Impact of Sociocultural Background and Assessment Data Upon School Psychologists' Decisions.

ERIC Educational Resources Information Center

Huebner, E. Scott; Cummings, Jack A.

1985-01-01

Psychologists (N=56) participated in an adapted version of Algozzine and Ysseldyke's (1981) diagnostic simulation to investigate the effects of sociocultural background (rural vs. suburban) and assessment data (normal vs. learning disabled) on educational decisions. Findings suggest school psychologists utilize multiple sources of information but…

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

Grand Challenges in Clinical Decision Support v10

PubMed Central

Sittig, Dean F.; Wright, Adam; Osheroff, Jerome A.; Middleton, Blackford; Teich, Jonathan M.; Ash, Joan S.; Campbell, Emily; Bates, David W.

2008-01-01

There is a pressing need for high-quality, effective means of designing, developing, presenting, implementing, evaluating, and maintaining all types of clinical decision support capabilities for clinicians, patients and consumers. Using an iterative, consensus-building process we identified a rank-ordered list of the top 10 grand challenges in clinical decision support. This list was created to educate and inspire researchers, developers, funders, and policy-makers. The list of challenges in order of importance that they be solved if patients and organizations are to begin realizing the fullest benefits possible of these systems consists of: Improve the human-computer interface; Disseminate best practices in CDS design, development, and implementation; Summarize patient-level information; Prioritize and filter recommendations to the user; Create an architecture for sharing executable CDS modules and services; Combine recommendations for patients with co-morbidities; Prioritize CDS content development and implementation; Create internet-accessible clinical decision support repositories; Use freetext information to drive clinical decision support; Mine large clinical databases to create new CDS. Identification of solutions to these challenges is critical if clinical decision support is to achieve its potential and improve the quality, safety and efficiency of healthcare. PMID:18029232

Exploring Decision-Making of HIV-Infected Hispanics and African Americans Participating in Clinical Trials

PubMed Central

Rivera-Goba, Migdalia V.; Dominguez, Dinora C.; Stoll, Pamela; Grady, Christine; Ramos, Catalina; Mican, JoAnn M.

2011-01-01

Underrepresentation of HIV-infected Hispanics and African Americans in clinical trials seriously limits our understanding of the benefits and risks of treatment in these populations. This qualitative study examined factors that racial/ethnic minority patients consider when making decisions regarding research participation. Thirty-five HIV-infected Hispanic and African American patients enrolled in clinical research protocols at the National Institutes of Health were recruited to participate in focus groups and in-depth interviews. The sample of mostly men (n = 22), had a mean age of 45, nearly equal representation of race/ethnicity, and diagnosed 2 to 22 years ago. Baseline questionnaires included demographics and measures of social support and acculturation. Interviewers had similar racial/ethnic, cultural, and linguistic backgrounds as the participants. Four major themes around participants’ decisions to enroll in clinical trials emerged: Enhancers, Barriers, Beliefs, and Psychosocial Context. Results may help researchers develop strategies to facilitate inclusion of HIV-infected Hispanics and African Americans into clinical trials. PMID:21256054

Non-clinical influences on clinical decision-making: a major challenge to evidence-based practice.

PubMed

Hajjaj, F M; Salek, M S; Basra, M K A; Finlay, A Y

2010-05-01

This article reviews an aspect of daily clinical practice which is of critical importance in virtually every clinical consultation, but which is seldom formally considered. Non-clinical influences on clinical decision-making profoundly affect medical decisions. These influences include patient-related factors such as socioeconomic status, quality of life and patient's expectations and wishes, physician-related factors such as personal characteristics and interaction with their professional community, and features of clinical practice such as private versus public practice as well as local management policies. This review brings together the different strands of knowledge concerning non-clinical influences on clinical decision-making. This aspect of decision-making may be the biggest obstacle to the reality of practising evidence-based medicine. It needs to be understood in order to develop clinical strategies that will facilitate the practice of evidence-based medicine.

The Cape Town Clinical Decision Rule for Streptococcal Pharyngitis in Children

PubMed Central

Engel, Mark Emmanuel; Cohen, Karen; Gounden, Ronald; Kengne, Andre P.; Barth, Dylan Dominic; Whitelaw, Andrew C; Francis, Veronica; Badri, Motasim; Stewart, Annemie; Dale, James B.; Mayosi, Bongani M.; Maartens, Gary

2016-01-01

Background Existing clinical decision rules (CDR) to diagnose group A streptococcal (GAS) pharyngitis have not been validated in sub-Saharan Africa. We developed a locally applicable CDR while evaluating existing CDRs for diagnosing GAS pharyngitis in South African children. Methods We conducted a prospective cohort study and enrolled 997 children aged 3-15 years presenting to primary care clinics with a complaint of sore throat, and whose parents provided consent. Main outcome measures were signs and symptoms of pharyngitis, and a positive GAS culture from a throat swab. Bivariate and multivariate analyses were used to develop the clinical decision rule. In addition, the diagnostic effectiveness of six existing rules for predicting a positive culture in our cohort was assessed. Results 206 of 982 children (21%) had a positive GAS culture. Tonsillar swelling, tonsillar exudates, tender or enlarged anterior cervical lymph nodes, absence of cough and absence of rhinorrhea were associated with positive cultures in bivariate and multivariate analyses. Four variables (tonsillar swelling and one of tonsillar exudate, no rhinorrhea, no cough), when used in a cumulative score, showed 83.7% sensitivity and 32.2% specificity for GAS pharyngitis. Of existing rules tested, the McIsaac rule had the highest positive predictive value (28%), but missed 49% of the culture-positive children who should have been treated. Conclusion The new four-variable clinical decision rule for GAS pharyngitis (i.e., tonsillar swelling and one of tonsillar exudate, no rhinorrhea, no cough) outperformed existing rules for GAS pharyngitis diagnosis in children with symptomatic sore throat in Cape Town. PMID:27870815

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.

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

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

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

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.

The utility of clinical decision tools for diagnosing osteoporosis in postmenopausal women with rheumatoid arthritis

PubMed Central

Brand, Caroline; Lowe, Adrian; Hall, Stephen

2008-01-01

Background Patients with rheumatoid arthritis have a higher risk of low bone mineral density than normal age matched populations. There is limited evidence to support cost effectiveness of population screening in rheumatoid arthritis and case finding strategies have been proposed as a means to increase cost effectiveness of diagnostic screening for osteoporosis. This study aimed to assess the performance attributes of generic and rheumatoid arthritis specific clinical decision tools for diagnosing osteoporosis in a postmenopausal population with rheumatoid arthritis who attend ambulatory specialist rheumatology clinics. Methods A cross-sectional study of 127 ambulatory post-menopausal women with rheumatoid arthritis was performed. Patients currently receiving or who had previously received bone active therapy were excluded. Eligible women underwent clinical assessment and dual-energy-xray absorptiometry (DXA) bone mineral density assessment. Clinical decision tools, including those specific for rheumatoid arthritis, were compared to seven generic post-menopausal tools to predict osteoporosis (defined as T score < -2.5). Sensitivity, specificity, positive predictive and negative predictive values and area under the curve were assessed. The diagnostic attributes of the clinical decision tools were compared by examination of the area under the receiver-operator-curve. Results One hundred and twenty seven women participated. The median age was 62 (IQR 56–71) years. Median disease duration was 108 (60–168) months. Seventy two (57%) women had no record of a previous DXA examination. Eighty (63%) women had T scores at femoral neck or lumbar spine less than -1. The area under the ROC curve for clinical decision tool prediction of T score <-2.5 varied between 0.63 and 0.76. The rheumatoid arthritis specific decision tools did not perform better than generic tools, however, the National Osteoporosis Foundation score could potentially reduce the number of unnecessary DXA

Clinical decision regret among critical care nurses: a qualitative analysis.

PubMed

Arslanian-Engoren, Cynthia; Scott, Linda D

2014-01-01

Decision regret is a negative cognitive emotion associated with experiences of guilt and situations of interpersonal harm. These negative affective responses may contribute to emotional exhaustion in critical care nurses (CCNs), increased staff turnover rates and high medication error rates. Yet, little is known about clinical decision regret among CCNs or the conditions or situations (e.g., feeling sleepy) that may precipitate its occurrence. To examine decision regret among CCNs, with an emphasis on clinical decisions made when nurses were most sleepy. A content analytic approach was used to examine the narrative descriptions of clinical decisions by CCNs when sleepy. Six decision regret themes emerged that represented deviations in practice or performance behaviors that were attributed to fatigued CCNs. While 157 CCNs disclosed a clinical decision they made at work while sleepy, the prevalence may be underestimated and warrants further investigation. Copyright © 2014 Elsevier Inc. All rights reserved.

Clinical decision making: how surgeons do it.

PubMed

Crebbin, Wendy; Beasley, Spencer W; Watters, David A K

2013-06-01

Clinical decision making is a core competency of surgical practice. It involves two distinct types of mental process best considered as the ends of a continuum, ranging from intuitive and subconscious to analytical and conscious. In practice, individual decisions are usually reached by a combination of each, according to the complexity of the situation and the experience/expertise of the surgeon. An expert moves effortlessly along this continuum, according to need, able to apply learned rules or algorithms to specific presentations, choosing these as a result of either pattern recognition or analytical thinking. The expert recognizes and responds quickly to any mismatch between what is observed and what was expected, coping with gaps in information and making decisions even where critical data may be uncertain or unknown. Even for experts, the cognitive processes involved are difficult to articulate as they tend to be very complex. However, if surgeons are to assist trainees in developing their decision-making skills, the processes need to be identified and defined, and the competency needs to be measurable. This paper examines the processes of clinical decision making in three contexts: making a decision about how to manage a patient; preparing for an operative procedure; and reviewing progress during an operative procedure. The models represented here are an exploration of the complexity of the processes, designed to assist surgeons understand how expert clinical decision making occurs and to highlight the challenge of teaching these skills to surgical trainees. © 2013 The Authors. ANZ Journal of Surgery © 2013 Royal Australasian College of Surgeons.

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.

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

[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.

Factors and outcomes of decision making for cancer clinical trial participation.

PubMed

Biedrzycki, Barbara A

2011-09-01

To describe factors and outcomes related to the decision-making process regarding participation in a cancer clinical trial. Cross-sectional, descriptive. Urban, academic, National Cancer Institute-designated comprehensive cancer center in the mid-Atlantic United States. 197 patients with advanced gastrointestinal cancer. Mailed survey using one investigator-developed instrument, eight instruments used in published research, and a medical record review. disease context, sociodemographics, hope, quality of life, trust in healthcare system, trust in health professional, preference for research decision control, understanding risks, and information. decision to accept or decline research participation and satisfaction with this decision. All of the factors within the Research Decision Making Model together predicted cancer clinical trial participation and satisfaction with this decision. The most frequently preferred decision-making style for research participation was shared (collaborative) (83%). Multiple factors affect decision making for cancer clinical trial participation and satisfaction with this decision. Shared decision making previously was an unrecognized factor and requires further investigation. Enhancing the process of research decision making may facilitate an increase in cancer clinical trial enrollment rates. Oncology nurses have unique opportunities as educators and researchers to support shared decision making by those who prefer this method for deciding whether to accept or decline cancer clinical trial participation.

Personalizing Drug Selection Using Advanced Clinical Decision Support

PubMed Central

Pestian, John; Spencer, Malik; Matykiewicz, Pawel; Zhang, Kejian; Vinks, Alexander A.; Glauser, Tracy

2009-01-01

This article describes the process of developing an advanced pharmacogenetics clinical decision support at one of the United States’ leading pediatric academic medical centers. This system, called CHRISTINE, combines clinical and genetic data to identify the optimal drug therapy when treating patients with epilepsy or Attention Deficit Hyperactivity Disorder. In the discussion a description of clinical decision support systems is provided, along with an overview of neurocognitive computing and how it is applied in this setting. PMID:19898682

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.

User-centered design to improve clinical decision support in primary care.

PubMed

Brunner, Julian; Chuang, Emmeline; Goldzweig, Caroline; Cain, Cindy L; Sugar, Catherine; Yano, Elizabeth M

2017-08-01

A growing literature has demonstrated the ability of user-centered design to make clinical decision support systems more effective and easier to use. However, studies of user-centered design have rarely examined more than a handful of sites at a time, and have frequently neglected the implementation climate and organizational resources that influence clinical decision support. The inclusion of such factors was identified by a systematic review as "the most important improvement that can be made in health IT evaluations." (1) Identify the prevalence of four user-centered design practices at United States Veterans Affairs (VA) primary care clinics and assess the perceived utility of clinical decision support at those clinics; (2) Evaluate the association between those user-centered design practices and the perceived utility of clinical decision support. We analyzed clinic-level survey data collected in 2006-2007 from 170 VA primary care clinics. We examined four user-centered design practices: 1) pilot testing, 2) provider satisfaction assessment, 3) formal usability assessment, and 4) analysis of impact on performance improvement. We used a regression model to evaluate the association between user-centered design practices and the perceived utility of clinical decision support, while accounting for other important factors at those clinics, including implementation climate, available resources, and structural characteristics. We also examined associations separately at community-based clinics and at hospital-based clinics. User-centered design practices for clinical decision support varied across clinics: 74% conducted pilot testing, 62% conducted provider satisfaction assessment, 36% conducted a formal usability assessment, and 79% conducted an analysis of impact on performance improvement. Overall perceived utility of clinical decision support was high, with a mean rating of 4.17 (±.67) out of 5 on a composite measure. "Analysis of impact on performance

Accuracy of intuition in clinical decision-making among novice clinicians.

PubMed

Price, Amanda; Zulkosky, Kristen; White, Krista; Pretz, Jean

2017-05-01

To assess the reliance on intuitive and analytical approaches during clinical decision-making among novice clinicians and whether that reliance is associated with accurate decision-making. Nurse educators and managers tend to emphasize analysis over intuition during clinical decision-making though nurses typically report some reliance on intuition in their practice. We hypothesized that under certain conditions, reliance on intuition would support accurate decision-making, even among novices. This study utilized an experimental design with clinical complication (familiar vs. novel) and decision phase (cue acquisition, diagnosis and action) as within-subjects' factors, and simulation role (observer, family, auxiliary nurse and primary nurse) as between-subjects' factor. We examined clinical decision-making accuracy among final semester pre-licensure nursing students in a simulation experience. Students recorded their reasoning about emerging clinical complications with their patient during two distinct points in the simulation; one point involved a familiar complication and the other a relatively novel complication. All data were collected during Spring 2015. Although most participants relied more heavily on analysis than on intuition, use of intuition during the familiar complication was associated with more accurate decision-making, particularly in guiding attention to relevant cues. With the novel complication, use of intuition appeared to hamper decision-making, particularly for those in an observer role. Novice clinicians should be supported by educators and nurse managers to note when their intuitions are likely to be valid. Our findings emphasize the integrated nature of intuition and analysis in clinical decision-making. © 2016 John Wiley & Sons Ltd.

Factors influencing the clinical decision-making of midwives: a qualitative study.

PubMed

Daemers, Darie O A; van Limbeek, Evelien B M; Wijnen, Hennie A A; Nieuwenhuijze, Marianne J; de Vries, Raymond G

2017-10-06

Although midwives make clinical decisions that have an impact on the health and well-being of mothers and babies, little is known about how they make those decisions. Wide variation in intrapartum decisions to refer women to obstetrician-led care suggests that midwives' decisions are based on more than the evidence based medicine (EBM) model - i.e. clinical evidence, midwife's expertise, and woman's values - alone. With this study we aimed to explore the factors that influence clinical decision-making of midwives who work independently. We used a qualitative approach, conducting in-depth interviews with a purposive sample of 11 Dutch primary care midwives. Data collection took place between May and September 2015. The interviews were semi-structured, using written vignettes to solicit midwives' clinical decision-making processes (Think Aloud method). We performed thematic analysis on the transcripts. We identified five themes that influenced clinical decision-making: the pregnant woman as a whole person, sources of knowledge, the midwife as a whole person, the collaboration between maternity care professionals, and the organisation of care. Regarding the midwife, her decisions were shaped not only by her experience, intuition, and personal circumstances, but also by her attitudes about physiology, woman-centredness, shared decision-making, and collaboration with other professionals. The nature of the local collaboration between maternity care professionals and locally-developed protocols dominated midwives' clinical decision-making. When midwives and obstetricians had different philosophies of care and different practice styles, their collaborative efforts were challenged. Midwives' clinical decision-making is a more varied and complex process than the EBM framework suggests. If midwives are to succeed in their role as promoters and protectors of physiological pregnancy and birth, they need to understand how clinical decisions in a multidisciplinary context are

The patient's role in clinical decision-making.

PubMed

Brody, D S

1980-11-01

Practicing physicians must frequently make decisions about how much they wish to encourage patient participation in clinical decision-making and how to respond to rational patient demands that do not coincide with their own decisions. These are difficult ethical dilemmas with no indisputable or universal solutions. The traditional concept of the doctor-patient relationship places the patient in a passive, compliant role. The patient's only obligation is to seek competent help and cooperate with the physician. A number of factors have contributed to the continued dominance of the traditional doctor-patient imbalance of power. Despite these factors, there seems to be a great deal of public dissatisfaction with health care delivery in the United States; demands for more patient autonomy are increasing. This paper discusses the concept of mutual participation, presents an approach to encouraging patient participation in clinical decision-making, and considers its theoretical advantages.

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

Consensus Recommendations for Systematic Evaluation of Drug-Drug Interaction Evidence for Clinical Decision Support

PubMed Central

Scheife, Richard T.; Hines, Lisa E.; Boyce, Richard D.; Chung, Sophie P.; Momper, Jeremiah; Sommer, Christine D.; Abernethy, Darrell R.; Horn, John; Sklar, Stephen J.; Wong, Samantha K.; Jones, Gretchen; Brown, Mary; Grizzle, Amy J.; Comes, Susan; Wilkins, Tricia Lee; Borst, Clarissa; Wittie, Michael A.; Rich, Alissa; Malone, Daniel C.

2015-01-01

Background Healthcare organizations, compendia, and drug knowledgebase vendors use varying methods to evaluate and synthesize evidence on drug-drug interactions (DDIs). This situation has a negative effect on electronic prescribing and medication information systems that warn clinicians of potentially harmful medication combinations. Objective To provide recommendations for systematic evaluation of evidence from the scientific literature, drug product labeling, and regulatory documents with respect to DDIs for clinical decision support. Methods A conference series was conducted to develop a structured process to improve the quality of DDI alerting systems. Three expert workgroups were assembled to address the goals of the conference. The Evidence Workgroup consisted of 15 individuals with expertise in pharmacology, drug information, biomedical informatics, and clinical decision support. Workgroup members met via webinar from January 2013 to February 2014. Two in-person meetings were conducted in May and September 2013 to reach consensus on recommendations. Results We developed expert-consensus answers to three key questions: 1) What is the best approach to evaluate DDI evidence?; 2) What evidence is required for a DDI to be applicable to an entire class of drugs?; and 3) How should a structured evaluation process be vetted and validated? Conclusion Evidence-based decision support for DDIs requires consistent application of transparent and systematic methods to evaluate the evidence. Drug information systems that implement these recommendations should be able to provide higher quality information about DDIs in drug compendia and clinical decision support tools. PMID:25556085

Physicians' perspectives on communication and decision making in clinical encounters for treatment of latent tuberculosis infection.

PubMed

Dobler, Claudia C; Bosnic-Anticevich, Sinthia; Armour, Carol L

2018-01-01

The aim of the study was to explore the views of tuberculosis (TB) physicians on treatment of latent TB infection (LTBI), focusing on decision making and communication in clinical practice. 20 Australian TB physicians participated in a semistructured interview in person or over the telephone. Interviews were recorded, transcribed and analysed thematically. The study identified challenges that physicians face when discussing treatment for LTBI with patients. These included difficulties explaining the concept of latency (in particular to patients from culturally and linguistically diverse backgrounds) and providing guidance to patients while still framing treatment decisions as a choice. Tailored estimates of the risk of developing TB and the risk of developing an adverse effect from LTBI treatment were considered the most important information for decision making and discussion with patients. Physicians acknowledged that there is a significant amount of unwarranted treatment variation, which they attributed to the lack of evidence about the risk-benefit balance of LTBI treatment in certain scenarios and guidelines that refer to the need for case-by-case decision making in many instances. In order to successfully implement LTBI treatment at a clinical level, consideration should be given to research on how to best address communication challenges arising in clinical encounters.

Physicians' perspectives on communication and decision making in clinical encounters for treatment of latent tuberculosis infection

PubMed Central

Bosnic-Anticevich, Sinthia; Armour, Carol L.

2018-01-01

The aim of the study was to explore the views of tuberculosis (TB) physicians on treatment of latent TB infection (LTBI), focusing on decision making and communication in clinical practice. 20 Australian TB physicians participated in a semistructured interview in person or over the telephone. Interviews were recorded, transcribed and analysed thematically. The study identified challenges that physicians face when discussing treatment for LTBI with patients. These included difficulties explaining the concept of latency (in particular to patients from culturally and linguistically diverse backgrounds) and providing guidance to patients while still framing treatment decisions as a choice. Tailored estimates of the risk of developing TB and the risk of developing an adverse effect from LTBI treatment were considered the most important information for decision making and discussion with patients. Physicians acknowledged that there is a significant amount of unwarranted treatment variation, which they attributed to the lack of evidence about the risk–benefit balance of LTBI treatment in certain scenarios and guidelines that refer to the need for case-by-case decision making in many instances. In order to successfully implement LTBI treatment at a clinical level, consideration should be given to research on how to best address communication challenges arising in clinical encounters. PMID:29577042

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

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.

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.

The impact of simulation sequencing on perceived clinical decision making.

PubMed

Woda, Aimee; Hansen, Jamie; Paquette, Mary; Topp, Robert

2017-09-01

An emerging nursing education trend is to utilize simulated learning experiences as a means to optimize competency and decision making skills. The purpose of this study was to examine differences in students' perception of clinical decision making and clinical decision making-related self-confidence and anxiety based on the sequence (order) in which they participated in a block of simulated versus hospital-based learning experiences. A quasi-experimental crossover design was used. Between and within group differences were found relative to self-confidence with the decision making process. When comparing groups, at baseline the simulation followed by hospital group had significantly higher self-confidence scores, however, at 14-weeks both groups were not significantly different. Significant within group differences were found in the simulation followed by hospital group only, demonstrating a significant decrease in clinical decision making related anxiety across the semester. Finally, there were no significant difference in; perceived clinical decision making within or between the groups at the two measurement points. Preliminary findings suggest that simulated learning experiences can be offered with alternating sequences without impacting the process, anxiety or confidence with clinical decision making. This study provides beginning evidence to guide curriculum development and allow flexibility based on student needs and available resources. Copyright © 2017. Published by Elsevier Ltd.

Improving decision making about clinical trial participation – a randomised controlled trial of a decision aid for women considering participation in the IBIS-II breast cancer prevention trial

PubMed Central

Juraskova, I; Butow, P; Bonner, C; Bell, M L; Smith, A B; Seccombe, M; Boyle, F; Reaby, L; Cuzick, J; Forbes, J F

2014-01-01

Background: Decision aids may improve informed consent in clinical trial recruitment, but have not been evaluated in this context. This study investigated whether decision aids (DAs) can reduce decisional difficulties among women considering participation in the International Breast Cancer Intervention Study-II (IBIS-II) trial. Methods: The IBIS-II trial investigated breast cancer prevention with anastrazole in two cohorts: women with increased risk (Prevention), and women treated for ductal carcinoma in situ (DCIS). Australia, New Zealand and United Kingdom participants were randomised to receive a DA (DA group) or standard trial consent materials (control group). Questionnaires were completed after deciding about participation in IBIS-II (post decision) and 3 months later (follow-up). Results: Data from 112 Prevention and 34 DCIS participants were analysed post decision (73 DA; 73 control); 95 Prevention and 24 DCIS participants were analysed at follow-up (58 DA; 61 control). There was no effect on the primary outcome of decisional conflict. The DCIS–DA group had higher knowledge post decision, and the Prevention-DA group had lower decisional regret at follow-up. Conclusions: This was the first study to evaluate a DA in the clinical trial setting. The results suggest DAs can potentially increase knowledge and reduce decisional regret about clinical trial participation. PMID:24892447

[Factors influencing nurses' clinical decision making--focusing on critical thinking disposition].

PubMed

Park, Seungmi; Kwon, In Gak

2007-10-01

The purpose of this study was to investigate the factors influencing nurses' clinical decision making focusing on critical thinking disposition. The subjects of this study consisted of 505 nurses working at one of the general hospitals located in Seoul. Data was collected by a self-administered questionnaire between December 2006 and January 2007. Data was analyzed by one way ANOVA, Pearson correlation coefficients, and stepwise multiple regression using SPSS Win 14.0. The mean scores of critical thinking disposition and clinical decision making were 99.10 and 134.32 respectively. Clinical decision making scores were significantly higher in groups under continuing education, with a master or higher degree, with clinical experience more than 5 years, or with experts. Critical thinking disposition and its subscales have a significant correlation with clinical decision making. Intellectual eagerness/curiosity, prudence, clinical experience, intellectual honesty, self-confidence, and healthy skepticism were important factors influencing clinical decision making(adjusted R(2)=33%). Results of this study suggest that various strategies such as retaining experienced nurses, encouraging them to continue with education and enhancing critical thinking disposition are warranted for development of clinical decision making.

Understanding complex clinical reasoning in infectious diseases for improving clinical decision support design.

PubMed

Islam, Roosan; Weir, Charlene R; Jones, Makoto; Del Fiol, Guilherme; Samore, Matthew H

2015-11-30

Clinical experts' cognitive mechanisms for managing complexity have implications for the design of future innovative healthcare systems. The purpose of the study is to examine the constituents of decision complexity and explore the cognitive strategies clinicians use to control and adapt to their information environment. We used Cognitive Task Analysis (CTA) methods to interview 10 Infectious Disease (ID) experts at the University of Utah and Salt Lake City Veterans Administration Medical Center. Participants were asked to recall a complex, critical and vivid antibiotic-prescribing incident using the Critical Decision Method (CDM), a type of Cognitive Task Analysis (CTA). Using the four iterations of the Critical Decision Method, questions were posed to fully explore the incident, focusing in depth on the clinical components underlying the complexity. Probes were included to assess cognitive and decision strategies used by participants. The following three themes emerged as the constituents of decision complexity experienced by the Infectious Diseases experts: 1) the overall clinical picture does not match the pattern, 2) a lack of comprehension of the situation and 3) dealing with social and emotional pressures such as fear and anxiety. All these factors contribute to decision complexity. These factors almost always occurred together, creating unexpected events and uncertainty in clinical reasoning. Five themes emerged in the analyses of how experts deal with the complexity. Expert clinicians frequently used 1) watchful waiting instead of over- prescribing antibiotics, engaged in 2) theory of mind to project and simulate other practitioners' perspectives, reduced very complex cases into simple 3) heuristics, employed 4) anticipatory thinking to plan and re-plan events and consulted with peers to share knowledge, solicit opinions and 5) seek help on patient cases. The cognitive strategies to deal with decision complexity found in this study have important

Clinical Decision Making in the Management of Patients With Cervicogenic Dizziness: A Case Series.

PubMed

Jung, Francis C; Mathew, Sherin; Littmann, Andrew E; MacDonald, Cameron W

2017-11-01

Study Design Case series. Background Although growing recognition of cervicogenic dizziness (CGD) is emerging, there is still no gold standard for the diagnosis of CGD. The purpose of this case series is to describe the clinical decision making utilized in the management of 7 patients presenting with CGD. Case Description Patients presenting with neck pain and accompanying subjective symptoms, including dizziness, unsteadiness, light-headedness, and visual disturbance, were selected. Clinical evidence of a temporal relationship between neck pain and dizziness, with or without sensorimotor disturbances, was assessed. Clinical decision making followed a 4-step process, informed by the current available best evidence. Outcome measures included the numeric rating scale for dizziness and neck pain, the Dizziness Handicap Inventory, Patient-Specific Functional Scale, and global rating of change. Outcomes Seven patients (mean age, 57 years; range, 31-86 years; 7 female) completed physical therapy management at an average of 13 sessions (range, 8-30 sessions) over a mean of 7 weeks. Clinically meaningful improvements were observed in the numeric rating scale for dizziness (mean difference, 5.7; 95% confidence interval [CI]: 4.0, 7.5), neck pain (mean difference, 5.4; 95% CI: 3.8, 7.1), and the Dizziness Handicap Inventory (mean difference, 32.6; 95% CI: 12.9, 52.2) at discontinuation. Patients also demonstrated overall satisfaction via the Patient-Specific Functional Scale (mean difference, 9) and global rating of change (mean, +6). Discussion This case series describes the physical therapist decision making, management, and outcomes in patients with CGD. Further investigation is warranted to develop a valid clinical decision-making guideline to inform management of patients with CGD. Level of Evidence Diagnosis, therapy, level 4. J Orthop Sports Phys Ther 2017;47(11):874-884. Epub 9 Oct 2017. doi:10.2519/jospt.2017.7425.

Decision support for clinical laboratory capacity planning.

PubMed

van Merode, G G; Hasman, A; Derks, J; Goldschmidt, H M; Schoenmaker, B; Oosten, M

1995-01-01

The design of a decision support system for capacity planning in clinical laboratories is discussed. The DSS supports decisions concerning the following questions: how should the laboratory be divided into job shops (departments/sections), how should staff be assigned to workstations and how should samples be assigned to workstations for testing. The decision support system contains modules for supporting decisions at the overall laboratory level (concerning the division of the laboratory into job shops) and for supporting decisions at the job shop level (assignment of staff to workstations and sample scheduling). Experiments with these modules are described showing both the functionality and the validity.

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

[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.

Differing levels of clinical evidence: exploring communication challenges in shared decision making. Introduction.

PubMed

Smith, Quentin W; Street, Richard L; Volk, Robert J; Fordis, Michael

2013-02-01

The near ubiquitous access to information is transforming the roles and relationships among clinical professionals, patients, and their care givers in nearly all aspects of healthcare. Informed patients engage their physicians in conversations about their conditions, options and the tradeoffs among diagnostic and therapeutic benefits and harms. The processes of care today increasingly and explicitly integrate exploration of patient values and preferences as patients and clinicians jointly engage in reaching decisions about care. The informed patient of today who can understand and use scientific information can participate as an equal partner with her clinician. Others with beliefs or educational, cultural, or literacy backgrounds that pose challenges to comprehending and applying evidence may face disenfranchisement. These barriers are significant enough, even in the face of certainty of evidence, that clinicians and investigators have given much thought to how best to engage all patients in decision making. However, barriers remain, as most decision making must occur in settings where uncertainty, if not considerable uncertainty, accompanies any statement of what we know. In September 2011, health care and health communication experts came together in Rockville, Maryland under the auspices of the Agency for Healthcare Research and Quality (AHRQ) John M. Eisenberg Center for Clinical Decisions and Communications Science Annual Meeting to explore the challenges of differing levels of evidence in promoting shared decisions and to propose strategies for going forward in addressing these challenges. Eight scholarly papers emerged, and with this introductory article, comprise this special issue of Medical Care Research and Review.

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.

Four Factors of Clinical Decision Making: A Teaching Model.

ERIC Educational Resources Information Center

Leist, James C.; Konen, Joseph C.

1996-01-01

Four factors of clinical decision making identified by medical students include quality of care, cost, ethics, and legal concerns. This paper argues that physicians have two responsibilities in the clinical decision-making model: to be the primary advocate for quality health care and to ensure balance among the four factors, working in partnership…

Clinical Decision Making of Rural Novice Nurses

ERIC Educational Resources Information Center

Seright, Teresa J.

2010-01-01

The purpose of this study was to develop substantive theory regarding decision making by the novice nurse in a rural hospital setting. Interviews were guided by the following research questions: What cues were used by novice rural registered nurses in order to make clinical decisions? What were the sources of feedback which influenced subsequent…

Computerized clinical decision support systems for chronic disease management: A decision-maker-researcher partnership systematic review

PubMed Central

2011-01-01

Background The use of computerized clinical decision support systems (CCDSSs) may improve chronic disease management, which requires recurrent visits to multiple health professionals, ongoing disease and treatment monitoring, and patient behavior modification. The objective of this review was to determine if CCDSSs improve the processes of chronic care (such as diagnosis, treatment, and monitoring of disease) and associated patient outcomes (such as effects on biomarkers and clinical exacerbations). Methods We conducted a decision-maker-researcher partnership systematic review. We searched MEDLINE, EMBASE, Ovid's EBM Reviews database, Inspec, and reference lists for potentially eligible articles published up to January 2010. We included randomized controlled trials that compared the use of CCDSSs to usual practice or non-CCDSS controls. Trials were eligible if at least one component of the CCDSS was designed to support chronic disease management. We considered studies 'positive' if they showed a statistically significant improvement in at least 50% of relevant outcomes. Results Of 55 included trials, 87% (n = 48) measured system impact on the process of care and 52% (n = 25) of those demonstrated statistically significant improvements. Sixty-five percent (36/55) of trials measured impact on, typically, non-major (surrogate) patient outcomes, and 31% (n = 11) of those demonstrated benefits. Factors of interest to decision makers, such as cost, user satisfaction, system interface and feature sets, unique design and deployment characteristics, and effects on user workflow were rarely investigated or reported. Conclusions A small majority (just over half) of CCDSSs improved care processes in chronic disease management and some improved patient health. Policy makers, healthcare administrators, and practitioners should be aware that the evidence of CCDSS effectiveness is limited, especially with respect to the small number and size of studies measuring patient outcomes

Implementation of workflow engine technology to deliver basic clinical decision support functionality.

PubMed

Huser, Vojtech; Rasmussen, Luke V; Oberg, Ryan; Starren, Justin B

2011-04-10

Workflow engine technology represents a new class of software with the ability to graphically model step-based knowledge. We present application of this novel technology to the domain of clinical decision support. Successful implementation of decision support within an electronic health record (EHR) remains an unsolved research challenge. Previous research efforts were mostly based on healthcare-specific representation standards and execution engines and did not reach wide adoption. We focus on two challenges in decision support systems: the ability to test decision logic on retrospective data prior prospective deployment and the challenge of user-friendly representation of clinical logic. We present our implementation of a workflow engine technology that addresses the two above-described challenges in delivering clinical decision support. Our system is based on a cross-industry standard of XML (extensible markup language) process definition language (XPDL). The core components of the system are a workflow editor for modeling clinical scenarios and a workflow engine for execution of those scenarios. We demonstrate, with an open-source and publicly available workflow suite, that clinical decision support logic can be executed on retrospective data. The same flowchart-based representation can also function in a prospective mode where the system can be integrated with an EHR system and respond to real-time clinical events. We limit the scope of our implementation to decision support content generation (which can be EHR system vendor independent). We do not focus on supporting complex decision support content delivery mechanisms due to lack of standardization of EHR systems in this area. We present results of our evaluation of the flowchart-based graphical notation as well as architectural evaluation of our implementation using an established evaluation framework for clinical decision support architecture. We describe an implementation of a free workflow technology

The use of decision analysis to examine ethical decision making by critical care nurses.

PubMed

Hughes, K K; Dvorak, E M

1997-01-01

To examine the extent to which critical care staff nurses make ethical decisions that coincide with those recommended by a decision analytic model. Nonexperimental, ex post facto. Midwestern university-affiliated 500 bed tertiary care medical center. One hundred critical care staff nurses randomly selected from seven critical care units. Complete responses were obtained from 82 nurses (for a final response rate of 82%). The dependent variable--consistent decision making--was measured as staff nurses' abilities to make ethical decisions that coincided with those prescribed by the decision model. Subjects completed two instruments, the Ethical Decision Analytic Model, a computer-administered instrument designed to measure staff nurses' abilities to make consistent decisions about a chemically-impaired colleague; and a Background Inventory. The results indicate marked consensus among nurses when informal methods were used. However, there was little consistency between the nurses' informal decisions and those recommended by the decision analytic model. Although 50% (n = 41) of all nurses chose a course of action that coincided with the model's least optimal alternative, few nurses agreed with the model as to the most optimal course of action. The findings also suggest that consistency was unrelated (p > 0.05) to the nurses' educational background or years of clinical experience; that most subjects reported receiving little or no education in decision making during their basic nursing education programs; but that exposure to decision-making strategies was related to years of nursing experience (p < 0.05). The findings differ from related studies that have found a moderate degree of consistency between nurses and decision analytic models for strictly clinical decision tasks, especially when those tasks were less complex. However, the findings partially coincide with other findings that decision analysis may not be particularly well-suited to the critical care environment

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.

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.

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.

Impact of clinical and health services research projects on decision-making: a qualitative study

PubMed Central

2013-01-01

Background This article reports on the impact assessment experience of a funding program of non-commercial clinical and health services research. The aim was to assess the level of implementation of results from a subgroup of research projects (on respiratory diseases), and to detect barriers (or facilitators) in the translation of new knowledge to informed decision-making. Methods A qualitative study was performed. The sample consisted of six projects on respiratory diseases funded by the Agency for Health Quality and Assessment of Catalonia between 1996 and 2004. Semi-structured interviews to key informants including researchers and healthcare decision-makers were carried out. Interviews were recorded, transcribed verbatim and analysed on an individual (key informant) and group (project) basis. In addition, the differences between achieved and expected impacts were described. Results Twenty-three semi-structured interviews were conducted. Most participants indicated changes in health services or clinical practice had resulted from research. The channels used to transfer new knowledge were mainly conventional ones, but also in less explicit ways, such as with the involvement of local scientific societies, or via debates and discussions with colleagues and local leaders. The barriers and facilitators identified were mostly organizational (in research management, and clinical and healthcare practice), although there were also some related to the nature of the research as well as personal factors. Both the expected and achieved impacts enabled the identification of the gaps between what is expected and what is truly achieved. Conclusions In this study and according to key informants, the impact of these research projects on decision-making can be direct (the application of a finding or innovation) or indirect, contributing to a more complex change in clinical practice and healthcare organization, both having other contextual factors. The channels used to transfer

Clinical decision-making: predictors of patient participation in nursing care.

