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Sample records for clinical decision analysis

  1. The clinical decision analysis using decision tree

    PubMed Central

    Bae, Jong-Myon

    2014-01-01

    The clinical decision analysis (CDA) has used to overcome complexity and uncertainty in medical problems. The CDA is a tool allowing decision-makers to apply evidence-based medicine to make objective clinical decisions when faced with complex situations. The usefulness and limitation including six steps in conducting CDA were reviewed. The application of CDA results should be done under shared decision with patients’ value. PMID:25358466

  2. The clinical decision analysis using decision tree.

    PubMed

    Bae, Jong-Myon

    2014-01-01

    The clinical decision analysis (CDA) has used to overcome complexity and uncertainty in medical problems. The CDA is a tool allowing decision-makers to apply evidence-based medicine to make objective clinical decisions when faced with complex situations. The usefulness and limitation including six steps in conducting CDA were reviewed. The application of CDA results should be done under shared decision with patients' value.

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

    PubMed

    Gillespie, Mary

    2010-11-01

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

  4. Decision-theoretic refinement planning: a new method for clinical decision analysis.

    PubMed

    Doan, A; Haddawy, P; Kahn, C E

    1995-01-01

    Clinical decision analysis seeks to identify the optimal management strategy by modelling the uncertainty and risks entailed in the diagnosis, natural history, and treatment of a particular problem or disorder. Decision trees are the most frequently used model in clinical decision analysis, but can be tedious to construct, cumbersome to use, and computationally prohibitive, especially with large, complex decision problems. We present a new method for clinical decision analysis that combines the techniques of decision theory and artificial intelligence. Our model uses a modular representation of knowledge that simplifies model building and enables more fully automated decision making. Moreover, the model exploits problem structures to yield better computational efficiency. As an example we apply our techniques to the problem of management of acute deep venous thrombosis.

  5. Medical and nursing clinical decision making: a comparative epistemological analysis.

    PubMed

    Rashotte, Judy; Carnevale, F A

    2004-07-01

    The aim of this article is to explore the complex forms of knowledge involved in diagnostic and interventional decision making by comparing the processes in medicine and nursing, including nurse practitioners. Many authors assert that the practice of clinical decision making involves the application of theoretical knowledge (acquired in the classroom and textbooks) as well as research evidence, upon concrete particular cases. This approach draws on various universal principles and algorithms to facilitate the task. On the other hand, others argue that this involves an intuitive form of judgement that is difficult to teach, one that is acquired principally through experience. In an exploration of these issues, this article consists of three sections. A clarification of terms commonly used when discussing decision making is provided in the first section. In the second section, an epistemological analysis of decision making is presented by examining several perspectives and comparing them for their use in the nursing and medical literature. Bunge's epistemological framework for decision making (based on scientific realism) is explored for its fit with the aims of medicine and nursing. The final section presents a discussion of knowledge utilization and decision making as it relates to the implications for the education and ongoing development of nurse practitioners. It is concluded that Donald Schön's conception of reflective practice best characterizes the skillful conduct of clinical decision making.

  6. From decision to shared-decision: Introducing patients' preferences into clinical decision analysis.

    PubMed

    Sacchi, Lucia; Rubrichi, Stefania; Rognoni, Carla; Panzarasa, Silvia; Parimbelli, Enea; Mazzanti, Andrea; Napolitano, Carlo; Priori, Silvia G; Quaglini, Silvana

    2015-09-01

    Taking into account patients' preferences has become an essential requirement in health decision-making. Even in evidence-based settings where directions are summarized into clinical practice guidelines, there might exist situations where it is important for the care provider to involve the patient in the decision. In this paper we propose a unified framework to promote the shift from a traditional, physician-centered, clinical decision process to a more personalized, patient-oriented shared decision-making (SDM) environment. We present the theoretical, technological and architectural aspects of a framework that encapsulates decision models and instruments to elicit patients' preferences into a single tool, thus enabling physicians to exploit evidence-based medicine and shared decision-making in the same encounter. We show the implementation of the framework in a specific case study related to the prevention and management of the risk of thromboembolism in atrial fibrillation. We describe the underlying decision model and how this can be personalized according to patients' preferences. The application of the framework is tested through a pilot clinical evaluation study carried out on 20 patients at the Rehabilitation Cardiology Unit at the IRCCS Fondazione Salvatore Maugeri hospital (Pavia, Italy). The results point out the importance of running personalized decision models, which can substantially differ from models quantified with population coefficients. This study shows that the tool is potentially able to overcome some of the main barriers perceived by physicians in the adoption of SDM. In parallel, the development of the framework increases the involvement of patients in the process of care focusing on the centrality of individual patients. Copyright © 2014 Elsevier B.V. All rights reserved.

  7. Clinical decision support tools: analysis of online drug information databases

    PubMed Central

    Clauson, Kevin A; Marsh, Wallace A; Polen, Hyla H; Seamon, Matthew J; Ortiz, Blanca I

    2007-01-01

    Background Online drug information databases are used to assist in enhancing clinical decision support. However, the choice of which online database to consult, purchase or subscribe to is likely made based on subjective elements such as history of use, familiarity, or availability during professional training. The purpose of this study was to evaluate clinical decision support tools for drug information by systematically comparing the most commonly used online drug information databases. Methods Five commercially available and two freely available online drug information databases were evaluated according to scope (presence or absence of answer), completeness (the comprehensiveness of the answers), and ease of use. Additionally, a composite score integrating all three criteria was utilized. Fifteen weighted categories comprised of 158 questions were used to conduct the analysis. Descriptive statistics and Chi-square were used to summarize the evaluation components and make comparisons between databases. Scheffe's multiple comparison procedure was used to determine statistically different scope and completeness scores. The composite score was subjected to sensitivity analysis to investigate the effect of the choice of percentages for scope and completeness. Results The rankings for the databases from highest to lowest, based on composite scores were Clinical Pharmacology, Micromedex, Lexi-Comp Online, Facts & Comparisons 4.0, Epocrates Online Premium, RxList.com, and Epocrates Online Free. Differences in scope produced three statistical groupings with Group 1 (best) performers being: Clinical Pharmacology, Micromedex, Facts & Comparisons 4.0, Lexi-Comp Online, Group 2: Epocrates Premium and RxList.com and Group 3: Epocrates Free (p < 0.05). Completeness scores were similarly stratified. Collapsing the databases into two groups by access (subscription or free), showed the subscription databases performed better than the free databases in the measured criteria (p < 0

  8. Clinical decision support tools: analysis of online drug information databases.

    PubMed

    Clauson, Kevin A; Marsh, Wallace A; Polen, Hyla H; Seamon, Matthew J; Ortiz, Blanca I

    2007-03-08

    Online drug information databases are used to assist in enhancing clinical decision support. However, the choice of which online database to consult, purchase or subscribe to is likely made based on subjective elements such as history of use, familiarity, or availability during professional training. The purpose of this study was to evaluate clinical decision support tools for drug information by systematically comparing the most commonly used online drug information databases. Five commercially available and two freely available online drug information databases were evaluated according to scope (presence or absence of answer), completeness (the comprehensiveness of the answers), and ease of use. Additionally, a composite score integrating all three criteria was utilized. Fifteen weighted categories comprised of 158 questions were used to conduct the analysis. Descriptive statistics and Chi-square were used to summarize the evaluation components and make comparisons between databases. Scheffe's multiple comparison procedure was used to determine statistically different scope and completeness scores. The composite score was subjected to sensitivity analysis to investigate the effect of the choice of percentages for scope and completeness. The rankings for the databases from highest to lowest, based on composite scores were Clinical Pharmacology, Micromedex, Lexi-Comp Online, Facts & Comparisons 4.0, Epocrates Online Premium, RxList.com, and Epocrates Online Free. Differences in scope produced three statistical groupings with Group 1 (best) performers being: Clinical Pharmacology, Micromedex, Facts & Comparisons 4.0, Lexi-Comp Online, Group 2: Epocrates Premium and RxList.com and Group 3: Epocrates Free (p < 0.05). Completeness scores were similarly stratified. Collapsing the databases into two groups by access (subscription or free), showed the subscription databases performed better than the free databases in the measured criteria (p < 0.001). Online drug

  9. Clinical decision analysis using microcomputers. A case of coexistent hepatocellular carcinoma and abdominal aortic aneurysm.

    PubMed

    Wong, J B; Moskowitz, A J; Pauker, S G

    1986-12-01

    Many difficult medical decisions involve uncertainty. Decision analysis-an explicit, normative and analytic approach to making decisions under uncertainty-provides a probabilistic framework for exploring difficult problems in nondeterministic domains. As the methodology has advanced, clinical decision analysis has been applied to increasingly complex medical problems and disseminated widely in the medical literature. Unfortunately, this approach imposes a heavy computational burden on analysts. Microcomputer-based decision-support software can ease this burden.

  10. Decision analysis in anaesthesia: a tool for developing and analysing clinical management plans.

    PubMed

    Yentis, S M

    2006-07-01

    Traditional medical decision making is unstructured and incorporates evidence haphazardly. I present a more structured approach based on decision analysis, a model that considers all relevant options and outcomes informed by evidence where appropriate. This method is useful both for planning clinical management and for analysing decisions already taken.

  11. Clinical decision support foundations.

    PubMed

    Pradhan, Malcolm; Liaw, Siaw Teng

    2010-01-01

    This chapter gives an educational overview of: * The elements of a clinical decision; * The elements of decision making: prior probability, evidence (likelihood), posterior probability, actions, utility (value); * A framework for decision making, and support, encompassing validity, utility, importance and certainty; and * The required elements of a clinical decision support system. * The role of knowledge management in the construction and maintenance of clinical decision support.

  12. Clinical decision modeling system

    PubMed Central

    Shi, Haiwen; Lyons-Weiler, James

    2007-01-01

    Background Decision analysis techniques can be applied in complex situations involving uncertainty and the consideration of multiple objectives. Classical decision modeling techniques require elicitation of too many parameter estimates and their conditional (joint) probabilities, and have not therefore been applied to the problem of identifying high-performance, cost-effective combinations of clinical options for diagnosis or treatments where many of the objectives are unknown or even unspecified. Methods We designed a Java-based software resource, the Clinical Decision Modeling System (CDMS), to implement Naïve Decision Modeling, and provide a use case based on published performance evaluation measures of various strategies for breast and lung cancer detection. Because cost estimates for many of the newer methods are not yet available, we assume equal cost. Our use case reveals numerous potentially high-performance combinations of clinical options for the detection of breast and lung cancer. Results Naïve Decision Modeling is a highly practical applied strategy which guides investigators through the process of establishing evidence-based integrative translational clinical research priorities. CDMS is not designed for clinical decision support. Inputs include performance evaluation measures and costs of various clinical options. The software finds trees with expected emergent performance characteristics and average cost per patient that meet stated filtering criteria. Key to the utility of the software is sophisticated graphical elements, including a tree browser, a receiver-operator characteristic surface plot, and a histogram of expected average cost per patient. The analysis pinpoints the potentially most relevant pairs of clinical options ('critical pairs') for which empirical estimates of conditional dependence may be critical. The assumption of independence can be tested with retrospective studies prior to the initiation of clinical trials designed to

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

    SciTech Connect

    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.

  14. By-person factor analysis in clinical ethical decision making: Q methodology in end-of-life care decisions.

    PubMed

    Wong, William; Eiser, Arnold R; Mrtek, Robert G; Heckerling, Paul S

    2004-01-01

    To determine the usefulness of Q methodology to locate and describe shared subjective influences on clinical decision making among participant physicians using hypothetical cases containing common ethical issues. Qualitative study using by-person factor analysis of subjective Q sort data matrix. University medical center. Convenience sample of internal medicine attending physicians and house staff (n = 35) at one midwestern academic health sciences center. Presented with four hypothetical cases involving urgent decision making near the end of life, participants selected one of three specific clinical actions offered for each case. Immediately afterward and while considering their decision, each respondent sorted twenty-five subjective self-referent items in terms of the influence of each statement on their decision-making process. By-person factor analysis, where participants are defined as variates, yielded information about the attitudinal background the physicians brought to their consideration of each hypothetical case. We performed a second-order factor analysis on all of the subjective viewpoints to determine if a smaller core of shared attitudes existed across some or all of the four case vignettes. Factor scores for each item and post-sort comments from interviews conducted individually with each respondent guided the interpretation of ethical perspective used by these respondents in making clinical decisions about the cases. Second-order factor analysis on seventeen viewpoints used by physicians in the four hypothetical urgent decision cases revealed three moderately correlated (r2 < 40%) subjective core attitudinal guides used broadly among all the cases and among sixteen of the seventeen original factors. Across all the cases, our participants were guided in general by: (1) patient-focused beneficence, (2) a patient- and surrogate-focused perspective that includes risk avoidance, and (3) best interest of the patient guided by ethical values. Economic

  15. Quantitative ultrasound texture analysis for clinical decision making support

    NASA Astrophysics Data System (ADS)

    Wu, Jie Ying; Beland, Michael; Konrad, Joseph; Tuomi, Adam; Glidden, David; Grand, David; Merck, Derek

    2015-03-01

    We propose a general ultrasound (US) texture-analysis and machine-learning framework for detecting the presence of disease that is suitable for clinical application across clinicians, disease types, devices, and operators. Its stages are image selection, image filtering, ROI selection, feature parameterization, and classification. Each stage is modular and can be replaced with alternate methods. Thus, this framework is adaptable to a wide range of tasks. Our two preliminary clinical targets are hepatic steatosis and adenomyosis diagnosis. For steatosis, we collected US images from 288 patients and their pathology-determined values of steatosis (%) from biopsies. Two radiologists independently reviewed all images and identified the region of interest (ROI) most representative of the hepatic echotexture for each patient. To parameterize the images into comparable quantities, we filter the US images at multiple scales for various texture responses. For each response, we collect a histogram of pixel features within the ROI, and parameterize it as a Gaussian function using its mean, standard deviation, kurtosis, and skew to create a 36-feature vector. Our algorithm uses a support vector machine (SVM) for classification. Using a threshold of 10%, we achieved 72.81% overall accuracy, 76.18% sensitivity, and 65.96% specificity in identifying steatosis with leave-ten-out cross-validation (p<0.0001). Extending this framework to adenomyosis, we identified 38 patients with MR-confirmed findings of adenomyosis and previous US studies and 50 controls. A single rater picked the best US-image and ROI for each case. Using the same processing pipeline, we obtained 76.14% accuracy, 86.00% sensitivity, and 63.16% specificity with leave-one-out cross-validation (p<0.0001).

  16. Doctors' attitudes to risk in difficult clinical decisions: application of decision analysis in hepatobiliary disease.

    PubMed

    Theodossi, A; Spiegelhalter, D J; McFarlane, I G; Williams, R

    1984-07-28

    Twelve doctors with special training in hepatology independently reviewed two to five cases each from a group of seven cases of complicated hepatobiliary problems. A doctor's willingness to take risks to improve his patients' health was quantified by a wagering technique based on the probability of achieving a successful intervention. These probabilities were then used to calculate "utilities," which represented the average opinion of the doctors about the relative worth of each of six predefined states of health. The results showed that, in the context of risky decisions for severely ill patients, a year of life was considered by the doctors to be worth 44% of a full recovery; being mobile for that year increased this value to 57%. Survival for up to five years with restricted mobility was considered to be worth 70% of a full recovery and the ability to work during that period increased this value to 85%. It is concluded that in clinical decision making the uncertainty and preferences implicit in a course of action can be quantified and thus made explicit.

  17. Decision time for clinical decision support systems.

    PubMed

    O'Sullivan, Dympna; Fraccaro, Paolo; Carson, Ewart; Weller, Peter

    2014-08-01

    Clinical decision support systems are interactive software systems designed to help clinicians with decision-making tasks, such as determining a diagnosis or recommending a treatment for a patient. Clinical decision support systems are a widely researched topic in the computer science community, but their inner workings are less well understood by, and known to, clinicians. This article provides a brief explanation of clinical decision support systems and some examples of real-world systems. It also describes some of the challenges to implementing these systems in clinical environments and posits some reasons for the limited adoption of decision-support systems in practice. It aims to engage clinicians in the development of decision support systems that can meaningfully help with their decision-making tasks and to open a discussion about the future of automated clinical decision support as a part of healthcare delivery. © 2014 Royal College of Physicians.

  18. Clinical decision guidelines for NHS cosmetic surgery: analysis of current limitations and recommendations for future development.

    PubMed

    Cook, S A; Rosser, R; Meah, S; James, M I; Salmon, P

    2003-07-01

    Because of increasing demand for publicly funded elective cosmetic surgery, clinical decision guidelines have been developed to select those patients who should receive it. The aims of this study were to identify: the main characteristics of such guidelines; whether and how they influence clinical decision making; and ways in which they should be improved. UK health authorities were asked for their current guidelines for elective cosmetic surgery and, in a single plastic surgery unit, we examined the impact of its guidelines by observing consultations and interviewing surgeons and managers. Of 115 authorities approached, 32 reported using guidelines and provided sufficient information for analysis. Guidelines mostly concerned arbitrary sets of cosmetic procedures and lacked reference to an evidence base. They allowed surgery for specified anatomical, functional or symptomatic reasons, but these indications varied between guidelines. Most guidelines also permitted surgery 'exceptionally' for psychological reasons. The guidelines that were studied in detail did not appreciably influence surgeons' decisions, which reflected criteria that were not cited in the guidelines, including cost of the procedure and whether patients sought restoration or improvement of their appearance. Decision guidelines in this area have several limitations. Future guidelines should: include all cosmetic procedures; be informed by a broad range of evidence; and, arguably, include several nonclinical criteria that currently inform surgeons' decision-making.

  19. A meta-analysis of confidence and judgment accuracy in clinical decision making.

    PubMed

    Miller, Deborah J; Spengler, Elliot S; Spengler, Paul M

    2015-10-01

    The overconfidence bias occurs when clinicians overestimate the accuracy of their clinical judgments. This bias is thought to be robust leading to an almost universal recommendation by clinical judgment scholars for clinicians to temper their confidence in clinical decision making. An extension of the Meta-Analysis of Clinical Judgment (Spengler et al., 2009) project, the authors synthesized over 40 years of research from 36 studies, from 1970 to 2011, in which the confidence ratings of 1,485 clinicians were assessed in relation to the accuracy of their judgments about mental health (e.g., diagnostic decision making, violence risk assessment, prediction of treatment failure) or psychological issues (e.g., personality assessment). Using a random effects model a small but statistically significant effect (r = .15; CI = .06, .24) was found showing that confidence is better calibrated with accuracy than previously assumed. Approximately 50% of the total variance between studies was due to heterogeneity and not to chance. Mixed effects and meta-regression moderator analyses revealed that confidence is calibrated with accuracy least when there are repeated judgments, and more when there are higher base rate problems, when decisions are made with written materials, and for earlier published studies. Sensitivity analyses indicate a bias toward publishing smaller sample studies with smaller or negative confidence-accuracy effects. Implications for clinical judgment research and for counseling psychology training and practice are discussed.

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

    PubMed

    Michelson, James D

    2013-11-01

    The development of a robust treatment algorithm for ankle fractures based on well-established stability criteria has been shown to be prognostic with respect to treatment and outcomes. In parallel with the development of improved understanding of the biomechanical rationale of ankle fracture treatment has been an increased emphasis on assessing the effectiveness of medical and surgical interventions. The purpose of this study was to investigate the use of using decision analysis in the assessment of the cost effectiveness of operative treatment of ankle fractures based on the existing clinical data in the literature. Using the data obtained from a previous structured review of the ankle fracture literature, decision analysis trees were constructed using standard software. The decision nodes for the trees were based on ankle fracture stability criteria previously published. The outcomes were assessed by calculated Quality-Adjusted Life Years (QALYs) assigned to achieving normal ankle function, developing posttraumatic arthritis, or sustaining a postoperative infection. Sensitivity analysis was undertaken by varying the patient's age, incidence of arthritis, and incidence or infection. Decision analysis trees captured the essential aspects of clinical decision making in ankle fracture treatment in a clinically useful manner. In general, stable fractures yielded better outcomes with nonoperative treatment, whereas unstable fractures had better outcomes with surgery. These were consistent results over a wide range of postoperative infection rates. Varying the age of the patient did not qualitatively change the results. Between the ages of 30 and 80 years, surgery yielded higher expected QALYs than nonoperative care for unstable fractures, and generated lower QALYs than nonoperative care for stable fractures. Using local cost estimates for operative and nonoperative treatment, the incremental cost of surgery for unstable fractures was less than $40,000 per QALY (the

  1. 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

  2. Prospective decision analysis modeling indicates that clinical decisions in vascular surgery often fail to maximize patient expected utility.

    PubMed

    Brothers, Thomas E; Cox, Montgomery H; Robison, Jacob G; Elliott, Bruce M; Nietert, Paul

    2004-08-01

    Applied prospectively to patients with peripheral arterial disease, individualized decision analysis has the potential to improve the surgeon's ability to optimize patient outcome. A prospective, randomized trial comparing Markov surgical decision analysis to standard decision-making was performed in 206 patients with symptomatic lower extremity arterial disease. Utility assessment and quality of life were determined from individual patients prior to treatment. Vascular surgeons provided estimates of probability of treatment outcome, intended and actual treatment plans, and assessment of comfort with the decision (PDPI). Treatment plans and PDPI evaluations were repeated after each surgeon was made aware of model predictions for half of the patients in a randomized manner. Optimal treatments predicted by decision analysis differed significantly from the surgeon's initial plan and consisted of bypass for 30 versus 29%, respectively, angioplasty for 28 versus 11%, amputation for 31 versus 6%, and medical management for 34 versus 54% (agreement 50%, kappa 0.28). Surgeon awareness of the decision model results did not alter the verbalized final plan, but did trend toward less frequent use of bypass. Patients for whom the model agreed with the surgeon's initial plan were less likely to undergo bypass (13 versus 30%, P < 0.01). Greater surgeon comfort was present when the initial plan and model agreed (PDPI score 47.5 versus 45.6, P < 0.005). Individualized application of a decision model to patients with peripheral arterial disease suggests that arterial bypass is frequently recommended even when it may not maximize patient expected utility.

  3. Analysis of Community Practice Clinical Decision-Making Skills in Pharmacy Students.

    ERIC Educational Resources Information Center

    Greer, Marianne L.; Kirk, Kenneth W.

    1988-01-01

    A computerized, simulation-based instrument, consisting of four community practice clinical scenarios, collected information-searching data and the students' decisions. The appropriateness of the decisions, assessed by three clinical judges, and the focus of information search, based on the computer-collected process data, were the dependent…

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

    PubMed

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

    2016-01-01

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

  5. Should TIA patients be hospitalized or referred to a same-day clinic?: a decision analysis.

    PubMed

    Joshi, Jay K; Ouyang, Bichun; Prabhakaran, Shyam

    2011-12-13

    For patients presenting with TIA, a previous study concluded that hospitalization is cost-effective compared to discharge without treatment from the emergency department. We performed a cost-effectiveness analysis of hospitalization vs urgent clinic evaluation following TIA. Among a cohort of TIA patients, we created a decision tree model to compare the decision to hospitalize or refer to urgent-access specialty clinic. We estimated probabilities, utilities, and direct costs from the available literature and calculated incremental cost-effectiveness ratio (ICER). We assumed equal access to standard medical treatments between the 2 approaches; however, we estimated higher tissue plasminogen activator (tPA) utilization among hospitalized patients. We performed sensitivity analyses to assess all assumptions in our model. In patients with TIA aged 65-74 years, hospitalization yielded additional 0.00026 quality-adjusted life-years (QALYs) at 1 year, but at an additional cost of $5,573 per patient compared to urgent clinic evaluation (ICER = $21,434,615/QALY). Over 30 years, the ICER was $3,473,125/QALY. These results were not sensitive to varying 48-hour stroke risk, length of stay, tPA utilization rate, QALYs saved per tPA treatment, and hospitalization and clinic costs, and cost saved per tPA treatment. Despite increased access to tPA in the hospital, we found that hospitalization is not cost-effective compared to same-day clinic evaluation following TIA. A very small fraction of patients benefits from hospitalization if urgent-access TIA clinics are available. The widespread development of urgent-access TIA clinics is warranted.

  6. Can computerized clinical decision support systems improve diabetes management? A systematic review and meta-analysis.

    PubMed

    Jeffery, R; Iserman, E; Haynes, R B

    2013-06-01

    To systematically review randomized trials that assessed the effects of computerized clinical decision support systems in ambulatory diabetes management compared with a non-computerized clinical decision support system control. We included all diabetes trials from a comprehensive computerized clinical decision support system overview completed in January 2010, and searched EMBASE, MEDLINE, INSPEC/COMPENDEX and Evidence-Based Medicine Reviews (EBMR) from January 2010 to April 2012. Reference lists of related reviews, included articles and Clinicaltrials.gov were also searched. Randomized controlled trials of patients with diabetes in ambulatory care settings comparing a computerized clinical decision support system intervention with a non-computerized clinical decision support system control, measuring either a process of care or a patient outcome, were included. Screening of studies, data extraction, risk of bias and quality of evidence assessments were carried out independently by two reviewers, and discrepancies were resolved through consensus or third-party arbitration. Authors were contacted for any missing data. Fifteen trials were included (13 from the previous review and two from the current search). Only one study was at low risk of bias, while the others were of moderate to high risk of bias because of methodological limitations. HbA1c (3 months' follow-up), quality of life and hospitalization (12 months' follow-up) were pooled and all favoured the computerized clinical decision support systems over the control, although none were statistically significant. Triglycerides and practitioner performance tended to favour computerized clinical decision support systems although results were too heterogeneous to pool. Computerized clinical decision support systems in diabetes management may marginally improve clinical outcomes, but confidence in the evidence is low because of risk of bias, inconsistency and imprecision. © 2012 The Authors. Diabetic Medicine

  7. Mechanical versus clinical data combination in selection and admissions decisions: a meta-analysis.

    PubMed

    Kuncel, Nathan R; Klieger, David M; Connelly, Brian S; Ones, Deniz S

    2013-11-01

    In employee selection and academic admission decisions, holistic (clinical) data combination methods continue to be relied upon and preferred by practitioners in our field. This meta-analysis examined and compared the relative predictive power of mechanical methods versus holistic methods in predicting multiple work (advancement, supervisory ratings of performance, and training performance) and academic (grade point average) criteria. There was consistent and substantial loss of validity when data were combined holistically-even by experts who are knowledgeable about the jobs and organizations in question-across multiple criteria in work and academic settings. In predicting job performance, the difference between the validity of mechanical and holistic data combination methods translated into an improvement in prediction of more than 50%. Implications for evidence-based practice are discussed. (c) 2013 APA, all rights reserved.

  8. How clinical decisions are made.

    PubMed

    Bate, Louise; Hutchinson, Andrew; Underhill, Jonathan; Maskrey, Neal

    2012-10-01

    There is much variation in the implementation of the best available evidence into clinical practice. These gaps between evidence and practice are often a result of multiple individual decisions. When making a decision, there is so much potentially relevant information available, it is impossible to know or process it all (so called 'bounded rationality'). Usually, a limited amount of information is selected to reach a sufficiently satisfactory decision, a process known as satisficing. There are two key processes used in decision making: System 1 and System 2. System 1 involves fast, intuitive decisions; System 2 is a deliberate analytical approach, used to locate information which is not instantly recalled. Human beings unconsciously use System 1 processing whenever possible because it is quicker and requires less effort than System 2. In clinical practice, gaps between evidence and practice can occur when a clinician develops a pattern of knowledge, which is then relied on for decisions using System 1 processing, without the activation of a System 2 check against the best available evidence from high quality research. The processing of information and decision making may be influenced by a number of cognitive biases, of which the decision maker may be unaware. Interventions to encourage appropriate use of System 1 and System 2 processing have been shown to improve clinical decision making. Increased understanding of decision making processes and common sources of error should help clinical decision makers to minimize avoidable mistakes and increase the proportion of decisions that are better.

  9. Net clinical benefit of oral anticoagulants: a multiple criteria decision analysis.

    PubMed

    Hsu, Jason C; Hsieh, Cheng-Yang; Yang, Yea-Huei Kao; Lu, Christine Y

    2015-01-01

    This study quantitatively evaluated the comparative efficacy and safety of new oral anticoagulants (dabigatran, rivaroxaban, and apizaban) and warfarin for treatment of nonvalvular atrial fibrillation. We also compared these agents under different scenarios, including population with high risk of stroke and for primary vs. secondary stroke prevention. We used multiple criteria decision analysis (MCDA) to assess the benefit-risk of these medications. Our MCDA models contained criteria for benefits (prevention of ischemic stroke and systemic embolism) and risks (intracranial and extracranial bleeding). We calculated a performance score for each drug accounting for benefits and risks in comparison to treatment alternatives. Overall, new agents had higher performance scores than warfarin; in order of performance scores: dabigatran 150 mg (0.529), rivaroxaban (0.462), apixaban (0.426), and warfarin (0.191). For patients at a higher risk of stroke (CHADS2 score≥3), apixaban had the highest performance score (0.686); performance scores for other drugs were 0.462 for dabigatran 150 mg, 0.392 for dabigatran 110 mg, 0.271 for rivaroxaban, and 0.116 for warfarin. Dabigatran 150 mg had the highest performance score for primary stroke prevention, while dabigatran 110 mg had the highest performance score for secondary prevention. Our results suggest that new oral anticoagulants might be preferred over warfarin. Selecting appropriate medicines according to the patient's condition based on information from an integrated benefit-risk assessment of treatment options is crucial to achieve optimal clinical outcomes.

  10. Clinical judgment and decision making.

    PubMed

    Garb, Howard N

    2005-01-01

    When clinical psychologists make judgments, are they likely to be correct or incorrect? The following topics are reviewed: (a) methodological advances in evaluating the validity of descriptions of personality and psychopathology, (b) recent findings on the cognitive processes of clinicians, and (c) the validity of judgments and utility of decisions made by mental health professionals. Results from research on clinical judgment and decision making and their relationship to conflicts within the field of clinical psychology are discussed.

  11. Amatoxin poisoning treatment decision-making: pharmaco-therapeutic clinical strategy assessment using multidimensional multivariate statistic analysis.

    PubMed

    Poucheret, Patrick; Fons, Françoise; Doré, Jean Christophe; Michelot, Didier; Rapior, Sylvie

    2010-06-15

    Ninety percent of fatal higher fungus poisoning is due to amatoxin-containing mushroom species. In addition to absence of antidote, no chemotherapeutic consensus was reported. The aim of the present study is to perform a retrospective multidimensional multivariate statistic analysis of 2110 amatoxin poisoning clinical cases, in order to optimize therapeutic decision-making. Our results allowed to classify drugs as a function of their influence on one major parameter: patient survival. Active principles were classified as first intention, second intention, adjuvant or controversial pharmaco-therapeutic clinical intervention. We conclude that (1) retrospective multidimensional multivariate statistic analysis of complex clinical dataset might help future therapeutic decision-making and (2) drugs such as silybin, N-acetylcystein and putatively ceftazidime are clearly associated, in amatoxin poisoning context, with higher level of patient survival.

  12. Quantitative imaging biomarkers: the application of advanced image processing and analysis to clinical and preclinical decision making.

    PubMed

    Prescott, Jeffrey William

    2013-02-01

    The importance of medical imaging for clinical decision making has been steadily increasing over the last four decades. Recently, there has also been an emphasis on medical imaging for preclinical decision making, i.e., for use in pharamaceutical and medical device development. There is also a drive towards quantification of imaging findings by using quantitative imaging biomarkers, which can improve sensitivity, specificity, accuracy and reproducibility of imaged characteristics used for diagnostic and therapeutic decisions. An important component of the discovery, characterization, validation and application of quantitative imaging biomarkers is the extraction of information and meaning from images through image processing and subsequent analysis. However, many advanced image processing and analysis methods are not applied directly to questions of clinical interest, i.e., for diagnostic and therapeutic decision making, which is a consideration that should be closely linked to the development of such algorithms. This article is meant to address these concerns. First, quantitative imaging biomarkers are introduced by providing definitions and concepts. Then, potential applications of advanced image processing and analysis to areas of quantitative imaging biomarker research are described; specifically, research into osteoarthritis (OA), Alzheimer's disease (AD) and cancer is presented. Then, challenges in quantitative imaging biomarker research are discussed. Finally, a conceptual framework for integrating clinical and preclinical considerations into the development of quantitative imaging biomarkers and their computer-assisted methods of extraction is presented.

  13. Net Clinical Benefit of Oral Anticoagulants: A Multiple Criteria Decision Analysis

    PubMed Central

    Yang, Yea-Huei Kao; Lu, Christine Y.

    2015-01-01

    Background This study quantitatively evaluated the comparative efficacy and safety of new oral anticoagulants (dabigatran, rivaroxaban, and apizaban) and warfarin for treatment of nonvalvular atrial fibrillation. We also compared these agents under different scenarios, including population with high risk of stroke and for primary vs. secondary stroke prevention. Methods We used multiple criteria decision analysis (MCDA) to assess the benefit-risk of these medications. Our MCDA models contained criteria for benefits (prevention of ischemic stroke and systemic embolism) and risks (intracranial and extracranial bleeding). We calculated a performance score for each drug accounting for benefits and risks in comparison to treatment alternatives. Results Overall, new agents had higher performance scores than warfarin; in order of performance scores: dabigatran 150 mg (0.529), rivaroxaban (0.462), apixaban (0.426), and warfarin (0.191). For patients at a higher risk of stroke (CHADS2 score≥3), apixaban had the highest performance score (0.686); performance scores for other drugs were 0.462 for dabigatran 150 mg, 0.392 for dabigatran 110 mg, 0.271 for rivaroxaban, and 0.116 for warfarin. Dabigatran 150 mg had the highest performance score for primary stroke prevention, while dabigatran 110 mg had the highest performance score for secondary prevention. Conclusions Our results suggest that new oral anticoagulants might be preferred over warfarin. Selecting appropriate medicines according to the patient’s condition based on information from an integrated benefit-risk assessment of treatment options is crucial to achieve optimal clinical outcomes. PMID:25897861

  14. Referral of surgical patients to an anaesthetic clinic: a decision-making analysis.

    PubMed

    Lee, A; Lum, M E; Hillman, K M; Bauman, A

    1994-10-01

    Effective utilization of an anaesthetic clinic depends on appropriate referral of high-risk surgical patients. The decision-making behaviour of anaesthetists and nurses was examined to identify factors that influence the referral of patients to an outpatient anaesthetic clinic. Eleven consultant anaesthetists, seven anaesthetic trainees and sixteen nurses working in anaesthetic areas estimated the likelihood that they would refer patients for each of the 30 scenarios presented. The relative importance of each factor influencing the decision to refer as determined by the 34 participants were: type of procedure (22%), co-morbidities (18%), fitness (13%), history of anaesthetic problems (12%), medications (11%), age (10%), obesity (8%) and anxiety (6%). Indicative risk factors identified were aged 65 years or over, unable to climb more than two flights of stairs, presence of significant medical problems, gross obesity, history of anaesthetic problems, taking regular medications, scheduled for major surgery and expressed anxiety about the anaesthetic. There were large variations in the decision-making behaviour among health professional groups.

  15. Diagnostic Accuracy of Clinical Decision Rules to Exclude Fractures in Acute Ankle Injuries: Systematic Review and Meta-analysis.

    PubMed

    Barelds, Ingrid; Krijnen, Wim P; van de Leur, Johannes P; van der Schans, Cees P; Goddard, Robert J

    2017-07-29

    Ankle decision rules are developed to expedite patient care and reduce the number of radiographs of the ankle and foot. Currently, only three systematic reviews have been conducted on the accuracy of the Ottawa Ankle and Foot Rules (OAFR) in adults and children. However, no systematic review has been performed to determine the most accurate ankle decision rule. The purpose of this study is to examine which clinical decision rules are the most accurate for excluding ankle fracture after acute ankle trauma. A systematic search was conducted in the databases PubMed, CINAHL, PEDro, ScienceDirect, and EMBASE. The sensitivity, specificity, likelihood ratios, and diagnostic odds ratio of the included studies were calculated. A meta-analysis was conducted if the accuracy of a decision rule was available from at least three different experimental studies. Eighteen studies satisfied the inclusion criteria. These included six ankle decision rules, specifically, the Ottawa Ankle Rules, Tuning Fork Test, Low Risk Ankle Rule, Malleolar and Midfoot Zone Algorithms, and the Bernese Ankle Rules. Meta-analysis of the Ottawa Ankle Rules (OAR), OAFR, Bernese Ankle Rules, and the Malleolar Zone Algorithm resulted in a negative likelihood ratio of 0.12, 0.14, 0.39, and 0.23, respectively. The OAR and OAFR are the most accurate decision rules for excluding fractures in the event of an acute ankle injury. Copyright © 2017 Elsevier Inc. All rights reserved.

  16. GPS Decision Analysis Process

    DTIC Science & Technology

    2005-06-23

    712 A/B: GPS Decision Analysis Process Revised title:___________________________________________________________________ Presented in (input and Bold...JUN 2005 2. REPORT TYPE N/A 3. DATES COVERED - 4. TITLE AND SUBTITLE GPS Decision Analysis Process 5a. CONTRACT NUMBER 5b. GRANT NUMBER...Prescribed by ANSI Std Z39-18 GPS Decision Analysis Process Nisha Shah The Boeing Company 73rd MORS Symposium US Military Academy – West Point 21-23

  17. Colon trauma--clinical staging for surgical decision making. Analysis of 119 cases.

    PubMed

    Morgado, P J; Alfaro, R; Morgado, P J; León, P

    1992-10-01

    A retrospective study is presented of 119 patients admitted to the Central Hospital of the Venezuelan Institute of Social Security, in Caracas, between 1982 and 1990, with the diagnosis of colon trauma. Several parameters including age, etiology, time elapsed between the accident or assault and hospital admission, preoperative and postoperative hemoglobin and diastolic blood pressure, associated lesions, procedure practiced, complication rate, and hospital mortality are reviewed. The second and third decades of life appear most often involved. Most patients reached the hospital within the first four hours of the accident or assault. Anemia, sustained diastolic hypotension, and number of organs involved in addition to the colon were important prognostic factors for complications. Apparently the surgical procedure, with simple suture or resection, mostly without "protective" colostomy, was not very relevant. Hospital mortality was 2.4 percent. A staging system based on clinical conditions for decision making in the operating room was used in an attempt to inject some objectivity into the surgical approach.

  18. Bayesian decision sequential analysis with survival endpoint in phase II clinical trials.

    PubMed

    Zhao, Lili; Woodworth, George

    2009-04-30

    Chen and Chaloner (Statist. Med. 2006; 25:2956-2966. DOI: 10.1002/sim.2429) present a Bayesian stopping rule for a single-arm clinical trial with a binary endpoint. In some cases, earlier stopping may be possible by basing the stopping rule on the time to a binary event. We investigate the feasibility of computing exact, Bayesian, decision-theoretic time-to-event stopping rules for a single-arm group sequential non-inferiority trial relative to an objective performance criterion. For a conjugate prior distribution, exponential failure time distribution, and linear and threshold loss structures, we obtain the optimal Bayes stopping rule by backward induction. We compute frequentist operating characteristics of including Type I error, statistical power, and expected run length. We also briefly address design issues.

