation system.

Effort-Based Decision Making in Schizophrenia: Evaluation of Paradigms to Measure Motivational Deficits.

PubMed

Green, Michael F; Horan, William P

2015-09-01

Effort-based decision making requires one to decide how much effort to expend for a certain amount of reward. As the amount of reward goes up most people are willing to exert more effort. This relationship between reward level and effort expenditure can be measured in specialized performance-based tasks that have only recently been applied to schizophrenia. Such tasks provide a way to measure objectively motivational deficits in schizophrenia, which now are only assessed with clinical interviews of negative symptoms. The articles in this theme provide reviews of the relevant animal and human literatures (first 2 articles), and then a psychometric evaluation of 5 effort-based decision making paradigms (last 2 articles). This theme section is intended to stimulate interest in this emerging area among basic scientists developing paradigms for preclinical studies, human experimentalists trying to disentangle factors that contribute to performance on effort-based tasks, and investigators looking for objective endpoints for clinical trials of negative symptoms in schizophrenia. © The Author 2015. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Sideline coverage: when to get radiographs? A review of clinical decision tools.

PubMed

Gould, Sara J; Cardone, Dennis A; Munyak, John; Underwood, Philipp J; Gould, Stephen A

2014-05-01

Sidelines coverage presents unique challenges in the evaluation of injured athletes. Health care providers may be confronted with the question of when to obtain radiographs following an injury. Given that most sidelines coverage occurs outside the elite level, radiographs are not readily available at the time of injury, and the decision of when to send a player for radiographs must be made based on physical examination. Clinical tools have been developed to aid in identifying injuries that are likely to result in radiographically important fractures or dislocations. A search for the keywords x-ray and decision rule along with the anatomic locations shoulder, elbow, wrist, knee, and ankle was performed using the PubMed database. No limits were set regarding year of publication. We selected meta-analyses, randomized controlled trials, and survey results. Our selection focused on the largest, most well-studied published reports. We also attempted to include studies that reported the application of the rules to the field of sports medicine. Retrospective literature review. Level 4. The Ottawa Foot and Ankle Rules have been validated and implemented and are appropriate for use in both pediatric and adult populations. The Ottawa Knee Rules have been widely studied, validated, and accepted for evaluation of knee injuries. There are promising studies of decision rules for clinically important fractures of the wrist, but these studies have not been validated. The elbow has been evaluated with good outcomes via the elbow extension test, which has been validated in both single and multicenter studies. Currently, there are no reliable clinical decision tools for traumatic sports injuries to the shoulder to aid in the decision of when to obtain radiographs. Clinical decision tools have been developed to aid in the diagnosis and management of injuries commonly sustained during sporting events. Tools that have been appropriately validated in populations outside the initial study population can assist sports medicine physicians in the decision of when to get radiographs from the sidelines.

Impact of gender on the decision to participate in a clinical trial: a cross-sectional study.

PubMed

Lobato, Lucas; Bethony, Jeffrey Michael; Pereira, Fernanda Bicalho; Grahek, Shannon Lee; Diemert, David; Gazzinelli, Maria Flávia

2014-11-06

In order for Informed Consent to be ethical and valid each clinical trial participant must be able to make a voluntary decision to participate, free from pressure or coercion. Nonetheless, many factors may influence the decision reached, and such influences may be different for male and female volunteers. Being aware of these differences may help researches develop better processes for obtaining consent that safeguard the right of autonomy for all participants. The goal of this study was to evaluate potential gender-based differences in the factors influencing clinical trial participation. This cross-sectional study was conducted in the Northeast region of Minas Gerais, Brazil, in October 2011. A structured questionnaire was administered to 143 volunteers (48 male, 95 female) screened for participation in a clinical study of an investigational functional food with potential anthelminthic properties. Answers regarding their decision to participate in the study were compared, by gender, using chi-square and Mann Whitney tests. Odds ratios (OR) was used to measure association. A majority of subjects (58% of males, 59% of females) listed the desire to collaborate with the development of a product against parasitic worms as their main reason for participation. Females were significantly more likely to report a decision influenced by friends, family, or researchers (OR 3.14, 3.45, and 3.46 respectively, p < 0.005). Females were also significantly more likely to report a decision influenced by general altruistic considerations (OR 8.45, p < 0.005). There was no difference, by gender, in the report of decisions influenced by informational meetings, understanding of the disease, or the availability of medical treatments or exams. There was also no difference in knowledge of the rights of research participants. Study results indicate that there is a strong difference between male and female participants regarding social influences on the decision to participate in clinical research. Further research into the impact this may have on autonomy is warranted.

Colorectal cancer patients' attitudes towards involvement in decision making.

PubMed

Beaver, Kinta; Campbell, Malcolm; Craven, Olive; Jones, David; Luker, Karen A; Susnerwala, Shabbir S

2009-03-01

To design and administer an attitude rating scale, exploring colorectal cancer patients' views of involvement in decision making. To examine the impact of socio-demographic and/or treatment-related factors on decision making. To conduct principal components analysis to determine if the scale could be simplified into a number of factors for future clinical utility. An attitude rating scale was constructed based on previous qualitative work and administered to colorectal cancer patients using a cross-sectional survey approach. 375 questionnaires were returned (81.7% response). For patients it was important to be informed and involved in the decision-making process. Information was not always used to make decisions as patients placed their trust in medical expertise. Women had more positive opinions on decision making and were more likely to want to make decisions. Written information was understood to a greater degree than verbal information. The scale could be simplified to a number of factors, indicating clinical utility. Few studies have explored the attitudes of colorectal cancer patients towards involvement in decision making. This study presents new insights into how patients view the concept of participation; important when considering current policy imperatives in the UK of involving service users in all aspects of care and treatment.

Description and status update on GELLO: a proposed standardized object-oriented expression language for clinical decision support.

PubMed

Sordo, Margarita; Boxwala, Aziz A; Ogunyemi, Omolola; Greenes, Robert A

2004-01-01

A major obstacle to sharing computable clinical knowledge is the lack of a common language for specifying expressions and criteria. Such a language could be used to specify decision criteria, formulae, and constraints on data and action. Al-though the Arden Syntax addresses this problem for clinical rules, its generalization to HL7's object-oriented data model is limited. The GELLO Expression language is an object-oriented language used for expressing logical conditions and computations in the GLIF3 (GuideLine Interchange Format, v. 3) guideline modeling language. It has been further developed under the auspices of the HL7 Clinical Decision Support Technical Committee, as a proposed HL7 standard., GELLO is based on the Object Constraint Language (OCL), because it is vendor-independent, object-oriented, and side-effect-free. GELLO expects an object-oriented data model. Although choice of model is arbitrary, standardization is facilitated by ensuring that the data model is compatible with the HL7 Reference Information Model (RIM).

Heart failure analysis dashboard for patient's remote monitoring combining multiple artificial intelligence technologies.

PubMed

Guidi, G; Pettenati, M C; Miniati, R; Iadanza, E

2012-01-01

In this paper we describe an Heart Failure analysis Dashboard that, combined with a handy device for the automatic acquisition of a set of patient's clinical parameters, allows to support telemonitoring functions. The Dashboard's intelligent core is a Computer Decision Support System designed to assist the clinical decision of non-specialist caring personnel, and it is based on three functional parts: Diagnosis, Prognosis, and Follow-up management. Four Artificial Intelligence-based techniques are compared for providing diagnosis function: a Neural Network, a Support Vector Machine, a Classification Tree and a Fuzzy Expert System whose rules are produced by a Genetic Algorithm. State of the art algorithms are used to support a score-based prognosis function. The patient's Follow-up is used to refine the diagnosis.

A clinical decision rule to prioritize polysomnography in patients with suspected sleep apnea.

PubMed

Rodsutti, Julvit; Hensley, Michael; Thakkinstian, Ammarin; D'Este, Catherine; Attia, John

2004-06-15

To derive and validate a clinical decision rule that can help to prioritize patients who are on waiting lists for polysomnography, Prospective data collection on consecutive patients referred to a sleep center. The Newcastle Sleep Disorders Centre, University of Newcastle, NSW, Australia. Consecutive adult patients who had been scheduled for initial diagnostic polysomnography. Eight hundred and thirty-seven patients were used for derivation of the decision rule. An apnea-hypopnoea index of at least 5 was used as the cutoff point to diagnose sleep apnea. Fifteen clinical features were included in the analyses using logistic regression to construct a model from the derivation data set. Only 5 variables--age, sex, body mass index, snoring, and stopping breathing during sleep--were significantly associated with sleep apnea. A scoring scheme based on regression coefficients was developed, and the total score was trichotomized into low-, moderate-, and high-risk groups with prevalence of sleep apnea of 8%, 51%, and 82%, respectively. Color-coded tables were developed for ease of use. The clinical decision rule was validated on a separate set of 243 patients. Receiver operating characteristic analysis confirmed that the decision rule performed well, with the area under the curve being similar for both the derivation and validation sets: 0.81 and 0.79, P =.612. We conclude that this decision rule was able to accurately classify the risk of sleep apnea and will be useful for prioritizing patients with suspected sleep apnea who are on waiting lists for polysomnography.

Intraoperative Clinical Decision Support for Anesthesia: A Narrative Review of Available Systems.

PubMed

Nair, Bala G; Gabel, Eilon; Hofer, Ira; Schwid, Howard A; Cannesson, Maxime

2017-02-01

With increasing adoption of anesthesia information management systems (AIMS), there is growing interest in utilizing AIMS data for intraoperative clinical decision support (CDS). CDS for anesthesia has the potential for improving quality of care, patient safety, billing, and compliance. Intraoperative CDS can range from passive and post hoc systems to active real-time systems that can detect ongoing clinical issues and deviations from best practice care. Real-time CDS holds the most promise because real-time alerts and guidance can drive provider behavior toward evidence-based standardized care during the ongoing case. In this review, we describe the different types of intraoperative CDS systems with specific emphasis on real-time systems. The technical considerations in developing and implementing real-time CDS are systematically covered. This includes the functional modules of a CDS system, development and execution of decision rules, and modalities to alert anesthesia providers concerning clinical issues. We also describe the regulatory aspects that affect development, implementation, and use of intraoperative CDS. Methods and measures to assess the effectiveness of intraoperative CDS are discussed. Last, we outline areas of future development of intraoperative CDS, particularly the possibility of providing predictive and prescriptive decision support.

[A computerised clinical decision-support system for the management of depression in Primary Care].

PubMed

Aragonès, Enric; Comín, Eva; Cavero, Myriam; Pérez, Víctor; Molina, Cristina; Palao, Diego

Despite its clinical relevance and its importance as a public health problem, there are major gaps in the management of depression. Evidence-based clinical guidelines are useful to improve processes and clinical outcomes. In order to make their implementation easier these guidelines have been transformed into computerised clinical decision support systems. In this article, a description is presented on the basics and characteristics of a new computerised clinical guideline for the management of major depression, developed in the public health system in Catalonia. This tool helps the clinician to establish reliable and accurate diagnoses of depression, to choose the best treatment a priori according to the disease and the patient characteristics. It also emphasises the importance of systematic monitoring to assess the clinical course, and to adjust therapeutic interventions to the patient's needs at all times. Copyright © 2016 Elsevier España, S.L.U. All rights reserved.