PubMed

Florin, Jan; Ehrenberg, Anna; Ehnfors, Margareta

2008-11-01

To investigate predictors of patients' preferences for participation in clinical decision-making in inpatient nursing care. Patient participation in decision-making in nursing care is regarded as a prerequisite for good clinical practice regarding the person's autonomy and integrity. A cross-sectional survey of 428 persons, newly discharged from inpatient care. The survey was conducted using the Control Preference Scale. Multiple logistic regression analysis was used for testing the association of patient characteristics with preferences for participation. Patients, in general, preferred adopting a passive role. However, predictors for adopting an active participatory role were the patient's gender (odds ratio = 1.8), education (odds ratio = 2.2), living condition (odds ratio = 1.8) and occupational status (odds ratio = 2.0). A probability of 53% was estimated, which female senior citizens with at least a high school degree and who lived alone would prefer an active role in clinical decision-making. At the same time, a working cohabiting male with less than a high school degree had a probability of 8% for active participation in clinical decision making in nursing care. Patient preferences for participation differed considerably and are best elicited by assessment of the individual patient. Relevance to clinical practice. The nurses have a professional responsibility to act in such a way that patients can participate and make decisions according to their own values from an informed position. Access to knowledge of patients'basic assumptions and preferences for participation is of great value for nurses in the care process. There is a need for nurses to use structured methods and tools for eliciting individual patient preferences regarding participation in clinical decision-making.

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

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.

Decision Analysis: Engineering Science or Clinical Art

DTIC Science & Technology

1979-11-01

TECHNICAL REPORT TR 79-2-97 DECISION ANALYSIS: ENGINEERING SCIENCE OR CLINICAL ART ? by Dennis M. Buede Prepared for Defense Advanced Research...APPLICATIONS OF THE ENGINEER- ING SCIENCE AND CLINICAL ART EXTREMES 9 3.1 Applications of the Engineering Science Approach 9 3.1.1 Mexican electrical...DISCUSSION 29 4.1 Engineering Science versus Clinical Art : A Characterization of When Each is Most Attractive 30 4.2 The Implications of the Engineering

Advancing clinical decision support using lessons from outside of healthcare: an interdisciplinary systematic review

PubMed Central

2012-01-01

Background Greater use of computerized decision support (DS) systems could address continuing safety and quality problems in healthcare, but the healthcare field has struggled to implement DS technology. This study surveys DS experience across multiple non-healthcare disciplines for new insights that are generalizable to healthcare provider decisions. In particular, it sought design principles and lessons learned from the other disciplines that could inform efforts to accelerate the adoption of clinical decision support (CDS). Methods Our systematic review drew broadly from non-healthcare databases in the basic sciences, social sciences, humanities, engineering, business, and defense: PsychINFO, BusinessSource Premier, Social Sciences Abstracts, Web of Science, and Defense Technical Information Center. Because our interest was in DS that could apply to clinical decisions, we selected articles that (1) provided a review, overview, discussion of lessons learned, or an evaluation of design or implementation aspects of DS within a non-healthcare discipline and (2) involved an element of human judgment at the individual level, as opposed to decisions that can be fully automated or that are made at the organizational level. Results Clinical decisions share some similarities with decisions made by military commanders, business managers, and other leaders: they involve assessing new situations and choosing courses of action with major consequences, under time pressure, and with incomplete information. We identified seven high-level DS system design features from the non-healthcare literature that could be applied to CDS: providing broad, system-level perspectives; customizing interfaces to specific users and roles; making the DS reasoning transparent; presenting data effectively; generating multiple scenarios covering disparate outcomes (e.g., effective; effective with side effects; ineffective); allowing for contingent adaptations; and facilitating collaboration. The

[Clinical decision making and critical thinking in the nursing diagnostic process].

PubMed

Müller-Staub, Maria

2006-10-01

The daily routine requires complex thinking processes of nurses, but clinical decision making and critical thinking are underestimated in nursing. A great demand for educational measures in clinical judgement related with the diagnostic process was found in nurses. The German literature hardly describes nursing diagnoses as clinical judgements about human reactions on health problems / life processes. Critical thinking is described as an intellectual, disciplined process of active conceptualisation, application and synthesis of information. It is gained through observation, experience, reflection and communication and leads thinking and action. Critical thinking influences the aspects of clinical decision making a) diagnostic judgement, b) therapeutic reasoning and c) ethical decision making. Human reactions are complex processes and in their course, human behavior is interpreted in the focus of health. Therefore, more attention should be given to the nursing diagnostic process. This article presents the theoretical framework of the paper "Clinical decision making: Fostering critical thinking in the nursing diagnostic process through case studies".

Clinical decision making in dermatology: observation of consultations and the patients' perspectives.

PubMed

Hajjaj, F M; Salek, M S; Basra, M K A; Finlay, A Y

2010-01-01

Clinical decision making is a complex process and might be influenced by a wide range of clinical and non-clinical factors. Little is known about this process in dermatology. The aim of this study was to explore the different types of management decisions made in dermatology and to identify factors influencing those decisions from observation of consultations and interviews with the patients. 61 patient consultations were observed by a physician with experience in dermatology. The patients were interviewed immediately after each consultation. Consultations and interviews were audio recorded, transcribed and their content analysed using thematic content analysis. The most common management decisions made during the consultations included: follow-up, carrying out laboratory investigation, starting new topical treatment, renewal of systemic treatment, renewal of topical treatment, discharging patients and starting new systemic treatment. Common influences on those decisions included: clinical factors such as ineffectiveness of previous therapy, adherence to prescribing guidelines, side-effects of medications, previous experience with the treatment, deterioration or improvement in the skin condition, and chronicity of skin condition. Non-clinical factors included: patient's quality of life, patient's friends or relatives, patient's time commitment, travel or transportation difficulties, treatment-related costs, availability of consultant, and availability of treatment. The study has shown that patients are aware that management decisions in dermatology are influenced by a wide range of clinical and non-clinical factors. Education programmes should be developed to improve the quality of decision making. Copyright © 2010 S. Karger AG, Basel.

Clinical decision-making of rural novice nurses.

PubMed

Seright, T J

2011-01-01

Nurses in rural settings are often the first to assess and interpret the patient's clinical presentations. Therefore, an understanding of how nurses experience decision-making is important in terms of educational preparation, resource allocation to rural areas, institutional cultures, and patient outcomes. Theory development was based on the in-depth investigation of 12 novice nurses practicing in rural critical access hospitals in a north central state. This grounded theory study consisted of face-to-face interviews with 12 registered nurses, nine of whom were observed during their work day. The participants were interviewed a second time, as a method of member checking, and during this interview they reviewed their transcripts, the emerging themes and categories. Directors of nursing from both the research sites and rural hospitals not involved in the study, experienced researchers, and nurse educators facilitated triangulation of the findings. 'Sociocentric rationalizing' emerged as the central phenomenon and referred to the sense of belonging and agency which impacted the decision-making in this small group of novice nurses in rural critical access hospitals. The observed consequences, which were conceptualized during the axial coding process and were derived from observations and interviews of the 12 novice nurses in this study include: (1) gathering information before making a decision included assessment of: the credibility of co-workers, patients' subjective and objective data, and one's own past and current experiences; (2) conferring with co-workers as a direct method of confirming/denying decisions being made was considered more realistic and expedient than policy books and decision trees; (3) rural practicum clinical experiences, along with support after orientation, provide for transition to the rural nurse role; (4) involved directors of nursing served as both models and protectors of novice nurses placed in high accountability positions early in

Clinical decision-making among new graduate nurses attending residency programs in Saudi Arabia.

PubMed

Al-Dossary, Reem Nassar; Kitsantas, Panagiota; Maddox, P J

2016-02-01

This study examined the impact of residency programs on clinical decision-making of new Saudi graduate nurses who completed a residency program compared to new Saudi graduate nurses who did not participate in residency programs. This descriptive study employed a convenience sample (N=98) of new graduate nurses from three hospitals in Saudi Arabia. A self-administered questionnaire was used to collect data. Clinical decision-making skills were measured using the Clinical Decision Making in Nursing Scale. Descriptive statistics, independent t-tests, and multiple linear regression analysis were utilized to examine the effect of residency programs on new graduate nurses' clinical decision-making skills. On average, resident nurses had significantly higher levels of clinical decision-making skills than non-residents (t=23.25, p=0.000). Enrollment in a residency program explained 86.9% of the variance in total clinical decision making controlling for age and overall grade point average. The findings of this study support evidence in the nursing literature conducted primarily in the US and Europe that residency programs have a positive influence on new graduate nurses' clinical decision-making skills. This is the first study to examine the impact of residency programs on clinical decision-making among new Saudi graduate nurses who completed a residency program. The findings of this study underscore the need for the development and implementation of residency programs for all new nurses. Copyright © 2015 Elsevier Inc. All rights reserved.

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

Clinical Decisions Made in Primary Care Clinics Before and After Choosing Wisely.

PubMed

Kost, Amanda; Genao, Inginia; Lee, Jay W; Smith, Stephen R

2015-01-01

The Choosing Wisely campaign encourages physicians to avoid low-value care. Although widely lauded, no study has examined its impact on clinical decisions made in primary care settings. We compared clinical decisions made for 5 Choosing Wisely recommendations over two 6-month time periods before and after the campaign launch and an educational intervention to promote it at 3 primary care residency clinics. The rate of recommendations adherence was high (93.2%) at baseline but did significantly increase to 96.5% after the launch. These findings suggest primary care physicians respond to training and publicity in low-value care, though further research is needed. Given that even small decreases of physician test ordering can produce large cost savings, the Choosing Wisely project may help achieve the health care triple aim. © Copyright 2015 by the American Board of Family Medicine.

An integrated, ethically driven environmental model of clinical decision making in emergency settings.

PubMed

Wolf, Lisa

2013-02-01

To explore the relationship between multiple variables within a model of critical thinking and moral reasoning. A quantitative descriptive correlational design using a purposive sample of 200 emergency nurses. Measured variables were accuracy in clinical decision-making, moral reasoning, perceived care environment, and demographics. Analysis was by bivariate correlation using Pearson's product-moment correlation coefficients, chi square and multiple linear regression analysis. The elements as identified in the integrated ethically-driven environmental model of clinical decision-making (IEDEM-CD) corrected depict moral reasoning and environment of care as factors significantly affecting accuracy in decision-making. The integrated, ethically driven environmental model of clinical decision making is a framework useful for predicting clinical decision making accuracy for emergency nurses in practice, with further implications in education, research and policy. A diagnostic and therapeutic framework for identifying and remediating individual and environmental challenges to accurate clinical decision making. © 2012, The Author. International Journal of Nursing Knowledge © 2012, NANDA International.

Classifying clinical decision making: interpreting nursing intuition, heuristics and medical diagnosis.

PubMed

Buckingham, C D; Adams, A

2000-10-01

This is the second of two linked papers exploring decision making in nursing. The first paper, 'Classifying clinical decision making: a unifying approach' investigated difficulties with applying a range of decision-making theories to nursing practice. This is due to the diversity of terminology and theoretical concepts used, which militate against nurses being able to compare the outcomes of decisions analysed within different frameworks. It is therefore problematic for nurses to assess how good their decisions are, and where improvements can be made. However, despite the range of nomenclature, it was argued that there are underlying similarities between all theories of decision processes and that these should be exposed through integration within a single explanatory framework. A proposed solution was to use a general model of psychological classification to clarify and compare terms, concepts and processes identified across the different theories. The unifying framework of classification was described and this paper operationalizes it to demonstrate how different approaches to clinical decision making can be re-interpreted as classification behaviour. Particular attention is focused on classification in nursing, and on re-evaluating heuristic reasoning, which has been particularly prone to theoretical and terminological confusion. Demonstrating similarities in how different disciplines make decisions should promote improved multidisciplinary collaboration and a weakening of clinical elitism, thereby enhancing organizational effectiveness in health care and nurses' professional status. This is particularly important as nurses' roles continue to expand to embrace elements of managerial, medical and therapeutic work. Analysing nurses' decisions as classification behaviour will also enhance clinical effectiveness, and assist in making nurses' expertise more visible. In addition, the classification framework explodes the myth that intuition, traditionally associated

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.

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.

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.

Designing and evaluating an interprofessional shared decision-making and goal-setting decision aid for patients with diabetes in clinical care - systematic decision aid development and study protocol

PubMed Central

2014-01-01

Background Care of patients with diabetes often occurs in the context of other chronic illness. Competing disease priorities and competing patient-physician priorities present challenges in the provision of care for the complex patient. Guideline implementation interventions to date do not acknowledge these intricacies of clinical practice. As a result, patients and providers are left overwhelmed and paralyzed by the sheer volume of recommendations and tasks. An individualized approach to the patient with diabetes and multiple comorbid conditions using shared decision-making (SDM) and goal setting has been advocated as a patient-centred approach that may facilitate prioritization of treatment options. Furthermore, incorporating interprofessional integration into practice may overcome barriers to implementation. However, these strategies have not been taken up extensively in clinical practice. Objectives To systematically develop and test an interprofessional SDM and goal-setting toolkit for patients with diabetes and other chronic diseases, following the Knowledge to Action framework. Methods 1. Feasibility study: Individual interviews with primary care physicians, nurses, dietitians, pharmacists, and patients with diabetes will be conducted, exploring their experiences with shared decision-making and priority-setting, including facilitators and barriers, the relevance of a decision aid and toolkit for priority-setting, and how best to integrate it into practice. 2. Toolkit development: Based on this data, an evidence-based multi-component SDM toolkit will be developed. The toolkit will be reviewed by content experts (primary care, endocrinology, geriatricians, nurses, dietitians, pharmacists, patients) for accuracy and comprehensiveness. 3. Heuristic evaluation: A human factors engineer will review the toolkit and identify, list and categorize usability issues by severity. 4. Usability testing: This will be done using cognitive task analysis. 5. Iterative

The Relationship Between the Clinical Orientation of Substance Abuse Professionals and Their Clinical Decisions

ERIC Educational Resources Information Center

Toriello, Paul J.; Leierer, Stephen J.

2005-01-01

In this study, the authors examined the relationship between the clinical orientations of substance abuse professionals (SAPs) and their clinical decisions. Cluster analysis grouped a sample of 245 SAPs on two clinical orientations that differed in their relative endorsement of traditional versus contemporary substance abuse counseling processes…

Clinical Decision Support Tools for Osteoporosis Disease Management: A Systematic Review of Randomized Controlled Trials

PubMed Central

Straus, Sharon E.

2008-01-01

BACKGROUND Studies indicate a gap between evidence and clinical practice in osteoporosis management. Tools that facilitate clinical decision making at the point of care are promising strategies for closing these practice gaps. OBJECTIVE To systematically review the literature to identify and describe the effectiveness of tools that support clinical decision making in osteoporosis disease management. DATA SOURCES Medline, EMBASE, CINAHL, and EBM Reviews (CDSR, DARE, CCTR, and ACP J Club), and contact with experts in the field. REVIEW METHODS Randomized controlled trials (RCTs) in any language from 1966 to July 2006 investigating disease management interventions in patients at risk for osteoporosis. Outcomes included fractures and bone mineral density (BMD) testing. Two investigators independently assessed articles for relevance and study quality, and extracted data using standardized forms. RESULTS Of 1,246 citations that were screened for relevance, 13 RCTs met the inclusion criteria. Reported study quality was generally poor. Meta-analysis was not done because of methodological and clinical heterogeneity; 77% of studies included a reminder or education as a component of their intervention. Three studies of reminders plus education targeted to physicians and patients showed increased BMD testing (RR range 1.43 to 8.67) and osteoporosis medication use (RR range 1.60 to 8.67). A physician reminder plus a patient risk assessment strategy found reduced fractures [RR 0.58, 95% confidence interval (CI) 0.37 to 0.90] and increased osteoporosis therapy (RR 2.44, CI 1.43 to 4.17). CONCLUSION Multi-component tools that are targeted to physicians and patients may be effective for supporting clinical decision making in osteoporosis disease management. Electronic supplementary material The online version of this article (doi:10.1007/s11606-008-0812-9) contains supplementary material, which is available to authorized users. PMID:18836782

A study to derive a clinical decision rule for triage of emergency department patients with chest pain: design and methodology

PubMed Central

Hess, Erik P; Wells, George A; Jaffe, Allan; Stiell, Ian G

2008-01-01

Background Chest pain is the second most common chief complaint in North American emergency departments. Data from the U.S. suggest that 2.1% of patients with acute myocardial infarction and 2.3% of patients with unstable angina are misdiagnosed, with slightly higher rates reported in a recent Canadian study (4.6% and 6.4%, respectively). Information obtained from the history, 12-lead ECG, and a single set of cardiac enzymes is unable to identify patients who are safe for early discharge with sufficient sensitivity. The 2007 ACC/AHA guidelines for UA/NSTEMI do not identify patients at low risk for adverse cardiac events who can be safely discharged without provocative testing. As a result large numbers of low risk patients are triaged to chest pain observation units and undergo provocative testing, at significant cost to the healthcare system. Clinical decision rules use clinical findings (history, physical exam, test results) to suggest a diagnostic or therapeutic course of action. Currently no methodologically robust clinical decision rule identifies patients safe for early discharge. Methods/design The goal of this study is to derive a clinical decision rule which will allow emergency physicians to accurately identify patients with chest pain who are safe for early discharge. The study will utilize a prospective cohort design. Standardized clinical variables will be collected on all patients at least 25 years of age complaining of chest pain prior to provocative testing. Variables strongly associated with the composite outcome acute myocardial infarction, revascularization, or death will be further analyzed with multivariable analysis to derive the clinical rule. Specific aims are to: i) apply standardized clinical assessments to patients with chest pain, incorporating results of early cardiac testing; ii) determine the inter-observer reliability of the clinical information; iii) determine the statistical association between the clinical findings and the

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.

The role of emotions in clinical reasoning and decision making.

PubMed

Marcum, James A

2013-10-01

What role, if any, should emotions play in clinical reasoning and decision making? Traditionally, emotions have been excluded from clinical reasoning and decision making, but with recent advances in cognitive neuropsychology they are now considered an important component of them. Today, cognition is thought to be a set of complex processes relying on multiple types of intelligences. The role of mathematical logic (hypothetico-deductive thinking) or verbal linguistic intelligence in cognition, for example, is well documented and accepted; however, the role of emotional intelligence has received less attention-especially because its nature and function are not well understood. In this paper, I argue for the inclusion of emotions in clinical reasoning and decision making. To that end, developments in contemporary cognitive neuropsychology are initially examined and analyzed, followed by a review of the medical literature discussing the role of emotions in clinical practice. Next, a published clinical case is reconstructed and used to illustrate the recognition and regulation of emotions played during a series of clinical consultations, which resulted in a positive medical outcome. The paper's main thesis is that emotions, particularly in terms of emotional intelligence as a practical form of intelligence, afford clinical practitioners a robust cognitive resource for providing quality medical care.

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.

A study of diverse clinical decision support rule authoring environments and requirements for integration

PubMed Central

2012-01-01

Background Efficient rule authoring tools are critical to allow clinical Knowledge Engineers (KEs), Software Engineers (SEs), and Subject Matter Experts (SMEs) to convert medical knowledge into machine executable clinical decision support rules. The goal of this analysis was to identify the critical success factors and challenges of a fully functioning Rule Authoring Environment (RAE) in order to define requirements for a scalable, comprehensive tool to manage enterprise level rules. Methods The authors evaluated RAEs in active use across Partners Healthcare, including enterprise wide, ambulatory only, and system specific tools, with a focus on rule editors for reminder and medication rules. We conducted meetings with users of these RAEs to discuss their general experience and perceived advantages and limitations of these tools. Results While the overall rule authoring process is similar across the 10 separate RAEs, the system capabilities and architecture vary widely. Most current RAEs limit the ability of the clinical decision support (CDS) interventions to be standardized, sharable, interoperable, and extensible. No existing system meets all requirements defined by knowledge management users. Conclusions A successful, scalable, integrated rule authoring environment will need to support a number of key requirements and functions in the areas of knowledge representation, metadata, terminology, authoring collaboration, user interface, integration with electronic health record (EHR) systems, testing, and reporting. PMID:23145874

Automating Guidelines for Clinical Decision Support: Knowledge Engineering and Implementation.

PubMed

Tso, Geoffrey J; Tu, Samson W; Oshiro, Connie; Martins, Susana; Ashcraft, Michael; Yuen, Kaeli W; Wang, Dan; Robinson, Amy; Heidenreich, Paul A; Goldstein, Mary K

2016-01-01

As utilization of clinical decision support (CDS) increases, it is important to continue the development and refinement of methods to accurately translate the intention of clinical practice guidelines (CPG) into a computable form. In this study, we validate and extend the 13 steps that Shiffman et al. 5 identified for translating CPG knowledge for use in CDS. During an implementation project of ATHENA-CDS, we encoded complex CPG recommendations for five common chronic conditions for integration into an existing clinical dashboard. Major decisions made during the implementation process were recorded and categorized according to the 13 steps. During the implementation period, we categorized 119 decisions and identified 8 new categories required to complete the project. We provide details on an updated model that outlines all of the steps used to translate CPG knowledge into a CDS integrated with existing health information technology.

mHealth for Clinical Decision-Making in Sub-Saharan Africa: A Scoping Review

PubMed Central

Albersen, Bregje Joanna Antonia; De Brouwere, Vincent; van Roosmalen, Jos; Zweekhorst, Marjolein

2017-01-01

Background In a bid to deliver quality health services in resource-poor settings, mobile health (mHealth) is increasingly being adopted. The role of mHealth in facilitating evidence-based clinical decision-making through data collection, decision algorithms, and evidence-based guidelines, for example, is established in resource-rich settings. However, the extent to which mobile clinical decision support systems (mCDSS) have been adopted specifically in resource-poor settings such as Africa and the lessons learned about their use in such settings are yet to be established. Objective The aim of this study was to synthesize evidence on the use of mHealth for point-of-care decision support and improved quality of care by health care workers in Africa. Methods A scoping review of 4 peer-reviewed and 1 grey literature databases was conducted. No date limits were applied, but only articles in English language were selected. Using pre-established criteria, 2 reviewers screened articles and extracted data. Articles were analyzed using Microsoft Excel and MAXQDA. Results We retained 22 articles representing 11 different studies in 7 sub-Saharan African countries. Interventions were mainly in the domain of maternal health and ranged from simple text messaging (short message service, SMS) to complex multicomponent interventions. Although health workers are generally supportive of mCDSS and perceive them as useful, concerns about increased workload and altered workflow hinder sustainability. Facilitators and barriers to use of mCDSS include technical and infrastructural support, ownership, health system challenges, and training. Conclusions The use of mCDSS in sub-Saharan Africa is an indication of progress in mHealth, although their effect on quality of service delivery is yet to be fully explored. Lessons learned are useful for informing future research, policy, and practice for technologically supported health care delivery, especially in resource-poor settings. PMID

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.

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.

Reducing Risk with Clinical Decision Support

PubMed Central

Maloney, F.L.; Feblowitz, J.; Samal, L.; Sato, L.; Wright, A.

2014-01-01

Summary Objective Identify clinical opportunities to intervene to prevent a malpractice event and determine the proportion of malpractice claims potentially preventable by clinical decision support (CDS). Materials and Methods Cross-sectional review of closed malpractice claims over seven years from one malpractice insurance company and seven hospitals in the Boston area. For each event, clinical opportunities to intervene to avert the malpractice event and the presence or absence of CDS that might have a role in preventing the event, were assigned by a panel of expert raters. Compensation paid out to resolve a claim (indemnity), was associated with each CDS type. Results Of the 477 closed malpractice cases, 359 (75.3%) were categorized as substantiated and 195 (54%) had at least one opportunity to intervene. Common opportunities to intervene related to performance of procedure, diagnosis, and fall prevention. We identified at least one CDS type for 63% of substantiated claims. The 41 CDS types identified included clinically significant test result alerting, diagnostic decision support and electronic tracking of instruments. Cases with at least one associated intervention accounted for $40.3 million (58.9%) of indemnity. Discussion CDS systems and other forms of health information technology (HIT) are expected to improve quality of care, but their potential to mitigate risk had not previously been quantified. Our results suggest that, in addition to their known benefits for quality and safety, CDS systems within HIT have a potential role in decreasing malpractice payments. Conclusion More than half of malpractice events and over $40 million of indemnity were potentially preventable with CDS. PMID:25298814

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.

Are patient decision aids the best way to improve clinical decision making? Report of the IPDAS Symposium.

PubMed

Holmes-Rovner, Margaret; Nelson, Wendy L; Pignone, Michael; Elwyn, Glyn; Rovner, David R; O'Connor, Annette M; Coulter, Angela; Correa-de-Araujo, Rosaly

2007-01-01

This article reports on the International Patient Decision Aid Standards Symposium held in 2006 at the annual meeting of the Society for Medical Decision Making in Cambridge, Massachusetts. The symposium featured a debate regarding the proposition that "decision aids are the best way to improve clinical decision making.'' The formal debate addressed the theoretical problem of the appropriate gold standard for an improved decision, efficacy of decision aids, and prospects for implementation. Audience comments and questions focused on both theory and practice: the often unacknowledged roots of decision aids in expected utility theory and the practical problems of limited patient decision aid implementation in health care. The participants' vote on the proposition was approximately half for and half against.

What can Natural Language Processing do for Clinical Decision Support?

PubMed Central

Demner-Fushman, Dina; Chapman, Wendy W.; McDonald, Clement J.

2009-01-01

Computerized Clinical Decision Support (CDS) aims to aid decision making of health care providers and the public by providing easily accessible health-related information at the point and time it is needed. Natural Language Processing (NLP) is instrumental in using free-text information to drive CDS, representing clinical knowledge and CDS interventions in standardized formats, and leveraging clinical narrative. The early innovative NLP research of clinical narrative was followed by a period of stable research conducted at the major clinical centers and a shift of mainstream interest to biomedical NLP. This review primarily focuses on the recently renewed interest in development of fundamental NLP methods and advances in the NLP systems for CDS. The current solutions to challenges posed by distinct sublanguages, intended user groups, and support goals are discussed. PMID:19683066

Instruments to assess the perception of physicians in the decision-making process of specific clinical encounters: a systematic review

PubMed Central

Légaré, France; Moher, David; Elwyn, Glyn; LeBlanc, Annie; Gravel, Karine

2007-01-01

Background The measurement of processes and outcomes that reflect the complexity of the decision-making process within specific clinical encounters is an important area of research to pursue. A systematic review was conducted to identify instruments that assess the perception physicians have of the decision-making process within specific clinical encounters. Methods For every year available up until April 2007, PubMed, PsycINFO, Current Contents, Dissertation Abstracts and Sociological Abstracts were searched for original studies in English or French. Reference lists from retrieved studies were also consulted. Studies were included if they reported a self-administered instrument evaluating physicians' perceptions of the decision-making process within specific clinical encounters, contained sufficient description to permit critical appraisal and presented quantitative results based on administering the instrument. Two individuals independently assessed the eligibility of the instruments and abstracted information on their conceptual underpinnings, main evaluation domain, development, format, reliability, validity and responsiveness. They also assessed the quality of the studies that reported on the development of the instruments with a modified version of STARD. Results Out of 3431 records identified and screened for evaluation, 26 potentially relevant instruments were assessed; 11 met the inclusion criteria. Five instruments were published before 1995. Among those published after 1995, five offered a corresponding patient version. Overall, the main evaluation domains were: satisfaction with the clinical encounter (n = 2), mutual understanding between health professional and patient (n = 2), mental workload (n = 1), frustration with the clinical encounter (n = 1), nurse-physician collaboration (n = 1), perceptions of communication competence (n = 2), degree of comfort with a decision (n = 1) and information on medication (n = 1). For most instruments (n = 10), some

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.

Postnatal Psychosocial Assessment and Clinical Decision-Making, a Descriptive Study.

PubMed

Sims, Deborah; Fowler, Cathrine

2018-05-18

The aim of this study is to describe experienced child and family health nurses' clinical decision-making during a postnatal psychosocial assessment. Maternal emotional wellbeing in the postnatal year optimises parenting and promotes infant development. Psychosocial assessment potentially enables early intervention and reduces the risk of a mental disorder occurring during this time of change. Assessment accuracy, and the interventions used are determined by the standard of nursing decision-making. A qualitative methodology was employed to explore decision-making behaviour when conducting a postnatal psychosocial assessment. This study was conducted in an Australian early parenting organisation. Twelve experienced child and family health nurses were interviewed. A detailed description of a postnatal psychosocial assessment process was obtained using a critical incident technique. Template analysis was used to determine the information domains the nurses accessed, and content analysis was used to determine the nurses' thinking strategies, to make clinical decisions from this assessment. The nurses described 24 domains of information and used 17 thinking strategies, in a variety of combinations. The four information domains most commonly used were parenting, assessment tools, women-determined issues and sleep. The seven thinking strategies most commonly used were searching for information, forming relationships between the information, recognising a pattern, drawing a conclusion, setting priorities, providing explanations for the information and judging the value of the information. The variety and complexity of the clinical decision-making involved in postnatal psychosocial assessment confirms that the nurses use information appropriately and within their scope of nursing practice. The standard of clinical decision-making determines the results of the assessment and the optimal access to care. Knowledge of the information domains and the decision-making strategies

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

SANDS: an architecture for clinical decision support in a National Health Information Network.

PubMed

Wright, Adam; Sittig, Dean F

2007-10-11

A new architecture for clinical decision support called SANDS (Service-oriented Architecture for NHIN Decision Support) is introduced and its performance evaluated. The architecture provides a method for performing clinical decision support across a network, as in a health information exchange. Using the prototype we demonstrated that, first, a number of useful types of decision support can be carried out using our architecture; and, second, that the architecture exhibits desirable reliability and performance characteristics.

[Cancer screening in clinical practice: the value of shared decision-making].

PubMed

Cornuz, Jacques; Junod, Noëlle; Pasche, Olivier; Guessous, Idris

2010-07-14

Shared decision-making approach to uncertain clinical situations such as cancer screening seems more appropriate than ever. Shared decision making can be defined as an interactive process where physician and patient share all the stages of the decision making process. For patients who wish to be implicated in the management of their health conditions, physicians might express difficulty to do so. Use of patient decision aids appears to improve such process of shared decision making.

Applying a family systems lens to proxy decision making in clinical practice and research.

PubMed

Rolland, John S; Emanuel, Linda L; Torke, Alexia M

2017-03-01

When patients are incapacitated and face serious illness, family members must make medical decisions for the patient. Medical decision sciences give only modest attention to the relationships among patients and their family members, including impact that these relationships have on the decision-making process. A review of the literature reveals little effort to systematically apply a theoretical framework to the role of family interactions in proxy decision making. A family systems perspective can provide a useful lens through which to understand the dynamics of proxy decision making. This article considers the mutual impact of family systems on the processes and outcomes of proxy decision making. The article first reviews medical decision science's evolution and focus on proxy decision making and then reviews a family systems approach, giving particular attention to Rolland's Family Systems Illness Model. A case illustrates how clinical practice and how research would benefit from bringing family systems thinking to proxy decisions. We recommend including a family systems approach in medical decision science research and clinical practices around proxy decisions making. We propose that clinical decisions could be less conflicted and less emotionally troubling for families and clinicians if family systems approaches were included. This perspective opens new directions for research and novel approaches to clinical care. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Clinical decision support tool for Co-management signalling.

PubMed

Horta, Alexandra Bayão; Salgado, Cátia; Fernandes, Marta; Vieira, Susana; Sousa, João M; Papoila, Ana Luísa; Xavier, Miguel

2018-05-01

Co-management between internists and surgeons of selected patients is becoming one of the pillars of modern clinical management in large hospitals. Defining the patients to be co-managed is essential. The aim of this study is to create a decision tool using real-world patient data collected in the preoperative period, to support the decision on which patients should have the co-management service offered. Data was collected from the electronic clinical health records of patients who had an International Classification of Diseases, 9th edition (ICD-9) code of colorectal surgery during the period between January 2012 and October 2014 in a 200 bed private teaching hospital in Lisbon. ICD-9 codes of colorectal surgery [48.5 and 48.6 (anterior rectal resection and abdominoperineal resection), 45.7 (partial colectomy), 45.8 (Total Colectomy), and 45.9 (Bowel Anastomosis)] were used. Only patients above 18 years old were considered. Patients with more than one procedure were excluded from the study. From these data the authors investigated the construction of predictive models using logistic regression and Takagi-Sugeno fuzzy modelling. Data contains information obtained from the clinical records of a cohort of 344 adult patients. Data from 398 emergent and elective surgeries were collected, from which 54 were excluded because they were second procedures for the same patients. Four preoperative variables were identified as being the most predictive of co-management, in multivariable regression analysis. The final model performed well after being internally validated (0.81 AUC, 77% accuracy, 74% sensitivity, 78% specificity, 93% negative predictive value). The results indicate that the decision process can be more objective and potentially automated. The authors developed a prediction model based on preoperative characteristics, in order to support the decision for the co-management of surgical patients in the postoperative ward setting. The model is a simple bedside

The clinical utility index as a practical multiattribute approach to drug development decisions.

PubMed

Poland, B; Hodge, F L; Khan, A; Clemen, R T; Wagner, J A; Dykstra, K; Krishna, R

2009-07-01

We identify some innovative approaches to predicting overall patient benefit from investigational drugs to support development decisions. We then illustrate calculation of a probabilistic clinical utility index (CUI), an implementation of multiattribute utility that focuses on clinical attributes. We recommend use of the CUI for the support of early drug development decisions because of its practicality, reasonable accuracy, and transparency to decision makers, at stages in which financial factors that may dominate later-phase decisions are less critical.

[Clinical decision making: Fostering critical thinking in the nursing diagnostic process through case studies].

PubMed

Müller-Staub, Maria; Stuker-Studer, Ursula

2006-10-01

Case studies, based on actual patients' situations, provide a method of clinical decision making to foster critical thinking in nurses. This paper describes the method and process of group case studies applied in continuous education settings. This method bases on Balints' case supervision and was further developed and combined with the nursing diagnostic process. A case study contains different phases: Pre-phase, selection phase, case delineation and case work. The case provider narratively tells the situation of a patient. This allows the group to analyze and cluster signs and symptoms, to state nursing diagnoses and to derive nursing interventions. Results of the case study are validated by applying the theoretical background and critical appraisal of the case provider. Learning effects of the case studies were evaluated by means of qualitative questionnaires and analyzed according to Mayring. Findings revealed the following categories: a) Patients' problems are perceived in a patient centred way, accurate nursing diagnoses are stated and effective nursing interventions implemented. b) Professional nursing tasks are more purposefully perceived and named more precise. c) Professional nursing relationship, communication and respectful behaviour with patients were perceived in differentiated ways. The theoretical framework is described in the paper "Clinical decision making and critical thinking in the nursing diagnostic process". (Müller-Staub, 2006).

The thinking doctor: clinical decision making in contemporary medicine.

PubMed

Trimble, Michael; Hamilton, Paul

2016-08-01

Diagnostic errors are responsible for a significant number of adverse events. Logical reasoning and good decision-making skills are key factors in reducing such errors, but little emphasis has traditionally been placed on how these thought processes occur, and how errors could be minimised. In this article, we explore key cognitive ideas that underpin clinical decision making and suggest that by employing some simple strategies, physicians might be better able to understand how they make decisions and how the process might be optimised. © 2016 Royal College of Physicians.

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…

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…

Experiential and rational decision making: a survey to determine how emergency physicians make clinical decisions.

PubMed

Calder, Lisa A; Forster, Alan J; Stiell, Ian G; Carr, Laura K; Brehaut, Jamie C; Perry, Jeffrey J; Vaillancourt, Christian; Croskerry, Patrick

2012-10-01

Dual-process psychological theories argue that clinical decision making is achieved through a combination of experiential (fast and intuitive) and rational (slower and systematic) cognitive processes. To determine whether emergency physicians perceived their clinical decisions in general to be more experiential or rational and how this compared with other physicians. A validated psychometric tool, the Rational Experiential Inventory (REI-40), was sent through postal mail to all emergency physicians registered with the College of Physicians and Surgeons of Ontario, according to their website in November 2009. Forty statements were ranked on a Likert scale from 1 (Definitely False) to 5 (Definitely True). An initial survey was sent out, followed by reminder cards and a second survey to non-respondents. Analysis included descriptive statistics, Student t tests, analysis of variance and comparison of mean scores with those of cardiologists from New Zealand. The response rate in this study was 46.9% (434/925). The respondents' median age was 41-50 years; they were mostly men (72.6%) and most had more than 10 years of clinical experience (66.8%). The mean REI-40 rational scores were higher than the experiential scores (3.93/5 (SD 0.35) vs 3.33/5 (SD 0.49), p<0.0001), similar to the mean scores of cardiologists from New Zealand (mean rational 3.93/5, mean experiential 3.05/5). The mean experiential scores were significantly higher for female respondents than for male respondents (3.40/5 (SD 0.49) vs 3.30/5 (SD 0.48), p=0.003). Overall, emergency physicians favoured rational decision making rather than experiential decision making; however, female emergency physicians had higher experiential scores than male emergency physicians. This has important implications for future knowledge translation and decision support efforts among emergency physicians.

Clinical staging: its importance in therapeutic decisions and clinical trials.