  19. Prevalence of clinically significant decisional conflict: an analysis of five studies on decision-making in primary care

    PubMed Central

    Thompson-Leduc, Philippe; Turcotte, Stéphane; Labrecque, Michel; Légaré, France

    2016-01-01

    Objectives Unresolved clinically significant decisional conflict (CSDC) in patients following a consultation with health professionals is often the result of inadequate patient involvement in decision-making and may result in poor outcomes. We sought to identify the prevalence of CSDC in studies on decision-making in primary care and to explore its risk factors. Setting We performed a secondary analysis of existing data sets from studies conducted in Primary Care Practice-Based Research Networks in Québec and Ontario, Canada. Participants Eligible studies included a patient-reported measure on the 16-item Decisional Conflict Scale (DCS) following a decision made with a healthcare professional with no study design restriction. Primary and secondary outcome measures CSDC was defined as a score ≥25/100 on the DCS. The prevalence of CSDC was stratified by sex; and patient-level logistic regression analysis was performed to explore its potential risk factors. Data sets of studies were analysed individually and qualitatively compared. Results 5 projects conducted between 2003 and 2010 were included. They covered a range of decisions: prenatal genetic screening, antibiotics for acute respiratory infections and miscellaneous. Altogether, the 5 projects gathered data from encounters with a total of 1338 primary care patients (69% female; range of age 15–83). The prevalence of CSDC in patients varied across studies and ranged from 10.3% (95% CI 7.2% to 13.4%) to 31.1% (95% CI 26.6% to 35.6%). Across the 5 studies, risk factors of CSDC included being male, living alone and being 45 or older. Conclusions Prevalence of CSDC in patients who had enrolled in studies conducted in primary care contexts was substantial and appeared to vary according to the type of decision as well as to patient characteristics such as sex, living arrangement and age. Patients presenting risk factors of CSDC should be offered tools to increase their involvement in decision-making. PMID:27354076

  20. “Do Not Resuscitate” Decisions in Acute Respiratory Distress Syndrome. A Secondary Analysis of Clinical Trial Data

    PubMed Central

    Wiener, Renda Soylemez; Walkey, Allan J.

    2014-01-01

    Rationale: Factors and outcomes associated with end-of-life decision-making among patients during clinical trials in the intensive care unit are unclear. Objectives: We sought to determine patterns and outcomes of Do Not Resuscitate (DNR) decisions among critically ill patients with acute respiratory distress syndrome (ARDS) enrolled in a clinical trial. Methods: We performed a secondary analysis of data from the ARDS Network Fluid and Catheter Treatment Trial (FACTT), collected between 2000 and 2005. We calculated mortality outcomes stratified by code status, and compared baseline characteristics of patients who became DNR during the trial with participants who remained full code. Measurements and Main Results: Among 809 FACTT participants with a code status recorded, 232 (28.7%) elected DNR status. Specifically, 37 (15.9%) chose to withhold cardiopulmonary resuscitation alone, 44 (19.0%) elected to withhold some life support measures in addition to cardiopulmonary resuscitation, and 151 (65.1%) had life support withdrawn. Admission severity of illness as measured by APACHE III score was strongly associated with election of DNR status (odds ratio, 2.2; 95% confidence interval, 1.85–2.62; P < 0.0001). Almost all (97.0%; 225 of 232) patients who selected DNR status died, and 79% (225 of 284) of patients who died during the trial were DNR. Among patients who chose DNR status but did not elect withdrawal of life support, 91% (74 of 81) died. Conclusions: The vast majority of deaths among clinical trial patients with ARDS were preceded by a DNR order. Unlike other studies of end-of-life decision-making in the intensive care unit, nearly all patients who became DNR died. The impact of variation of practice in end-of-life decision-making during clinical trials warrants further study. PMID:25386717

  1. 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

  2. Recommendations for Standardizing Glucose Reporting and Analysis to Optimize Clinical Decision Making in Diabetes: The Ambulatory Glucose Profile

    PubMed Central

    Bergenstal, Richard M.; Ahmann, Andrew J.; Bailey, Timothy; Beck, Roy W.; Bissen, Joan; Buckingham, Bruce; Deeb, Larry; Dolin, Robert H.; Garg, Satish K.; Goland, Robin; Hirsch, Irl B.; Klonoff, David C.; Kruger, Davida F.; Matfin, Glenn; Mazze, Roger S.; Olson, Beth A.; Parkin, Christopher; Peters, Anne; Powers, Margaret A.; Rodriguez, Henry; Southerland, Phil; Strock, Ellie S.; Tamborlane, William; Wesley, David M.

    2013-01-01

    Underutilization of glucose data and lack of easy and standardized glucose data collection, analysis, visualization, and guided clinical decision making are key contributors to poor glycemic control among individuals with type 1 diabetes mellitus. An expert panel of diabetes specialists, facilitated by the International Diabetes Center and sponsored by the Helmsley Charitable Trust, met in 2012 to discuss recommendations for standardizing the analysis and presentation of glucose monitoring data, with the initial focus on data derived from continuous glucose monitoring systems. The panel members were introduced to a universal software report, the Ambulatory Glucose Profile, and asked to provide feedback on its content and functionality, both as a research tool and in clinical settings. This article provides a summary of the topics and issues discussed during the meeting and presents recommendations from the expert panel regarding the need to standardize glucose profile summary metrics and the value of a uniform glucose report to aid clinicians, researchers, and patients. PMID:23567014

  3. Decision-tree analysis of clinical data to aid diagnostic reasoning for equine laminitis: a cross-sectional study.

    PubMed

    Wylie, C E; Shaw, D J; Verheyen, K L P; Newton, J R

    2016-04-23

    The objective of this cross-sectional study was to compare the prevalence of selected clinical signs in laminitis cases and non-laminitic but lame controls to evaluate their capability to discriminate laminitis from other causes of lameness. Participating veterinary practitioners completed a checklist of laminitis-associated clinical signs identified by literature review. Cases were defined as horses/ponies with veterinary-diagnosed, clinically apparent laminitis; controls were horses/ponies with any lameness other than laminitis. Associations were tested by logistic regression with adjusted odds ratios (ORs) and 95% confidence intervals, with veterinary practice as an a priori fixed effect. Multivariable analysis using graphical classification tree-based statistical models linked laminitis prevalence with specific combinations of clinical signs. Data were collected for 588 cases and 201 controls. Five clinical signs had a difference in prevalence of greater than +50 per cent: 'reluctance to walk' (OR 4.4), 'short, stilted gait at walk' (OR 9.4), 'difficulty turning' (OR 16.9), 'shifting weight' (OR 17.7) and 'increased digital pulse' (OR 13.2) (all P<0.001). 'Bilateral forelimb lameness' was the best discriminator; 92 per cent of animals with this clinical sign had laminitis (OR 40.5, P<0.001). If, in addition, horses/ponies had an 'increased digital pulse', 99 per cent were identified as laminitis. 'Presence of a flat/convex sole' also significantly enhanced clinical diagnosis discrimination (OR 15.5, P<0.001). This is the first epidemiological laminitis study to use decision-tree analysis, providing the first evidence base for evaluating clinical signs to differentially diagnose laminitis from other causes of lameness. Improved evaluation of the clinical signs displayed by laminitic animals examined by first-opinion practitioners will lead to equine welfare improvements.

  4. The impact of physician burnout on clinical and academic productivity of gynecologic oncologists: A decision analysis.

    PubMed

    Turner, Taylor B; Dilley, Sarah E; Smith, Haller J; Huh, Warner K; Modesitt, Susan C; Rose, Stephen L; Rice, Laurel W; Fowler, Jeffrey M; Straughn, J Michael

    2017-09-01

    Physician burnout is associated with mental illness, alcohol abuse, and job dissatisfaction. Our objective was to estimate the impact of burnout on productivity of gynecologic oncologists during the first half of their career. A decision model evaluated the impact of burnout on total relative value (RVU) production during the first 15years of practice for gynecologic oncologists entering the workforce from 2011 to 2015. The SGO practice survey provided physician demographics and mean annual RVUs. Published data were used to estimate probability of burnout for male and female gynecologic oncologists, and the impact of depression, alcohol abuse, and early retirement. Academic productivity was defined as annual PubMed publications since finishing fellowship. Without burnout, RVU production for the cohort of 250 gynecologic oncologists was 26.2 million (M) RVUs over 15years. With burnout, RVU production decreased by 1.6 M (5.9% decrease). Disproportionate rates of burnout among females resulted in 1.1 M lost RVUs for females vs. 488 K for males. Academic production without burnout was estimated at 9277 publications for the cohort. Burnout resulted in 1383 estimated fewer publications over 15years (14.9%). The impact of burnout on clinical and academic productivity is substantial across all specialties. As health care systems struggle with human resource shortages, this study highlights the need for effective burnout prevention and wellness programs for gynecologic oncologists. Unless significant resources are designated to wellness programs, burnout will increasingly affect the care of our patients and the advancement of our field. Copyright © 2017 Elsevier Inc. All rights reserved.

  5. Two approaches to incorporate clinical data uncertainty into multiple criteria decision analysis for benefit-risk assessment of medicinal products.

    PubMed

    Wen, Shihua; Zhang, Lanju; Yang, Bo

    2014-07-01

    The Problem formulation, Objectives, Alternatives, Consequences, Trade-offs, Uncertainties, Risk attitude, and Linked decisions (PrOACT-URL) framework and multiple criteria decision analysis (MCDA) have been recommended by the European Medicines Agency for structured benefit-risk assessment of medicinal products undergoing regulatory review. The objective of this article was to provide solutions to incorporate the uncertainty from clinical data into the MCDA model when evaluating the overall benefit-risk profiles among different treatment options. Two statistical approaches, the δ-method approach and the Monte-Carlo approach, were proposed to construct the confidence interval of the overall benefit-risk score from the MCDA model as well as other probabilistic measures for comparing the benefit-risk profiles between treatment options. Both approaches can incorporate the correlation structure between clinical parameters (criteria) in the MCDA model and are straightforward to implement. The two proposed approaches were applied to a case study to evaluate the benefit-risk profile of an add-on therapy for rheumatoid arthritis (drug X) relative to placebo. It demonstrated a straightforward way to quantify the impact of the uncertainty from clinical data to the benefit-risk assessment and enabled statistical inference on evaluating the overall benefit-risk profiles among different treatment options. The δ-method approach provides a closed form to quantify the variability of the overall benefit-risk score in the MCDA model, whereas the Monte-Carlo approach is more computationally intensive but can yield its true sampling distribution for statistical inference. The obtained confidence intervals and other probabilistic measures from the two approaches enhance the benefit-risk decision making of medicinal products. Copyright © 2014 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

  6. Does gait analysis change clinical decision-making in poststroke patients? Results from a pragmatic prospective observational study.

    PubMed

    Ferrarin, M; Rabuffetti, M; Bacchini, M; Casiraghi, A; Castagna, A; Pizzi, A; Montesano, A

    2015-04-01

    Gait analysis (GA) was demonstrated to change presurgical planning and improve gait outcomes in children with Cerebral Palsy. GA is often used also to assess walking capability of poststroke subjects, although its influence in the clinical management of these patients has not yet been established. To assess the impact of GA on clinical decision-making in adult chronic poststroke patients. Pragmatic prospective observational study. Rehabilitation hospital, both outpatients and inpatients. Forty-nine patients (age: 53.3±14.5 years) who had had a cerebrovascular accident 35.2±26.4 months before and were referred to the gait analysis service. Recommendations of therapeutic treatments before and after the analysis of GA data were compared, together with the confidence level of recommendations on a 10-point scale. Frequency of changes of post-GA vs pre-GA recommendations were computed for each recommendation type: surgery, botulinum toxin (BT), orthotic management and physiotherapy. Based on the analysis of GA data, 71% of poststroke subjects had their treatment planning changed in some components. Indeed, 73% of patients with indications for surgery had their surgical planning changed; 81%, 37% and 32% had, respectively, their BT, orthotic and physiotherapy planning changed. Confidence level of recommendations increased significantly after GA, in both the whole group of patients (from 6.7±1.4 to 8.7±0.6, P<0.01) and the subgroup whose recommendations had not changed (7.0±1.5 vs. 8.8±0.4, P<0.01). GA significantly influences the therapeutic planning and reinforces decision-making for chronic poststroke patients. Further work should be done to better translate GA results into indications for specific physiotherapy. The use of GA as a tool to better define the rehabilitation planning in post-stroke patients should be fostered, particularly when surgery or botulinum toxin are considered and/or the prescription of orthoses is hypothesised.

  7. Entrustment Decision Making in Clinical Training.

    PubMed

    Ten Cate, Olle; Hart, Danielle; Ankel, Felix; Busari, Jamiu; Englander, Robert; Glasgow, Nicholas; Holmboe, Eric; Iobst, William; Lovell, Elise; Snell, Linda S; Touchie, Claire; Van Melle, Elaine; Wycliffe-Jones, Keith

    2016-02-01

    The decision to trust a medical trainee with the critical responsibility to care for a patient is fundamental to clinical training. When carefully and deliberately made, such decisions can serve as significant stimuli for learning and also shape the assessment of trainees. Holding back entrustment decisions too much may hamper the trainee's development toward unsupervised practice. When carelessly made, however, they jeopardize patient safety. Entrustment decision-making processes, therefore, deserve careful analysis.Members (including the authors) of the International Competency-Based Medical Education Collaborative conducted a content analysis of the entrustment decision-making process in health care training during a two-day summit in September 2013 and subsequently reviewed the pertinent literature to arrive at a description of the critical features of this process, which informs this article.The authors discuss theoretical backgrounds and terminology of trust and entrustment in the clinical workplace. The competency-based movement and the introduction of entrustable professional activities force educators to rethink the grounds for assessment in the workplace. Anticipating a decision to grant autonomy at a designated level of supervision appears to align better with health care practice than do most current assessment practices. The authors distinguish different modes of trust and entrustment decisions and elaborate five categories, each with related factors, that determine when decisions to trust trainees are made: the trainee, supervisor, situation, task, and the relationship between trainee and supervisor. The authors' aim in this article is to lay a theoretical foundation for a new approach to workplace training and assessment.

  8. Stochastic decision analysis

    NASA Technical Reports Server (NTRS)

    Lacksonen, Thomas A.

    1994-01-01

    Small space flight project design at NASA Langley Research Center goes through a multi-phase process from preliminary analysis to flight operations. The process insures that each system achieves its technical objectives with demonstrated quality and within planned budgets and schedules. A key technical component of early phases is decision analysis, which is a structure procedure for determining the best of a number of feasible concepts based upon project objectives. Feasible system concepts are generated by the designers and analyzed for schedule, cost, risk, and technical measures. Each performance measure value is normalized between the best and worst values and a weighted average score of all measures is calculated for each concept. The concept(s) with the highest scores are retained, while others are eliminated from further analysis. This project automated and enhanced the decision analysis process. Automation of the decision analysis process was done by creating a user-friendly, menu-driven, spreadsheet macro based decision analysis software program. The program contains data entry dialog boxes, automated data and output report generation, and automated output chart generation. The enhancements to the decision analysis process permit stochastic data entry and analysis. Rather than enter single measure values, the designers enter the range and most likely value for each measure and concept. The data can be entered at the system or subsystem level. System level data can be calculated as either sum, maximum, or product functions of the subsystem data. For each concept, the probability distributions are approximated for each measure and the total score for each concept as either constant, triangular, normal, or log-normal distributions. Based on these distributions, formulas are derived for the probability that the concept meets any given constraint, the probability that the concept meets all constraints, and the probability that the concept is within a given

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

    PubMed

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

    2015-07-01

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

  10. Potential Cost-Effectiveness of a New Infant Tuberculosis Vaccine in South Africa - Implications for Clinical Trials: A Decision Analysis

    PubMed Central

    Ditkowsky, Jared B.; Schwartzman, Kevin

    2014-01-01

    Novel tuberculosis vaccines are in varying stages of pre-clinical and clinical development. This study seeks to estimate the potential cost-effectiveness of a BCG booster vaccine, while accounting for costs of large-scale clinical trials, using the MVA85A vaccine as a case study for estimating potential costs. We conducted a decision analysis from the societal perspective, using a 10-year time frame and a 3% discount rate. We predicted active tuberculosis cases and tuberculosis-related costs for a hypothetical cohort of 960,763 South African newborns (total born in 2009). We compared neonatal vaccination with bacille Calmette-Guérin alone to vaccination with bacille Calmette-Guérin plus a booster vaccine at 4 months. We considered booster efficacy estimates ranging from 40% to 70%, relative to bacille Calmette-Guérin alone. We accounted for the costs of Phase III clinical trials. The booster vaccine was assumed to prevent progression to active tuberculosis after childhood infection, with protection decreasing linearly over 10 years. Trial costs were prorated to South Africa's global share of bacille Calmette-Guérin vaccination. Vaccination with bacille Calmette-Guérin alone resulted in estimated tuberculosis-related costs of $89.91 million 2012 USD, and 13,610 tuberculosis cases in the birth cohort, over the 10 years. Addition of the booster resulted in estimated cost savings of $7.69–$16.68 million USD, and 2,800–4,160 cases averted, for assumed efficacy values ranging from 40%–70%. A booster tuberculosis vaccine in infancy may result in net societal cost savings as well as fewer active tuberculosis cases, even if efficacy is relatively modest and large scale Phase III studies are required. PMID:24454706

  11. Transforming user needs into functional requirements for an antibiotic clinical decision support system: explicating content analysis for system design.

    PubMed

    Bright, T J

    2013-01-01

    Many informatics studies use content analysis to generate functional requirements for system development. Explication of this translational process from qualitative data to functional requirements can strengthen the understanding and scientific rigor when applying content analysis in informatics studies. To describe a user-centered approach transforming emergent themes derived from focus group data into functional requirements for informatics solutions and to illustrate these methods to the development of an antibiotic clinical decision support system (CDS). THE APPROACH CONSISTED OF FIVE STEPS: 1) identify unmet therapeutic planning information needs via Focus Group Study-I, 2) develop a coding framework of therapeutic planning themes to refine the domain scope to antibiotic therapeutic planning, 3) identify functional requirements of an antibiotic CDS system via Focus Group Study-II, 4) discover informatics solutions and functional requirements from coded data, and 5) determine the types of information needed to support the antibiotic CDS system and link with the identified informatics solutions and functional requirements. The coding framework for Focus Group Study-I revealed unmet therapeutic planning needs. Twelve subthemes emerged and were clustered into four themes; analysis indicated a need for an antibiotic CDS intervention. Focus Group Study-II included five types of information needs. Comments from the Barrier/Challenge to information access and Function/Feature themes produced three informatics solutions and 13 functional requirements of an antibiotic CDS system. Comments from the Patient, Institution, and Domain themes generated required data elements for each informatics solution. This study presents one example explicating content analysis of focus group data and the analysis process to functional requirements from narrative data. Illustration of this 5-step method was used to develop an antibiotic CDS system, resolving unmet antibiotic prescribing

  12. Genetic Analysis of Arrhythmogenic Diseases in the Era of NGS: The Complexity of Clinical Decision-Making in Brugada Syndrome

    PubMed Central

    Allegue, Catarina; Coll, Mònica; Mates, Jesus; Campuzano, Oscar; Iglesias, Anna; Sobrino, Beatriz; Brion, Maria; Amigo, Jorge; Carracedo, Angel; Brugada, Pedro; Brugada, Josep; Brugada, Ramon

    2015-01-01

    Background The use of next-generation sequencing enables a rapid analysis of many genes associated with sudden cardiac death in diseases like Brugada Syndrome. Genetic variation is identified and associated with 30–35% of cases of Brugada Syndrome, with nearly 20–25% attributable to variants in SCN5A, meaning many cases remain undiagnosed genetically. To evaluate the role of genetic variants in arrhythmogenic diseases and the utility of next-generation sequencing, we applied this technology to resequence 28 main genes associated with arrhythmogenic disorders. Materials and Methods A cohort of 45 clinically diagnosed Brugada Syndrome patients classified as SCN5A-negative was analyzed using next generation sequencing. Twenty-eight genes were resequenced: AKAP9, ANK2, CACNA1C, CACNB2, CASQ2, CAV3, DSC2, DSG2, DSP, GPD1L, HCN4, JUP, KCNE1, KCNE2, KCNE3, KCNH2, KCNJ2, KCNJ5, KCNQ1, NOS1AP, PKP2, RYR2, SCN1B, SCN3B, SCN4B, SCN5A, SNTA1, and TMEM43. A total of 85 clinically evaluated relatives were also genetically analyzed to ascertain familial segregation. Results and Discussion Twenty-two patients carried 30 rare genetic variants in 12 genes, only 4 of which were previously associated with Brugada Syndrome. Neither insertion/deletion nor copy number variation were detected. We identified genetic variants in novel candidate genes potentially associated to Brugada Syndrome. These include: 4 genetic variations in AKAP9 including a de novo genetic variation in 3 positive cases; 5 genetic variations in ANK2 detected in 4 cases; variations in KCNJ2 together with CASQ2 in 1 case; genetic variations in RYR2, including a de novo genetic variation and desmosomal proteins encoding genes including DSG2, DSP and JUP, detected in 3 of the cases. Larger gene panels or whole exome sequencing should be considered to identify novel genes associated to Brugada Syndrome. However, application of approaches such as whole exome sequencing would difficult the interpretation for clinical

  13. Does CT-based Rigidity Analysis Influence Clinical Decision-making in Simulations of Metastatic Bone Disease?

    PubMed

    Nazarian, Ara; Entezari, Vahid; Villa-Camacho, Juan C; Zurakowski, David; Katz, Jeffrey N; Hochman, Mary; Baldini, Elizabeth H; Vartanians, Vartan; Rosen, Max P; Gebhardt, Mark C; Terek, Richard M; Damron, Timothy A; Yaszemski, Michael J; Snyder, Brian D

    2016-03-01

    There is a need to improve the prediction of fracture risk for patients with metastatic bone disease. CT-based rigidity analysis (CTRA) is a sensitive and specific method, yet its influence on clinical decision-making has never been quantified. What is the influence of CTRA on providers' perceived risk of fracture? (2) What is the influence of CTRA on providers' treatment recommendations in simulated clinical scenarios of metastatic bone disease of the femur? (3) Does CTRA improve interobserver agreement regarding treatment recommendations? We conducted a survey among 80 academic physicians (orthopaedic oncologists, musculoskeletal radiologists, and radiation oncologists) using simulated vignettes of femoral lesions presented as three separate scenarios: (1) no CTRA input (baseline); (2) CTRA input suggesting increased risk of fracture (CTRA+); and (3) CTRA input suggesting decreased risk of fracture (CTRA-). Participants were asked to rate the patient's risk of fracture on a scale of 0% to 100% and to provide a treatment recommendation. Overall response rate was 62.5% (50 of 80). When CTRA suggested an increased risk of fracture, physicians perceived the fracture risk to be slightly greater (37% ± 3% versus 42% ± 3%, p < 0.001; mean difference [95% confidence interval {CI}] = 5% [4.7%-5.2%]) and were more prone to recommend surgical stabilization (46% ± 9% versus 54% ± 9%, p < 0.001; mean difference [95% CI] = 9% [7.9-10.1]). When CTRA suggested a decreased risk of fracture, physicians perceived the risk to be slightly decreased (37% ± 25% versus 35% ± 25%, p = 0.04; mean difference [95% CI] = 2% [2.74%-2.26%]) and were less prone to recommend surgical stabilization (46% ± 9% versus 42% ± 9%, p < 0.03; mean difference [95% CI] = 4% [3.9-5.1]). The effect size of the influence of CTRA on physicians' perception of fracture risk and treatment planning varied with lesion severity and specialty of the responders. CTRA did not increase interobserver agreement

  14. Clinical Decision Support and Palivizumab

    PubMed Central

    Hogan, A.; Michel, J.; Localio, A.R.; Karavite, D.; Song, L.; Ramos, M.J.; Fiks, A.G.; Lorch, S.; Grundmeier, R.W.

    2015-01-01

    Background and Objectives Palivizumab can reduce hospitalizations due to respiratory syncytial virus (RSV), but many eligible infants fail to receive the full 5-dose series. The efficacy of clinical decision support (CDS) in fostering palivizumab receipt has not been studied. We sought a comprehensive solution for identifying eligible patients and addressing barriers to palivizumab administration. Methods We developed workflow and CDS tools targeting patient identification and palivizumab administration. We randomized 10 practices to receive palivizumab-focused CDS and 10 to receive comprehensive CDS for premature infants in a 3-year longitudinal cluster-randomized trial with 2 baseline and 1 intervention RSV seasons. Results There were 356 children eligible to receive palivizumab, with 194 in the palivizumab-focused group and 162 in the comprehensive CDS group. The proportion of doses administered to children in the palivizumab-focused intervention group increased from 68.4% and 65.5% in the two baseline seasons to 84.7% in the intervention season. In the comprehensive intervention group, proportions of doses administered declined during the baseline seasons (from 71.9% to 62.4%) with partial recovery to 67.9% during the intervention season. The palivizumab-focused group improved by 19.2 percentage points in the intervention season compared to the prior baseline season (p < 0.001), while the comprehensive intervention group only improved 5.5 percentage points (p = 0.288). The difference in change between study groups was significant (p = 0.05). Conclusions Workflow and CDS tools integrated in an EHR may increase the administration of palivizumab. The support focused on palivizumab, rather than comprehensive intervention, was more effective at improving palivizumab administration. PMID:26767069

  15. ClinicalAccess: a clinical decision support tool.

    PubMed

    Crowell, Karen; Vardell, Emily

    2015-01-01

    ClinicalAccess is a new clinical decision support tool that uses a question-and-answer format to mirror clinical decision-making strategies. The unique format of ClinicalAccess delivers concise, authoritative answers to more than 120,000 clinical questions. This column presents a review of the product, a sample search, and a comparison with other point-of-care search engines.

  16. Decision analysis in restorative dentistry.

    PubMed

    Anusavice, K J

    1992-12-01

    Standardization of clinical decisions in restorative dentistry should be based on the tenets of the Hippocratic Oath. Although there is wide variability in preventive and operative treatment decisions, some of these decisions may lead along parallel courses to similar, clinically ethical outcomes. However, what parameters must be considered in judging the relative magnitude of positive and negative outcomes? This paper proposes several decision-making strategies for selecting optimum treatment plans for preventive and restorative situations. The caries-risk level of patients must first be identified in a systematic way and then it must be coupled with treatment options that are consistent with the potential future caries increment. A decision-tree approach and/or the treatment-index concept can then be applied to specific clinical conditions and preventive-restorative options to derive an "expected value" for each possible outcome.

  17. 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…

  18. 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…

  19. Informing the design of clinical decision support services for evaluation of children with minor blunt head trauma in the emergency department: a sociotechnical analysis.

    PubMed

    Sheehan, Barbara; Nigrovic, Lise E; Dayan, Peter S; Kuppermann, Nathan; Ballard, Dustin W; Alessandrini, Evaline; Bajaj, Lalit; Goldberg, Howard; Hoffman, Jeffrey; Offerman, Steven R; Mark, Dustin G; Swietlik, Marguerite; Tham, Eric; Tzimenatos, Leah; Vinson, David R; Jones, Grant S; Bakken, Suzanne

    2013-10-01

    Integration of clinical decision support services (CDSS) into electronic health records (EHRs) may be integral to widespread dissemination and use of clinical prediction rules in the emergency department (ED). However, the best way to design such services to maximize their usefulness in such a complex setting is poorly understood. We conducted a multi-site cross-sectional qualitative study whose aim was to describe the sociotechnical environment in the ED to inform the design of a CDSS intervention to implement the Pediatric Emergency Care Applied Research Network (PECARN) clinical prediction rules for children with minor blunt head trauma. Informed by a sociotechnical model consisting of eight dimensions, we conducted focus groups, individual interviews and workflow observations in 11 EDs, of which 5 were located in academic medical centers and 6 were in community hospitals. A total of 126 ED clinicians, information technology specialists, and administrators participated. We clustered data into 19 categories of sociotechnical factors through a process of thematic analysis and subsequently organized the categories into a sociotechnical matrix consisting of three high-level sociotechnical dimensions (workflow and communication, organizational factors, human factors) and three themes (interdisciplinary assessment processes, clinical practices related to prediction rules, EHR as a decision support tool). Design challenges that emerged from the analysis included the need to use structured data fields to support data capture and re-use while maintaining efficient care processes, supporting interdisciplinary communication, and facilitating family-clinician interaction for decision-making. Copyright © 2013 Elsevier Inc. All rights reserved.

  20. A shotgun wedding: business decision support meets clinical decision support.

    PubMed

    Oliveira, Jason

    2002-01-01

    By effectively closing the loop between the data, analytics, processes, and methods supporting business and clinical decision making, a healthcare organization closes the loop between its knowledge generation activities and its actions at the bedside: knowledge guiding actions, actions generating knowledge.

  1. Clinical decision-making in senior nursing students in Iran.

    PubMed

    Jahanpour, Faezeh; Sharif, Farkhondeh; Salsali, Mahvash; Kaveh, Mohammad H; Williams, Leonie M

    2010-12-01

    Clinical decision-making is the basis for professional nursing practice. This can be taught and learned through appropriate teaching and clinical experiences. Unfortunately, it has been observed that many graduates are unable to demonstrate suitable clinical decision-making skills. Research and study on the process of decision-making and factors influencing it assists educators to find the appropriate educational and clinical strategies to teach nursing students. To explore the experience of nursing students and their view points regarding the factors influencing their development of clinical decision-making skills. An exploratory qualitative approach utilizing grounded theory methods was used; focus group interviews were undertaken with 32 fourth year nursing students and data were analysed using constant comparative analysis. Four main themes emerged from the data: clinical instructor incompetency, low self-efficacy, unconducive clinical learning climate and experiencing stress. The data indicated that students could not make clinical decisions independently. The findings of this study support the need to reform aspects of the curriculum in Iran in order to increase theory-practice integration and prepare a conductive clinical learning climate that enhances learning clinical decision-making with less stress.

  2. Family patterns of decision-making in pediatric clinical trials.

    PubMed

    Snethen, Julia A; Broome, Marion E; Knafl, Kathleen; Deatrick, Janet A; Angst, Denise B

    2006-06-01

    The decision-making process related to a child's participation in clinical trials often involves multiple family members. The aim of this study was to compare family patterns of decision-making within and across family units in pediatric clinical trials. Participants for this secondary analysis included 14 families from a larger study of informed consent. Four distinct patterns of decision-making were identified: Exclusionary, informative, collaborative, and delegated. These patterns varied with regard to three dimensions of parents' decision-making goals, child level of involvement, and the parental role. These patterns of decision-making affect how parents and children communicate with health professionals and influence the effectiveness of health care providers interactions with the family related to the decision-making process.

  3. “How are patient characteristics relevant for physicians' clinical decision making in diabetes?: An analysis of qualitative results from a cross-national factorial experiment”

    PubMed Central

    Campbell, Stephen M; Renfrew, Megan R; Marceau, Lisa D; Roland, Martin; McKinlay, John B

    2008-01-01

    Variations in medical practice have been widely documented and are a linchpin in explanations of health disparities. Evidence shows that clinical decision making varies according to patient, provider and health system characteristics. However, less is known about the processes underlying these aggregate associations and how physicians interpret various patient attributes. Verbal protocol analysis (otherwise known as ‘think-aloud’) techniques were used to analyze open-ended data from 244 physicians to examine which patient characteristics physicians identify as relevant for their decision making. Data are from a vignette-based factorial experiment measuring the effects of: (a) patient attributes (age, gender, race and socioeconomic status); (b) physician characteristics (gender and years of clinical experience); and (c) features of the healthcare system in two countries (USA, United Kingdom) on clinical decision making for diabetes. We find that physicians used patients’ demographic characteristics only as a starting point in their assessments, and proceeded to make detailed assessments about cognitive ability, motivation, social support and other factors they consider predictive of adherence with medical recommendations and therefore relevant to treatment decisions. These non-medical characteristics of patients were mentioned with much greater consistency than traditional biophysiologic markers of risk such as race, gender, and age. Types of explanations identified varied somewhat according to patient characteristics and to the country in which the interview took place. Results show that basic demographic characteristics are inadequate to the task of capturing information physicians draw from doctor-patient encounters, and that in order to fully understand differential clinical decision making there is a need to move beyond documentation of aggregate associations and further explore the mental and social processes at work. PMID:18703267

  4. A multimedia electronic patient record (ePR) system to improve decision support in pre- and rehabilitation through clinical and movement analysis

    NASA Astrophysics Data System (ADS)

    Liu, Brent; Documet, Jorge; McNitt-Gray, Sarah; Requejo, Phil; McNitt-Gray, Jill

    2011-03-01

    Clinical decisions for improving motor function in patients both with disability as well as improving an athlete's performance are made through clinical and movement analysis. Currently, this analysis facilitates identifying abnormalities in a patient's motor function for a large amount of neuro-musculoskeletal pathologies. However definitively identifying the underlying cause or long-term consequences of a specific abnormality in the patient's movement pattern is difficult since this requires information from multiple sources and formats across different times and currently relies on the experience and intuition of the expert clinician. In addition, this data must be persistent for longitudinal outcomes studies. Therefore a multimedia ePR system integrating imaging informatics data could have a significant impact on decision support within this clinical workflow. We present the design and architecture of such an ePR system as well as the data types that need integration in order to develop relevant decision support tools. Specifically, we will present two data model examples: 1) A performance improvement project involving volleyball athletes and 2) Wheelchair propulsion evaluation of patients with disabilities. The end result is a new frontier area of imaging informatics research within rehabilitation engineering and biomechanics.

  5. Evaluation of Nursing Documentation Completion of Stroke Patients in the Emergency Department: A Pre-Post Analysis Using Flowsheet Templates and Clinical Decision Support.

    PubMed

    Richardson, Karen J; Sengstack, Patricia; Doucette, Jeffrey N; Hammond, William E; Schertz, Matthew; Thompson, Julie; Johnson, Constance

    2016-02-01

    The primary aim of this performance improvement project was to determine whether the electronic health record implementation of stroke-specific nursing documentation flowsheet templates and clinical decision support alerts improved the nursing documentation of eligible stroke patients in seven stroke-certified emergency departments. Two system enhancements were introduced into the electronic record in an effort to improve nursing documentation: disease-specific documentation flowsheets and clinical decision support alerts. Using a pre-post design, project measures included six stroke management goals as defined by the National Institute of Neurological Disorders and Stroke and three clinical decision support measures based on entry of orders used to trigger documentation reminders for nursing: (1) the National Institutes of Health's Stroke Scale, (2) neurological checks, and (3) dysphagia screening. Data were reviewed 6 months prior (n = 2293) and 6 months following the intervention (n = 2588). Fisher exact test was used for statistical analysis. Statistical significance was found for documentation of five of the six stroke management goals, although effect sizes were small. Customizing flowsheets to meet the needs of nursing workflow showed improvement in the completion of documentation. The effects of the decision support alerts on the completeness of nursing documentation were not statistically significant (likely due to lack of order entry). For example, an order for the National Institutes of Health Stroke Scale was entered only 10.7% of the time, which meant no alert would fire for nursing in the postintervention group. Future work should focus on decision support alerts that trigger reminders for clinicians to place relevant orders for this population.

  6. Nurses' decision-making in ethically relevant clinical situations using the example of breathlessness: study protocol of a reflexive grounded theory integrating Goffman's framework analysis

    PubMed Central

    Dunger, Christine; Schnell, Martin W; Bausewein, Claudia

    2017-01-01

    Introduction Decision-making (DM) in healthcare can be understood as an interactive process addressing decision makers' reasoning as well as their visible behaviour after the decision is made. Other key elements of DM are ethical aspects and the role as well as the treatment options of the examined professions. Nurses' DM to choose interventions in situations of severe breathlessness is such interactions. They are also ethically relevant regarding the vulnerability of affected patients and possible restrictions or treatment options. The study aims to explore which factors influence nurses' DM to use nursing interventions in situations where patients suffer from severe breathlessness. Methods and analysis Qualitative study including nurses in German hospital wards and hospices. A triangulation of different methods of data collection—participant observation and qualitative expert interviews—and analysis merge in a reflexive grounded theory approach which integrates Goffman's framework analysis. It allows an analysis of nurses' self-statements about DM, their behaviour in relevant clinical situations and its influences. Data collection and analysis will be examined simultaneously. Ethics and dissemination Informed consent will be gained from all participants and the institutional stakeholders. Ongoing consent has to be ensured since observations will take place in healthcare institutions and many patients will be highly vulnerable. The study has been evaluated and approved by the Witten/Herdecke University Ethics Committee, Witten, Germany. Results of the study will be published at congresses and in journal papers. PMID:28399508

  7. Use Of Clinical Decision Analysis In Predicting The Efficacy Of Newer Radiological Imaging Modalities: Radioscintigraphy Versus Single Photon Transverse Section Emission Computed Tomography

    NASA Astrophysics Data System (ADS)

    Prince, John R.

    1982-12-01

    Sensitivity, specificity, and predictive accuracy have been shown to be useful measures of the clinical efficacy of diagnostic tests and can be used to predict the potential improvement in diagnostic certitude resulting from the introduction of a competing technology. This communication demonstrates how the informal use of clinical decision analysis may guide health planners in the allocation of resources, purchasing decisions, and implementation of high technology. For didactic purposes the focus is on a comparison between conventional planar radioscintigraphy (RS) and single photon transverse section emission conputed tomography (SPECT). For example, positive predictive accuracy (PPA) for brain RS in a specialist hospital with a 50% disease prevalance is about 95%. SPECT should increase this predicted accuracy to 96%. In a primary care hospital with only a 15% disease prevalance the PPA is only 77% and SPECT may increase this accuracy to about 79%. Similar calculations based on published data show that marginal improvements are expected with SPECT in the liver. It is concluded that: a) The decision to purchase a high technology imaging modality such as SPECT for clinical purposes should be analyzed on an individual organ system and institutional basis. High technology may be justified in specialist hospitals but not necessarily in primary care hospitals. This is more dependent on disease prevalance than procedure volume; b) It is questionable whether SPECT imaging will be competitive with standard RS procedures. Research should concentrate on the development of different medical applications.

  8. Analysis of the process of representing clinical statements for decision-support applications: a comparison of openEHR archetypes and HL7 virtual medical record.