Dual Processing Model for Medical Decision-Making: An Extension to Diagnostic Testing

PubMed Central

Tsalatsanis, Athanasios; Hozo, Iztok; Kumar, Ambuj; Djulbegovic, Benjamin

2015-01-01

Dual Processing Theories (DPT) assume that human cognition is governed by two distinct types of processes typically referred to as type 1 (intuitive) and type 2 (deliberative). Based on DPT we have derived a Dual Processing Model (DPM) to describe and explain therapeutic medical decision-making. The DPM model indicates that doctors decide to treat when treatment benefits outweigh its harms, which occurs when the probability of the disease is greater than the so called “threshold probability” at which treatment benefits are equal to treatment harms. Here we extend our work to include a wider class of decision problems that involve diagnostic testing. We illustrate applicability of the proposed model in a typical clinical scenario considering the management of a patient with prostate cancer. To that end, we calculate and compare two types of decision-thresholds: one that adheres to expected utility theory (EUT) and the second according to DPM. Our results showed that the decisions to administer a diagnostic test could be better explained using the DPM threshold. This is because such decisions depend on objective evidence of test/treatment benefits and harms as well as type 1 cognition of benefits and harms, which are not considered under EUT. Given that type 1 processes are unique to each decision-maker, this means that the DPM threshold will vary among different individuals. We also showed that when type 1 processes exclusively dominate decisions, ordering a diagnostic test does not affect a decision; the decision is based on the assessment of benefits and harms of treatment. These findings could explain variations in the treatment and diagnostic patterns documented in today’s clinical practice. PMID:26244571

Patients’ priorities for treatment decision making during periods of incapacity: quantitative survey

PubMed Central

RID, ANNETTE; WESLEY, ROBERT; PAVLICK, MARK; MAYNARD, SHARON; ROTH, KATALIN; WENDLER, DAVID

2017-01-01

Objective Clinical practice aims to respect patient autonomy by basing treatment decisions for incapacitated patients on their own preferences. Yet many patients do not complete an advance directive, and those who do frequently just designate a family member to make decisions for them. This finding raises the concern that clinical practice may be based on a mistaken understanding of patient priorities. The present study aimed to collect systematic data on how patients prioritize the goals of treatment decision making. Method We employed a self-administered, quantitative survey of patients in a tertiary care center. Results Some 80% or more of the 1169 respondents (response rate = 59.8%) ranked six of eight listed goals for treatment decision making as important. When asked which goal was most important, 38.8% identified obtaining desired or avoiding unwanted treatments, 20.0% identified minimizing stress or financial burden on their family, and 14.6% identified having their family help to make treatment decisions. No single goal was designated as most important by 25.0% of participants. Significance of Results Patients endorsed three primary goals with respect to decision making during periods of incapacity: being treated consistent with their own preferences; minimizing the burden on their family; and involving their family in the decision-making process. However, no single goal was prioritized by a clear majority of patients. These findings suggest that advance care planning should not be limited to documenting patients’ treatment preferences. Clinicians should also discuss and document patients’ priorities for how decisions are to be made. Moreover, future research should evaluate ways to modify current practice to promote all three of patients primary goals for treatment decision making. PMID:25273677

Dual Processing Model for Medical Decision-Making: An Extension to Diagnostic Testing.

PubMed

Tsalatsanis, Athanasios; Hozo, Iztok; Kumar, Ambuj; Djulbegovic, Benjamin

2015-01-01

Dual Processing Theories (DPT) assume that human cognition is governed by two distinct types of processes typically referred to as type 1 (intuitive) and type 2 (deliberative). Based on DPT we have derived a Dual Processing Model (DPM) to describe and explain therapeutic medical decision-making. The DPM model indicates that doctors decide to treat when treatment benefits outweigh its harms, which occurs when the probability of the disease is greater than the so called "threshold probability" at which treatment benefits are equal to treatment harms. Here we extend our work to include a wider class of decision problems that involve diagnostic testing. We illustrate applicability of the proposed model in a typical clinical scenario considering the management of a patient with prostate cancer. To that end, we calculate and compare two types of decision-thresholds: one that adheres to expected utility theory (EUT) and the second according to DPM. Our results showed that the decisions to administer a diagnostic test could be better explained using the DPM threshold. This is because such decisions depend on objective evidence of test/treatment benefits and harms as well as type 1 cognition of benefits and harms, which are not considered under EUT. Given that type 1 processes are unique to each decision-maker, this means that the DPM threshold will vary among different individuals. We also showed that when type 1 processes exclusively dominate decisions, ordering a diagnostic test does not affect a decision; the decision is based on the assessment of benefits and harms of treatment. These findings could explain variations in the treatment and diagnostic patterns documented in today's clinical practice.

Patterns of out-of-home placement decision-making in child welfare.

PubMed

Chor, Ka Ho Brian; McClelland, Gary M; Weiner, Dana A; Jordan, Neil; Lyons, John S

2013-10-01

Out-of-home placement decision-making in child welfare is founded on the best interest of the child in the least restrictive setting. After a child is removed from home, however, little is known about the mechanism of placement decision-making. This study aims to systematically examine the patterns of out-of-home placement decisions made in a state's child welfare system by comparing two models of placement decision-making: a multidisciplinary team decision-making model and a clinically based decision support algorithm. Based on records of 7816 placement decisions representing 6096 children over a 4-year period, hierarchical log-linear modeling characterized concordance or agreement, and discordance or disagreement when comparing the two models and accounting for age-appropriate placement options. Children aged below 16 had an overall concordance rate of 55.7%, most apparent in the least restrictive (20.4%) and the most restrictive placement (18.4%). Older youth showed greater discordant distributions (62.9%). Log-linear analysis confirmed the overall robustness of concordance (odd ratios [ORs] range: 2.9-442.0), though discordance was most evident from small deviations from the decision support algorithm, such as one-level under-placement in group home (OR=5.3) and one-level over-placement in residential treatment center (OR=4.8). Concordance should be further explored using child-level clinical and placement stability outcomes. Discordance might be explained by dynamic factors such as availability of placements, caregiver preferences, or policy changes and could be justified by positive child-level outcomes. Empirical placement decision-making is critical to a child's journey in child welfare and should be continuously improved to effect positive child welfare outcomes. Copyright © 2013 Elsevier Ltd. All rights reserved.

Patients' priorities for treatment decision making during periods of incapacity: quantitative survey.

PubMed

Rid, Annette; Wesley, Robert; Pavlick, Mark; Maynard, Sharon; Roth, Katalin; Wendler, David

2015-10-01

Clinical practice aims to respect patient autonomy by basing treatment decisions for incapacitated patients on their own preferences. Yet many patients do not complete an advance directive, and those who do frequently just designate a family member to make decisions for them. This finding raises the concern that clinical practice may be based on a mistaken understanding of patient priorities. The present study aimed to collect systematic data on how patients prioritize the goals of treatment decision making. We employed a self-administered, quantitative survey of patients in a tertiary care center. Some 80% or more of the 1169 respondents (response rate = 59.8%) ranked six of eight listed goals for treatment decision making as important. When asked which goal was most important, 38.8% identified obtaining desired or avoiding unwanted treatments, 20.0% identified minimizing stress or financial burden on their family, and 14.6% identified having their family help to make treatment decisions. No single goal was designated as most important by 25.0% of participants. Patients endorsed three primary goals with respect to decision making during periods of incapacity: being treated consistent with their own preferences; minimizing the burden on their family; and involving their family in the decision-making process. However, no single goal was prioritized by a clear majority of patients. These findings suggest that advance care planning should not be limited to documenting patients' treatment preferences. Clinicians should also discuss and document patients' priorities for how decisions are to be made. Moreover, future research should evaluate ways to modify current practice to promote all three of patients primary goals for treatment decision making.

Towards generic online multicriteria decision support in patient-centred health care.

PubMed

Dowie, Jack; Kjer Kaltoft, Mette; Salkeld, Glenn; Cunich, Michelle

2015-10-01

To introduce a new online generic decision support system based on multicriteria decision analysis (MCDA), implemented in practical and user-friendly software (Annalisa©). All parties in health care lack a simple and generic way to picture and process the decisions to be made in pursuit of improved decision making and more informed choice within an overall philosophy of person- and patient-centred care. The MCDA-based system generates patient-specific clinical guidance in the form of an opinion as to the merits of the alternative options in a decision, which are all scored and ranked. The scores for each option combine, in a simple expected value calculation, the best estimates available now for the performance of those options on patient-determined criteria, with the individual patient's preferences, expressed as importance weightings for those criteria. The survey software within which the Annalisa file is embedded (Elicia©) customizes and personalizes the presentation and inputs. Principles relevant to the development of such decision-specific MCDA-based aids are noted and comparisons with alternative implementations presented. The necessity to trade-off practicality (including resource constraints) with normative rigour and empirical complexity, in both their development and delivery, is emphasized. The MCDA-/Annalisa-based decision support system represents a prescriptive addition to the portfolio of decision-aiding tools available online to individuals and clinicians interested in pursuing shared decision making and informed choice within a commitment to transparency in relation to both the evidence and preference bases of decisions. Some empirical data establishing its usability are provided. © 2013 The Authors. Health Expectations published by John Wiley & Sons Ltd.

[Application of pharmacoeconomics in clinical management].

PubMed

Amat Díaz, M; Poveda Andrés, J L; Carrera-Hueso, F J

2011-05-01

The present article discusses the importance of clinical management in the transformation of organizations and its role in the daily activities of health professionals and, in particular, of hospital pharmacists. Because of social changes, healthcare models must make the shift from more rigid management models toward new organizational models based on clinical management. From this perspective, pharmacoeconomics is viewed as a useful tool to introduce the criteria of efficiency in all decisions subject to clinical management, including those on pharmacotherapeutics. Subsequently, the application of this discipline is discussed in real decision-making scenarios and settings for its use within the context of the work of hospital pharmacy are proposed. Copyright © 2011 Sociedad Española de Farmacia Hospitalaria. Published by Elsevier Espana. All rights reserved.

Design of a randomized clinical trial of a colorectal cancer screening decision aid to promote appropriate screening in community-dwelling older adults.