PubMed

Denis, L J

1992-02-01

International collaboration has resulted in a revised and unified 1987 formulation for the TNM classification in solid tumors. The simplification and eliminations of most variables caused difficulties for the clinical use of the system in some tumors such as bladder cancer. The approval of the proposed adaptation covering the tumor mass, subdividing the T4 category and adapting the stage grouping, resolves these difficulties. Published reports demonstrate support for the TNM system as a clinical base for treatment decisions and prognosis. The TNMG stage and grade are important basic prognostic factors, but other prognostic factors, especially biologic tumor activity, are under clinical investigation. The TNM classification is the initial evaluation after histologic confirmation of cancer to guide treatment and prognosis. The quality of the evaluation is enhanced by precise communication on the employed methodology.

Preprocessing Structured Clinical Data for Predictive Modeling and Decision Support

PubMed Central

Oliveira, Mónica Duarte; Janela, Filipe; Martins, Henrique M. G.

2016-01-01

Summary Background EHR systems have high potential to improve healthcare delivery and management. Although structured EHR data generates information in machine-readable formats, their use for decision support still poses technical challenges for researchers due to the need to preprocess and convert data into a matrix format. During our research, we observed that clinical informatics literature does not provide guidance for researchers on how to build this matrix while avoiding potential pitfalls. Objectives This article aims to provide researchers a roadmap of the main technical challenges of preprocessing structured EHR data and possible strategies to overcome them. Methods Along standard data processing stages – extracting database entries, defining features, processing data, assessing feature values and integrating data elements, within an EDPAI framework –, we identified the main challenges faced by researchers and reflect on how to address those challenges based on lessons learned from our research experience and on best practices from related literature. We highlight the main potential sources of error, present strategies to approach those challenges and discuss implications of these strategies. Results Following the EDPAI framework, researchers face five key challenges: (1) gathering and integrating data, (2) identifying and handling different feature types, (3) combining features to handle redundancy and granularity, (4) addressing data missingness, and (5) handling multiple feature values. Strategies to address these challenges include: cross-checking identifiers for robust data retrieval and integration; applying clinical knowledge in identifying feature types, in addressing redundancy and granularity, and in accommodating multiple feature values; and investigating missing patterns adequately. Conclusions This article contributes to literature by providing a roadmap to inform structured EHR data preprocessing. It may advise researchers on potential

The cognitive processes underpinning clinical decision in triage assessment: a theoretical conundrum?

PubMed

Noon, Amy J

2014-01-01

High quality clinical decision-making (CDM) has been highlighted as a priority across the nursing profession. Triage nurses, in the Accident and Emergency (A&E) department, work in considerable levels of uncertainty and require essential skills including: critical thinking, evaluation and decision-making. The content of this paper aims to promote awareness of how triage nurses make judgements and decisions in emergency situations. By exploring relevant literature on clinical judgement and decision-making theory, this paper demonstrates the importance of high quality decision-making skills underpinning the triage nurse's role. Having an awareness of how judgements and decisions are made is argued as essential, in a time where traditional nurse boundaries and responsibilities are never more challenged. It is hoped that the paper not only raises this awareness in general but also, in particular, engages the triage nurse to look more critically at how they make their own decisions in their everyday practice. Copyright © 2013 Elsevier Ltd. All rights reserved.

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

PubMed

Smith, Megan; Higgs, Joy; Ellis, Elizabeth

2010-02-01

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

Multi-criteria clinical decision support: A primer on the use of multiple criteria decision making methods to promote evidence-based, patient-centered healthcare.

PubMed

Dolan, James G

2010-01-01

Current models of healthcare quality recommend that patient management decisions be evidence-based and patient-centered. Evidence-based decisions require a thorough understanding of current information regarding the natural history of disease and the anticipated outcomes of different management options. Patient-centered decisions incorporate patient preferences, values, and unique personal circumstances into the decision making process and actively involve both patients along with health care providers as much as possible. Fundamentally, therefore, evidence-based, patient-centered decisions are multi-dimensional and typically involve multiple decision makers.Advances in the decision sciences have led to the development of a number of multiple criteria decision making methods. These multi-criteria methods are designed to help people make better choices when faced with complex decisions involving several dimensions. They are especially helpful when there is a need to combine "hard data" with subjective preferences, to make trade-offs between desired outcomes, and to involve multiple decision makers. Evidence-based, patient-centered clinical decision making has all of these characteristics. This close match suggests that clinical decision support systems based on multi-criteria decision making techniques have the potential to enable patients and providers to carry out the tasks required to implement evidence-based, patient-centered care effectively and efficiently in clinical settings.The goal of this paper is to give readers a general introduction to the range of multi-criteria methods available and show how they could be used to support clinical decision-making. Methods discussed include the balance sheet, the even swap method, ordinal ranking methods, direct weighting methods, multi-attribute decision analysis, and the analytic hierarchy process (AHP).

Multi-criteria clinical decision support: A primer on the use of multiple criteria decision making methods to promote evidence-based, patient-centered healthcare

PubMed Central

Dolan, James G.

2010-01-01

Current models of healthcare quality recommend that patient management decisions be evidence-based and patient-centered. Evidence-based decisions require a thorough understanding of current information regarding the natural history of disease and the anticipated outcomes of different management options. Patient-centered decisions incorporate patient preferences, values, and unique personal circumstances into the decision making process and actively involve both patients along with health care providers as much as possible. Fundamentally, therefore, evidence-based, patient-centered decisions are multi-dimensional and typically involve multiple decision makers. Advances in the decision sciences have led to the development of a number of multiple criteria decision making methods. These multi-criteria methods are designed to help people make better choices when faced with complex decisions involving several dimensions. They are especially helpful when there is a need to combine “hard data” with subjective preferences, to make trade-offs between desired outcomes, and to involve multiple decision makers. Evidence-based, patient-centered clinical decision making has all of these characteristics. This close match suggests that clinical decision support systems based on multi-criteria decision making techniques have the potential to enable patients and providers to carry out the tasks required to implement evidence-based, patient-centered care effectively and efficiently in clinical settings. The goal of this paper is to give readers a general introduction to the range of multi-criteria methods available and show how they could be used to support clinical decision-making. Methods discussed include the balance sheet, the even swap method, ordinal ranking methods, direct weighting methods, multi-attribute decision analysis, and the analytic hierarchy process (AHP) PMID:21394218

Optimal data systems: the future of clinical predictions and decision support.

PubMed

Celi, Leo A; Csete, Marie; Stone, David

2014-10-01

The purpose of the review is to describe the evolving concept and role of data as it relates to clinical predictions and decision-making. Critical care medicine is, as an especially data-rich specialty, becoming acutely cognizant not only of its historic deficits in data utilization but also of its enormous potential for capturing, mining, and leveraging such data into well-designed decision support modalities as well as the formulation of robust best practices. Modern electronic medical records create an opportunity to design complete and functional data systems that can support clinical care to a degree never seen before. Such systems are often referred to as 'data-driven,' but a better term is 'optimal data systems' (ODS). Here we discuss basic features of an ODS and its benefits, including the potential to transform clinical prediction and decision support.

Mobile clinical decision support systems and applications: a literature and commercial review.

PubMed

Martínez-Pérez, Borja; de la Torre-Díez, Isabel; López-Coronado, Miguel; Sainz-de-Abajo, Beatriz; Robles, Montserrat; García-Gómez, Juan Miguel

2014-01-01

The latest advances in eHealth and mHealth have propitiated the rapidly creation and expansion of mobile applications for health care. One of these types of applications are the clinical decision support systems, which nowadays are being implemented in mobile apps to facilitate the access to health care professionals in their daily clinical decisions. The aim of this paper is twofold. Firstly, to make a review of the current systems available in the literature and in commercial stores. Secondly, to analyze a sample of applications in order to obtain some conclusions and recommendations. Two reviews have been done: a literature review on Scopus, IEEE Xplore, Web of Knowledge and PubMed and a commercial review on Google play and the App Store. Five applications from each review have been selected to develop an in-depth analysis and to obtain more information about the mobile clinical decision support systems. Ninety-two relevant papers and 192 commercial apps were found. Forty-four papers were focused only on mobile clinical decision support systems. One hundred seventy-one apps were available on Google play and 21 on the App Store. The apps are designed for general medicine and 37 different specialties, with some features common in all of them despite of the different medical fields objective. The number of mobile clinical decision support applications and their inclusion in clinical practices has risen in the last years. However, developers must be careful with their interface or the easiness of use, which can impoverish the experience of the users.

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.

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.

The incremental impact of cardiac MRI on clinical decision-making.

PubMed

Rajwani, Adil; Stewart, Michael J; Richardson, James D; Child, Nicholas M; Maredia, Neil

2016-01-01

Despite a significant expansion in the use of cardiac MRI (CMR), there is inadequate evaluation of its incremental impact on clinical decision-making over and above other well-established modalities. We sought to determine the incremental utility of CMR in routine practice. 629 consecutive CMR studies referred by 44 clinicians from 9 institutions were evaluated. Pre-defined algorithms were used to determine the incremental influence on diagnostic thinking, influence on clinical management and thus the overall clinical utility. Studies were also subdivided and evaluated according to the indication for CMR. CMR provided incremental information to the clinician in 85% of cases, with incremental influence on diagnostic thinking in 85% of cases and incremental impact on management in 42% of cases. The overall incremental utility of CMR exceeded 90% in 7 out of the 13 indications, whereas in settings such as the evaluation of unexplained ventricular arrhythmia or mild left ventricular systolic dysfunction, this was <50%. CMR was frequently able to inform and influence decision-making in routine clinical practice, even with analyses that accepted only incremental clinical information and excluded a redundant duplication of imaging. Significant variations in yield were noted according to the indication for CMR. These data support a wider integration of CMR services into cardiac imaging departments. These data are the first to objectively evaluate the incremental value of a UK CMR service in clinical decision-making. Such data are essential when seeking justification for a CMR service.

Information management to enable personalized medicine: stakeholder roles in building clinical decision support.

PubMed

Downing, Gregory J; Boyle, Scott N; Brinner, Kristin M; Osheroff, Jerome A

2009-10-08

Advances in technology and the scientific understanding of disease processes are presenting new opportunities to improve health through individualized approaches to patient management referred to as personalized medicine. Future health care strategies that deploy genomic technologies and molecular therapies will bring opportunities to prevent, predict, and pre-empt disease processes but will be dependent on knowledge management capabilities for health care providers that are not currently available. A key cornerstone to the potential application of this knowledge will be effective use of electronic health records. In particular, appropriate clinical use of genomic test results and molecularly-targeted therapies present important challenges in patient management that can be effectively addressed using electronic clinical decision support technologies. Approaches to shaping future health information needs for personalized medicine were undertaken by a work group of the American Health Information Community. A needs assessment for clinical decision support in electronic health record systems to support personalized medical practices was conducted to guide health future development activities. Further, a suggested action plan was developed for government, researchers and research institutions, developers of electronic information tools (including clinical guidelines, and quality measures), and standards development organizations to meet the needs for personalized approaches to medical practice. In this article, we focus these activities on stakeholder organizations as an operational framework to help identify and coordinate needs and opportunities for clinical decision support tools to enable personalized medicine. This perspective addresses conceptual approaches that can be undertaken to develop and apply clinical decision support in electronic health record systems to achieve personalized medical care. In addition, to represent meaningful benefits to personalized

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.

Complex contexts and relationships affect clinical decisions in group therapy.

PubMed

Tasca, Giorgio A; Mcquaid, Nancy; Balfour, Louise

2016-09-01

Clinical errors tend to be underreported even though examining them can provide important training and professional development opportunities. The group therapy context may be prone to clinician errors because of the added complexity within which therapists work and patients receive treatment. We discuss clinical errors that occurred within a group therapy in which a patient for whom group was not appropriate was admitted to the treatment and then was not removed by the clinicians. This was countertherapeutic for both patient and group. Two clinicians were involved: a clinical supervisor who initially assessed and admitted the patient to the group, and a group therapist. To complicate matters, the group therapy occurred within the context of a clinical research trial. The errors, possible solutions, and recommendations are discussed within Reason's Organizational Accident Model (Reason, 2000). In particular, we discuss clinician errors in the context of countertransference and clinician heuristics, group therapy as a local work condition that complicates clinical decision-making, and the impact of the research context as a latent organizational factor. We also present clinical vignettes from the pregroup preparation, group therapy, and supervision. Group therapists are more likely to avoid errors in clinical decisions if they engage in reflective practice about their internal experiences and about the impact of the context in which they work. Therapists must keep in mind the various levels of group functioning, especially related to the group-as-a-whole (i.e., group composition, cohesion, group climate, and safety) when making complex clinical decisions in order to optimize patient outcomes. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

A social-technological epistemology of clinical decision-making as mediated by imaging.

PubMed

van Baalen, Sophie; Carusi, Annamaria; Sabroe, Ian; Kiely, David G

2017-10-01

In recent years there has been growing attention to the epistemology of clinical decision-making, but most studies have taken the individual physicians as the central object of analysis. In this paper we argue that knowing in current medical practice has an inherently social character and that imaging plays a mediating role in these practices. We have analyzed clinical decision-making within a medical expert team involved in diagnosis and treatment of patients with pulmonary hypertension (PH), a rare disease requiring multidisciplinary team involvement in diagnosis and management. Within our field study, we conducted observations, interviews, video tasks, and a panel discussion. Decision-making in the PH clinic involves combining evidence from heterogeneous sources into a cohesive framing of a patient, in which interpretations of the different sources can be made consistent with each other. Because pieces of evidence are generated by people with different expertise and interpretation and adjustments take place in interaction between different experts, we argue that this process is socially distributed. Multidisciplinary team meetings are an important place where information is shared, discussed, interpreted, and adjusted, allowing for a collective way of seeing and a shared language to be developed. We demonstrate this with an example of image processing in the PH service, an instance in which knowledge is distributed over multiple people who play a crucial role in generating an evaluation of right heart function. Finally, we argue that images fulfill a mediating role in distributed knowing in 3 ways: first, as enablers or tools in acquiring information; second, as communication facilitators; and third, as pervasively framing the epistemic domain. With this study of clinical decision-making in diagnosis and treatment of PH, we have shown that clinical decision-making is highly social and mediated by technologies. The epistemology of clinical decision-making needs

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.

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:

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.

An Internationally Consented Standard for Nursing Process-Clinical Decision Support Systems in Electronic Health Records.

PubMed

Müller-Staub, Maria; de Graaf-Waar, Helen; Paans, Wolter

2016-11-01

Nurses are accountable to apply the nursing process, which is key for patient care: It is a problem-solving process providing the structure for care plans and documentation. The state-of-the art nursing process is based on classifications that contain standardized concepts, and therefore, it is named Advanced Nursing Process. It contains valid assessments, nursing diagnoses, interventions, and nursing-sensitive patient outcomes. Electronic decision support systems can assist nurses to apply the Advanced Nursing Process. However, nursing decision support systems are missing, and no "gold standard" is available. The study aim is to develop a valid Nursing Process-Clinical Decision Support System Standard to guide future developments of clinical decision support systems. In a multistep approach, a Nursing Process-Clinical Decision Support System Standard with 28 criteria was developed. After pilot testing (N = 29 nurses), the criteria were reduced to 25. The Nursing Process-Clinical Decision Support System Standard was then presented to eight internationally known experts, who performed qualitative interviews according to Mayring. Fourteen categories demonstrate expert consensus on the Nursing Process-Clinical Decision Support System Standard and its content validity. All experts agreed the Advanced Nursing Process should be the centerpiece for the Nursing Process-Clinical Decision Support System and should suggest research-based, predefined nursing diagnoses and correct linkages between diagnoses, evidence-based interventions, and patient outcomes.

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.

Pharmacists’ Perceptions of the Influence of Interactions with the Pharmaceutical Industry on Clinical Decision-Making

PubMed Central

Tejani, Aaron M; Loewen, Peter; Bachand, Richard; Harder, Curtis K

2015-01-01

Background: There is a paucity of literature examining the perceptions of Canadian pharmacists toward drug promotion by the pharmaceutical industry and pharmacist–industry interactions. Objectives: To determine whether hospital pharmacists perceive their interactions with the pharmaceutical industry as influencing their clinical decision-making or that of their colleagues and whether hospital pharmacists perceive that interactions with the pharmaceutical industry create a conflict of interest. Methods: A cross-sectional survey of the complete sample of hospital pharmacists practising in 3 large health authorities in a single Canadian province was conducted from February to April 2010. Results: A total of 224 responses were received from the approximately 480 pharmacists in the target health authorities (response rate approximately 47%). Fifty-eight percent of respondents (127/218) did not believe that information received at industry-sponsored events influenced their clinical decision-making. Most (142/163 [87%]) disagreed that small gifts influenced their clinical decision-making, whereas responses were divided for large gifts. Respondents were also divided on the issue of whether their interactions created conflicts of interest, with most of those who had received gifts agreeing that large gifts would create a conflict of interest (134/163 [82%]) whereas small gifts would not (100/163 [61%]). There were positive correlations between respondents’ beliefs about their own susceptibility to influence from sponsored events or receipt of small or large gifts and the susceptibility of others, but 22% of respondents (28/127) expressed a different perception about sponsored events, all believing themselves to be less influenced than their colleagues. Only 6% (4/64) of those who received large gifts and 4% (5/142) of those who received small gifts and felt they were not influenced by these gifts reported that it was likely others would be influenced by the receipt of

Clinical decision support improves quality of telephone triage documentation - an analysis of triage documentation before and after computerized clinical decision support

PubMed Central

2014-01-01

Background Clinical decision support (CDS) has been shown to be effective in improving medical safety and quality but there is little information on how telephone triage benefits from CDS. The aim of our study was to compare triage documentation quality associated with the use of a clinical decision support tool, ExpertRN©. Methods We examined 50 triage documents before and after a CDS tool was used in nursing triage. To control for the effects of CDS training we had an additional control group of triage documents created by nurses who were trained in the CDS tool, but who did not use it in selected notes. The CDS intervention cohort of triage notes was compared to both the pre-CDS notes and the CDS trained (but not using CDS) cohort. Cohorts were compared using the documentation standards of the American Academy of Ambulatory Care Nursing (AAACN). We also compared triage note content (documentation of associated positive and negative features relating to the symptoms, self-care instructions, and warning signs to watch for), and documentation defects pertinent to triage safety. Results Three of five AAACN documentation standards were significantly improved with CDS. There was a mean of 36.7 symptom features documented in triage notes for the CDS group but only 10.7 symptom features in the pre-CDS cohort (p < 0.0001) and 10.2 for the cohort that was CDS-trained but not using CDS (p < 0.0001). The difference between the mean of 10.2 symptom features documented in the pre-CDS and the mean of 10.7 symptom features documented in the CDS-trained but not using was not statistically significant (p = 0.68). Conclusions CDS significantly improves triage note documentation quality. CDS-aided triage notes had significantly more information about symptoms, warning signs and self-care. The changes in triage documentation appeared to be the result of the CDS alone and not due to any CDS training that came with the CDS intervention. Although this study shows that CDS

Clinical Decision Support to Implement CYP2D6 Drug-Gene Interaction.

PubMed

Caraballo, Pedro J; Parkulo, Mark; Blair, David; Elliott, Michelle; Schultz, Cloann; Sutton, Joseph; Rao, Padma; Bruflat, Jamie; Bleimeyer, Robert; Crooks, John; Gabrielson, Donald; Nicholson, Wayne; Rohrer Vitek, Carolyn; Wix, Kelly; Bielinski, Suzette J; Pathak, Jyotishman; Kullo, Iftikhar

2015-01-01

The level of CYP2D6 metabolic activity can be predicted by pharmacogenomic testing, and concomitant use of clinical decision support has the potential to prevent adverse effects from those drugs metabolized by this enzyme. Our initial findings after implementation of clinical decision support alerts integrated in the electronic health records suggest high feasibility, but also identify important challenges.

Patients' perceptions of sharing in decisions: a systematic review of interventions to enhance shared decision making in routine clinical practice.

PubMed

Légaré, France; Turcotte, Stéphane; Stacey, Dawn; Ratté, Stéphane; Kryworuchko, Jennifer; Graham, Ian D

2012-01-01

Shared decision making is the process in which a healthcare choice is made jointly by the health professional and the patient. Little is known about what patients view as effective or ineffective strategies to implement shared decision making in routine clinical practice. This systematic review evaluates the effectiveness of interventions to improve health professionals' adoption of shared decision making in routine clinical practice, as seen by patients. We searched electronic databases (PubMed, the Cochrane Library, EMBASE, CINAHL, and PsycINFO) from their inception to mid-March 2009. We found additional material by reviewing the reference lists of the studies found in the databases; systematic reviews of studies on shared decision making; the proceedings of various editions of the International Shared Decision Making Conference; and the transcripts of the Society for Medical Decision Making's meetings. In our study selection, we included randomized controlled trials, controlled clinical trials, controlled before-and-after studies, and interrupted time series analyses in which patients evaluated interventions to improve health professionals' adoption of shared decision making. The interventions in question consisted of the distribution of printed educational material; educational meetings; audit and feedback; reminders; and patient-mediated initiatives (e.g. patient decision aids). Two reviewers independently screened the studies and extracted data. Statistical analyses considered categorical and continuous process measures. We computed the standardized effect size for each outcome at the 95% confidence interval. The primary outcome of interest was health professionals' adoption of shared decision making as reported by patients in a self-administered questionnaire. Of the 6764 search results, 21 studies reported 35 relevant comparisons. Overall, the quality of the studies ranged from 0% to 83%. Only three of the 21 studies reported a clinically significant effect

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.

Hemispheric Activation Differences in Novice and Expert Clinicians during Clinical Decision Making

ERIC Educational Resources Information Center

Hruska, Pam; Hecker, Kent G.; Coderre, Sylvain; McLaughlin, Kevin; Cortese, Filomeno; Doig, Christopher; Beran, Tanya; Wright, Bruce; Krigolson, Olav

2016-01-01

Clinical decision making requires knowledge, experience and analytical/non-analytical types of decision processes. As clinicians progress from novice to expert, research indicates decision-making becomes less reliant on foundational biomedical knowledge and more on previous experience. In this study, we investigated how knowledge and experience…

[Cognitive traps and clinical decisions].

PubMed

Motterlini, Matteo

2017-12-01

We are fallible, we have limited computational capabilities, limited access to information, little memory. Moreover, in everyday life, we feel joy, fear, anger, and other emotions that influence our decisions in a little, "calculated" way. Not everyone, however, is also aware that the mistakes we make are often systematic and therefore, in particular circumstances, are foreseeable. Doctors and patients are constantly called upon to make decisions. They need to identify relevant information (for example, the symptoms or outcome of an examination), formulate a judgment (for example a diagnosis), choose an action course among the various possible ones based on one's own preferences (e.g. medication or surgery), so act. The exact size of the medical error is unknown, but probably huge. In fact, the more we investigate and the more we find. Often these mistakes depend on the cognitive process. Any (rational) decision requires, in particular, an assessment of the possible effects of the action it implements; for example how much pleasure or pain it will cause us. In the medical field, too, the principle of informed consent provides that the patient's preferences and values are to guide clinical choices. Yet, not always the preferences that people express before making an experience match with their preferences after living that experience. Some ingenious experiments suggest (in a seemingly paradoxical way) that before a direct experience, people prefer less pain; after that experience they prefer more, but with a better memory.

Towards meaningful medication-related clinical decision support: recommendations for an initial implementation.

PubMed

Phansalkar, S; Wright, A; Kuperman, G J; Vaida, A J; Bobb, A M; Jenders, R A; Payne, T H; Halamka, J; Bloomrosen, M; Bates, D W

2011-01-01

Clinical decision support (CDS) can improve safety, quality, and cost-effectiveness of patient care, especially when implemented in computerized provider order entry (CPOE) applications. Medication-related decision support logic forms a large component of the CDS logic in any CPOE system. However, organizations wishing to implement CDS must either purchase the computable clinical content or develop it themselves. Content provided by vendors does not always meet local expectations. Most organizations lack the resources to customize the clinical content and the expertise to implement it effectively. In this paper, we describe the recommendations of a national expert panel on two basic medication-related CDS areas, specifically, drug-drug interaction (DDI) checking and duplicate therapy checking. The goals of this study were to define a starter set of medication-related alerts that healthcare organizations can implement in their clinical information systems. We also draw on the experiences of diverse institutions to highlight the realities of implementing medication decision support. These findings represent the experiences of institutions with a long history in the domain of medication decision support, and the hope is that this guidance may improve the feasibility and efficiency CDS adoption across healthcare settings.

TUW @ TREC Clinical Decision Support Track

DTIC Science & Technology

2014-11-01

and the ShARe/CLEF eHealth Evaluation Lab [8,3] running in 2013 and 2014. Here we briefly describe the goals of the first TREC Clinical Decision...Wendy W. Chapman, David Mart́ınez, Guido Zuccon, and João R. M. Palotti. Overview of the share/clef ehealth evalu- ation lab 2014. In Information Access...Zuccon. Overview of the share/clef ehealth evaluation lab 2013. In Information Access Evaluation. Multilinguality, Multimodality, and Visualization

A Closer Look at Racism and Heterosexism in Medical Students' Clinical Decision-Making Related to HIV Pre-Exposure Prophylaxis (PrEP): Implications for PrEP Education.

PubMed

Calabrese, Sarah K; Earnshaw, Valerie A; Krakower, Douglas S; Underhill, Kristen; Vincent, Wilson; Magnus, Manya; Hansen, Nathan B; Kershaw, Trace S; Mayer, Kenneth H; Betancourt, Joseph R; Dovidio, John F

2018-04-01

Social biases among healthcare providers could limit PrEP access. In this survey study of 115 US medical students, we examined associations between biases (racism and heterosexism) and PrEP clinical decision-making and explored prior PrEP education as a potential buffer. After viewing a vignette about a PrEP-seeking MSM patient, participants reported anticipated patient behavior (condomless sex, extra-relational sex, and adherence), intention to prescribe PrEP to the patient, biases, and background characteristics. Minimal evidence for racism affecting clinical decision-making emerged. In unadjusted analyses, heterosexism indirectly affected prescribing intention via all anticipated behaviors, tested as parallel mediators. Participants expressing greater heterosexism more strongly anticipated increased risk behavior and adherence problems, which were associated with lower prescribing intention. The indirect effect via condomless sex remained significant adjusting for background characteristics. Prior PrEP education did not buffer any indirect effects. Heterosexism may compromise PrEP provision to MSM and should be addressed in PrEP-related medical education.

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

Clinical decision-making and therapeutic approaches in osteopathy - a qualitative grounded theory study.

PubMed

Thomson, Oliver P; Petty, Nicola J; Moore, Ann P

2014-02-01

There is limited understanding of how osteopaths make decisions in relation to clinical practice. The aim of this research was to construct an explanatory theory of the clinical decision-making and therapeutic approaches of experienced osteopaths in the UK. Twelve UK registered osteopaths participated in this constructivist grounded theory qualitative study. Purposive and theoretical sampling was used to select participants. Data was collected using semi-structured interviews which were audio-recorded and transcribed. As the study approached theoretical sufficiency, participants were observed and video-recorded during a patient appointment, which was followed by a video-prompted interview. Constant comparative analysis was used to analyse and code data. Data analysis resulted in the construction of three qualitatively different therapeutic approaches which characterised participants and their clinical practice, termed; Treater, Communicator and Educator. Participants' therapeutic approach influenced their approach to clinical decision-making, the level of patient involvement, their interaction with patients, and therapeutic goals. Participants' overall conception of practice lay on a continuum ranging from technical rationality to professional artistry, and contributed to their therapeutic approach. A range of factors were identified which influenced participants' conception of practice. The findings indicate that there is variation in osteopaths' therapeutic approaches to practice and clinical decision-making, which are influenced by their overall conception of practice. This study provides the first explanatory theory of the clinical decision-making and therapeutic approaches of osteopaths. Copyright © 2013 Elsevier Ltd. All rights reserved.

Artificial intelligence framework for simulating clinical decision-making: a Markov decision process approach.

PubMed

Bennett, Casey C; Hauser, Kris

2013-01-01

In the modern healthcare system, rapidly expanding costs/complexity, the growing myriad of treatment options, and exploding information streams that often do not effectively reach the front lines hinder the ability to choose optimal treatment decisions over time. The goal in this paper is to develop a general purpose (non-disease-specific) computational/artificial intelligence (AI) framework to address these challenges. This framework serves two potential functions: (1) a simulation environment for exploring various healthcare policies, payment methodologies, etc., and (2) the basis for clinical artificial intelligence - an AI that can "think like a doctor". This approach combines Markov decision processes and dynamic decision networks to learn from clinical data and develop complex plans via simulation of alternative sequential decision paths while capturing the sometimes conflicting, sometimes synergistic interactions of various components in the healthcare system. It can operate in partially observable environments (in the case of missing observations or data) by maintaining belief states about patient health status and functions as an online agent that plans and re-plans as actions are performed and new observations are obtained. This framework was evaluated using real patient data from an electronic health record. The results demonstrate the feasibility of this approach; such an AI framework easily outperforms the current treatment-as-usual (TAU) case-rate/fee-for-service models of healthcare. The cost per unit of outcome change (CPUC) was $189 vs. $497 for AI vs. TAU (where lower is considered optimal) - while at the same time the AI approach could obtain a 30-35% increase in patient outcomes. Tweaking certain AI model parameters could further enhance this advantage, obtaining approximately 50% more improvement (outcome change) for roughly half the costs. Given careful design and problem formulation, an AI simulation framework can approximate optimal

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.

Clinical decision making and the expected value of information.

PubMed

Willan, Andrew R

2007-01-01

The results of the HOPE study, a randomized clinical trial, provide strong evidence that 1) ramipril prevents the composite outcome of cardiovascular death, myocardial infarction or stroke in patients who are at high risk of a cardiovascular event and 2) ramipril is cost-effective at a threshold willingness-to-pay of $10,000 to prevent an event of the composite outcome. In this report the concept of the expected value of information is used to determine if the information provided by the HOPE study is sufficient for decision making in the US and Canada. and results Using the cost-effectiveness data from a clinical trial, or from a meta-analysis of several trials, one can determine, based on the number of future patients that would benefit from the health technology under investigation, the expected value of sample information (EVSI) of a future trial as a function of proposed sample size. If the EVSI exceeds the cost for any particular sample size then the current information is insufficient for decision making and a future trial is indicated. If, on the other hand, there is no sample size for which the EVSI exceeds the cost, then there is sufficient information for decision making and no future trial is required. Using the data from the HOPE study these concepts are applied for various assumptions regarding the fixed and variable cost of a future trial and the number of patients who would benefit from ramipril. Expected value of information methods provide a decision-analytic alternative to the standard likelihood methods for assessing the evidence provided by cost-effectiveness data from randomized clinical trials.

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.

Real-Time Clinical Decision Support Decreases Inappropriate Plasma Transfusion.

PubMed

Shah, Neil; Baker, Steven A; Spain, David; Shieh, Lisa; Shepard, John; Hadhazy, Eric; Maggio, Paul; Goodnough, Lawrence T

2017-08-01

To curtail inappropriate plasma transfusions, we instituted clinical decision support as an alert upon order entry if the patient's recent international normalized ratio (INR) was 1.7 or less. The alert was suppressed for massive transfusion and within operative or apheresis settings. The plasma order was automatically removed upon alert acceptance while clinical exception reasons allowed for continued transfusion. Alert impact was studied comparing a 7-month control period with a 4-month intervention period. Monthly plasma utilization decreased 17.4%, from a mean ± SD of 3.40 ± 0.48 to 2.82 ± 0.6 plasma units per hundred patient days (95% confidence interval [CI] of difference, -0.1 to 1.3). Plasma transfused below an INR of 1.7 or less decreased from 47.6% to 41.6% (P = .0002; odds ratio, 0.78; 95% CI, 0.69-0.89). The alert recommendation was accepted 33% of the time while clinical exceptions were chosen in the remaining cases (active bleeding, 31%; other clinical indication, 33%; and apheresis, 2%). Alert acceptance rate varied significantly among different provider specialties. Clinical decision support can help curtail inappropriate plasma use but needs to be part of a comprehensive strategy including audit and feedback for comprehensive, long-term changes. © American Society for Clinical Pathology, 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

Making informed capital investment decisions for clinical technology.

PubMed

Poplin, Brian

2011-02-01

Hospitals can make more-informed decisions related to clinical equipment purchases by using a variety of data sources in planning their investment strategies. Data sources generally fall into three buckets: Data that are internally generated by hospitals. Public data. Industry data that are available for purchase.

The role of emotion in clinical decision making: an integrative literature review.

PubMed

Kozlowski, Desirée; Hutchinson, Marie; Hurley, John; Rowley, Joanne; Sutherland, Joanna

2017-12-15

Traditionally, clinical decision making has been perceived as a purely rational and cognitive process. Recently, a number of authors have linked emotional intelligence (EI) to clinical decision making (CDM) and calls have been made for an increased focus on EI skills for clinicians. The objective of this integrative literature review was to identify and synthesise the empirical evidence for a role of emotion in CDM. A systematic search of the bibliographic databases PubMed, PsychINFO, and CINAHL (EBSCO) was conducted to identify empirical studies of clinician populations. Search terms were focused to identify studies reporting clinician emotion OR clinician emotional intelligence OR emotional competence AND clinical decision making OR clinical reasoning. Twenty three papers were retained for synthesis. These represented empirical work from qualitative, quantitative, and mixed-methods approaches and comprised work with a focus on experienced emotion and on skills associated with emotional intelligence. The studies examined nurses (10), physicians (7), occupational therapists (1), physiotherapists (1), mixed clinician samples (3), and unspecified infectious disease experts (1). We identified two main themes in the context of clinical decision making: the subjective experience of emotion; and, the application of emotion and cognition in CDM. Sub-themes under the subjective experience of emotion were: emotional response to contextual pressures; emotional responses to others; and, intentional exclusion of emotion from CDM. Under the application of emotion and cognition in CDM, sub-themes were: compassionate emotional labour - responsiveness to patient emotion within CDM; interdisciplinary tension regarding the significance and meaning of emotion in CDM; and, emotion and moral judgement. Clinicians' experienced emotions can and do affect clinical decision making, although acknowledgement of that is far from universal. Importantly, this occurs in the in the absence of a

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

Autonomy, religion and clinical decisions: findings from a national physician survey

PubMed Central

Lawrence, R E; Curlin, F A

2010-01-01

Background Patient autonomy has been promoted as the most important principle to guide difficult clinical decisions. To examine whether practising physicians indeed value patient autonomy above other considerations, physicians were asked to weight patient autonomy against three other criteria that often influence doctors’ decisions. Associations between physicians’ religious characteristics and their weighting of the criteria were also examined. Methods Mailed survey in 2007 of a stratified random sample of 1000 US primary care physicians, selected from the American Medical Association masterfile. Physicians were asked how much weight should be given to the following: (1) the patient’s expressed wishes and values, (2) the physician’s own judgment about what is in the patient’s best interest, (3) standards and recommendations from professional medical bodies and (4) moral guidelines from religious traditions. Results Response rate 51% (446/879). Half of physicians (55%) gave the patient’s expressed wishes and values “the highest possible weight”. In comparative analysis, 40% gave patient wishes more weight than the other three factors, and 13% ranked patient wishes behind some other factor. Religious doctors tended to give less weight to the patient’s expressed wishes. For example, 47% of doctors with high intrinsic religious motivation gave patient wishes the “highest possible weight”, versus 67% of those with low (OR 0.5; 95% CI 0.3 to 0.8). Conclusions Doctors believe patient wishes and values are important, but other considerations are often equally or more important. This suggests that patient autonomy does not guide physicians’ decisions as much as is often recommended in the ethics literature. PMID:19332575

Development of a clinical decision model for thyroid nodules

PubMed Central

Stojadinovic, Alexander; Peoples, George E; Libutti, Steven K; Henry, Leonard R; Eberhardt, John; Howard, Robin S; Gur, David; Elster, Eric A; Nissan, Aviram

2009-01-01

Background Thyroid nodules represent a common problem brought to medical attention. Four to seven percent of the United States adult population (10–18 million people) has a palpable thyroid nodule, however the majority (>95%) of thyroid nodules are benign. While, fine needle aspiration remains the most cost effective and accurate diagnostic tool for thyroid nodules in current practice, over 20% of patients undergoing FNA of a thyroid nodule have indeterminate cytology (follicular neoplasm) with associated malignancy risk prevalence of 20–30%. These patients require thyroid lobectomy/isthmusectomy purely for the purpose of attaining a definitive diagnosis. Given that the majority (70–80%) of these patients have benign surgical pathology, thyroidectomy in these patients is conducted principally with diagnostic intent. Clinical models predictive of malignancy risk are needed to support treatment decisions in patients with thyroid nodules in order to reduce morbidity associated with unnecessary diagnostic surgery. Methods Data were analyzed from a completed prospective cohort trial conducted over a 4-year period involving 216 patients with thyroid nodules undergoing ultrasound (US), electrical impedance scanning (EIS) and fine needle aspiration cytology (FNA) prior to thyroidectomy. A Bayesian model was designed to predict malignancy in thyroid nodules based on multivariate dependence relationships between independent covariates. Ten-fold cross-validation was performed to estimate classifier error wherein the data set was randomized into ten separate and unique train and test sets consisting of a training set (90% of records) and a test set (10% of records). A receiver-operating-characteristics (ROC) curve of these predictions and area under the curve (AUC) were calculated to determine model robustness for predicting malignancy in thyroid nodules. Results Thyroid nodule size, FNA cytology, US and EIS characteristics were highly predictive of malignancy. Cross

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

The use of emotional intelligence capabilities in clinical reasoning and decision-making: A qualitative, exploratory study.