    PubMed

    González-Ferrer, A; Peleg, M; Marcos, M; Maldonado, J A

    2016-07-01

    Delivering patient-specific decision-support based on computer-interpretable guidelines (CIGs) requires mapping CIG clinical statements (data items, clinical recommendations) into patients' data. This is most effectively done via intermediate data schemas, which enable querying the data according to the semantics of a shared standard intermediate schema. This study aims to evaluate the use of HL7 virtual medical record (vMR) and openEHR archetypes as intermediate schemas for capturing clinical statements from CIGs that are mappable to electronic health records (EHRs) containing patient data and patient-specific recommendations. Using qualitative research methods, we analyzed the encoding of ten representative clinical statements taken from two CIGs used in real decision-support systems into two health information models (openEHR archetypes and HL7 vMR instances) by four experienced informaticians. Discussion among the modelers about each case study example greatly increased our understanding of the capabilities of these standards, which we share in this educational paper. Differing in content and structure, the openEHR archetypes were found to contain a greater level of representational detail and structure while the vMR representations took fewer steps to complete. The use of openEHR in the encoding of CIG clinical statements could potentially facilitate applications other than decision-support, including intelligent data analysis and integration of additional properties of data items from existing EHRs. On the other hand, due to their smaller size and fewer details, the use of vMR potentially supports quicker mapping of EHR data into clinical statements.

  9. Clinical Decision Support Systems and Prevention

    PubMed Central

    Njie, Gibril J.; Proia, Krista K.; Thota, Anilkrishna B.; Finnie, Ramona K.C.; Hopkins, David P.; Banks, Starr M.; Callahan, David B.; Pronk, Nicolaas P.; Rask, Kimberly J.; Lackland, Daniel T.; Kottke, Thomas E.

    2016-01-01

    Context Clinical decision support systems (CDSSs) can help clinicians assess cardiovascular disease (CVD) risk and manage CVD risk factors by providing tailored assessments and treatment recommendations based on individual patient data. The goal of this systematic review was to examine the effectiveness of CDSSs in improving screening for CVD risk factors, practices for CVD-related preventive care services such as clinical tests and prescribed treatments, and management of CVD risk factors. Evidence acquisition An existing systematic review (search period, January 1975–January 2011) of CDSSs for any condition was initially identified. Studies of CDSSs that focused on CVD prevention in that review were combined with studies identified through an updated search (January 2011–October 2012). Data analysis was conducted in 2013. Evidence synthesis A total of 45 studies qualified for inclusion in the review. Improvements were seen for recommended screening and other preventive care services completed by clinicians, recommended clinical tests completed by clinicians, and recommended treatments prescribed by clinicians (median increases of 3.8, 4.0, and 2.0 percentage points, respectively). Results were inconsistent for changes in CVD risk factors such as systolic and diastolic blood pressure, total and low-density lipoprotein cholesterol, and hemoglobin A1C levels. Conclusions CDSSs are effective in improving clinician practices related to screening and other preventive care services, clinical tests, and treatments. However, more evidence is needed from implementation of CDSSs within the broad context of comprehensive service delivery aimed at reducing CVD risk and CVD-related morbidity and mortality. PMID:26477805

  10. Latent effects decision analysis

    DOEpatents

    Cooper, J Arlin [Albuquerque, NM; Werner, Paul W [Albuquerque, NM

    2004-08-24

    Latent effects on a system are broken down into components ranging from those far removed in time from the system under study (latent) to those which closely effect changes in the system. Each component is provided with weighted inputs either by a user or from outputs of other components. A non-linear mathematical process known as `soft aggregation` is performed on the inputs to each component to provide information relating to the component. This information is combined in decreasing order of latency to the system to provide a quantifiable measure of an attribute of a system (e.g., safety) or to test hypotheses (e.g., for forensic deduction or decisions about various system design options).

  11. Strategies for Teaching Clinical Decision-Making.

    ERIC Educational Resources Information Center

    Boney, Jo; Baker, Jacqueline D.

    1997-01-01

    Research and a literature review suggest that nurses lack skills for effective clinical decision making. An educational program that facilitated development of critical thinking focused on four qualities: determining accuracy of information, determining bias, identifying inconsistencies in reasoning, and evaluating the strength of an argument. (SK)

  12. Query Reformulation for Clinical Decision Support Search

    DTIC Science & Technology

    2014-11-01

    Query Reformulation for Clinical Decision Support Search Luca Soldaini, Arman Cohan, Andrew Yates, Nazli Goharian, Ophir Frieder Information...work, we present a query reformulation approach that addresses the unique formulation of case reports, making them suitable to be used on a general... reformulation approach does not directly take into account the generic question type (diagnosis, test, treatment) provided with each approach. To ameliorate

  13. Decision Analysis Using Extended Techniques

    PubMed Central

    Lau, Joseph; Pauker, Stephen G.

    1985-01-01

    Clinical problems are often complex, repetitive and time dependent. Using only the classical decision tree formalism to model such details are often impractical if not impossible. A number of techniques are described here that could be used to reduce the complexity and to improve the representation. A case illustration describes how such techniques may be used.

  14. Qualitative analysis of vendor discussions on the procurement of Computerised Physician Order Entry and Clinical Decision Support systems in hospitals.

    PubMed

    Cresswell, Kathrin M; Lee, Lisa; Slee, Ann; Coleman, Jamie; Bates, David W; Sheikh, Aziz

    2015-10-26

    We studied vendor perspectives about potentially transferable lessons for implementing organisations and national strategies surrounding the procurement of Computerised Physician Order Entry (CPOE)/Clinical Decision Support (CDS) systems in English hospitals. Data were collected from digitally audio-recorded discussions from a series of CPOE/CDS vendor round-table discussions held in September 2014 in the UK. Nine participants, representing 6 key vendors operating in the UK, attended. The discussions were transcribed verbatim and thematically analysed. Vendors reported a range of challenges surrounding the procurement and contracting processes of CPOE/CDS systems, including hospitals' inability to adequately assess their own needs and then select a suitable product, rushed procurement and implementation processes that resulted in difficulties in meaningfully engaging with vendors, as well as challenges relating to contracting leading to ambiguities in implementation roles. Consequently, relationships between system vendors and hospitals were often strained, the vendors attributing this to a lack of hospital management's appreciation of the complexities associated with implementation efforts. Future anticipated challenges included issues surrounding the standardisation of data to enable their aggregation across systems for effective secondary uses, and implementation of data exchange with providers outside the hospital. Our results indicate that there are significant issues surrounding capacity to procure and optimise CPOE/CDS systems among UK hospitals. There is an urgent need to encourage more synergistic and collaborative working between providers and vendors and for a more centralised support for National Health Service hospitals, which draws on a wider body of experience, including a formalised procurement framework with value-based product specifications. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a

  15. Qualitative analysis of vendor discussions on the procurement of Computerised Physician Order Entry and Clinical Decision Support systems in hospitals

    PubMed Central

    Cresswell, Kathrin M; Lee, Lisa; Slee, Ann; Coleman, Jamie; Bates, David W; Sheikh, Aziz

    2015-01-01

    Objectives We studied vendor perspectives about potentially transferable lessons for implementing organisations and national strategies surrounding the procurement of Computerised Physician Order Entry (CPOE)/Clinical Decision Support (CDS) systems in English hospitals. Setting Data were collected from digitally audio-recorded discussions from a series of CPOE/CDS vendor round-table discussions held in September 2014 in the UK. Participants Nine participants, representing 6 key vendors operating in the UK, attended. The discussions were transcribed verbatim and thematically analysed. Results Vendors reported a range of challenges surrounding the procurement and contracting processes of CPOE/CDS systems, including hospitals’ inability to adequately assess their own needs and then select a suitable product, rushed procurement and implementation processes that resulted in difficulties in meaningfully engaging with vendors, as well as challenges relating to contracting leading to ambiguities in implementation roles. Consequently, relationships between system vendors and hospitals were often strained, the vendors attributing this to a lack of hospital management's appreciation of the complexities associated with implementation efforts. Future anticipated challenges included issues surrounding the standardisation of data to enable their aggregation across systems for effective secondary uses, and implementation of data exchange with providers outside the hospital. Conclusions Our results indicate that there are significant issues surrounding capacity to procure and optimise CPOE/CDS systems among UK hospitals. There is an urgent need to encourage more synergistic and collaborative working between providers and vendors and for a more centralised support for National Health Service hospitals, which draws on a wider body of experience, including a formalised procurement framework with value-based product specifications. PMID:26503385

  16. 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…

  17. 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…

  18. Computerized Clinical Decision Support: Contributions from 2015.

    PubMed

    Koutkias, V; Bouaud, J

    2016-11-10

    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. 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. 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. While there are notable examples of routinely used decision support systems, this 2015 review on CDSSs and CPOE systems still shows that, despite methodological contributions, theoretical frameworks, and prototype developments, these technologies are not yet widely spread (at least with their full functionalities) in routine clinical practice. Further research, testing, evaluation, and training are still needed for these tools to be adopted in clinical practice and, ultimately, illustrate the benefits that they promise.

  19. Initial Decision and Risk Analysis

    SciTech Connect

    Engel, David W.

    2012-02-29

    Decision and Risk Analysis capabilities will be developed for industry consideration and possible adoption within Year 1. These tools will provide a methodology for merging qualitative ranking of technology maturity and acknowledged risk contributors with quantitative metrics that drive investment decision processes. Methods and tools will be initially introduced as applications to the A650.1 case study, but modular spreadsheets and analysis routines will be offered to industry collaborators as soon as possible to stimulate user feedback and co-development opportunities.

  20. Nurses' decision-making in ethically relevant clinical situations using the example of breathlessness: study protocol of a reflexive grounded theory integrating Goffman's framework analysis.

    PubMed

    Dunger, Christine; Schnell, Martin W; Bausewein, Claudia

    2017-02-22

    Decision-making (DM) in healthcare can be understood as an interactive process addressing decision makers' reasoning as well as their visible behaviour after the decision is made. Other key elements of DM are ethical aspects and the role as well as the treatment options of the examined professions. Nurses' DM to choose interventions in situations of severe breathlessness is such interactions. They are also ethically relevant regarding the vulnerability of affected patients and possible restrictions or treatment options. The study aims to explore which factors influence nurses' DM to use nursing interventions in situations where patients suffer from severe breathlessness. Qualitative study including nurses in German hospital wards and hospices. A triangulation of different methods of data collection-participant observation and qualitative expert interviews-and analysis merge in a reflexive grounded theory approach which integrates Goffman's framework analysis. It allows an analysis of nurses' self-statements about DM, their behaviour in relevant clinical situations and its influences. Data collection and analysis will be examined simultaneously. Informed consent will be gained from all participants and the institutional stakeholders. Ongoing consent has to be ensured since observations will take place in healthcare institutions and many patients will be highly vulnerable. The study has been evaluated and approved by the Witten/Herdecke University Ethics Committee, Witten, Germany. Results of the study will be published at congresses and in journal papers. 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/.

  1. Multicriteria decision analysis: Overview and implications for environmental decision making

    USGS Publications Warehouse

    Hermans, Caroline M.; Erickson, Jon D.; Erickson, Jon D.; Messner, Frank; Ring, Irene

    2007-01-01

    Environmental decision making involving multiple stakeholders can benefit from the use of a formal process to structure stakeholder interactions, leading to more successful outcomes than traditional discursive decision processes. There are many tools available to handle complex decision making. Here we illustrate the use of a multicriteria decision analysis (MCDA) outranking tool (PROMETHEE) to facilitate decision making at the watershed scale, involving multiple stakeholders, multiple criteria, and multiple objectives. We compare various MCDA methods and their theoretical underpinnings, examining methods that most realistically model complex decision problems in ways that are understandable and transparent to stakeholders.

  2. 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.

  3. Computerized Clinical Decision Support: Contributions from 2014.

    PubMed

    Bouaud, J; Koutkias, V

    2015-08-13

    To summarize recent research and propose a selection of best papers published in 2014 in the field of computerized clinical decision support for the Decision Support section of the IMIA yearbook. A literature review was performed by searching two bibliographic databases for papers related to clinical decision support systems (CDSSs) and computerized provider order entry systems in order to select a list of candidate best papers to be then peer-reviewed by external reviewers. A consensus meeting between the two section editors and the editorial team was finally organized to conclude on the selection of best papers. Among the 1,254 returned papers published in 2014, the full review process selected four best papers. The first one is an experimental contribution to a better understanding of unintended uses of CDSSs. The second paper describes the effective use of previously collected data to tailor and adapt a CDSS. The third paper presents an innovative application that uses pharmacogenomic information to support personalized medicine. The fourth paper reports on the long-term effect of the routine use of a CDSS for antibiotic therapy. As health information technologies spread more and more meaningfully, CDSSs are improving to answer users' needs more accurately. The exploitation of previously collected data and the use of genomic data for decision support has started to materialize. However, more work is still needed to address issues related to the correct usage of such technologies, and to assess their effective impact in the long term.

  4. Computerized Clinical Decision Support: Contributions from 2014

    PubMed Central

    Koutkias, V.

    2015-01-01

    Summary Objective To summarize recent research and propose a selection of best papers published in 2014 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 systems in order to select a list of candidate best papers to be then peer-reviewed by external reviewers. A consensus meeting between the two section editors and the editorial team was finally organized to conclude on the selection of best papers. Results Among the 1,254 returned papers published in 2014, the full review process selected four best papers. The first one is an experimental contribution to a better understanding of unintended uses of CDSSs. The second paper describes the effective use of previously collected data to tailor and adapt a CDSS. The third paper presents an innovative application that uses pharmacogenomic information to support personalized medicine. The fourth paper reports on the long-term effect of the routine use of a CDSS for antibiotic therapy. Conclusions As health information technologies spread more and more meaningfully, CDSSs are improving to answer users’ needs more accurately. The exploitation of previously collected data and the use of genomic data for decision support has started to materialize. However, more work is still needed to address issues related to the correct usage of such technologies, and to assess their effective impact in the long term. PMID:26293858

  5. Prototype Application of Mobile, Cloud-based, Watson-Like Technologies for TBI/PTSD Clinical Decision Support and Predictive Analysis

    DTIC Science & Technology

    2013-09-01

    analytics to improve clinical outcomes for veterans, soldiers, and their families with traumatic brain injury (TBI) and posttraumatic stress disorder...clinical ontology, decision support, expert system, mHealth , PTSD, semantic parsing, TBI 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF...analytics, and improve clinical outcomes for veterans, soldiers, and their families with traumatic brain injury (TBI) and posttraumatic stress disorder

  6. Training Decisions Technology Analysis

    DTIC Science & Technology

    1992-06-01

    Costs 89 5.3 Discussion of Constrained TDY-to- School Resources 90 5.4 Summary and Recommendations 93 6. Sensitivity Analysis 94 6.1 Methods 94 6.2...Analyzer Training 34 4.1 The ISEM-P Model 68 TABLE OF TABLES TablePage 5.1 25% Reduction in TDY-to- School Costs 76 5.2 25% Reduction in ABR Attendance 77 5.3...AFS 328X4 Reduced TDY-to- School 79 5.4 25% Reduction in ABR 328X4 Student Flow 79 5.5 Example Representative Site Training Capacity Results 81 5.6

  7. Probability, clinical decision making and hypothesis testing

    PubMed Central

    Banerjee, A.; Jadhav, S. L.; Bhawalkar, J. S.

    2009-01-01

    Few clinicians grasp the true concept of probability expressed in the ‘P value.’ For most, a statistically significant P value is the end of the search for truth. In fact, the opposite is the case. The present paper attempts to put the P value in proper perspective by explaining different types of probabilities, their role in clinical decision making, medical research and hypothesis testing. PMID:21234167

  8. Dialogic Consensus In Clinical Decision-Making.

    PubMed

    Walker, Paul; Lovat, Terry

    2016-12-01

    This paper is predicated on the understanding that clinical encounters between clinicians and patients should be seen primarily as inter-relations among persons and, as such, are necessarily moral encounters. It aims to relocate the discussion to be had in challenging medical decision-making situations, including, for example, as the end of life comes into view, onto a more robust moral philosophical footing than is currently commonplace. In our contemporary era, those making moral decisions must be cognizant of the existence of perspectives other than their own, and be attuned to the demands of inter-subjectivity. Applicable to clinical practice, we propose and justify a Habermasian approach as one useful means of achieving what can be described as dialogic consensus. The Habermasian approach builds around, first, his discourse theory of morality as universalizable to all and, second, communicative action as a cooperative search for truth. It is a concrete way to ground the discourse which must be held in complex medical decision-making situations, in its actual reality. Considerations about the theoretical underpinnings of the application of dialogic consensus to clinical practice, and potential difficulties, are explored.

  9. Thinking processes used by nurses in clinical decision making.

    PubMed

    Higuchi, Kathryn A Smith; Donald, Janet G

    2002-04-01

    Clinical decision making forms the basis of expert clinical practice. The purpose of this study was to investigate and document the thinking processes used by nurses in clinical decision making situations so the processes could guide educational practice. Clinical data was analyzed to reveal that clinical decision making is complex and requires a variety of thinking processes. Medical and surgical nurses used different thinking processes, showing the importance of context in clinical decision making. The nursing exemplars and working vocabulary developed in this study to describe the thinking processes used in clinical decision making can be used in nursing education.

  10. Creating clinical decision support systems for respiratory medicine.

    PubMed

    Tams, Carl G; Euliano, Neil R

    2015-01-01

    Clinical decision support systems are vital for advances in improving patient therapeutic care. We share lessons learned from creating two respiratory clinical decisions support systems for ventilating patients in a critical care setting.

  11. Decision analysis: a basic overview for the pediatric surgeon.

    PubMed

    Burd, Randall S; Sonnenberg, Frank A

    2002-02-01

    Decision making in medicine requires choosing the option that best maximizes benefit while minimizing risk and cost. Even though uncertainty is an inherent feature of any clinical issue, clinicians and policy makers frequently are required to evaluate the best evidence and make therapeutic or policy decisions based on that evidence. Decision analysis is a quantitative approach to decision making under conditions of uncertainty that can be applied to specific types of clinical problems. This method disaggregates a complex clinical problem into its most important components that then can be understood more easily and analyzed quantitatively. Decision analysis has many potential applications in medicine and can be applied to solve specific clinical problems, analyze health care costs, or develop health care policies. In this review, the basic methods for constructing and analyzing decision analyses will be presented, and specific applications of this method to pediatric surgery will be discussed. Copyright 2002 by W.B. Saunders Company

  12. [Comparison of the Cost-Effectiveness of the SOX and COX Regimens in Patients with Unresectable Advanced and Recurrent Colorectal Cancer Using a Clinical Decision Analysis Approach].

    PubMed

    Nagase, Satoshi; Iyoda, Tomokazu; Kanno, Hiroshi; Akase, Tomohide; Arakawa, Ichiro; Inoue, Tadao; Uetsuka, Yoshio

    2016-10-01

    Phase III clinical trials have comfirmed that the S-1 plus oxaliplatin(SOX)is inferior to the capecitabine plus oxaliplatin (COX)regimen in the treatment of metastatic colorectal cancer.On the basis of these findings, we compared, using a clinical decision analysis-based approach, the cost-effectiveness of the SOX and COX regimens.Herein, we simulated the expected effects and costs of the SOX and COX regimens using the markov model.Clinical data were obtained from Hong's 2012 report.The cost data comprised the costs for pharmacist labor, material, inspection, and treatment for adverse event, as well as the total cost of care at the advanced stage.The result showed that the expected cost of the SOX and COX regimen was 1,538,330 yen, and 1,429,596 yen, respectively, with an expected survival rate of 29.18 months, and 28.63 months, respectively.The incremental cost-effectiveness ratio of the SOX regimen was 197,698 yen/month; thus, the SOX regimen was found to be more cost-effective that the COX regimen.

  13. Life and Death Decision Analysis.

    DTIC Science & Technology

    1979-12-01

    LIFE SMOKING: CANCER, EMPHYSEMA, SHORTENED LIFE BATHING: FALLING, ELECTROCUTION CONTRACEPTION: DEATH , ILLNESS PREGNANCY: DEATH , ILLNESS ABORTION ...economic effect is the one with the highest probability of causing my death . -13- EXPECTED NET SYSTEM DESIGN BENEFIT TO ME DEATH DEATH (r A(excluding death ...0-AO81 424 STANFORD UNIV CALIF DEPT OF ENGtNEERING-ECONOM!C SYSTEMS F/6 12/1 LIFE ANDI DEATH DECISION ANALYSIS.CU) DEC 79 R A HOWARD N0OOIN-79-C-0036

  14. [Clinical decisions in a philosophical perspective].

    PubMed

    Wulff, H R

    1993-09-20

    Medicine is both a scientific and a humanistic discipline. The foundation for clinical decisions has four components (two scientific and two humanistic). 1) The biological component (reasoning based on biological theory). Biological thinking is currently being revolutionised, partly through the development of systems theory. 2) The empirical component (reasoning based on experience from earlier patients), which comprises both uncontrolled and controlled experience. 3) The empathic-hermeneutic component (reasoning based on an understanding of the patient as a fellow human being). Empathy requires hermeneutic knowledge which can be acquired through personal experience and by qualitative research. 4) The ethical component which comprises both utilitarian and deontological considerations.

  15. Subjective measures and clinical decision making.

    PubMed

    Delitto, A

    1989-07-01

    I have attempted to use Feinstein's model of clinimetric indexes and his criteria as a focus for further development of measures that in physical therapy are currently considered "soft" or "subjective". I feel this development will enhance the body of knowledge by objectifying a portion of clinical assessment (eg, the patient's complaints, "subjective" portion of the POMR's SOAP format) that is in tremendous need of quantification. By making these "soft" data "hard," I feel we will enhance the decision-making power of clinicians.

  16. Best Practices in Clinical Decision Support

    PubMed Central

    Wright, Adam; Phansalkar, Shobha; Bloomrosen, Meryl; Jenders, Robert A.; Bobb, Anne M.; Halamka, John D.; Kuperman, Gilad; Payne, Thomas H.; Teasdale, S.; Vaida, A. J.; Bates, D. W.

    2010-01-01

    Background Evidence demonstrates that clinical decision support (CDS) is a powerful tool for improving healthcare quality and ensuring patient safety. However, implementing and maintaining effective decision support interventions presents multiple technical and organizational challenges. Purpose To identify best practices for CDS, using the domain of preventive care reminders as an example. Methods We assembled a panel of experts in CDS and held a series of facilitated online and inperson discussions. We analyzed the results of these discussions using a grounded theory method to elicit themes and best practices. Results Eight best practice themes were identified as important: deliver CDS in the most appropriate ways, develop effective governance structures, consider use of incentives, be aware of workflow, keep content current, monitor and evaluate impact, maintain high quality data, and consider sharing content. Keys themes within each of these areas were also described. Conclusion Successful implementation of CDS requires consideration of both technical and socio-technical factors. The themes identified in this study provide guidance on crucial factors that need consideration when CDS is implemented across healthcare settings. These best practice themes may be useful for developers, implementers, and users of decision support. PMID:21991299

  17. Driving and dementia: a clinical decision pathway

    PubMed Central

    Carter, Kirsty; Monaghan, Sophie; O'Brien, John; Teodorczuk, Andrew; Mosimann, Urs; Taylor, John-Paul

    2015-01-01

    Objective This study aimed to develop a pathway to bring together current UK legislation, good clinical practice and appropriate management strategies that could be applied across a range of healthcare settings. Methods The pathway was constructed by a multidisciplinary clinical team based in a busy Memory Assessment Service. A process of successive iteration was used to develop the pathway, with input and refinement provided via survey and small group meetings with individuals from a wide range of regional clinical networks and diverse clinical backgrounds as well as discussion with mobility centres and Forum of Mobility Centres, UK. Results We present a succinct clinical pathway for patients with dementia, which provides a decision-making framework for how health professionals across a range of disciplines deal with patients with dementia who drive. Conclusions By integrating the latest guidance from diverse roles within older people's health services and key experts in the field, the resulting pathway reflects up-to-date policy and encompasses differing perspectives and good practice. It is potentially a generalisable pathway that can be easily adaptable for use internationally, by replacing UK legislation for local regulations. A limitation of this pathway is that it does not address the concern of mild cognitive impairment and how this condition relates to driving safety. © 2014 The Authors. International Journal of Geriatric Psychiatry published by John Wiley & Sons, Ltd. PMID:24865643

  18. 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

  19. Considerations for a successful clinical decision support system.

    PubMed

    Castillo, Ranielle S; Kelemen, Arpad

    2013-07-01

    Clinical decision support systems have the potential to improve patient care in a multitude of ways. Clinical decision support systems can aid in the reduction of medical errors and reduction in adverse drug events, ensure comprehensive treatment of patient illnesses and conditions, encourage the adherence to guidelines, shorten patient length of stay, and decrease expenses over time. A clinical decision support system is one of the key components for reaching compliance for Meaningful Use. In this article, the advantages, potential drawbacks, and clinical decision support system adoption barriers are discussed, followed by an in-depth review of the characteristics that make a clinical decision support system successful. The legal and ethical issues that come with the implementation of a clinical decision support system within an organization and the future expectations of clinical decision support system are reviewed.

  20. Clinical and economic impact of a combination Haemophilus influenzae and Hepatitis B vaccine: estimating cost-effectiveness using decision analysis.

    PubMed

    Fendrick, A M; Lee, J H; LaBarge, C; Glick, H A

    1999-02-01

    Compliance with hepatitis B virus (HBV) vaccine remains suboptimal, despite a recommendation by the Advisory Committee on Immunization Practices of the US Public Health Service that all newborns be vaccinated. Although a combined HBV-Haemophilus influenzae type b (Hib) vaccine may improve acceptance of the HBV vaccine, the clinical and economic consequences of this intervention are uncertain. To compare the health impact and cost-effectiveness of the following 2 immunization strategies: current practice of administering HBV vaccine separately (75% compliance) and Hib vaccine alone or as part of a multivalent vaccine (95% compliance); and strategy of delivering a combined HBV-Hib vaccine (95% compliance). A Markov model simulated the natural history of acute and chronic HBV and Hib disease in a cohort of US newborns. Clinical and economic variables were obtained from published reports. The Hib-related outcomes were the same in both strategies, because the efficacy and compliance with Hib vaccine were assumed to be equivalent in both. A 53% reduction in the number of cases of HBV infection with the combination strategy (n = 8541) was estimated when compared with current practice (n = 18 044), along with 205 fewer HBV-related deaths per 1 million infants. Immunization costs of the combination strategy were $11.5 million higher than for current practice ($108.4 million compared with $96.9 million), whereas the cost of HBV-related disease was $4.0 million lower than in current practice. The incremental cost-effectiveness ratio for the combination strategy was $17700 per year of life saved. An HBV-Hib vaccine in US infants yields substantial benefits, with a cost-effectiveness ratio that is lower than that of many commonly used medical interventions.

  1. Adoption of clinical decision support in multimorbidity: a systematic review.

    PubMed

    Fraccaro, Paolo; Arguello Casteleiro, Mercedes; Ainsworth, John; Buchan, Iain

    2015-01-07

    Patients with multiple conditions have complex needs and are increasing in number as populations age. This multimorbidity is one of the greatest challenges facing health care. Having more than 1 condition generates (1) interactions between pathologies, (2) duplication of tests, (3) difficulties in adhering to often conflicting clinical practice guidelines, (4) obstacles in the continuity of care, (5) confusing self-management information, and (6) medication errors. In this context, clinical decision support (CDS) systems need to be able to handle realistic complexity and minimize iatrogenic risks. The aim of this review was to identify to what extent CDS is adopted in multimorbidity. This review followed PRISMA guidance and adopted a multidisciplinary approach. Scopus and PubMed searches were performed by combining terms from 3 different thesauri containing synonyms for (1) multimorbidity and comorbidity, (2) polypharmacy, and (3) CDS. The relevant articles were identified by examining the titles and abstracts. The full text of selected/relevant articles was analyzed in-depth. For articles appropriate for this review, data were collected on clinical tasks, diseases, decision maker, methods, data input context, user interface considerations, and evaluation of effectiveness. A total of 50 articles were selected for the full in-depth analysis and 20 studies were included in the final review. Medication (n=10) and clinical guidance (n=8) were the predominant clinical tasks. Four studies focused on merging concurrent clinical practice guidelines. A total of 17 articles reported their CDS systems were knowledge-based. Most articles reviewed considered patients' clinical records (n=19), clinical practice guidelines (n=12), and clinicians' knowledge (n=10) as contextual input data. The most frequent diseases mentioned were cardiovascular (n=9) and diabetes mellitus (n=5). In all, 12 articles mentioned generalist doctor(s) as the decision maker(s). For articles reviewed

  2. Adoption of Clinical Decision Support in Multimorbidity: A Systematic Review

    PubMed Central

    Arguello Casteleiro, Mercedes; Ainsworth, John; Buchan, Iain

    2015-01-01

    Background Patients with multiple conditions have complex needs and are increasing in number as populations age. This multimorbidity is one of the greatest challenges facing health care. Having more than 1 condition generates (1) interactions between pathologies, (2) duplication of tests, (3) difficulties in adhering to often conflicting clinical practice guidelines, (4) obstacles in the continuity of care, (5) confusing self-management information, and (6) medication errors. In this context, clinical decision support (CDS) systems need to be able to handle realistic complexity and minimize iatrogenic risks. Objective The aim of this review was to identify to what extent CDS is adopted in multimorbidity. Methods This review followed PRISMA guidance and adopted a multidisciplinary approach. Scopus and PubMed searches were performed by combining terms from 3 different thesauri containing synonyms for (1) multimorbidity and comorbidity, (2) polypharmacy, and (3) CDS. The relevant articles were identified by examining the titles and abstracts. The full text of selected/relevant articles was analyzed in-depth. For articles appropriate for this review, data were collected on clinical tasks, diseases, decision maker, methods, data input context, user interface considerations, and evaluation of effectiveness. Results A total of 50 articles were selected for the full in-depth analysis and 20 studies were included in the final review. Medication (n=10) and clinical guidance (n=8) were the predominant clinical tasks. Four studies focused on merging concurrent clinical practice guidelines. A total of 17 articles reported their CDS systems were knowledge-based. Most articles reviewed considered patients’ clinical records (n=19), clinical practice guidelines (n=12), and clinicians’ knowledge (n=10) as contextual input data. The most frequent diseases mentioned were cardiovascular (n=9) and diabetes mellitus (n=5). In all, 12 articles mentioned generalist doctor(s) as the

  3. An Organizational Informatics Analysis of Colorectal, Breast, and Cervical Cancer Screening Clinical Decision Support and Information Systems within Community Health Centers

    ERIC Educational Resources Information Center

    Carney, Timothy Jay

    2012-01-01

    A study design has been developed that employs a dual modeling approach to identify factors associated with facility-level cancer screening improvement and how this is mediated by the use of clinical decision support. This dual modeling approach combines principles of (1) Health Informatics, (2) Cancer Prevention and Control, (3) Health Services…

  4. An Organizational Informatics Analysis of Colorectal, Breast, and Cervical Cancer Screening Clinical Decision Support and Information Systems within Community Health Centers

    ERIC Educational Resources Information Center

    Carney, Timothy Jay

    2012-01-01

    A study design has been developed that employs a dual modeling approach to identify factors associated with facility-level cancer screening improvement and how this is mediated by the use of clinical decision support. This dual modeling approach combines principles of (1) Health Informatics, (2) Cancer Prevention and Control, (3) Health Services…

  5. Best-fit model of exploratory and confirmatory factor analysis of the 2010 Medical Council of Canada Qualifying Examination Part I clinical decision-making cases.

    PubMed

    Champlain, André F De

    2015-01-01

    This study aims to assess the fit of a number of exploratory and confirmatory factor analysis models to the 2010 Medical Council of Canada Qualifying Examination Part I (MCCQE1) clinical decision-making (CDM) cases. The outcomes of this study have important implications for a range of domains, including scoring and test development. The examinees included all first-time Canadian medical graduates and international medical graduates who took the MCCQE1 in spring or fall 2010. The fit of one- to five-factor exploratory models was assessed for the item response matrix of the 2010 CDM cases. Five confirmatory factor analytic models were also examined with the same CDM response matrix. The structural equation modeling software program Mplus was used for all analyses. Out of the five exploratory factor analytic models that were evaluated, a three-factor model provided the best fit. Factor 1 loaded on three medicine cases, two obstetrics and gynecology cases, and two orthopedic surgery cases. Factor 2 corresponded to pediatrics, and the third factor loaded on psychiatry cases. Among the five confirmatory factor analysis models examined in this study, three- and four-factor lifespan period models and the five-factor discipline models provided the best fit. The results suggest that knowledge of broad disciplinary domains best account for performance on CDM cases. In test development, particular effort should be placed on developing CDM cases according to broad discipline and patient age domains; CDM testlets should be assembled largely using the criteria of discipline and age.

  6. Clinical Decision Support Capabilities of Commercially-available Clinical Information Systems

    PubMed Central

    Wright, Adam; Sittig, Dean F.; Ash, Joan S.; Sharma, Sapna; Pang, Justine E.; Middleton, Blackford

    2009-01-01

    Background The most effective decision support systems are integrated with clinical information systems, such as inpatient and outpatient electronic health records (EHRs) and computerized provider order entry (CPOE) systems. Purpose The goal of this project was to describe and quantify the results of a study of decision support capabilities in Certification Commission for Health Information Technology (CCHIT) certified electronic health record systems. Methods The authors conducted a series of interviews with representatives of nine commercially available clinical information systems, evaluating their capabilities against 42 different clinical decision support features. Results Six of the nine reviewed systems offered all the applicable event-driven, action-oriented, real-time clinical decision support triggers required for initiating clinical decision support interventions. Five of the nine systems could access all the patient-specific data items identified as necessary. Six of the nine systems supported all the intervention types identified as necessary to allow clinical information systems to tailor their interventions based on the severity of the clinical situation and the user's workflow. Only one system supported all the offered choices identified as key to allowing physicians to take action directly from within the alert. Discussion The principal finding relates to system-by-system variability. The best system in our analysis had only a single missing feature (from 42 total) while the worst had eighteen.This dramatic variability in CDS capability among commercially available systems was unexpected and is a cause for concern. Conclusions These findings have implications for four distinct constituencies: purchasers of clinical information systems, developers of clinical decision support, vendors of clinical information systems and certification bodies. PMID:19567796

  7. Decision analysis: a primer and application to pain-related studies.

    PubMed

    Kim, Jaewhan; Nelson, Richard; Biskupiak, Joseph

    2008-01-01

    Decision analysis is a quantitative approach to decision making under uncertainty that explicitly states all relevant components of the decision, including statement of the problem, identification of the perspective of the decision maker, alternative courses of action and their consequences, and a model that illustrates the decision-making process. Decision trees and Markov models are used to provide a simplified version of complex clinical problems to help decision makers understand the risks and benefits of several clinical options. This article provides an introduction to decision analysis by describing the construction of decision trees and Markov models and employing examples from the recent literature.

  8. Effects of a computerized provider order entry and a clinical decision support system to improve cefazolin use in surgical prophylaxis: a cost saving analysis.

    PubMed

    Okumura, Lucas M; Veroneze, Izelandia; Burgardt, Celia I; Fragoso, Marta F

    2016-01-01

    Computerized Provider Order Entry (CPOE) and Clinical Decision Support System (CDSS) help practitioners to choose evidence-based decisions, regarding patients' needs. Despite its use in developed countries, in Brazil, the impact of a CPOE/CDSS to improve cefazolin use in surgical prophylaxis was not assessed yet. We aimed to evaluate the impact of a CDSS to improve the use of prophylactic cefazolin and to assess the cost savings associated to inappropriate prescribing. This is a cross-sectional study that compared two different scenarios: one prior CPOE/CDSS versus after software implementation. We conducted twelve years of data analysis (3 years prior and 9 years after CDSS implementation), where main outcomes from this study included: cefazolin Defined Daily Doses/100 bed-days (DDD), crude costs and product of costs-DDD (cost-DDD/100 bed-days). We applied a Spearman rho non-parametric test to assess the reduction of cefazolin consumption through the years. In twelve years, 84,383 vials of cefazolin were dispensed and represented 38.89 DDD/100 bed-days or USD 44,722.99. Surgical wards were the largest drug prescribers and comprised >95% of our studied sample. While in 2002, there were 6.31 DDD/100 bed-days, 9 years later there was a reduction to 2.15 (p<0.05). In a scenario without CDSS, the hospital would have consumed 75.72 DDD/100 bed-days, which is equivalent to USD 116 998.07. It is estimated that CDSS provided USD 50,433.39 of cost savings. The implementation of a CPOE/CDSS helped to improve prophylactic cefazolin use by reducing its consumption and estimated direct costs.

  9. Effects of a computerized provider order entry and a clinical decision support system to improve cefazolin use in surgical prophylaxis: a cost saving analysis

    PubMed Central

    Veroneze, Izelandia; Burgardt, Celia I.; Fragoso, Marta F.

    2016-01-01

    Background: Computerized Provider Order Entry (CPOE) and Clinical Decision Support System (CDSS) help practitioners to choose evidence-based decisions, regarding patients’ needs. Despite its use in developed countries, in Brazil, the impact of a CPOE/CDSS to improve cefazolin use in surgical prophylaxis was not assessed yet. Objective: We aimed to evaluate the impact of a CDSS to improve the use of prophylactic cefazolin and to assess the cost savings associated to inappropriate prescribing. Methods: This is a cross-sectional study that compared two different scenarios: one prior CPOE/CDSS versus after software implementation. We conducted twelve years of data analysis (3 years prior and 9 years after CDSS implementation), where main outcomes from this study included: cefazolin Defined Daily Doses/100 bed-days (DDD), crude costs and product of costs-DDD (cost-DDD/100 bed-days). We applied a Spearman rho non-parametric test to assess the reduction of cefazolin consumption through the years. Results: In twelve years, 84,383 vials of cefazolin were dispensed and represented 38.89 DDD/100 bed-days or USD 44,722.99. Surgical wards were the largest drug prescribers and comprised >95% of our studied sample. While in 2002, there were 6.31 DDD/100 bed-days, 9 years later there was a reduction to 2.15 (p<0.05). In a scenario without CDSS, the hospital would have consumed 75.72 DDD/100 bed-days, which is equivalent to USD 116 998.07. It is estimated that CDSS provided USD 50,433.39 of cost savings. Conclusion: The implementation of a CPOE/CDSS helped to improve prophylactic cefazolin use by reducing its consumption and estimated direct costs. PMID:27785159

  10. User Centered Clinical Decision Support Tools

    PubMed Central

    Sofianou, A.; Kannry, J.; Mann, D.M.; McGinn, T.G.