PubMed

Kistler, Christine E; Golin, Carol; Morris, Carolyn; Dalton, Alexandra F; Harris, Russell P; Dolor, Rowena; Ferrari, Renée M; Brewer, Noel T; Lewis, Carmen L

2017-12-01

Appropriate colorectal cancer screening in older adults should be aligned with the likelihood of net benefit. In general, patient decision aids improve knowledge and values clarity, but in older adults, they may also help patients identify their individual likelihood of benefit and foster individualized decision-making. We report on the design of a randomized clinical trial to understand the effects of a patient decision aid on appropriate colorectal cancer screening. This report includes a description of the baseline characteristics of participants. English-speaking primary care patients aged 70-84 years who were not currently up to date with screening were recruited into a randomized clinical trial comparing a tailored colorectal cancer screening decision aid with an attention control. The intervention group received a decision aid that included a values clarification exercise and individualized decision-making worksheet, while the control group received an educational pamphlet on safe driving behaviors. The primary outcome was appropriate screening at 6 months based on chart review. We used a composite measure to define appropriate screening as screening for participants in good health, a discussion about screening for patients in intermediate health, and no screening for patients in poor health. Health state was objectively determined using patients' Charlson Comorbidity Index score and age. A total of 14 practices in central North Carolina participated as part of a practice-based research network. In total, 424 patients were recruited to participate and completed a baseline visit. Overall, 79% of participants were White and 58% female, with a mean age of 76.8 years. Patient characteristics between groups were similar by age, gender, race, education, insurance coverage, or work status. Overall, 70% had some college education or more, 57% were married, and virtually all had Medicare insurance (90%). The three primary medical conditions among the cohort were a history of diabetes, pneumonia, and cancer (28%, 26%, and 21%, respectively). We designed a randomized clinical trial to test a novel use of a patient decision aid to promote appropriate colorectal cancer screening and have recruited a diverse study population that seems similar between the intervention and control groups. The study should be able to determine the ability of a patient decision aid to increase individualized and appropriate colorectal cancer screening.

Evidence Based Medicine – New Approaches and Challenges

PubMed Central

Masic, Izet; Miokovic, Milan; Muhamedagic, Belma

2008-01-01

CONFLICT OF INTEREST: NONE DECLARED Evidence based medicine (EBM) is the conscientious, explicit, judicious and reasonable use of modern, best evidence in making decisions about the care of individual patients. EBM integrates clinical experience and patient values with the best available research information. It is a movement which aims to increase the use of high quality clinical research in clinical decision making. EBM requires new skills of the clinician, including efficient literature-searching, and the application of formal rules of evidence in evaluating the clinical literature. The practice of evidence-based medicine is a process of lifelong, self-directed, problem-based learning in which caring for one’s own patients creates the need for clinically important information about diagnosis, prognosis, therapy and other clinical and health care issues. It is not “cookbook” with recipes, but its good application brings cost-effective and better health care. The key difference between evidence-based medicine and traditional medicine is not that EBM considers the evidence while the latter does not. Both take evidence into account; however, EBM demands better evidence than has traditionally been used. One of the greatest achievements of evidence-based medicine has been the development of systematic reviews and meta-analyses, methods by which researchers identify multiple studies on a topic, separate the best ones and then critically analyze them to come up with a summary of the best available evidence. The EBM-oriented clinicians of tomorrow have three tasks: a) to use evidence summaries in clinical practice; b) to help develop and update selected systematic reviews or evidence-based guidelines in their area of expertise; and c) to enrol patients in studies of treatment, diagnosis and prognosis on which medical practice is based. PMID:24109156

Leveraging Electronic Tablets for General Pediatric Care

PubMed Central

McKee, S.; Dugan, T.M.; Downs, S.M.

2015-01-01

Summary Background We have previously shown that a scan-able paper based interface linked to a computerized clinical decision support system (CDSS) can effectively screen patients in pediatric waiting rooms and support the physician using evidence based care guidelines at the time of clinical encounter. However, the use of scan-able paper based interface has many inherent limitations including lacking real time communication with the CDSS and being prone to human and system errors. An electronic tablet based user interface can not only overcome these limitations, but may also support advanced functionality for clinical and research use. However, use of such devices for pediatric care is not well studied in clinical settings. Objective In this pilot study, we enhance our pediatric CDSS with an electronic tablet based user interface and evaluate it for usability as well as for changes in patient questionnaire completion rates. Methods Child Health Improvement through Computers Leveraging Electronic Tablets or CHICLET is an electronic tablet based user interface. It is developed to augment the existing scan-able paper interface to our CDSS. For the purposes of this study, we deployed CHICLET in one outpatient pediatric clinic. Usability factors for CHICLET were evaluated via caregiver and staff surveys. Results When compared to the scan-able paper based interface, we observed an 18% increase or 30% relative increase in question completion rates using CHICLET. This difference was statistically significant. Caregivers and staff survey results were positive for using CHICLET in clinical environment. Conclusions Electronic tablets are a viable interface for capturing patient self-report in pediatric waiting rooms. We further hypothesize that the use of electronic tablet based interfaces will drive advances in computerized clinical decision support and create opportunities for patient engagement. PMID:25848409

Patient-Provider Communication: Does Electronic Messaging Reduce Incoming Telephone Calls?

PubMed

Dexter, Eve N; Fields, Scott; Rdesinski, Rebecca E; Sachdeva, Bhavaya; Yamashita, Daisuke; Marino, Miguel

2016-01-01

Internet-based patient portals are increasingly being implemented throughout health care organizations to enhance health and optimize communication between patients and health professionals. The decision to adopt a patient portal requires careful examination of the advantages and disadvantages of implementation. This study aims to investigate 1 proposed advantage of implementation: alleviating some of the clinical workload faced by employees. A retrospective time-series analysis of the correlation between the rate of electronic patient-to-provider messages-a common attribute of Internet-based patient portals-and incoming telephone calls. The rate of electronic messages and incoming telephone calls were monitored from February 2009 to June 2014 at 4 economically diverse clinics (a federally qualified health center, a rural health clinic, a community-based clinic, and a university-based clinic) related to 1 university hospital. All 4 clinics showed an increase in the rate of portal use as measured by electronic patient-to-provider messaging during the study period. Electronic patient-to-provider messaging was significantly positively correlated with incoming telephone calls at 2 of the clinics (r = 0.546, P < .001 and r = 0.543, P < .001). The remaining clinics were not significantly correlated but demonstrated a weak positive correlation (r = 0.098, P = .560 and r = 0.069, P = .671). Implementation and increased use of electronic patient-to-provider messaging was associated with increased use of telephone calls in 2 of the study clinics. While practices are increasingly making the decision of whether to implement a patient portal as part of their system of care, it is important that the motivation behind such a change not be based on the idea that it will alleviate clinical workload. © Copyright 2016 by the American Board of Family Medicine.

A prospective, longitudinal study to evaluate the clinical utility of a predictive algorithm that detects risk of opioid use disorder.

PubMed

Brenton, Ashley; Lee, Chee; Lewis, Katrina; Sharma, Maneesh; Kantorovich, Svetlana; Smith, Gregory A; Meshkin, Brian

2018-01-01

The purpose of this study was to determine the clinical utility of an algorithm-based decision tool designed to assess risk associated with opioid use. Specifically, we sought to assess how physicians were using the profile in patient care and how its use affected patient outcomes. A prospective, longitudinal study was conducted to assess the utility of precision medicine testing in 5,397 patients across 100 clinics in the USA. Using a patent-protected, validated algorithm combining specific genetic risk factors with phenotypic traits, patients were categorized into low-, moderate-, and high-risk patients for opioid abuse. Physicians who ordered precision medicine testing were asked to complete patient evaluations and document their actions, decisions, and perceptions regarding the utility of the precision medicine tests. The patient outcomes associated with each treatment action were carefully documented. Physicians used the profile to guide treatment decisions for over half of the patients. Of those, guided treatment decisions for 24.5% of the patients were opioid related, including changing the opioid prescribed, starting an opioid, or titrating a patient off the opioid. Treatment guidance was strongly influenced by profile-predicted opioid use disorder (OUD) risk. Most importantly, patients whose physicians used the profile to guide opioid-related treatment decisions had improved clinical outcomes, including better pain management by medication adjustments, with an average pain decrease of 3.4 points on a scale of 1-10. Patients whose physicians used the profile to guide opioid-related treatment decisions had improved clinical outcomes, as measured by decreased pain levels resulting from better pain management with prescribed medications. The clinical utility of the profile is twofold. It provides clinically actionable recommendations that can be used to 1) prevent OUD through limiting initial opioid prescriptions and 2) reduce pain in patients at low risk of developing OUD.

A prospective, longitudinal study to evaluate the clinical utility of a predictive algorithm that detects risk of opioid use disorder

PubMed Central

Brenton, Ashley; Lee, Chee; Lewis, Katrina; Sharma, Maneesh; Kantorovich, Svetlana; Smith, Gregory A; Meshkin, Brian

2018-01-01

Purpose The purpose of this study was to determine the clinical utility of an algorithm-based decision tool designed to assess risk associated with opioid use. Specifically, we sought to assess how physicians were using the profile in patient care and how its use affected patient outcomes. Patients and methods A prospective, longitudinal study was conducted to assess the utility of precision medicine testing in 5,397 patients across 100 clinics in the USA. Using a patent-protected, validated algorithm combining specific genetic risk factors with phenotypic traits, patients were categorized into low-, moderate-, and high-risk patients for opioid abuse. Physicians who ordered precision medicine testing were asked to complete patient evaluations and document their actions, decisions, and perceptions regarding the utility of the precision medicine tests. The patient outcomes associated with each treatment action were carefully documented. Results Physicians used the profile to guide treatment decisions for over half of the patients. Of those, guided treatment decisions for 24.5% of the patients were opioid related, including changing the opioid prescribed, starting an opioid, or titrating a patient off the opioid. Treatment guidance was strongly influenced by profile-predicted opioid use disorder (OUD) risk. Most importantly, patients whose physicians used the profile to guide opioid-related treatment decisions had improved clinical outcomes, including better pain management by medication adjustments, with an average pain decrease of 3.4 points on a scale of 1–10. Conclusion Patients whose physicians used the profile to guide opioid-related treatment decisions had improved clinical outcomes, as measured by decreased pain levels resulting from better pain management with prescribed medications. The clinical utility of the profile is twofold. It provides clinically actionable recommendations that can be used to 1) prevent OUD through limiting initial opioid prescriptions and 2) reduce pain in patients at low risk of developing OUD. PMID:29379313

Evidence and evidence gaps in therapies of nasal obstruction and rhinosinusitis

PubMed Central

Rotter, Nicole

2016-01-01

Therapeutic decisions in otorhinolaryngology are based on clinical experience, surgical skills, and scientific evidence. Recently, evidence-based therapies have gained increased attention and importance due to their potential to improve the individual patient’s treatment and their potential at the same time to reduce treatment costs. In clinical practice, it is almost impossible to stay ahead of the increasing mass of literature and on the other hand critically assess the presented data. A solid scientific and statistical knowledge as well as a significant amount of spare time are required to detect systematic bias and other errors in study designs, also with respect to assessing whether or not a study should be part of an individual therapeutic decision. Meta-analyses, reviews, and clinical guidelines are, therefore, of increasing importance for evidence-based therapy in clinical practice. This review is an update of the availability of external evidence for the treatment of nasal obstruction and rhinosinusitis. It becomes evident that both groups of diseases differ significantly in the availability of external evidence. Furthermore, it becomes obvious that surgical treatment options are normally based on evidence of significantly lower quality than medical treatment options. PMID:28025606

The IDEA Assessment Tool: Assessing the Reporting, Diagnostic Reasoning, and Decision-Making Skills Demonstrated in Medical Students' Hospital Admission Notes.