PubMed

Hutchinson, Marie; Hurley, John; Kozlowski, Desirée; Whitehair, Leeann

2018-02-01

To explore clinical nurses' experiences of using emotional intelligence capabilities during clinical reasoning and decision-making. There has been little research exploring whether, or how, nurses employ emotional intelligence (EI) in clinical reasoning and decision-making. Qualitative phase of a larger mixed-methods study. Semistructured qualitative interviews with a purposive sample of registered nurses (n = 12) following EI training and coaching. Constructivist thematic analysis was employed to analyse the narrative transcripts. Three themes emerged: the sensibility to engage EI capabilities in clinical contexts, motivation to actively engage with emotions in clinical decision-making and incorporating emotional and technical perspectives in decision-making. Continuing to separate cognition and emotion in research, theorising and scholarship on clinical reasoning is counterproductive. Understanding more about nurses' use of EI has the potential to improve the calibre of decisions, and the safety and quality of care delivered. © 2017 John Wiley & Sons Ltd.

A multiple biomarker risk score for guiding clinical decisions using a decision curve approach.

PubMed

Hughes, Maria F; Saarela, Olli; Blankenberg, Stefan; Zeller, Tanja; Havulinna, Aki S; Kuulasmaa, Kari; Yarnell, John; Schnabel, Renate B; Tiret, Laurence; Salomaa, Veikko; Evans, Alun; Kee, Frank

2012-08-01

We assessed whether a cardiovascular risk model based on classic risk factors (e.g. cholesterol, blood pressure) could refine disease prediction if it included novel biomarkers (C-reactive protein, N-terminal pro-B-type natriuretic peptide, troponin I) using a decision curve approach which can incorporate clinical consequences. We evaluated whether a model including biomarkers and classic risk factors could improve prediction of 10 year risk of cardiovascular disease (CVD; chronic heart disease and ischaemic stroke) against a classic risk factor model using a decision curve approach in two prospective MORGAM cohorts. This included 7739 men and women with 457 CVD cases from the FINRISK97 cohort; and 2524 men with 259 CVD cases from PRIME Belfast. The biomarker model improved disease prediction in FINRISK across the high-risk group (20-40%) but not in the intermediate risk group, at the 23% risk threshold net benefit was 0.0033 (95% CI 0.0013-0.0052). However, in PRIME Belfast the net benefit of decisions guided by the decision curve was improved across intermediate risk thresholds (10-20%). At p(t) = 10% in PRIME, the net benefit was 0.0059 (95% CI 0.0007-0.0112) with a net increase in 6 true positive cases per 1000 people screened and net decrease of 53 false positive cases per 1000 potentially leading to 5% fewer treatments in patients not destined for an event. The biomarker model improves 10-year CVD prediction at intermediate and high-risk thresholds and in particular, could be clinically useful at advising middle-aged European males of their CVD risk.

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.

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.

Gender and venture capital decision-making: the effects of technical background and social capital on entrepreneurial evaluations.

PubMed

Tinkler, Justine E; Bunker Whittington, Kjersten; Ku, Manwai C; Davies, Andrea Rees

2015-05-01

Research on gender and workplace decision-making tends to address either supply-side disparities between men's and women's human and social capital, or demand-side differences in the status expectations of women and men workers. In addition, this work often relies on causal inferences drawn from empirical data collected on worker characteristics and their workplace outcomes. In this study, we demonstrate how tangible education and work history credentials - typically associated with supply-side characteristics - work in tandem with cultural beliefs about gender to influence the evaluative process that underlies venture capital decisions made in high-growth, high-tech entrepreneurship. Using an experimental design, we simulate funding decisions by venture capitalists (VCs) for men and women entrepreneurs that differ in technical background and the presence of important social ties. We demonstrate the presence of two distinct aspects of VCs' evaluation: that of the venture and that of the entrepreneur, and find that the gender of the entrepreneur influences evaluations most when the person, rather than the venture, is the target of evaluation. Technical background qualifications moderate the influence of gendered expectations, and women receive more of a payoff than men from having a close contact to the evaluating VC. We discuss the implications for future research on gender and work. Copyright © 2014 Elsevier Inc. All rights reserved.

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.

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.

Evaluating online diagnostic decision support tools for the clinical setting.

PubMed

Pryor, Marie; White, David; Potter, Bronwyn; Traill, Roger

2012-01-01

Clinical decision support tools available at the point of care are an effective adjunct to support clinicians to make clinical decisions and improve patient outcomes. We developed a methodology and applied it to evaluate commercially available online clinical diagnostic decision support (DDS) tools for use at the point of care. We identified 11 commercially available DDS tools and assessed these against an evaluation instrument that included 6 categories; general information, content, quality control, search, clinical results and other features. We developed diagnostically challenging clinical case scenarios based on real patient experience that were commonly missed by junior medical staff. The evaluation was divided into 2 phases; an initial evaluation of all identified and accessible DDS tools conducted by the Clinical Information Access Portal (CIAP) team and a second phase that further assessed the top 3 tools identified in the initial evaluation phase. An evaluation panel consisting of senior and junior medical clinicians from NSW Health conducted the second phase. Of the eleven tools that were assessed against the evaluation instrument only 4 tools completely met the DDS definition that was adopted for this evaluation and were able to produce a differential diagnosis. From the initial phase of the evaluation 4 DDS tools scored 70% or more (maximum score 96%) for the content category, 8 tools scored 65% or more (maximum 100%) for the quality control category, 5 tools scored 65% or more (maximum 94%) for the search category, and 4 tools score 70% or more (maximum 81%) for the clinical results category. The second phase of the evaluation was focused on assessing diagnostic accuracy for the top 3 tools identified in the initial phase. Best Practice ranked highest overall against the 6 clinical case scenarios used. Overall the differentiating factor between the top 3 DDS tools was determined by diagnostic accuracy ranking, ease of use and the confidence and

Continuous quality improvement for the clinical decision unit.

PubMed

Mace, Sharon E

2004-01-01

Clinical decision units (CDUs) are a relatively new and growing area of medicine in which patients undergo rapid evaluation and treatment. Continuous quality improvement (CQI) is important for the establishment and functioning of CDUs. CQI in CDUs has many advantages: better CDU functioning, fulfillment of Joint Commission on Accreditation of Healthcare Organizations mandates, greater efficiency/productivity, increased job satisfaction, better performance improvement, data availability, and benchmarking. Key elements include a database with volume indicators, operational policies, clinical practice protocols (diagnosis specific/condition specific), monitors, benchmarks, and clinical pathways. Examples of these important parameters are given. The CQI process should be individualized for each CDU and hospital.

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.

Factors influencing alert acceptance: a novel approach for predicting the success of clinical decision support

PubMed Central

Seidling, Hanna M; Phansalkar, Shobha; Seger, Diane L; Paterno, Marilyn D; Shaykevich, Shimon; Haefeli, Walter E

2011-01-01

Background Clinical decision support systems can prevent knowledge-based prescription errors and improve patient outcomes. The clinical effectiveness of these systems, however, is substantially limited by poor user acceptance of presented warnings. To enhance alert acceptance it may be useful to quantify the impact of potential modulators of acceptance. Methods We built a logistic regression model to predict alert acceptance of drug–drug interaction (DDI) alerts in three different settings. Ten variables from the clinical and human factors literature were evaluated as potential modulators of provider alert acceptance. ORs were calculated for the impact of knowledge quality, alert display, textual information, prioritization, setting, patient age, dose-dependent toxicity, alert frequency, alert level, and required acknowledgment on acceptance of the DDI alert. Results 50 788 DDI alerts were analyzed. Providers accepted only 1.4% of non-interruptive alerts. For interruptive alerts, user acceptance positively correlated with frequency of the alert (OR 1.30, 95% CI 1.23 to 1.38), quality of display (4.75, 3.87 to 5.84), and alert level (1.74, 1.63 to 1.86). Alert acceptance was higher in inpatients (2.63, 2.32 to 2.97) and for drugs with dose-dependent toxicity (1.13, 1.07 to 1.21). The textual information influenced the mode of reaction and providers were more likely to modify the prescription if the message contained detailed advice on how to manage the DDI. Conclusion We evaluated potential modulators of alert acceptance by assessing content and human factors issues, and quantified the impact of a number of specific factors which influence alert acceptance. This information may help improve clinical decision support systems design. PMID:21571746

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

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.

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.

Identifying design considerations for a shared decision aid for use at the point of outpatient clinical care: An ethnographic study at an inner city clinic.

PubMed

Hajizadeh, Negin; Perez Figueroa, Rafael E; Uhler, Lauren M; Chiou, Erin; Perchonok, Jennifer E; Montague, Enid

2013-03-06

Computerized decision aids could facilitate shared decision-making at the point of outpatient clinical care. The objective of this study was to investigate whether a computerized shared decision aid would be feasible to implement in an inner-city clinic by evaluating the current practices in shared decision-making, clinicians' use of computers, patient and clinicians' attitudes and beliefs toward computerized decision aids, and the influence of time on shared decision-making. Qualitative data analysis of observations and semi-structured interviews with patients and clinicians at an inner-city outpatient clinic. The findings provided an exploratory look at the prevalence of shared decision-making and attitudes about health information technology and decision aids. A prominent barrier to clinicians engaging in shared decision-making was a lack of perceived patient understanding of medical information. Some patients preferred their clinicians make recommendations for them rather than engage in formal shared decision-making. Health information technology was an integral part of the clinic visit and welcomed by most clinicians and patients. Some patients expressed the desire to engage with health information technology such as viewing their medical information on the computer screen with their clinicians. All participants were receptive to the idea of a decision aid integrated within the clinic visit although some clinicians were concerned about the accuracy of prognostic estimates for complex medical problems. We identified several important considerations for the design and implementation of a computerized decision aid including opportunities to: bridge clinician-patient communication about medical information while taking into account individual patients' decision-making preferences, complement expert clinician judgment with prognostic estimates, take advantage of patient waiting times, and make tasks involved during the clinic visit more efficient. These findings

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.

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

Clinical decision making-a functional medicine perspective.

PubMed

Pizzorno, Joseph E

2012-09-01

As 21st century health care moves from a disease-based approach to a more patient-centric system that can address biochemical individuality to improve health and function, clinical decision making becomes more complex. Accentuating the problem is the lack of a clear standard for this more complex functional medicine approach. While there is relatively broad agreement in Western medicine for what constitutes competent assessment of disease and identification of related treatment approaches, the complex functional medicine model posits multiple and individualized diagnostic and therapeutic approaches, most or many of which have reasonable underlying science and principles, but which have not been rigorously tested in a research or clinical setting. This has led to non-rigorous thinking and sometimes to uncritical acceptance of both poorly documented diagnostic procedures and ineffective therapies, resulting in less than optimal clinical care.

Clinical Decision Making—A Functional Medicine Perspective

PubMed Central

2012-01-01

As 21st century health care moves from a disease-based approach to a more patient-centric system that can address biochemical individuality to improve health and function, clinical decision making becomes more complex. Accentuating the problem is the lack of a clear standard for this more complex functional medicine approach. While there is relatively broad agreement in Western medicine for what constitutes competent assessment of disease and identification of related treatment approaches, the complex functional medicine model posits multiple and individualized diagnostic and therapeutic approaches, most or many of which have reasonable underlying science and principles, but which have not been rigorously tested in a research or clinical setting. This has led to non-rigorous thinking and sometimes to uncritical acceptance of both poorly documented diagnostic procedures and ineffective therapies, resulting in less than optimal clinical care. PMID:24278827

Acceptance of clinical decision support surveillance technology in the clinical pharmacy.

PubMed

English, Dan; Ankem, Kalyani; English, Kathleen

2017-03-01

There are clinical and economic benefits to incorporating clinical decision support systems (CDSSs) in patient care interventions in the clinical pharmacy setting. However, user dissatisfaction and resistance to HIT can prevent optimal use of such systems, particularly when users employ system workarounds and overrides. The present study applied a modified version of the unified theory of acceptance and use of technology (UTAUT) to evaluate the disposition and satisfaction with CDSS among clinical pharmacists who perform surveillance to identify potential medication therapy interventions on patients in the hospital setting. A survey of clinical pharmacists (N = 48) was conducted. Partial least squares (PLS) regression was used to analyze the influence of the UTAUT-related variables on behavioral intention and satisfaction with CDSS among clinical pharmacists. While behavioral intention did not predict actual use of HIT, facilitating conditions had a direct effect on pharmacists' use of CDSS. Likewise, satisfaction with CDSS was found to have a direct effect on use, with more satisfied users being less inclined to employ workarounds or overrides of the system. Based on the findings, organizational structures that facilitate CDSS use and user satisfaction affect the extent to which pharmacy and health care management maximize use in the clinical pharmacy setting.

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

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.

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/.

Is there a need for a clinical decision rule in blunt wrist trauma?

PubMed

van den Brand, Crispijn L; van Leerdam, Roderick H; van Ufford, Jet H M E Quarles; Rhemrev, Steven J

2013-11-01

Blunt wrist trauma is a very common injury in emergency medicine. However, in contrast to other extremity trauma, there is no clinical decision rule for radiography in patients with blunt wrist trauma. The purpose of this study is to describe current practice and to assess the need and feasibility for a clinical decision rule for radiography in patients with blunt wrist trauma. All patients with blunt wrist trauma who presented to our Emergency Department (ED) during a 6-month period were included in this study. Basic demographics were analysed and the radiography ratio was determined. The radiography results were compared for different demographic groups. Current practice and the need and feasibility for a decision rule were evaluated using Stiell's checklist for clinical decision rules. A total of 1019 patients with 1032 blunt wrist injuries presented at our ED in a period of 6 months. In 91.4% of patients, radiographs were taken. In 41.6% of those radiographed, a fracture was visible on plain radiography. Fractures were most common in the paediatric and senior age groups. However, even in the lower-risk groups we observed a fracture incidence of about 20%. There is no need for a clinical decision rule for radiography in patients with blunt wrist trauma because the fracture ratio is high. Neither does it seem feasible to develop a highly sensitive and efficient decision rule. Therefore, the authors recommend radiography in all patients with blunt wrist trauma presenting to the ED. Copyright © 2013 Elsevier Ltd. All rights reserved.

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.

Clinical decisions for anterior restorations: the concept of restorative volume.

PubMed

Cardoso, Jorge André; Almeida, Paulo Júlio; Fischer, Alex; Phaxay, Somano Luang

2012-12-01

The choice of the most appropriate restoration for anterior teeth is often a difficult decision. Numerous clinical and technical factors play an important role in selecting the treatment option that best suits the patient and the restorative team. Experienced clinicians have developed decision processes that are often more complex than may seem. Less experienced professionals may find difficulties making treatment decisions because of the widely varied restorative materials available and often numerous similar products offered by different manufacturers. The authors reviewed available evidence and integrated their clinical experience to select relevant factors that could provide a logical and practical guideline for restorative decisions in anterior teeth. The presented concept of restorative volume is based on structural, optical, and periodontal factors. Each of these factors will influence the short- and long-term behavior of restorations in terms of esthetics, biology, and function. Despite the marked evolution of esthetic restorative techniques and materials, significant limitations still exist, which should be addressed by researchers. The presented guidelines must be regarded as a mere orientation for risk analysis. A comprehensive individual approach should always be the core of restorative esthetic treatments. The complex decision process for anterior esthetic restorations can be clarified by a systematized examination of structural, optical, and periodontal factors. The basis for the proposed thought process is the concept of restorative volume that is a contemporary interpretation of restoration categories and their application. © 2012 Wiley Periodicals, Inc.

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

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

Recommendations for Clinical Decision Support Deployment: Synthesis of a Roundtable of Medical Directors of Information Systems

PubMed Central

Jenders, Robert A.; Osheroff, Jerome A.; Sittig, Dean F.; Pifer, Eric A.; Teich, Jonathan M

2007-01-01

Background: Ample evidence exists that clinical decision support (CDS) can improve clinician performance. Nevertheless, additional evidence demonstrates that clinicians still do not perform adequately in many instances. This suggests an ongoing need for implementation of CDS, in turn prompting development of a roadmap for national action regarding CDS. Objective: Develop practical advice to aid CDS implementation in order to improve clinician performance. Method: Structured group interview during a roundtable discussion by medical directors of information systems (N = 30), with subsequent review by participants and synthesis. Results: Participant consensus was that CDS should be comprehensive and should involve techniques such as order sets and facilitated documentation as well as alerts; should be subject to ongoing feedback; and should flow from and be governed by an organization’s clinical goals. Conclusion: A structured roundtable discussion of clinicians experienced in health information technology can yield practical, consensus advice for implementation of CDS. PMID:18693858

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

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.

Whole mind and shared mind in clinical decision-making.

PubMed

Epstein, Ronald Mark

2013-02-01

To review the theory, research evidence and ethical implications regarding "whole mind" and "shared mind" in clinical practice in the context of chronic and serious illnesses. Selective critical review of the intersection of classical and naturalistic decision-making theories, cognitive neuroscience, communication research and ethics as they apply to decision-making and autonomy. Decision-making involves analytic thinking as well as affect and intuition ("whole mind") and sharing cognitive and affective schemas of two or more individuals ("shared mind"). Social relationships can help processing of complex information that otherwise would overwhelm individuals' cognitive capacities. Medical decision-making research, teaching and practice should consider both analytic and non-analytic cognitive processes. Further, research should consider that decisions emerge not only from the individual perspectives of patients, their families and clinicians, but also the perspectives that emerge from the interactions among them. Social interactions have the potential to enhance individual autonomy, as well as to promote relational autonomy based on shared frames of reference. Shared mind has the potential to result in wiser decisions, greater autonomy and self-determination; yet, clinicians and patients should be vigilant for the potential of hierarchical relationships to foster coercion or silencing of the patient's voice. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

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.

Clinical decision-making and secondary findings in systems medicine.

PubMed

Fischer, T; Brothers, K B; Erdmann, P; Langanke, M

2016-05-21

Systems medicine is the name for an assemblage of scientific strategies and practices that include bioinformatics approaches to human biology (especially systems biology); "big data" statistical analysis; and medical informatics tools. Whereas personalized and precision medicine involve similar analytical methods applied to genomic and medical record data, systems medicine draws on these as well as other sources of data. Given this distinction, the clinical translation of systems medicine poses a number of important ethical and epistemological challenges for researchers working to generate systems medicine knowledge and clinicians working to apply it. This article focuses on three key challenges: First, we will discuss the conflicts in decision-making that can arise when healthcare providers committed to principles of experimental medicine or evidence-based medicine encounter individualized recommendations derived from computer algorithms. We will explore in particular whether controlled experiments, such as comparative effectiveness trials, should mediate the translation of systems medicine, or if instead individualized findings generated through "big data" approaches can be applied directly in clinical decision-making. Second, we will examine the case of the Riyadh Intensive Care Program Mortality Prediction Algorithm, pejoratively referred to as the "death computer," to demonstrate the ethical challenges that can arise when big-data-driven scoring systems are applied in clinical contexts. We argue that the uncritical use of predictive clinical algorithms, including those envisioned for systems medicine, challenge basic understandings of the doctor-patient relationship. Third, we will build on the recent discourse on secondary findings in genomics and imaging to draw attention to the important implications of secondary findings derived from the joint analysis of data from diverse sources, including data recorded by patients in an attempt to realize their

Privacy-Preserving Patient-Centric Clinical Decision Support System on Naïve Bayesian Classification.

PubMed

Liu, Ximeng; Lu, Rongxing; Ma, Jianfeng; Chen, Le; Qin, Baodong

2016-03-01

Clinical decision support system, which uses advanced data mining techniques to help clinician make proper decisions, has received considerable attention recently. The advantages of clinical decision support system include not only improving diagnosis accuracy but also reducing diagnosis time. Specifically, with large amounts of clinical data generated everyday, naïve Bayesian classification can be utilized to excavate valuable information to improve a clinical decision support system. Although the clinical decision support system is quite promising, the flourish of the system still faces many challenges including information security and privacy concerns. In this paper, we propose a new privacy-preserving patient-centric clinical decision support system, which helps clinician complementary to diagnose the risk of patients' disease in a privacy-preserving way. In the proposed system, the past patients' historical data are stored in cloud and can be used to train the naïve Bayesian classifier without leaking any individual patient medical data, and then the trained classifier can be applied to compute the disease risk for new coming patients and also allow these patients to retrieve the top- k disease names according to their own preferences. Specifically, to protect the privacy of past patients' historical data, a new cryptographic tool called additive homomorphic proxy aggregation scheme is designed. Moreover, to leverage the leakage of naïve Bayesian classifier, we introduce a privacy-preserving top- k disease names retrieval protocol in our system. Detailed privacy analysis ensures that patient's information is private and will not be leaked out during the disease diagnosis phase. In addition, performance evaluation via extensive simulations also demonstrates that our system can efficiently calculate patient's disease risk with high accuracy in a privacy-preserving way.

Studying the effect of clinical uncertainty on physicians' decision-making using ILIAD.

PubMed

Anderson, J D; Jay, S J; Weng, H C; Anderson, M M

1995-01-01

The influence of uncertainty on physicians' practice behavior is not well understood. In this research, ILIAD, a diagnostic expert system, has been used to study physicians' responses to uncertainty and how their responses affected clinical performance. The simulation mode of ILIAD was used to standardize the presentation and scoring of two cases to 46 residents in emergency medicine, internal medicine, family practice and transitional medicine at Methodist Hospital of Indiana. A questionnaire was used to collect additional data on how physicians respond to clinical uncertainty. A structural equation model was developed, estimated, and tested. The results indicate that stress that physicians experience in dealing with clinical uncertainty has a negative effect on their clinical performance. Moreover, the way that physicians respond to uncertainty has positive and negative effects on their performance. Open discussions with patients about clinical decisions and the use of practice guidelines improves performance. However, when the physician's clinical decisions are influenced by patient demands or their peers, their performance scores decline.

Medical students, clinical preventive services, and shared decision-making.

PubMed

Keefe, Carole W; Thompson, Margaret E; Noel, Mary Margaret

2002-11-01

Improving access to preventive care requires addressing patient, provider, and systems barriers. Patients often lack knowledge or are skeptical about the importance of prevention. Physicians feel that they have too little time, are not trained to deliver preventive services, and are concerned about the effectiveness of prevention. We have implemented an educational module in the required family practice clerkship (1) to enhance medical student learning about common clinical preventive services and (2) to teach students how to inform and involve patients in shared decision making about those services. Students are asked to examine available evidence-based information for preventive screening services. They are encouraged to look at the recommendations of various organizations and use such resources as reports from the U.S. Preventive Services Task Force to determine recommendations they want to be knowledgeable about in talking with their patients. For learning shared decision making, students are trained to use a model adapted from Braddock and colleagues(1) to discuss specific screening services and to engage patients in the process of making informed decisions about what is best for their own health. The shared decision making is presented and modeled by faculty, discussed in small groups, and students practice using Web-based cases and simulations. The students are evaluated using formative and summative performance-based assessments as they interact with simulated patients about (1) screening for high blood cholesterol and other lipid abnormalities, (2) screening for colorectal cancer, (3) screening for prostate cancer, and (4) screening for breast cancer. The final student evaluation is a ten-minute, videotaped discussion with a simulated patient about screening for colorectal cancer that is graded against a checklist that focuses primarily on the elements of shared decision making. Our medical students appear quite willing to accept shared decision making as

Clinical decision rules, spinal pain classification and prediction of treatment outcome: A discussion of recent reports in the rehabilitation literature

PubMed Central

2012-01-01

Clinical decision rules are an increasingly common presence in the biomedical literature and represent one strategy of enhancing clinical-decision making with the goal of improving the efficiency and effectiveness of healthcare delivery. In the context of rehabilitation research, clinical decision rules have been predominantly aimed at classifying patients by predicting their treatment response to specific therapies. Traditionally, recommendations for developing clinical decision rules propose a multistep process (derivation, validation, impact analysis) using defined methodology. Research efforts aimed at developing a “diagnosis-based clinical decision rule” have departed from this convention. Recent publications in this line of research have used the modified terminology “diagnosis-based clinical decision guide.” Modifications to terminology and methodology surrounding clinical decision rules can make it more difficult for clinicians to recognize the level of evidence associated with a decision rule and understand how this evidence should be implemented to inform patient care. We provide a brief overview of clinical decision rule development in the context of the rehabilitation literature and two specific papers recently published in Chiropractic and Manual Therapies. PMID:22726639

An integrated review of the correlation between critical thinking ability and clinical decision-making in nursing.

PubMed

Lee, Daphne Sk; Abdullah, Khatijah Lim; Subramanian, Pathmawathi; Bachmann, Robert Thomas; Ong, Swee Leong

2017-12-01

To explore whether there is a correlation between critical thinking ability and clinical decision-making among nurses. Critical thinking is currently considered as an essential component of nurses' professional judgement and clinical decision-making. If confirmed, nursing curricula may be revised emphasising on critical thinking with the expectation to improve clinical decision-making and thus better health care. Integrated literature review. The integrative review was carried out after a comprehensive literature search using electronic databases Ovid, EBESCO MEDLINE, EBESCO CINAHL, PROQuest and Internet search engine Google Scholar. Two hundred and 22 articles from January 1980 to end of 2015 were retrieved. All studies evaluating the relationship between critical thinking and clinical decision-making, published in English language with nurses or nursing students as the study population, were included. No qualitative studies were found investigating the relationship between critical thinking and clinical decision-making, while 10 quantitative studies met the inclusion criteria and were further evaluated using the Quality Assessment and Validity Tool. As a result, one study was excluded due to a low-quality score, with the remaining nine accepted for this review. Four of nine studies established a positive relationship between critical thinking and clinical decision-making. Another five studies did not demonstrate a significant correlation. The lack of refinement in studies' design and instrumentation were arguably the main reasons for the inconsistent results. Research studies yielded contradictory results as regard to the relationship between critical thinking and clinical decision-making; therefore, the evidence is not convincing. Future quantitative studies should have representative sample size, use critical thinking measurement tools related to the healthcare sector and evaluate the predisposition of test takers towards their willingness and ability to think

Do educational interventions improve nurses' clinical decision making and judgement? A systematic review.

PubMed

Thompson, Carl; Stapley, Sally

2011-07-01

Despite the growing popularity of decision making in nursing curricula, the effectiveness of educational interventions to improve nursing judgement and decision making is unknown. We sought to synthesise and summarise the comparative evidence for educational interventions to improve nursing judgements and clinical decisions. A systematic review. Electronic databases: Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, CINAHL and PsycINFO, Social Sciences Citation Index, OpenSIGLE conference proceedings and hand searching nursing journals. Studies published since 1960, reporting any educational intervention that aimed to improve nurses' clinical judgements or decision making were included. Studies were assessed for relevance and quality. Data extracted included study design; educational setting; the nature of participants; whether the study was concerned with the clinical application of skills or the application of theory; the type of decision targeted by the intervention (e.g. diagnostic reasoning) and whether the evaluation of the intervention focused on efficacy or effectiveness. A narrative approach to study synthesis was used due to heterogeneity in interventions, study samples, outcomes and settings and incomplete reporting of effect sizes. From 5262 initial citations 24 studies were included in the review. A variety of educational approaches were reported. Study quality and content reporting was generally poor. Pedagogical theories were widely used but use of decision theory (with the exception of subjective expected utility theory implicit in decision analysis) was rare. The effectiveness and efficacy of interventions was mixed. Educational interventions to improve nurses' judgements and decisions are complex and the evidence from comparative studies does little to reduce the uncertainty about 'what works'. Nurse educators need to pay attention to decision, as well as pedagogical, theory in the design of interventions. Study design and

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 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

Clinical decision support systems for addressing information needs of physicians.

PubMed

Denekamp, Yaron

2007-11-01

Clinicians routinely practice in a state of incomplete information--about the patient, and about medical knowledge pertaining to patients' care. Consequently, there is now growing interest in the use of CDSS to bring decision support to the point of care. CDSS can impact physician behavior in routine practice. Nonetheless, CDSSs are meant to support humans who are ultimately responsible for the clinical decisions, rather than replace them. Although the adoption of CDSS has proceeded at a slow pace, there is a widespread recognition that CDSSs are expected to play a crucial role in reducing medical errors and improving the quality and efficacy of health care. This will be facilitated by the gradual maturation of electronic health record systems and the emergence of standard terminologies and messaging standards for the exchange of clinical data.

Human Cognitive Limitations. Broad, Consistent, Clinical Application of Physiological Principles Will Require Decision Support.

PubMed

Morris, Alan H

2018-02-01

Our education system seems to fail to enable clinicians to broadly understand core physiological principles. The emphasis on reductionist science, including "omics" branches of research, has likely contributed to this decrease in understanding. Consequently, clinicians cannot be expected to consistently make clinical decisions linked to best physiological evidence. This is a large-scale problem with multiple determinants, within an even larger clinical decision problem: the failure of clinicians to consistently link their decisions to best evidence. Clinicians, like all human decision-makers, suffer from significant cognitive limitations. Detailed context-sensitive computer protocols can generate personalized medicine instructions that are well matched to individual patient needs over time and can partially resolve this problem.

Assessing an Adolescent's Capacity for Autonomous Decision-Making in Clinical Care.

PubMed

Michaud, Pierre-André; Blum, Robert Wm; Benaroyo, Lazare; Zermatten, Jean; Baltag, Valentina

2015-10-01

The purpose of this article is to provide policy guidance on how to assess the capacity of minor adolescents for autonomous decision-making without a third party authorization, in the field of clinical care. In June 2014, a two-day meeting gathered 20 professionals from all continents, working in the field of adolescent medicine, neurosciences, developmental and clinical psychology, sociology, ethics, and law. Formal presentations and discussions were based on a literature search and the participants' experience. The assessment of adolescent decision-making capacity includes the following: (1) a review of the legal context consistent with the principles of the Convention on the Rights of the Child; (2) an empathetic relationship between the adolescent and the health care professional/team; (3) the respect of the adolescent's developmental stage and capacities; (4) the inclusion, if relevant, of relatives, peers, teachers, or social and mental health providers with the adolescent's consent; (5) the control of coercion and other social forces that influence decision-making; and (6) a deliberative stepwise appraisal of the adolescent's decision-making process. This stepwise approach, already used among adults with psychiatric disorders, includes understanding the different facets of the given situation, reasoning on the involved issues, appreciating the outcomes linked with the decision(s), and expressing a choice. Contextual and psychosocial factors play pivotal roles in the assessment of adolescents' decision-making capacity. The evaluation must be guided by a well-established procedure, and health professionals should be trained accordingly. These proposals are the first to have been developed by a multicultural, multidisciplinary expert panel. Copyright © 2015 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

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.

Backgrounds in Language.

ERIC Educational Resources Information Center

Maxwell, John C.; Long, Barbara K.

"Backgrounds in Language," a field-tested inservice course designed for use by groups of 15 or 25 language arts teachers, provides the subject matter background teachers need to make informed decisions about what curriculum materials to use in what way, at what time, and with which students. The course is comprised of eight 2-hour sessions,…

Nurses' Use of Race in Clinical Decision Making.

PubMed

Sellers, Sherrill L; Moss, Melissa E; Calzone, Kathleen; Abdallah, Khadijah E; Jenkins, Jean F; Bonham, Vence L

2016-11-01

To examine nurses' self-reported use of race in clinical evaluation. This cross-sectional study analyzed data collected from three separate studies using the Genetics and Genomics in Nursing Practice Survey, which includes items about use of race and genomic information in nursing practice. The Racial Attributes in Clinical Evaluation (RACE) scale was used to measure explicit clinical use of race among nurses from across the United States. Multivariate regression analysis was used to examine associations between RACE score and individual-level characteristics and beliefs in 5,733 registered nurses. Analysis revealed significant relationships between RACE score and nurses' race and ethnicity, educational level, and views on the clinical importance of patient demographic characteristics. Asian nurses reported RACE scores 1.41 points higher than White nurses (p < .001), and Black nurses reported RACE scores 0.55 points higher than White nurses (p < .05). Compared to diploma-level nurses, the baccalaureate-level nurses reported 0.69 points higher RACE scores (p < .05), master's-level nurses reported 1.63 points higher RACE scores (p < .001), and doctorate-level nurses reported 1.77 points higher RACE scores (p < .01). In terms of clinical importance of patient characteristics, patient race and ethnicity corresponded to a 0.54-point increase in RACE score (p < .001), patient genes to a 0.21-point increase in RACE score (p < .001), patient family history to a 0.15-point increase in RACE score (p < .01), and patient age to a 0.19-point increase in RACE score (p < .001). Higher reported use of race among minority nurses may be due, in part, to differential levels of racial self-awareness. A relatively linear positive relationship between level of nursing degree nursing education and use of race suggests that a stronger foundation of knowledge about genetic ancestry, population genetics and the concept "race" and genetic ancestry may increase in clinical decision making

Exploring the use of Option Grid™ patient decision aids in a sample of clinics in Poland.

PubMed

Scalia, Peter; Elwyn, Glyn; Barr, Paul; Song, Julia; Zisman-Ilani, Yaara; Lesniak, Monika; Mullin, Sarah; Kurek, Krzysztof; Bushell, Matt; Durand, Marie-Anne

2018-05-29

Research on the implementation of patient decision aids to facilitate shared decision making in clinical settings has steadily increased across Western countries. A study which implements decision aids and measures their impact on shared decision making has yet to be conducted in the Eastern part of Europe. To study the use of Option Grid TM patient decision aids in a sample of Grupa LUX MED clinics in Warsaw, Poland, and measure their impact on shared decision making. We conducted a pre-post interventional study. Following a three-month period of usual care, clinicians from three Grupa LUX MED clinics received a one-hour training session on how to use three Option Grid TM decision aids and were provided with copies for use for four months. Throughout the study, all eligible patients were asked to complete the three-item CollaboRATE patient-reported measure of shared decision making after their clinical encounter. CollaboRATE enables patients to assess the efforts clinicians make to: (i) inform them about their health issues; (ii) listen to 'what matters most'; (iii) integrate their treatment preference in future plans. A Hierarchical Logistic Regression model was performed to understand which variables had an effect on CollaboRATE. 2,048 patients participated in the baseline phase; 1,889 patients participated in the intervention phase. Five of the thirteen study clinicians had a statistically significant increase in their CollaboRATE scores (p<.05) when comparing baseline phase to intervention phase. All five clinicians were located at the same clinic, the only clinic where an overall increase (non-significant) in the mean CollaboRATE top score percentage occurred from baseline phase (M=60 %, SD=0.49; 95 % CI [57-63 %]) to intervention phase (M=62 %, SD=0.49; 95% CI [59-65%]). Only three of those five clinicians who had a statistically significant increase had a clinically significant difference. The implementation of Option Grid TM helped some clinicians

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

Implementation of a cystic fibrosis lung transplant referral patient decision aid in routine clinical practice: an observational study.

PubMed

Stacey, Dawn; Vandemheen, Katherine L; Hennessey, Rosamund; Gooyers, Tracy; Gaudet, Ena; Mallick, Ranjeeta; Salgado, Josette; Freitag, Andreas; Berthiaume, Yves; Brown, Neil; Aaron, Shawn D

2015-02-07

The decision to have lung transplantation as treatment for end-stage lung disease from cystic fibrosis (CF) has benefits and serious risks. Although patient decision aids are effective interventions for helping patients reach a quality decision, little is known about implementing them in clinical practice. Our study evaluated a sustainable approach for implementing a patient decision aid for adults with CF considering referral for lung transplantation. A prospective pragmatic observational study was guided by the Knowledge-to-Action Framework. Healthcare professionals in all 23 Canadian CF clinics were eligible. We surveyed participants regarding perceived barriers and facilitators to patient decision aid use. Interventions tailored to address modifiable identified barriers included training, access to decision aids, and conference calls. The primary outcome was >80% use of the decision aid in year 2. Of 23 adult CF clinics, 18 participated (78.2%) and 13 had healthcare professionals attend training. Baseline barriers were healthcare professionals' inadequate knowledge for supporting patients making decisions (55%), clarifying patients' values for outcomes of options (58%), and helping patients handle conflicting views of others (71%). Other barriers were lack of time (52%) and needing to change how transplantation is discussed (42%). Baseline facilitators were healthcare professionals feeling comfortable discussing bad transplantation outcomes (74%), agreeing the decision aid would be easy to experiment with (71%) and use in the CF clinic (87%), and agreeing that using the decision aid would not require reorganization of the CF clinic (90%). After implementing the decision aid with interventions tailored to the barriers, decision aid use increased from 29% at baseline to 85% during year 1 and 92% in year 2 (p < 0.001). Compared to baseline, more healthcare professionals at the end of the study were confident in supporting decision-making (p = 0.03) but

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

Deepening the quality of clinical reasoning and decision-making in rural hospital nursing practice.

PubMed

Sedgwick, M G; Grigg, L; Dersch, S

2014-01-01

Rural acute care nursing requires an extensive breadth and depth of knowledge as well as the ability to quickly reason through problems in order to make sound clinical decisions. This reasoning often occurs within an environment that has minimal medical or ancillary support. Registered nurses (RN) new to rural nursing, and employers, have raised concerns about patient safety while new nurses make the transition into rural practice. In addition, feeling unprepared for the rigors of rural hospital nursing practice is a central issue influencing RN recruitment and retention. Understanding how rural RNs reason is a key element for identifying professional development needs and may support recruitment and retention of skilled rural nurses. The purpose of this study was to explore how rural RNs reason through clinical problems as well as to assess the quality of such reasoning. This study used a non-traditional approach for data collection. Fifteen rural acute care nurses with varying years of experience working in southern Alberta, Canada, were observed while they provided care to patients of varying acuity within a simulated rural setting. Following the simulation, semi-structured interviews were conducted using a substantive approach to critical thinking. Findings revealed that the ability to engage in deep clinical reasoning varied considerably among participants despite being given the same information under the same circumstances. Furthermore, the number of years of experience did not seem to be directly linked to the ability to engage in sound clinical reasoning. Novice nurses, however, did rely heavily on others in their decision making in order to ensure they were making the right decision. Hence, their relationships with other staff members influenced their ability to engage in clinical reasoning and decision making. In situations where the patient's condition was deteriorating quickly, regardless of years of experience, all of the participants depended on

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.