    2014-01-01

    Summary Background Dissemination and adoption of clinical decision support (CDS) tools is a major initiative of the Affordable Care Act’s Meaningful Use program. Adoption of CDS tools is multipronged with personal, organizational, and clinical settings factoring into the successful utilization rates. Specifically, the diffusion of innovation theory implies that ‘early adopters’ are more inclined to use CDS tools and younger physicians tend to be ranked in this category. Objective This study examined the differences in adoption of CDS tools across providers’ training level. Participants From November 2010 to 2011, 168 residents and attendings from an academic medical institution were enrolled into a randomized controlled trial. Intervention The intervention arm had access to the CDS tool through the electronic health record (EHR) system during strep and pneumonia patient visits. Main Measures The EHR system recorded details on how intervention arm interacted with the CDS tool including acceptance of the initial CDS alert, completion of risk-score calculators and the signing of medication order sets. Using the EHR data, the study performed bivariate tests and general estimating equation (GEE) modeling to examine the differences in adoption of the CDS tool across residents and attendings. Key Results The completion rates of the CDS calculator and medication order sets were higher amongst first year residents compared to all other training levels. Attendings were the less likely to accept the initial step of the CDS tool (29.3%) or complete the medication order sets (22.4%) that guided their prescription decisions, resulting in attendings ordering more antibiotics (37.1%) during an CDS encounter compared to residents. Conclusion There is variation in adoption of CDS tools across training levels. Attendings tended to accept the tool less but ordered more medications. CDS tools should be tailored to clinicians’ training levels. PMID:25589914

  11. Suicide Danger: Clinical Estimation and Decision.

    ERIC Educational Resources Information Center

    Maltsberger, John T.

    1988-01-01

    Maintains that traditional mental status examination and clinical intuition or empathetic judgment are insufficient to predict suicide. Describes five components involved in the formulation of suicide risk: analysis of the patient's past response to stress, assessment of vulnerability to life-threatening affects, assessment of exterior sustaining…

  12. 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

  13. 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

  14. Shared clinical decision making. A Saudi Arabian perspective.

    PubMed

    AlHaqwi, Ali I; AlDrees, Turki M; AlRumayyan, Ahmad; AlFarhan, Ali I; Alotaibi, Sultan S; AlKhashan, Hesham I; Badri, Motasim

    2015-12-01

    To determine preferences of patients regarding their involvement in the clinical decision making process and the related factors in Saudi Arabia.   This cross-sectional study was conducted in a major family practice center in King Abdulaziz Medical City, Riyadh, Saudi Arabia, between March and May 2012. Multivariate multinomial regression models were fitted to identify factors associated with patients preferences.  The study included 236 participants. The most preferred decision-making style was shared decision-making (57%), followed by paternalistic  (28%), and informed consumerism (14%). The preference for shared clinical decision making was significantly higher among male patients and those with higher level of education, whereas paternalism was significantly higher among older patients and those with chronic health conditions, and consumerism was significantly higher in younger age groups. In multivariate multinomial regression analysis, compared with the shared group, the consumerism group were more likely to be female [adjusted odds ratio  (AOR) =2.87, 95% confidence interval [CI] 1.31-6.27, p=0.008] and non-dyslipidemic (AOR=2.90, 95% CI: 1.03-8.09, p=0.04), and the paternalism group were more likely to be older (AOR=1.03, 95% CI: 1.01-1.05, p=0.04), and female (AOR=2.47, 95% CI: 1.32-4.06, p=0.008).  Preferences of patients for involvement in the clinical decision-making varied considerably. In our setting, underlying factors that influence these preferences identified in this study should be considered and tailored individually to achieve optimal treatment outcomes.

  15. Using Cluster Analysis to Examine Husband-Wife Decision Making

    ERIC Educational Resources Information Center

    Bonds-Raacke, Jennifer M.

    2006-01-01

    Cluster analysis has a rich history in many disciplines and although cluster analysis has been used in clinical psychology to identify types of disorders, its use in other areas of psychology has been less popular. The purpose of the current experiments was to use cluster analysis to investigate husband-wife decision making. Cluster analysis was…

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

    PubMed

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

    2014-09-01

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

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

    PubMed Central

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

    2016-01-01

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

  18. Medical Question Answering for Clinical Decision Support.

    PubMed

    Goodwin, Travis R; Harabagiu, Sanda M

    2016-10-01

    The goal of modern Clinical Decision Support (CDS) systems is to provide physicians with information relevant to their management of patient care. When faced with a medical case, a physician asks questions about the diagnosis, the tests, or treatments that should be administered. Recently, the TREC-CDS track has addressed this challenge by evaluating results of retrieving relevant scientific articles where the answers of medical questions in support of CDS can be found. Although retrieving relevant medical articles instead of identifying the answers was believed to be an easier task, state-of-the-art results are not yet sufficiently promising. In this paper, we present a novel framework for answering medical questions in the spirit of TREC-CDS by first discovering the answer and then selecting and ranking scientific articles that contain the answer. Answer discovery is the result of probabilistic inference which operates on a probabilistic knowledge graph, automatically generated by processing the medical language of large collections of electronic medical records (EMRs). The probabilistic inference of answers combines knowledge from medical practice (EMRs) with knowledge from medical research (scientific articles). It also takes into account the medical knowledge automatically discerned from the medical case description. We show that this novel form of medical question answering (Q/A) produces very promising results in (a) identifying accurately the answers and (b) it improves medical article ranking by 40%.

  19. Medical Question Answering for Clinical Decision Support

    PubMed Central

    Goodwin, Travis R.; Harabagiu, Sanda M.

    2017-01-01

    The goal of modern Clinical Decision Support (CDS) systems is to provide physicians with information relevant to their management of patient care. When faced with a medical case, a physician asks questions about the diagnosis, the tests, or treatments that should be administered. Recently, the TREC-CDS track has addressed this challenge by evaluating results of retrieving relevant scientific articles where the answers of medical questions in support of CDS can be found. Although retrieving relevant medical articles instead of identifying the answers was believed to be an easier task, state-of-the-art results are not yet sufficiently promising. In this paper, we present a novel framework for answering medical questions in the spirit of TREC-CDS by first discovering the answer and then selecting and ranking scientific articles that contain the answer. Answer discovery is the result of probabilistic inference which operates on a probabilistic knowledge graph, automatically generated by processing the medical language of large collections of electronic medical records (EMRs). The probabilistic inference of answers combines knowledge from medical practice (EMRs) with knowledge from medical research (scientific articles). It also takes into account the medical knowledge automatically discerned from the medical case description. We show that this novel form of medical question answering (Q/A) produces very promising results in (a) identifying accurately the answers and (b) it improves medical article ranking by 40%. PMID:28758046

  20. The evidence-based clinical decision support guide: mucogingival/esthetics making clinical decisions in the absence of strong evidence.

    PubMed

    Merijohn, George K

    2007-09-01

    Although evidence-based decision-making in dentistry is quickly evolving, large gaps remain in our clinical knowledge base regarding every day decisions and procedures. Especially in the absence of strong evidence, as is the case with mucogingival conditions, risk assessment and identification are important components of the clinical decision-making process. Utilization of clinical decision support (CDS) guides, frameworks and systems enhances chairside decision-making and improves delivery of patient care. This article introduces an Evidence-Based Clinical Decision Support Guide for mucogingival/esthetic situations. This CDS guide delineates treatment strategies based upon evidence-based risk assessment and when possible, risk management. It provides the clinician with a framework that will support decision-making at the point of care. Recommendations for consultation, treatment and referral are reviewed.

  1. 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

  2. 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…

  3. Can Gait Signatures Provide Quantitative Measures for Aiding Clinical Decision-Making? A Systematic Meta-Analysis of Gait Variability Behavior in Patients with Parkinson's Disease

    PubMed Central

    König, Niklas; Singh, Navrag B.; Baumann, Christian R.; Taylor, William R.

    2016-01-01

    A disturbed, inconsistent walking pattern is a common feature of patients with Parkinson's disease (PwPD). Such extreme variability in both temporal and spatial parameters of gait has been associated with unstable walking and an elevated prevalence of falls. However, despite their ability to discretise healthy from pathological function, normative variability values for key gait parameters are still missing. Furthermore, an understanding of each parameter's response to pathology, as well as the inter-parameter relationships, has received little attention. The aim of this systematic literature review and meta-analysis was therefore to define threshold levels for pathological gait variability as well as to investigate whether all gait parameters are equally perturbed in PwPD. Based on a broader systematic literature search that included 13′195 titles, 34 studies addressed Parkinson's disease, presenting 800 PwPD and 854 healthy subjects. Eight gait parameters were compared, of which six showed increased levels of variability during walking in PwPD. The most commonly reported parameter, coefficient of variation of stride time, revealed an upper threshold of 2.4% to discriminate the two groups. Variability of step width, however, was consistently lower in PwPD compared to healthy subjects, and therefore suggests an explicit sensory motor system control mechanism to prioritize balance during walking. The results provide a clear functional threshold for monitoring treatment efficacy in patients with Parkinson's disease. More importantly, however, quantification of specific functional deficits could well provide a basis for locating the source and extent of the neurological damage, and therefore aid clinical decision-making for individualizing therapies. PMID:27445759

  4. Advancing Alternative Analysis: Integration of Decision Science.

    PubMed

    Malloy, Timothy F; Zaunbrecher, Virginia M; Batteate, Christina M; Blake, Ann; Carroll, William F; Corbett, Charles J; Hansen, Steffen Foss; Lempert, Robert J; Linkov, Igor; McFadden, Roger; Moran, Kelly D; Olivetti, Elsa; Ostrom, Nancy K; Romero, Michelle; Schoenung, Julie M; Seager, Thomas P; Sinsheimer, Peter; Thayer, Kristina A

    2017-06-13

    Decision analysis-a systematic approach to solving complex problems-offers tools and frameworks to support decision making that are increasingly being applied to environmental challenges. Alternatives analysis is a method used in regulation and product design to identify, compare, and evaluate the safety and viability of potential substitutes for hazardous chemicals. We assessed whether decision science may assist the alternatives analysis decision maker in comparing alternatives across a range of metrics. A workshop was convened that included representatives from government, academia, business, and civil society and included experts in toxicology, decision science, alternatives assessment, engineering, and law and policy. Participants were divided into two groups and were prompted with targeted questions. Throughout the workshop, the groups periodically came together in plenary sessions to reflect on other groups' findings. We concluded that the further incorporation of decision science into alternatives analysis would advance the ability of companies and regulators to select alternatives to harmful ingredients and would also advance the science of decision analysis. We advance four recommendations: a) engaging the systematic development and evaluation of decision approaches and tools; b) using case studies to advance the integration of decision analysis into alternatives analysis; c) supporting transdisciplinary research; and d) supporting education and outreach efforts. https://doi.org/10.1289/EHP483.

  5. Advancing Alternative Analysis: Integration of Decision Science.

    PubMed

    Malloy, Timothy F; Zaunbrecher, Virginia M; Batteate, Christina; Blake, Ann; Carroll, William F; Corbett, Charles J; Hansen, Steffen Foss; Lempert, Robert; Linkov, Igor; McFadden, Roger; Moran, Kelly D; Olivetti, Elsa; Ostrom, Nancy; Romero, Michelle; Schoenung, Julie; Seager, Thomas; Sinsheimer, Peter; Thayer, Kristina

    2016-10-28

    Decision analysis-a systematic approach to solving complex problems-offers tools and frameworks to support decision making that are increasingly being applied to environmental challenges. Alternatives analysis is a method used in regulation and product design to identify, compare, and evaluate the safety and viability of potential substitutes for hazardous chemicals. Assess whether decision science may assist the alternatives analysis decision maker in comparing alternatives across a range of metrics. A workshop was convened that included representatives from government, academia, business, and civil society and included experts in toxicology, decision science, alternatives assessment, engineering, and law and policy. Participants were divided into two groups and prompted with targeted questions. Throughout the workshop, the groups periodically came together in plenary sessions to reflect on other groups' findings. We conclude the further incorporation of decision science into alternatives analysis would advance the ability of companies and regulators to select alternatives to harmful ingredients, and would also advance the science of decision analysis. We advance four recommendations: (1) engaging the systematic development and evaluation of decision approaches and tools; (2) using case studies to advance the integration of decision analysis into alternatives analysis; (3) supporting transdisciplinary research; and (4) supporting education and outreach efforts.

  6. Application of multicriteria decision analysis in environmental decision making.

    PubMed

    Kiker, Gregory A; Bridges, Todd S; Varghese, Arun; Seager, P Thomas P; Linkov, Igor

    2005-04-01

    Decision making in environmental projects can be complex and seemingly intractable, principally because of the inherent trade-offs between sociopolitical, environmental, ecological, and economic factors. The selection of appropriate remedial and abatement strategies for contaminated sites, land use planning, and regulatory processes often involves multiple additional criteria such as the distribution of costs and benefits, environmental impacts for different populations, safety, ecological risk, or human values. Some of these criteria cannot be easily condensed into a monetary value, partly because environmental concerns often involve ethical and moral principles that may not be related to any economic use or value. Furthermore, even if it were possible to aggregate multiple criteria rankings into a common unit, this approach would not always be desirable because the ability to track conflicting stakeholder preferences may be lost in the process. Consequently, selecting from among many different alternatives often involves making trade-offs that fail to satisfy 1 or more stakeholder groups. Nevertheless, considerable research in the area of multicriteria decision analysis (MCDA) has made available practical methods for applying scientific decision theoretical approaches to complex multicriteria problems. This paper presents a review of the available literature and provides recommendations for applying MCDA techniques in environmental projects. A generalized framework for decision analysis is proposed to highlight the fundamental ingredients for more structured and tractable environmental decision making.

  7. THE CAUSAL ANALYSIS / DIAGNOSIS DECISION ...

    EPA Pesticide Factsheets

    CADDIS is an on-line decision support system that helps investigators in the regions, states and tribes find, access, organize, use and share information to produce causal evaluations in aquatic systems. It is based on the US EPA's Stressor Identification process which is a formal method for identifying causes of impairments in aquatic systems. CADDIS 2007 increases access to relevant information useful for causal analysis and provides methods and tools that practitioners can use to analyze their own data. The new Candidate Cause section provides overviews of commonly encountered causes of impairments to aquatic systems: metals, sediments, nutrients, flow alteration, temperature, ionic strength, and low dissolved oxygen. CADDIS includes new Conceptual Models that illustrate the relationships from sources to stressors to biological effects. An Interactive Conceptual Model for phosphorus links the diagram with supporting literature citations. The new Analyzing Data section helps practitioners analyze their data sets and interpret and use those results as evidence within the USEPA causal assessment process. Downloadable tools include a graphical user interface statistical package (CADStat), and programs for use with the freeware R statistical package, and a Microsoft Excel template. These tools can be used to quantify associations between causes and biological impairments using innovative methods such as species-sensitivity distributions, biological inferenc

  8. THE CAUSAL ANALYSIS / DIAGNOSIS DECISION ...

    EPA Pesticide Factsheets

    CADDIS is an on-line decision support system that helps investigators in the regions, states and tribes find, access, organize, use and share information to produce causal evaluations in aquatic systems. It is based on the US EPA's Stressor Identification process which is a formal method for identifying causes of impairments in aquatic systems. CADDIS 2007 increases access to relevant information useful for causal analysis and provides methods and tools that practitioners can use to analyze their own data. The new Candidate Cause section provides overviews of commonly encountered causes of impairments to aquatic systems: metals, sediments, nutrients, flow alteration, temperature, ionic strength, and low dissolved oxygen. CADDIS includes new Conceptual Models that illustrate the relationships from sources to stressors to biological effects. An Interactive Conceptual Model for phosphorus links the diagram with supporting literature citations. The new Analyzing Data section helps practitioners analyze their data sets and interpret and use those results as evidence within the USEPA causal assessment process. Downloadable tools include a graphical user interface statistical package (CADStat), and programs for use with the freeware R statistical package, and a Microsoft Excel template. These tools can be used to quantify associations between causes and biological impairments using innovative methods such as species-sensitivity distributions, biological inferenc

  9. 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.

  10. Clinical models of decision making in addiction.

    PubMed

    Koffarnus, Mikhail N; Kaplan, Brent A

    2017-08-26

    As research on decision making in addiction accumulates, it is increasingly clear that decision-making processes are dysfunctional in addiction and that this dysfunction may be fundamental to the initiation and maintenance of addictive behavior. How drug-dependent individuals value and choose among drug and nondrug rewards is consistently different from non-dependent individuals. The present review focuses on the assessment of decision-making in addiction. We cover the common behavioral tasks that have shown to be fruitful in decision-making research and highlight analytical and graphical considerations, when available, to facilitate comparisons within and among studies. Delay discounting tasks, drug demand tasks, drug choice tasks, the Iowa Gambling Task, and the Balloon Analogue Risk Task are included. Copyright © 2017 Elsevier Inc. All rights reserved.

  11. 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

    Purpose To examine nurses’ self-reported use of race in clinical evaluation. Design 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. Methods Multivariate regression analysis was used to examine associations between RACE score and individual-level characteristics and beliefs in 5,733 registered nurses. Findings 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). Conclusions 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

  12. Understanding The Decision Context: DPSIR, Decision Landscape, And Social Network Analysis

    EPA Science Inventory

    Establishing the decision context for a management problem is the critical first step for effective decision analysis. Understanding the decision context allow stakeholders and decision-makers to integrate the societal, environmental, and economic considerations that must be con...

  13. Understanding The Decision Context: DPSIR, Decision Landscape, And Social Network Analysis

    EPA Science Inventory

    Establishing the decision context for a management problem is the critical first step for effective decision analysis. Understanding the decision context allow stakeholders and decision-makers to integrate the societal, environmental, and economic considerations that must be con...

  14. Data Decision Analysis: Project Shoal

    SciTech Connect

    Forsgren, Frank; Pohll, Greg; Tracy, John

    1999-01-01

    The purpose of this study was to determine the most appropriate field activities in terms of reducing the uncertainty in the groundwater flow and transport model at the Project Shoal area. The data decision analysis relied on well-known tools of statistics and uncertainty analysis. This procedure identified nine parameters that were deemed uncertain. These included effective porosity, hydraulic head, surface recharge, hydraulic conductivity, fracture correlation scale, fracture orientation, dip angle, dissolution rate of radionuclides from the puddle glass, and the retardation coefficient, which describes the sorption characteristics. The parameter uncertainty was described by assigning prior distributions for each of these parameters. Next, the various field activities were identified that would provide additional information on these parameters. Each of the field activities was evaluated by an expert panel to estimate posterior distribution of the parameters assuming a field activity was performed. The posterior distributions describe the ability of the field activity to estimate the true value of the nine parameters. Monte Carlo techniques were used to determine the current uncertainty, the reduction of uncertainty if a single parameter was known with certainty, and the reduction of uncertainty expected from each field activity on the model predictions. The mean breakthrough time to the downgradient land withdrawal boundary and the peak concentration at the control boundary were used to evaluate the uncertainty reduction. The radionuclide 137Cs was used as the reference solute, as its migration is dependent on all of the parameters. The results indicate that the current uncertainty of the model yields a 95 percent confidence interval between 42 and 1,412 years for the mean breakthrough time and an 18 order-of-magnitude range in peak concentration. The uncertainty in effective porosity and recharge dominates the uncertainty in the model predictions, while the

  15. Personalizing Drug Selection Using Advanced Clinical Decision Support.

    PubMed

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

    2009-06-23

    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.

  16. 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

  17. Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to success

    PubMed Central

    Kawamoto, Kensaku; Houlihan, Caitlin A; Balas, E Andrew; Lobach, David F

    2005-01-01

    Objective To identify features of clinical decision support systems critical for improving clinical practice. Design Systematic review of randomised controlled trials. Data sources Literature searches via Medline, CINAHL, and the Cochrane Controlled Trials Register up to 2003; and searches of reference lists of included studies and relevant reviews. Study selection Studies had to evaluate the ability of decision support systems to improve clinical practice. Data extraction Studies were assessed for statistically and clinically significant improvement in clinical practice and for the presence of 15 decision support system features whose importance had been repeatedly suggested in the literature. Results Seventy studies were included. Decision support systems significantly improved clinical practice in 68% of trials. Univariate analyses revealed that, for five of the system features, interventions possessing the feature were significantly more likely to improve clinical practice than interventions lacking the feature. Multiple logistic regression analysis identified four features as independent predictors of improved clinical practice: automatic provision of decision support as part of clinician workflow (P < 0.00001), provision of recommendations rather than just assessments (P = 0.0187), provision of decision support at the time and location of decision making (P = 0.0263), and computer based decision support (P = 0.0294). Of 32 systems possessing all four features, 30 (94%) significantly improved clinical practice. Furthermore, direct experimental justification was found for providing periodic performance feedback, sharing recommendations with patients, and requesting documentation of reasons for not following recommendations. Conclusions Several features were closely correlated with decision support systems' ability to improve patient care significantly. Clinicians and other stakeholders should implement clinical decision support systems that incorporate these

  18. 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.

  19. 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

  20. 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

  1. Patient decision-making for clinical genetics.

    PubMed

    Anderson, Gwen

    2007-03-01

    Medicine is incorporating genetic services into all avenues of health-care, ranging from the rarest to the most common diseases. Cognitive theories of decision-making still dominate professionals' understanding of patient decision-making about how to use genetic information and whether to have testing. I discovered a conceptual model of decision-making while carrying out a phenomenological-hermeneutic descriptive study of a convenience sample of 12 couples who were interviewed while deciding whether to undergo prenatal genetic testing. Thirty-two interviews were conducted with 12 men and 12 women separately. Interviews were transcribed verbatim and all data were analyzed using three levels of coding that were sorted into 30 categories and then abstracted into three emergent meta-themes that described men's and women's attempts to make sense and find meaning in how to best use prenatal genetic technology. Their descriptions of how they thought about, communicated, and coped with their decision were so detailed it was possible to discern nine different types of thinking they engaged in while deciding to accept or decline testing. They believed that decision-making is a process of working through your own personal style of thinking. This might include only one or any combination of the following types of thinking: analytical, ethical, moral, reflective, practical, hypothetical, judgmental, scary, and second sight, as described in detail by these 12 couples.

  2. 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

  3. Encounter Decision Aid vs. Clinical Decision Support or Usual Care to Support Patient-Centered Treatment Decisions in Osteoporosis: The Osteoporosis Choice Randomized Trial II.

    PubMed

    LeBlanc, Annie; Wang, Amy T; Wyatt, Kirk; Branda, Megan E; Shah, Nilay D; Van Houten, Holly; Pencille, Laurie; Wermers, Robert; Montori, Victor M

    2015-01-01

    Osteoporosis Choice, an encounter decision aid, can engage patients and clinicians in shared decision making about osteoporosis treatment. Its effectiveness compared to the routine provision to clinicians of the patient's estimated risk of fracture using the FRAX calculator is unknown. Patient-level, randomized, three-arm trial enrolling women over 50 with osteopenia or osteoporosis eligible for treatment with bisphosphonates, where the use of Osteoporosis Choice was compared to FRAX only and to usual care to determine impact on patient knowledge, decisional conflict, involvement in the decision-making process, decision to start and adherence to bisphosphonates. We enrolled 79 women in the three arms. Because FRAX estimation alone and usual care produced similar results, we grouped them for analysis. Compared to these, use of Osteoporosis Choice increased patient knowledge (median score 6 vs. 4, p = .01), improved understanding of fracture risk and risk reduction with bisphosphonates (p = .01 and p<.0001, respectively), had no effect on decision conflict, and increased patient engagement in the decision making process (OPTION scores 57% vs. 43%, p = .001). Encounters with the decision aid were 0.8 minutes longer (range: 33 minutes shorter to 3.0 minutes longer). There were twice as many patients receiving and filling prescriptions in the decision aid arm (83% vs. 40%, p = .07); medication adherence at 6 months was no different across arms. Supporting both patients and clinicians during the clinical encounter with the Osteoporosis Choice decision aid efficiently improves treatment decision making when compared to usual care with or without clinical decision support with FRAX results. clinical trials.gov NCT00949611.

  4. Clinical inferences and decisions--III. Utility assessment and the Bayesian decision model.

    PubMed

    Aspinall, P A; Hill, A R

    1984-01-01

    It is accepted that errors of misclassifications, however small, can occur in clinical decisions but it cannot be assumed that the importance associated with false positive errors is the same as that for false negatives. The relative importance of these two types of error is frequently implied by a decision maker in the different weighting factors or utilities he assigns to the alternative consequences of his decisions. Formal procedures are available by which it is possible to make explicit in numerical form the value or worth of the outcome of a decision process. The two principal methods are described for generating utilities as associated with clinical decisions. The concept and application of utility is then expanded from a unidimensional to a multidimensional problem where, for example, one variable may be state of health and another monetary assets. When combined with the principles of subjective probability and test criterion selection outlined in Parts I and II of this series, the consequent use of utilities completes the framework upon which the general Bayesian model of clinical decision making is based. The five main stages in this general decision making model are described and applications of the model are illustrated with clinical examples from the field of ophthalmology. These include examples for unidimensional and multidimensional problems which are worked through in detail to illustrate both the principles and methodology involved in a rationalized normative model of clinical decision making behaviour.

  5. 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

  6. Patient participation in palliative care decisions: An ethnographic discourse analysis

    PubMed Central

    Bélanger, Emmanuelle; Rodríguez, Charo; Groleau, Danielle; Légaré, France; MacDonald, Mary Ellen; Marchand, Robert

    2016-01-01

    The participation of patients in making decisions about their care is especially important towards the end of life because palliative care decisions involve extensive uncertainty and are heavily influenced by personal values. Yet, there is a scarcity of studies directly observing clinical interactions between palliative patients and their health care providers. In this study, we aimed to understand how patient participation in palliative care decisions is constructed through discourse in a community hospital-based palliative care team. This qualitative study combined ethnographic observations of a palliative care team with discourse analysis. Eighteen palliative care patients with cancer diagnoses, six family physicians, and two nurses were involved in the study. Multiple interactions were observed between each patient and health care providers over the course of 1 year, for a total of 101 consultations, 24 of which were audio-recorded. The analysis consisted in looking for the interpretive repertoires (i.e., familiar lines of argument used to justify actions) that were used to justify patient participation in decision-making during clinical interactions, as well as exploring their implications for decision roles and end-of-life care. Patients and their health care providers seldom addressed their decision-making roles explicitly. Rather, they constructed patient participation in palliative care decisions in a covert manner. Four interpretive repertoires were used to justify patient participation: (1) exposing uncertainty, (2) co-constructing patient preferences, (3) affirming patient autonomy, and finally (4) upholding the authority of health care providers. The results demonstrate how patients and health care providers used these arguments to negotiate their respective roles in decision-making. In conclusion, patients and health care providers used a variety of interpretive repertoires to covertly negotiate their roles in decision-making, and to legitimize

  7. Patient participation in palliative care decisions: An ethnographic discourse analysis.

    PubMed

    Bélanger, Emmanuelle; Rodríguez, Charo; Groleau, Danielle; Légaré, France; MacDonald, Mary Ellen; Marchand, Robert

    2016-01-01

    The participation of patients in making decisions about their care is especially important towards the end of life because palliative care decisions involve extensive uncertainty and are heavily influenced by personal values. Yet, there is a scarcity of studies directly observing clinical interactions between palliative patients and their health care providers. In this study, we aimed to understand how patient participation in palliative care decisions is constructed through discourse in a community hospital-based palliative care team. This qualitative study combined ethnographic observations of a palliative care team with discourse analysis. Eighteen palliative care patients with cancer diagnoses, six family physicians, and two nurses were involved in the study. Multiple interactions were observed between each patient and health care providers over the course of 1 year, for a total of 101 consultations, 24 of which were audio-recorded. The analysis consisted in looking for the interpretive repertoires (i.e., familiar lines of argument used to justify actions) that were used to justify patient participation in decision-making during clinical interactions, as well as exploring their implications for decision roles and end-of-life care. Patients and their health care providers seldom addressed their decision-making roles explicitly. Rather, they constructed patient participation in palliative care decisions in a covert manner. Four interpretive repertoires were used to justify patient participation: (1) exposing uncertainty, (2) co-constructing patient preferences, (3) affirming patient autonomy, and finally (4) upholding the authority of health care providers. The results demonstrate how patients and health care providers used these arguments to negotiate their respective roles in decision-making. In conclusion, patients and health care providers used a variety of interpretive repertoires to covertly negotiate their roles in decision-making, and to legitimize

  8. Decision aids for people considering taking part in clinical trials.

    PubMed

    Gillies, Katie; Cotton, Seonaidh C; Brehaut, Jamie C; Politi, Mary C; Skea, Zoe

    2015-11-27

    Several interventions have been developed to promote informed consent for participants in clinical trials. However, many of these interventions focus on the content and structure of information (e.g. enhanced information or changes to the presentation format) rather than the process of decision making. Patient decision aids support a decision making process about medical options. Decision aids support the decision process by providing information about available options and their associated outcomes, alongside information that enables patients to consider what value they place on particular outcomes, and provide structured guidance on steps of decision making. They have been shown to be effective for treatment and screening decisions but evidence on their effectiveness in the context of informed consent for clinical trials has not been synthesised. To assess the effectiveness of decision aids for clinical trial informed consent compared to no intervention, standard information (i.e. usual practice) or an alternative intervention on the decision making process. We searched the following databases and to March 2015: Cochrane Central Register of Controlled Trials (CENTRAL), The Cochrane Library; MEDLINE (OvidSP) (from 1950); EMBASE (OvidSP) (from 1980); PsycINFO (OvidSP) (from 1806); ASSIA (ProQuest) (from 1987); WHO International Clinical Trials Registry Platform (ICTRP) (http://apps.who.int/trialsearch/); ClinicalTrials.gov; ISRCTN Register (http://www.controlled-trials.com/isrctn/). We also searched reference lists of included studies and relevant reviews. We contacted study authors and other experts. There were no language restrictions. We included randomised and quasi-randomised controlled trials comparing decision aids in the informed consent process for clinical trials alone, or in conjunction with standard information (such as written or verbal) or alongside alternative interventions (e.g. paper-based versus web-based decision aids). Included trials involved

  9. Decision modeling for fire incident analysis

    Treesearch

    Donald G. MacGregor; Armando González-Cabán

    2009-01-01

    This paper reports on methods for representing and modeling fire incidents based on concepts and models from the decision and risk sciences. A set of modeling techniques are used to characterize key fire management decision processes and provide a basis for incident analysis. The results of these methods can be used to provide insights into the structure of fire...

  10. Clinical Decision Making among Dental Students and General Practitioners.

    ERIC Educational Resources Information Center

    Grembowski, David; And Others

    1989-01-01

    Senior dental students and family dental practitioners were surveyed concerning their choice of pairs of alternative treatments and the technical and patient factors influencing their decisions. Greater agreement in clinical decision-making was found among dentists than among students for all four pairs of alternative services. (MSE)

  11. Computers in pharmacokinetics. Choosing software for clinical decision making.

    PubMed

    Buffington, D E; Lampasona, V; Chandler, M H

    1993-09-01

    Over the past 20 years, pharmacokinetic programs have been developed for clinical decision making. These clinical pharmacokinetic software programs are designed to assist the clinician in the analysis, interpretation and reporting of serum drug concentration data for a variety of medications. The programs vary in the extent of features and range of medications supported and thus warrant careful review before selecting or purchasing such a program for routine use. A series of programs which are commercially available in the United States was reviewed for this article. The focus of the review is not to recommend a single program or to provide a ranked list of commercially available programs. Information is presented to clinicians to better their understanding of the features of these computer-based clinical resources. As an introduction to this topic, the information presented concentrates on the system and support features. Those programs that were reviewed demonstrate the ability to assist in the analysis of serum or plasma drug concentration data for most of the medications that warrant therapeutic drug monitoring. They provide both Bayesian and non-Bayesian methods for predicting serum drug concentrations. Standard personal computers were sufficient to run each of the programs reviewed. In addition, most programs offered technical and clinical support. However, the quality of the user manuals and training material varies among software programs. In-depth analytical comparisons are currently being conducted for future publication.

  12. Recreational Boating Safety: Analysis for Programmatic Decisions.

    DTIC Science & Technology

    1984-04-01

    AFD-AI147 661 RECREATIONAL BORTING SAFETY: ANALYSIS FOR PROGRAMMATIC L/2 DECISIONS(U) MANDEX INC MCLEAN VA L GREENBERG ET AL. APR 84 USCG-D-9-84...CHART NATIONAL *IUIItAU Of SANOAS - It3 - A =.. ... Report No. CG-D-9-84 • • RECREATIONAL BOATING SAFETY ANALYSIS FOR PROGRAMMATIC DECISIONS 6 0 I...orDt . Title and Subtitle5.,,,or , April 1984 0 Recreational Boating Safety: 6. PerformingOrganization Coat Analysis for Programmatic Decisions 1 8

  13. Patient-reported outcomes in randomised controlled trials of colorectal cancer: an analysis determining the availability of robust data to inform clinical decision-making

    PubMed Central

    Whale, Katie; Fish, Daniel; Fayers, Peter; Cafaro, Valentina; Pusic, Andrea; Blazeby, Jane M.; Efficace, Fabio

    2016-01-01

    Purpose Randomised controlled trials (RCTs) are the most robust study design measuring outcomes of colorectal cancer (CRC) treatments, but to influence clinical practice trial design and reporting of patient-reported outcomes (PROs) must be of high quality. Objectives of this study were as follows: to examine the quality of PRO reporting in RCTs of CRC treatment; to assess the availability of robust data to inform clinical decision-making; and to investigate whether quality of reporting improved over time. Methods A systematic review from January 2004–February 2012 identified RCTs of CRC treatment describing PROs. Relevant abstracts were screened and manuscripts obtained. Methodological quality was assessed using International Society for Quality of Life Research—patient-reported outcome reporting standards. Changes in reporting quality over time were established by comparison with previous data, and risk of bias was assessed with the Cochrane risk of bias tool. Results Sixty-six RCTs were identified, seven studies (10 %) reported survival benefit favouring the experimental treatment, 35 trials (53 %) identified differences in PROs between treatment groups, and the clinical significance of these differences was discussed in 19 studies (29 %). The most commonly reported treatment type was chemotherapy (n = 45; 68 %). Improvements over time in key methodological issues including the documentation of missing data and the discussion of the clinical significance of PROs were found. Thirteen trials (20 %) had high-quality reporting. Conclusions Whilst improvements in PRO quality reporting over time were found, several recent studies still fail to robustly inform clinical practice. Quality of PRO reporting must continue to improve to maximise the clinical impact of PRO findings. PMID:25910987

  14. The reliability of an epilepsy treatment clinical decision support system.

    PubMed

    Standridge, Shannon; Faist, Robert; Pestian, John; Glauser, Tracy; Ittenbach, Richard

    2014-10-01

    We developed a content validated computerized epilepsy treatment clinical decision support system to assist clinicians with selecting the best antiepilepsy treatments. Before disseminating our computerized epilepsy treatment clinical decision support system, further rigorous validation testing was necessary. As reliability is a precondition of validity, we verified proof of reliability first. We evaluated the consistency of the epilepsy treatment clinical decision support system in three areas including the preferred antiepilepsy drug choice, the top three recommended choices, and the rank order of the three choices. We demonstrated 100% reliability on 15,000 executions involving a three-step process on five different common pediatric epilepsy syndromes. Evidence for the reliability of the epilepsy treatment clinical decision support system was essential for the long-term viability of the system, and served as a crucial component for the next phase of system validation.

  15. 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.

  16. Clinical model for ethical cardiopulmonary resuscitation decision-making.

    PubMed

    Hayes, B

    2013-01-01

    Decisions to withhold cardiopulmonary resuscitation (CPR) for future cardiac arrest continue to be problematic, with a lack of consistency in how doctors approach this decision. To develop a clinical model that can be used in education to improve consistency in CPR decision-making. A qualitative study, using semistructured interviews with a total of 33 senior doctors, junior doctors and nurses from two Melbourne hospitals explored how decisions to withhold CPR are made. Interviews explored: issues arising; how doctors learn to make these decisions; how they deal with disagreement and their experiences of performing CPR. The transcripts were coded and analysed thematically. Three major themes were identified: CPR as a life-and-death decision; good and bad dying; and trust. The research also defined the two elements to a CPR decision: (i) technical and (ii) ethical. Applying ethical principles commonly used in medicine, a model for ethical CPR decision-making has been developed that identifies four patient groups, each with a different discussion aim. This approach simplifies the complexities of the CPR decision, providing a structured way to teach CPR decision-making to doctors and thereby achieve greater consistency in the decisions made. © 2012 The Author; Internal Medicine Journal © 2012 Royal Australasian College of Physicians.

  17. [International outcomes from attempts to implement a clinical decision support system in gastroenterology].

    PubMed

    Tenório, Josceli Maria; Hummel, Anderson Diniz; Sdepanian, Vera Lucia; Pisa, Ivan Torres; de Fátima Marin, Heimar

    2011-01-01

    This study aimed at describing the recent experience acquired with the implementation and use of clinical decision support system in gastroenterology in order to determine the level of development, tests used and advantages that such a system can offer to the medical practice. A search in the PubMed, LILACS and ISI Web of Knowledge databases for studies in decision-making support systems in gastroenterology including original papers produced from 2005 to 2010 was performed. A total of 104 scientific papers were retrieved initially. These were analyzed using inclusion and exclusion criteria, thus yielding nine studies for further analysis. The clinical decision support system analyzed in the present study showed a great variety of clinical problems regarding the investigation of a disease and the determination of a diagnosis. Eighty-nine per cent of the studies showed experimental models for clinical decision support system development. Seventy-eight per cent of the studies described the outcomes obtained with artificial intelligence technique. Two studies compared the clinical decision support system performance with that of a doctor, and only one research work described a controlled study evidencing improvements in the medical practice. The studies analyzed showed evidence of potential benefits that clinical decision support system can bring to the clinical practice. However, further controlled studies performed in medical day-to-day conditions and environment should be performed in order to provide more clear evidence of the usefulness of clinical decision support system in the medical practice.

  18. A Framework and Model for Evaluating Clinical Decision Support Architectures

    PubMed Central

    Wright, Adam; Sittig, Dean F.

    2008-01-01

    In this paper, we develop a four-phase model for evaluating architectures for clinical decision support that focuses on: defining a set of desirable features for a decision support architecture; building a proof-of-concept prototype; demonstrating that the architecture is useful by showing that it can be integrated with existing decision support systems and comparing its coverage to that of other architectures. We apply this framework to several well-known decision support architectures, including Arden Syntax, GLIF, SEBASTIAN and SAGE PMID:18462999

  19. Making Good Decisions in Healthcare with Multi-Criteria Decision Analysis: The Use, Current Research and Future Development of MCDA.