PubMed

Baker, Elizabeth A; Ledford, Cynthia H; Fogg, Louis; Way, David P; Park, Yoon Soo

2015-01-01

Construct: Clinical skills are used in the care of patients, including reporting, diagnostic reasoning, and decision-making skills. Written comprehensive new patient admission notes (H&Ps) are a ubiquitous part of student education but are underutilized in the assessment of clinical skills. The interpretive summary, differential diagnosis, explanation of reasoning, and alternatives (IDEA) assessment tool was developed to assess students' clinical skills using written comprehensive new patient admission notes. The validity evidence for assessment of clinical skills using clinical documentation following authentic patient encounters has not been well documented. Diagnostic justification tools and postencounter notes are described in the literature (1,2) but are based on standardized patient encounters. To our knowledge, the IDEA assessment tool is the first published tool that uses medical students' H&Ps to rate students' clinical skills. The IDEA assessment tool is a 15-item instrument that asks evaluators to rate students' reporting, diagnostic reasoning, and decision-making skills based on medical students' new patient admission notes. This study presents validity evidence in support of the IDEA assessment tool using Messick's unified framework, including content (theoretical framework), response process (interrater reliability), internal structure (factor analysis and internal-consistency reliability), and relationship to other variables. Validity evidence is based on results from four studies conducted between 2010 and 2013. First, the factor analysis (2010, n = 216) yielded a three-factor solution, measuring patient story, IDEA, and completeness, with reliabilities of .79, .88, and .79, respectively. Second, an initial interrater reliability study (2010) involving two raters demonstrated fair to moderate consensus (κ = .21-.56, ρ =.42-.79). Third, a second interrater reliability study (2011) with 22 trained raters also demonstrated fair to moderate agreement (intraclass correlations [ICCs] = .29-.67). There was moderate reliability for all three skill domains, including reporting skills (ICC = .53), diagnostic reasoning skills (ICC = .64), and decision-making skills (ICC = .63). Fourth, there was a significant correlation between IDEA rating scores (2010-2013) and final Internal Medicine clerkship grades (r = .24), 95% confidence interval (CI) [.15, .33]. The IDEA assessment tool is a novel tool with validity evidence to support its use in the assessment of students' reporting, diagnostic reasoning, and decision-making skills. The moderate reliability achieved supports formative or lower stakes summative uses rather than high-stakes summative judgments.

Comparing a Mobile Decision Support System Versus the Use of Printed Materials for the Implementation of an Evidence-Based Recommendation: Protocol for a Qualitative Evaluation.

PubMed

Camacho, Jhon; Medina Ch, Ana María; Landis-Lewis, Zach; Douglas, Gerald; Boyce, Richard

2018-04-13

The distribution of printed materials is the most frequently used strategy to disseminate and implement clinical practice guidelines, although several studies have shown that the effectiveness of this approach is modest at best. Nevertheless, there is insufficient evidence to support the use of other strategies. Recent research has shown that the use of computerized decision support presents a promising approach to address some aspects of this problem. The aim of this study is to provide qualitative evidence on the potential effect of mobile decision support systems to facilitate the implementation of evidence-based recommendations included in clinical practice guidelines. We will conduct a qualitative study with two arms to compare the experience of primary care physicians while they try to implement an evidence-based recommendation in their clinical practice. In the first arm, we will provide participants with a printout of the guideline article containing the recommendation, while in the second arm, we will provide participants with a mobile app developed after formalizing the recommendation text into a clinical algorithm. Data will be collected using semistructured and open interviews to explore aspects of behavioral change and technology acceptance involved in the implementation process. The analysis will be comprised of two phases. During the first phase, we will conduct a template analysis to identify barriers and facilitators in each scenario. Then, during the second phase, we will contrast the findings from each arm to propose hypotheses about the potential impact of the system. We have formalized the narrative in the recommendation into a clinical algorithm and have developed a mobile app. Data collection is expected to occur during 2018, with the first phase of analysis running in parallel. The second phase is scheduled to conclude in July 2019. Our study will further the understanding of the role of mobile decision support systems in the implementation of clinical practice guidelines. Furthermore, we will provide qualitative evidence to aid decisions made by low- and middle-income countries' ministries of health about investments in these technologies. ©Jhon Camacho, Ana María Medina Ch, Zach Landis-Lewis, Gerald Douglas, Richard Boyce. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 13.04.2018.

The Development of Delta: Using Agile to Develop a Decision Aid for Pediatric Oncology Clinical Trial Enrollment.

PubMed

Robertson, Eden G; Wakefield, Claire E; Cohn, Richard J; O'Brien, Tracey; Ziegler, David S; Fardell, Joanna E

2018-05-04

The internet is increasingly being used to disseminate health information. Given the complexity of pediatric oncology clinical trials, we developed Delta, a Web-based decision aid to support families deciding whether or not to enroll their child with cancer in a clinical trial. This paper details the Agile development process of Delta and user testing results of Delta. Development was iterative and involved 5 main stages: a requirements analysis, planning, design, development, and user testing. For user testing, we conducted 13 eye-tracking analyses and think-aloud interviews with health care professionals (n=6) and parents (n=7). Results suggested that there was minimal rereading of content and a high level of engagement in content. However, there were some navigational problems. Participants reported high acceptability (12/13) and high usability of the website (8/13). Delta demonstrates the utility for the use of Agile in the development of a Web-based decision aid for health purposes. Our study provides a clear step-by-step guide to develop a Web-based psychosocial tool within the health setting. ©Eden G Robertson, Claire E Wakefield, Richard J Cohn, Tracey O'Brien, David S Ziegler, Joanna E Fardell. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 04.05.2018.

Temporal characteristics of decisions in hospital encounters: a threshold for shared decision making? A qualitative study.

PubMed

Ofstad, Eirik H; Frich, Jan C; Schei, Edvin; Frankel, Richard M; Gulbrandsen, Pål

2014-11-01

To identify and characterize physicians' statements that contained evidence of clinically relevant decisions in encounters with patients in different hospital settings. Qualitative analysis of 50 videotaped encounters from wards, the emergency room (ER) and outpatient clinics in a department of internal medicine at a Norwegian university hospital. Clinical decisions could be grouped in a temporal order: decisions which had already been made, and were brought into the encounter by the physician (preformed decisions), decisions made in the present (here-and-now decisions), and decisions prescribing future actions given a certain course of events (conditional decisions). Preformed decisions were a hallmark in the ward and conditional decisions a main feature of ER encounters. Clinical decisions related to a patient-physician encounter spanned a time frame exceeding the duration of the encounter. While a distribution of decisions over time and space fosters sharing and dilution of responsibility between providers, it makes the decision making process hard to access for patients. In order to plan when and how to involve patients in decisions, physicians need increased awareness of when clinical decisions are made, who usually makes them, and who should make them. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Investigating a self-scoring interview simulation for learning and assessment in the medical consultation.

PubMed

Bruen, Catherine; Kreiter, Clarence; Wade, Vincent; Pawlikowska, Teresa

2017-01-01

Experience with simulated patients supports undergraduate learning of medical consultation skills. Adaptive simulations are being introduced into this environment. The authors investigate whether it can underpin valid and reliable assessment by conducting a generalizability analysis using IT data analytics from the interaction of medical students (in psychiatry) with adaptive simulations to explore the feasibility of adaptive simulations for supporting automated learning and assessment. The generalizability (G) study was focused on two clinically relevant variables: clinical decision points and communication skills. While the G study on the communication skills score yielded low levels of true score variance, the results produced by the decision points, indicating clinical decision-making and confirming user knowledge of the process of the Calgary-Cambridge model of consultation, produced reliability levels similar to what might be expected with rater-based scoring. The findings indicate that adaptive simulations have potential as a teaching and assessment tool for medical consultations.

Decision models in the evaluation of psychotropic drugs : useful tool or useless toy?

PubMed

Barbui, Corrado; Lintas, Camilla

2006-09-01

A current contribution in the European Journal of Health Economics employs a decision model to compare health care costs of olanzapine and risperidone treatment for schizophrenia. The model suggests that a treatment strategy of first-line olanzapine is cost-saving over a 1-year period, with additional clinical benefits in the form of avoided relapses in the long-term. From a clinical perspective this finding is indubitably relevant, but can physicians and policy makers believe it? The study is presented in a balanced way, assumptions are based on data extracted from clinical trials published in major psychiatric journals, and the theoretical underpinnings of the model are reasonable. Despite these positive aspects, we believe that the methodology used in this study-the decision model approach-is an unsuitable and potentially misleading tool for evaluating psychotropic drugs. In this commentary, taking the olanzapine vs. risperidone model as an example, arguments are provided to support this statement.

Comparing the effect of a decision aid plus patient navigation with usual care on colorectal cancer screening completion in vulnerable populations: study protocol for a randomized controlled trial

PubMed Central

2014-01-01

Background Screening can reduce colorectal cancer (CRC) incidence and mortality. However, screening is underutilized in vulnerable patient populations, particularly among Latinos. Patient-directed decision aids can increase CRC screening knowledge, self-efficacy, and intent; however, their effect on actual screening test completion tends to be modest. This is probably because decision aids do not address some of the patient-specific barriers that prevent successful completion of CRC screening in these populations. These individual barriers might be addressed though patient navigation interventions. This study will test a combined decision aid and patient navigator intervention on screening completion in diverse populations of vulnerable primary care patients. Methods/Design We will conduct a multisite, randomized controlled trial with patient-level randomization. Planned enrollment is 300 patients aged 50 to 75 years at average CRC risk presenting for appointments at two primary clinics in North Carolina and New Mexico. Intervention participants will view a video decision aid immediately before the clinic visit. The 14 to 16 minute video presents information about fecal occult blood tests and colonoscopy and will be viewed on a portable computer tablet in English or Spanish. Clinic-based patient navigators are bilingual and bicultural and will provide both face-to-face and telephone-based navigation. Control participants will view an unrelated food safety video and receive usual care. The primary outcome is completion of a CRC screening test at six months. Planned subgroup analyses include examining intervention effectiveness in Latinos, who will be oversampled. Secondarily, the trial will evaluate the intervention effects on knowledge of CRC screening, self-efficacy, intent, and patient-provider communication. The study will also examine whether patient ethnicity, acculturation, language preference, or health insurance status moderate the intervention effect on CRC screening. Discussion This pragmatic randomized controlled trial will test a combined decision aid and patient navigator intervention targeting CRC screening completion. Findings from this trial may inform future interventions and implementation policies designed to promote CRC screening in vulnerable patient populations and to reduce screening disparities. Clinical trial registration ClinicalTrials.gov NCT02054598. PMID:25004983

The laboratory diagnosis of testosterone deficiency.