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

Decision tree-based method for integrating gene expression, demographic, and clinical data to determine disease endotypes

PubMed Central

2013-01-01

Background Complex diseases are often difficult to diagnose, treat and study due to the multi-factorial nature of the underlying etiology. Large data sets are now widely available that can be used to define novel, mechanistically distinct disease subtypes (endotypes) in a completely data-driven manner. However, significant challenges exist with regard to how to segregate individuals into suitable subtypes of the disease and understand the distinct biological mechanisms of each when the goal is to maximize the discovery potential of these data sets. Results A multi-step decision tree-based method is described for defining endotypes based on gene expression, clinical covariates, and disease indicators using childhood asthma as a case study. We attempted to use alternative approaches such as the Student’s t-test, single data domain clustering and the Modk-prototypes algorithm, which incorporates multiple data domains into a single analysis and none performed as well as the novel multi-step decision tree method. This new method gave the best segregation of asthmatics and non-asthmatics, and it provides easy access to all genes and clinical covariates that distinguish the groups. Conclusions The multi-step decision tree method described here will lead to better understanding of complex disease in general by allowing purely data-driven disease endotypes to facilitate the discovery of new mechanisms underlying these diseases. This application should be considered a complement to ongoing efforts to better define and diagnose known endotypes. When coupled with existing methods developed to determine the genetics of gene expression, these methods provide a mechanism for linking genetics and exposomics data and thereby accounting for both major determinants of disease. PMID:24188919

What We Can Learn from Amazon for Clinical Decision Support Systems.

PubMed

Abid, Sidra; Keshavjee, Karim; Karim, Arsalan; Guergachi, Aziz

2017-01-01

Health care continue to lag behind other industries, such as retail and financial services, in the use of decision-support-like tools. Amazon is particularly prolific in the use of advanced predictive and prescriptive analytics to assist its customers to purchase more, while increasing satisfaction, retention, repeat-purchases and loyalty. How can we do the same in health care? In this paper, we explore various elements of the Amazon website and Amazon's data science and big data practices to gather inspiration for re-designing clinical decision support in the health care sector. For each Amazon element we identified, we present one or more clinical applications to help us better understand where Amazon's.

Impact of clinical decision rules on clinical care of traumatic injuries to the foot and ankle, knee, cervical spine, and head.

PubMed

Perry, Jeffrey J; Stiell, Ian G

2006-12-01

Traumatic injuries to the ankle/foot, knee, cervical spine, and head are very commonly seen in emergency and accident departments around the world. There has been much interest in the development of clinical decision rules to help guide the investigations of these patients in a standardised and cost-effective manner. In this article we reviewed the impact of the Ottawa ankle rules, Ottawa knee rules, Canadian C-spine rule and the Canadian CT head rule. The studies conducted have confirmed that the use of well developed clinical decision rules results in less radiography, less time spent in the emergency department and does not decrease patient satisfaction or result in misdiagnosis. Emergency physicians around the world should adopt the use of clinical decision rules for ankle/foot, knee, cervical spine and minor head injuries. With relatively simple implementation strategies, care can be standardized and costs reduced while providing excellent clinical 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.

Mobile learning app: A novel method to teach clinical decision making in prosthodontics.

PubMed

Deshpande, Saee; Chahande, Jaishree; Rathi, Akhil

2017-01-01

Prosthodontics involves replacing lost dentofacial structures using artificial substitutes. Due to availability of many materials and techniques, clinician's clinical decision-making regarding appropriate selection of prosthesis requires critical thinking abilities and is demanding. Especially during graduate training years, learners do not receive the exposure to a variety of cases, thus their clinical reasoning skills are not developed optimally. Therefore, using the trend of incorporating technology in education, we developed a mobile learning app for this purpose. The aim of this study was to evaluate learners' perceptions of this app's utility and impact on their clinical decision-making skills. After taking informed consent, interns of the Department of Prosthodontics of VSPM Dental College, Nagpur, India, during the academic year May 2015-May 2016 were sent the link for the app to be installed in their Android smartphones. Their perceptions were recorded on a feedback questionnaire using 5-point Likert scale. The script concordance test (SCT) was used to check for changes in clinical reasoning abilities. Out of 120 students who were sent the link, 102 downloaded the link and 92 completed the feedback questionnaire and appeared for the SCT (response rate: 76%). The overall response to the app was positive for more than two-thirds of interns, who reported a greater confidence in their clinical decision-making around prostheses through this app and 94% of the students felt that this app should be regularly used along with conventional teaching techniques. Mean SCT scores were pretest 41.5 (±1.7) and posttest 63 (±2.4) (P < 0.005). Clinical decision-making in prosthodontics, a mobile learning app, is an effective way to improve clinical reasoning skills for planning prosthodontic rehabilitation. It is well received by students.

The interaction of patient race, provider bias, and clinical ambiguity on pain management decisions.

PubMed

Hirsh, Adam T; Hollingshead, Nicole A; Ashburn-Nardo, Leslie; Kroenke, Kurt

2015-06-01

Although racial disparities in pain care are widely reported, much remains to be known about the role of provider and contextual factors. We used computer-simulated patients to examine the influence of patient race, provider racial bias, and clinical ambiguity on pain decisions. One hundred twenty-nine medical residents/fellows made assessment (pain intensity) and treatment (opioid and nonopioid analgesics) decisions for 12 virtual patients with acute pain. Race (black/white) and clinical ambiguity (high/low) were manipulated across vignettes. Participants completed the Implicit Association Test and feeling thermometers, which assess implicit and explicit racial biases, respectively. Individual- and group-level analyses indicated that race and ambiguity had an interactive effect on providers' decisions, such that decisions varied as a function of ambiguity for white but not for black patients. Individual differences across providers were observed for the effect of race and ambiguity on decisions; however, providers' implicit and explicit biases did not account for this variability. These data highlight the complexity of racial disparities and suggest that differences in care between white and black patients are, in part, attributable to the nature (ie, ambiguity) of the clinical scenario. The current study suggests that interventions to reduce disparities should differentially target patient, provider, and contextual factors. This study examined the unique and collective influence of patient race, provider racial bias, and clinical ambiguity on providers' pain management decisions. These results could inform the development of interventions aimed at reducing disparities and improving pain care. Copyright © 2015 American Pain Society. Published by 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.

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

Making medical decisions in dependence of genetic background: estimation of the utility of DNA testing in clinical, pharmaco-epidemiological or genetic studies.

PubMed

Nguyen, Thuy Trang; Schäfer, Helmut; Timmesfeld, Nina

2013-05-01

An index measuring the utility of testing a DNA marker before deciding between two alternative treatments is proposed which can be estimated from pharmaco-epidemiological case-control or cohort studies. In the case-control design, external estimates of the prevalence of the disease and of the frequency of the genetic risk variant are required for estimating the utility index. Formulas for point and interval estimates are derived. Empirical coverage probabilities of the confidence intervals were estimated under different scenarios of disease prevalence, prevalence of drug use, and population frequency of the genetic variant. To illustrate our method, we re-analyse pharmaco-epidemiological case-control data on oral contraceptive intake and venous thrombosis in carriers and non-carriers of the factor V Leiden mutation. We also re-analyse cross-sectional data from the Framingham study on a gene-diet interaction between an APOA2 polymorphism and high saturated fat intake on obesity. We conclude that the utility index may be helpful to evaluate and appraise the potential clinical and public health relevance of gene-environment interaction effects detected in genomic and candidate gene association studies and may be a valuable decision support for designing prospective studies on the clinical utility. © 2013 Wiley Periodicals, Inc.

Enhancing decision making about participation in cancer clinical trials: development of a question prompt list

PubMed Central

Brown, Richard F.; Shuk, Elyse; Leighl, Natasha; Butow, Phyllis; Ostroff, Jamie; Edgerson, Shawna; Tattersall, Martin

2016-01-01

Purpose Slow accrual to cancer clinical trials impedes the progress of effective new cancer treatments. Poor physician–patient communication has been identified as a key contributor to low trial accrual. Question prompt lists (QPLs) have demonstrated a significant promise in facilitating communication in general, surgical, and palliative oncology settings. These simple patient interventions have not been tested in the oncology clinical trial setting. We aimed to develop a targeted QPL for clinical trials (QPL-CT). Method Lung, breast, and prostate cancer patients who either had (trial experienced) or had not (trial naive) participated in a clinical trial were invited to join focus groups to help develop and explore the acceptability of a QPL-CT. Focus groups were audio-recorded and transcribed. A research team, including a qualitative data expert, analyzed these data to explore patients’ decision-making processes and views about the utility of the QPL-CT prompt to aid in trial decision making. Results Decision making was influenced by the outcome of patients’ comparative assessment of perceived risks versus benefits of a trial, and the level of trust patients had in their doctors’ recommendation about the trial. Severity of a patient’s disease influenced trial decision making only for trial-naive patients. Conclusion Although patients were likely to prefer a paternalistic decision-making style, they expressed valuation of the QPL as an aid to decision making. QPL-CT utility extended beyond the actual consultation to include roles both before and after the clinical trial discussion. PMID:20593202

Features of computerized clinical decision support systems supportive of nursing practice: a literature review.

PubMed

Lee, Seonah

2013-10-01

This study aimed to organize the system features of decision support technologies targeted at nursing practice into assessment, problem identification, care plans, implementation, and outcome evaluation. It also aimed to identify the range of the five stage-related sequential decision supports that computerized clinical decision support systems provided. MEDLINE, CINAHL, and EMBASE were searched. A total of 27 studies were reviewed. The system features collected represented the characteristics of each category from patient assessment to outcome evaluation. Several features were common across the reviewed systems. For the sequential decision support, all of the reviewed systems provided decision support in sequence for patient assessment and care plans. Fewer than half of the systems included problem identification. There were only three systems operating in an implementation stage and four systems in outcome evaluation. Consequently, the key steps for sequential decision support functions were initial patient assessment, problem identification, care plan, and outcome evaluation. Providing decision support in such a full scope will effectively help nurses' clinical decision making. By organizing the system features, a comprehensive picture of nursing practice-oriented computerized decision support systems was obtained; however, the development of a guideline for better systems should go beyond the scope of a literature review.

Design Recommendations for Pharmacogenomics Clinical Decision Support Systems

PubMed Central

Khelifi, Maher; Tarczy-Hornoch, Peter; Devine, Emily B.; Pratt, Wanda

2017-01-01

The use of pharmacogenomics (PGx) in clinical practice still faces challenges to fully adopt genetic information in targeting drug therapy. To incorporate genetics into clinical practice, many support the use of Pharmacogenomics Clinical Decision Support Systems (PGx-CDS) for medication prescriptions. This support was fueled by new guidelines to incorporate genetics for optimizing drug dosage and reducing adverse events. In addition, the complexity of PGx led to exploring CDS outside the paradigm of the basic CDS tools embedded in commercial electronic health records. Therefore, designing the right CDS is key to unleashing the full potential of pharmacogenomics and making it a part of clinicians’ daily workflow. In this work, we 1) identify challenges and barriers of the implementation of PGx-CDS in clinical settings, 2) develop a new design approach to CDS with functional characteristics that can improve the adoption of pharmacogenomics guidelines and thus patient safety, and 3) create design guidelines and recommendations for such PGx-CDS tools. PMID:28815136

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.

Nurses’ Use of Race in Clinical Decision Making

PubMed Central

Sellers, Sherrill L.; Moss, Melissa E.; Calzone, Kathleen; Abdallah, Khadijah E.; Jenkins, Jean F.; Bonham, Vence L.

2017-01-01

ancestry may increase in clinical decision making could allow nurses to more appropriately use of race in clinical care. Integrating patient demographic characteristics into clinical decisions is an important component of nursing practice. Clinical Relevance Registered nurses provide care for diverse racial and ethnic patient populations and stand on the front line of clinical care, making them essential for reducing racial and ethnic disparities in healthcare delivery. Exploring registered nurses’ individual-level characteristics and clinical use of race may provide a more comprehensive understanding of specific training needs and inform nursing education and practice. PMID:27676232

The Use of Intuition in Homeopathic Clinical Decision Making: An Interpretative Phenomenological Study

PubMed Central

Brien, Sarah; Dibb, Bridget; Burch, Alex

2011-01-01

While intuition plays a role in clinical decision making within conventional medicine, little is understood about its use in complementary and alternative medicine (CAM). The aim of this qualitative study was to investigate intuition from the perspective of homeopathic practitioners; its' manifestation, how it was recognized, its origins and when it was used within daily clinical practice. Semi-structured interviews were carried out with clinically experienced non-National Health Service (NHS) UK homeopathic practitioners. Interpretative phenomenological analysis was used to analyze the data. Homeopaths reported many similarities with conventional medical practitioner regarding the nature, perceived origin and manifestation of their intuitions in clinical practice. Intuition was used in two key aspects of the consultation: (i) to enhance the practitioner-patient relationship, these were generally trusted; and (ii) intuitions relating to the prescribing decision. Homeopaths were cautious about these latter intuitions, testing any intuitive thoughts through deductive reasoning before accepting them. Their reluctance is not surprising given the consequences for patient care, but we propose this also reflects homeopaths' sensitivity to the academic and medical mistrust of both homeopathy and intuition. This study is the first to explore the use of intuition in decision making in any form of complementary medicine. The similarities with conventional practitioners may provide confidence in validating intuition as a legitimate part of the decision making process for these specific practitioners. Further work is needed to elucidate if these findings reflect intuitive use in clinical practice of other CAM practitioners in both private and NHS (i.e., time limited) settings. PMID:19773389

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.

What Is a "Good" Treatment Decision? Decisional Control, Knowledge, Treatment Decision Making, and Quality of Life in Men with Clinically Localized Prostate Cancer.

PubMed

Orom, Heather; Biddle, Caitlin; Underwood, Willie; Nelson, Christian J; Homish, D Lynn

2016-08-01

We explored whether active patient involvement in decision making and greater patient knowledge are associated with better treatment decision-making experiences and better quality of life (QOL) among men with clinically localized prostate cancer. Localized prostate cancer treatment decision making is an advantageous model for studying patient treatment decision-making dynamics because there are multiple treatment options and a lack of empirical evidence to recommend one over the other; consequently, it is recommended that patients be fully involved in making the decision. Men with newly diagnosed clinically localized prostate cancer (N = 1529) completed measures of decisional control, prostate cancer knowledge, and decision-making experiences (decisional conflict and decision-making satisfaction and difficulty) shortly after they made their treatment decision. Prostate cancer-specific QOL was assessed at 6 months after treatment. More active involvement in decision making and greater knowledge were associated with lower decisional conflict and higher decision-making satisfaction but greater decision-making difficulty. An interaction between decisional control and knowledge revealed that greater knowledge was only associated with greater difficulty for men actively involved in making the decision (67% of sample). Greater knowledge, but not decisional control, predicted better QOL 6 months after treatment. Although men who are actively involved in decision making and more knowledgeable may make more informed decisions, they could benefit from decisional support (e.g., decision-making aids, emotional support from providers, strategies for reducing emotional distress) to make the process easier. Men who were more knowledgeable about prostate cancer and treatment side effects at the time that they made their treatment decision may have appraised their QOL as higher because they had realistic expectations about side effects. © The Author(s) 2016.

Decision analysis in clinical cardiology: When is coronary angiography required in aortic stenosis

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

Georgeson, S.; Meyer, K.B.; Pauker, S.G.

1990-03-15

Decision analysis offers a reproducible, explicit approach to complex clinical decisions. It consists of developing a model, typically a decision tree, that separates choices from chances and that specifies and assigns relative values to outcomes. Sensitivity analysis allows exploration of alternative assumptions. Cost-effectiveness analysis shows the relation between dollars spent and improved health outcomes achieved. In a tutorial format, this approach is applied to the decision whether to perform coronary angiography in a patient who requires aortic valve replacement for critical aortic stenosis.

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.

Development and use of active clinical decision support for preemptive pharmacogenomics

PubMed Central

Bell, Gillian C; Crews, Kristine R; Wilkinson, Mark R; Haidar, Cyrine E; Hicks, J Kevin; Baker, Donald K; Kornegay, Nancy M; Yang, Wenjian; Cross, Shane J; Howard, Scott C; Freimuth, Robert R; Evans, William E; Broeckel, Ulrich; Relling, Mary V; Hoffman, James M

2014-01-01

Background Active clinical decision support (CDS) delivered through an electronic health record (EHR) facilitates gene-based drug prescribing and other applications of genomics to patient care. Objective We describe the development, implementation, and evaluation of active CDS for multiple pharmacogenetic test results reported preemptively. Materials and methods Clinical pharmacogenetic test results accompanied by clinical interpretations are placed into the patient's EHR, typically before a relevant drug is prescribed. Problem list entries created for high-risk phenotypes provide an unambiguous trigger for delivery of post-test alerts to clinicians when high-risk drugs are prescribed. In addition, pre-test alerts are issued if a very-high risk medication is prescribed (eg, a thiopurine), prior to the appropriate pharmacogenetic test result being entered into the EHR. Our CDS can be readily modified to incorporate new genes or high-risk drugs as they emerge. Results Through November 2012, 35 customized pharmacogenetic rules have been implemented, including rules for TPMT with azathioprine, thioguanine, and mercaptopurine, and for CYP2D6 with codeine, tramadol, amitriptyline, fluoxetine, and paroxetine. Between May 2011 and November 2012, the pre-test alerts were electronically issued 1106 times (76 for thiopurines and 1030 for drugs metabolized by CYP2D6), and the post-test alerts were issued 1552 times (1521 for TPMT and 31 for CYP2D6). Analysis of alert outcomes revealed that the interruptive CDS appropriately guided prescribing in 95% of patients for whom they were issued. Conclusions Our experience illustrates the feasibility of developing computational systems that provide clinicians with actionable alerts for gene-based drug prescribing at the point of care. PMID:23978487

Genes and personality characteristics: Possible association of the genetic background with intelligence and decision making in 830 Caucasian Greek subjects

PubMed Central

Marinos, Georgios; Naziris, Nikolaos; Limnaios, Stefanos A.; Drakoulis, Nikolaos

2014-01-01

It is well known that intelligence consists of a variety of interactional and cognitive skills and abilities (e.g. tradecraft; critical and divergent thinking; perception of foreign information). Decision making is defined as the conscious choice between given options, relating to a problem. Both genetic background and environment comprise key elements for personality characteristics of the human being. The aim of this study is to determine the frequency distribution of rs324420, rs1800497, rs363050, rs6265, rs1328674 polymorphisms known to be involved in individual personality characteristics, in 830 Greek Subjects. The study is independent from direct clinical measurements (e.g. IQ measurements; physiological tests). The population of the volunteers is described, based on genotype, sex, with the respective gene frequencies, including the Minor Allele Frequency (MAF). A potential influence of the volunteer gender with the above characteristics (based on genotypes and alleles) is examined and finally, volunteers are classified as follows: A volunteer receives + 1, for each genotype/allele, which enhances his intelligence or his decision-making. In contrast, he receives − 1, for each genotype/allele, which relegates the individual characteristic. No statistically significant gender-characteristics correlation is observed. According to their genetic profile, a rate of 92.5%, of the volunteers may be characterized by prudence and temperance of thought, with only a small proportion of them (7.5%) may be classified as genetically spontaneous and adventurous. Regarding intelligence, the study population may lay around average and a little above it, at a rate of 96.3%, while the edges of the scale suggest only a 0.5% of the volunteers, who, although the “smartest”, somehow seem to lack prudence. In conclusion, individuals with low cognitive ability may be more prudent than others and vice versa, while the “smartest” ones tend to be more risky, in decision

Emergency physicians' attitudes toward and use of clinical decision rules for radiography.

PubMed

Graham, I D; Stiell, I G; Laupacis, A; O'Connor, A M; Wells, G A

1998-02-01

1) To assess Canadian emergency physicians' (EPs') use of and attitudes toward 2 radiographic clinical decision rules that have recently been developed and to identify physician characteristics associated with decision rule use; 2) to determine the use of CT head and cervical spine radiography by EPs and their beliefs about the appropriateness of expert recommendations supporting the routine use of these radiographic procedures; and 3) to determine the potential acceptance of clinical decision rules for CT scan in patients with minor head injury and cervical spine radiography in trauma patients. A cross-sectional anonymous mail survey of a random sample of 300 members of the Canadian Association of Emergency Physicians using Dillman's Total Design Method for mail surveys. Of 288 eligible physicians, 232 (81%) responded. More than 95% of the respondents stated they currently used the Ottawa Ankle Rules and were willing to consider using the newly developed Ottawa Knee Rule. Physician characteristics related to frequent use of the Ottawa Ankle Rules were younger age, fewer years since graduating from medical school, part time or resident employment status, working in a hospital without a CT scanner, and believing that decision rules are not oversimplified cookbook medicine or too rigid to apply. Eighty-five percent did not agree that all patients with minor head injuries should receive a CT head scan and only 3.5% stated they always refer such patients for CT scan. Similarly, 78.5% of the respondents did not agree that all trauma patients should receive cervical spine radiography and only 13.2% said they always refer such patients for cervical spine radiography. Ninety-seven and 98% stated they would be willing to consider using well-validated decision rules for CT scan of the head and cervical spine radiography, respectively. Fifty-two percent and 67% of the respondents required the proposed CT and C-spine to be 100% sensitive for identifying serious injuries

Shared decision making in mental health: the importance for current clinical practice.

PubMed

Alguera-Lara, Victoria; Dowsey, Michelle M; Ride, Jemimah; Kinder, Skye; Castle, David

2017-12-01

We reviewed the literature on shared decision making (regarding treatments in psychiatry), with a view to informing our understanding of the decision making process and the barriers that exist in clinical practice. Narrative review of published English-language articles. After culling, 18 relevant articles were included. Themes identified included models of psychiatric care, benefits for patients, and barriers. There is a paucity of published studies specifically related to antipsychotic medications. Shared decision making is a central part of the recovery paradigm and is of increasing importance in mental health service delivery. The field needs to better understand the basis on which decisions are reached regarding psychiatric treatments. Discrete choice experiments might be useful to inform the development of tools to assist shared decision making in psychiatry.

How can clinical practice guidelines be adapted to facilitate shared decision making? A qualitative key-informant study.

PubMed

van der Weijden, Trudy; Pieterse, Arwen H; Koelewijn-van Loon, Marije S; Knaapen, Loes; Légaré, France; Boivin, Antoine; Burgers, Jako S; Stiggelbout, Anne M; Faber, Marjan; Elwyn, Glyn

2013-10-01

To explore how clinical practice guidelines can be adapted to facilitate shared decision making. This was a qualitative key-informant study with group discussions and semi-structured interviews. First, 75 experts in guideline development or shared decision making participated in group discussions at two international conferences. Next, health professionals known as experts in depression or breast cancer, experts on clinical practice guidelines and/or shared decision making, and patient representatives were interviewed (N=20). Using illustrative treatment decisions on depression or breast cancer, we asked the interviewees to indicate as specifically as they could how guidelines could be used to facilitate shared decision making. Interviewees suggested some generic strategies, namely to include a separate chapter on the importance of shared decision making, to use language that encourages patient involvement, and to develop patient versions of guidelines. Recommendation-specific strategies, related to specific decision points in the guideline, were also suggested: These include structuring the presentation of healthcare options to increase professionals' option awareness; structuring the deliberation process between professionals and patients; and providing relevant patient support tools embedded at important decision points in the guideline. This study resulted in an overview of strategies to adapt clinical practice guidelines to facilitate shared decision making. Some strategies seemed more contentious than others. Future research should assess the feasibility and impact of these strategies to make clinical practice guidelines more conducive to facilitate shared decision making.

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.

Computerized clinical decision support for prescribing: provision does not guarantee uptake

PubMed Central

Moxey, Annette; Robertson, Jane; Newby, David; Hains, Isla; Williamson, Margaret; Pearson, Sallie-Anne

2010-01-01

There is wide variability in the use and adoption of recommendations generated by computerized clinical decision support systems (CDSSs) despite the benefits they may bring to clinical practice. We conducted a systematic review to explore the barriers to, and facilitators of, CDSS uptake by physicians to guide prescribing decisions. We identified 58 studies by searching electronic databases (1990–2007). Factors impacting on CDSS use included: the availability of hardware, technical support and training; integration of the system into workflows; and the relevance and timeliness of the clinical messages. Further, systems that were endorsed by colleagues, minimized perceived threats to professional autonomy, and did not compromise doctor-patient interactions were accepted by users. Despite advances in technology and CDSS sophistication, most factors were consistently reported over time and across ambulatory and institutional settings. Such factors must be addressed when deploying CDSSs so that improvements in uptake, practice and patient outcomes may be achieved. PMID:20064798

Evaluating the decision accuracy and speed of clinical data visualizations.

PubMed

Pieczkiewicz, David S; Finkelstein, Stanley M

2010-01-01

Clinicians face an increasing volume of biomedical data. Assessing the efficacy of systems that enable accurate and timely clinical decision making merits corresponding attention. This paper discusses the multiple-reader multiple-case (MRMC) experimental design and linear mixed models as means of assessing and comparing decision accuracy and latency (time) for decision tasks in which clinician readers must interpret visual displays of data. These tools can assess and compare decision accuracy and latency (time). These experimental and statistical techniques, used extensively in radiology imaging studies, offer a number of practical and analytic advantages over more traditional quantitative methods such as percent-correct measurements and ANOVAs, and are recommended for their statistical efficiency and generalizability. An example analysis using readily available, free, and commercial statistical software is provided as an appendix. While these techniques are not appropriate for all evaluation questions, they can provide a valuable addition to the evaluative toolkit of medical informatics research.

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…

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.

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.

Robot decisions: on the importance of virtuous judgment in clinical decision making.

PubMed

Gelhaus, Petra

2011-10-01

The aim of this article is to argue for the necessity of emotional professional virtues in the understanding of good clinical practice. This understanding is required for a proper balance of capacities in medical education and further education of physicians. For this reason an ideal physician, incarnating the required virtues, skills and knowledge is compared with a non-emotional robot that is bound to moral rules. This fictive confrontation is meant to clarify why certain demands on the personality of the physician are justified, in addition to a rule- and principle-based moral orientation and biomedical knowledge and skills. Philosophical analysis of thought experiments inspired by science fiction literature by Isaac Asimov. Although prima facie a rule-oriented robot seems more reliable and trustworthy, the complexity of clinical judgment is not met by an encompassing and never contradictory set of rules from which one could logically derive decisions. There are different ways how the robot could still work, but at the cost of the predictability of its behaviour and its moral orientation. In comparison, a virtuous human doctor who is also bound to these rules, although less strictly, will more reliably keep at moral objectives, be understandable, be more flexible in case the rules come to their limits, and will be more predictable in these critical situations. Apart from these advantages of the virtuous human doctor referring to her own person, the most problematic deficit of the robot is its lacking deeper understanding of the inner mental events of patients which makes good contact, good communication and good influence impossible. Although an infallibly rule-oriented robot seems more reliable at first view, in situations that require complex decisions like clinical practice the agency of a moral human person is more trustworthy. Furthermore, the understanding of the patient's emotions must remain insufficient for a non-emotional, non-human being. Because

The interaction of patient race, provider bias, and clinical ambiguity on pain management decisions

PubMed Central

Hirsh, Adam T.; Hollingshead, Nicole A.; Ashburn-Nardo, Leslie; Kroenke, Kurt

2015-01-01

Although racial disparities in pain care are widely reported, much remains to be known about the role of provider and contextual factors. We used computer-simulated patients to examine the influence of patient race, provider racial bias, and clinical ambiguity on pain decisions. One hundred twenty nine medical residents/fellows made assessment (pain intensity) and treatment (opioid and non-opioid analgesics) decisions for 12 virtual patients with acute pain. Race (Black/White) and clinical ambiguity (high/low) were manipulated across vignettes. Participants completed the Implicit Association Test and feeling thermometers, which assess implicit and explicit racial biases, respectively. Individual- and group-level analyses indicated that race and ambiguity had an interactive effect on providers’ decisions, such that decisions varied as a function of ambiguity for White but not Black patients. Individual differences across providers were observed for the effect of race and ambiguity on decisions; however providers’ implicit and explicit biases did not account for this variability. These data highlight the complexity of racial disparities and suggest that differences in care between White and Black patients are, in part, attributable to the nature (i.e., ambiguity) of the clinical scenario. The current study suggests that interventions to reduce disparities should differentially target patient, provider, and contextual factors. PMID:25828370

Recommendations for Selecting Drug-Drug Interactions for Clinical Decision Support

PubMed Central

Tilson, Hugh; Hines, Lisa E.; McEvoy, Gerald; Weinstein, David M.; Hansten, Philip D.; Matuszewski, Karl; le Comte, Marianne; Higby-Baker, Stefanie; Hanlon, Joseph T.; Pezzullo, Lynn; Vieson, Kathleen; Helwig, Amy L.; Huang, Shiew-Mei; Perre, Anthony; Bates, David W.; Poikonen, John; Wittie, Michael A.; Grizzle, Amy J.; Brown, Mary; Malone, Daniel C.

2016-01-01

Purpose To recommend principles for including drug-drug interactions (DDIs) in clinical decision support. Methods A conference series was conducted to improve clinical decision support (CDS) for DDIs. The Content Workgroup met monthly by webinar from January 2013 to February 2014, with two in-person meetings to reach consensus. The workgroup consisted of 20 experts in pharmacology, drug information, and CDS from academia, government agencies, health information (IT) vendors, and healthcare organizations. Workgroup members addressed four key questions: (1) What process should be used to develop and maintain a standard set of DDIs?; (2) What information should be included in a knowledgebase of standard DDIs?; (3) Can/should a list of contraindicated drug pairs be established?; and (4) How can DDI alerts be more intelligently filtered? Results To develop and maintain a standard set of DDIs for CDS in the United States, we recommend a transparent, systematic, and evidence-driven process with graded recommendations by a consensus panel of experts and oversight by a national organization. We outline key DDI information needed to help guide clinician decision-making. We recommend judicious classification of DDIs as contraindicated, as only a small set of drug combinations are truly contraindicated. Finally, we recommend more research to identify methods to safely reduce repetitive and less relevant alerts. Conclusion A systematic ongoing process is necessary to select DDIs for alerting clinicians. We anticipate that our recommendations can lead to consistent and clinically relevant content for interruptive DDIs, and thus reduce alert fatigue and improve patient safety. PMID:27045070

Incorporating uncertainty regarding applicability of evidence from meta-analyses into clinical decision making.

PubMed

Kriston, Levente; Meister, Ramona

2014-03-01

Judging applicability (relevance) of meta-analytical findings to particular clinical decision-making situations remains challenging. We aimed to describe an evidence synthesis method that accounts for possible uncertainty regarding applicability of the evidence. We conceptualized uncertainty regarding applicability of the meta-analytical estimates to a decision-making situation as the result of uncertainty regarding applicability of the findings of the trials that were included in the meta-analysis. This trial-level applicability uncertainty can be directly assessed by the decision maker and allows for the definition of trial inclusion probabilities, which can be used to perform a probabilistic meta-analysis with unequal probability resampling of trials (adaptive meta-analysis). A case study with several fictitious decision-making scenarios was performed to demonstrate the method in practice. We present options to elicit trial inclusion probabilities and perform the calculations. The result of an adaptive meta-analysis is a frequency distribution of the estimated parameters from traditional meta-analysis that provides individually tailored information according to the specific needs and uncertainty of the decision maker. The proposed method offers a direct and formalized combination of research evidence with individual clinical expertise and may aid clinicians in specific decision-making situations. Copyright © 2014 Elsevier Inc. All rights reserved.

Frontopolar cortex and decision-making efficiency: comparing brain activity of experts with different professional background during an exploration-exploitation task.

PubMed

Laureiro-Martínez, Daniella; Canessa, Nicola; Brusoni, Stefano; Zollo, Maurizio; Hare, Todd; Alemanno, Federica; Cappa, Stefano F

2013-01-01

An optimal balance between efficient exploitation of available resources and creative exploration of alternatives is critical for adaptation and survival. Previous studies associated these behavioral drives with, respectively, the dopaminergic mesocorticolimbic system and frontopolar-intraparietal networks. We study the activation of these systems in two age and gender-matched groups of experienced decision-makers differing in prior professional background, with the aim to understand the neural bases of individual differences in decision-making efficiency (performance divided by response time). We compare brain activity of entrepreneurs (who currently manage the organization they founded based on their venture idea) and managers (who are constantly involved in making strategic decisions but have no venture experience) engaged in a gambling-task assessing exploitative vs. explorative decision-making. Compared with managers, entrepreneurs showed higher decision-making efficiency, and a stronger activation in regions of frontopolar cortex (FPC) previously associated with explorative choice. Moreover, activity across a network of regions previously linked to explore/exploit tradeoffs explained individual differences in choice efficiency. These results suggest new avenues for the study of individual differences in the neural antecedents of efficient decision-making.

Frontopolar cortex and decision-making efficiency: comparing brain activity of experts with different professional background during an exploration-exploitation task

PubMed Central

Laureiro-Martínez, Daniella; Canessa, Nicola; Brusoni, Stefano; Zollo, Maurizio; Hare, Todd; Alemanno, Federica; Cappa, Stefano F.

2014-01-01

An optimal balance between efficient exploitation of available resources and creative exploration of alternatives is critical for adaptation and survival. Previous studies associated these behavioral drives with, respectively, the dopaminergic mesocorticolimbic system and frontopolar-intraparietal networks. We study the activation of these systems in two age and gender-matched groups of experienced decision-makers differing in prior professional background, with the aim to understand the neural bases of individual differences in decision-making efficiency (performance divided by response time). We compare brain activity of entrepreneurs (who currently manage the organization they founded based on their venture idea) and managers (who are constantly involved in making strategic decisions but have no venture experience) engaged in a gambling-task assessing exploitative vs. explorative decision-making. Compared with managers, entrepreneurs showed higher decision-making efficiency, and a stronger activation in regions of frontopolar cortex (FPC) previously associated with explorative choice. Moreover, activity across a network of regions previously linked to explore/exploit tradeoffs explained individual differences in choice efficiency. These results suggest new avenues for the study of individual differences in the neural antecedents of efficient decision-making. PMID:24478664

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.

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.

Feminist poststructuralism: a methodological paradigm for examining clinical decision-making.

PubMed

Arslanian-Engoren, Cynthia

2002-03-01

To present the philosophical framework of feminist poststructuralism, discuss its use as an innovative research approach and its implications for nursing knowledge development and practice. This perspective examines the construction of meaning, power relationships, and the importance of language as it affects contemporary healthcare decisions. It seeks to identify and expose biases that marginalize the healthcare needs of women and contribute to healthcare disparities for this population. Additionally, a feminist poststructuralist perspective seeks to develop new knowledge for understanding gender differences. A feminist poststructuralist perspective represents an alternative paradigm for studying the phenomenon of clinical decision-making. An empirical application example of a feminist poststructuralist perspective is provided. This exemplar investigated emergency department registered nurses' triage decisions for men and women with symptoms suggestive of coronary heart disease.

A Survey on Turkish nursing students' perception of clinical learning environment and its association with academic motivation and clinical decision making.

PubMed

Aktaş, Yeşim Yaman; Karabulut, Neziha

2016-01-01

Nursing education is a process that includes theoretical and practical learning and requires the acquisition of theoretical knowledge and skill. Nursing students need a good clinical practice environment in order to apply their knowledge and skills due to the fact that the clinical practice settings play an important role in the nursing profession. This study was carried out in an effort to explore nursing students' perception of the clinical learning environment and its association with academic motivation and clinical decision making. A descriptive survey design was used. This study was conducted in Giresun University in Turkey. Participants were second-, third- and fourth-year undergraduate students (n=222) in the Bachelor of Nursing Science Degree in the academic spring term of 2014-2015. The data was collected using the 'Clinical Learning Environment Scale', the 'Academic Motivation, and the 'The Clinical Decision Making in Nursing Scale'. Of the respondents in this study, 45% of the students were second class, 30.6% of the students were third class and 24.3% of the students were fourth class. There was a statistically significant positive correlation found between the clinical learning environment and the nursing students' academic motivation (r=0.182, p<.05). However, there was no correlation between the clinical learning environment and clinical decision making (r=0.082, p>.05). One of the prerequisites for the training of qualified students is to provide nursing students with a qualified clinical environment. It was found that nursing students' academic motivation increased as the quality of their clinical learning environment improved. Copyright © 2015 Elsevier Ltd. All rights reserved.