    PubMed

    Mühlbacher, Axel C; Kaczynski, Anika

    2016-02-01

    Healthcare decision making is usually characterized by a low degree of transparency. The demand for transparent decision processes can be fulfilled only when assessment, appraisal and decisions about health technologies are performed under a systematic construct of benefit assessment. The benefit of an intervention is often multidimensional and, thus, must be represented by several decision criteria. Complex decision problems require an assessment and appraisal of various criteria; therefore, a decision process that systematically identifies the best available alternative and enables an optimal and transparent decision is needed. For that reason, decision criteria must be weighted and goal achievement must be scored for all alternatives. Methods of multi-criteria decision analysis (MCDA) are available to analyse and appraise multiple clinical endpoints and structure complex decision problems in healthcare decision making. By means of MCDA, value judgments, priorities and preferences of patients, insurees and experts can be integrated systematically and transparently into the decision-making process. This article describes the MCDA framework and identifies potential areas where MCDA can be of use (e.g. approval, guidelines and reimbursement/pricing of health technologies). A literature search was performed to identify current research in healthcare. The results showed that healthcare decision making is addressing the problem of multiple decision criteria and is focusing on the future development and use of techniques to weight and score different decision criteria. This article emphasizes the use and future benefit of MCDA.

  20. How decision analysis can further nanoinformatics.

    PubMed

    Bates, Matthew E; Larkin, Sabrina; Keisler, Jeffrey M; Linkov, Igor

    2015-01-01

    The increase in nanomaterial research has resulted in increased nanomaterial data. The next challenge is to meaningfully integrate and interpret these data for better and more efficient decisions. Due to the complex nature of nanomaterials, rapid changes in technology, and disunified testing and data publishing strategies, information regarding material properties is often illusive, uncertain, and/or of varying quality, which limits the ability of researchers and regulatory agencies to process and use the data. The vision of nanoinformatics is to address this problem by identifying the information necessary to support specific decisions (a top-down approach) and collecting and visualizing these relevant data (a bottom-up approach). Current nanoinformatics efforts, however, have yet to efficiently focus data acquisition efforts on the research most relevant for bridging specific nanomaterial data gaps. Collecting unnecessary data and visualizing irrelevant information are expensive activities that overwhelm decision makers. We propose that the decision analytic techniques of multicriteria decision analysis (MCDA), value of information (VOI), weight of evidence (WOE), and portfolio decision analysis (PDA) can bridge the gap from current data collection and visualization efforts to present information relevant to specific decision needs. Decision analytic and Bayesian models could be a natural extension of mechanistic and statistical models for nanoinformatics practitioners to master in solving complex nanotechnology challenges.

  1. How decision analysis can further nanoinformatics

    PubMed Central

    Bates, Matthew E; Larkin, Sabrina; Keisler, Jeffrey M

    2015-01-01

    Summary The increase in nanomaterial research has resulted in increased nanomaterial data. The next challenge is to meaningfully integrate and interpret these data for better and more efficient decisions. Due to the complex nature of nanomaterials, rapid changes in technology, and disunified testing and data publishing strategies, information regarding material properties is often illusive, uncertain, and/or of varying quality, which limits the ability of researchers and regulatory agencies to process and use the data. The vision of nanoinformatics is to address this problem by identifying the information necessary to support specific decisions (a top-down approach) and collecting and visualizing these relevant data (a bottom-up approach). Current nanoinformatics efforts, however, have yet to efficiently focus data acquisition efforts on the research most relevant for bridging specific nanomaterial data gaps. Collecting unnecessary data and visualizing irrelevant information are expensive activities that overwhelm decision makers. We propose that the decision analytic techniques of multicriteria decision analysis (MCDA), value of information (VOI), weight of evidence (WOE), and portfolio decision analysis (PDA) can bridge the gap from current data collection and visualization efforts to present information relevant to specific decision needs. Decision analytic and Bayesian models could be a natural extension of mechanistic and statistical models for nanoinformatics practitioners to master in solving complex nanotechnology challenges. PMID:26425410

  2. A regret theory approach to decision curve analysis: A novel method for eliciting decision makers' preferences and decision-making

    PubMed Central

    2010-01-01

    Background Decision curve analysis (DCA) has been proposed as an alternative method for evaluation of diagnostic tests, prediction models, and molecular markers. However, DCA is based on expected utility theory, which has been routinely violated by decision makers. Decision-making is governed by intuition (system 1), and analytical, deliberative process (system 2), thus, rational decision-making should reflect both formal principles of rationality and intuition about good decisions. We use the cognitive emotion of regret to serve as a link between systems 1 and 2 and to reformulate DCA. Methods First, we analysed a classic decision tree describing three decision alternatives: treat, do not treat, and treat or no treat based on a predictive model. We then computed the expected regret for each of these alternatives as the difference between the utility of the action taken and the utility of the action that, in retrospect, should have been taken. For any pair of strategies, we measure the difference in net expected regret. Finally, we employ the concept of acceptable regret to identify the circumstances under which a potentially wrong strategy is tolerable to a decision-maker. Results We developed a novel dual visual analog scale to describe the relationship between regret associated with "omissions" (e.g. failure to treat) vs. "commissions" (e.g. treating unnecessary) and decision maker's preferences as expressed in terms of threshold probability. We then proved that the Net Expected Regret Difference, first presented in this paper, is equivalent to net benefits as described in the original DCA. Based on the concept of acceptable regret we identified the circumstances under which a decision maker tolerates a potentially wrong decision and expressed it in terms of probability of disease. Conclusions We present a novel method for eliciting decision maker's preferences and an alternative derivation of DCA based on regret theory. Our approach may be intuitively more

  3. A regret theory approach to decision curve analysis: a novel method for eliciting decision makers' preferences and decision-making.

    PubMed

    Tsalatsanis, Athanasios; Hozo, Iztok; Vickers, Andrew; Djulbegovic, Benjamin

    2010-09-16

    Decision curve analysis (DCA) has been proposed as an alternative method for evaluation of diagnostic tests, prediction models, and molecular markers. However, DCA is based on expected utility theory, which has been routinely violated by decision makers. Decision-making is governed by intuition (system 1), and analytical, deliberative process (system 2), thus, rational decision-making should reflect both formal principles of rationality and intuition about good decisions. We use the cognitive emotion of regret to serve as a link between systems 1 and 2 and to reformulate DCA. First, we analysed a classic decision tree describing three decision alternatives: treat, do not treat, and treat or no treat based on a predictive model. We then computed the expected regret for each of these alternatives as the difference between the utility of the action taken and the utility of the action that, in retrospect, should have been taken. For any pair of strategies, we measure the difference in net expected regret. Finally, we employ the concept of acceptable regret to identify the circumstances under which a potentially wrong strategy is tolerable to a decision-maker. We developed a novel dual visual analog scale to describe the relationship between regret associated with "omissions" (e.g. failure to treat) vs. "commissions" (e.g. treating unnecessary) and decision maker's preferences as expressed in terms of threshold probability. We then proved that the Net Expected Regret Difference, first presented in this paper, is equivalent to net benefits as described in the original DCA. Based on the concept of acceptable regret we identified the circumstances under which a decision maker tolerates a potentially wrong decision and expressed it in terms of probability of disease. We present a novel method for eliciting decision maker's preferences and an alternative derivation of DCA based on regret theory. Our approach may be intuitively more appealing to a decision-maker, particularly

  4. Workflow-driven clinical decision support for personalized oncology.

    PubMed

    Bucur, Anca; van Leeuwen, Jasper; Christodoulou, Nikolaos; Sigdel, Kamana; Argyri, Katerina; Koumakis, Lefteris; Graf, Norbert; Stamatakos, Georgios

    2016-07-21

    The adoption in oncology of Clinical Decision Support (CDS) may help clinical users to efficiently deal with the high complexity of the domain, lead to improved patient outcomes, and reduce the current knowledge gap between clinical research and practice. While significant effort has been invested in the implementation of CDS, the uptake in the clinic has been limited. The barriers to adoption have been extensively discussed in the literature. In oncology, current CDS solutions are not able to support the complex decisions required for stratification and personalized treatment of patients and to keep up with the high rate of change in therapeutic options and knowledge. To address these challenges, we propose a framework enabling efficient implementation of meaningful CDS that incorporates a large variety of clinical knowledge models to bring to the clinic comprehensive solutions leveraging the latest domain knowledge. We use both literature-based models and models built within the p-medicine project using the rich datasets from clinical trials and care provided by the clinical partners. The framework is open to the biomedical community, enabling reuse of deployed models by third-party CDS implementations and supporting collaboration among modelers, CDS implementers, biomedical researchers and clinicians. To increase adoption and cope with the complexity of patient management in oncology, we also support and leverage the clinical processes adhered to by healthcare organizations. We design an architecture that extends the CDS framework with workflow functionality. The clinical models are embedded in the workflow models and executed at the right time, when and where the recommendations are needed in the clinical process. In this paper we present our CDS framework developed in p-medicine and the CDS implementation leveraging the framework. To support complex decisions, the framework relies on clinical models that encapsulate relevant clinical knowledge. Next to

  5. Software Development for Decision Analysis

    DTIC Science & Technology

    1975-03-01

    34|"𔃻" ’’ " ’■|’■’ J - " ■»—w—"■ ■ 1 »I ■■ »I mill 1 11 1 MI independence (Category 1) or partial Independence (Categories 2 and 3) can >>e...place vandom variable 1 after decision 3 in the tree. In the nuit phase of our research, we hope to develop general algorithms for translating any...nMiu uiiim^p^M (^PLANT EFFICIENCY^ \\~r\\ |1T) % (CAPITAL COSTS Tris ^ /KW (OPERATING COSTS^) r=TTl MILLS /KWH (jmc^lTIQn-j] MILLS /KWH.*’** By

  6. Developing and implementing computerized protocols for standardization of clinical decisions.

    PubMed

    Morris, A H

    2000-03-07

    Humans have only a limited ability to incorporate information in decision making. In certain situations, the mismatch between this limitation and the availability of extensive information contributes to the varying performance and high error rate of clinical decision makers. Variation in clinical practice is due in part to clinicians' poor compliance with guidelines and recommended therapies. The use of decision-support tools is a response to both the information revolution and poor compliance. Computerized protocols used to deliver decision support can be configured to contain much more detail than textual guidelines or paper-based flow diagrams. Such protocols can generate patient-specific instructions for therapy that can be carried out with little interclinician variability; however, clinicians must be willing to modify personal styles of clinical management. Protocols need not be perfect. Several defensible and reasonable approaches are available for clinical problems. However, one of these reasonable approaches must be chosen and incorporated into the protocol to promote consistent clinical decisions. This reasoning is the basis of an explicit method of decision support that allows the rigorous evaluation of interventions, including use of the protocols themselves. Computerized protocols for mechanical ventilation and management of intravenous fluid and hemodynamic factors in patients with the acute respiratory distress syndrome provide case studies for this discussion.

  7. A cost-effectiveness analysis comparing a clinical decision rule versus usual care to risk stratify children for intraabdominal injury after blunt torso trauma.

    PubMed

    Nishijima, Daniel K; Yang, Zhuo; Clark, John A; Kuppermann, Nathan; Holmes, James F; Melnikow, Joy

    2013-11-01

    Recently a clinical decision rule (CDR) to identify children at very low risk for intraabdominal injury needing acute intervention (IAI) following blunt torso trauma was developed. Potential benefits of a CDR include more appropriate abdominal computed tomography (CT) use and decreased hospital costs. The objective of this study was to compare the cost-effectiveness of implementing the CDR compared to usual care for the evaluation of children with blunt torso trauma. The hypothesis was that compared to usual care, implementation of the CDR would result in lower CT use and hospital costs. A cost-effectiveness decision analytic model was constructed comparing the costs and outcomes of implementation of the CDR to usual care in the evaluation of children with blunt torso trauma. Probabilities from a multicenter cohort study of children with blunt torso trauma were derived; estimated costs were based on those at the study coordinating site. Outcome measures included missed IAI, number of abdominal CT scans, total costs, and incremental cost-effectiveness ratios. Sensitivity analyses varying imputed probabilities, costs, and scenarios were conducted. Using a hypothetical cohort of 1,000 children with blunt torso trauma, the base case model projected that the implementation of the CDR would result in 0.50 additional missed IAIs, a total cost savings of $54,527, and 104 fewer abdominal CT scans compared to usual care. The usual care strategy would cost $108,110 to prevent missing one additional IAI. Findings were robust under multiple sensitivity analyses. Compared to usual care, implementation of the CDR in the evaluation of children with blunt torso trauma would reduce hospital costs and abdominal CT imaging, with a slight increase in the risk of missed intraabdominal IAI. © 2013 by the Society for Academic Emergency Medicine.

  8. 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.

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

    PubMed Central

    2016-01-01

    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. PMID:28123917

  10. [Treatment evaluation and clinical decision making using HKT-30-ROM].

    PubMed

    Ter Horst, P; van Ham, M; Spreen, M; Bogaerts, S

    2014-01-01

    By means of repeated, well-supported measurements of clinical dynamic indicators from the Historical, Clinical and Future - 30 (HKT-30) it is possible to monitor behavioural changes on the basis of risks and needs. The addition of extra score parameters allows us to distinguish client-specific risks and needs. In treatment evaluation it is important to visualise changes in these indicators of treatment evaluation because they are the key to the clinical decision-making process that determines further treatment and rehabilitation. To investigate whether HKT-30 indicators can be used to measure and visualise behavioral changes for the purpose of treatment evaluation. A case study is used to illustrate how clinicians at the Forensic Psychiatric Clinic (FPK), De Woenselse Poort, ascertain risks, needs and changes and clarify these factors for the purpose of treatment evaluation and clinical decision-making. Routine treatment evaluation aided by visualised clinical HKT-30 indicators give the treatment team and the client a clearer picture of the behavioral changes for which the forensic treatment was prescribed. This evaluation provides significant starting-points for clinical decision making. Routine treatment evaluation along with a suitably adjusted HKT-30 make behavioural changes visible, render clinical decisions more transparent and provide valuable starting-points for a dialogue with the client about his treatment.

  11. 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…

  12. 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…

  13. 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.

  14. Virtual medical record implementation for enhancing clinical decision support.

    PubMed

    Gomoi, Valentin-Sergiu; Dragu, Daniel; Stoicu-Tivadar, Vasile

    2012-01-01

    Development of clinical decision support systems (CDS) is a process which highly depends on the local databases, this resulting in low interoperability. To increase the interoperability of CDS a standard representation of clinical information is needed. The paper suggests a CDS architecture which integrates several HL7 standards and the new vMR (virtual Medical Record). The clinical information for the CDS systems (the vMR) is represented with Topic Maps technology. Beside the implementation of the vMR, the architecture integrates: a Data Manager, an interface, a decision making system (based on Egadss), a retrieving data module. Conclusions are issued.

  15. 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.

  16. LIMSI @ 2014 Clinical Decision Support Track

    DTIC Science & Technology

    2014-11-01

    UMLS semantics in mapping vocabularies. In Proceedings of the AMIA symposium, page 815. American Medical Informatics Association, 1998. [2] Aurélie...Elhadad, Carol Friedman, and Marianthi Markatou. Automated knowledge acquisition from clinical narrative reports. In AMIA Annual Symposium Proceedings

  17. Cognitive Elements in Clinical Decision-Making

    ERIC Educational Resources Information Center

    Dunphy, Bruce C.; Cantwell, Robert; Bourke, Sid; Fleming, Mark; Smith, Bruce; Joseph, K. S.; Dunphy, Stacey L

    2010-01-01

    Physician cognition, metacognition and affect may have an impact upon the quality of clinical reasoning. The purpose of this study was to examine the relationship between measures of physician metacognition and affect and patient outcomes in obstetric practice. Reflective coping (RC), proactive coping, need for cognition (NFC), tolerance for…

  18. Cognitive Elements in Clinical Decision-Making

    ERIC Educational Resources Information Center

    Dunphy, Bruce C.; Cantwell, Robert; Bourke, Sid; Fleming, Mark; Smith, Bruce; Joseph, K. S.; Dunphy, Stacey L

    2010-01-01

    Physician cognition, metacognition and affect may have an impact upon the quality of clinical reasoning. The purpose of this study was to examine the relationship between measures of physician metacognition and affect and patient outcomes in obstetric practice. Reflective coping (RC), proactive coping, need for cognition (NFC), tolerance for…

  19. 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.

  20. Clinical decision support: the power behind the electronic health record.

    PubMed

    Glaser, John

    2008-07-01

    There are six strategic objectives for promoting adoption of clinical decision support: Use a standardized format for representing clinical data and CDS interventions. Ensure appropriate access to clinical data and CDS interventions. Provide support and incentives for providers to use CDS. Disseminate information about best practices for system design, CDS delivery, and CDS implementation. Continue national demonstrations and evaluation of CDS use. Leverage data interchange between EHRs.

  1. A clinical decision algorithm for hospital inpatients with impaired decision-making capacity.

    PubMed

    Chase, Jack

    2014-08-01

    Impaired decision-making capacity is a frequent complication of inpatient hospitalization, with potential negative impacts on patients and the healthcare system. Studies of clinician behavior show difficulty in diagnosis and management of capacity impairment. Appropriate management of incapacitated patients may benefit safety, medical outcomes, and healthcare expenditure. To create a clinical decision algorithm for identification and management of hospital inpatients with impaired capacity. The Department of Risk Management at San Francisco General Hospital (SFGH) convened a multidisciplinary workgroup to improve management of incapacitated patients. The workgroup studied institutional data and case experience, solicited mental health expertise, and performed a brief review of published tools for management of incapacitated patients. The workgroup produced a clinical decision algorithm for hospital inpatients with impaired decision-making capacity. The algorithm is explained via 3 common scenarios, and notable details include identification and management in a single visual diagram, emphasis on safety planning for a high-risk subset of incapacitated patients, and explanation for multiple disciplines of consultation. The algorithm was disseminated to providers, workshops were conducted, and associated quality improvements were implemented. Initial feedback was positive, relating to clinical competency, decreased practice anxiety, and improved teamwork. Impaired decision-making capacity is frequent among hospitalized patients, including at SFGH. An algorithm, based on institutional review and prior published work, is presented as an example to address the common challenge of acutely ill patients with impaired decision-making capacity. © 2014 Society of Hospital Medicine.

  2. Decision analysis applications and the CERCLA process

    SciTech Connect

    Purucker, S.T.; Lyon, B.F. |

    1994-06-01

    Quantitative decision methods can be developed during environmental restoration projects that incorporate stakeholder input and can complement current efforts that are undertaken for data collection and alternatives evaluation during the CERCLA process. These decision-making tools can supplement current EPA guidance as well as focus on problems that arise as attempts are made to make informed decisions regarding remedial alternative selection. In examining the use of such applications, the authors discuss the use of decision analysis tools and their impact on collecting data and making environmental decisions from a risk-based perspective. They will look at the construction of objective functions for quantifying different risk-based perspective. They will look at the construction of objective functions for quantifying different risk-based decision rules that incorporate stakeholder concerns. This represents a quantitative method for implementing the Data Quality Objective (DQO) process. These objective functions can be expressed using a variety of indices to analyze problems that currently arise in the environmental field. Examples include cost, magnitude of risk, efficiency, and probability of success or failure. Based on such defined objective functions, a project can evaluate the impact of different risk and decision selection strategies on data worth and alternative selection.

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

    PubMed Central

    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. PMID:28269916

  4. Decision-problem state analysis methodology

    NASA Technical Reports Server (NTRS)

    Dieterly, D. L.

    1980-01-01

    A methodology for analyzing a decision-problem state is presented. The methodology is based on the analysis of an incident in terms of the set of decision-problem conditions encountered. By decomposing the events that preceded an unwanted outcome, such as an accident, into the set of decision-problem conditions that were resolved, a more comprehensive understanding is possible. All human-error accidents are not caused by faulty decision-problem resolutions, but it appears to be one of the major areas of accidents cited in the literature. A three-phase methodology is presented which accommodates a wide spectrum of events. It allows for a systems content analysis of the available data to establish: (1) the resolutions made, (2) alternatives not considered, (3) resolutions missed, and (4) possible conditions not considered. The product is a map of the decision-problem conditions that were encountered as well as a projected, assumed set of conditions that should have been considered. The application of this methodology introduces a systematic approach to decomposing the events that transpired prior to the accident. The initial emphasis is on decision and problem resolution. The technique allows for a standardized method of accident into a scenario which may used for review or the development of a training simulation.

  5. Enhanced Decision Analysis Support System.

    DTIC Science & Technology

    1981-03-01

    vklues will have. Any entry sta:ting with an R will be treated 0.430.2 0.43 .1 III ALT LO ALT A RRECCE Value F-4 45.0 .0.0 50.0 50.0 50.0 50.0 r-is...analysis. CtttttttttS C A V T I 0 t t i. ANY ENTRY STARTING WITH THE LETTER R WILL BE TREATED AS REGRET (LESS IS BETTER) IN THE SENSITIVITY ANALYSIS. ALL...CHARACTERS STARTING WITH ANY OTHER LETTERINUMERALI 01 CHARACTER WILL BE TREATED A VALUE (MORE IS SETTER) IN THE SENSITIVITY ANALYSIS. ts t t t t t t t t5

  6. 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

  7. Decision Analysis for Equipment Selection

    ERIC Educational Resources Information Center

    Cilliers, J. J.

    2005-01-01

    Equipment selection during process design is a critical aspect of chemical engineering and requires engineering judgment and subjective analysis. When educating chemical engineering students in the selection of proprietary equipment during design, the focus is often on the types of equipment available and their operating characteristics. The…

  8. Semantic Interoperability in Clinical Decision Support Systems: A Systematic Review.

    PubMed

    Marco-Ruiz, Luis; Bellika, Johan Gustav

    2015-01-01

    The interoperability of Clinical Decision Support (CDS) systems with other health information systems has become one of the main limitations to their broad adoption. Semantic interoperability must be granted in order to share CDS modules across different health information systems. Currently, numerous standards for different purposes are available to enable the interoperability of CDS systems. We performed a literature review to identify and provide an overview of the available standards that enable CDS interoperability in the areas of clinical information, decision logic, terminology, and web service interfaces.

  9. 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).

  10. 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

  11. 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

  12. The factors facilitating and inhibiting effective clinical decision-making in nursing: a qualitative study.

    PubMed

    Hagbaghery, Mohsen Adib; Salsali, Mahvash; Ahmadi, Fazlolah

    2004-04-06

    BACKGROUND: Nurses' practice takes place in a context of ongoing advances in research and technology. The dynamic and uncertain nature of health care environment requires nurses to be competent decision-makers in order to respond to clients' needs. Recently, the public and the government have criticized Iranian nurses because of poor quality of patient care. However nurses' views and experiences on factors that affect their clinical function and clinical decision-making have rarely been studied. METHODS: Grounded theory methodology was used to analyze the participants' lived experiences and their viewpoints regarding the factors affecting their clinical function and clinical decision-making. Semi-structured interviews and participant observation methods were used to gather the data. Thirty-eight participants were interviewed and twelve sessions of observation were carried out. Constant comparative analysis method was used to analyze the data. RESULTS: Five main themes emerged from the data. From the participants' points of view, "feeling competent", "being self-confident", "organizational structure", "nursing education", and "being supported" were considered as important factors in effective clinical decision-making. CONCLUSION: As participants in this research implied, being competent and self-confident are the most important personal factors influencing nurses clinical decision-making. Also external factors such as organizational structure, access to supportive resources and nursing education have strengthening or inhibiting effects on the nurses' decisions. Individual nurses, professional associations, schools of nursing, nurse educators, organizations that employ nurses and government all have responsibility for developing and finding strategies that facilitate nurses' effective clinical decision-making. They are responsible for identifying barriers and enhancing factors within the organizational structure that facilitate nurses' clinical decision-making.

  13. The factors facilitating and inhibiting effective clinical decision-making in nursing: a qualitative study

    PubMed Central

    Hagbaghery, Mohsen Adib; Salsali, Mahvash; Ahmadi, Fazlolah

    2004-01-01

    Background Nurses' practice takes place in a context of ongoing advances in research and technology. The dynamic and uncertain nature of health care environment requires nurses to be competent decision-makers in order to respond to clients' needs. Recently, the public and the government have criticized Iranian nurses because of poor quality of patient care. However nurses' views and experiences on factors that affect their clinical function and clinical decision-making have rarely been studied. Methods Grounded theory methodology was used to analyze the participants' lived experiences and their viewpoints regarding the factors affecting their clinical function and clinical decision-making. Semi-structured interviews and participant observation methods were used to gather the data. Thirty-eight participants were interviewed and twelve sessions of observation were carried out. Constant comparative analysis method was used to analyze the data. Results Five main themes emerged from the data. From the participants' points of view, "feeling competent", "being self-confident", "organizational structure", "nursing education", and "being supported" were considered as important factors in effective clinical decision-making. Conclusion As participants in this research implied, being competent and self-confident are the most important personal factors influencing nurses clinical decision-making. Also external factors such as organizational structure, access to supportive resources and nursing education have strengthening or inhibiting effects on the nurses' decisions. Individual nurses, professional associations, schools of nursing, nurse educators, organizations that employ nurses and government all have responsibility for developing and finding strategies that facilitate nurses' effective clinical decision-making. They are responsible for identifying barriers and enhancing factors within the organizational structure that facilitate nurses' clinical decision-making. PMID

  14. A study to explore if dentists' anxiety affects their clinical decision-making.

    PubMed

    Chipchase, S Y; Chapman, H R; Bretherton, R

    2017-02-24

    Aims To develop a measure of dentists' anxiety in clinical situations; to establish if dentists' anxiety in clinical situations affected their self-reported clinical decision-making; to establish if occupational stress, as demonstrated by burnout, is associated with anxiety in clinical situations and clinical decision-making; and to explore the relationship between decision-making style and the clinical decisions which are influenced by anxiety.Design Cross-sectional study.Setting Primary Dental Care.Subjects and methods A questionnaire battery [Maslach Burnout Inventory, measuring burnout; Melbourne Decision Making Questionnaire, measuring decision-making style; Dealing with Uncertainty Questionnaire (DUQ), measuring coping with diagnostic uncertainty; and a newly designed Dentists' Anxieties in Clinical Situations Scale, measuring dentists' anxiety (DACSS-R) and change of treatment (DACSS-C)] was distributed to dentists practicing in Nottinghamshire and Lincolnshire. Demographic data were collected and dentists gave examples of anxiety-provoking situations and their responses to them.Main outcome measure Respondents' self-reported anxiety in various clinical situations on a 11-point Likert Scale (DACSS-R) and self-reported changes in clinical procedures (Yes/No; DACSS-C). The DACSS was validated using multiple t-tests and a principal component analysis. Differences in DACSS-R ratings and burnout, decision-making and dealing with uncertainty were explored using Pearson correlations and multiple regression analysis. Qualitative data was subject to a thematic analysis.Results The DACSS-R revealed a four-factor structure and had high internal reliability (Cronbach's α = 0.94). Those with higher DACSS-R scores of anxiety were more likely to report changes in clinical procedures (DACSS-C scores). DACSS-R scores were associated with decision-making self-esteem and style as measured by the MDMQ and all burnout subscales, though not with scores on the DUQ scale

  15. Exploration Clinical Decision Support System: Medical Data Architecture

    NASA Technical Reports Server (NTRS)

    Lindsey, Tony; Shetye, Sandeep; Shaw, Tianna (Editor)

    2016-01-01

    The Exploration Clinical Decision Support (ECDS) System project is intended to enhance the Exploration Medical Capability (ExMC) Element for extended duration, deep-space mission planning in HRP. A major development guideline is the Risk of "Adverse Health Outcomes & Decrements in Performance due to Limitations of In-flight Medical Conditions". ECDS attempts to mitigate that Risk by providing crew-specific health information, actionable insight, crew guidance and advice based on computational algorithmic analysis. The availability of inflight health diagnostic computational methods has been identified as an essential capability for human exploration missions. Inflight electronic health data sources are often heterogeneous, and thus may be isolated or not examined as an aggregate whole. The ECDS System objective provides both a data architecture that collects and manages disparate health data, and an active knowledge system that analyzes health evidence to deliver case-specific advice. A single, cohesive space-ready decision support capability that considers all exploration clinical measurements is not commercially available at present. Hence, this Task is a newly coordinated development effort by which ECDS and its supporting data infrastructure will demonstrate the feasibility of intelligent data mining and predictive modeling as a biomedical diagnostic support mechanism on manned exploration missions. The initial step towards ground and flight demonstrations has been the research and development of both image and clinical text-based computer-aided patient diagnosis. Human anatomical images displaying abnormal/pathological features have been annotated using controlled terminology templates, marked-up, and then stored in compliance with the AIM standard. These images have been filtered and disease characterized based on machine learning of semantic and quantitative feature vectors. The next phase will evaluate disease treatment response via quantitative linear

  16. Decision Aids Can Support Cancer Clinical Trials Decisions: Results of a Randomized Trial.

    PubMed

    Politi, Mary C; Kuzemchak, Marie D; Kaphingst, Kimberly A; Perkins, Hannah; Liu, Jingxia; Byrne, Margaret M

    2016-12-01

    Cancer patients often do not make informed decisions regarding clinical trial participation. This study evaluated whether a web-based decision aid (DA) could support trial decisions compared with our cancer center's website. Adults diagnosed with cancer in the past 6 months who had not previously participated in a cancer clinical trial were eligible. Participants were randomized to view the DA or our cancer center's website (enhanced usual care [UC]). Controlling for whether participants had heard of cancer clinical trials and educational attainment, multivariable linear regression examined group on knowledge, self-efficacy for finding trial information, decisional conflict (values clarity and uncertainty), intent to participate, decision readiness, and trial perceptions. Two hundred patients (86%) consented between May 2014 and April 2015. One hundred were randomized to each group. Surveys were completed by 87 in the DA group and 90 in the UC group. DA group participants reported clearer values regarding trial participation than UC group participants reported (least squares [LS] mean = 15.8 vs. 32, p < .0001) and less uncertainty (LS mean = 24.3 vs. 36.4, p = .025). The DA group had higher objective knowledge than the UC group's (LS mean = 69.8 vs. 55.8, p < .0001). There were no differences between groups in intent to participate. Improvements on key decision outcomes including knowledge, self-efficacy, certainty about choice, and values clarity among participants who viewed the DA suggest web-based DAs can support informed decisions about trial participation among cancer patients facing this preference-sensitive choice. Although better informing patients before trial participation could improve retention, more work is needed to examine DA impact on enrollment and retention. This paper describes evidence regarding a decision tool to support patients' decisions about trial participation. By improving knowledge, helping patients clarify preferences for

  17. Cabergoline versus levodopa monotherapy: a decision analysis.

    PubMed

    Smala, Antje M; Spottke, E Annika; Machat, Olaf; Siebert, Uwe; Meyer, Dieter; Köhne-Volland, Rudolf; Reuther, Martin; DuChane, Janeen; Oertel, Wolfgang H; Berger, Karin B; Dodel, Richard C

    2003-08-01

    We evaluated the incremental cost-effectiveness of cabergoline compared with levodopa monotherapy in patients with early Parkinson's disease (PD) in the German healthcare system. The study design was based on cost-effectiveness analysis using a Markov model with a 10-year time horizon. Model input data was based on a clinical trial "Early Treatment of PD with Cabergoline" as well as on cost data of a German hospital/office-based PD network. Direct and indirect medical and nonmedical costs were included. Outcomes were costs, disease stage, cumulative complication incidence, and mortality. An annual discount rate of 5% was applied and the societal perspective was chosen. The target population included patients in Hoehn and Yahr Stages I to III. It was found that the occurrence of motor complications was significantly lower in patients on cabergoline monotherapy. For patients aged >/=60 years of age, cabergoline monotherapy was cost effective when considering costs per decreased UPDRS score. Each point decrease in the UPDRS (I-IV) resulted in costs of euro;1,031. Incremental costs per additional motor complication-free patient were euro;104,400 for patients <60 years of age and euro;57,900 for patients >/=60 years of age. In conclusion, this decision-analytic model calculation for PD was based almost entirely on clinical and observed data with a limited number of assumptions. Although costs were higher in patients on cabergoline, the corresponding cost-effectiveness ratio for cabergoline was at least as favourable as the ratios for many commonly accepted therapies.

  18. 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.

  19. 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.

  20. Interactive financial decision support for clinical research trials.

    PubMed

    Holler, Benjamin; Forgione, Dana A; Baisden, Clinton E; Abramson, David A; Calhoon, John H

    2011-01-01

    The purpose of this article is to describe a decision support approach useful for evaluating proposals to conduct clinical research trials. Physicians often do not have the time or background to account for all the expenses of a clinical trial. Their evaluation process may be limited and driven by factors that do not indicate the potential for financial losses that a trial may impose. We analyzed clinical trial budget templates used by hospitals, health science centers, research universities, departments of medicine, and medical schools. We compiled a databank of costs and reviewed recent research trials conducted by the Department of Cardiothoracic Surgery in a major academic health science center. We then developed an interactive spreadsheet-based budgetary decision support approach that accounts for clinical trial income and costs. It can be tailored to provide quick and understandable data entry, accurate cost rates per subject, and clear go/no-go signals for the physician.

  1. Hip Arthroplasty Pseudotumors: Pathogenesis, Imaging, and Clinical Decision Making

    PubMed Central

    Davis, Derik L; Morrison, James J

    2016-01-01

    Pseudotumors are a complication of hip arthroplasty. The goal of this article is to review the clinical presentation, pathogenesis, histology, and the role of diagnostic imaging in clinical decision making for treatment, and surveillance of pseudotumors. We will discuss the multimodal imaging appearances, differential diagnosis, associated complications, treatment, and prognosis of pseudotumors, as an aid to the assessment of orthopedic prostheses at the hip. PMID:27195183

  2. Microcomputer-Based Expert System for Clinical Decision-Making

    PubMed Central

    Hudson, Donna L.; Estrin, Thelma

    1981-01-01

    A computerized rule-based expert system for chest pain analysis in the emergency room has been developed as a medical decision-making tool. The rules are based on a previously established criteria mapping procedure developed for evaluating emergency room decisions. The system is implemented in PASCAL, a standardized language, and hence is machine-independent, and also has modest memory requirements. The overall design permits usage by those unfamiliar with computers.

  3. A roadmap for national action on clinical decision support.

    PubMed

    Osheroff, Jerome A; Teich, Jonathan M; Middleton, Blackford; Steen, Elaine B; Wright, Adam; Detmer, Don E

    2007-01-01

    This document comprises an AMIA Board of Directors approved White Paper that presents a roadmap for national action on clinical decision support. It is published in JAMIA for archival and dissemination purposes. The full text of this material has been previously published on the AMIA Web site (www.amia.org/inside/initiatives/cds). AMIA is the copyright holder.

  4. A Roadmap for National Action on Clinical Decision Support

    PubMed Central

    Osheroff, Jerome A.; Teich, Jonathan M.; Middleton, Blackford; Steen, Elaine B.; Wright, Adam; Detmer, Don E.

    2007-01-01

    This document comprises an AMIA Board of Directors approved White Paper that presents a roadmap for national action on clinical decision support. It is published in JAMIA for archival and dissemination purposes. The full text of this material has been previously published on the AMIA Web site (www.amia.org/inside/initiatives/cds). AMIA is the copyright holder. PMID:17213487

  5. Thinking Processes Used by Nurses in Clinical Decision Making.

    ERIC Educational Resources Information Center

    Higuchi, Kathryn A. Smith; Donald, Janet G.

    2002-01-01

    Interviews with eight medical and surgical nurses and audits of patient charts investigated clinical decision-making processes. Predominant thinking processes were description of facts, selection of information, inference, syntheses, and verification, with differences between medical and surgical specialties. Exemplars of thinking processes…

  6. 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.

  7. 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.

  8. Analysis weighs issues in divestiture decisions.

    PubMed

    Spallina, J M

    1990-07-01

    Financial managers faced with the task of recommending whether diversified services should be dissolved or continued need a logical means of analysis. Their evaluations should consider not only the venture's financial results but concerns specific to the hospital and its market, as well as related social and legal issues. Failure analysis, a function of business portfolio management, helps put these variables in perspective and provides a framework for decision making.

  9. Incorporating clinical guidelines through clinician decision-making

    PubMed Central

    Falzer, Paul R; Moore, Brent A; Garman, D Melissa

    2008-01-01

    Background It is generally acknowledged that a disparity between knowledge and its implementation is adversely affecting quality of care. An example commonly cited is the failure of clinicians to follow clinical guidelines. A guiding assumption of this view is that adherence should be gauged by a standard of conformance. At least some guideline developers dispute this assumption and claim that their efforts are intended to inform and assist clinical practice, not to function as standards of performance. However, their ability to assist and inform will remain limited until an alternative to the conformance criterion is proposed that gauges how evidence-based guidelines are incorporated into clinical decisions. Methods The proposed investigation has two specific aims to identify the processes that affect decisions about incorporating clinical guidelines, and then to develop ad test a strategy that promotes the utilization of evidence-based practices. This paper focuses on the first aim. It presents the rationale, introduces the clinical paradigm of treatment-resistant schizophrenia, and discusses an exemplar of clinician non-conformance to a clinical guideline. A modification of the original study is proposed that targets psychiatric trainees and draws on a cognitively rich theory of decision-making to formulate hypotheses about how the guideline is incorporated into treatment decisions. Twenty volunteer subjects recruited from an accredited psychiatry training program will respond to sixty-four vignettes that represent a fully crossed 2 × 2 × 2 × 4 within-subjects design. The variables consist of criteria contained in the clinical guideline and other relevant factors. Subjects will also respond to a subset of eight vignettes that assesses their overall impression of the guideline. Generalization estimating equation models will be used to test the study's principal hypothesis and perform secondary analyses. Implications The original design of phase two of the

  10. Gait analysis: clinical facts.

    PubMed

    Baker, Richard; Esquenazi, Alberto; Benedetti, Maria G; Desloovere, Kaat

    2016-08-01

    Gait analysis is a well-established tool for the quantitative assessment of gait disturbances providing functional diagnosis, assessment for treatment planning, and monitoring of disease progress. There is a large volume of literature on the research use of gait analysis, but evidence on its clinical routine use supports a favorable cost-benefit ratio in a limited number of conditions. Initially gait analysis was introduced to clinical practice to improve the management of children with cerebral palsy. However, there is good evidence to extend its use to patients with various upper motor neuron diseases, and to lower limb amputation. Thereby, the methodology for properly conducting and interpreting the exam is of paramount relevance. Appropriateness of gait analysis prescription and reliability of data obtained are required in the clinical environment. This paper provides an overview on guidelines for managing a clinical gait analysis service and on the principal clinical domains of its application: cerebral palsy, stroke, traumatic brain injury and lower limb amputation.