PubMed

Paduch, Darius A; Brannigan, Robert E; Fuchs, Eugene F; Kim, Edward D; Marmar, Joel L; Sandlow, Jay I

2014-05-01

The evaluation and treatment of hypogonadal men has become an important part of urologic practice. Fatigue, loss of libido, and erectile dysfunction are commonly reported, but nonspecific symptoms and laboratory verification of low testosterone (T) are an important part of evaluation in addition to a detailed history and physical examination. Significant intraindividual fluctuations in serum T levels, biologic variation of T action on end organs, the wide range of T levels in human serum samples, and technical limitations of currently available assays have led to poor reliability of T measurements in the clinical laboratory setting. There is no universally accepted threshold of T concentration that distinguishes eugonadal from hypogonadal men; thus, laboratory results have to be interpreted in the appropriate clinical setting. This review focuses on clinical, biological, and technological challenges that affect serum T measurements to educate clinicians regarding technological advances and limitations of the currently available laboratory methods to diagnose hypogonadism. A collaborative effort led by the American Urological Association between practicing clinicians, patient advocacy groups, government regulatory agencies, industry, and professional societies is underway to provide optimized assay platforms and evidence-based normal assay ranges to guide clinical decision making. Until such standardization is commonplace in clinical laboratories, the decision to treat should be based on the presence of signs and symptoms in addition to serum T measurements. Rigid interpretation of T ranges should not dictate clinical decision making or define coverage of treatment by third party payers. Copyright © 2014 Elsevier Inc. All rights reserved.

Evidence-based medicine in primary care: qualitative study of family physicians

PubMed Central

Tracy, C Shawn; Dantas, Guilherme Coelho; Upshur, Ross EG

2003-01-01

Background The objectives of this study were: a) to examine physician attitudes to and experience of the practice of evidence-based medicine (EBM) in primary care; b) to investigate the influence of patient preferences on clinical decision-making; and c) to explore the role of intuition in family practice. Method Qualitative analysis of semi-structured interviews of 15 family physicians purposively selected from respondents to a national survey on EBM mailed to a random sample of Canadian family physicians. Results Participants mainly welcomed the promotion of EBM in the primary care setting. A significant number of barriers and limitations to the implementation of EBM were identified. EBM is perceived by some physicians as a devaluation of the 'art of medicine' and a threat to their professional/clinical autonomy. Issues regarding the trustworthiness and credibility of evidence were of great concern, especially with respect to the influence of the pharmaceutical industry. Attempts to become more evidence-based often result in the experience of conflicts. Patient factors exert a powerful influence on clinical decision-making and can serve as trumps to research evidence. A widespread belief that intuition plays a vital role in primary care reinforced views that research evidence must be considered alongside other factors such as patient preferences and the clinical judgement and experience of the physician. Discussion Primary care physicians are increasingly keen to consider research evidence in clinical decision-making, but there are significant concerns about the current model of EBM. Our findings support the proposed revisions to EBM wherein greater emphasis is placed on clinical expertise and patient preferences, both of which remain powerful influences on physician behaviour. PMID:12740025

Automatic identification of high impact articles in PubMed to support clinical decision making.

PubMed

Bian, Jiantao; Morid, Mohammad Amin; Jonnalagadda, Siddhartha; Luo, Gang; Del Fiol, Guilherme

2017-09-01

The practice of evidence-based medicine involves integrating the latest best available evidence into patient care decisions. Yet, critical barriers exist for clinicians' retrieval of evidence that is relevant for a particular patient from primary sources such as randomized controlled trials and meta-analyses. To help address those barriers, we investigated machine learning algorithms that find clinical studies with high clinical impact from PubMed®. Our machine learning algorithms use a variety of features including bibliometric features (e.g., citation count), social media attention, journal impact factors, and citation metadata. The algorithms were developed and evaluated with a gold standard composed of 502 high impact clinical studies that are referenced in 11 clinical evidence-based guidelines on the treatment of various diseases. We tested the following hypotheses: (1) our high impact classifier outperforms a state-of-the-art classifier based on citation metadata and citation terms, and PubMed's® relevance sort algorithm; and (2) the performance of our high impact classifier does not decrease significantly after removing proprietary features such as citation count. The mean top 20 precision of our high impact classifier was 34% versus 11% for the state-of-the-art classifier and 4% for PubMed's® relevance sort (p=0.009); and the performance of our high impact classifier did not decrease significantly after removing proprietary features (mean top 20 precision=34% vs. 36%; p=0.085). The high impact classifier, using features such as bibliometrics, social media attention and MEDLINE® metadata, outperformed previous approaches and is a promising alternative to identifying high impact studies for clinical decision support. Copyright © 2017 Elsevier Inc. All rights reserved.

Evaluation of the acceptability and usability of a decision support system to encourage safe and effective use of opioid therapy for chronic, noncancer pain by primary care providers.

PubMed

Trafton, Jodie; Martins, Susana; Michel, Martha; Lewis, Eleanor; Wang, Dan; Combs, Ann; Scates, Naquell; Tu, Samson; Goldstein, Mary K

2010-04-01

To develop and evaluate a clinical decision support system (CDSS) named Assessment and Treatment in Healthcare: Evidenced-Based Automation (ATHENA)-Opioid Therapy, which encourages safe and effective use of opioid therapy for chronic, noncancer pain. CDSS development and iterative evaluation using the analysis, design, development, implementation, and evaluation process including simulation-based and in-clinic assessments of usability for providers followed by targeted system revisions. Volunteers provided detailed feedback to guide improvements in the graphical user interface, and content and design changes to increase clinical usefulness, understandability, clinical workflow fit, and ease of completing guideline recommended practices. Revisions based on feedback increased CDSS usability ratings over time. Practice concerns outside the scope of the CDSS were also identified. Usability testing optimized the CDSS to better address barriers such as lack of provider education, confusion in dosing calculations and titration schedules, access to relevant patient information, provider discontinuity, documentation, and access to validated assessment tools. It also highlighted barriers to good clinical practice that are difficult to address with CDSS technology in its current conceptualization. For example, clinicians indicated that constraints on time and competing priorities in primary care, discomfort in patient-provider communications, and lack of evidence to guide opioid prescribing decisions impeded their ability to provide effective, guideline-adherent pain management. Iterative testing was essential for designing a highly usable and acceptable CDSS; however, identified barriers may limit the impact of the ATHENA-Opioid Therapy system and other CDSS on clinical practices and outcomes unless CDSS are paired with parallel initiatives to address these issues.

Use of Biomarkers to Guide Decisions on Adjuvant Systemic Therapy for Women With Early-Stage Invasive Breast Cancer: American Society of Clinical Oncology Clinical Practice Guideline.

PubMed

Harris, Lyndsay N; Ismaila, Nofisat; McShane, Lisa M; Andre, Fabrice; Collyar, Deborah E; Gonzalez-Angulo, Ana M; Hammond, Elizabeth H; Kuderer, Nicole M; Liu, Minetta C; Mennel, Robert G; Van Poznak, Catherine; Bast, Robert C; Hayes, Daniel F

2016-04-01

To provide recommendations on appropriate use of breast tumor biomarker assay results to guide decisions on adjuvant systemic therapy for women with early-stage invasive breast cancer. A literature search and prospectively defined study selection sought systematic reviews, meta-analyses, randomized controlled trials, prospective-retrospective studies, and prospective comparative observational studies published from 2006 through 2014. Outcomes of interest included overall survival and disease-free or recurrence-free survival. Expert panel members used informal consensus to develop evidence-based guideline recommendations. The literature search identified 50 relevant studies. One randomized clinical trial and 18 prospective-retrospective studies were found to have evaluated the clinical utility, as defined by the guideline, of specific biomarkers for guiding decisions on the need for adjuvant systemic therapy. No studies that met guideline criteria for clinical utility were found to guide choice of specific treatments or regimens. In addition to estrogen and progesterone receptors and human epidermal growth factor receptor 2, the panel found sufficient evidence of clinical utility for the biomarker assays Oncotype DX, EndoPredict, PAM50, Breast Cancer Index, and urokinase plasminogen activator and plasminogen activator inhibitor type 1 in specific subgroups of breast cancer. No biomarker except for estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2 was found to guide choices of specific treatment regimens. Treatment decisions should also consider disease stage, comorbidities, and patient preferences. © 2016 by American Society of Clinical Oncology.

Mental Health Providers' Decision-Making Around the Implementation of Evidence-Based Treatment for PTSD.

PubMed

Osei-Bonsu, Princess E; Bolton, Rendelle E; Wiltsey Stirman, Shannon; Eisen, Susan V; Herz, Lawrence; Pellowe, Maura E

2017-04-01

It is estimated that <15% of veterans with posttraumatic stress disorder (PTSD) have engaged in two evidence-based psychotherapies highly recommended by VA-cognitive processing therapy (CPT) and prolonged exposure (PE). CPT and PE guidelines specify which patients are appropriate, but research suggests that providers may be more selective than the guidelines. In addition, PTSD clinical guidelines encourage "shared decision-making," but there is little research on what processes providers use to make decisions about CPT/PE. Sixteen licensed psychologists and social workers from two VA medical centers working with ≥1 patient with PTSD were interviewed about patient factors considered and decision-making processes for CPT/PE use. Qualitative analyses revealed that patient readiness and comorbid conditions influenced decisions to use or refer patients with PTSD for CPT/PE. Providers reported mentally derived and instances of patient-involved decision-making around CPT/PE use. Continued efforts to assist providers in making informed and collaborative decisions about CPT/PE use are discussed.

[Treatment Decision-Making Process of Cancer Patients].

PubMed

Lee, Shiu-Yu C Katie

2016-10-01

The decision-making process that is used by cancer patients to determine their treatment has become more multi-foci, difficult and complicated in recent years. This has in part been attributed to the increasing incidence rate of cancer in Taiwan and the rapid development of medical technologies and treatment modalities. Oncology nurses must assist patients and family to make informed and value-based treatment decisions. Decision-making is an information process that involves appraising one's own expectation and values based on his/her knowledge on cancer and treatment options. Because cancer treatment involves risks and uncertainties, and impacts quality of life, the treatment decision-making for cancer is often stressful, or even conflicting. This paper discusses the decision-making behaviors of cancer patients and the decisional conflict, participation, and informational needs that are involved in cancer treatment. The trend toward shared decision-making and decisional support will be also explored in order to facilitate the future development of appropriate clinical interventions and research.

Improving Medical Students' Application of Knowledge and Clinical Decision-Making Through a Porcine-Based Integrated Cardiac Basic Science Program.

PubMed

Stott, Martyn Charles; Gooseman, Michael Richard; Briffa, Norman Paul

2016-01-01

Despite the concerted effort of modern undergraduate curriculum designers, the ability to integrate basic sciences in clinical rotations is an ongoing problem in medical education. Students and newly qualified doctors themselves report worry about the effect this has on their clinical performance. There are examples in the literature to support development of attempts at integrating such aspects, but this "vertical integration" has proven to be difficult. We designed an expert-led integrated program using dissection of porcine hearts to improve the use of cardiac basic sciences in clinical medical students' decision-making processes. To our knowledge, this is the first time in the United Kingdom that an animal model has been used to teach undergraduate clinical anatomy to medical students to direct wider application of knowledge. Action research methodology was used to evaluate the local curriculum and assess learners needs, and the agreed teaching outcomes, methods, and delivery outline were established. A total of 18 students in the clinical years of their degree program attended, completing precourse and postcourse multichoice questions examinations and questionnaires to assess learners' development. Student's knowledge scores improved by 17.5% (p = 0.01; students t-test). Students also felt more confident at applying underlying knowledge to decision-making and diagnosis in clinical medicine. An expert teacher (consultant surgeon) was seen as beneficial to students' understanding and appreciation. This study outlines how the development of a teaching intervention using porcine-based methods successfully improved both student's knowledge and application of cardiac basic sciences. We recommend that clinicians fully engage with integrating previously learnt underlying sciences to aid students in developing decision-making and diagnostic skills as well as a deeper approach to learning. Copyright © 2016 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

IBM’s Health Analytics and Clinical Decision Support

PubMed Central

Sun, J.; Knoop, S.; Shabo, A.; Carmeli, B.; Sow, D.; Syed-Mahmood, T.; Rapp, W.