THE IMPACT OF RACISM ON CLINICIAN COGNITION, BEHAVIOR, AND CLINICAL DECISION MAKING

PubMed Central

van Ryn, Michelle; Burgess, Diana J.; Dovidio, John F.; Phelan, Sean M.; Saha, Somnath; Malat, Jennifer; Griffin, Joan M.; Fu, Steven S.; Perry, Sylvia

2014-01-01

Over the past two decades, thousands of studies have demonstrated that Blacks receive lower quality medical care than Whites, independent of disease status, setting, insurance, and other clinically relevant factors. Despite this, there has been little progress towards eradicating these inequities. Almost a decade ago we proposed a conceptual model identifying mechanisms through which clinicians’ behavior, cognition, and decision making might be influenced by implicit racial biases and explicit racial stereotypes, and thereby contribute to racial inequities in care. Empirical evidence has supported many of these hypothesized mechanisms, demonstrating that White medical care clinicians: (1) hold negative implicit racial biases and explicit racial stereotypes, (2) have implicit racial biases that persist independently of and in contrast to their explicit (conscious) racial attitudes, and (3) can be influenced by racial bias in their clinical decision making and behavior during encounters with Black patients. This paper applies evidence from several disciplines to further specify our original model and elaborate on the ways racism can interact with cognitive biases to affect clinicians’ behavior and decisions and in turn, patient behavior and decisions. We then highlight avenues for intervention and make specific recommendations to medical care and grant-making organizations. PMID:24761152

Decaying Relevance of Clinical Data Towards Future Decisions in Data-Driven Inpatient Clinical Order Sets

PubMed Central

Chen, Jonathan H; Alagappan, Muthuraman; Goldstein, Mary K; Asch, Steven M; Altman, Russ B

2017-01-01

Objective Determine how varying longitudinal historical training data can impact prediction of future clinical decisions. Estimate the “decay rate” of clinical data source relevance. Materials and Methods 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. Results 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. Discussion 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. Conclusions and Relevance Prioritizing small amounts of recent data is more effective than using larger amounts of older data towards future clinical predictions. PMID:28495350

Applying Probabilistic Decision Models to Clinical Trial Design

PubMed Central

Smith, Wade P; Phillips, Mark H

2018-01-01

Clinical trial design most often focuses on a single or several related outcomes with corresponding calculations of statistical power. We consider a clinical trial to be a decision problem, often with competing outcomes. Using a current controversy in the treatment of HPV-positive head and neck cancer, we apply several different probabilistic methods to help define the range of outcomes given different possible trial designs. Our model incorporates the uncertainties in the disease process and treatment response and the inhomogeneities in the patient population. Instead of expected utility, we have used a Markov model to calculate quality adjusted life expectancy as a maximization objective. Monte Carlo simulations over realistic ranges of parameters are used to explore different trial scenarios given the possible ranges of parameters. This modeling approach can be used to better inform the initial trial design so that it will more likely achieve clinical relevance. PMID:29888075

Physician Attitudes toward Adopting Genome-Guided Prescribing through Clinical Decision Support

PubMed Central

Overby, Casey Lynnette; Erwin, Angelika Ludtke; Abul-Husn, Noura S.; Ellis, Stephen B.; Scott, Stuart A.; Obeng, Aniwaa Owusu; Kannry, Joseph L.; Hripcsak, George; Bottinger, Erwin P.; Gottesman, Omri

2014-01-01

This study assessed physician attitudes toward adopting genome-guided prescribing through clinical decision support (CDS), prior to enlisting in the Clinical Implementation of Personalized Medicine through Electronic Health Records and Genomics pilot pharmacogenomics project (CLIPMERGE PGx). We developed a survey instrument that includes the Evidence Based Practice Attitude Scale, adapted to measure attitudes toward adopting genome-informed interventions (EBPAS-GII). The survey also includes items to measure physicians’ characteristics (awareness, experience, and perceived usefulness), attitudes about personal genome testing (PGT) services, and comfort using technology. We surveyed 101 General Internal Medicine physicians from the Icahn School of Medicine at Mount Sinai (ISMMS). The majority were residency program trainees (~88%). Prior to enlisting into CLIPMERGE PGx, most physicians were aware of and had used decision support aids. Few physicians, however, were aware of and had used genome-guided prescribing. The majority of physicians viewed decision support aids and genotype data as being useful for making prescribing decisions. Most physicians had not heard of, but were willing to use, PGT services and felt comfortable interpreting PGT results. Most physicians were comfortable with technology. Physicians who perceived genotype data to be useful in making prescribing decisions, had more positive attitudes toward adopting genome-guided prescribing through CDS. Our findings suggest that internal medicine physicians have a deficit in their familiarity and comfort interpreting and using genomic information. This has reinforced the importance of gathering feedback and guidance from our enrolled physicians when designing genome-guided CDS and the importance of prioritizing genomic medicine education at our institutions. PMID:25562141

Ethnic bias and clinical decision-making among New Zealand medical students: an observational study.

PubMed

Harris, Ricci; Cormack, Donna; Stanley, James; Curtis, Elana; Jones, Rhys; Lacey, Cameron

2018-01-23

Health professional racial/ethnic bias may impact on clinical decision-making and contribute to subsequent ethnic health inequities. However, limited research has been undertaken among medical students. This paper presents findings from the Bias and Decision-Making in Medicine (BDMM) study, which sought to examine ethnic bias (Māori (indigenous peoples) compared with New Zealand European) among medical students and associations with clinical decision-making. All final year New Zealand (NZ) medical students in 2014 and 2015 (n = 888) were invited to participate in a cross-sectional online study. Key components included: two chronic disease vignettes (cardiovascular disease (CVD) and depression) with randomized patient ethnicity (Māori or NZ European) and questions on patient management; implicit bias measures (an ethnicity preference Implicit Association Test (IAT) and an ethnicity and compliant patient IAT); and, explicit ethnic bias questions. Associations between ethnic bias and clinical decision-making responses to vignettes were tested using linear regression. Three hundred and two students participated (34% response rate). Implicit and explicit ethnic bias favoring NZ Europeans was apparent among medical students. In the CVD vignette, no significant differences in clinical decision-making by patient ethnicity were observed. There were also no differential associations by patient ethnicity between any measures of ethnic bias (implicit or explicit) and patient management responses in the CVD vignette. In the depression vignette, some differences in the ranking of recommended treatment options were observed by patient ethnicity and explicit preference for NZ Europeans was associated with increased reporting that NZ European patients would benefit from treatment but not Māori (slope difference 0.34, 95% CI 0.08, 0.60; p = 0.011), although this was the only significant finding in these analyses. NZ medical students demonstrated ethnic bias, although

Which breast cancer decisions remain non-compliant with guidelines despite the use of computerised decision support?

PubMed Central

Séroussi, B; Laouénan, C; Gligorov, J; Uzan, S; Mentré, F; Bouaud, J

2013-01-01

Background: Despite multidisciplinary tumour boards (MTBs), non-compliance with clinical practice guidelines is still observed for breast cancer patients. Computerised clinical decision support systems (CDSSs) may improve the implementation of guidelines, but cases of non-compliance persist. Methods: OncoDoc2, a guideline-based decision support system, has been routinely used to remind MTB physicians of patient-specific recommended care plans. Non-compliant MTB decisions were analysed using a multivariate adjusted logistic regression model. Results: Between 2007 and 2009, 1624 decisions for invasive breast cancers with a global non-compliance rate of 8.3% were analysed. Patient factors associated with non-compliance were age>80 years (odds ratio (OR): 7.7; 95% confidence interval (CI): 3.7–15.7) in pre-surgical decisions; microinvasive tumour (OR: 5.2; 95% CI: 1.5–17.5), surgical discovery of microinvasion in addition to a unique invasive tumour (OR: 4.2; 95% CI: 1.4–12.5), and prior neoadjuvant treatment (OR: 4.2; 95% CI: 1.1–15.1) in decisions with recommendation of re-excision; age<35 years (OR: 4.7; 95% CI: 1.9–11.4), positive hormonal receptors with human epidermal growth factor receptor 2 overexpression (OR: 15.7; 95% CI: 3.1–78.7), and the absence of prior axillary surgery (OR: 17.2; 95% CI: 5.1–58.1) in adjuvant decisions. Conclusion: Residual non-compliance despite the use of OncoDoc2 illustrates the need to question the clinical profiles where evidence is missing. These findings challenge the weaknesses of guideline content rather than the use of CDSSs. PMID:23942076

A point-of-care chemistry test for reduction of turnaround and clinical decision time.

PubMed

Lee, Eui Jung; Shin, Sang Do; Song, Kyoung Jun; Kim, Seong Chun; Cho, Jin Seong; Lee, Seung Chul; Park, Ju Ok; Cha, Won Chul

2011-06-01

Our study compared clinical decision time between patients managed with a point-of-care chemistry test (POCT) and patients managed with the traditional central laboratory test (CLT). This was a randomized controlled multicenter trial in the emergency departments (EDs) of 5 academic teaching hospitals. We randomly assigned patients to POCT or CLT stratified by the Emergency Severity Index. A POCT chemistry analyzer (Piccolo; Abaxis, Inc, Union City, Calif), which is able to test liver panel, renal panel, pancreas enzymes, lipid panel, electrolytes, and blood gases, was set up in each ED. Primary and secondary end point was turnaround time and door-to-clinical-decision time. The total 2323 patients were randomly assigned to the POCT group (n = 1167) or to the CLT group (n = 1156). All of the basic characteristics were similar in the 2 groups. The turnaround time (median, interquartile range [IQR]) of the POCT group was shorter than that of the CLT group (14, 12-19 versus 55, 45-69 minutes; P < .0001). The median (IQR) door-to-clinical-decision time was also shorter in the POCT compared with the CLT group (46, 33-61 versus 86, 68-107 minutes; P < .0001). The proportion of patients who had new decisions within 60 minutes was 72.8% for the POCT group and 12.5% for the CLT group (P < .0001). A POCT chemistry analyzer in the ED shortens the test turnaround and ED clinical decision times compared with CLT. Copyright © 2011 Elsevier Inc. All rights reserved.

Clinical decision-making to facilitate appropriate patient management in chiropractic practice: 'the 3-questions model'.

PubMed

Amorin-Woods, Lyndon G; Parkin-Smith, Gregory F

2012-03-14

A definitive diagnosis in chiropractic clinical practice is frequently elusive, yet decisions around management are still necessary. Often, a clinical impression is made after the exclusion of serious illness or injury, and care provided within the context of diagnostic uncertainty. Rather than focussing on labelling the condition, the clinician may choose to develop a defendable management plan since the response to treatment often clarifies the diagnosis. This paper explores the concept and elements of defensive problem-solving practice, with a view to developing a model of agile, pragmatic decision-making amenable to real-world application. A theoretical framework that reflects the elements of this approach will be offered in order to validate the potential of a so called '3-Questions Model'; Clinical decision-making is considered to be a key characteristic of any modern healthcare practitioner. It is, thus, prudent for chiropractors to re-visit the concept of defensible practice with a view to facilitate capable clinical decision-making and competent patient examination skills. In turn, the perception of competence and trustworthiness of chiropractors within the wider healthcare community helps integration of chiropractic services into broader healthcare settings.

Exploring Patient Values in Medical Decision Making: A Qualitative Study

PubMed Central

Lee, Yew Kong; Low, Wah Yun; Ng, Chirk Jenn

2013-01-01

Background Patient decisions are influenced by their personal values. However, there is a lack of clarity and attention on the concept of patient values in the clinical context despite clear emphasis on patient values in evidence-based medicine and shared decision making. The aim of the study was to explore the concept of patient values in the context of making decisions about insulin initiation among people with type 2 diabetes. Methods and Findings We conducted individual in-depth interviews with people with type 2 diabetes who were making decisions about insulin treatment. Participants were selected purposively to achieve maximum variation. A semi-structured topic guide was used to guide the interviews which were audio-recorded and analysed using a thematic approach. We interviewed 21 participants between January 2011 and March 2012. The age range of participants was 28–67 years old. Our sample comprised 9 women and 12 men. Three main themes, ‘treatment-specific values’, ‘life goals and philosophies’, and ‘personal and social background’, emerged from the analysis. The patients reported a variety of insulin-specific values, which were negative and/or positive beliefs about insulin. They framed insulin according to their priorities and philosophies in life. Patients’ decisions were influenced by sociocultural (e.g. religious background) and personal backgrounds (e.g. family situations). Conclusions This study highlighted the need for expanding the current concept of patient values in medical decision making. Clinicians should address more than just values related to treatment options. Patient values should include patients’ priorities, life philosophy and their background. Current decision support tools, such as patient decision aids, should consider these new dimensions when clarifying patient values. PMID:24282518

Exploring patient values in medical decision making: a qualitative study.

PubMed

Lee, Yew Kong; Low, Wah Yun; Ng, Chirk Jenn

2013-01-01

Patient decisions are influenced by their personal values. However, there is a lack of clarity and attention on the concept of patient values in the clinical context despite clear emphasis on patient values in evidence-based medicine and shared decision making. The aim of the study was to explore the concept of patient values in the context of making decisions about insulin initiation among people with type 2 diabetes. We conducted individual in-depth interviews with people with type 2 diabetes who were making decisions about insulin treatment. Participants were selected purposively to achieve maximum variation. A semi-structured topic guide was used to guide the interviews which were audio-recorded and analysed using a thematic approach. We interviewed 21 participants between January 2011 and March 2012. The age range of participants was 28-67 years old. Our sample comprised 9 women and 12 men. Three main themes, 'treatment-specific values', 'life goals and philosophies', and 'personal and social background', emerged from the analysis. The patients reported a variety of insulin-specific values, which were negative and/or positive beliefs about insulin. They framed insulin according to their priorities and philosophies in life. Patients' decisions were influenced by sociocultural (e.g. religious background) and personal backgrounds (e.g. family situations). This study highlighted the need for expanding the current concept of patient values in medical decision making. Clinicians should address more than just values related to treatment options. Patient values should include patients' priorities, life philosophy and their background. Current decision support tools, such as patient decision aids, should consider these new dimensions when clarifying patient values.

Use of antipsychotic blood levels in clinician decision making: A cross-over study using clinical vignettes of patients with schizophrenia.

PubMed

Savitz, Adam; Melkote, Rama; Riley, Ralph; Pobre, Maria A; McQuarrie, Kelly; Williamson, David; Banderas, Benjamin

2018-05-19

The cause of treatment failure of antipsychotic medications is often difficult to determine in patients with schizophrenia. Evaluation of antipsychotic blood levels (ABLs) may aid clinicians in determining the cause of antipsychotic failure. The Clinical Assessment of the Schizophrenia Patient (CASP) was developed to evaluate clinical decision making during outpatient visits. The CASP assesses changes in medications, psychosocial treatments, and acute interventions along with factors influencing clinical decision making. Nine vignettes representative of clinical situations in patients with schizophrenia were created in two versions (one with ABLs, one without ABLs). The CASP was used to evaluate clinical decisions using the vignettes. Thirty-four clinicians participated in the study. In 8 out of 9 vignettes, most clinicians (at least 89.7%) made a different clinical decision with ABLs compared to without ABLs. In assessing the usefulness of ABLs, a majority (60.7%-85.7%, depending on the vignette) of clinicians responded that ABLs changed their clinical decision for 8 vignettes. Most clinicians (79%-93%) responded that they were more confident in their decisions with ABL information. This study demonstrated that ABLs have the potential to influence clinical decision making in the treatment of patients with schizophrenia. Copyright © 2018. Published by Elsevier B.V.

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.

What is a “good” treatment decision?: Decisional control, knowledge, treatment decision-making, and quality of life in men with clinically localized prostate cancer

PubMed Central

Orom, Heather; Biddle, Caitlin; Underwood, Willie; Nelson, Christian J.; Homish, D. Lynn

2016-01-01

Objective We explored whether active patient involvement in decision making and greater patient knowledge are associated with better treatment decision making experiences and better quality of life (QOL) among men with clinically localized prostate cancer. Localized prostate cancer treatment decision-making is an advantageous model for studying patient treatment decision-making dynamics as there are multiple treatment options and a lack of empirical evidence to recommend one over the other; consequently, it is recommended that patients be fully involved in making the decision. Methods Men with newly diagnosed clinically localized prostate cancer (N=1529) completed measures of decisional control, prostate cancer knowledge, and their decision-making experience (decisional conflict, and decision-making satisfaction and difficulty) shortly after they made their treatment decision. Prostate cancer-specific QOL was assessed 6-months after treatment. Results More active involvement in decision making and greater knowledge were associated with lower decisional conflict and higher decision-making satisfaction, but greater decision-making difficulty. An interaction between decisional control and knowledge revealed that greater knowledge was only associated with greater difficulty for men actively involved in making the decision (67% of sample). Greater knowledge, but not decisional control predicted better QOL 6-months post-treatment. Conclusion Although men who are actively involved in decision making and more knowledgeable may make more informed decisions, they could benefit from decisional support (e.g., decision-making aids, emotional support from providers, strategies for reducing emotional distress) to make the process easier. Men who were more knowledgeable about prostate cancer and treatment side effects at the time they made their treatment decision may have appraised their QOL as higher because they had realistic expectations about side effects. PMID:26957566

Patient involvement in decision-making: a cross-sectional study in a Malaysian primary care clinic

PubMed Central

Ambigapathy, Ranjini; Ng, Chirk Jenn

2016-01-01

Objective Shared decision-making has been advocated as a useful model for patient management. In developing Asian countries such as Malaysia, there is a common belief that patients prefer a passive role in clinical consultation. As such, the objective of this study was to determine Malaysian patients’ role preference in decision-making and the associated factors. Design A cross-sectional study. Setting Study was conducted at an urban primary care clinic in Malaysia in 2012. Participants Patients aged >21 years were chosen using systematic random sampling. Methods Consenting patients answered a self-administered questionnaire, which included demographic data and their preferred and actual role before and after consultation. Doctors were asked to determine patients’ role preference. The Control Preference Scale was used to assess patients’ role preference. Primary outcome Prevalence of patients’ preferred role in decision-making. Secondary outcomes (1) Actual role played by the patient in decision-making. (2) Sociodemographic factors associated with patients’ preferred role in decision-making. (3) Doctors’ perception of patients’ involvement in decision-making. Results The response rate was 95.1% (470/494). Shared decision-making was preferred by 51.9% of patients, followed by passive (26.3%) and active (21.8%) roles in decision-making. Higher household income was significantly associated with autonomous role preference (p=0.018). Doctors’ perception did not concur with patients’ preferred role. Among patients whom doctors perceived to prefer a passive role, 73.5% preferred an autonomous role (p=0.900, κ=0.006). Conclusions The majority of patients attending the primary care clinic preferred and played an autonomous role in decision-making. Doctors underestimated patients’ preference to play an autonomous role. PMID:26729393

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 two-stage clinical decision support system for early recognition and stratification of patients with sepsis: an observational cohort study.

PubMed

Amland, Robert C; Lyons, Jason J; Greene, Tracy L; Haley, James M

2015-10-01

To examine the diagnostic accuracy of a two-stage clinical decision support system for early recognition and stratification of patients with sepsis. Observational cohort study employing a two-stage sepsis clinical decision support to recognise and stratify patients with sepsis. The stage one component was comprised of a cloud-based clinical decision support with 24/7 surveillance to detect patients at risk of sepsis. The cloud-based clinical decision support delivered notifications to the patients' designated nurse, who then electronically contacted a provider. The second stage component comprised a sepsis screening and stratification form integrated into the patient electronic health record, essentially an evidence-based decision aid, used by providers to assess patients at bedside. Urban, 284 acute bed community hospital in the USA; 16,000 hospitalisations annually. Data on 2620 adult patients were collected retrospectively in 2014 after the clinical decision support was implemented. 'Suspected infection' was the established gold standard to assess clinical decision support clinimetric performance. A sepsis alert activated on 417 (16%) of 2620 adult patients hospitalised. Applying 'suspected infection' as standard, the patient population characteristics showed 72% sensitivity and 73% positive predictive value. A postalert screening conducted by providers at bedside of 417 patients achieved 81% sensitivity and 94% positive predictive value. Providers documented against 89% patients with an alert activated by clinical decision support and completed 75% of bedside screening and stratification of patients with sepsis within one hour from notification. A clinical decision support binary alarm system with cross-checking functionality improves early recognition and facilitates stratification of patients with sepsis.

[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.

The pitfalls of premature closure: clinical decision-making in a case of aortic dissection

PubMed Central

Kumar, Bharat; Kanna, Balavenkatesh; Kumar, Suresh

2011-01-01

Premature closure is a type of cognitive error in which the physician fails to consider reasonable alternatives after an initial diagnosis is made. It is a common cause of delayed diagnosis and misdiagnosis borne out of a faulty clinical decision-making process. The authors present a case of aortic dissection in which premature closure was avoided by the aggressive pursuit of the appropriate differential diagnosis, and discuss the importance of disciplined clinical decision-making in the setting of chest pain. PMID:22679162

Are clinical decisions in endodontics influenced by the patient's fee-paying status?

PubMed

Walker, I; Gilbert, D; Asimakopoulou, K

2015-12-01

We explored whether the fee status of a UK patient influences clinical decision-making in endodontics. In a randomised-controlled vignette study describing either an 'NHS-funded', 'Privately-funded' or undisclosed fee-status patient, we examined the importance vocational trainer dentists placed on a series of factors normally considered when deciding whether to offer patients endodontic treatment as opposed to extracting the tooth. N = 119 experienced (M years post qualification = 20.01) dentists participated. Having read a vignette describing a hypothetical patient who could potentially be treated either endodontically or through an extraction, dentists rated a series of factors they would normally consider (for example, poor oral hygiene, the rest of their mouth is unfilled and caries-free), before recommending either endodontic treatment or an extraction. The patient's funding status had no influence on these dentists' clinical decision-making when considering endodontic treatment as an option (p >0.05) with the exception of a single item relating to infrequent attendance where the NHS patient was more likely than the 'undisclosed-fee' patient, to be offered extractions (F (2, 116) 3.43, p <0.04). We have found no strong evidence to suggest that the fee-status of a patient influences clinical decision-making in endodontic treatment by experienced dentists.

Clinical Decision Making and Mental Health Service Use Among Persons With Severe Mental Illness Across Europe.

PubMed

Cosh, Suzanne; Zenter, Nadja; Ay, Esra-Sultan; Loos, Sabine; Slade, Mike; De Rosa, Corrado; Luciano, Mario; Berecz, Roland; Glaub, Theodora; Munk-Jørgensen, Povl; Krogsgaard Bording, Malene; Rössler, Wulf; Kawohl, Wolfram; Puschner, Bernd

2017-09-01

The study explored relationships between preferences for and experiences of clinical decision making (CDM) with service use among persons with severe mental illness. Data from a prospective observational study in six European countries were examined. Associations of baseline staff-rated (N=213) and patient-rated (N=588) preferred and experienced decision making with service use were examined at baseline by using binomial regressions and at 12-month follow-up by using multilevel models. A preference by patients and staff for active patient involvement in decision making, rather than shared or passive decision making, was associated with longer hospital admissions and higher costs at baseline and with increases in admissions over 12 months (p=.043). Low patient-rated satisfaction with an experienced clinical decision was also related to increased costs over the study period (p=.005). A preference for shared decision making may reduce health care costs by reducing inpatient admissions. Patient satisfaction with decisions was a predictor of costs, and clinicians should maximize patient satisfaction with CDM.

GELLO: an object-oriented query and expression language for clinical decision support.

PubMed

Sordo, Margarita; Ogunyemi, Omolola; Boxwala, Aziz A; Greenes, Robert A

2003-01-01

GELLO is a purpose-specific, object-oriented (OO) query and expression language. GELLO is the result of a concerted effort of the Decision Systems Group (DSG) working with the HL7 Clinical Decision Support Technical Committee (CDSTC) to provide the HL7 community with a common format for data encoding and manipulation. GELLO will soon be submitted for ballot to the HL7 CDSTC for consideration as a standard.

A Clinical Decision Support System for Breast Cancer Patients

NASA Astrophysics Data System (ADS)

Fernandes, Ana S.; Alves, Pedro; Jarman, Ian H.; Etchells, Terence A.; Fonseca, José M.; Lisboa, Paulo J. G.

This paper proposes a Web clinical decision support system for clinical oncologists and for breast cancer patients making prognostic assessments, using the particular characteristics of the individual patient. This system comprises three different prognostic modelling methodologies: the clinically widely used Nottingham prognostic index (NPI); the Cox regression modelling and a partial logistic artificial neural network with automatic relevance determination (PLANN-ARD). All three models yield a different prognostic index that can be analysed together in order to obtain a more accurate prognostic assessment of the patient. Missing data is incorporated in the mentioned models, a common issue in medical data that was overcome using multiple imputation techniques. Risk group assignments are also provided through a methodology based on regression trees, where Boolean rules can be obtained expressed with patient characteristics.

Developing an Interactive Data Visualization Tool to Assess the Impact of Decision Support on Clinical Operations.

PubMed

Huber, Timothy C; Krishnaraj, Arun; Monaghan, Dayna; Gaskin, Cree M

2018-05-18

Due to mandates from recent legislation, clinical decision support (CDS) software is being adopted by radiology practices across the country. This software provides imaging study decision support for referring providers at the point of order entry. CDS systems produce a large volume of data, providing opportunities for research and quality improvement. In order to better visualize and analyze trends in this data, an interactive data visualization dashboard was created using a commercially available data visualization platform. Following the integration of a commercially available clinical decision support product into the electronic health record, a dashboard was created using a commercially available data visualization platform (Tableau, Seattle, WA). Data generated by the CDS were exported from the data warehouse, where they were stored, into the platform. This allowed for real-time visualization of the data generated by the decision support software. The creation of the dashboard allowed the output from the CDS platform to be more easily analyzed and facilitated hypothesis generation. Integrating data visualization tools into clinical decision support tools allows for easier data analysis and can streamline research and quality improvement efforts.

Using Clinical Decision Support Software in Health Insurance Company

NASA Astrophysics Data System (ADS)

Konovalov, R.; Kumlander, Deniss

This paper proposes the idea to use Clinical Decision Support software in Health Insurance Company as a tool to reduce the expenses related to Medication Errors. As a prove that this class of software will help insurance companies reducing the expenses, the research was conducted in eight hospitals in United Arab Emirates to analyze the amount of preventable common Medication Errors in drug prescription.

Medication-related clinical decision support alert overrides in inpatients.

PubMed

Nanji, Karen C; Seger, Diane L; Slight, Sarah P; Amato, Mary G; Beeler, Patrick E; Her, Qoua L; Dalleur, Olivia; Eguale, Tewodros; Wong, Adrian; Silvers, Elizabeth R; Swerdloff, Michael; Hussain, Salman T; Maniam, Nivethietha; Fiskio, Julie M; Dykes, Patricia C; Bates, David W

2018-05-01

To define the types and numbers of inpatient clinical decision support alerts, measure the frequency with which they are overridden, and describe providers' reasons for overriding them and the appropriateness of those reasons. We conducted a cross-sectional study of medication-related clinical decision support alerts over a 3-year period at a 793-bed tertiary-care teaching institution. We measured the rate of alert overrides, the rate of overrides by alert type, the reasons cited for overrides, and the appropriateness of those reasons. Overall, 73.3% of patient allergy, drug-drug interaction, and duplicate drug alerts were overridden, though the rate of overrides varied by alert type (P < .0001). About 60% of overrides were appropriate, and that proportion also varied by alert type (P < .0001). Few overrides of renal- (2.2%) or age-based (26.4%) medication substitutions were appropriate, while most duplicate drug (98%), patient allergy (96.5%), and formulary substitution (82.5%) alerts were appropriate. Despite warnings of potential significant harm, certain categories of alert overrides were inappropriate >75% of the time. The vast majority of duplicate drug, patient allergy, and formulary substitution alerts were appropriate, suggesting that these categories of alerts might be good targets for refinement to reduce alert fatigue. Almost three-quarters of alerts were overridden, and 40% of the overrides were not appropriate. Future research should optimize alert types and frequencies to increase their clinical relevance, reducing alert fatigue so that important alerts are not inappropriately overridden.

Clinical decision making in cancer care: a review of current and future roles of patient age.

PubMed

Tranvåg, Eirik Joakim; Norheim, Ole Frithjof; Ottersen, Trygve

2018-05-09

Patient age is among the most controversial patient characteristics in clinical decision making. In personalized cancer medicine it is important to understand how individual characteristics do affect practice and how to appropriately incorporate such factors into decision making. Some argue that using age in decision making is unethical, and how patient age should guide cancer care is unsettled. This article provides an overview of the use of age in clinical decision making and discusses how age can be relevant in the context of personalized medicine. We conducted a scoping review, searching Pubmed for English references published between 1985 and May 2017. References concerning cancer, with patients above the age of 18 and that discussed age in relation to diagnostic or treatment decisions were included. References that were non-medical or concerning patients below the age of 18, and references that were case reports, ongoing studies or opinion pieces were excluded. Additional references were collected through snowballing and from selected reports, guidelines and articles. Three hundred and forty-seven relevant references were identified. Patient age can have many and diverse roles in clinical decision making: Contextual roles linked to access (age influences how fast patients are referred to specialized care) and incidence (association between increasing age and increasing incidence rates for cancer); patient-relevant roles linked to physiology (age-related changes in drug metabolism) and comorbidity (association between increasing age and increasing number of comorbidities); and roles related to interventions, such as treatment (older patients receive substandard care) and outcome (survival varies by age). Patient age is integrated into cancer care decision making in a range of ways that makes it difficult to claim age-neutrality. Acknowledging this and being more transparent about the use of age in decision making are likely to promote better clinical decisions

Public Response to Cost-Quality Tradeoffs in Clinical Decisions

PubMed Central

Beach, Mary Catherine; Asch, David A.; Jepson, Christopher; Hershey, John C.; Mohr, Tara; McMorrow, Stacey; Ubel, Peter A.

2011-01-01

Purpose To explore public attitudes toward the incorporation of cost-effectiveness analysis into clinical decisions. Methods The authors presented 781 jurors with a survey describing 1 of 6 clinical encounters in which a physician has to choose between cancer screening tests. They provided cost-effectiveness data for all tests, and in each scenario, the most effective test was more expensive. They instructed respondents to imagine that he or she was the physician in the scenario and asked them to choose which test to recommend and then explain their choice in an open-ended manner. The authors then qualitatively analyzed the responses by identifying themes and developed a coding scheme. Two authors separately coded the statements with high overall agreement (kappa = 0.76). Categories were not mutually exclusive. Results Overall, 410 respondents (55%) chose the most expensive option, and 332 respondents (45%) choose a less expensive option. Explanatory comments were given by 82% respondents. Respondents who chose the most expensive test focused on the increased benefit (without directly acknowledging the additional cost) (39%), a general belief that life is more important than money (22%), the significance of cancer risk for the patient in the scenario (20%), the belief that the benefit of the test was worth the additional cost (8%), and personal anecdotes/preferences (6%). Of the respondents who chose the less expensive test, 40% indicated that they did not believe that the patient in the scenario was at significant risk for cancer, 13% indicated that they thought the less expensive test was adequate or not meaningfully different from the more expensive test, 12% thought the cost of the test was not worth the additional benefit, 9% indicated that the test was too expensive (without mention of additional benefit), and 7% responded that resources were limited. Conclusions Public response to cost-quality tradeoffs is mixed. Although some respondents justified their

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.

The experience of physicians in pharmacogenomic clinical decision support within eight German university hospitals.

PubMed

Hinderer, Marc; Boeker, Martin; Wagner, Sebastian A; Binder, Harald; Ückert, Frank; Newe, Stephanie; Hülsemann, Jan L; Neumaier, Michael; Schade-Brittinger, Carmen; Acker, Till; Prokosch, Hans-Ulrich; Sedlmayr, Brita

2017-06-01

The aim of this study was to assess the physicians' attitude, their knowledge and their experience in pharmacogenomic clinical decision support in German hospitals. We conducted an online survey to address physicians of 13 different medical specialties across eight German university hospitals. In total, 564 returned questionnaires were analyzed. The remaining knowledge gap, the uncertainty of test reimbursement and the physicians' lack of awareness of existing pharmacogenomic clinical decision support systems (CDSS) are the major barriers for implementing pharmacogenomic CDSS into German hospitals. Furthermore, pharmacogenomic CDSS are most effective in the form of real-time decision support for internists. Physicians in German hospitals require additional education of both genetics and pharmacogenomics. They need to be provided with access to relevant pharmacogenomic CDSS.

Clinical Decision Support Alert Appropriateness: A Review and Proposal for Improvement

PubMed Central

McCoy, Allison B.; Thomas, Eric J.; Krousel-Wood, Marie; Sittig, Dean F.

2014-01-01

Background Many healthcare providers are adopting clinical decision support (CDS) systems to improve patient safety and meet meaningful use requirements. Computerized alerts that prompt clinicians about drug-allergy, drug-drug, and drug-disease warnings or provide dosing guidance are most commonly implemented. Alert overrides, which occur when clinicians do not follow the guidance presented by the alert, can hinder improved patient outcomes. Methods We present a review of CDS alerts and describe a proposal to develop novel methods for evaluating and improving CDS alerts that builds upon traditional informatics approaches. Our proposal incorporates previously described models for predicting alert overrides that utilize retrospective chart review to determine which alerts are clinically relevant and which overrides are justifiable. Results Despite increasing implementations of CDS alerts, detailed evaluations rarely occur because of the extensive labor involved in manual chart reviews to determine alert and response appropriateness. Further, most studies have solely evaluated alert overrides that are appropriate or justifiable. Our proposal expands the use of web-based monitoring tools with an interactive dashboard for evaluating CDS alert and response appropriateness that incorporates the predictive models. The dashboard provides 2 views, an alert detail view and a patient detail view, to provide a full history of alerts and help put the patient's events in context. Conclusion The proposed research introduces several innovations to address the challenges and gaps in alert evaluations. This research can transform alert evaluation processes across healthcare settings, leading to improved CDS, reduced alert fatigue, and increased patient safety. PMID:24940129

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.

Clinical care paths: a role for finance in clinical decision-making.

PubMed

Abrams, Michael N; Cummings, Simone; Hage, Dana

2012-12-01

Care paths map the critical actions and decision points across a patient's course of medical treatment; their purpose is to guide physicians in the delivery of high-quality care while reducing care costs by avoiding services that do not contribute meaningfully to positive outcomes. Each care path development initiative should be led by a respected physician champion, whose specialty is in the area of the care episode being mapped, with the support of a clinician project manager. Once the care path has been developed and implemented, the finance leader's role begins in earnest with the tracking of financial and clinical data against care paths.

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

Improving Breast Cancer Surgical Treatment Decision Making: The iCanDecide Randomized Clinical Trial.

PubMed

Hawley, Sarah T; Li, Yun; An, Lawrence C; Resnicow, Kenneth; Janz, Nancy K; Sabel, Michael S; Ward, Kevin C; Fagerlin, Angela; Morrow, Monica; Jagsi, Reshma; Hofer, Timothy P; Katz, Steven J

2018-03-01

Purpose This study was conducted to determine the effect of iCanDecide, an interactive and tailored breast cancer treatment decision tool, on the rate of high-quality patient decisions-both informed and values concordant-regarding locoregional breast cancer treatment and on patient appraisal of decision making. Methods We conducted a randomized clinical trial of newly diagnosed patients with early-stage breast cancer making locoregional treatment decisions. From 22 surgical practices, 537 patients were recruited and randomly assigned online to the iCanDecide interactive and tailored Web site (intervention) or the iCanDecide static Web site (control). Participants completed a baseline survey and were mailed a follow-up survey 4 to 5 weeks after enrollment to assess the primary outcome of a high-quality decision, which consisted of two components, high knowledge and values-concordant treatment, and secondary outcomes (decision preparation, deliberation, and subjective decision quality). Results Patients in the intervention arm had higher odds of making a high-quality decision than did those in the control arm (odds ratio, 2.00; 95% CI, 1.37 to 2.92; P = .0004), which was driven primarily by differences in the rates of high knowledge between groups. The majority of patients in both arms made values-concordant treatment decisions (78.6% in the intervention arm and 81.4% in the control arm). More patients in the intervention arm had high decision preparation (estimate, 0.18; 95% CI, 0.02 to 0.34; P = .027), but there were no significant differences in the other decision appraisal outcomes. The effect of the intervention was similar for women who were leaning strongly toward a treatment option at enrollment compared with those who were not. Conclusion The tailored and interactive iCanDecide Web site, which focused on knowledge building and values clarification, positively affected high-quality decisions largely by improving knowledge compared with static online

Impact of Dysphagia Severity on Clinical Decision Making via Telerehabilitation

PubMed Central

Burns, Clare L.; Theodoros, Deborah G.; Russell, Trevor G.

2014-01-01

Abstract Objective: Recent research supports the proposal that valid and reliable clinical swallow examinations (CSEs) can be conducted via telerehabilitation. However, no studies have explored whether dysphagia severity has an impact on the success of the session or its outcomes. The current study examined how dysphagia severity impacted on either (a) clinical decision making for safety of oral intake or (b) clinician perceptions of CSEs conducted via telerehabilitation. Subjects and Methods: One hundred patients (25 nondysphagics and 25 mild, 25 moderate, and 25 severe dysphagics) were assessed using a telehealth system and methodology reported in prior research. For each assessment, the online and face-to-face (FTF) clinicians simultaneously completed a structured CSE. On session completion, the online clinician indicated level of agreement with two statements regarding the level of rapport and ability to competently assess the patient. Results: In each of the four groups, acceptable levels of agreement were observed between raters for the three primary outcomes (decisions regarding oral/nonoral intake and safe food and fluids) as well as over 90% of the CSE items. Clinicians agreed they could develop good rapport with the majority of patients in all groups. However, for a small but significant (p<0.5) proportion of patents in the severe dysphagic group, clinicians disagreed they were able to satisfactorily and competently assess to the best of their abilities using the telerehabilitation system. Conclusions: Clinical decisions made during and as an outcome of the total CSE were found to be comparable to those made in the FTF environment regardless of dysphagia severity. Clinicians noted some difficulty assessing patients with greater complexity, which occurred in greater numbers in the group with severe dysphagia. PMID:24443927

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…

The professional medical ethics model of decision making under conditions of clinical uncertainty.