  11. Clinical Decision Support Systems for Comorbidity: Architecture, Algorithms, and Applications

    PubMed Central

    Fan, Aihua; Tang, Yu

    2017-01-01

    In this paper, we present the design of a clinical decision support system (CDSS) for monitoring comorbid conditions. Specifically, we address the architecture of a CDSS by characterizing it from three layers and discuss the algorithms in each layer. Also we address the applications of CDSSs in a few real scenarios and analyze the accuracy of a CDSS in consideration of the potential conflicts when using multiple clinical practice guidelines concurrently. Finally, we compare the system performance in our design with that in the other design schemes. Our study shows that our proposed design can achieve a clinical decision in a shorter time than the other designs, while ensuring a high level of system accuracy. PMID:28373881

  12. Improving the implementation of clinical decision support systems.

    PubMed

    Rüping, Stefan; Anguita, Alberto; Bucur, Anca; Cirstea, Traian Cristian; Jacobs, Björn; Torge, Antje

    2013-01-01

    Clinical decision support (CDS) systems promise to improve the quality of clinical care by helping physicians to make better, more informed decisions efficiently. However, the design and testing of CDS systems for practical medical use is cumbersome. It has been recognized that this may easily lead to a problematic mismatch between the developers' idea of the system and requirements from clinical practice. In this paper, we will present an approach to reduce the complexity of constructing a CDS system. The approach is based on an ontological annotation of data resources, which improves standardization and the semantic processing of data. This, in turn, allows to use data mining tools to automatically create hypotheses for CDS models, which reduces the manual workload in the creation of a new model. The approach is implemented in the context of EU research project p-medicine. A proof of concept implementation on data from an existing Leukemia study is presented.

  13. Dynamic clinical data mining: search engine-based decision support.

    PubMed

    Celi, Leo Anthony; Zimolzak, Andrew J; Stone, David J

    2014-06-23

    The research world is undergoing a transformation into one in which data, on massive levels, is freely shared. In the clinical world, the capture of data on a consistent basis has only recently begun. We propose an operational vision for a digitally based care system that incorporates data-based clinical decision making. The system would aggregate individual patient electronic medical data in the course of care; query a universal, de-identified clinical database using modified search engine technology in real time; identify prior cases of sufficient similarity as to be instructive to the case at hand; and populate the individual patient's electronic medical record with pertinent decision support material such as suggested interventions and prognosis, based on prior outcomes. Every individual's course, including subsequent outcomes, would then further populate the population database to create a feedback loop to benefit the care of future patients.

  14. Clinical Decision Support for Immunizations (CDSi): A Comprehensive, Collaborative Strategy

    PubMed Central

    Arzt, Noam H.

    2016-01-01

    This article focuses on the requirements and current developments in clinical decision support technologies for immunizations (CDSi) in both the public health and clinical communities, with an emphasis on shareable solutions. The requirements of the Electronic Health Record Incentive Programs have raised some unique challenges for the clinical community, including vocabulary mapping, update of changing guidelines, single immunization schedule, and scalability. This article discusses new, collaborative approaches whose long-term goal is to make CDSi more sustainable for both the public and private sectors. PMID:27789956

  15. Improving Intelligence Analysis With Decision Science.

    PubMed

    Dhami, Mandeep K; Mandel, David R; Mellers, Barbara A; Tetlock, Philip E

    2015-11-01

    Intelligence analysis plays a vital role in policy decision making. Key functions of intelligence analysis include accurately forecasting significant events, appropriately characterizing the uncertainties inherent in such forecasts, and effectively communicating those probabilistic forecasts to stakeholders. We review decision research on probabilistic forecasting and uncertainty communication, drawing attention to findings that could be used to reform intelligence processes and contribute to more effective intelligence oversight. We recommend that the intelligence community (IC) regularly and quantitatively monitor its forecasting accuracy to better understand how well it is achieving its functions. We also recommend that the IC use decision science to improve these functions (namely, forecasting and communication of intelligence estimates made under conditions of uncertainty). In the case of forecasting, decision research offers suggestions for improvement that involve interventions on data (e.g., transforming forecasts to debias them) and behavior (e.g., via selection, training, and effective team structuring). In the case of uncertainty communication, the literature suggests that current intelligence procedures, which emphasize the use of verbal probabilities, are ineffective. The IC should, therefore, leverage research that points to ways in which verbal probability use may be improved as well as exploring the use of numerical probabilities wherever feasible. © Her Majesty the Queen in Right of Canada, as represented by Defence Research and Development Canada 2015.

  16. 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).

  17. Clinical decisions support malfunctions in a commercial electronic health record.

    PubMed

    Kassakian, Steven Z; Yackel, Thomas R; Gorman, Paul N; Dorr, David A

    2017-09-06

    Determine if clinical decision support (CDS) malfunctions occur in a commercial electronic health record (EHR) system, characterize their pathways and describe methods of detection. We retrospectively examined the firing rate for 226 alert type CDS rules for detection of anomalies using both expert visualization and statistical process control (SPC) methods over a five year period. Candidate anomalies were investigated and validated. Twenty-one candidate CDS anomalies were identified from 8,300 alert-months. Of these candidate anomalies, four were confirmed as CDS malfunctions, eight as false-positives, and nine could not be classified. The four CDS malfunctions were a result of errors in knowledge management: 1) inadvertent addition and removal of a medication code to the electronic formulary list; 2) a seasonal alert which was not activated; 3) a change in the base data structures; and 4) direct editing of an alert related to its medications. 154 CDS rules (68%) were amenable to SPC methods and the test characteristics were calculated as a sensitivity of 95%, positive predictive value of 29% and F-measure 0.44. CDS malfunctions were found to occur in our EHR. All of the pathways for these malfunctions can be described as knowledge management errors. Expert visualization is a robust method of detection, but is resource intensive. SPC-based methods, when applicable, perform reasonably well retrospectively. CDS anomalies were found to occur in a commercial EHR and visual detection along with SPC analysis represents promising methods of malfunction detection.

  18. Teaching the Tools of Pharmaceutical Care Decision-Analysis.

    ERIC Educational Resources Information Center

    Rittenhouse, Brian E.

    1994-01-01

    A method of decision-analysis in pharmaceutical care that integrates epidemiology and economics is presented, including an example illustrating both the deceptive nature of medical decision making and the power of decision analysis. Principles in determining both general and specific probabilities of interest and use of decision trees for…

  19. Teaching the Tools of Pharmaceutical Care Decision-Analysis.

    ERIC Educational Resources Information Center

    Rittenhouse, Brian E.

    1994-01-01

    A method of decision-analysis in pharmaceutical care that integrates epidemiology and economics is presented, including an example illustrating both the deceptive nature of medical decision making and the power of decision analysis. Principles in determining both general and specific probabilities of interest and use of decision trees for…

  20. Using nursing clinical decision support systems to achieve meaningful use.

    PubMed

    Harrison, Roberta L; Lyerla, Frank

    2012-07-01

    The Health Information Technology and Clinical Health Act (one component of the American Recovery and Reinvestment Act) is responsible for providing incentive payments to hospitals and eligible providers in an effort to support the adoption of electronic health records. Future penalties are planned for electronic health record noncompliance. In order to receive incentives and avoid penalties, hospitals and eligible providers must demonstrate "meaningful use" of their electronic health records. One of the meaningful-use objectives established by the Centers for Medicare & Medicaid Services involves the use of a clinical decision support rule that addresses a hospital-defined, high-priority condition. This article describes the Plan-Do-Study-Act process for creating and implementing a nursing clinical decision support system designed to improve guideline adherence for hypoglycemia management. This project identifies hypoglycemia management as the high-priority area. However, other facilities with different high-priority conditions may find the process presented in this article useful for implementing additional clinical decision support rules geared toward improving outcomes and meeting federal mandates.

  1. A decision class analysis of critical care life-support decision-making.

    PubMed

    Seiver, A

    1993-02-01

    Decision analysis is a powerful methodology that can help clinicians make good decisions. Because it is not practical to place a decision analyst at the bedside in critical care units, the application of this methodology will require leveraging the analyst through computer-based systems. A decision class analysis is a collective analysis of a group of decisions that provides the high-level specification for such a computer system. This paper presents a decision class analysis of critical care life-support decisions. Key elements of this analysis are: the simplification of an otherwise extremely complex multistage sequential decision problem by using a sequence of two-stage models, and the use of six generic knowledge maps that capture the extremely complex relevant medical knowledge.

  2. Integrating computerized clinical decision support systems into clinical work: A meta-synthesis of qualitative research.

    PubMed

    Miller, Anne; Moon, Brian; Anders, Shilo; Walden, Rachel; Brown, Steven; Montella, Diane

    2015-12-01

    Computerized clinical decision support systems (CDSS) are an emerging means for improving healthcare safety, quality and efficiency, but meta-analyses findings are mixed. This meta-synthesis aggregates qualitative research findings as possible explanations for variable quantitative research outcomes. Qualitative studies published between 2000 and 2013 in English, involving physicians, registered and advanced practice nurses' experience of CDSS use in clinical practice were included. PubMed and CINAHL databases were searched. Study titles and abstracts were screened against inclusion criteria. Retained studies were appraised against quality criteria. Findings were extracted iteratively from studies in the 4th quartile of quality scores. Two reviewers constructed themes inductively. A third reviewer applied the defined themes deductively achieving 92% agreement. 3798 unique records were returned; 56 met inclusion criteria and were reviewed against quality criteria. 9 studies were of sufficiently high quality for synthetic analysis. Five major themes (clinician-patient-system integration; user interface usability; the need for better 'algorithms'; system maturity; patient safety) were defined. Despite ongoing development, CDSS remains an emerging technology. Lack of understanding about and lack of consideration for the interaction between human decision makers and CDSS is a major reason for poor system adoption and use. Further high-quality qualitative research is needed to better understand human-system interaction issues. These issues may continue to confound quantitative study results if not addressed. Copyright © 2015. Published by Elsevier Ireland Ltd.

  3. Potential clinical and economic outcomes of active beta-D-glucan surveillance with preemptive therapy for invasive candidiasis at intensive care units: a decision model analysis.

    PubMed

    Pang, Y-K; Ip, M; You, J H S

    2017-01-01

    Early initiation of antifungal treatment for invasive candidiasis is associated with change in mortality. Beta-D-glucan (BDG) is a fungal cell wall component and a serum diagnostic biomarker of fungal infection. Clinical findings suggested an association between reduced invasive candidiasis incidence in intensive care units (ICUs) and BDG-guided preemptive antifungal therapy. We evaluated the potential cost-effectiveness of active BDG surveillance with preemptive antifungal therapy in patients admitted to adult ICUs from the perspective of Hong Kong healthcare providers. A Markov model was designed to simulate the outcomes of active BDG surveillance with preemptive therapy (surveillance group) and no surveillance (standard care group). Candidiasis-associated outcome measures included mortality rate, quality-adjusted life year (QALY) loss, and direct medical cost. Model inputs were derived from the literature. Sensitivity analyses were conducted to evaluate the robustness of model results. In base-case analysis, the surveillance group was more costly (1387 USD versus 664 USD) (1 USD = 7.8 HKD), with lower candidiasis-associated mortality rate (0.653 versus 1.426 per 100 ICU admissions) and QALY loss (0.116 versus 0.254) than the standard care group. The incremental cost per QALY saved by the surveillance group was 5239 USD/QALY. One-way sensitivity analyses found base-case results to be robust to variations of all model inputs. In probabilistic sensitivity analysis, the surveillance group was cost-effective in 50 % and 100 % of 10,000 Monte Carlo simulations at willingness-to-pay (WTP) thresholds of 7200 USD/QALY and ≥27,800 USD/QALY, respectively. Active BDG surveillance with preemptive therapy appears to be highly cost-effective to reduce the candidiasis-associated mortality rate and save QALYs in the ICU setting.

  4. 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

  5. Defense against nuclear weapons: a decision analysis.

    PubMed

    Orient, J M

    1985-02-01

    Response to the public health threat posed by nuclear weapons is a medical imperative. The United States, in contrast to other nations, has chosen a course that assures maximal casualties in the event of a nuclear attack, on the theory that prevention of the attack is incompatible with preventive measures against its consequences, such as blast injuries and radiation sickness. A decision analysis approach clarifies the risks and benefits of a change to a strategy of preparedness.

  6. 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.

  7. System-Agnostic Clinical Decision Support Services: Benefits and Challenges for Scalable Decision Support

    PubMed Central

    Kawamoto, Kensaku; Del Fiol, Guilherme; Orton, Charles; Lobach, David F

    2010-01-01

    System-agnostic clinical decision support (CDS) services provide patient evaluation capabilities that are independent of specific CDS systems and system implementation contexts. While such system-agnostic CDS services hold great potential for facilitating the widespread implementation of CDS systems, little has been described regarding the benefits and challenges of their use. In this manuscript, the authors address this need by describing potential benefits and challenges of using a system-agnostic CDS service. This analysis is based on the authors’ formal assessments of, and practical experiences with, various approaches to developing, implementing, and maintaining CDS capabilities. In particular, the analysis draws on the authors’ experience developing and leveraging a system-agnostic CDS Web service known as SEBASTIAN. A primary potential benefit of using a system-agnostic CDS service is the relative ease and flexibility with which the service can be leveraged to implement CDS capabilities across applications and care settings. Other important potential benefits include facilitation of centralized knowledge management and knowledge sharing; the potential to support multiple underlying knowledge representations and knowledge resources through a common service interface; improved simplicity and componentization; easier testing and validation; and the enabling of distributed CDS system development. Conversely, important potential challenges include the increased effort required to develop knowledge resources capable of being used in many contexts and the critical need to standardize the service interface. Despite these challenges, our experiences to date indicate that the benefits of using a system-agnostic CDS service generally outweigh the challenges of using this approach to implementing and maintaining CDS systems. PMID:21603281

  8. System-agnostic clinical decision support services: benefits and challenges for scalable decision support.

    PubMed

    Kawamoto, Kensaku; Del Fiol, Guilherme; Orton, Charles; Lobach, David F

    2010-01-01

    System-agnostic clinical decision support (CDS) services provide patient evaluation capabilities that are independent of specific CDS systems and system implementation contexts. While such system-agnostic CDS services hold great potential for facilitating the widespread implementation of CDS systems, little has been described regarding the benefits and challenges of their use. In this manuscript, the authors address this need by describing potential benefits and challenges of using a system-agnostic CDS service. This analysis is based on the authors' formal assessments of, and practical experiences with, various approaches to developing, implementing, and maintaining CDS capabilities. In particular, the analysis draws on the authors' experience developing and leveraging a system-agnostic CDS Web service known as SEBASTIAN. A primary potential benefit of using a system-agnostic CDS service is the relative ease and flexibility with which the service can be leveraged to implement CDS capabilities across applications and care settings. Other important potential benefits include facilitation of centralized knowledge management and knowledge sharing; the potential to support multiple underlying knowledge representations and knowledge resources through a common service interface; improved simplicity and componentization; easier testing and validation; and the enabling of distributed CDS system development. Conversely, important potential challenges include the increased effort required to develop knowledge resources capable of being used in many contexts and the critical need to standardize the service interface. Despite these challenges, our experiences to date indicate that the benefits of using a system-agnostic CDS service generally outweigh the challenges of using this approach to implementing and maintaining CDS systems.

  9. Clinical Decision Support for Vascular Disease in Community Family Practice

    PubMed Central

    Keshavjee, K; Holbrook, AM; Lau, E; Esporlas-Jewer, I; Troyan, S

    2006-01-01

    The COMPETE III Vascular Disease Tracker (C3VT) is a personalized, Web-based, clinical decision support tool that provides patients and physicians access to a patient’s 16 individual vascular risk markers, specific advice for each marker and links to best practices in vascular disease management. It utilizes the chronic care model1 so that physicians can better manage patients with chronic diseases. Over 1100 patients have been enrolled into the COMPETE III study to date.

  10. The value of decision tree analysis in planning anaesthetic care in obstetrics.

    PubMed

    Bamber, J H; Evans, S A

    2016-08-01

    The use of decision tree analysis is discussed in the context of the anaesthetic and obstetric management of a young pregnant woman with joint hypermobility syndrome with a history of insensitivity to local anaesthesia and a previous difficult intubation due to a tongue tumour. The multidisciplinary clinical decision process resulted in the woman being delivered without complication by elective caesarean section under general anaesthesia after an awake fibreoptic intubation. The decision process used is reviewed and compared retrospectively to a decision tree analytical approach. The benefits and limitations of using decision tree analysis are reviewed and its application in obstetric anaesthesia is discussed.

  11. Reliability analysis framework for computer-assisted medical decision systems

    SciTech Connect

    Habas, Piotr A.; Zurada, Jacek M.; Elmaghraby, Adel S.; Tourassi, Georgia D.

    2007-02-15

    We present a technique that enhances computer-assisted decision (CAD) systems with the ability to assess the reliability of each individual decision they make. Reliability assessment is achieved by measuring the accuracy of a CAD system with known cases similar to the one in question. The proposed technique analyzes the feature space neighborhood of the query case to dynamically select an input-dependent set of known cases relevant to the query. This set is used to assess the local (query-specific) accuracy of the CAD system. The estimated local accuracy is utilized as a reliability measure of the CAD response to the query case. The underlying hypothesis of the study is that CAD decisions with higher reliability are more accurate. The above hypothesis was tested using a mammographic database of 1337 regions of interest (ROIs) with biopsy-proven ground truth (681 with masses, 656 with normal parenchyma). Three types of decision models, (i) a back-propagation neural network (BPNN), (ii) a generalized regression neural network (GRNN), and (iii) a support vector machine (SVM), were developed to detect masses based on eight morphological features automatically extracted from each ROI. The performance of all decision models was evaluated using the Receiver Operating Characteristic (ROC) analysis. The study showed that the proposed reliability measure is a strong predictor of the CAD system's case-specific accuracy. Specifically, the ROC area index for CAD predictions with high reliability was significantly better than for those with low reliability values. This result was consistent across all decision models investigated in the study. The proposed case-specific reliability analysis technique could be used to alert the CAD user when an opinion that is unlikely to be reliable is offered. The technique can be easily deployed in the clinical environment because it is applicable with a wide range of classifiers regardless of their structure and it requires neither additional

  12. Reliability analysis framework for computer-assisted medical decision systems.

    PubMed

    Habas, Piotr A; Zurada, Jacek M; Elmaghraby, Adel S; Tourassi, Georgia D

    2007-02-01

    We present a technique that enhances computer-assisted decision (CAD) systems with the ability to assess the reliability of each individual decision they make. Reliability assessment is achieved by measuring the accuracy of a CAD system with known cases similar to the one in question. The proposed technique analyzes the feature space neighborhood of the query case to dynamically select an input-dependent set of known cases relevant to the query. This set is used to assess the local (query-specific) accuracy of the CAD system. The estimated local accuracy is utilized as a reliability measure of the CAD response to the query case. The underlying hypothesis of the study is that CAD decisions with higher reliability are more accurate. The above hypothesis was tested using a mammographic database of 1337 regions of interest (ROIs) with biopsy-proven ground truth (681 with masses, 656 with normal parenchyma). Three types of decision models, (i) a back-propagation neural network (BPNN), (ii) a generalized regression neural network (GRNN), and (iii) a support vector machine (SVM), were developed to detect masses based on eight morphological features automatically extracted from each ROI. The performance of all decision models was evaluated using the Receiver Operating Characteristic (ROC) analysis. The study showed that the proposed reliability measure is a strong predictor of the CAD system's case-specific accuracy. Specifically, the ROC area index for CAD predictions with high reliability was significantly better than for those with low reliability values. This result was consistent across all decision models investigated in the study. The proposed case-specific reliability analysis technique could be used to alert the CAD user when an opinion that is unlikely to be reliable is offered. The technique can be easily deployed in the clinical environment because it is applicable with a wide range of classifiers regardless of their structure and it requires neither additional

  13. Rita Kennedy: case analysis for decision-making.

    PubMed

    Wood, V; Rubin, S

    1992-02-01

    For nurse educators, the teaching environment has changed drastically. During the past two decades, the pressures of public, professional and educational accountability have impacted on the nursing instructor. Clinical teaching of student nurses has not escaped these pressures and poses concerns for nursing instructors. The Rita Kennedy case illustrates some of today's issues. To illustrate some of the difficulties in dealing with such issues, the case will be analysed using the Schnelle's model. Although Schnelle's framework was initially used for analysis for business cases, the framework for analysis and decision-making is also applicable in nursing education. The following analysis will first discuss assumptions, followed by an alternative course of action, decision and recommendation. However, to assist understanding, the information in the Kennedy case has been categorised in the Table.

  14. Decision Analysis Tools for Volcano Observatories

    NASA Astrophysics Data System (ADS)

    Hincks, T. H.; Aspinall, W.; Woo, G.

    2005-12-01

    Staff at volcano observatories are predominantly engaged in scientific activities related to volcano monitoring and instrumentation, data acquisition and analysis. Accordingly, the academic education and professional training of observatory staff tend to focus on these scientific functions. From time to time, however, staff may be called upon to provide decision support to government officials responsible for civil protection. Recognizing that Earth scientists may have limited technical familiarity with formal decision analysis methods, specialist software tools that assist decision support in a crisis should be welcome. A review is given of two software tools that have been under development recently. The first is for probabilistic risk assessment of human and economic loss from volcanic eruptions, and is of practical use in short and medium-term risk-informed planning of exclusion zones, post-disaster response, etc. A multiple branch event-tree architecture for the software, together with a formalism for ascribing probabilities to branches, have been developed within the context of the European Community EXPLORIS project. The second software tool utilizes the principles of the Bayesian Belief Network (BBN) for evidence-based assessment of volcanic state and probabilistic threat evaluation. This is of practical application in short-term volcano hazard forecasting and real-time crisis management, including the difficult challenge of deciding when an eruption is over. An open-source BBN library is the software foundation for this tool, which is capable of combining synoptically different strands of observational data from diverse monitoring sources. A conceptual vision is presented of the practical deployment of these decision analysis tools in a future volcano observatory environment. Summary retrospective analyses are given of previous volcanic crises to illustrate the hazard and risk insights gained from use of these tools.

  15. Uncertainty and objectivity in clinical decision making: a clinical case in emergency medicine.

    PubMed

    Engebretsen, Eivind; Heggen, Kristin; Wieringa, Sietse; Greenhalgh, Trisha

    2016-12-01

    The evidence-based practice and evidence-based medicine (EBM) movements have promoted standardization through guideline development methodologies based on systematic reviews and meta-analyses of best available research. EBM has challenged clinicians to question their reliance on practical reasoning and clinical judgement. In this paper, we argue that the protagonists of EBM position their mission as reducing uncertainty through the use of standardized methods for knowledge evaluation and use. With this drive towards uniformity, standardization and control comes a suspicion towards intuition, creativity and uncertainty as integral parts of medical practice. We question the appropriateness of attempts to standardize professional practice through a discussion of the importance of uncertainty. Greenhalgh's taxonomy of uncertainty is used to inform an analysis of the clinical reasoning occurring in a potentially life threatening emergency situation with a young patient. The case analysis is further developed by the use of the Canadian philosopher Bernard Lonergan's theory about understanding and objective knowing. According to Lonergan it is not by getting rid of or even by reducing uncertainty, but by attending systematically to it and by relating to it in a self-conscious way, that objective knowledge can be obtained. The paper concludes that uncertainty is not a regrettable and unavoidable aspect of decision making but a productive component of clinical reasoning.

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

    PubMed Central

    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. PMID:26958298

  17. 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.

  18. 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.

  19. Decision analysis for INEL hazardous waste storage

    SciTech Connect

    Page, L.A.; Roach, J.A.

    1994-01-01

    In mid-November 1993, the Idaho National Engineering Laboratory (INEL) Waste Reduction Operations Complex (WROC) Manager requested that the INEL Hazardous Waste Type Manager perform a decision analysis to determine whether or not a new Hazardous Waste Storage Facility (HWSF) was needed to store INEL hazardous waste (HW). In response to this request, a team was formed to perform a decision analysis for recommending the best configuration for storage of INEL HW. Personnel who participated in the decision analysis are listed in Appendix B. The results of the analysis indicate that the existing HWSF is not the best configuration for storage of INEL HW. The analysis detailed in Appendix C concludes that the best HW storage configuration would be to modify and use a portion of the Waste Experimental Reduction Facility (WERF) Waste Storage Building (WWSB), PBF-623 (Alternative 3). This facility was constructed in 1991 to serve as a waste staging facility for WERF incineration. The modifications include an extension of the current Room 105 across the south end of the WWSB and installing heating, ventilation, and bay curbing, which would provide approximately 1,600 ft{sup 2} of isolated HW storage area. Negotiations with the State to discuss aisle space requirements along with modifications to WWSB operating procedures are also necessary. The process to begin utilizing the WWSB for HW storage includes planned closure of the HWSF, modification to the WWSB, and relocation of the HW inventory. The cost to modify the WWSB can be funded by a reallocation of funding currently identified to correct HWSF deficiencies.

  20. Clinical decision making in exercise prescription for fall prevention.

    PubMed

    Haas, Romi; Maloney, Stephen; Pausenberger, Eva; Keating, Jennifer L; Sims, Jane; Molloy, Elizabeth; Jolly, Brian; Morgan, Prue; Haines, Terry

    2012-05-01

    Physical therapists often prescribe exercises for fall prevention. Understanding the factors influencing the clinical decision-making processes used by expert physical therapists working in specialist fall and balance clinics may assist other therapists in prescribing exercises for fall prevention with greater efficacy. The objective of this study was to describe the factors influencing the clinical decision-making processes used by expert physical therapists to prescribe exercises for fall prevention. This investigation was a qualitative study from a phenomenological perspective. Semistructured telephone interviews were conducted with 24 expert physical therapists recruited primarily from the Victorian Falls Clinic Coalition. Interviews focused on 3 exercise prescription contexts: face-to-face individual therapy, group exercise programs, and home exercise programs. Interviews elicited information about therapist practices and the therapist, patient, and environmental factors influencing the clinical decision-making processes for the selection of exercise setting, type, dosage (intensity, quantity, rest periods, duration, and frequency), and progression. Strategies for promoting adherence and safety were also discussed. Data were analyzed with a framework approach by 3 investigators. Participants described highly individualized exercise prescription approaches tailored to address key findings from physical assessments. Dissonance between prescribing a program that was theoretically correct on the basis of physiological considerations and prescribing one that a client would adhere to was evident. Safety considerations also were highly influential on the exercise type and setting prescribed. Terminology for describing the intensity of balance exercises was vague relative to terminology for describing the intensity of strength exercises. Physical therapists with expertise in fall prevention adopted an individualized approach to exercise prescription that was based on

  1. Application Analysis and Decision with Dynamic Analysis

    DTIC Science & Technology

    2014-12-01

    debugging tool, “ adb ”. The tool, adb , is used several times to interact with the mobile VM, by capturing the screenshot, sending SMS messages, executing...and logcat to watch log files. Analysis is ready to begin in earnest. The application is installed on the phone and then launched, all via adb

  2. Development and description of a decision analysis based decision support tool for stroke prevention in atrial fibrillation

    PubMed Central

    Thomson, R.; Robinson, A.; Greenaway, J.; Lowe, P.

    2002-01-01

    Background: There is an increasing move towards clinical decision making that engages the patient, which has led to the development and use of decision aids to support better decisions. The treatment of patients in atrial fibrillation (AF) with warfarin to prevent stroke is a decision that is sensitive to patient preferences as shown by a previous decision analysis. Aim: To develop a computerised decision support tool, building upon a previous decision analysis, which would engage individual patient preferences in reaching a shared decision on whether to take warfarin to prevent stroke. Methods: The development process had two main phases: (1) the development phase which employed focus groups and repeated interviews with GPs/practice nurses and patients alongside an iterative development of a computerised tool; (2) the training and testing phase in which GPs and practice nurses underwent training in the use of the tool, including the use of simulated patients. The tool was then used in a feasibility study in a small number of patients with AF to inform the design of a subsequent randomised controlled trial. Results: The prototype tool had three components: (1) derivation of an individual patient's values for relevant health states using a standard gamble; (2) presentation/discussion of a patient's risks of stroke using the Framingham equation and the benefits/risks of warfarin from a systematic literature review; and (3) decision making component incorporating the outcome of a Markov decision analysis model. Older patients could be taken through the decision analysis based computerised tool, and patients and clinicians welcomed information on risks and benefits of treatments. The tool required time and training to use. Patients' decisions in the feasibility phase did not necessarily coincide with the output of the decision analysis model, but decision conflict appeared to be reduced and both patients and GPs were satisfied with the process. Conclusions: It is

  3. Helping patients make choices about breast reconstruction: A decision analysis approach

    PubMed Central

    Sun, Clement S.; Cantor, Scott B.; Reece, Gregory P.; Fingeret, Michelle C.; Crosby, Melissa A.; Markey, Mia K.

    2014-01-01

    Decision analysis can help breast reconstruction patients and their surgeons to methodically evaluate clinical alternatives and make hard decisions. The purpose of this paper is to help plastic surgeons guide patients in making decisions though a case study in breast reconstruction. By making good decisions, patient outcomes may be improved. This paper aims to illustrate decision analysis techniques from the patient perspective with an emphasis on her values and preferences. We introduce normative decision-making through a fictional breast reconstruction patient and systematically build the decision basis to help her make a good decision. We broadly identify alternatives of breast reconstruction, propose types of outcomes that the patient should consider, discuss sources of probabilistic information and outcome values, and demonstrate how to make a good decision. The concepts presented here may be extended to other shared decision-making problems in plastic and reconstructive surgery. In addition, we discuss how sensitivity analysis may test the robustness of the decision and how to evaluate the quality of decisions. We also present tools to help implement these concepts in practice. Finally, we examine limitations that hamper adoption of patient decision analysis in reconstructive surgery and healthcare in general. In particular, we emphasize the need for routine collection of quality of life information, out-of-pocket expense, and recovery time. PMID:25357022

  4. Power and conflict in intensive care clinical decision making.

    PubMed

    Coombs, Maureen

    2003-06-01

    It is clear that current government policy places increasing emphasis on the need for flexible team working. This requires a shared understanding of roles and working practices. However, review of the current literature reveals that such a collaborative working environment has not as yet, been fully achieved. Role definitions and power bases based on traditional and historical boundaries continue to exist. This ethnographic study explores decision making between doctors and nurses in the intensive care environment in order to examine contemporary clinical roles in this clinical specialty. Three intensive care units were selected as field sites and data was collected through participant observation, ethnographic interviews and documentation. A key issue arising in this study is that whilst the nursing role in intensive care has changed, this has had little impact on how clinical decisions are made. Both medical and nursing staff identify conflict during patient management discussions. However, it is predominantly nurses who seek to redress this conflict area through developing specific behaviours for this clinical forum. Using this approach to resolve such team issues has grave implications if the government vision of interdisciplinary team working is to be realised.

  5. DYNAMICALLY EVOLVING CLINICAL PRACTICES AND IMPLICATIONS FOR PREDICTING MEDICAL DECISIONS

    PubMed Central

    CHEN, JONATHAN H; GOLDSTEIN, MARY K; ASCH, STEVEN M; ALTMAN, RUSS B

    2015-01-01

    Automatically data-mining clinical practice patterns from electronic health records (EHR) can enable prediction of future practices as a form of clinical decision support (CDS). Our objective is to determine the stability of learned clinical practice patterns over time and what implication this has when using varying longitudinal historical data sources towards predicting future decisions. We trained an association rule engine for clinical orders (e.g., labs, imaging, medications) using structured inpatient data from a tertiary academic hospital. Comparing top order associations per admission diagnosis from training data in 2009 vs. 2012, we find practice variability from unstable diagnoses with rank biased overlap (RBO)<0.35 (e.g., pneumonia) to stable admissions for planned procedures (e.g., chemotherapy, surgery) with comparatively high RBO>0.6. Predicting admission orders for future (2013) patients with associations trained on recent (2012) vs. older (2009) data improved accuracy evaluated by area under the receiver operating characteristic curve (ROC-AUC) 0.89 to 0.92, precision at ten (positive predictive value of the top ten predictions against actual orders) 30% to 37%, and weighted recall (sensitivity) at ten 2.4% to 13%, (P<10−10). Training with more longitudinal data (2009-2012) was no better than only using recent (2012) data. Secular trends in practice patterns likely explain why smaller but more recent training data is more accurate at predicting future practices. PMID:26776186

  6. How does Evidence Affect Clinical Decision-making?

    PubMed Central

    Fontelo, Paul; Liu, Fang; Uy, Raymonde C.

    2017-01-01

    In 1998, the “Evidence Cart” was introduced to provide decision-support tools at the point of care. A recent study showed that a majority of doctors who previously stated that evidence was not needed sought it nevertheless when it was easily available. In this study, invited clinicians were asked to rate the usefulness of evidence provided as abstracts and “the bottom-line summaries” (TBL) using a modified version of a Web app for searching PubMed and then specify reasons how it might affect their clinical decision-making. The responses were captured in the server’s log. One hundred and one reviews were submitted with 22 reviews for abstracts and 79 for TBLs. The overall usefulness Likert score (1=least useful, 7=most useful) was 5.02±1.96 (4.77±2.11 for abstracts and 5.09±1.92 for TBL). The basis for scores was specified in only about half (53/101) of reviews. The most frequent single reason (32%) was that it led to a new skill, diagnostic test, or treatment plan. Two or more reasons were given in 16 responses (30.2%). Two-thirds more responders used TBL summaries than abstracts confirming further that clinicians prefer convenient easy-to-read evidence at the point of care. This study seems to show similar results as the Evidence Cart study on the usefulness of evidence in clinical decision-making. PMID:26337628

  7. 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.

  8. A highly scalable, interoperable clinical decision support service

    PubMed Central

    Goldberg, Howard S; Paterno, Marilyn D; Rocha, Beatriz H; Schaeffer, Molly; Wright, Adam; Erickson, Jessica L; Middleton, Blackford

    2014-01-01

    Objective To create a clinical decision support (CDS) system that is shareable across healthcare delivery systems and settings over large geographic regions. Materials and methods The enterprise clinical rules service (ECRS) realizes nine design principles through a series of enterprise java beans and leverages off-the-shelf rules management systems in order to provide consistent, maintainable, and scalable decision support in a variety of settings. Results The ECRS is deployed at Partners HealthCare System (PHS) and is in use for a series of trials by members of the CDS consortium, including internally developed systems at PHS, the Regenstrief Institute, and vendor-based systems deployed at locations in Oregon and New Jersey. Performance measures indicate that the ECRS provides sub-second response time when measured apart from services required to retrieve data and assemble the continuity of care document used as input. Discussion We consider related work, design decisions, comparisons with emerging national standards, and discuss uses and limitations of the ECRS. Conclusions ECRS design, implementation, and use in CDS consortium trials indicate that it provides the flexibility and modularity needed for broad use and performs adequately. Future work will investigate additional CDS patterns, alternative methods of data passing, and further optimizations in ECRS performance. PMID:23828174

  9. Relationships Between Clinical Decision-Making Patterns and Self-Efficacy and Nursing Professionalism in Korean Pediatric Nurses.

    PubMed

    Choi, Miyoung; Kim, Jisoo

    2015-01-01

    As pediatric nurses must make decisions on a regular basis when caring for hospitalized children, clinical decision-making abilities are necessary in this profession. In the present study, we explored clinical decision-making patterns and their association with self-efficacy and nursing professionalism in pediatric nurses. We surveyed 173 pediatric nurses and analyzed the relationships between their clinical decision-making patterns and self-efficacy and nursing professionalism. Factor analysis identified 5 clinical decision-making patterns: patient-family-nurse collaborative (PNC), individual patient-oriented (IP), nurse model-oriented (NM), pattern-oriented intuitive (PI), and nursing knowledge-oriented (NK). The most frequently observed clinical decision-making pattern was the PNC. The self-efficacy and nursing professionalism were found to be higher in pediatric nurses using the IP and NM, and were lower for those using the PNC. Thus, the present results suggest that pediatric nurses' clinical decision-making patterns are influenced by nursing professionalism and self-efficacy. Therefore, intervention programs focusing on these variables might improve clinical decision-making in pediatric nurses. Copyright © 2015 Elsevier Inc. All rights reserved.

  10. SANDS - Sediment Analysis Network for Decision Support

    NASA Astrophysics Data System (ADS)

    Hardin, D. M.; Hawkins, L.; He, M.; Ebersole, S.

    2010-12-01

    Since the year 2000, Eastern Louisiana, coastal Mississippi, Alabama, and the western Florida panhandle have been affected by 28 tropical storms, seven of which were hurricanes. These tropical cyclones have significantly altered normal coastal processes and characteristics in the Gulf region through sediment disturbance. Although tides, seasonality, and agricultural development influence suspended sediment and sediment deposition over periods of time, tropical storm activity has the capability of moving the largest sediment loads in the shortest periods of time for coastal areas. The SANDS project is also investigating the effects of sediment immersed oil from the Deepwater Horizon disaster in April 2010 which has the potential to resurface as a result of tropical storm activity. The importance of sediments upon water quality, coastal erosion, habitats and nutrients has made their study and monitoring vital to decision makers in the region. Currently agencies such as United States Army Corps of Engineers (USACE), NASA, and Geological Survey of Alabama (GSA) are employing a variety of in-situ and airborne based measurements to assess and monitor sediment loading and deposition. These methods provide highly accurate information but are limited in geographic range, are not continuous over a region and, in the case of airborne LIDAR are expensive and do not recur on a regular basis. Multi-temporal and multi-spectral satellite imagery that shows tropical-storm-induced suspended sediment and storm-surge sediment deposits can provide decision makers with immediate and long-term information about the impacts of tropical storms and hurricanes. It can also be valuable for those conducting research and for projects related to coastal issues such as recovery, planning, management, and mitigation. The Sediment Analysis Network for Decision Support has generated a number of decision support products derived from MODIS, Landsat and SeaWiFS instruments that potentially support

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

    PubMed

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

    2016-10-03

    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

  12. Do MRI Structured Reports for Multiple Sclerosis Contain Adequate Information for Clinical Decision-Making?

    PubMed

    Alessandrino, Francesco; Pichiecchio, Anna; Mallucci, Giulia; Ghione, Emanuele; Romani, Alfredo; Bergamaschi, Roberto; Bastianello, Stefano

    2017-09-27

    Few data are available on how often MRI reports provide sufficient information for clinical decision-making in patients with multiple sclerosis (MS). The aim of this study is to evaluate if structured reporting of MRI in MS contain adequate information for clinical decision-making compared with nonstructured reporting. Brain and spinal cord MRI reports of patients with suspected or known MS before and after implementation of a structured reporting template were included. Brain and spinal cord MRI reports were assessed for presence of 11 and three key features relevant for management of MS, respectively. Three neurologists evaluated reports and images to assess lesion load, presence of sufficient information for clinical decision-making, and necessity to review MR images for clinical decision-making. Statistical analysis included t tests and chi-square tests. Thirty-two structured and 37 nonstructured reports were reviewed. Brain MRI nonstructured reports contained a mean ± SD of 3.59 ± 0.76 key features, and structured reports contained a mean of 10.25 ± 1.32 key features (p < 0.001). No significant difference was observed in the number of key features in nonstructured and structured spinal cord MRI reports. All neurologists could understand lesion load significantly more often when reading structured versus nonstructured reports (p < 0.001). For two of the three neurologists, structured reports contained adequate information for clinical decision-making more often than did nonstructured reports (p < 0.001 and p = 0.006). When reading nonstructured reports, two of the three neurologists needed to evaluate images significantly more often (p < 0.001). Structured reports of MRI in patients with MS provided more adequate information for clinical decision-making than nonstructured reports.