2014-01-01

Summary Objectives This survey explores the role of big data and health analytics developed by IBM in supporting the transformation of healthcare by augmenting evidence-based decision-making. Methods Some problems in healthcare and strategies for change are described. It is argued that change requires better decisions, which, in turn, require better use of the many kinds of healthcare information. Analytic resources that address each of the information challenges are described. Examples of the role of each of the resources are given. Results There are powerful analytic tools that utilize the various kinds of big data in healthcare to help clinicians make more personalized, evidenced-based decisions. Such resources can extract relevant information and provide insights that clinicians can use to make evidence-supported decisions. There are early suggestions that these resources have clinical value. As with all analytic tools, they are limited by the amount and quality of data. Conclusion Big data is an inevitable part of the future of healthcare. There is a compelling need to manage and use big data to make better decisions to support the transformation of healthcare to the personalized, evidence-supported model of the future. Cognitive computing resources are necessary to manage the challenges in employing big data in healthcare. Such tools have been and are being developed. The analytic resources, themselves, do not drive, but support healthcare transformation. PMID:25123736

A method and knowledge base for automated inference of patient problems from structured data in an electronic medical record.

PubMed

Wright, Adam; Pang, Justine; Feblowitz, Joshua C; Maloney, Francine L; Wilcox, Allison R; Ramelson, Harley Z; Schneider, Louise I; Bates, David W

2011-01-01

Accurate knowledge of a patient's medical problems is critical for clinical decision making, quality measurement, research, billing and clinical decision support. Common structured sources of problem information include the patient problem list and billing data; however, these sources are often inaccurate or incomplete. To develop and validate methods of automatically inferring patient problems from clinical and billing data, and to provide a knowledge base for inferring problems. We identified 17 target conditions and designed and validated a set of rules for identifying patient problems based on medications, laboratory results, billing codes, and vital signs. A panel of physicians provided input on a preliminary set of rules. Based on this input, we tested candidate rules on a sample of 100,000 patient records to assess their performance compared to gold standard manual chart review. The physician panel selected a final rule for each condition, which was validated on an independent sample of 100,000 records to assess its accuracy. Seventeen rules were developed for inferring patient problems. Analysis using a validation set of 100,000 randomly selected patients showed high sensitivity (range: 62.8-100.0%) and positive predictive value (range: 79.8-99.6%) for most rules. Overall, the inference rules performed better than using either the problem list or billing data alone. We developed and validated a set of rules for inferring patient problems. These rules have a variety of applications, including clinical decision support, care improvement, augmentation of the problem list, and identification of patients for research cohorts.

The practice of evidence-based medicine involves the care of whole persons.

PubMed

Richardson, W Scott

2017-04-01

In this issue of the Journal, Dr. Fava posits that evidence-based medicine (EBM) was bound to fail. I share some of the concerns he expresses, yet I see more reasons for optimism. Having been on rounds with both Drs. Engel and Sackett, I reckon they would have agreed more than they disagreed. Their central teaching was the compassionate and well-informed care of sick persons. The model that emerged from these rounds was that patient care could be both person-centered and evidence-based, that clinical judgment was essential to both, and the decisions could and should be shared. Both clinicians and patients can bring knowledge from several sources into the shared decision making process in the clinical encounter, including evidence from clinical care research. I thank Dr. Fava for expressing legitimate doubts and providing useful criticism, yet I am cautiously optimistic that the model of EBM described here is robust enough to meet the challenges and is not doomed to fail. Copyright © 2017 Elsevier Inc. All rights reserved.

Healthcare justice and human rights in perinatal medicine.

PubMed

Chervenak, Frank A; McCullough, Laurence B

2016-06-01

This article describes an approach to ethics of perinatal medicine in which "women and children first" plays a central role, based on the concept of healthcare justice. Healthcare justice requires that all patients receive clinical management based on their clinical needs, which are defined by deliberative (evidence-based, rigorous, transparent, and accountable) clinical judgment. All patients in perinatal medicine includes pregnant, fetal, and neonatal patients. Healthcare justice also protects the informed consent process, which is intended to empower the exercise of patient autonomy in the decision-making process about patient care. In the context of healthcare justice, the informed consent process should not be influenced by ethically irrelevant factors. Healthcare justice should be understood as a basis for the human rights to healthcare and to participate in decisions about one's healthcare. Healthcare justice in perinatal medicine creates an essential role for the perinatologist to be an effective advocate for pregnant, fetal, and neonatal patients, i.e., for "women and children first." Copyright © 2016 Elsevier Inc. All rights reserved.

A Clinical Decision Support System Using Ultrasound Textures and Radiologic Features to Distinguish Metastasis From Tumor-Free Cervical Lymph Nodes in Patients With Papillary Thyroid Carcinoma.

PubMed

Abbasian Ardakani, Ali; Reiazi, Reza; Mohammadi, Afshin

2018-03-30

This study investigated the potential of a clinical decision support approach for the classification of metastatic and tumor-free cervical lymph nodes (LNs) in papillary thyroid carcinoma on the basis of radiologic and textural analysis through ultrasound (US) imaging. In this research, 170 metastatic and 170 tumor-free LNs were examined by the proposed clinical decision support method. To discover the difference between the groups, US imaging was used for the extraction of radiologic and textural features. The radiologic features in the B-mode scans included the echogenicity, margin, shape, and presence of microcalcification. To extract the textural features, a wavelet transform was applied. A support vector machine classifier was used to classify the LNs. In the training set data, a combination of radiologic and textural features represented the best performance with sensitivity, specificity, accuracy, and area under the curve (AUC) values of 97.14%, 98.57%, 97.86%, and 0.994, respectively, whereas the classification based on radiologic and textural features alone yielded lower performance, with AUCs of 0.964 and 0.922. On testing the data set, the proposed model could classify the tumor-free and metastatic LNs with an AUC of 0.952, which corresponded to sensitivity, specificity, and accuracy of 93.33%, 96.66%, and 95.00%. The clinical decision support method based on textural and radiologic features has the potential to characterize LNs via 2-dimensional US. Therefore, it can be used as a supplementary technique in daily clinical practice to improve radiologists' understanding of conventional US imaging for characterizing LNs. © 2018 by the American Institute of Ultrasound in Medicine.

Linking data to decision-making: applying qualitative data analysis methods and software to identify mechanisms for using outcomes data.

PubMed

Patel, Vaishali N; Riley, Anne W

2007-10-01

A multiple case study was conducted to examine how staff in child out-of-home care programs used data from an Outcomes Management System (OMS) and other sources to inform decision-making. Data collection consisted of thirty-seven semi-structured interviews with clinicians, managers, and directors from two treatment foster care programs and two residential treatment centers, and individuals involved with developing the OMS; and observations of clinical and quality management meetings. Case study and grounded theory methodology guided analyses. The application of qualitative data analysis software is described. Results show that although staff rarely used data from the OMS, they did rely on other sources of systematically collected information to inform clinical, quality management, and program decisions. Analyses of how staff used these data suggest that improving the utility of OMS will involve encouraging staff to participate in data-based decision-making, and designing and implementing OMS in a manner that reflects how decision-making processes operate.

Answering medical questions at the point of care: a cross-sectional study comparing rapid decisions based on PubMed and Epistemonikos searches with evidence-based recommendations developed with the GRADE approach.

PubMed

Izcovich, Ariel; Criniti, Juan Martín; Popoff, Federico; Ragusa, Martín Alberto; Gigler, Cristel; Gonzalez Malla, Carlos; Clavijo, Manuela; Manzotti, Matias; Diaz, Martín; Catalano, Hugo Norberto; Neumann, Ignacio; Guyatt, Gordon

2017-08-07

Using the best current evidence to inform clinical decisions remains a challenge for clinicians. Given the scarcity of trustworthy clinical practice guidelines providing recommendations to answer clinicians' daily questions, clinical decision support systems (ie, assistance in question identification and answering) emerge as an attractive alternative. The trustworthiness of the recommendations achieved by such systems is unknown. To evaluate the trustworthiness of a question identification and answering system that delivers timely recommendations. Cross-sectional study. We compared the responses to 100 clinical questions related to inpatient management provided by two rapid response methods with 'Gold Standard' recommendations. One of the rapid methods was based on PubMed and the other on Epistemonikos database. We defined our 'Gold Standard' as trustworthy published evidence-based recommendations or, when unavailable, recommendations developed locally by a panel of six clinicians following the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. Recommendations provided by the rapid strategies were classified as potentially misleading or reasonable. We also determined if the potentially misleading recommendations could have been avoided with the appropriate implementation of searching and evidence summary tools. We were able to answer all of the 100 questions with both rapid methods. Of the 200 recommendations obtained, 6.5% (95% CI 3% to 9.9%) were classified as potentially misleading and 93.5% (95% CI 90% to 96.9%) as reasonable. 6 of the 13 potentially misleading recommendations could have been avoided by the appropriate usage of the Epistemonikos matrix tool or by constructing summary of findings tables. No significant differences were observed between the evaluated rapid response methods. A question answering service based on the GRADE approach proved feasible to implement and provided appropriate guidance for most identified questions. Our approach could help stakeholders in charge of managing resources and defining policies for patient care to improve evidence-based decision-making in an efficient and feasible manner. © 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.

Make versus buy: a financial perspective.

PubMed

Kisner, Harold J

2003-01-01

Clinical laboratories are often faced with the decision to either perform a service in-house using their own assets or outsource the service to another vendor. This decision affects many aspects of the laboratory's business, from the macroeconomic perspective of outsourcing the laboratory service to a laboratory vendor, to the microeconomics of determining whether to refer a test out to their reference laboratory or perform the test in-house. The basis for decision making includes many variables, but a detailed financial analysis is usually the basis for the decision, especially when the decision only affects the laboratory and not the rest of the institution. Other factors often come into play, and depending on the magnitude, the "make versus buy" decision could be based more on strategic or political factors than economics. Even when noneconomic factors are involved, an effort usually is made to quantify those factors so that the make versus buy decision is reduced to financial terms. The previous article in this issue, "Effectively Managing Your Reference Laboratory Relationship" by Ronald L. Weiss, M.D., focused on the "buy" decision relating to managing the reference laboratory relationship. Although that article took a more clinical perspective through the eyes of the reference laboratory, this article looks at the make versus buy decision from a financial perspective through the eyes of the buying party.

Family-based treatment of a 17-year-old twin presenting with emerging anorexia nervosa: a case study using the "Maudsley method".