PubMed

McCullough, Laurence B

2013-02-01

The professional medical ethics model of decision making may be applied to decisions clinicians and patients make under the conditions of clinical uncertainty that exist when evidence is low or very low. This model uses the ethical concepts of medicine as a profession, the professional virtues of integrity and candor and the patient's virtue of prudence, the moral management of medical uncertainty, and trial of intervention. These features combine to justifiably constrain clinicians' and patients' autonomy with the goal of preventing nondeliberative decisions of patients and clinicians. To prevent biased recommendations by the clinician that promote such nondeliberative decisions, medically reasonable alternatives supported by low or very low evidence should be offered but not recommended. The professional medical ethics model of decision making aims to improve the quality of decisions by reducing the unacceptable variation that can result from nondeliberative decision making by patients and clinicians when evidence is low or very low.

Integrating HL7 RIM and ontology for unified knowledge and data representation in clinical decision support systems.

PubMed

Zhang, Yi-Fan; Tian, Yu; Zhou, Tian-Shu; Araki, Kenji; Li, Jing-Song

2016-01-01

The broad adoption of clinical decision support systems within clinical practice has been hampered mainly by the difficulty in expressing domain knowledge and patient data in a unified formalism. This paper presents a semantic-based approach to the unified representation of healthcare domain knowledge and patient data for practical clinical decision making applications. A four-phase knowledge engineering cycle is implemented to develop a semantic healthcare knowledge base based on an HL7 reference information model, including an ontology to model domain knowledge and patient data and an expression repository to encode clinical decision making rules and queries. A semantic clinical decision support system is designed to provide patient-specific healthcare recommendations based on the knowledge base and patient data. The proposed solution is evaluated in the case study of type 2 diabetes mellitus inpatient management. The knowledge base is successfully instantiated with relevant domain knowledge and testing patient data. Ontology-level evaluation confirms model validity. Application-level evaluation of diagnostic accuracy reaches a sensitivity of 97.5%, a specificity of 100%, and a precision of 98%; an acceptance rate of 97.3% is given by domain experts for the recommended care plan orders. The proposed solution has been successfully validated in the case study as providing clinical decision support at a high accuracy and acceptance rate. The evaluation results demonstrate the technical feasibility and application prospect of our approach. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

[CLINICAL BACKGROUND ANALYSIS ABOUT TRANSURETHRAL ELECTROCOAGULATION].

PubMed

Katsui, Masahiro; Kikuchi, Eiji; Yazawa, Satoshi; Hagiwara, Masayuki; Morita, Shinya; Shinoda, Kazunobu; Kosaka, Takeo; Mizuno, Ryuichi; Shinojima, Toshiaki; Asanuma, Hiroshi; Miyajima, Akira; Oya, Mototsugu

2015-10-01

Transurethral electrocoagulation (TUC) is a rare event but occurs in a constant manner with various causes or disorders and reduces patient quality of life. So far there have been no reports focusing on the details of TUC. We focused on the clinical background and related causes in cases of TUC in our institution. We identified 76 cases (65 patients) who underwent TUC at Keio University Hospital between April 2001 and March 2011. We focused on patient background, especially with respect to the primary disease, treatment modality, use of antiplatelet or anticoagulant agent, timing of TUC, type of electrosurgical device, and the incidence of transfusion. The primary disease for TUC included bladder tumor (BT) in 31 cases, benign prostate hyperplasia (BPH) in 13, prostate cancer (PCa) in 13, idiopathic bladder bleeding in 4, periarteritis nodosa in 3, uterine cervical cancer in 3, and others in 9. TUC after transurethral resection (TUR) was found in 38 cases, including transurethral resection of bladder tumor (TURBT) in 26 of 31 BT cases and transurethral resection of prostate (TURP) in 12 of 13 BPH cases. After TURBT, TUC was performed before removal of a urethral catheter in 7 cases, and after removal of a urethral catheter in 19 cases. With regard to TUC associated with TURP, the average estimated prostate volume in TUC cases before removal of the urethral catheter was 66.2 ml, which was significantly larger than that in TUC cases after removal of the urethral catheter (46.1 ml, p = 0.045). TUC after the radiation therapy was observed in 21 cases, and the average time from the radiation therapy to TUC was 3.4 years (7 months-10 years). TUC was caused by multiple causes or disorders, and 75% of our TUC was associated with BT, BPH or PCa. TUC associated with TURBT frequently occurred within 1 week after TURBT but was still observed after 1 month following the operation. All TUC associated with TURP occurred within 3 weeks after operation. The average period from

Safety of clinical and non-clinical decision makers in telephone triage: a narrative review.

PubMed

Wheeler, Sheila Q; Greenberg, Mary E; Mahlmeister, Laura; Wolfe, Nicole

2015-09-01

Patient safety is a persistent problem in telephone triage research; however, studies have not differentiated between clinicians' and non-clinicians' respective safety. Currently, four groups of decision makers perform aspects of telephone triage: clinicians (physicians, nurses), and non-clinicians (emergency medical dispatchers (EMD) and clerical staff). Using studies published between 2002-2012, we applied Donabedian's structure-process-outcome model to examine groups' systems for evidence of system completeness (a minimum measure of structure and quality). We defined system completeness as the presence of a decision maker and four additional components: guidelines, documentation, training, and standards. Defining safety as appropriate referrals (AR) - (right time, right place with the right person), we measured each groups' corresponding AR rate percentages (outcomes). We analyzed each group's respective decision-making process as a safe match to the telephone triage task, based on each group's system structure completeness, process and AR rates (outcome). Studies uniformly noted system component presence: nurses (2-4), physicians (1), EMDs (2), clerical staff (1). Nurses had the highest average appropriate referral (AR) rates (91%), physicians' AR (82% average). Clerical staff had no system and did not perform telephone triage by standard definitions; EMDs may represent the use of the wrong system. Telephone triage appears least safe after hours when decision makers with the least complete systems (physicians, clerical staff) typically manage calls. At minimum, telephone triage decision makers should be clinicians; however, clinicians' safety calls for improvement. With improved training, standards and CDSS quality, the 24/7 clinical call center has potential to represent the national standard. © The Author(s) 2015.

Clinical Decision Support Reduces Overuse of Red Blood Cell Transfusions: Interrupted Time Series Analysis.

PubMed

Kassakian, Steven Z; Yackel, Thomas R; Deloughery, Thomas; Dorr, David A

2016-06-01

Red blood cell transfusion is the most common procedure in hospitalized patients in the US. Growing evidence suggests that a sizeable percentage of these transfusions are inappropriate, putting patients at significant risk and increasing costs to the health care system. We performed a retrospective quasi-experimental study from November 2008 until November 2014 in a 576-bed tertiary care hospital. The intervention consisted of an interruptive clinical decision support alert shown to a provider when a red blood cell transfusion was ordered in a patient whose most recent hematocrit was ≥21%. We used interrupted time series analysis to determine whether our primary outcome of interest, rate of red blood cell transfusion in patients with hematocrit ≥21% per 100 patient (pt) days, was reduced by the implementation of the clinical decision support tool. The rate of platelet transfusions was used as a nonequivalent dependent control variable. A total of 143,000 hospital admissions were included in our analysis. Red blood cell transfusions decreased from 9.4 to 7.8 per 100 pt days after the clinical decision support intervention was implemented. Interrupted time series analysis showed that significant decline of 0.05 (95% confidence interval [CI], 0.03-0.07; P < .001) units of red blood cells transfused per 100 pt days per month was already underway in the preintervention period. This trend accelerated to 0.1 (95% CI, 0.09-0.12; P < .001) units of red blood cells transfused per 100 pt days per month following the implementation of the clinical decision support tool. There was no statistical change in the rate of platelet transfusion resulting from the intervention. The implementation of an evidence-based clinical decision support tool was associated with a significant decline in the overuse of red blood cell transfusion. We believe this intervention could be easily replicated in other hospitals using commercial electronic health records and a similar reduction in

Emergency nurses' knowledge, attitude and clinical decision making skills about pain.

PubMed

Ucuzal, Meral; Doğan, Runida

2015-04-01

Pain is the most common reason that patients come to the emergency department. Emergency nurses have an indispensable role in the management of this pain. The aim of this study was to examine emergency nurses' knowledge, attitude and clinical decision-making skills about pain. This descriptive study was conducted in a state and a university hospital between September and October 2012 in Malatya, Turkey. Of 98 nurses working in the emergency departments of these two hospitals, 57 returned the questionnaires. The response rate was 58%. Data were collected using the Demographic Information Questionnaire, Knowledge and Attitude Questionnaire about Pain and Clinical Decision Making Survey. Frequency, percentage, mean and standard deviation were used to evaluate data. 75.4% of participant nurses knew that patients' own statement about their pain was the most reliable indicator during pain assessment. Almost half of the nurses believed that patients should be encouraged to endure the pain as much as possible before resorting to a pain relief method. The results also indicate that most of nurses think that a sleeping patient does not have any pain and pain relief should be postponed as it can influence the diagnosis negatively. It is determined that the pain scale was not used frequently. Only 35.1% of nurses reported keeping records of pain. Despite all the recommendations of substantial past research the results of this study indicate that emergency nurses continue to demonstrate inadequate knowledge, clinical decision-making skills and negative attitudes about pain. Copyright © 2014 Elsevier Ltd. All rights reserved.

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.

Comparative-effectiveness research to aid population decision making by relating clinical outcomes and quality-adjusted life years.

PubMed

Campbell, Jonathan D; Zerzan, Judy; Garrison, Louis P; Libby, Anne M

2013-04-01

Comparative-effectiveness research (CER) at the population level is missing standardized approaches to quantify and weigh interventions in terms of their clinical risks, benefits, and uncertainty. We proposed an adapted CER framework for population decision making, provided example displays of the outputs, and discussed the implications for population decision makers. Building on decision-analytical modeling but excluding cost, we proposed a 2-step approach to CER that explicitly compared interventions in terms of clinical risks and benefits and linked this evidence to the quality-adjusted life year (QALY). The first step was a traditional intervention-specific evidence synthesis of risks and benefits. The second step was a decision-analytical model to simulate intervention-specific progression of disease over an appropriate time. The output was the ability to compare and quantitatively link clinical outcomes with QALYs. The outputs from these CER models include clinical risks, benefits, and QALYs over flexible and relevant time horizons. This approach yields an explicit, structured, and consistent quantitative framework to weigh all relevant clinical measures. Population decision makers can use this modeling framework and QALYs to aid in their judgment of the individual and collective risks and benefits of the alternatives over time. Future research should study effective communication of these domains for stakeholders. Copyright © 2013 Elsevier HS Journals, Inc. All rights reserved.

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.

Virtual clinics in glaucoma care: face-to-face versus remote decision-making.

PubMed

Clarke, Jonathan; Puertas, Renata; Kotecha, Aachal; Foster, Paul J; Barton, Keith

2017-07-01

To examine the agreement in clinical decisions of glaucoma status made in a virtual glaucoma clinic with those made during a face-to-face consultation. A trained nurse and technicians entered data prospectively for 204 patients into a proforma. A subsequent face-to-face clinical assessment was completed by either a glaucoma consultant or fellow. Proformas were reviewed remotely by one of two additional glaucoma consultants, and 12 months later, by the clinicians who had undertaken the original clinical examination. The interobserver and intraobserver decision-making agreements of virtual assessment versus standard care were calculated. We identified adverse disagreement between face-to-face and virtual review in 7/204 (3.4%, 95% CI 0.9% to 5.9%) patients, where virtual review failed to predict a need to accelerated follow-up identified in face-to-face review. Misclassification events were rare, occurring in 1.9% (95% CI 0.3% to 3.8%) of assessments. Interobserver κ (95% CI) showed only fair agreement (0.24 (0.04 to 0.43)); this improved to moderate agreement when only consultant decisions were compared against each other (κ=0.41 (0.16 to 0.65)). The intraobserver agreement κ (95% CI) for the consultant was 0.274 (0.073 to 0.476), and that for the fellow was 0.264 (0.031 to 0.497). The low rate of adverse misclassification, combined with the slowly progressive nature of most glaucoma, and the fact that patients will all be regularly reassessed, suggests that virtual clinics offer a safe, logistically viable option for selected patients with glaucoma. 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/.

Value for money in changing clinical practice: should decisions about guidelines and implementation strategies be made sequentially or simultaneously?

PubMed

Hoomans, Ties; Severens, Johan L; Evers, Silvia M A A; Ament, Andre J H A

2009-01-01

Decisions about clinical practice change, that is, which guidelines to adopt and how to implement them, can be made sequentially or simultaneously. Decision makers adopting a sequential approach first compare the costs and effects of alternative guidelines to select the best set of guideline recommendations for patient management and subsequently examine the implementation costs and effects to choose the best strategy to implement the selected guideline. In an integral approach, decision makers simultaneously decide about the guideline and the implementation strategy on the basis of the overall value for money in changing clinical practice. This article demonstrates that the decision to use a sequential v. an integral approach affects the need for detailed information and the complexity of the decision analytic process. More importantly, it may lead to different choices of guidelines and implementation strategies for clinical practice change. The differences in decision making and decision analysis between the alternative approaches are comprehensively illustrated using 2 hypothetical examples. We argue that, in most cases, an integral approach to deciding about change in clinical practice is preferred, as this provides more efficient use of scarce health-care resources.

Development of a Model of Interprofessional Shared Clinical Decision Making in the ICU: A Mixed-Methods Study.

PubMed

DeKeyser Ganz, Freda; Engelberg, Ruth; Torres, Nicole; Curtis, Jared Randall

2016-04-01

To develop a model to describe ICU interprofessional shared clinical decision making and the factors associated with its implementation. Ethnographic (observations and interviews) and survey designs. Three ICUs (two in Israel and one in the United States). A convenience sample of nurses and physicians. None. Observations and interviews were analyzed using ethnographic and grounded theory methodologies. Questionnaires included a demographic information sheet and the Jefferson Scale of Attitudes toward Physician-Nurse Collaboration. From observations and interviews, we developed a conceptual model of the process of shared clinical decision making that involves four stepped levels, proceeding from the lowest to the highest levels of collaboration: individual decision, information exchange, deliberation, and shared decision. This process is influenced by individual, dyadic, and system factors. Most decisions were made at the lower two levels. Levels of perceived collaboration were moderate with no statistically significant differences between physicians and nurses or between units. Both qualitative and quantitative data corroborated that physicians and nurses from all units were similarly and moderately satisfied with their level of collaboration and shared decision making. However, most ICU clinical decision making continues to take place independently, where there is some sharing of information but rarely are decisions made collectively. System factors, such as interdisciplinary rounds and unit culture, seem to have a strong impact on this process. This study provides a model for further study and improvement of interprofessional shared decision making.

Development and evaluation of a comprehensive clinical decision support taxonomy: comparison of front-end tools in commercial and internally developed electronic health record systems

PubMed Central

Sittig, Dean F; Ash, Joan S; Feblowitz, Joshua; Meltzer, Seth; McMullen, Carmit; Guappone, Ken; Carpenter, Jim; Richardson, Joshua; Simonaitis, Linas; Evans, R Scott; Nichol, W Paul; Middleton, Blackford

2011-01-01

Background Clinical decision support (CDS) is a valuable tool for improving healthcare quality and lowering costs. However, there is no comprehensive taxonomy of types of CDS and there has been limited research on the availability of various CDS tools across current electronic health record (EHR) systems. Objective To develop and validate a taxonomy of front-end CDS tools and to assess support for these tools in major commercial and internally developed EHRs. Study design and methods We used a modified Delphi approach with a panel of 11 decision support experts to develop a taxonomy of 53 front-end CDS tools. Based on this taxonomy, a survey on CDS tools was sent to a purposive sample of commercial EHR vendors (n=9) and leading healthcare institutions with internally developed state-of-the-art EHRs (n=4). Results Responses were received from all healthcare institutions and 7 of 9 EHR vendors (response rate: 85%). All 53 types of CDS tools identified in the taxonomy were found in at least one surveyed EHR system, but only 8 functions were present in all EHRs. Medication dosing support and order facilitators were the most commonly available classes of decision support, while expert systems (eg, diagnostic decision support, ventilator management suggestions) were the least common. Conclusion We developed and validated a comprehensive taxonomy of front-end CDS tools. A subsequent survey of commercial EHR vendors and leading healthcare institutions revealed a small core set of common CDS tools, but identified significant variability in the remainder of clinical decision support content. PMID:21415065

Computer Decision Support to Improve Autism Screening and Care in Community Pediatric Clinics

ERIC Educational Resources Information Center

Bauer, Nerissa S.; Sturm, Lynne A.; Carroll, Aaron E.; Downs, Stephen M.

2013-01-01

An autism module was added to an existing computer decision support system (CDSS) to facilitate adherence to recommended guidelines for screening for autism spectrum disorders in primary care pediatric clinics. User satisfaction was assessed by survey and informal feedback at monthly meetings between clinical staff and the software team. To assess…

Reward-related decision making in older adults: relationship to clinical presentation of depression.

PubMed

McGovern, Amanda R; Alexopoulos, George S; Yuen, Genevieve S; Morimoto, Sarah Shizuko; Gunning-Dixon, Faith M

2014-11-01

Impairment in reward processes has been found in individuals with depression and in the aging population. The purpose of this study was twofold: (1) to use an affective neuroscience probe to identify abnormalities in reward-related decision making in late-life depression; and (2) to examine the relationship of reward-related decision making abnormalities in depressed, older adults to the clinical expression of apathy in depression. We hypothesized that relative to older, healthy subjects, depressed, older patients would exhibit impaired decision making and that apathetic, depressed patients would show greater impairment in decision making than non-apathetic, depressed patients. We used the Iowa Gambling Task to examine reward-related decision making in 60 non-demented, older patients with non-psychotic major depression and 36 older, psychiatrically healthy participants. Apathy was quantified using the Apathy Evaluation Scale. Of those with major depression, 18 individuals reported clinically significant apathy, whereas 42 participants did not have apathy. Older adults with depression and healthy comparison participants did not differ in their performance on the Iowa Gambling Task. However, apathetic, depressed older adults adopted an advantageous strategy and selected cards from the conservative decks compared with non-apathetic, depressed older adults. Non-apathetic, depressed patients showed a failure to adopt a conservative strategy and persisted in making risky decisions throughout the task. This study indicates that apathy in older, depressed adults is associated with a conservative response style on a behavioral probe of the systems involved in reward-related decision making. This conservative response style may be the result of reduced sensitivity to rewards in apathetic individuals. Copyright © 2014 John Wiley & Sons, Ltd.

The Associations Between the Religious Background, Social Supports, and Do-Not-Resuscitate Orders in Taiwan

PubMed Central

Lin, Kuan-Han; Chen, Yih-Sharng; Chou, Nai-Kuan; Huang, Sheng-Jean; Wu, Chau-Chung; Chen, Yen-Yuan

2016-01-01

Abstract Prior studies have demonstrated important implications related to religiosity and a do-not-resuscitate (DNR) decision. However, the association between patients’ religious background and DNR decisions is vague. In particular, the association between the religious background of Buddhism/Daoism and DNR decisions has never been examined. The objective of this study was to examine the association between patients’ religious background and their DNR decisions, with a particular focus on Buddhism/Daoism. The medical records of the patients who were admitted to the 3 surgical intensive care units (SICU) in a university-affiliated medical center located at Northern Taiwan from June 1, 2011 to December 31, 2013 were retrospectively collected. We compared the clinical/demographic variables of DNR patients with those of non-DNR patients using the Student t test or χ2 test depending on the scale of the variables. We used multivariate logistic regression analysis to examine the association between the religious backgrounds and DNR decisions. A sample of 1909 patients was collected: 122 patients had a DNR order; and 1787 patients did not have a DNR order. Old age (P = 0.02), unemployment (P = 0.02), admission diagnosis of “nonoperative, cardiac failure/insufficiency” (P = 0.03), and severe acute illness at SICU admission (P < 0.01) were significantly associated with signing of DNR orders. Patients’ religious background of Buddhism/Daoism (P = 0.04), married marital status (P = 0.02), and admission diagnosis of “postoperative, major surgery” (P = 0.02) were less likely to have a DNR order written during their SICU stay. Furthermore, patients with poor social support, as indicated by marital and working status, were more likely to consent to a DNR order during SICU stay. This study showed that the religious background of Buddhism/Daoism was significantly associated with a lower likelihood of consenting to a DNR, and poor social

Remote clinical decision-making: a clinician's definition.

PubMed

Brady, Mike; Northstone, Kate

2017-05-12

Aims Remote clinical decision-making (RCDM), commonly known as 'telephone triage' or 'hear and treat', describes clinicians' non-face-to-face involvement with patient care, and is an established strategy in UK ambulance services for managing increasing demand. However, there is no suitable definition of RCDM that fully explains the roles undertaken by clinicians in 999 hubs, or for its use as an ambulance quality indicator (AQI). The aim of this study, which is part of a larger evaluation of a new RCDM module in higher education, is to determine how clinicians define RCDM. Methods Three participants were asked, during semi-structured interviews, to define RCDM. The interviews were recorded, transcribed and thematically analysed. Results Clinicians do not focus on outcomes when defining RCDM, but on the efficacy of the process and the appropriateness of the determined outcome. Conclusion There is no precise description of the role of healthcare professionals in 999 clinical hubs, but there is a need for role clarity, for employees and organisations. The study questions the suitability of the definition of hear and treat as an AQI, as it does not appear to represent fully the various duties undertaken by 999 clinical hub healthcare professionals. More research is needed to consider the definition of RCDM in all its forms.

Mothers' process of decision making for gastrostomy placement.

PubMed

Brotherton, Ailsa; Abbott, Janice

2012-05-01

In this article we present the findings of an exploration of mothers' discourses on decision making for gastrostomy placement for their child. Exploring in-depth interviews of a purposive sample, we analyzed the mothers' discourses of the decision-making process to understand how their experiences of the process influenced their subsequent constructions of decision making. Mothers negotiated decision making by reflecting on their personal experiences of feeding their child, either orally or via a tube, and interwove their background experiences with the communications from members of the health care team until a decision was reached. Decision making was often fraught with difficulty, resulting in anxiety and guilt. Experiences of decision making ranged from perceived coercion to true choice, which encompasses a truly child-centered decision. The resulting impact of the decision-making process on the mothers was profound. We conclude with an exploration of the implications for clinical practice and describe how health care professionals can support mothers to ensure that decision-making processes for gastrostomy placement in children are significantly improved.

An Examination of Accelerated and Basic Baccalaureate Nursing Students' Perceptions of Clinical Decision Making

ERIC Educational Resources Information Center

Krumwiede, Kelly A.

2010-01-01

Developing decision-making skills is essential in education in order to be a competent nurse. The purpose of this study was to examine and compare the perceptions of clinical decision-making skills of students enrolled in accelerated and basic baccalaureate nursing programs. A comparative descriptive research design was used for this study.…

Factors Predicting Oncology Care Providers' Behavioral Intention to Adopt Clinical Decision Support Systems

ERIC Educational Resources Information Center

Wolfenden, Andrew

2012-01-01

The purpose of this quantitative correlation study was to examine the predictors of user behavioral intention on the decision of oncology care providers to adopt or reject the clinical decision support system. The Unified Theory of Acceptance and Use of Technology (UTAUT) formed the foundation of the research model and survey instrument. The…

Measuring the impact of diagnostic decision support on the quality of clinical decision making: development of a reliable and valid composite score.

PubMed

Ramnarayan, Padmanabhan; Kapoor, Ritika R; Coren, Michael; Nanduri, Vasantha; Tomlinson, Amanda L; Taylor, Paul M; Wyatt, Jeremy C; Britto, Joseph F

2003-01-01

Few previous studies evaluating the benefits of diagnostic decision support systems have simultaneously measured changes in diagnostic quality and clinical management prompted by use of the system. This report describes a reliable and valid scoring technique to measure the quality of clinical decision plans in an acute medical setting, where diagnostic decision support tools might prove most useful. Sets of differential diagnoses and clinical management plans generated by 71 clinicians for six simulated cases, before and after decision support from a Web-based pediatric differential diagnostic tool (ISABEL), were used. A composite quality score was calculated separately for each diagnostic and management plan by considering the appropriateness value of each component diagnostic or management suggestion, a weighted sum of individual suggestion ratings, relevance of the entire plan, and its comprehensiveness. The reliability and validity (face, concurrent, construct, and content) of these two final scores were examined. Two hundred fifty-two diagnostic and 350 management suggestions were included in the interrater reliability analysis. There was good agreement between raters (intraclass correlation coefficient, 0.79 for diagnoses, and 0.72 for management). No counterintuitive scores were demonstrated on visual inspection of the sets. Content validity was verified by a consultation process with pediatricians. Both scores discriminated adequately between the plans of consultants and medical students and correlated well with clinicians' subjective opinions of overall plan quality (Spearman rho 0.65, p < 0.01). The diagnostic and management scores for each episode showed moderate correlation (r = 0.51). The scores described can be used as key outcome measures in a larger study to fully assess the value of diagnostic decision aids, such as the ISABEL system.

Nurses' pressure ulcer related judgements and decisions in clinical practice: a systematic review.

PubMed

Samuriwo, Ray; Dowding, Dawn

2014-12-01

Pressure ulcers are considered to be an adverse outcome of care that should never occur in clinical practice. The formation of a pressure ulcer is also perceived to be an indicator of poor quality nursing care. Therefore, pressure ulcer prevention is a priority for nurses, healthcare professionals and healthcare organisations throughout the world. A key factor in pressure ulcer prevention and management is individual nurse decision making. To synthesise the literature on the judgement and decision making of nurses in relation to the assessment, prevention, grading and management of pressure ulcers in all care settings (hospital and community). A systematic search of published literature relating to judgement and decision making in nurses, with a focus on the prevention and management of pressure ulcers. A search of electronic databases from 1992 to present, together with hand searching of the reference lists of retrieved publications, to identify published papers that reported results of studies evaluating the decision making of nurses in relation to the prevention and management of pressure ulcers. Abstracts were independently reviewed by two authors and full text of potentially relevant articles retrieved. Each paper included in this systematic review was evaluated using recognised appraisal criteria relevant to the specific study design. Included papers provided empirical data on key aspects of nurses' pressure ulcer related judgements and decision making. Data were synthesised into themes using narrative analysis. Sixteen studies and one systematic review were included in the review, focusing on pressure ulcer risk assessment, pressure ulcer prevention, grading of pressure ulcers and treatment decisions. The results indicated that assessment tools were not routinely used to identify pressure ulcer risk, and that nurses rely on their own knowledge and experience rather than research evidence to decide what skin care to deliver. Emphasising pressure ulcer risk

Development of a prototype clinical decision support tool for osteoporosis disease management: a qualitative study of focus groups

PubMed Central

2010-01-01

Background Osteoporosis affects over 200 million people worldwide, and represents a significant cost burden. Although guidelines are available for best practice in osteoporosis, evidence indicates that patients are not receiving appropriate diagnostic testing or treatment according to guidelines. The use of clinical decision support systems (CDSSs) may be one solution because they can facilitate knowledge translation by providing high-quality evidence at the point of care. Findings from a systematic review of osteoporosis interventions and consultation with clinical and human factors engineering experts were used to develop a conceptual model of an osteoporosis tool. We conducted a qualitative study of focus groups to better understand physicians' perceptions of CDSSs and to transform the conceptual osteoporosis tool into a functional prototype that can support clinical decision making in osteoporosis disease management at the point of care. Methods The conceptual design of the osteoporosis tool was tested in 4 progressive focus groups with family physicians and general internists. An iterative strategy was used to qualitatively explore the experiences of physicians with CDSSs; and to find out what features, functions, and evidence should be included in a working prototype. Focus groups were conducted using a semi-structured interview guide using an iterative process where results of the first focus group informed changes to the questions for subsequent focus groups and to the conceptual tool design. Transcripts were transcribed verbatim and analyzed using grounded theory methodology. Results Of the 3 broad categories of themes that were identified, major barriers related to the accuracy and feasibility of extracting bone mineral density test results and medications from the risk assessment questionnaire; using an electronic input device such as a Tablet PC in the waiting room; and the importance of including well-balanced information in the patient education

Mapping clinical outcomes expectations to treatment decisions: an application to vestibular schwannoma management.

PubMed

Cheung, Steven W; Aranda, Derick; Driscoll, Colin L W; Parsa, Andrew T

2010-02-01

Complex medical decision making obligates tradeoff assessments among treatment outcomes expectations, but an accessible tool to perform the necessary analysis is conspicuously absent. We aimed to demonstrate methodology and feasibility of adapting conjoint analysis for mapping clinical outcomes expectations to treatment decisions in vestibular schwannoma (VS) management. Prospective. Tertiary medical center and US-based otologists/neurotologists. Treatment preference profiles among VS stakeholders-61 younger and 74 older prospective patients, 61 observation patients, and 60 surgeons-were assessed for the synthetic VS case scenario of a 10-mm tumor in association with useful hearing and normal facial function. Treatment attribute utility. Conjoint analysis attribute levels were set in accordance to the results of a meta-analysis. Forty-five case series were disaggregated to formulate microsurgery facial nerve and hearing preservation outcomes expectations models. Attribute utilities were computed and mapped to the realistic treatment choices of translabyrinthine craniotomy, middle fossa craniotomy, and gamma knife radiosurgery. Among the treatment attributes of likelihoods of causing deafness, temporary facial weakness for 2 months, and incurable cancer within 20 years, and recovery time, permanent deafness was less important to tumor surgeons, and temporary facial weakness was more important to tumor surgeons and observation patients (Wilcoxon rank-sum, p < 0.001). Inverse mapping of preference profiles to realistic treatment choices showed all study cohorts were inclined to choose gamma knife radiosurgery. Mapping clinical outcomes expectations to treatment decisions for a synthetic clinical scenario revealed inhomogeneous drivers of choice selection among study cohorts. Medical decision engines that analyze personal preferences of outcomes expectations for VS and many other diseases may be developed to promote shared decision making among health care stakeholders

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.

Endodontic retreatment. Aspects of decision making and clinical outcome.

PubMed

Kvist, T

2001-01-01

regardless of assessment method. Compared with Standard gamble Visual Analogue Scale systematically produced lower ratings. U-values were found to change considerably in both the short and long-term. Any significant correlation between endodontists' U-values and retreatment prescriptions could not be demonstrated. Surgical and nonsurgical retreatment were randomly assigned to 95 "failed" root filled teeth in 92 patients. Cases were followed clinically and radiographically for four years postoperatively. At the 12-month recall a statistically significant higher healing rate was observed for teeth retreated surgically. At the final 48-month recall no systematic difference was detected. Patients were found to be more subject to postoperative discomfort when teeth were retreated surgically compared with nonsurgically. Consequently, surgical retreatment tended to be associated with higher indirect costs than a nonsurgically approach. In the final part of the thesis it is argued that retreatment decision making in everyday clinical practice normally should be based on simple principles. It is suggested that in order to achieve the best overall consequence a periapical lesion in a root filled tooth that is not expected to heal should be retreated. Arguments to withhold retreatment should be based on (i) respect for patient autonomy, (ii) retreatment risks or (iii) retreatment costs.

Clinical Factors and the Decision to Transfuse Chronic Dialysis Patients

PubMed Central

Whitman, Cynthia B.; Shreay, Sanatan; Gitlin, Matthew; van Oijen, Martijn G. H.

2013-01-01

Summary Background and objectives Red blood cell transfusion was previously the principle therapy for anemia in CKD but became less prevalent after the introduction of erythropoiesis-stimulating agents. This study used adaptive choice-based conjoint analysis to identify preferences and predictors of transfusion decision-making in CKD. Design, setting, participants, & measurements A computerized adaptive choice-based conjoint survey was administered between June and August of 2012 to nephrologists, internists, and hospitalists listed in the American Medical Association Masterfile. The survey quantified the relative importance of 10 patient attributes, including hemoglobin levels, age, occult blood in stool, severity of illness, eligibility for transplant, iron indices, erythropoiesis-stimulating agents, cardiovascular disease, and functional status. Triggers of transfusions in common dialysis scenarios were studied, and based on adaptive choice-based conjoint-derived preferences, relative importance by performing multivariable regression to identify predictors of transfusion preferences was assessed. Results A total of 350 providers completed the survey (n=305 nephrologists; mean age=46 years; 21% women). Of 10 attributes assessed, absolute hemoglobin level was the most important driver of transfusions, accounting for 29% of decision-making, followed by functional status (16%) and cardiovascular comorbidities (12%); 92% of providers transfused when hemoglobin was 7.5 g/dl, independent of other factors. In multivariable regression, Veterans Administration providers were more likely to transfuse at 8.0 g/dl (odds ratio, 5.9; 95% confidence interval, 1.9 to 18.4). Although transplant eligibility explained only 5% of decision-making, nephrologists were five times more likely to value it as important compared with non-nephrologists (odds ratio, 5.2; 95% confidence interval, 2.4 to11.1). Conclusions Adaptive choice-based conjoint analysis was useful in predicting

Development and initial evaluation of a treatment decision dashboard

PubMed Central

2013-01-01

Background For many healthcare decisions, multiple alternatives are available with different combinations of advantages and disadvantages across several important dimensions. The complexity of current healthcare decisions thus presents a significant barrier to informed decision making, a key element of patient-centered care. Interactive decision dashboards were developed to facilitate decision making in Management, a field marked by similarly complicated choices. These dashboards utilize data visualization techniques to reduce the cognitive effort needed to evaluate decision alternatives and a non-linear flow of information that enables users to review information in a self-directed fashion. Theoretically, both of these features should facilitate informed decision making by increasing user engagement with and understanding of the decision at hand. We sought to determine if the interactive decision dashboard format can be successfully adapted to create a clinically realistic prototype patient decision aid suitable for further evaluation and refinement. Methods We created a computerized, interactive clinical decision dashboard and performed a pilot test of its clinical feasibility and acceptability using a multi-method analysis. The dashboard summarized information about the effectiveness, risks of side effects and drug-drug interactions, out-of-pocket costs, and ease of use of nine analgesic treatment options for knee osteoarthritis. Outcome evaluations included observations of how study participants utilized the dashboard, questionnaires to assess usability, acceptability, and decisional conflict, and an open-ended qualitative analysis. Results The study sample consisted of 25 volunteers - 7 men and 18 women - with an average age of 51 years. The mean time spent interacting with the dashboard was 4.6 minutes. Mean evaluation scores on scales ranging from 1 (low) to 7 (high) were: mechanical ease of use 6.1, cognitive ease of use 6.2, emotional difficulty 2

Quality, cost, and clinical decisions.

PubMed

Donabedian, A

1983-07-01

Clinical decisions require determining the objectives of care as well as selecting and implementing a strategy of care. At the very least the optimal strategy balances the expected benefit and harm from technical interventions. Health care practitioners tend to specify optimal strategies based on what they consider to be best for patients, without regard to monetary cost. This is an absolutist definition of quality. Individuals may place different valuations on the outcomes, are concerned with the monetary costs to themselves, and are particularly sensitive to the attributes of the interpersonal relationship with the practitioners. Including all of these leads to an individualized definition of the quality of care. But this specification of quality may be in conflict with a social definition of quality, which takes into account social as well as individual monetary costs, externalities, and the social distribution of quality. The health care professions may respond to the conflict in several ways, which are described in this article as evasion, rejection and confrontation, anticipation, advocacy, active complicity, passive complicity, and ambiguous adaptations.

Impact of advanced monitoring variables on intraoperative clinical decision-making: an international survey.

PubMed

Joosten, Alexandre; Desebbe, Olivier; Suehiro, Koichi; Essiet, Mfonobong; Alexander, Brenton; Ricks, Cameron; Rinehart, Joseph; Faraoni, David; Cecconi, Maurizio; Van der Linden, Philippe; Cannesson, Maxime

2017-02-01

To assess the relationship between the addition of advanced monitoring variables and changes in clinical decision-making. A 15-questions survey was anonymously emailed to international experts and physician members of five anesthesia societies which focused on assessing treatment decisions of clinicians during three realistic clinical scenarios measured at two distinct time points. The first is when typical case information and basic monitoring (T1) were provided, and then once again after the addition of advanced monitoring variables (T2). We hypothesized that the addition of advanced variables would increase the incidence of an optimal therapeutic decision (a priori defined as the answer with the highest percentage of expert agreement) and decrease the variability among the physician's suggested treatments. The survey was completed by 18 experts and 839 physicians. Overall, adding advanced monitoring did not significantly increase physician response accuracy, with the least substantial changes noted on questions related to volume expansion or vasopressor administration. Moreover, advanced monitoring data did not significantly decrease the high level of initial practice variability in physician suggested treatments (P = 0.13), in contrast to the low variability observed within the expert group (P = 0.039). Additionally, 5-10 years of practice (P < 0.0001) and a cardiovascular subspecialty (P = 0.048) were both physician characteristics associated with a higher rate of optimal therapeutic decisions. The addition of advanced variables was of limited benefit for most physicians, further indicating the need for more in depth education on the clinical value and technical understanding of such variables.

SFINX-a drug-drug interaction database designed for clinical decision support systems.

PubMed

Böttiger, Ylva; Laine, Kari; Andersson, Marine L; Korhonen, Tuomas; Molin, Björn; Ovesjö, Marie-Louise; Tirkkonen, Tuire; Rane, Anders; Gustafsson, Lars L; Eiermann, Birgit

2009-06-01

The aim was to develop a drug-drug interaction database (SFINX) to be integrated into decision support systems or to be used in website solutions for clinical evaluation of interactions. Key elements such as substance properties and names, drug formulations, text structures and references were defined before development of the database. Standard operating procedures for literature searches, text writing rules and a classification system for clinical relevance and documentation level were determined. ATC codes, CAS numbers and country-specific codes for substances were identified and quality assured to ensure safe integration of SFINX into other data systems. Much effort was put into giving short and practical advice regarding clinically relevant drug-drug interactions. SFINX includes over 8,000 interaction pairs and is integrated into Swedish and Finnish computerised decision support systems. Over 31,000 physicians and pharmacists are receiving interaction alerts through SFINX. User feedback is collected for continuous improvement of the content. SFINX is a potentially valuable tool delivering instant information on drug interactions during prescribing and dispensing.