  13. Building a normative decision support system for clinical and operational risk management in hemodialysis.

    PubMed

    Cornalba, Chiara; Bellazzi, Roberto G; Bellazzi, Riccardo

    2008-09-01

    This paper describes the design and implementation of a decision support system for risk management in hemodialysis (HD) departments. The proposed system exploits a domain ontology to formalize the problem as a Bayesian network. It also relies on a software tool, able to automatically collect HD data, to learn the network conditional probabilities. By merging prior knowledge and the available data, the system allows to estimate risk profiles both for patients and HD departments. The risk management process is completed by an influence diagram that enables scenario analysis to choose the optimal decisions that mitigate a patient's risk. The methods and design of the decision support tool are described in detail, and the derived decision model is presented. Examples and case studies are also shown. The tool is one of the few examples of normative system explicitly conceived to manage operational and clinical risks in health care environments.

  14. 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

  15. 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.

  16. 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.

  17. What's wrong with decision analysis? Can the left brain influence the right?

    PubMed

    Detsky, A S; Redelmeier, D; Abrams, H B

    1987-01-01

    In order to gain insight into the impact that decision analysis has had on clinical practice, we presented a published report on the utility of renal biopsy for patients with idiopathic nephrotic syndrome to a group of nephrologists and residents at a teaching hospital. Although the analysis showed that the decision to biopsy or use empiric steroids without biopsy was a toss-up in terms of patient outcomes, only one of six staff nephrologists was willing to forego the biopsy strategy. Many clinicians in the group discussed the pure value of the information (e.g in making statements about prognosis) derived from the biopsy as an important factor in the choice of clinical strategies, a characteristic which was not captured by the published analysis. Also, some clinicians were uncomfortable with the entire simulation process as there were no "real patients" in the study. It appeared that clinical intuition based on pattern recognition could not be influenced by the linear logic of decision analysis. We suggest that major challenges for decision analysts include incorporating the value of information into analyses, selecting and cultivating the most appropriate clinical audience, and demonstrating the benefits of decision analysis for either the decision-making process or health outcomes. Without meeting these challenges, decision analysis may remain an esoteric field within academic medicine, which will continue to have limited impact on clinical practice.

  18. Clinical equipoise and treatment decisions in cervical spondylotic myelopathy.

    PubMed

    Benatar, Michael

    2007-02-01

    The primary objective of this study is to evaluate clinician attitudes towards the treatment of cervical spondylotic myelopathy (CSM) in order to determine whether clinical equipoise exists for a segment of this patient population. The secondary objective is to examine the factors that influence treatment decisions. Cross-sectional internet-based survey of neurologists, neurosurgeons and orthopedic surgeons. Between 40-60% of respondents recommended surgery for (1) patients with minimal or no symptoms, but incidentally discovered increased T2 signal within the cervical cord on MRI, (2) patients with mild symptoms and indentation of the cervical cord but without increased T2 signal and (3) those with at least moderately severe clinical findings accompanied by MRI showing effacement of the thecal sac but without indentation of the cord or increased T2 signal. The severity of the radiological abnormalities most strongly influence treatment decisions. We conclude that clinical equipoise does exist for certain groups of patients with CSM, suggesting that a randomized controlled trial could be performed in this population.

  19. Modeling decision support rule interactions in a clinical setting.

    PubMed

    Sordo, Margarita; Rocha, Beatriz H; Morales, Alfredo A; Maviglia, Saverio M; Oglio, Elisa Dell'Oglio; Fairbanks, Amanda; Aroy, Teal; Dubois, David; Bouyer-Ferullo, Sharon; Rocha, Roberto A

    2013-01-01

    Traditionally, rule interactions are handled at implementation time through rule task properties that control the order in which rules are executed. By doing so, knowledge about the behavior and interactions of decision rules is not captured at modeling time. We argue that this is important knowledge that should be integrated in the modeling phase. In this project, we build upon current work on a conceptual schema to represent clinical knowledge for decision support in the form of if then rules. This schema currently captures provenance of the clinical content, context where such content is actionable (i.e. constraints) and the logic of the rule itself. For this project, we borrowed concepts from both the Semantic Web (i.e., Ontologies) and Complex Adaptive Systems (CAS), to explore a conceptual approach for modeling rule interactions in an enterprise-wide clinical setting. We expect that a more comprehensive modeling will facilitate knowledge authoring, editing and update; foster consistency in rules implementation and maintenance; and develop authoritative knowledge repositories to promote quality, safety and efficacy of healthcare.

  20. Impact of dysphagia severity on clinical decision making via telerehabilitation.

    PubMed

    Ward, Elizabeth C; Burns, Clare L; Theodoros, Deborah G; Russell, Trevor G

    2014-04-01

    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. 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. 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. 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.

  1. Providers' Response to Clinical Decision Support for QT Prolonging Drugs.

    PubMed

    Sharma, Sunita; Martijn Bos, J; Tarrell, Robert F; Simon, Gyorgy J; Morlan, Bruce W; Ackerman, Michael J; Caraballo, Pedro J

    2017-09-02

    Commonly used drugs in hospital setting can cause QT prolongation and trigger life-threatening arrhythmias. We evaluate changes in prescribing behavior after the implementation of a clinical decision support system to prevent the use of QT prolonging medications in the hospital setting. We conducted a quasi-experimental study, before and after the implementation of a clinical decision support system integrated in the electronic medical record (QT-alert system). This system detects patients at risk of significant QT prolongation (QTc>500ms) and alerts providers ordering QT prolonging drugs. We reviewed the electronic health record to assess the provider's responses which were classified as "action taken" (QT drug avoided, QT drug changed, other QT drug(s) avoided, ECG monitoring, electrolytes monitoring, QT issue acknowledged, other actions) or "no action taken". Approximately, 15.5% (95/612) of the alerts were followed by a provider's action in the pre-intervention phase compared with 21% (228/1085) in the post-intervention phase (p=0.006). The most common type of actions taken during pre-intervention phase compared to post-intervention phase were ECG monitoring (8% vs. 13%, p=0.002) and QT issue acknowledgment (2.1% vs. 4.1%, p=0.03). Notably, there was no significant difference for other actions including QT drug avoided (p=0.8), QT drug changed (p=0.06) and other QT drug(s) avoided (p=0.3). Our study demonstrated that the QT alert system prompted a higher proportion of providers to take action on patients at risk of complications. However, the overall impact was modest underscoring the need for educating providers and optimizing clinical decision support to further reduce drug-induced QT prolongation.

  2. Development of Automated Aids for Decision Analysis

    DTIC Science & Technology

    1976-05-01

    called state variables (or environ- mental variables) since they define the state of the decision environment. Decision variables must be defined in such...Vaibeison Endlogetious STRUCTURAL MODELO Varabls ~State Variables* (INTERACTION MODEL) Outcome Variables’ (Either State or Prefeence$Decision...decisions and states of the environment. This type of model requires the decision maker to aggregate mentally the effects of the interactions among his

  3. [Economic studies and decision analysis as tools for decision making].

    PubMed

    Rodríguez-Pimentel, Leticia; Silva-Romo, Rodolfo; Wacher-Rodarte, Niels

    2007-01-01

    Management implies decision-making and economics deals with efficiency which means to obtain the best possible results with the available resources, and to compare such results with those that were foreseen. The economic evaluation comprises a set of techniques aimed at comparing resource allocation on alternate courses of action and its consequences. In health care, these results are the overall well-being of the society. This paper summarizes the techniques that are customarily used in economic evaluation, and intends to serve as an introductory text to increasing the ability of the readers to grasp original articles in the field of health economics.

  4. The potential use of decision analysis to support shared decision making in the face of uncertainty: the example of atrial fibrillation and warfarin anticoagulation

    PubMed Central

    Robinson, A; Thomson, R

    2000-01-01

    The quality of patient care is dependent upon the quality of the multitude of decisions that are made daily in clinical practice. Increasingly, modern health care is seeking to pursue better decisions (including an emphasis on evidence-based practice) and to engage patients more in decisions on their care. However, many treatment decisions are made in the face of clinical uncertainty and may be critically dependent upon patient preferences. This has led to attempts to develop decision support tools that enable patients and clinicians to make better decisions. One approach that may be of value is decision analysis, which seeks to create a rational framework for evaluating complex medical decisions and to provide a systematic way of integrating potential outcomes with probabilistic information such as that generated by randomised controlled trials of interventions. This paper describes decision analysis and discusses the potential of this approach with reference to the clinical decision as to whether to treat patients in atrial fibrillation with warfarin to reduce their risk of stroke. (Quality in Health Care 2000;9:238–244) Key Words: decision analysis; quality of care; atrial fibrillation PMID:11101709

  5. The Risky Shift in Policy Decision Making: A Comparative Analysis

    ERIC Educational Resources Information Center

    Wilpert, B.; And Others

    1976-01-01

    Based on analysis of data on 432 decision-makers from around the world, this study examines the decision-making phenomenon that individuals tend to move toward riskier decisions after group discussion. Findings of the analysis contradicted earlier studies, showing a consistent shift toward greater risk avoidance. Available from Elsevier Scientific…

  6. The Risky Shift in Policy Decision Making: A Comparative Analysis

    ERIC Educational Resources Information Center

    Wilpert, B.; And Others

    1976-01-01

    Based on analysis of data on 432 decision-makers from around the world, this study examines the decision-making phenomenon that individuals tend to move toward riskier decisions after group discussion. Findings of the analysis contradicted earlier studies, showing a consistent shift toward greater risk avoidance. Available from Elsevier Scientific…

  7. ISHM Decision Analysis Tool: Operations Concept

    NASA Technical Reports Server (NTRS)

    2006-01-01

    The state-of-the-practice Shuttle caution and warning system warns the crew of conditions that may create a hazard to orbiter operations and/or crew. Depending on the severity of the alarm, the crew is alerted with a combination of sirens, tones, annunciator lights, or fault messages. The combination of anomalies (and hence alarms) indicates the problem. Even with much training, determining what problem a particular combination represents is not trivial. In many situations, an automated diagnosis system can help the crew more easily determine an underlying root cause. Due to limitations of diagnosis systems,however, it is not always possible to explain a set of alarms with a single root cause. Rather, the system generates a set of hypotheses that the crew can select from. The ISHM Decision Analysis Tool (IDAT) assists with this task. It presents the crew relevant information that could help them resolve the ambiguity of multiple root causes and determine a method for mitigating the problem. IDAT follows graphical user interface design guidelines and incorporates a decision analysis system. I describe both of these aspects.

  8. 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

  9. Decision Support for Diabetes in Scotland: Implementation and Evaluation of a Clinical Decision Support System.

    PubMed

    Conway, Nicholas; Adamson, Karen A; Cunningham, Scott G; Emslie Smith, Alistair; Nyberg, Peter; Smith, Blair H; Wales, Ann; Wake, Deborah J

    2017-09-01

    Automated clinical decision support systems (CDSS) are associated with improvements in health care delivery to those with long-term conditions, including diabetes. A CDSS was introduced to two Scottish regions (combined diabetes population ~30 000) via a national diabetes electronic health record. This study aims to describe users' reactions to the CDSS and to quantify impact on clinical processes and outcomes over two improvement cycles: December 2013 to February 2014 and August 2014 to November 2014. Feedback was sought via patient questionnaires, health care professional (HCP) focus groups, and questionnaires. Multivariable regression was used to analyze HCP SCI-Diabetes usage (with respect to CDSS message presence/absence) and case-control comparison of clinical processes/outcomes. Cases were patients whose HCP received a CDSS messages during the study period. Closely matched controls were selected from regions outside the study, following similar clinical practice (without CDSS). Clinical process measures were screening rates for diabetes-related complications. Clinical outcomes included HbA1c at 1 year. The CDSS had no adverse impact on consultations. HCPs were generally positive toward CDSS and used it within normal clinical workflow. CDSS messages were generated for 5692 cases, matched to 10 667 controls. Following clinic, the probability of patients being appropriately screened for complications more than doubled for most measures. Mean HbA1c improved in cases and controls but more so in cases (-2.3 mmol/mol [-0.2%] versus -1.1 [-0.1%], P = .003). The CDSS was well received; associated with improved efficiencies in working practices; and large improvements in guideline adherence. These evidence-based, early interventions can significantly reduce costly and devastating complications.

  10. Risk assessment and clinical decision making for colorectal cancer screening.

    PubMed

    Schroy, Paul C; Caron, Sarah E; Sherman, Bonnie J; Heeren, Timothy C; Battaglia, Tracy A

    2015-10-01

    Shared decision making (SDM) related to test preference has been advocated as a potentially effective strategy for increasing adherence to colorectal cancer (CRC) screening, yet primary care providers (PCPs) are often reluctant to comply with patient preferences if they differ from their own. Risk stratification advanced colorectal neoplasia (ACN) provides a rational strategy for reconciling these differences. To assess the importance of risk stratification in PCP decision making related to test preference for average-risk patients and receptivity to use of an electronic risk assessment tool for ACN to facilitate SDM. Mixed methods, including qualitative key informant interviews and a cross-sectional survey. PCPs at an urban, academic safety-net institution. Screening preferences, factors influencing patient recommendations and receptivity to use of a risk stratification tool. Nine PCPs participated in interviews and 57 completed the survey. Despite an overwhelming preference for colonoscopy by 95% of respondents, patient risk (67%) and patient preferences (63%) were more influential in their decision making than patient comorbidities (31%; P < 0.001). Age was the single most influential risk factor (excluding family history), with <20% of respondents choosing factors other than age. Most respondents reported that they would be likely to use a risk stratification tool in their practice either 'often' (43%) or sometimes (53%). Risk stratification was perceived to be important in clinical decision making, yet few providers considered risk factors other than age for average-risk patients. Providers were receptive to the use of a risk assessment tool for ACN when recommending an appropriate screening test for select patients. © 2013 John Wiley & Sons Ltd.

  11. Evaluation of RxNorm for Medication Clinical Decision Support.

    PubMed

    Freimuth, Robert R; Wix, Kelly; Zhu, Qian; Siska, Mark; Chute, Christopher G

    2014-01-01

    We evaluated the potential use of RxNorm to provide standardized representations of generic drug name and route of administration to facilitate management of drug lists for clinical decision support (CDS) rules. We found a clear representation of generic drug name but not route of administration. We identified several issues related to data quality, including erroneous or missing defined relationships, and the use of different concept hierarchies to represent the same drug. More importantly, we found extensive semantic precoordination of orthogonal concepts related to route and dose form, which would complicate the use of RxNorm for drug-based CDS. This study demonstrated that while RxNorm is a valuable resource for the standardization of medications used in clinical practice, additional work is required to enhance the terminology so that it can support expanded use cases, such as managing drug lists for CDS.

  12. 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.

  13. Studying the vendor perspective on clinical decision support.

    PubMed

    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.

  14. 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

  15. Patient management scenario: a framework for clinical decision and prognosis.

    PubMed

    Gospodarowicz, Mary; O'Sullivan, Brian

    2003-01-01

    The depiction of prognosis is one of the main activities and a mainstay in medical practice. In cancer, as in other diseases, the prognosis differs for a variety of situations and evolves with time and with medical interventions. Although most commonly described at diagnosis, prognosis may be defined at any time during the course of the disease and for any endpoint including response to therapy, failure of treatment, survival, or preservation of function, and so forth. To facilitate the accurate portrayal of the future, the prognosis should be defined within a specific setting, referred to as a 'management scenario'. In the concept of a management scenario, the prognosis is defined using systematically considered prognostic factors, interventions and the outcome of interest. A deliberate and careful determination of prognosis is essential to clinical decision making and patient care. We illustrate the use of the concept of management scenario in several clinical examples.

  16. Evaluation of RxNorm for Medication Clinical Decision Support

    PubMed Central

    Freimuth, Robert R.; Wix, Kelly; Zhu, Qian; Siska, Mark; Chute, Christopher G.

    2014-01-01

    We evaluated the potential use of RxNorm to provide standardized representations of generic drug name and route of administration to facilitate management of drug lists for clinical decision support (CDS) rules. We found a clear representation of generic drug name but not route of administration. We identified several issues related to data quality, including erroneous or missing defined relationships, and the use of different concept hierarchies to represent the same drug. More importantly, we found extensive semantic precoordination of orthogonal concepts related to route and dose form, which would complicate the use of RxNorm for drug-based CDS. This study demonstrated that while RxNorm is a valuable resource for the standardization of medications used in clinical practice, additional work is required to enhance the terminology so that it can support expanded use cases, such as managing drug lists for CDS. PMID:25954360

  17. Clinical and pharmacogenomic data mining: 2. A simple method for the combination of information from associations and multivariances to facilitate analysis, decision, and design in clinical research and practice.

    PubMed

    Robson, Barry; Mushlin, Richard

    2004-01-01

    The physician and researcher must ultimately be able to combine qualitative and quantitative features from a variety of combinations of observations on data of many component items (i.e., many dimensions), and hence reach simple conclusions about interpretation, rational courses of action, and design. In the first paper of this series, it was noted that such needs are challenging the classical means of using statistics. Hence, the paper proposed the use of a Generalized Theory of Expected Information or "Zeta Theory". The conjoint event [a,b,c,..] is seen as a rule of association for a,b,c,.. associated with a rule strength I(a;b;c;...) = xi(s,o[a,b,c,..]) - xi (s,e[a,b,c,...]), where xi is the incomplete Zeta Function. Here, o[a,b,c,...] is the observed, and e[a,b,c,..] the expected, frequency of occurrence of conjoint event [a,b,c,...]. The present paper explores how output from this approach might be assembled in a form better suited for decision support. Related to this is the difficulty that the treatment of covariance and multivariance was previously rendered as a "fuzzy association" so that the output would fall into a similar form as the true associations, but this was a somewhat ad hoc approach in which only the final I( ) had any meaning. Users at clinical research sites had subsequently requested an alternative approach in which "effective frequencies" o[ ] and e[ ] calculated from the above variances and used to evaluate I( ) give some intuitive feeling analogous to the association treatment, and this is explored here. Though the present paper is theoretical, real examples are used to illustrate application. One clinical-genomic example illustrates experimental design by identifying data which is, or is not, statistically germane to the study. We also report on some impressions based on applying these techniques in studies of real, extensive patient record data which are now emerging, as well as on molecular design data originally studied in part to

  18. Application of portfolio theory in decision tree analysis.

    PubMed

    Galligan, D T; Ramberg, C; Curtis, C; Ferguson, J; Fetrow, J

    1991-07-01

    A general application of portfolio analysis for herd decision tree analysis is described. In the herd environment, this methodology offers a means of employing population-based decision strategies that can help the producer control economic variation in expected return from a given set of decision options. An economic decision tree model regarding the use of prostaglandin in dairy cows with undetected estrus was used to determine the expected return of the decisions to use prostaglandin and breed on a timed basis, use prostaglandin and then breed on sign of estrus, or breed on signs of estrus. The risk attributes of these decision alternatives were calculated from the decision tree, and portfolio theory was used to find the efficient decision combinations (portfolios with the highest return for a given variance). The resulting combinations of decisions could be used to control return variation.

  19. 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.

  20. Clinical decision rules to distinguish between bacterial and aseptic meningitis

    PubMed Central

    Dubos, F; Lamotte, B; Bibi‐Triki, F; Moulin, F; Raymond, J; Gendrel, D; Bréart, G; Chalumeau, M

    2006-01-01

    Background Clinical decision rules have been derived to distinguish between bacterial and aseptic meningitis in the emergency room to avoid unnecessary antibiotic treatments and hospitalisations. Aims To evaluate the reproducibility and to compare the diagnostic performance of five clinical decision rules. Methods All children hospitalised for bacterial meningitis between 1995 and 2004 or aseptic meningitis between 2000 and 2004 have been included in a retrospective cohort study. Sensitivity and specificity were calculated by applying each rule to the patients. The best rule was a priori defined as the one yielding 100% sensitivity for bacterial meningitis, the highest specificity, and the greatest simplicity for a bedside application. Results Among the 166 patients included, 20 had bacterial meningitis and 146 had aseptic meningitis. Although three rules achieved 100% sensitivity (95% CI 84–100), one had a significantly lower specificity (13%, 95% CI 8–19) than those of the other two rules (57%, 95% CI 48–65; and 66%, 95% CI 57–73), which were not statistically different. The ease of manual computation of the rule developed by Nigrovic et al (a simple list of five items: seizure, blood neutrophil count, cerebrospinal fluid (CSF) Gram stain, CSF protein, CSF neutrophil count) was higher than the one developed by Bonsu and Harper. Conclusion On our population, the rule derived by Nigrovic et al had the best balance between accuracy and simplicity of manual computation and could help to avoid two thirds of unnecessary antibiotic treatments and hospitalisations. PMID:16595647

  1. Modelling elderly cardiac patients decision making using Cognitive Work Analysis: identifying requirements for patient decision aids.

    PubMed

    Dhukaram, Anandhi Vivekanandan; Baber, Chris

    2015-06-01

    Patients make various healthcare decisions on a daily basis. Such day-to-day decision making can have significant consequences on their own health, treatment, care, and costs. While decision aids (DAs) provide effective support in enhancing patient's decision making, to date there have been few studies examining patient's decision making process or exploring how the understanding of such decision processes can aid in extracting requirements for the design of DAs. This paper applies Cognitive Work Analysis (CWA) to analyse patient's decision making in order to inform requirements for supporting self-care decision making. This study uses focus groups to elicit information from elderly cardiovascular disease (CVD) patients concerning a range of decision situations they face on a daily basis. Specifically, the focus groups addressed issues related to the decision making of CVD in terms of medication compliance, pain, diet and exercise. The results of these focus groups are used to develop high level views using CWA. CWA framework decomposes the complex decision making problem to inform three approaches to DA design: one design based on high level requirements; one based on a normative model of decision-making for patients; and the third based on a range of heuristics that patients seem to use. CWA helps in extracting and synthesising decision making from different perspectives: decision processes, work organisation, patient competencies and strategies used in decision making. As decision making can be influenced by human behaviour like skills, rules and knowledge, it is argued that patients require support to different types of decision making. This paper also provides insights for designers in using CWA framework for the design of effective DAs to support patients in self-management. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  2. Influence of data display formats on physician investigators’ decisions to stop clinical trials: prospective trial with repeated measures

    PubMed Central

    Elting, Linda S; Martin, Charles G; Cantor, Scott B; Rubenstein, Edward B

    1999-01-01

    Objective To examine the effect of the method of data display on physician investigators’ decisions to stop hypothetical clinical trials for an unplanned statistical analysis. Design Prospective, mixed model design with variables between subjects and within subjects (repeated measures). Setting Comprehensive cancer centre. Participants 34 physicians, stratified by academic rank, who were conducting clinical trials. Interventions Participants were shown tables, pie charts, bar graphs, and icon displays containing hypothetical data from a clinical trial and were asked to decide whether to continue the trial or stop for an unplanned statistical analysis. Main outcome measure Percentage of accurate decisions with each type of display. Results Accuracy of decisions was affected by the type of data display and positive or negative framing of the data. More correct decisions were made with icon displays than with tables, pie charts, and bar graphs (82% v 68%, 56%, and 43%, respectively; P=0.03) and when data were negatively framed rather than positively framed in tables (93% v 47%; P=0.004). Conclusions Clinical investigators’ decisions can be affected by factors unrelated to the actual data. In the design of clinical trials information systems, careful consideration should be given to the method by which data are framed and displayed in order to reduce the impact of these extraneous factors. Key messagesIn clinical trials formal interim monitoring points, at which statistical tests are conducted, are designated a priori, but investigators also conduct informal interim monitoring, when statistical tests are not usedThis study investigated the effect of the method of displaying results on clinical investigators’ decisions to conduct unplanned analyses of a hypothetical clinical trialThe method of displaying results significantly influenced the accuracy of decisions, as did the framing of these results (positive or negative)The display formats preferred by the

  3. Cost/Effort Drivers and Decision Analysis

    NASA Technical Reports Server (NTRS)

    Seidel, Jonathan

    2010-01-01

    Engineering trade study analyses demand consideration of performance, cost and schedule impacts across the spectrum of alternative concepts and in direct reference to product requirements. Prior to detailed design, requirements are too often ill-defined (only goals ) and prone to creep, extending well beyond the Systems Requirements Review. Though lack of engineering design and definitive requirements inhibit the ability to perform detailed cost analyses, affordability trades still comprise the foundation of these future product decisions and must evolve in concert. This presentation excerpts results of the recent NASA subsonic Engine Concept Study for an Advanced Single Aisle Transport to demonstrate an affordability evaluation of performance characteristics and the subsequent impacts on engine architecture decisions. Applying the Process Based Economic Analysis Tool (PBEAT), development cost, production cost, as well as operation and support costs were considered in a traditional weighted ranking of the following system-level figures of merit: mission fuel burn, take-off noise, NOx emissions, and cruise speed. Weighting factors were varied to ascertain the architecture ranking sensitivities to these performance figures of merit with companion cost considerations. A more detailed examination of supersonic variable cycle engine cost is also briefly presented, with observations and recommendations for further refinements.

  4. The anatomy of clinical decision-making in multidisciplinary cancer meetings

    PubMed Central

    Soukup, Tayana; Petrides, Konstantinos V.; Lamb, Benjamin W.; Sarkar, Somita; Arora, Sonal; Shah, Sujay; Darzi, Ara; Green, James S. A.; Sevdalis, Nick

    2016-01-01

    Abstract In the UK, treatment recommendations for patients with cancer are routinely made by multidisciplinary teams in weekly meetings. However, their performance is variable. The aim of this study was to explore the underlying structure of multidisciplinary decision-making process, and examine how it relates to team ability to reach a decision. This is a cross-sectional observational study consisting of 1045 patient reviews across 4 multidisciplinary cancer teams from teaching and community hospitals in London, UK, from 2010 to 2014. Meetings were chaired by surgeons. We used a validated observational instrument (Metric for the Observation of Decision-making in Cancer Multidisciplinary Meetings) consisting of 13 items to assess the decision-making process of each patient discussion. Rated on a 5-point scale, the items measured quality of presented patient information, and contributions to review by individual disciplines. A dichotomous outcome (yes/no) measured team ability to reach a decision. Ratings were submitted to Exploratory Factor Analysis and regression analysis. The exploratory factor analysis produced 4 factors, labeled “Holistic and Clinical inputs” (patient views, psychosocial aspects, patient history, comorbidities, oncologists’, nurses’, and surgeons’ inputs), “Radiology” (radiology results, radiologists’ inputs), “Pathology” (pathology results, pathologists’ inputs), and “Meeting Management” (meeting chairs’ and coordinators’ inputs). A negative cross-loading was observed from surgeons’ input on the fourth factor with a follow-up analysis showing negative correlation (r = −0.19, P < 0.001). In logistic regression, all 4 factors predicted team ability to reach a decision (P < 0.001). Hawthorne effect is the main limitation of the study. The decision-making process in cancer meetings is driven by 4 underlying factors representing the complete patient profile and contributions to case review by all core

  5. Comparative impact of guidelines, clinical data, and decision support on prescribing decisions: an interactive web experiment with simulated cases.

    PubMed

    Sintchenko, Vitali; Coiera, Enrico; Iredell, Jonathan R; Gilbert, Gwendolyn L

    2004-01-01

    The aim of this study was to compare the clinical impact of computerized decision support with and without electronic access to clinical guidelines and laboratory data on antibiotic prescribing decisions. A crossover trial was conducted of four levels of computerized decision support-no support, antibiotic guidelines, laboratory reports, and laboratory reports plus a decision support system (DSS), randomly allocated to eight simulated clinical cases accessed by the Web. Rate of intervention adoption was measured by frequency of accessing information support, cost of use was measured by time taken to complete each case, and effectiveness of decision was measured by correctness of and self-reported confidence in individual prescribing decisions. Clinical impact score was measured by adoption rate and decision effectiveness. Thirty-one intensive care and infectious disease specialist physicians (ICPs and IDPs) participated in the study. Ventilator-associated pneumonia treatment guidelines were used in 24 (39%) of the 62 case scenarios for which they were available, microbiology reports in 36 (58%), and the DSS in 37 (60%). The use of all forms of information support did not affect clinicians' confidence in their decisions. Their use of the DSS plus microbiology report improved the agreement of decisions with those of an expert panel from 65% to 97% (p=0.0002), or to 67% (p=0.002) when antibiotic guidelines only were accessed. Significantly fewer IDPs than ICPs accessed information support in making treatment decisions. On average, it took 245 seconds to make a decision using the DSS compared with 113 seconds for unaided prescribing (p<0.001). The DSS plus microbiology reports had the highest clinical impact score (0.58), greater than that of electronic guidelines (0.26) and electronic laboratory reports (0.45). When used, computer-based decision support significantly improved decision quality. In measuring the impact of decision support systems, both their

  6. Sediment Analysis Network for Decision Support (SANDS)

    NASA Astrophysics Data System (ADS)

    Hardin, D. M.; Keiser, K.; Graves, S. J.; Conover, H.; Ebersole, S.

    2009-12-01

    Since the year 2000, Eastern Louisiana, coastal Mississippi, Alabama, and the western Florida panhandle have been affected by 28 tropical storms, seven of which were hurricanes. These tropical cyclones have significantly altered normal coastal processes and characteristics in the Gulf region through sediment disturbance. Although tides, seasonality, and agricultural development influence suspended sediment and sediment deposition over periods of time, tropical storm activity has the capability of moving the largest sediment loads in the shortest periods of time for coastal areas. The importance of sediments upon water quality, coastal erosion, habitats and nutrients has made their study and monitoring vital to decision makers in the region. Currently agencies such as United States Army Corps of Engineers (USACE), NASA, and Geological Survey of Alabama (GSA) are employing a variety of in-situ and airborne based measurements to assess and monitor sediment loading and deposition. These methods provide highly accurate information but are limited in geographic range, are not continuous over a region and, in the case of airborne LIDAR are expensive and do not recur on a regular basis. Multi-temporal and multi-spectral satellite imagery that shows tropical-storm-induced suspended sediment and storm-surge sediment deposits can provide decision makers with immediate and long-term information about the impacts of tropical storms and hurricanes. It can also be valuable for those conducting research and for projects related to coastal issues such as recovery, planning, management, and mitigation. The recently awarded Sediment Analysis Network for Decision Support will generate decision support products using NASA satellite observations from MODIS, Landsat and SeaWiFS instruments to support resource management, planning, and decision making activities in the Gulf of Mexico. Specifically, SANDS will generate decision support products that address the impacts of tropical storms

  7. Using imprecise probabilities to address the questions of inference and decision in randomized clinical trials.

    PubMed

    Gurrin, Lyle C; Sly, Peter D; Burton, Paul R

    2002-05-01

    Randomized controlled clinical trials play an important role in the development of new medical therapies. There is, however, an ethical issue surrounding the use of randomized treatment allocation when the patient is suffering from a life threatening condition and requires immediate treatment. Such patients can only benefit from the treatment they actually receive and not from the alternative therapy, even if it ultimately proves to be superior. We discuss a novel new way to analyse data from such clinical trials based on the use of the recently developed theory of imprecise probabilities. This work draws an explicit distinction between the related but nevertheless distinct questions of inference and decision in clinical trials. The traditional question of scientific interest asks 'Which treatment offers the greater chance of success?' and is the primary reason for conducting the clinical trial. The question of decision concerns the welfare of the patients in the clinical trial, asking whether the accumulated evidence favours one treatment over the other to such an extent that the next patient should decline randomization and instead express a preference for one treatment. Consideration of the decision question within the framework of imprecise probabilities leads to a mathematical definition of equipoise and a method for governing the randomization protocol of a clinical trial. This paper describes in detail the protocol for the conduct of clinical trials based on this new method of analysis, which is illustrated in a retrospective analysis of data from a clinical trial comparing the anti-emetic drugs ondansetron and droperidol in the treatment of postoperative nausea and vomiting. The proposed methodology is compared quantitatively using computer simulation studies with conventional clinical trial designs and is shown to maintain high statistical power with reduced sample sizes, at the expense of a high type I error rate that we argue is irrelevant in some

  8. Educational Planning and Decision Making: The Use of Decision and Control Analysis.

    ERIC Educational Resources Information Center

    Weathersby, George B.

    This paper provides a concise statement of the current technology of quantitative analysis as applied to university decisionmaking. The author argues that quantitative decision analysis can be particularly relevant in situations involving stress, uncertainty, large amounts of resources, and institutional survival. The process of decision analysis…

  9. Can patient decision aids help people make good decisions about participating in clinical trials? A study protocol

    PubMed Central

    Brehaut, Jamie C; Lott, Alison; Fergusson, Dean A; Shojania, Kaveh G; Kimmelman, Jonathan; Saginur, Raphael

    2008-01-01

    Background Evidence shows that the standard process for obtaining informed consent in clinical trials can be inadequate, with study participants frequently not understanding even basic information fundamental to giving informed consent. Patient decision aids are effective decision support tools originally designed to help patients make difficult treatment or screening decisions. We propose that incorporating decision aids into the informed consent process will improve the extent to which participants make decisions that are informed and consistent with their preferences. A mixed methods study will test this proposal. Methods Phase one of this project will involve assessment of a stratified random sample of 50 consent documents from recently completed investigator-initiated clinical trials, according to existing standards for supporting good decision making. Phase two will involve interviews of a purposive sample of 50 trial participants (10 participants from each of five different clinical areas) about their experience of the informed consent process, and how it could be improved. In phase three, we will convert consent forms for two completed clinical trials into decision aids and pilot test these new tools using a user-centered design approach, an iterative development process commonly employed in computer usability literature. In phase four, we will conduct a pilot observational study comparing the new tools to standard consent forms, with potential recruits to two hypothetical clinical trials. Outcomes will include knowledge of key aspects of the decision, knowledge of the probabilities of different outcomes, decisional conflict, the hypothetical participation decision, and qualitative impressions of the experience. Discussion This work will provide initial evidence about whether a patient decision aid can improve the informed consent process. The larger goal of this work is to examine whether study recruitment can be improved from (barely) informed consent

  10. 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

  11. Demographics of reintroduced populations: estimation, modeling, and decision analysis

    USGS Publications Warehouse

    Converse, Sarah J.; Moore, Clinton T.; Armstrong, Doug P.

    2013-01-01

    Reintroduction can be necessary for recovering populations of threatened species. However, the success of reintroduction efforts has been poorer than many biologists and managers would hope. To increase the benefits gained from reintroduction, management decision making should be couched within formal decision-analytic frameworks. Decision analysis is a structured process for informing decision making that recognizes that all decisions have a set of components—objectives, alternative management actions, predictive models, and optimization methods—that can be decomposed, analyzed, and recomposed to facilitate optimal, transparent decisions. Because the outcome of interest in reintroduction efforts is typically population viability or related metrics, models used in decision analysis efforts for reintroductions will need to include population models. In this special section of the Journal of Wildlife Management, we highlight examples of the construction and use of models for informing management decisions in reintroduced populations. In this introductory contribution, we review concepts in decision analysis, population modeling for analysis of decisions in reintroduction settings, and future directions. Increased use of formal decision analysis, including adaptive management, has great potential to inform reintroduction efforts. Adopting these practices will require close collaboration among managers, decision analysts, population modelers, and field biologists.

  12. Biostatistics in clinical decision making for cardiothoracic radiologists.

    PubMed

    Zurakowski, David; Johnson, Victor M; Lee, Edward Y

    2013-11-01

    Cardiothoracic radiologists are intuitively aware of sensitivity and specificity as they pertain to diagnostic tests involving clinical information. However, many cardiothoracic radiologists are unfamiliar with odds ratios, likelihood ratios, predictive values, and receiver operating characteristic (ROC) curves, which provide more information about the performance of a test. Our article will first review the fundamental concepts of sensitivity, specificity, predictive values, and likelihood ratios. The ROC curve methodology will be covered with an emphasis on creating a look-up table, a straightforward table that communicates important information to the clinician to aid in diagnosis. The article reviews sensitivity and specificity, as well as predictive values, logistic regression, and ROC curves, using conceptual principles without unnecessary mathematical rigor. We will apply principles of sensitivity and specificity to continuous measurements by constructing ROC curves in order to tie together key ideas in diagnostic decision making. Three clinical examples are presented to illustrate these fundamental statistical concepts: predictors of pulmonary embolism in children, use of dobutamine-cardiac magnetic resonance imaging to identify impaired ventricular function in patients who have suffered a myocardial infarction, and diagnostic accuracy of 64-multidetector row computed tomography to identify occluded vessels in adult patients with suspected coronary artery disease. In addition, a glossary is provided at the end of the article with key terms important in diagnostic imaging. An understanding of the concepts presented will assist cardiothoracic radiologists in critically discerning the usefulness of diagnostic tests and how these statistics can be applied to make judgments and decisions that are essential to clinical practice.

  13. Evidence-based practice: how to perform and use systematic reviews for clinical decision-making.

    PubMed

    Kranke, Peter

    2010-09-01

    One approach to clinical decision-making requires the integration of the best available research evidence with individual clinical expertise and patient values, and is known as evidence-based medicine (EBM). In clinical decision-making with the current best evidence, systematic reviews have an important role. This review article covers the basic principles of systematic reviews and meta-analyses, and their role in the process of evidence-based decision-making. The problems associated with traditional narrative reviews are discussed, as well as the way systematic reviews limit bias associated with the assembly, critical appraisal and synthesis of studies addressing specific clinical questions. The relevant steps in writing a systematic review from the formulation of an initial research question to sensitivity analyses in conjunction with the combined analysis of the pooled data are described. Important issues that need to be considered when appraising a systematic review or meta-analysis are outlined. Some of the terms that are used in the reporting of systematic reviews and meta-analyses, such as relative risk, confidence interval, Forest plot or L'Abbé plot, will be introduced and explained.

  14. DECISION ANALYSIS OF INCINERATION COSTS IN SUPERFUND SITE REMEDIATION

    EPA Science Inventory

    This study examines the decision-making process of the remedial design (RD) phase of on-site incineration projects conducted at Superfund sites. Decisions made during RD affect the cost and schedule of remedial action (RA). Decision analysis techniques are used to determine the...