PubMed

Loeb, Katharine L; Hirsch, Alicia M; Greif, Rebecca; Hildebrandt, Thomas B

2009-01-01

This article describes the successful application of family-based treatment (FBT) for a 17-year-old identical twin presenting with a 4-month history of clinically significant symptoms of anorexia nervosa (AN). FBT is a manualized treatment that has been studied in randomized controlled trials for adolescents with AN. This case study illustrates the administration of this evidence-based intervention in a clinical setting, highlighting how the best available research was used to make clinical decisions at each stage of treatment delivery.

Clinical Decision Support Systems (CDSS) for preventive management of COPD patients.

PubMed

Velickovski, Filip; Ceccaroni, Luigi; Roca, Josep; Burgos, Felip; Galdiz, Juan B; Marina, Nuria; Lluch-Ariet, Magí

2014-11-28

The use of information and communication technologies to manage chronic diseases allows the application of integrated care pathways, and the optimization and standardization of care processes. Decision support tools can assist in the adherence to best-practice medicine in critical decision points during the execution of a care pathway. The objectives are to design, develop, and assess a clinical decision support system (CDSS) offering a suite of services for the early detection and assessment of chronic obstructive pulmonary disease (COPD), which can be easily integrated into a healthcare providers' work-flow. The software architecture model for the CDSS, interoperable clinical-knowledge representation, and inference engine were designed and implemented to form a base CDSS framework. The CDSS functionalities were iteratively developed through requirement-adjustment/development/validation cycles using enterprise-grade software-engineering methodologies and technologies. Within each cycle, clinical-knowledge acquisition was performed by a health-informatics engineer and a clinical-expert team. A suite of decision-support web services for (i) COPD early detection and diagnosis, (ii) spirometry quality-control support, (iii) patient stratification, was deployed in a secured environment on-line. The CDSS diagnostic performance was assessed using a validation set of 323 cases with 90% specificity, and 96% sensitivity. Web services were integrated in existing health information system platforms. Specialized decision support can be offered as a complementary service to existing policies of integrated care for chronic-disease management. The CDSS was able to issue recommendations that have a high degree of accuracy to support COPD case-finding. Integration into healthcare providers' work-flow can be achieved seamlessly through the use of a modular design and service-oriented architecture that connect to existing health information systems.

Clinical Decision Support Systems (CDSS) for preventive management of COPD patients

PubMed Central

2014-01-01

Background The use of information and communication technologies to manage chronic diseases allows the application of integrated care pathways, and the optimization and standardization of care processes. Decision support tools can assist in the adherence to best-practice medicine in critical decision points during the execution of a care pathway. Objectives The objectives are to design, develop, and assess a clinical decision support system (CDSS) offering a suite of services for the early detection and assessment of chronic obstructive pulmonary disease (COPD), which can be easily integrated into a healthcare providers' work-flow. Methods The software architecture model for the CDSS, interoperable clinical-knowledge representation, and inference engine were designed and implemented to form a base CDSS framework. The CDSS functionalities were iteratively developed through requirement-adjustment/development/validation cycles using enterprise-grade software-engineering methodologies and technologies. Within each cycle, clinical-knowledge acquisition was performed by a health-informatics engineer and a clinical-expert team. Results A suite of decision-support web services for (i) COPD early detection and diagnosis, (ii) spirometry quality-control support, (iii) patient stratification, was deployed in a secured environment on-line. The CDSS diagnostic performance was assessed using a validation set of 323 cases with 90% specificity, and 96% sensitivity. Web services were integrated in existing health information system platforms. Conclusions Specialized decision support can be offered as a complementary service to existing policies of integrated care for chronic-disease management. The CDSS was able to issue recommendations that have a high degree of accuracy to support COPD case-finding. Integration into healthcare providers' work-flow can be achieved seamlessly through the use of a modular design and service-oriented architecture that connect to existing health information systems. PMID:25471545

Automated Modular Magnetic Resonance Imaging Clinical Decision Support System (MIROR): An Application in Pediatric Cancer Diagnosis

PubMed Central

Zarinabad, Niloufar; Meeus, Emma M; Manias, Karen; Foster, Katharine

2018-01-01

Background Advances in magnetic resonance imaging and the introduction of clinical decision support systems has underlined the need for an analysis tool to extract and analyze relevant information from magnetic resonance imaging data to aid decision making, prevent errors, and enhance health care. Objective The aim of this study was to design and develop a modular medical image region of interest analysis tool and repository (MIROR) for automatic processing, classification, evaluation, and representation of advanced magnetic resonance imaging data. Methods The clinical decision support system was developed and evaluated for diffusion-weighted imaging of body tumors in children (cohort of 48 children, with 37 malignant and 11 benign tumors). Mevislab software and Python have been used for the development of MIROR. Regions of interests were drawn around benign and malignant body tumors on different diffusion parametric maps, and extracted information was used to discriminate the malignant tumors from benign tumors. Results Using MIROR, the various histogram parameters derived for each tumor case when compared with the information in the repository provided additional information for tumor characterization and facilitated the discrimination between benign and malignant tumors. Clinical decision support system cross-validation showed high sensitivity and specificity in discriminating between these tumor groups using histogram parameters. Conclusions MIROR, as a diagnostic tool and repository, allowed the interpretation and analysis of magnetic resonance imaging images to be more accessible and comprehensive for clinicians. It aims to increase clinicians’ skillset by introducing newer techniques and up-to-date findings to their repertoire and make information from previous cases available to aid decision making. The modular-based format of the tool allows integration of analyses that are not readily available clinically and streamlines the future developments. PMID:29720361

Assessing infant and maternal readiness for newborn discharge.

PubMed

Jing, Ling; Bethancourt, Casidhe-Nicole; McDonagh, Thomas

2017-10-01

The review highlights the shift from prescribed length of stay (LOS) to mother-infant dyad readiness as the basis for making discharge decisions for healthy term newborns. We describe the components of readiness that should be considered in making the decision, focusing on infant clinical readiness, and maternal and familial readiness. Although the Newborns' and Mothers' Health Protection Act of 1996 aimed to protect infants and mothers by establishing a minimum LOS, the American Academy of Pediatrics 2015 policy on newborn discharge acknowledges the shift from LOS-based to readiness-based discharge decision-making. Healthcare providers must consider a variety of infant and maternal characteristics in determining the appropriate time to discharge a dyad, and mothers should be actively involved in the decision-making process. Criteria for infant clinical readiness include the following: establishment of effective feeding, evaluation of jaundice risk, review and discussion of infant and household vaccination status, obtainment of specimen for metabolic screening, tests of hearing ability, assessment of sepsis risk factors, screening for congenital heart disease, and evaluation of parental knowledge about infant safety measures. Important consideration should also be given to the mother's sociodemographic vulnerabilities, maternal confidence and perception of discharge readiness, and availability of postdischarge care continuity. The timing of newborn discharge should be a joint decision made by the mother and healthcare providers based on readiness. The decision should consider the infant's health status, the mother's health status, the mother's perception of readiness, and the availability of social and familial support for the mother and infant. Accessible and comprehensive support postdischarge is also important for helping infants achieve optimal health outcomes.

Technological innovations in the development of cardiovascular clinical information systems.

PubMed

Hsieh, Nan-Chen; Chang, Chung-Yi; Lee, Kuo-Chen; Chen, Jeen-Chen; Chan, Chien-Hui

2012-04-01

Recent studies have shown that computerized clinical case management and decision support systems can be used to assist surgeons in the diagnosis of disease, optimize surgical operation, aid in drug therapy and decrease the cost of medical treatment. Therefore, medical informatics has become an extensive field of research and many of these approaches have demonstrated potential value for improving medical quality. The aim of this study was to develop a web-based cardiovascular clinical information system (CIS) based on innovative techniques, such as electronic medical records, electronic registries and automatic feature surveillance schemes, to provide effective tools and support for clinical care, decision-making, biomedical research and training activities. The CIS developed for this study contained monitoring, surveillance and model construction functions. The monitoring layer function provided a visual user interface. At the surveillance and model construction layers, we explored the application of model construction and intelligent prognosis to aid in making preoperative and postoperative predictions. With the use of the CIS, surgeons can provide reasonable conclusions and explanations in uncertain environments.

Progress in evidence-based medicine: a quarter century on.

PubMed

Djulbegovic, Benjamin; Guyatt, Gordon H

2017-07-22

In response to limitations in the understanding and use of published evidence, evidence-based medicine (EBM) began as a movement in the early 1990s. EBM's initial focus was on educating clinicians in the understanding and use of published literature to optimise clinical care, including the science of systematic reviews. EBM progressed to recognise limitations of evidence alone, and has increasingly stressed the need to combine critical appraisal of the evidence with patient's values and preferences through shared decision making. In another progress, EBM incorporated and further developed the science of producing trustworthy clinical practice guidelines pioneered by investigators in the 1980s. EBM's enduring contributions to clinical medicine include placing the practice of medicine on a solid scientific basis, the development of more sophisticated hierarchies of evidence, the recognition of the crucial role of patient values and preferences in clinical decision making, and the development of the methodology for generating trustworthy recommendations. Copyright © 2017 Elsevier Ltd. All rights reserved.

Shared decision making: relevant concepts and facilitating strategies.

PubMed

Bae, Jong-Myon

2017-01-01

As the paradigm in healthcare nowadays is the evidence-based, patient-centered decision making, the issue of shared decision making (SDM) is highlighted. The aims of this manuscript were to look at the relevant concepts and suggest the facilitating strategies for overcoming barriers of conducting SDM. While the definitions of SDM were discordant, several concepts such as good communication, individual autonomy, patient participants, and patient-centered decision-making were involved. Further, the facilitating strategies of SDM were to educate and train physician, to apply clinical practice guidelines and patient decision aids, to develop valid measurement tools for evaluation of SDM processes, and to investigate the impact of SDM.

Toward better public health reporting using existing off the shelf approaches: A comparison of alternative cancer detection approaches using plaintext medical data and non-dictionary based feature selection.

PubMed

Kasthurirathne, Suranga N; Dixon, Brian E; Gichoya, Judy; Xu, Huiping; Xia, Yuni; Mamlin, Burke; Grannis, Shaun J

2016-04-01

Increased adoption of electronic health records has resulted in increased availability of free text clinical data for secondary use. A variety of approaches to obtain actionable information from unstructured free text data exist. These approaches are resource intensive, inherently complex and rely on structured clinical data and dictionary-based approaches. We sought to evaluate the potential to obtain actionable information from free text pathology reports using routinely available tools and approaches that do not depend on dictionary-based approaches. We obtained pathology reports from a large health information exchange and evaluated the capacity to detect cancer cases from these reports using 3 non-dictionary feature selection approaches, 4 feature subset sizes, and 5 clinical decision models: simple logistic regression, naïve bayes, k-nearest neighbor, random forest, and J48 decision tree. The performance of each decision model was evaluated using sensitivity, specificity, accuracy, positive predictive value, and area under the receiver operating characteristics (ROC) curve. Decision models parameterized using automated, informed, and manual feature selection approaches yielded similar results. Furthermore, non-dictionary classification approaches identified cancer cases present in free text reports with evaluation measures approaching and exceeding 80-90% for most metrics. Our methods are feasible and practical approaches for extracting substantial information value from free text medical data, and the results suggest that these methods can perform on par, if not better, than existing dictionary-based approaches. Given that public health agencies are often under-resourced and lack the technical capacity for more complex methodologies, these results represent potentially significant value to the public health field. Copyright © 2016 Elsevier Inc. All rights reserved.