Appropriateness for Total Joint Replacement: Perspectives of Decision-Makers

PubMed Central

Clavel, Nathalie; De coster, Carolyn; Pomey, Marie-Pascale; Sanmartin, Claudia; Bohm, Éric; Dunbar, Michael J.; Frank, CY; Hawker, Gillian; Noseworthy, Tom

2016-01-01

Background: Improving access to total joint replacement (TJR) has been a priority. Without robust mechanisms to ensure appropriateness, these procedures may be overused, incurring substantial costs. In that context, decision-makers are particularly concerned with the appropriateness of TJR. Objective: While our previous research focused on the appropriateness of TJR from clinical and patient perspectives, this study is aimed at understanding decision-makers' perspectives. Methods: Using a semi-structured guide, we interviewed a convenience sample of decision-makers in four Canadian provinces (Alberta, Manitoba, Nova Scotia and Quebec) between February and March 2013. For the purposes of this study, a decision-maker was defined as a manager, institutional leader or policy maker. Results: Fifteen interviews were conducted with decision-makers at ministry (n = 3), regional (n = 6) and institutional levels (n = 8). Decision-makers see themselves as having a key role in the appropriateness discourse, that of optimizing resource allocation and efficient delivery of services for TJR, to improve population outcomes. Conclusion: The decision-makers' view of appropriateness recognizes the importance of the clinical view, but it offers a very different input into the appropriateness discourse, more closely aligned with appropriateness of setting, which refers to cost-effectiveness considerations. PMID:27027795

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

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.

Employing clinical decision support to attain our strategic goal: the safe care of the surgical patient.

PubMed

Magid, Steven K; Pancoast, Paul E; Fields, Theodore; Bradley, Diane G; Williams, Robert B

2007-01-01

Clinical decision support can be employed to increase patient safety and improve workflow efficiencies for physicians and other healthcare providers. Physician input into the design and deployment of clinical decision support systems can increase the utility of the alerts and reduce the likelihood of "alert fatigue." The Hospital for Special Surgery is a 146-bed orthopedic facility that performs approximately 18,000 surgeries a year Efficient work processes are a necessity. The facility began implementing a new electronic health record system in June 2005 and plan to go live in summer 2007. This article reports on some of the clinical decision support rules and alerts being incorporated into the facility's system in the following categories--high-risk, high-frequency scenarios, rules that provide efficiencies and value from the presciber perspective, and rules that relate to patient safety.

When four principles are too many: bloodgate, integrity and an action-guiding model of ethical decision making in clinical practice.

PubMed

Muirhead, William

2012-04-01

Medical ethical analysis remains dominated by the principlist account first proposed by Beauchamp and Childress. This paper argues that the principlist model is unreflective of how ethical decisions are taken in clinical practice. Two kinds of medical ethical decisions are distinguished: biosocial ethics and clinical ethics. It is argued that principlism is an inappropriate model for clinical ethics as it is neither sufficiently action-guiding nor does it emphasise the professional integrity of the clinician. An alternative model is proposed for decision making in the realm of clinical ethics.

[Clinical everyday ethics-support in handling moral distress? : Evaluation of an ethical decision-making model for interprofessional clinical teams].

PubMed

Tanner, S; Albisser Schleger, H; Meyer-Zehnder, B; Schnurrer, V; Reiter-Theil, S; Pargger, H

2014-06-01

High-tech medicine and cost rationing provoke moral distress up to burnout syndromes. The consequences are severe, not only for those directly involved but also for the quality of patient care and the institutions. The multimodal model METAP (Modular, Ethical, Treatment, Allocation, Process) was developed as clinical everyday ethics to support the interprofessional ethical decision-making process. The distinctive feature of the model lays in education concerning ethics competence in dealing with difficult treatment decisions. METAP has been evaluated for quality testing. The research question of interest was whether METAP supports the handling of moral distress. The evaluation included 3 intensive care units and 3 geriatric units. In all, 33 single and 9 group interviews were held with 24 physicians, 44 nurses, and 9 persons from other disciplines. An additional questionnaire was completed by 122 persons (return rate 57%). Two-thirds of the interview answers and 55% of the questionnaire findings show that clinical everyday ethics supports the handling of moral distress, especially for interdisciplinary communication and collaboration and for the explanation and evaluation of treatment goals. METAP does not provide support for persons who are rarely confronted with ethical problems or have not applied the model long enough yet. To a certain degree, moral distress is unavoidable and must be addressed as an interprofessional problem. Herein, clinical everyday ethics may provide targeted support for ethical decision-making competence.

Clinical Decision Support Knowledge Management: Strategies for Success.

PubMed

Khalifa, Mohamed; Alswailem, Osama

2015-01-01

Clinical Decision Support Systems have been shown to increase quality of care, patient safety, improve adherence to guidelines for prevention and treatment, and avoid medication errors. Such systems depend mainly on two types of content; the clinical information related to patients and the medical knowledge related to the specialty that informs the system rules and alerts. At King Faisal Specialist Hospital and Research Center, Saudi Arabia, the Health Information Technology Affairs worked on identifying best strategies and recommendations for successful CDSS knowledge management. A review of literature was conducted to identify main areas of challenges and factors of success. A qualitative survey was used over six months' duration to collect opinions, experiences and suggestions from both IT and healthcare professionals. Recommendations were categorized into ten main topics that should be addressed during the development and implementation of CDSS knowledge management tools in the hospital.

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.

Recommended practices for computerized clinical decision support and knowledge management in community settings: a qualitative study

PubMed Central

2012-01-01

Background The purpose of this study was to identify recommended practices for computerized clinical decision support (CDS) development and implementation and for knowledge management (KM) processes in ambulatory clinics and community hospitals using commercial or locally developed systems in the U.S. Methods Guided by the Multiple Perspectives Framework, the authors conducted ethnographic field studies at two community hospitals and five ambulatory clinic organizations across the U.S. Using a Rapid Assessment Process, a multidisciplinary research team: gathered preliminary assessment data; conducted on-site interviews, observations, and field surveys; analyzed data using both template and grounded methods; and developed universal themes. A panel of experts produced recommended practices. Results The team identified ten themes related to CDS and KM. These include: 1) workflow; 2) knowledge management; 3) data as a foundation for CDS; 4) user computer interaction; 5) measurement and metrics; 6) governance; 7) translation for collaboration; 8) the meaning of CDS; 9) roles of special, essential people; and 10) communication, training, and support. Experts developed recommendations about each theme. The original Multiple Perspectives framework was modified to make explicit a new theoretical construct, that of Translational Interaction. Conclusions These ten themes represent areas that need attention if a clinic or community hospital plans to implement and successfully utilize CDS. In addition, they have implications for workforce education, research, and national-level policy development. The Translational Interaction construct could guide future applied informatics research endeavors. PMID:22333210

A Systematic Review of the Impact of Physician Implicit Racial Bias on Clinical Decision Making.

PubMed

Dehon, Erin; Weiss, Nicole; Jones, Jonathan; Faulconer, Whitney; Hinton, Elizabeth; Sterling, Sarah

2017-08-01

Disparities in diagnosis and treatment of racial minorities exist in the emergency department (ED). A better understanding of how physician implicit (unconscious) bias contributes to these disparities may help identify ways to eliminate such racial disparities. The objective of this systematic review was to examine and summarize the evidence on the association between physician implicit racial bias and clinical decision making. Based on PRISMA guidelines, a structured electronic literature search of PubMed, CINAHL, Scopus, and PsycINFO databases was conducted. Eligible studies were those that: 1) included physicians, 2) included the Implicit Association Test as a measure of implicit bias, 3) included an assessment of physician clinical decision making, and 4) were published in peer-reviewed journals between 1998 and 2016. Articles were reviewed for inclusion by two independent investigators. Data extraction was performed by one investigator and checked for accuracy by a second investigator. Two investigators independently scored the quality of articles using a modified version of the Downs and Black checklist. Of the 1,154 unique articles identified in the initial search, nine studies (n = 1,910) met inclusion criteria. Three of the nine studies involved emergency providers including residents, attending physicians, and advanced practice providers. The majority of studies used clinical vignettes to examine clinical decision making. Studies that included emergency medicine (EM) providers had vignettes relating to treatment of acute myocardial infarction, pain, and pediatric asthma. An implicit preference favoring white people was common across providers, regardless of specialty. Two of the nine studies found evidence of a relationship between implicit bias and clinical decision making; one of these studies included EM providers. This one study found that EM and internal medicine residents who demonstrated an implicit preference for white individuals were more likely

Knowledge of risk factors and the periodontal disease-systemic link in dental students' clinical decisions.

PubMed

Friesen, Lynn Roosa; Walker, Mary P; Kisling, Rebecca E; Liu, Ying; Williams, Karen B

2014-09-01

This study evaluated second-, third-, and fourth-year dental students' ability to identify systemic conditions associated with periodontal disease, risk factors most important for referral, and medications with an effect on the periodontium and their ability to apply this knowledge to make clinical decisions regarding treatment and referral of periodontal patients. A twenty-one question survey was administered at one U.S. dental school in the spring semester of 2012 to elicit the students' knowledge and confidence regarding clinical reasoning. The response rate was 86 percent. Periodontal risk factors were accurately selected by at least 50 percent of students in all three classes; these were poorly controlled diabetes, ≥6 mm pockets posteriorly, and lack of response to previous non-surgical therapy. Confidence in knowledge, knowledge of risk factors, and knowledge of medications with an effect on the periodontium improved with training and were predictive of better referral decision making. The greatest impact of training was seen on the students' ability to make correct decisions about referral and treatment for seven clinical scenarios. Although the study found a large increase in the students' abilities from the second through fourth years, the mean of 4.6 (out of 7) for the fourth-year students shows that, on average, those students missed correct treatment or referral on more than two of seven clinical cases. These results suggest that dental curricula should emphasize more critical decision making with respect to referral and treatment criteria in managing the periodontal patient.

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

Impact of clinical and health services research projects on decision-making: a qualitative study.

PubMed

Solans-Domènech, Maite; Adam, Paula; Guillamón, Imma; Permanyer-Miralda, Gaietà; Pons, Joan M V; Escarrabill, Joan

2013-05-10

This article reports on the impact assessment experience of a funding program of non-commercial clinical and health services research. The aim was to assess the level of implementation of results from a subgroup of research projects (on respiratory diseases), and to detect barriers (or facilitators) in the translation of new knowledge to informed decision-making. A qualitative study was performed. The sample consisted of six projects on respiratory diseases funded by the Agency for Health Quality and Assessment of Catalonia between 1996 and 2004. Semi-structured interviews to key informants including researchers and healthcare decision-makers were carried out. Interviews were recorded, transcribed verbatim and analysed on an individual (key informant) and group (project) basis. In addition, the differences between achieved and expected impacts were described. Twenty-three semi-structured interviews were conducted. Most participants indicated changes in health services or clinical practice had resulted from research. The channels used to transfer new knowledge were mainly conventional ones, but also in less explicit ways, such as with the involvement of local scientific societies, or via debates and discussions with colleagues and local leaders. The barriers and facilitators identified were mostly organizational (in research management, and clinical and healthcare practice), although there were also some related to the nature of the research as well as personal factors. Both the expected and achieved impacts enabled the identification of the gaps between what is expected and what is truly achieved. In this study and according to key informants, the impact of these research projects on decision-making can be direct (the application of a finding or innovation) or indirect, contributing to a more complex change in clinical practice and healthcare organization, both having other contextual factors. The channels used to transfer this new knowledge to clinical practice

Putting cognitive psychology to work: Improving decision-making in the medical encounter.

PubMed

Schwab, Abraham P

2008-12-01

Empirical research in social psychology has provided robust support for the accuracy of the heuristics and biases approach to human judgment. This research, however, has not been systematically investigated regarding its potential applications for specific health care decision-makers. This paper makes the case for investigating the heuristics and biases approach in the patient-physician relationship and recommends strategic empirical research. It is argued that research will be valuable for particular decisions in the clinic and for examining and altering the background conditions of patient and physician decision-making.

Advancing clinical decision support using lessons from outside of healthcare: an interdisciplinary systematic review.

PubMed

Wu, Helen W; Davis, Paul K; Bell, Douglas S

2012-08-17

Greater use of computerized decision support (DS) systems could address continuing safety and quality problems in healthcare, but the healthcare field has struggled to implement DS technology. This study surveys DS experience across multiple non-healthcare disciplines for new insights that are generalizable to healthcare provider decisions. In particular, it sought design principles and lessons learned from the other disciplines that could inform efforts to accelerate the adoption of clinical decision support (CDS). Our systematic review drew broadly from non-healthcare databases in the basic sciences, social sciences, humanities, engineering, business, and defense: PsychINFO, BusinessSource Premier, Social Sciences Abstracts, Web of Science, and Defense Technical Information Center. Because our interest was in DS that could apply to clinical decisions, we selected articles that (1) provided a review, overview, discussion of lessons learned, or an evaluation of design or implementation aspects of DS within a non-healthcare discipline and (2) involved an element of human judgment at the individual level, as opposed to decisions that can be fully automated or that are made at the organizational level. Clinical decisions share some similarities with decisions made by military commanders, business managers, and other leaders: they involve assessing new situations and choosing courses of action with major consequences, under time pressure, and with incomplete information. We identified seven high-level DS system design features from the non-healthcare literature that could be applied to CDS: providing broad, system-level perspectives; customizing interfaces to specific users and roles; making the DS reasoning transparent; presenting data effectively; generating multiple scenarios covering disparate outcomes (e.g., effective; effective with side effects; ineffective); allowing for contingent adaptations; and facilitating collaboration. The article provides examples of

The role of analogy-guided learning experiences in enhancing students' clinical decision-making skills.

PubMed

Edelen, Bonnie Gilbert; Bell, Alexandra Alice

2011-08-01

The purpose of this study was to address the need for effective educational interventions to promote students' clinical decision making (CDM) within clinical practice environments. Researchers used a quasi-experimental, non-equivalent groups, posttest-only design to assess differences in CDM ability between intervention group students who participated in analogy-guided learning activities and control group students who participated in traditional activities. For the intervention, analogy-guided learning activities were incorporated into weekly group discussions, reflective journal writing, and questioning with clinical faculty. The researcher-designed Assessment of Clinical Decision Making Rubric was used to assess indicators of CDM ability in all students' reflective journal entries. Results indicated that the intervention group demonstrated significantly higher levels of CDM ability in their journals compared with the control group (ES(sm) = 0.52). Recommendations provide nurse educators with strategies to maximize students' development of CDM ability, better preparing students for the demands they face when they enter the profession. Copyright 2011, SLACK Incorporated.

Evaluating the value of a web-based natural medicine clinical decision tool at an academic medical center

PubMed Central

2011-01-01

Background Consumer use of herbal and natural products (H/NP) is increasing, yet physicians are often unprepared to provide guidance due to lack of educational training. This knowledge deficit may place consumers at risk of clinical complications. We wished to evaluate the impact that a natural medicine clinical decision tool has on faculty attitudes, practice experiences, and needs with respect to H/NP. Methods All physicians and clinical staff (nurse practitioners, physicians assistants) (n = 532) in departments of Pediatrics, Family and Community Medicine, and Internal Medicine at our medical center were invited to complete 2 electronic surveys. The first survey was completed immediately before access to a H/NP clinical-decision tool was obtained; the second survey was completed the following year. Results Responses were obtained from 89 of 532 practitioners (16.7%) on the first survey and 87 of 535 (16.3%) clinicians on the second survey. Attitudes towards H/NP varied with gender, age, time in practice, and training. At baseline, before having an evidence-based resource available, nearly half the respondents indicated that they rarely or never ask about H/NP when taking a patient medication history. The majority of these respondents (81%) indicated that they would like to learn more about H/NP, but 72% admitted difficulty finding evidence-based information. After implementing the H/NP tool, 63% of database-user respondents indicated that they now ask patients about H/NP when taking a drug history. Compared to results from the baseline survey, respondents who used the database indicated that the tool significantly increased their ability to find reliable H/NP information (P < 0.0001), boosted their knowledge of H/NP (p < 0.0001), and increased their confidence in providing accurate H/NP answers to patients and colleagues (P < 0.0001). Conclusions Our results demonstrate healthcare provider knowledge and confidence with H/NP can be improved without costly and

Constructing a clinical decision-making framework for image-guided radiotherapy using a Bayesian Network

NASA Astrophysics Data System (ADS)

Hargrave, C.; Moores, M.; Deegan, T.; Gibbs, A.; Poulsen, M.; Harden, F.; Mengersen, K.

2014-03-01

A decision-making framework for image-guided radiotherapy (IGRT) is being developed using a Bayesian Network (BN) to graphically describe, and probabilistically quantify, the many interacting factors that are involved in this complex clinical process. Outputs of the BN will provide decision-support for radiation therapists to assist them to make correct inferences relating to the likelihood of treatment delivery accuracy for a given image-guided set-up correction. The framework is being developed as a dynamic object-oriented BN, allowing for complex modelling with specific subregions, as well as representation of the sequential decision-making and belief updating associated with IGRT. A prototype graphic structure for the BN was developed by analysing IGRT practices at a local radiotherapy department and incorporating results obtained from a literature review. Clinical stakeholders reviewed the BN to validate its structure. The BN consists of a sub-network for evaluating the accuracy of IGRT practices and technology. The directed acyclic graph (DAG) contains nodes and directional arcs representing the causal relationship between the many interacting factors such as tumour site and its associated critical organs, technology and technique, and inter-user variability. The BN was extended to support on-line and off-line decision-making with respect to treatment plan compliance. Following conceptualisation of the framework, the BN will be quantified. It is anticipated that the finalised decision-making framework will provide a foundation to develop better decision-support strategies and automated correction algorithms for IGRT.

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).

Clinical decision-making: heuristics and cognitive biases for the ophthalmologist.

PubMed

Hussain, Ahsen; Oestreicher, James

Diagnostic errors have a significant impact on health care outcomes and patient care. The underlying causes and development of diagnostic error are complex with flaws in health care systems, as well as human error, playing a role. Cognitive biases and a failure of decision-making shortcuts (heuristics) are human factors that can compromise the diagnostic process. We describe these mechanisms, their role with the clinician, and provide clinical scenarios to highlight the various points at which biases may emerge. We discuss strategies to modify the development and influence of these processes and the vulnerability of heuristics to provide insight and improve clinical outcomes. Copyright © 2017 Elsevier Inc. All rights reserved.

Advancing beyond the system: telemedicine nurses' clinical reasoning using a computerised decision support system for patients with COPD - an ethnographic study.

PubMed

Barken, Tina Lien; Thygesen, Elin; Söderhamn, Ulrika

2017-12-28

Telemedicine is changing traditional nursing care, and entails nurses performing advanced and complex care within a new clinical environment, and monitoring patients at a distance. Telemedicine practice requires complex disease management, advocating that the nurses' reasoning and decision-making processes are supported. Computerised decision support systems are being used increasingly to assist reasoning and decision-making in different situations. However, little research has focused on the clinical reasoning of nurses using a computerised decision support system in a telemedicine setting. Therefore, the objective of the study is to explore the process of telemedicine nurses' clinical reasoning when using a computerised decision support system for the management of patients with chronic obstructive pulmonary disease. The factors influencing the reasoning and decision-making processes were investigated. In this ethnographic study, a combination of data collection methods, including participatory observations, the think-aloud technique, and a focus group interview was employed. Collected data were analysed using qualitative content analysis. When telemedicine nurses used a computerised decision support system for the management of patients with complex, unstable chronic obstructive pulmonary disease, two categories emerged: "the process of telemedicine nurses' reasoning to assess health change" and "the influence of the telemedicine setting on nurses' reasoning and decision-making processes". An overall theme, termed "advancing beyond the system", represented the connection between the reasoning processes and the telemedicine work and setting, where being familiar with the patient functioned as a foundation for the nurses' clinical reasoning process. In the telemedicine setting, when supported by a computerised decision support system, nurses' reasoning was enabled by the continuous flow of digital clinical data, regular video-mediated contact and shared decision

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

Nurse supervisors' actions in relation to their decision-making style and ethical approach to clinical supervision.

PubMed

Berggren, Ingela; Severinsson, Elisabeth

2003-03-01

The aim of the study was to explore the decision-making style and ethical approach of nurse supervisors by focusing on their priorities and interventions in the supervision process. Clinical supervision promotes ethical awareness and behaviour in the nursing profession. A focus group comprised of four clinical nurse supervisors with considerable experience was studied using qualitative hermeneutic content analysis. The essence of the nurse supervisors' decision-making style is deliberations and priorities. The nurse supervisors' willingness, preparedness, knowledge and awareness constitute and form their way of creating a relationship. The nurse supervisors' ethical approach focused on patient situations and ethical principles. The core components of nursing supervision interventions, as demonstrated in supervision sessions, are: guilt, reconciliation, integrity, responsibility, conscience and challenge. The nurse supervisors' interventions involved sharing knowledge and values with the supervisees and recognizing them as nurses and human beings. Nurse supervisors frequently reflected upon the ethical principle of autonomy and the concept and substance of integrity. The nurse supervisors used an ethical approach that focused on caring situations in order to enhance the provision of patient care. They acted as role models, shared nursing knowledge and ethical codes, and focused on patient related situations. This type of decision-making can strengthen the supervisees' professional identity. The clinical nurse supervisors in the study were experienced and used evaluation decisions as their form of clinical decision-making activity. The findings underline the need for further research and greater knowledge in order to improve the understanding of the ethical approach to supervision.

Decision-Making Process Related to Participation in Phase I Clinical Trials: A Nonsystematic Review of the Existing Evidence.

PubMed

Gorini, Alessandra; Mazzocco, Ketti; Pravettoni, Gabriella

2015-01-01

Due to the lack of other treatment options, patient candidates for participation in phase I clinical trials are considered the most vulnerable, and many ethical concerns have emerged regarding the informed consent process used in the experimental design of such trials. Starting with these considerations, this nonsystematic review is aimed at analyzing the decision-making processes underlying patients' decision about whether to participate (or not) in phase I trials in order to clarify the cognitive and emotional aspects most strongly implicated in this decision. Considering that there is no uniform decision calculus and that many different variables other than the patient-physician relationship (including demographic, clinical, and personal characteristics) may influence patients' preferences for and processing of information, we conclude that patients' informed decision-making can be facilitated by creating a rigorously developed, calibrated, and validated computer tool modeled on each single patient's knowledge, values, and emotional and cognitive decisional skills. Such a tool will also help oncologists to provide tailored medical information that is useful to improve the shared decision-making process, thereby possibly increasing patient participation in clinical trials. © 2015 S. Karger AG, Basel.

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.

Caregivers' experience of the decision-making process for placing a person with dementia into a nursing home: comparing caregivers from Chinese ethnic minority with those from English-speaking backgrounds.

PubMed

Caldwell, Lauren; Low, Lee-Fay; Brodaty, Henry

2014-03-01

The experience of care transitions for people with dementia from ethnic minority groups has been poorly researched. Few studies have examined the decision to put someone on a waiting list for a nursing home and then actually accept a place. Many nursing homes have long waiting lists, but sometimes offers of a place are declined. Our aims were to investigate the decision-making process for placing a person with dementia on a waiting list for a nursing home, why offers of a place are accepted or declined, and the influence of cultural factors, comparing caregivers from Chinese and English-speaking backgrounds. Semi-structured interviews with 27 caregivers of people with dementia on waiting lists or living in nursing homes (20 Chinese background and seven English-speaking background) were conducted, with thematic analysis of factors affecting caregivers' decision-making. Caregivers were at different stages of decision-making when they applied for a waiting list - some were ready for placement, others applied "just in case," and for some there was no waiting time because of an urgent need for placement. Caregivers' decisions were influenced by their emotions and expectations of nursing homes. The decision-making process was similar for both cultural groups, but Chinese caregivers spoke more about their sense of duty, the need for a Chinese specific facility, and declining a place because of family disagreement. Understanding cultural issues, including stereotypes and concerns about nursing homes, and providing better information about admission processes may help caregivers by allaying their anxiety about nursing home placement.

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

Depression and Anxiety During Pregnancy: Evaluating the Literature in Support of Clinical Risk-Benefit Decision-Making.

PubMed

Dalke, Katharine Baratz; Wenzel, Amy; Kim, Deborah R

2016-06-01

Depression and anxiety during pregnancy are common, and patients and providers are faced with complex decisions regarding various treatment modalities. A structured discussion of the risks and benefits of options with the patient and her support team is recommended to facilitate the decision-making process. This clinically focused review, with emphasis on the last 3 years of published study data, evaluates the major risk categories of medication treatments, namely pregnancy loss, physical malformations, growth impairment, behavioral teratogenicity, and neonatal toxicity. Nonpharmacological treatment options, including neuromodulation and psychotherapy, are also briefly reviewed. Specific recommendations, drawn from the literature and the authors' clinical experience, are also offered to help guide the clinician in decision-making.

A matter of life and death: controversy at the interface between clinical and legal decision-making in prolonged disorders of consciousness.

PubMed

Turner-Stokes, Lynne

2017-07-01

Best interests decision-making and end-of-life care for patients in permanent vegetative or minimally conscious states (VS/MCS) is a complex area of clinical and legal practice, which is poorly understood by most clinicians, lawyers and members of the public. In recent weeks, the Oxford Shrieval lecture by Mr Justice Baker ('A Matter of Life and Death', 11 October 2016) and its subsequent reporting in the public press has sparked debate on the respective roles of clinicians, the Court of Protection and the Mental Capacity Act 2005 in decisions to withhold or withdraw life-sustaining treatments from patients with disorders of consciousness. The debate became polarised and confused by misquotation and inaccurate terminology, and highlighted a lack of knowledge about how patients in VS/MCS die in the absence of court approval. This article sets out the background and discussion and attempts to give a more accurate representation of the facts. In the spirit of transparency, I present a mortality review of all the patients in VS/MCS who have died under the care of my own unit in the last decade-with or without referral to the court, but always in accordance with the law. These data demonstrate that clinicians regularly undertake best interests decision-making in conjunction with families that may include life and death decisions (sometimes even the withdrawal or withholding of clinically assisted nutrition and hydration); and that these can be made within the current legal framework without necessarily involving the court in all cases. This is the first published case series of its kind. 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/.

Agile Acceptance Test–Driven Development of Clinical Decision Support Advisories: Feasibility of Using Open Source Software

PubMed Central

Baldwin, Krystal L; Kannan, Vaishnavi; Flahaven, Emily L; Parks, Cassandra J; Ott, Jason M; Willett, Duwayne L

2018-01-01

Background Moving to electronic health records (EHRs) confers substantial benefits but risks unintended consequences. Modern EHRs consist of complex software code with extensive local configurability options, which can introduce defects. Defects in clinical decision support (CDS) tools are surprisingly common. Feasible approaches to prevent and detect defects in EHR configuration, including CDS tools, are needed. In complex software systems, use of test–driven development and automated regression testing promotes reliability. Test–driven development encourages modular, testable design and expanding regression test coverage. Automated regression test suites improve software quality, providing a “safety net” for future software modifications. Each automated acceptance test serves multiple purposes, as requirements (prior to build), acceptance testing (on completion of build), regression testing (once live), and “living” design documentation. Rapid-cycle development or “agile” methods are being successfully applied to CDS development. The agile practice of automated test–driven development is not widely adopted, perhaps because most EHR software code is vendor-developed. However, key CDS advisory configuration design decisions and rules stored in the EHR may prove amenable to automated testing as “executable requirements.” Objective We aimed to establish feasibility of acceptance test–driven development of clinical decision support advisories in a commonly used EHR, using an open source automated acceptance testing framework (FitNesse). Methods Acceptance tests were initially constructed as spreadsheet tables to facilitate clinical review. Each table specified one aspect of the CDS advisory’s expected behavior. Table contents were then imported into a test suite in FitNesse, which queried the EHR database to automate testing. Tests and corresponding CDS configuration were migrated together from the development environment to production, with

Sharing clinical decisions for multimorbidity case management using social network and open-source tools.

PubMed

Martínez-García, Alicia; Moreno-Conde, Alberto; Jódar-Sánchez, Francisco; Leal, Sandra; Parra, Carlos

2013-12-01

Social networks applied through Web 2.0 tools have gained importance in health domain, because they produce improvements on the communication and coordination capabilities among health professionals. This is highly relevant for multimorbidity patients care because there is a large number of health professionals in charge of patient care, and this requires to obtain clinical consensus in their decisions. Our objective is to develop a tool for collaborative work among health professionals for multimorbidity patient care. We describe the architecture to incorporate decision support functionalities in a social network tool to enable the adoption of shared decisions among health professionals from different care levels. As part of the first stage of the project, this paper describes the results obtained in a pilot study about acceptance and use of the social network component in our healthcare setting. At Virgen del Rocío University Hospital we have designed and developed the Shared Care Platform (SCP) to provide support in the continuity of care for multimorbidity patients. The SCP has two consecutively developed components: social network component, called Clinical Wall, and Clinical Decision Support (CDS) system. The Clinical Wall contains a record where health professionals are able to debate and define shared decisions. We conducted a pilot study to assess the use and acceptance of the SCP by healthcare professionals through questionnaire based on the theory of the Technology Acceptance Model. In March 2012 we released and deployed the SCP, but only with the social network component. The pilot project lasted 6 months in the hospital and 2 primary care centers. From March to September 2012 we created 16 records in the Clinical Wall, all with a high priority. A total of 10 professionals took part in the exchange of messages: 3 internists and 7 general practitioners generated 33 messages. 12 of the 16 record (75%) were answered by the destination health professionals

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

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

PubMed

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

2016-01-01

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

Clinically speaking: A communication skills program for students from non-English speaking backgrounds.

PubMed

Miguel, Caroline San; Rogan, Fran; Kilstoff, Kathleen; Brown, Di

2006-09-01

This paper reports on the design, delivery and evaluation of an innovative oral communication skills program for first year students in a Bachelor of Nursing degree at an Australian university. This program was introduced in 2004 to meet the needs of first year undergraduate students from non-English speaking backgrounds who had experienced difficulties with spoken English while on clinical placement. The program consisted of early identification of students in need of communication development, a series of classes incorporated into the degree program to address students' needs, followed by a clinical placement block. This paper describes the structure of the program, discusses some of the major problems encountered by students in the clinical setting and presents some of the teaching strategies used to address these problems. Evaluations of the program suggest that students' communication skills and confidence improved, resulting in a more positive clinical experience for the majority of students.

Computerized clinical decision support systems for chronic disease management: a decision-maker-researcher partnership systematic review.

PubMed

Roshanov, Pavel S; Misra, Shikha; Gerstein, Hertzel C; Garg, Amit X; Sebaldt, Rolf J; Mackay, Jean A; Weise-Kelly, Lorraine; Navarro, Tamara; Wilczynski, Nancy L; Haynes, R Brian

2011-08-03

The use of computerized clinical decision support systems (CCDSSs) may improve chronic disease management, which requires recurrent visits to multiple health professionals, ongoing disease and treatment monitoring, and patient behavior modification. The objective of this review was to determine if CCDSSs improve the processes of chronic care (such as diagnosis, treatment, and monitoring of disease) and associated patient outcomes (such as effects on biomarkers and clinical exacerbations). We conducted a decision-maker-researcher partnership systematic review. We searched MEDLINE, EMBASE, Ovid's EBM Reviews database, Inspec, and reference lists for potentially eligible articles published up to January 2010. We included randomized controlled trials that compared the use of CCDSSs to usual practice or non-CCDSS controls. Trials were eligible if at least one component of the CCDSS was designed to support chronic disease management. We considered studies 'positive' if they showed a statistically significant improvement in at least 50% of relevant outcomes. Of 55 included trials, 87% (n = 48) measured system impact on the process of care and 52% (n = 25) of those demonstrated statistically significant improvements. Sixty-five percent (36/55) of trials measured impact on, typically, non-major (surrogate) patient outcomes, and 31% (n = 11) of those demonstrated benefits. Factors of interest to decision makers, such as cost, user satisfaction, system interface and feature sets, unique design and deployment characteristics, and effects on user workflow were rarely investigated or reported. A small majority (just over half) of CCDSSs improved care processes in chronic disease management and some improved patient health. Policy makers, healthcare administrators, and practitioners should be aware that the evidence of CCDSS effectiveness is limited, especially with respect to the small number and size of studies measuring patient outcomes.

Studying the Vendor Perspective on Clinical Decision Support

PubMed Central

Ash, Joan S.; Sittig, Dean F.; McMullen, Carmit K.; McCormack, James L.; Wright, Adam; Bunce, Arwen; Wasserman, Joseph; Mohan, Vishnu; Cohen, Deborah J.; Shapiro, Michael; Middleton, Blackford

2011-01-01

In prior work, using a Rapid Assessment Process (RAP), we have investigated clinical decision support (CDS) in ambulatory clinics and hospitals. We realized that individuals in these settings provide only one perspective related to the CDS landscape, which also includes content vendors and electronic health record (EHR) vendors. To discover content vendors’ perspectives and their perceived challenges, we modified RAP for industrial settings. We describe how we employed RAP, and show its utility by describing two illustrative themes. We found that while the content vendors believe they provide unique much-needed services, the amount of labor involved in content development is underestimated by others. We also found that the content vendors believe their products are resources to be used by practitioners, so they are somewhat protected from liability issues. To promote adequate understanding about these issues, we recommend a “three way conversation” among content vendors, EHR vendors, and user organizations. PMID:22195058

Optimization of the decision-making process for the selection of therapeutics to undergo clinical testing for spinal cord injury in the North American Clinical Trials Network.

PubMed

Guest, James; Harrop, James S; Aarabi, Bizhan; Grossman, Robert G; Fawcett, James W; Fehlings, Michael G; Tator, Charles H

2012-09-01

The North American Clinical Trials Network (NACTN) includes 9 clinical centers funded by the US Department of Defense and the Christopher Reeve Paralysis Foundation. Its purpose is to accelerate clinical testing of promising therapeutics in spinal cord injury (SCI) through the development of a robust interactive infrastructure. This structure includes key committees that serve to provide longitudinal guidance to the Network. These committees include the Executive, Data Management, and Neurological Outcome Assessments Committees, and the Therapeutic Selection Committee (TSC), which is the subject of this manuscript. The NACTN brings unique elements to the SCI field. The Network's stability is not restricted to a single clinical trial. Network members have diverse expertise and include experts in clinical care, clinical trial design and methodology, pharmacology, preclinical and clinical research, and advanced rehabilitation techniques. Frequent systematic communication is assigned a high value, as is democratic process, fairness and efficiency of decision making, and resource allocation. This article focuses on how decision making occurs within the TSC to rank alternative therapeutics according to 2 main variables: quality of the preclinical data set, and fit with the Network's aims and capabilities. This selection process is important because if the Network's resources are committed to a therapeutic, alternatives cannot be pursued. A proposed methodology includes a multicriteria decision analysis that uses a Multi-Attribute Global Inference of Quality matrix to quantify the process. To rank therapeutics, the TSC uses a series of consensus steps designed to reduce individual and group bias and limit subjectivity. Given the difficulties encountered by industry in completing clinical trials in SCI, stable collaborative not-for-profit consortia, such as the NACTN, may be essential to clinical progress in SCI. The evolution of the NACTN also offers substantial

Implementation of clinical decision rules in the emergency department.

PubMed

Stiell, Ian G; Bennett, Carol

2007-11-01

Clinical decision rules (CDRs) are tools designed to help clinicians make bedside diagnostic and therapeutic decisions. The development of a CDR involves three stages: derivation, validation, and implementation. Several criteria need to be considered when designing and evaluating the results of an implementation trial. In this article, the authors review the results of implementation studies evaluating the effect of four CDRs: the Ottawa Ankle Rules, the Ottawa Knee Rule, the Canadian C-Spine Rule, and the Canadian CT Head Rule. Four implementation studies demonstrated that the implementation of CDRs in the emergency department (ED) safely reduced the use of radiography for ankle, knee, and cervical spine injuries. However, a recent trial failed to demonstrate an impact on computed tomography imaging rates. Well-developed and validated CDRs can be successfully implemented into practice, efficiently standardizing ED care. However, further research is needed to identify barriers to implementation in order to achieve improved uptake in the ED.

Reproductive Ethics in Commercial Surrogacy: Decision-Making in IVF Clinics in New Delhi, India.

PubMed

Tanderup, Malene; Reddy, Sunita; Patel, Tulsi; Nielsen, Birgitte Bruun

2015-09-01

As a neo-liberal economy, India has become one of the new health tourism destinations, with commercial gestational surrogacy as an expanding market. Yet the Indian Assisted Reproductive Technology (ART) Bill has been pending for five years, and the guidelines issued by the Indian Council of Medical Research are somewhat vague and contradictory, resulting in self-regulated practices of fertility clinics. This paper broadly looks at clinical ethics in reproduction in the practice of surrogacy and decision-making in various procedures. Through empirical research in New Delhi, the capital of India, from December 2011 to November 2012, issues of decision-making on embryo transfer, fetal reduction, and mode of delivery were identified. Interviews were carried out with doctors in eighteen ART clinics, agents from four agencies, and fourteen surrogates. In aiming to fulfil the commissioning parents' demands, doctors were willing to go to the greatest extent possible in their medical practice. Autonomy and decision-making regarding choice of the number of embryos to transfer and the mode of delivery lay neither with commissioning parents nor surrogate mothers but mostly with doctors. In order to ensure higher success rates, surrogates faced the risk of multiple pregnancy and fetal reduction with little information regarding the risks involved. In the globalized market of commercial surrogacy in India, and with clinics compromising on ethics, there is an urgent need for formulation of regulative law for the clinical practice and maintenance of principles of reproductive ethics in order to ensure that the interests of surrogate mothers are safeguarded.