Adolescent Judgments and Reasoning about the Failure to Include Peers with Social Disabilities

ERIC Educational Resources Information Center

Bottema-Beutel, Kristen; Li, Zhushan

2015-01-01

Adolescents with autism spectrum disorder often do not have access to crucial peer social activities. This study examines how typically developing adolescents evaluate decisions not to include a peer based on disability status, and the justifications they apply to these decisions. A clinical interview methodology was used to elicit judgments and…

Using sense-making theory to aid understanding of the recognition, assessment and management of pain in patients with dementia in acute hospital settings.

PubMed

Dowding, Dawn; Lichtner, Valentina; Allcock, Nick; Briggs, Michelle; James, Kirstin; Keady, John; Lasrado, Reena; Sampson, Elizabeth L; Swarbrick, Caroline; José Closs, S

2016-01-01

The recognition, assessment and management of pain in hospital settings is suboptimal, and is a particular challenge in patients with dementia. The existing process guiding pain assessment and management in clinical settings is based on the assumption that nurses follow a sequential linear approach to decision making. In this paper we re-evaluate this theoretical assumption drawing on findings from a study of pain recognition, assessment and management in patients with dementia. To provide a revised conceptual model of pain recognition, assessment and management based on sense-making theories of decision making. The research we refer to is an exploratory ethnographic study using nested case sites. Patients with dementia (n=31) were the unit of data collection, nested in 11 wards (vascular, continuing care, stroke rehabilitation, orthopaedic, acute medicine, care of the elderly, elective and emergency surgery), located in four NHS hospital organizations in the UK. Data consisted of observations of patients at bedside (170h in total); observations of the context of care; audits of patient hospital records; documentary analysis of artefacts; semi-structured interviews (n=56) and informal open conversations with staff and carers (family members). Existing conceptualizations of pain recognition, assessment and management do not fully explain how the decision process occurs in clinical practice. Our research indicates that pain recognition, assessment and management is not an individual cognitive activity; rather it is carried out by groups of individuals over time and within a specific organizational culture or climate, which influences both health care professional and patient behaviour. We propose a revised theoretical model of decision making related to pain assessment and management for patients with dementia based on theories of sense-making, which is reflective of the reality of clinical decision making in acute hospital wards. The revised model recognizes the salience of individual cognition as well as acknowledging that decisions are constructed through social interaction and organizational context. The model will be used in further research to develop decision support interventions to assist with the assessment and management of patients with dementia in acute hospital settings. Copyright © 2015. Published by Elsevier Ltd.

Towards public health decision support: a systematic review of bidirectional communication approaches.

PubMed

Dixon, Brian E; Gamache, Roland E; Grannis, Shaun J

2013-05-01

To summarize the literature describing computer-based interventions aimed at improving bidirectional communication between clinical and public health. A systematic review of English articles using MEDLINE and Google Scholar. Search terms included public health, epidemiology, electronic health records, decision support, expert systems, and decision-making. Only articles that described the communication of information regarding emerging health threats from public health agencies to clinicians or provider organizations were included. Each article was independently reviewed by two authors. Ten peer-reviewed articles highlight a nascent but promising area of research and practice related to alerting clinicians about emerging threats. Current literature suggests that additional research and development in bidirectional communication infrastructure should focus on defining a coherent architecture, improving interoperability, establishing clear governance, and creating usable systems that will effectively deliver targeted, specific information to clinicians in support of patient and population decision-making. Increasingly available clinical information systems make it possible to deliver timely, relevant knowledge to frontline clinicians in support of population health. Future work should focus on developing a flexible, interoperable infrastructure for bidirectional communications capable of integrating public health knowledge into clinical systems and workflows.

Mental workload as a key factor in clinical decision making.

PubMed

Byrne, Aidan

2013-08-01

The decision making process is central to the practice of a clinician and has traditionally been described in terms of the hypothetico-deductive model. More recently, models adapted from cognitive psychology, such as the dual process and script theories have proved useful in explaining patterns of practice not consistent with purely cognitive based practice. The purpose of this paper is to introduce the concept of mental workload as a key determinant of the type of cognitive processing used by clinicians. Published research appears to be consistent with 'schemata' based cognition as the principle mode of working for those engaged in complex tasks under time pressure. Although conscious processing of factual data is also used, it may be the primary mode of cognition only in situations where time pressure is not a factor. Further research on the decision making process should be based on outcomes which are not dependant on conscious recall of past actions or events and include a measure of mental workload. This further appears to support the concept of the patient, within the clinical environment, as the most effective learning resource.

Development of a SNOMED CT based national medication decision support system.

PubMed

Greibe, Kell

2013-01-01

Physicians often lack the time to familiarize themselves with the details of particular allergies or other drug restrictions. Clinical Decision Support (CDS), based on a structured terminology as SNOMED CT (SCT), can help physicians get an overview, by automatically alerting allergy, interactions and other important information. The centralized CDS platform based on SCT, controls Allergy, Interactions, Risk Situation Drugs and Max Dose restrictions by the help of databases developed for these specific purposes. The CDS will respond to automatic web service requests from the hospital or GP electronic medication system (EMS) during prescription, and return alerts and information. The CDS also contains a Physicians Preference Database where the physicians individually can set which kind of alerts they want to see. The result is clinically useful information physicians can use as a base for a more effective and safer treatment, without developing alert fatigue.

A Benefit-Risk Analysis Approach to Capture Regulatory Decision-Making: Non-Small Cell Lung Cancer.

PubMed

Raju, G K; Gurumurthi, K; Domike, R; Kazandjian, D; Blumenthal, G; Pazdur, R; Woodcock, J

2016-12-01

Drug regulators around the world make decisions about drug approvability based on qualitative benefit-risk analyses. There is much interest in quantifying regulatory approaches to benefit and risk. In this work the use of a quantitative benefit-risk analysis was applied to regulatory decision-making about new drugs to treat advanced non-small cell lung cancer (NSCLC). Benefits and risks associated with 20 US Food and Drug Administration (FDA) decisions associated with a set of candidate treatments submitted between 2003 and 2015 were analyzed. For benefit analysis, the median overall survival (OS) was used where available. When not available, OS was estimated based on overall response rate (ORR) or progression-free survival (PFS). Risks were analyzed based on magnitude (or severity) of harm and likelihood of occurrence. Additionally, a sensitivity analysis was explored to demonstrate analysis of systematic uncertainty. FDA approval decision outcomes considered were found to be consistent with the benefit-risk logic. © 2016 American Society for Clinical Pharmacology and Therapeutics.

Applicability and accuracy of pretest probability calculations implemented in the NICE clinical guideline for decision making about imaging in patients with chest pain of recent onset.

PubMed

Roehle, Robert; Wieske, Viktoria; Schuetz, Georg M; Gueret, Pascal; Andreini, Daniele; Meijboom, Willem Bob; Pontone, Gianluca; Garcia, Mario; Alkadhi, Hatem; Honoris, Lily; Hausleiter, Jörg; Bettencourt, Nuno; Zimmermann, Elke; Leschka, Sebastian; Gerber, Bernhard; Rochitte, Carlos; Schoepf, U Joseph; Shabestari, Abbas Arjmand; Nørgaard, Bjarne; Sato, Akira; Knuuti, Juhani; Meijs, Matthijs F L; Brodoefel, Harald; Jenkins, Shona M M; Øvrehus, Kristian Altern; Diederichsen, Axel Cosmus Pyndt; Hamdan, Ashraf; Halvorsen, Bjørn Arild; Mendoza Rodriguez, Vladimir; Wan, Yung Liang; Rixe, Johannes; Sheikh, Mehraj; Langer, Christoph; Ghostine, Said; Martuscelli, Eugenio; Niinuma, Hiroyuki; Scholte, Arthur; Nikolaou, Konstantin; Ulimoen, Geir; Zhang, Zhaoqi; Mickley, Hans; Nieman, Koen; Kaufmann, Philipp A; Buechel, Ronny Ralf; Herzog, Bernhard A; Clouse, Melvin; Halon, David A; Leipsic, Jonathan; Bush, David; Jakamy, Reda; Sun, Kai; Yang, Lin; Johnson, Thorsten; Laissy, Jean-Pierre; Marcus, Roy; Muraglia, Simone; Tardif, Jean-Claude; Chow, Benjamin; Paul, Narinder; Maintz, David; Hoe, John; de Roos, Albert; Haase, Robert; Laule, Michael; Schlattmann, Peter; Dewey, Marc

2018-03-19

To analyse the implementation, applicability and accuracy of the pretest probability calculation provided by NICE clinical guideline 95 for decision making about imaging in patients with chest pain of recent onset. The definitions for pretest probability calculation in the original Duke clinical score and the NICE guideline were compared. We also calculated the agreement and disagreement in pretest probability and the resulting imaging and management groups based on individual patient data from the Collaborative Meta-Analysis of Cardiac CT (CoMe-CCT). 4,673 individual patient data from the CoMe-CCT Consortium were analysed. Major differences in definitions in the Duke clinical score and NICE guideline were found for the predictors age and number of risk factors. Pretest probability calculation using guideline criteria was only possible for 30.8 % (1,439/4,673) of patients despite availability of all required data due to ambiguity in guideline definitions for risk factors and age groups. Agreement regarding patient management groups was found in only 70 % (366/523) of patients in whom pretest probability calculation was possible according to both models. Our results suggest that pretest probability calculation for clinical decision making about cardiac imaging as implemented in the NICE clinical guideline for patients has relevant limitations. • Duke clinical score is not implemented correctly in NICE guideline 95. • Pretest probability assessment in NICE guideline 95 is impossible for most patients. • Improved clinical decision making requires accurate pretest probability calculation. • These refinements are essential for appropriate use of cardiac CT.

Ask the right question: a critical step for practicing evidence-based laboratory medicine.

PubMed

Price, Christopher P; Christenson, Robert H

2013-07-01

The purpose of laboratory medicine is to facilitate better decision making in clinical practice and healthcare delivery. Decision making implies an unresolved issue, problem or unmet need. The most important criterion for any investigation to be of value in clinical practice is that it addresses an unmet need. The different ways in which laboratory investigations are utilized in patient care can be represented in the form of questions. It is important that these questions are articulated to highlight the variables that will impact on the effectiveness of the investigation in the scenario being considered. These variables include the characteristics of the patient (or population) and clinical setting, the nature of the decision and action taken on receipt of the test result and the expected outcome. Asking a question is the first step of the evidence-based laboratory medicine (EBLM) cycle, the other steps being acquiring the evidence, critically appraising the evidence, applying the evidence and auditing use of the evidence. Getting the question right determines the quality of the whole process, thus, defines the quality in practice of laboratory medicine. Whilst the main focus of the EBLM cycle is to provide a strong evidence base for use in clinical practice, it is clear that the five steps are equally applicable in commissioning, delivery and audit (performance management) of services. Asking the right question is crucial to improving the quality of evidence, and practice, in laboratory medicine, and should be used in routine laboratory medicine practice and management throughout healthcare.