  15. Evaluation of a novel electronic genetic screening and clinical decision support tool in prenatal clinical settings.

    PubMed

    Edelman, Emily A; Lin, Bruce K; Doksum, Teresa; Drohan, Brian; Edelson, Vaughn; Dolan, Siobhan M; Hughes, Kevin; O'Leary, James; Vasquez, Lisa; Copeland, Sara; Galvin, Shelley L; DeGroat, Nicole; Pardanani, Setul; Gregory Feero, W; Adams, Claire; Jones, Renee; Scott, Joan

    2014-07-01

    "The Pregnancy and Health Profile" (PHP) is a free prenatal genetic screening and clinical decision support (CDS) software tool for prenatal providers. PHP collects family health history (FHH) during intake and provides point-of-care risk assessment for providers and education for patients. This pilot study evaluated patient and provider responses to PHP and effects of using PHP in practice. PHP was implemented in four clinics. Surveys assessed provider confidence and knowledge and patient and provider satisfaction with PHP. Data on the implementation process were obtained through semi-structured interviews with administrators. Quantitative survey data were analyzed using Chi square test, Fisher's exact test, paired t tests, and multivariate logistic regression. Open-ended survey questions and interviews were analyzed using qualitative thematic analysis. Of the 83% (513/618) of patients that provided feedback, 97% felt PHP was easy to use and 98% easy to understand. Thirty percent (21/71) of participating physicians completed both pre- and post-implementation feedback surveys [13 obstetricians (OBs) and 8 family medicine physicians (FPs)]. Confidence in managing genetic risks significantly improved for OBs on 2/6 measures (p values ≤0.001) but not for FPs. Physician knowledge did not significantly change. Providers reported value in added patient engagement and reported mixed feedback about the CDS report. We identified key steps, resources, and staff support required to implement PHP in a clinical setting. To our knowledge, this study is the first to report on the integration of patient-completed, electronically captured and CDS-enabled FHH software into primary prenatal practice. PHP is acceptable to patients and providers. Key to successful implementation in the future will be customization options and interoperability with electronic health records.

  16. Cloud Service Selection Using Multicriteria Decision Analysis

    PubMed Central

    Anuar, Nor Badrul; Shiraz, Muhammad; Haque, Israat Tanzeena

    2014-01-01

    Cloud computing (CC) has recently been receiving tremendous attention from the IT industry and academic researchers. CC leverages its unique services to cloud customers in a pay-as-you-go, anytime, anywhere manner. Cloud services provide dynamically scalable services through the Internet on demand. Therefore, service provisioning plays a key role in CC. The cloud customer must be able to select appropriate services according to his or her needs. Several approaches have been proposed to solve the service selection problem, including multicriteria decision analysis (MCDA). MCDA enables the user to choose from among a number of available choices. In this paper, we analyze the application of MCDA to service selection in CC. We identify and synthesize several MCDA techniques and provide a comprehensive analysis of this technology for general readers. In addition, we present a taxonomy derived from a survey of the current literature. Finally, we highlight several state-of-the-art practical aspects of MCDA implementation in cloud computing service selection. The contributions of this study are four-fold: (a) focusing on the state-of-the-art MCDA techniques, (b) highlighting the comparative analysis and suitability of several MCDA methods, (c) presenting a taxonomy through extensive literature review, and (d) analyzing and summarizing the cloud computing service selections in different scenarios. PMID:24696645

  17. Cloud service selection using multicriteria decision analysis.

    PubMed

    Whaiduzzaman, Md; Gani, Abdullah; Anuar, Nor Badrul; Shiraz, Muhammad; Haque, Mohammad Nazmul; Haque, Israat Tanzeena

    2014-01-01

    Cloud computing (CC) has recently been receiving tremendous attention from the IT industry and academic researchers. CC leverages its unique services to cloud customers in a pay-as-you-go, anytime, anywhere manner. Cloud services provide dynamically scalable services through the Internet on demand. Therefore, service provisioning plays a key role in CC. The cloud customer must be able to select appropriate services according to his or her needs. Several approaches have been proposed to solve the service selection problem, including multicriteria decision analysis (MCDA). MCDA enables the user to choose from among a number of available choices. In this paper, we analyze the application of MCDA to service selection in CC. We identify and synthesize several MCDA techniques and provide a comprehensive analysis of this technology for general readers. In addition, we present a taxonomy derived from a survey of the current literature. Finally, we highlight several state-of-the-art practical aspects of MCDA implementation in cloud computing service selection. The contributions of this study are four-fold: (a) focusing on the state-of-the-art MCDA techniques, (b) highlighting the comparative analysis and suitability of several MCDA methods, (c) presenting a taxonomy through extensive literature review, and (d) analyzing and summarizing the cloud computing service selections in different scenarios.

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

    PubMed

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

    2017-03-22

    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

  19. Factors associated with clinical decision-making in relation to treatment need for temporomandibular disorders.

    PubMed

    Yekkalam, Negin; Wänman, Anders

    2016-01-01

    The aim of this study was to analyze dentist's clinical decision-making related to treatment need for temporomandibular disorders (TMD) in an adult population. The study population comprised 779 randomly selected 35, 50, 65 and 75 year old individuals living in the county of Västerbotten, Sweden. The participants filled out a questionnaire and were examined clinically according to a structured protocol. The four examiners (two men, two women) were experienced dentists and were calibrated before the start of the study. After examination they individually assessed the need of treatment owing to TMD. In total, 15% of the study population was considered to have a treatment need owing to TMD. The highest estimate was noted for 35 and 50 years old women and the lowest for 65 and 75 years old men. Overall, 21% of the women and 8% of the men were considered to have a treatment need owing to TMD, with statistically significant differences between men and women for the 35 and 50 years old groups. Inter-individual variations in dentists' decisions were observed. In a multivariate analysis, female gender, signs and symptoms of TMD pain, signs and symptoms of TMD dysfunction and smoking were associated with estimated treatment need. The prevalence of estimated treatment need owing to TMD was fairly high, but the dentists' clinical decision-making process showed large inter-individual variability. The observation calls for further research on the factors affecting the decision-making process in care providers.

  20. A Primer on Bayesian Decision Analysis With an Application to a Kidney Transplant Decision.

    PubMed

    Neapolitan, Richard; Jiang, Xia; Ladner, Daniela P; Kaplan, Bruce

    2016-03-01

    A clinical decision support system (CDSS) is a computer program, which is designed to assist health care professionals with decision making tasks. A well-developed CDSS weighs the benefits of therapy versus the cost in terms of loss of quality of life and financial loss and recommends the decision that can be expected to provide maximum overall benefit. This article provides an introduction to developing CDSSs using Bayesian networks, such CDSS can help with the often complex decisions involving transplants. First, we review Bayes theorem in the context of medical decision making. Then, we introduce Bayesian networks, which can model probabilistic relationships among many related variables and are based on Bayes theorem. Next, we discuss influence diagrams, which are Bayesian networks augmented with decision and value nodes and which can be used to develop CDSSs that are able to recommend decisions that maximize the expected utility of the predicted outcomes to the patient. By way of comparison, we examine the benefit and challenges of using the Kidney Donor Risk Index as the sole decision tool. Finally, we develop a schema for an influence diagram that models generalized kidney transplant decisions and show how the influence diagram approach can provide the clinician and the potential transplant recipient with a valuable decision support tool.

  1. Clinical decision support for perioperative information management systems.

    PubMed

    Wanderer, Jonathan P; Ehrenfeld, Jesse M

    2013-12-01

    Clinical decision support (CDS) systems are being used to optimize the increasingly complex care that our health care system delivers. These systems have become increasingly important in the delivery of perioperative care for patients undergoing cardiac, thoracic, and vascular procedures. The adoption of perioperative information management systems (PIMS) has allowed these technologies to enter the operating room and support the clinical work flow of anesthesiologists and operational processes. Constructing effective CDS systems necessitates an understanding of operative work flow and technical considerations as well as achieving integration with existing information systems. In this review, we describe published examples of CDS for PIMS, including support for cardiopulmonary bypass separation physiological alarms, β-blocker guideline adherence, enhanced revenue capture for arterial line placement, and detection of hemodynamic monitoring gaps. Although these and other areas are amenable to CDS systems, the challenges of latency and data reliability represent fundamental limitations on the potential application of these tools to specific types of clinical issues. Ultimately, we expect that CDS will remain an important tool in our efforts to optimize the quality of care delivered.

  2. 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.

  3. Clinical Decision Support for Early Recognition of Sepsis.

    PubMed

    Amland, Robert C; Hahn-Cover, Kristin E

    2016-01-01

    Sepsis is an inflammatory response triggered by infection, with a high in-hospital mortality rate. Early recognition and treatment can reverse the inflammatory response, with evidence of improved patient outcomes. One challenge clinicians face is identifying the inflammatory syndrome against the background of the patient's infectious illness and comorbidities. An approach to this problem is implementation of computerized early warning tools for sepsis. This multicenter retrospective study sought to determine clinimetric performance of a cloud-based computerized sepsis clinical decision support system (CDS), understand the epidemiology of sepsis, and identify opportunities for quality improvement. Data encompassed 6200 adult hospitalizations from 2012 through 2013. Of 13% patients screened-in, 51% were already suspected to have an infection when the system activated. This study focused on a patient cohort screened-in before infection was suspected; median time from arrival to CDS activation was 3.5 hours, and system activation to diagnostic collect was another 8.6 hours.

  4. Clinical decision support system for the diagnosis of adolescence health.

    PubMed

    Moutsouri, Irene; Nikou, Amalia; Pampalou, Machi; Lentza, Maria; Spyridakis, Paulos; Mathiopoulou, Natassa; Konsoulas, Dimitris; Lampou, Marianna; Alexiou, Athanasios

    2015-01-01

    It is common that children confront psychological problems when they reach puberty. These problems could easily be overcome, but in many cases they could be severe, leading to social estrangement or worse in madness or death. According to information collected we designed a questionnaire about the psychology of adolescents in order to help people in that age or their elders find out if they have health issues. We used already published researches and material concerning all the psychological problems a child can confront in order to make a reliable questionnaire and to develop the clinical decision support system. Our main objective is to publish and administrate a web-based free tool for sharing medical knowledge about any psychological disease a child can already have or develop during puberty.

  5. A Four-Phase Model of the Evolution of Clinical Decision Support Architectures

    PubMed Central

    Wright, Adam; Sittig, Dean F.

    2008-01-01

    Background A large body of evidence over many years suggests that clinical decision support systems can be helpful in improving both clinical outcomes and adherence to evidence-based guidelines. However, to this day, clinical decision support systems are not widely used outside of a small number of sites. One reason why decision support systems are not widely used is the relative difficulty of integrating such systems into clinical workflows and computer systems. Purpose To review and synthesize the history of clinical decision support systems, and to propose a model of various architectures for integrating clinical decision support systems with clinical systems. Methods The authors conducted an extensive review of the clinical decision support literature since 1959, sequenced the systems and developed a model. Results The model developed consists of four phases: standalone decision support systems, decision support integrated into clinical systems, standards for sharing clinical decision support content and service models for decision support. These four phases have not heretofore been identified, but they track remarkably well with the chronological history of clinical decision support, and show evolving and increasingly sophisticated attempts to ease integrating decision support systems into clinical workflows and other clinical systems. Conclusions Each of the four evolutionary approaches to decision support architecture has unique advantages and disadvantages. A key lesson was that there were common limitations that almost all the approaches faced, and no single approach has been able to entirely surmount: 1) fixed knowledge representation systems inherently circumscribe the type of knowledge that can be represented in them, 2) there are serious terminological issues, 3) patient data may be spread across several sources with no single source having a complete view of the patient, and 4) major difficulties exist in transferring successful interventions from one

  6. Sequential decision analysis for nonstationary stochastic processes

    NASA Technical Reports Server (NTRS)

    Schaefer, B.

    1974-01-01

    A formulation of the problem of making decisions concerning the state of nonstationary stochastic processes is given. An optimal decision rule, for the case in which the stochastic process is independent of the decisions made, is derived. It is shown that this rule is a generalization of the Bayesian likelihood ratio test; and an analog to Wald's sequential likelihood ratio test is given, in which the optimal thresholds may vary with time.

  7. Abstraction and analysis of clinical guidance trees.

    PubMed

    Turner, Kenneth J

    2009-04-01

    The aims of this work were: to define an abstract notation for interactive decision trees; to formally analyse exploration errors in such trees through automated translation to Lotos (language of temporal ordering specification); to generate tree implementations through automated translation for an existing tree viewer, and to demonstrate the approach on healthcare examples created by the CGT (clinical guidance tree) project. An abstract and machine-readable notation was developed for describing clinical guidance trees: Ad/it (abstract decision/interactive trees). A methodology has been designed for creating trees using Ad/it. In particular, tree structure is separated from tree content. Tree structure and flow are designed and evaluated before committing to detailed content of the tree. Software tools have been created to translate Ad/it tree descriptions into Lotos and into CGT Viewer format. These representations support formal analysis and interactive exploration of decision trees. Through automated conversion of existing CGT trees, realistic healthcare applications have been used to validate the approach. All key objectives of the work have been achieved. An abstract notation has been created for decision trees, and is supported by automated translation and analysis. Although healthcare applications have been the main focus to date, the approach is generic and of value in almost any domain where decision trees are useful.

  8. [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.

  9. Radar Hardware Second Buy Decision Risk Analysis,

    DTIC Science & Technology

    Operations research, *Radar equipment, *Army procurement, *Decision making , *Risk, Symposia, Army research, Contracts, Cost estimates, Scheduling, Time, Requirements, Logistics planning, Army planning

  10. SANDS: An Architecture for Clinical Decision Support in a National Health Information Network

    PubMed Central

    Wright, Adam; Sittig, Dean F.

    2007-01-01

    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. PMID:18693950

  11. Journal club: Requiring clinical justification to override repeat imaging decision support: impact on CT use.

    PubMed

    O'Connor, Stacy D; Sodickson, Aaron D; Ip, Ivan K; Raja, Ali S; Healey, Michael J; Schneider, Louise I; Khorasani, Ramin

    2014-11-01

    The purpose of this study was to determine the impact of requiring clinical justification to override decision support alerts on repeat use of CT. This before and after intervention study was conducted at a 793-bed tertiary hospital with computerized physician order entry and clinical decision support systems. When a CT order is placed, decision support alerts the orderer if the patient's same body part has undergone CT within the past 90 days. The study cohort included all 28,420 CT orders triggering a repeat alert in 2010. The intervention required clinical justification, selected from a predetermined menu, to override repeat CT decision support alerts to place a CT order; otherwise the order could not be placed and was dropped. The primary outcome, dropped repeat CT orders, was analyzed using three methods: chi-square tests to compare proportions dropped before and after intervention; multiple logistic regression tests to control for orderer, care setting, and patient factors; and statistical process control for temporal trends. The repeat CT order drop rate had an absolute increase of 1.4%; 6.1% (682/11,230) before to 7.5% (1290/17,190) after intervention, which was a 23% relative change (7.5 - 6.1)/6.1 × 100 = 23%; p < 0.0001). Orders were dropped more often after intervention (odds ratio, 1.3; 95% CI, 1.1-1.4; p < 0.0001). Statistical control analysis supported the association between the increase in the drop rate with intervention rather than underlying trends. Adding a requirement for clinical justification to override alerts modestly but significantly improves the impact of repeat CT decision support (23% relative change), with the overall effect of preventing one in 13 repeat CT orders.

  12. A Scalable Architecture for Rule Engine Based Clinical Decision Support Systems.

    PubMed

    Chattopadhyay, Soumi; Banerjee, Ansuman; Banerjee, Nilanjan

    2015-01-01

    Clinical Decision Support systems (CDSS) have reached a fair level of sophistication and have emerged as the popular system of choice for their aid in clinical decision making. These decision support systems are based on rule engines navigate through a repertoire of clinical rules and multitudes of facts to assist a clinical expert to decide on the set of actuations in response to a medical situation. In this paper, we present the design of a scalable architecture for a rule engine based clinical decision system.

  13. The Development of a Normative Acquisition Decision Making Model Incorporating Decision Analysis Principles

    DTIC Science & Technology

    1987-09-01

    school of management represented a shift from the workshop orientation of Frederick Taylor to an entire organization perspective ( Hellriegel & Slocum...of information can vitally affect organizational and individual performance" ( Hellriegel and Slocum, 1974: 266). The communication process determines...principles of decision analysis (Matheson & Howard, 1983: 25). To make rational decisions, the following are required ( Hellriegel & Slocum, 1974: 152): 1

  14. Thomas: building Bayesian statistical expert systems to aid in clinical decision making.

    PubMed

    Lehmann, H P; Shortliffe, E H

    1991-08-01

    Knowledge-based system for classical statistical analysis must separate the task of analyzing data from that of using the results of the analysis. In contrast, a Bayesian framework for building biostatistical expert system allows for the integration of the data-analytic and decision-making tasks. The architecture of such a framework entails enabling the system (1) to make its recommendations on decision-analytic grounds; (2) to construct statistical models dynamically; (3) to update a statistical model based on the user's prior beliefs and on data from, the methodological concerns evinced by, the study. This architecture permits the knowledge engineer to represent a variety of types of statistical and domain knowledge. Construction of such systems requires that the knowledge engineer reinterpret traditional statistical concerns, such as by replacing the notion of statistical significance with that of a pragmatic clinical threshold. The clinical user of such a system can interact with the system at a semantic level appropriate to her fund of methodological knowledge, rather than at the level of statistical details. We demonstrate these issues with a prototype system called THOMAS which helps a physician decision maker interpret the results of a published randomized clinical trial.

  15. Risks, dangers and competing clinical decisions on venous thromboembolism prophylaxis in hospital care.

    PubMed

    Boiko, Olga; Sheaff, Rod; Child, Susan; Gericke, Christian A

    2014-07-01

    Drawing on wider sociologies of risk, this article examines the complexity of clinical risks and their management, focusing on risk management systems, expert decision-making and safety standards in health care. At the time of this study preventing venous thromboembolism (VTE) among in-patients was one of the top priorities for hospital safety in the English National Health Service (NHS). An analysis of 50 interviews examining hospital professionals' perceptions about VTE risks and prophylaxis illuminates how National Institute for Health and Clinical Excellence (NICE) guidelines influenced clinical decision-making in four hospitals in one NHS region. We examine four themes: the identification of new risks, the institutionalisation and management of risk, the relationship between risk and danger and the tensions between risk management systems and expert decision-making. The implementation of NICE guidelines for VTE prevention extended managerial control over risk management but some irreducible clinical dangers remained that were beyond the scope of the new VTE risk management systems. Linking sociologies of risk with the realities of hospital risk management reveals the capacity of these theories to illuminate both the possibilities and the limits of managerialism in health care. © 2014 The Authors. Sociology of Health & Illness © 2014 Foundation for the Sociology of Health & Illness/John Wiley & Sons Ltd.

  16. The perils of meta-regression to identify clinical decision support system success factors.

    PubMed

    Fillmore, Christopher L; Rommel, Casey A; Welch, Brandon M; Zhang, Mingyuan; Kawamoto, Kensaku

    2015-08-01

    Clinical decision support interventions are typically heterogeneous in nature, making it difficult to identify why some interventions succeed while others do not. One approach to identify factors important to the success of health information systems is the use of meta-regression techniques, in which potential explanatory factors are correlated with the outcome of interest. This approach, however, can result in misleading conclusions due to several issues. In this manuscript, we present a cautionary case study in the context of clinical decision support systems to illustrate the limitations of this type of analysis. We then discuss implications and recommendations for future work aimed at identifying success factors of medical informatics interventions. In particular, we identify the need for head-to-head trials in which the importance of system features is directly evaluated in a prospective manner.

  17. Decision Support Systems and Public Policy Analysis.

    ERIC Educational Resources Information Center

    Hall, Owen P., Jr.

    1986-01-01

    This article outlines an approach for developing and applying computerized decision support systems to the formulation and evaluation of public policy. To meet the challenge of financial resource limitations, new management systems must be developed to improve both governmental efficiency and decision-making effectiveness. (Author/BS)

  18. DAUBERT DECISION APPLIED TO GEOSPATIAL ANALYSIS

    EPA Science Inventory

    Protection of the environment is, in part, dependent on the quality of data used in decision making. Whether the decisions are part of the scientific process or relate to application of the laws governing people and their living conditions, good quality data are required/needed ...

  19. 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.

  20. Clinical Decision Support Systems (CDSS) in GRID Environments.

    PubMed

    Blanquer, Ignacio; Hernández, Vicente; Segrelles, Damià; Robles, Montserrat; García, Juan Miguel; Robledo, Javier Vicente

    2005-01-01

    This paper presents an architecture defined for searching and executing Clinical Decision Support Systems (CDSS) in a LCG2/GT2 Grid environment, using web-based protocols. A CDSS is a system that provides a classification of the patient illness according to the knowledge extracted from clinical practice and using the patient's information in a structured format. The CDSS classification engines can be installed in any site and can be used by different medical users from a Virtual Organization (VO). All users in a VO can consult and execute different classification engines that have been installed in the Grid independently of the platform, architecture or site where the engines are installed or the users are located. The present paper present a solution to requirements such as short-job execution, reducing the response delay on LCG2 environments and providing grid-enabled authenticated access through web portals. Resource discovering and job submission is performed through web services, which are also described in the article.

  1. A clinical decision rule for streptococcal pharyngitis management: An update

    PubMed Central

    Nasirian, Hosain; TarvijEslami, Saeedeh; Matini, Esfandiar; Bayesh, Seyedehsara; Omaraee, Yasaman

    2017-01-01

    PURPOSE: Group A streptococcal (GAS) pharyngitis is a common disease worldwide. We aimed to establish a pragmatic program as a clinical decision rule for GAS pharyngitis diagnosis. MATERIALS AND METHODS: This article derived from a research project on children aged 6–15 years. Five hundred and seventy-one children met the enrollment criteria on whom throat culture and validities of clinical findings were assessed in positive and negative throat culture groups. RESULTS: Positive GAS throat culture group included 99 (17.3%) patients with a positive culture. Negative GAS throat culture group included 472 (82.6%) patients. Exudate or enlarged tender nodes each one had 63% and 68% sensitivity and 31.5% and 37.5% specificity with a high percentage of negative predictive value (NPV) 80.54% and 85.09%, respectively. Sequence test revealed validities of exudate plus enlarged nodes at 43.62% sensitivity and 57.19% specificity with 83% NPV. CONCLUSIONS: High NPV of 83% indicated that similar prevalence in the absence of either exudate or enlarged tender lymph nodes. Probability of GAS negative throat cultures among children suspected of GAS pharyngitis was 83% and would correctly not receive inopportune antibiotics. PMID:28367027

  2. [Human body meridian spatial decision support system for clinical treatment and teaching of acupuncture and moxibustion].

    PubMed

    Wu, Dehua

    2016-01-01

    The spatial position and distribution of human body meridian are expressed limitedly in the decision support system (DSS) of acupuncture and moxibustion at present, which leads to the failure to give the effective quantitative analysis on the spatial range and the difficulty for the decision-maker to provide a realistic spatial decision environment. Focusing on the limit spatial expression in DSS of acupuncture and moxibustion, it was proposed that on the basis of the geographic information system, in association of DSS technology, the design idea was developed on the human body meridian spatial DSS. With the 4-layer service-oriented architecture adopted, the data center integrated development platform was taken as the system development environment. The hierarchical organization was done for the spatial data of human body meridian via the directory tree. The structured query language (SQL) server was used to achieve the unified management of spatial data and attribute data. The technologies of architecture, configuration and plug-in development model were integrated to achieve the data inquiry, buffer analysis and program evaluation of the human body meridian spatial DSS. The research results show that the human body meridian spatial DSS could reflect realistically the spatial characteristics of the spatial position and distribution of human body meridian and met the constantly changeable demand of users. It has the powerful spatial analysis function and assists with the scientific decision in clinical treatment and teaching of acupuncture and moxibustion. It is the new attempt to the informatization research of human body meridian.

  3. A rule-based clinical decision model to support interpretation of multiple data in health examinations.

    PubMed

    Kuo, Kuan-Liang; Fuh, Chiou-Shann

    2011-12-01

    Health examinations can obtain relatively complete health information and thus are important for the personal and public health management. For clinicians, one of the most important works in the health examinations is to interpret the health examination results. Continuously interpreting numerous health examination results of healthcare receivers is tedious and error-prone. This paper proposes a clinical decision support system to assist solving above problems. In order to customize the clinical decision support system intuitively and flexibly, this paper also proposes the rule syntax to implement computer-interpretable logic for health examinations. It is our purpose in this paper to describe the methodology of the proposed clinical decision support system. The evaluation was performed by the implementation and execution of decision rules on health examination results and a survey on clinical decision support system users. It reveals the efficiency and user satisfaction of proposed clinical decision support system. Positive impact of clinical data interpretation is also noted.

  4. Clinical process cost analysis.

    PubMed

    Marrin, C A; Johnson, L C; Beggs, V L; Batalden, P B

    1997-09-01

    New systems of reimbursement are exerting enormous pressure on clinicians and hospitals to reduce costs. Using cheaper supplies or reducing the length of stay may be a satisfactory short-term solution, but the best strategy for long-term success is radical reduction of costs by reengineering the processes of care. However, few clinicians or institutions know the actual costs of medical care; nor do they understand, in detail, the activities involved in the delivery of care. Finally, there is no accepted method for linking the two. Clinical process cost analysis begins with the construction of a detailed flow diagram incorporating each activity in the process of care. The cost of each activity is then calculated, and the two are linked. This technique was applied to Diagnosis Related Group 75 to analyze the real costs of the operative treatment of lung cancer at one institution. Total costs varied between $6,400 and $7,700. The major driver of costs was personnel time, which accounted for 55% of the total. Forty percent of the total cost was incurred in the operating room. The cost of care decreased progressively during hospitalization. Clinical process cost analysis provides detailed information about the costs and processes of care. The insights thus obtained may be used to reduce costs by reengineering the process.

  5. Unconscious race and social class bias among acute care surgical clinicians and clinical treatment decisions.

    PubMed

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

    2015-05-01

    Significant health inequities persist among minority and socially disadvantaged patients. Better understanding of how unconscious biases affect clinical decision making may help to illuminate clinicians' roles in propagating disparities. To determine whether clinicians' unconscious race and/or social class biases correlate with patient management decisions. We conducted a web-based survey among 230 physicians from surgery and related specialties at an academic, level I trauma center from December 1, 2011, through January 31, 2012. We administered clinical vignettes, each with 3 management questions. Eight vignettes assessed the relationship between unconscious bias and clinical decision making. We performed ordered logistic regression analysis on the Implicit Association Test (IAT) scores and used multivariable analysis to determine whether implicit bias was associated with the vignette responses. Differential response times (D scores) on the IAT as a surrogate for unconscious bias. Patient management vignettes varied by patient race or social class. Resulting D scores were calculated for each management decision. In total, 215 clinicians were included and consisted of 74 attending surgeons, 32 fellows, 86 residents, 19 interns, and 4 physicians with an undetermined level of education. Specialties included surgery (32.1%), anesthesia (18.1%), emergency medicine (18.1%), orthopedics (7.9%), otolaryngology (7.0%), neurosurgery (7.0%), critical care (6.0%), and urology (2.8%); 1.9% did not report a departmental affiliation. Implicit race and social class biases were present in most respondents. Among all clinicians, mean IAT D scores for race and social class were 0.42 (95% CI, 0.37-0.48) and 0.71 (95% CI, 0.65-0.78), respectively. Race and class scores were similar across departments (general surgery, orthopedics, urology, etc), race, or age. Women demonstrated less bias concerning race (mean IAT D score, 0.39 [95% CI, 0.29-0.49]) and social class (mean IAT D score

  6. THOMAS: Building Bayesian Statistical Expert Systems to Aid in Clinical Decision Making

    PubMed Central

    Lehmann, Harold P.; Shortliffe, Edward H.

    1990-01-01

    Previous knowledge-based systems for statistical analysis separate the numeric knowledge needed for data analysis from the heuristic knowledge employed in using the results of the analysis. In contrast, a Bayesian framework for building biostatistical expert systems allows for the integration of the data-analytic and decision-making tasks. The architecture of such a framework entails enabling the system (1) to make its recommendations on decision-analytic grounds; (2) to update a statistical model based on the user's prior beliefs and on data from, and methodological concerns evinced by, the study; (3) to construct statistical models dynamically. This architecture permits the knowledge engineer to represent a variety of types of statistical and domain knowledge, such as methodological knowledge. Construction of such systems requires that the knowledge engineer reinterpret traditional statistical concerns, such as by replacing the notion of statistical significance with that of a pragmatic clinical threshold. The user of such a system can interact with the system at the level of general methodological concerns, rather than at the level of statistical details. We demonstrate these issues with a prototype system called THOMAS which helps a physician decision maker to interpret the results of a published randomized clinical trial.

  7. Optimizing Clinical Decision Support in the Electronic Health Record. Clinical Characteristics Associated with the Use of a Decision Tool for Disposition of ED Patients with Pulmonary Embolism.

    PubMed

    Ballard, Dustin W; Vemula, Ridhima; Chettipally, Uli K; Kene, Mamata V; Mark, Dustin G; Elms, Andrew K; Lin, James S; Reed, Mary E; Huang, Jie; Rauchwerger, Adina S; Vinson, David R

    2016-09-21

    Adoption of clinical decision support (CDS) tools by clinicians is often limited by workflow barriers. We sought to assess characteristics associated with clinician use of an electronic health record-embedded clinical decision support system (CDSS). In a prospective study on emergency department (ED) activation of a CDSS tool across 14 hospitals between 9/1/14 to 4/30/15, the CDSS was deployed at 10 active sites with an on-site champion, education sessions, iterative feedback, and up to 3 gift cards/clinician as an incentive. The tool was also deployed at 4 passive sites that received only an introductory educational session. Activation of the CDSS - which calculated the Pulmonary Embolism Severity Index (PESI) score and provided guidance - and associated clinical data were collected prospectively. We used multivariable logistic regression with random effects at provider/facility levels to assess the association between activation of the CDSS tool and characteristics at: 1) patient level (PESI score), 2) provider level (demographics and clinical load at time of activation opportunity), and 3) facility level (active vs. passive site, facility ED volume, and ED acuity at time of activation opportunity). Out of 662 eligible patient encounters, the CDSS was activated in 55%: active sites: 68% (346/512); passive sites 13% (20/150). In bivariate analysis, active sites had an increase in activation rates based on the number of prior gift cards the physician had received (96% if 3 prior cards versus 60% if 0, p<0.0001). At passive sites, physicians < age 40 had higher rates of activation (p=0.03). In multivariable analysis, active site status, low ED volume at the time of diagnosis and PESI scores I or II (compared to III or higher) were associated with higher likelihood of CDSS activation. Performing on-site tool promotion significantly increased odds of CDSS activation. Optimizing CDSS adoption requires active education.

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

    PubMed Central

    Hajjaj, FM; Salek, MS; Basra, MKA; Finlay, AY

    2010-01-01

    Summary 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. PMID:20436026

  9. 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.

  10. Proposal for Development of EBM-CDSS (Evidence-Based Clinical Decision Support System) to Aid Prognostication in Terminally Ill Patients

    DTIC Science & Technology

    2010-10-01

    regarding continuation of life-sustaining vs. palliative care . Finally, using regret DCA, the optimal decision for the specific patient is suggested...is to develop an Evidence-based Clinical Decision Support (CDSS-EBM) system and make it available at the point of care to improve prognostication of...Analysis and Regret theory to compare multiple decision strategies based on the decision maker’s personal attitudes towards each strategy

  11. Using Data Mining Strategies in Clinical Decision Making: A Literature Review.

    PubMed

    Chen, Lu-Yen A; Fawcett, Tonks N

    2016-10-01

    Several data-mining models have been embedded in the clinical environment to improve decision making and patient safety. Consequently, it is crucial to survey the principal data-mining strategies currently used in clinical decision making and to determine the disadvantages and advantages of using these strategies in data mining in clinical decision making. A literature review was conducted, which identified 21 relevant articles. The article findings showed that multiple models of data mining were used in clinical decision making. Although data mining is efficient and accurate, the models are limited with respect to disease and condition.

  12. 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.

  13. Engineering of a Clinical Decision Support Framework for the Point of Care Use

    PubMed Central

    Wilk, Szymon; Michalowski, Wojtek; O’Sullivan, Dympna; Farion, Ken; Matwin, Stan

    2008-01-01

    Computerized decision support for use at the point of care has to be comprehensive. It means that clinical information stored in electronic health records needs to be integrated with various forms of clinical knowledge (elicited from experts, discovered from data or summarized in systematic reviews of clinical trials). In order to provide such comprehensive support we created the MET-A3Support framework for constructing clinical applications aimed at various medical conditions. We employed the multiagent system paradigm and the O-MaSE methodology to define an engineering process involving three main activities: requirements engineering, analysis and design. Then we applied the process to build MET-A3Support. The paper describes the engineering process and its results, including models representing selected elements of our framework. PMID:18999068

  14. Engineering of a clinical decision support framework for the point of care use.

    PubMed

    Wilk, Szymon; Michalowski, Wojtek; O'Sullivan, Dympna; Farion, Ken; Matwin, Stan

    2008-11-06

    Computerized decision support for use at the point of care has to be comprehensive. It means that clinical information stored in electronic health records needs to be integrated with various forms of clinical knowledge (elicited from experts, discovered from data or summarized in systematic reviews of clinical trials). In order to provide such comprehensive support we created the MET-A3Support framework for constructing clinical applications aimed at various medical conditions. We employed the multiagent system paradigm and the O-MaSE methodology to define an engineering process involving three main activities: requirements engineering, analysis and design. Then we applied the process to build MET-A3Support. The paper describes the engineering process and its results, including models representing selected elements of our framework.

  15. A Framework for Decision Analysis and Critique.

    DTIC Science & Technology

    1981-07-01

    characteristics of decision-making systems. Generally, it is the case that emotional and motivational characteristics of decision systems are given relatively...of the dimensions of determinants as depicted in Figure 1, Einhorn and Hogarth do not speak to the three explicit issues of the complexity of stimuli...components. To a lesser extent, they do point toward some research on the motivational processes that may underlie the usage of less than optimal

  16. ALTERNATIVE FUTURES ANALYSIS: A FRAMEWORK FOR COMMUNITY DECISION-MAKING

    EPA Science Inventory

    Alternative futures analysis is an assessment approach designed to inform community decisions about land and water use. We conducted an alternative futures analysis in Oregon's Willamette River Basin. Three alternative future landscapes for the year 2050 were depicted and compare...

  17. ALTERNATIVE FUTURES ANALYSIS: A FRAMEWORK FOR COMMUNITY DECISION-MAKING

    EPA Science Inventory

    Alternative futures analysis is an assessment approach designed to inform community decisions about land and water use. We conducted an alternative futures analysis in Oregon's Willamette River Basin. Three alternative future landscapes for the year 2050 were depicted and compare...

  18. A Windows-based tool for the study of clinical decision-making.

    PubMed

    Mackel, J V; Farris, H; Mittman, B S; Wilkes, M; Kanouse, D E

    1995-01-01

    Studies of health-provider decision-making, and of their practice patterns, play a central role in efforts to improve the quality and effectiveness of care and in decreasing costs of healthcare delivery systems. Researchers from a variety of disciplines have studied a broad range of clinical conditions, using a number of methodological approaches and measurement tools, including self-report, written clinical vignettes, simulated clinical encounters using actors as patients and analysis of medical records and administrative data. Although these provide information about the outcomes of clinical decisions, they provide little or no information about the process of the decision. Most clinicians agree that the decision process is as important as the outcome, and indeed it is not unusual to have an exemplary process but a poor outcome. Process information is therefore a crucial dimension of care evaluation. In this paper, we describe a new software product that was originally used to measure diagnostic reasoning in the basic medical science of immunology; subsequently adapted to measure key steps in the clinical decision-making process. This Windows-based software is user-friendly, inexpensive, and requires only commonly available hardware for its operation. It is very flexible, permitting the creation of unlimited numbers and types of clinical scenarios, with diagnostic and/or management approaches. Being clinically "real-world," the scenarios are familiar to the user, who is therefore likely to respond in a "real-world" fashion, with the consequent improved accuracy of data. In addition, a wide range of users may be accommodated. The clinical activities of physicians, nurses, pharmacists, and any other clinical providers may be measured and analyzed by the system. Non-clinical providers, such as managers and administrators, could also be assessed. The system has three major modes. In the Authoring Mode, the author creates a menu, which is common to a number of linked

  19. 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

  20. 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…

  1. 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…

  2. Clinical Decision Support Systems for the Practice of Evidence-based Medicine

    PubMed Central

    Sim, Ida; Gorman, Paul; Greenes, Robert A.; Haynes, R. Brian; Kaplan, Bonnie; Lehmann, Harold; Tang, Paul C.

    2001-01-01

    Background: The use of clinical decision support systems to facilitate the practice of evidence-based medicine promises to substantially improve health care quality. Objective: To describe, on the basis of the proceedings of the Evidence and Decision Support track at the 2000 AMIA Spring Symposium, the research and policy challenges for capturing research and practice-based evidence in machine-interpretable repositories, and to present recommendations for accelerating the development and adoption of clinical decision support systems for evidence-based medicine. Results: The recommendations fall into five broad areas—capture literature-based and practice-based evidence in machine-interpretable knowledge bases; develop maintainable technical and methodological foundations for computer-based decision support; evaluate the clinical effects and costs of clinical decision support systems and the ways clinical decision support systems affect and are affected by professional and organizational practices; identify and disseminate best practices for work flow–sensitive implementations of clinical decision support systems; and establish public policies that provide incentives for implementing clinical decision support systems to improve health care quality. Conclusions: Although the promise of clinical decision support system–facilitated evidence-based medicine is strong, substantial work remains to be done to realize the potential benefits. PMID:11687560

  3. An exploration of the correlates of nurse practitioners' clinical decision-making abilities.

    PubMed

    Chen, Shiah-Lian; Hsu, Hsiu-Ying; Chang, Chin-Fu; Lin, Esther Ching-Lan

    2016-04-01

    This study investigated nurse practitioners' clinical decision-making abilities and the factors that affect these abilities. Nurse practitioners play an important role in clinical care decision-making; however, studies exploring the factors that affect their decision-making abilities are lacking. A cross-sectional descriptive survey was employed. A purposive sample of 197 nurse practitioners was recruited from a medical centre in central Taiwan. Structured questionnaires consisting of the Knowledge Readiness Scale, the Critical Thinking Disposition Inventory and the Clinical Decision-Making Model Inventory were used to collect data. The intuitive-analytical type was the most commonly used decision-making model, and the intuitive type was the least frequently used model. The decision-making model used was significantly related to the nurse practitioners' work unit. Significant differences were noted between the nurse practitioners' clinical decision-making models and their critical thinking dispositions (openness and empathy). The nurse practitioners' years of work experience, work unit, professional knowledge and critical thinking disposition (openness and empathy as well as holistic and reflective dispositions) predicted the nurse practitioners' analytical decision-making scores. Age, years of nurse practitioner work experience, work unit and critical thinking disposition (holistic and reflective) predicted the nurse practitioners' intuitive decision-making scores. This study contributes to the topic of clinical decision-making by describing various types of nurse practitioner decision-making. The factors associated with analytic and intuitive decision-making scores were identified. These findings might be beneficial when planning continuing education programmes to enhance the clinical decision-making abilities of nurse practitioners. The study results showed that nurse practitioners demonstrated various clinical decision-making types across different work units

  4. Clinical Decision Support for Early Recognition of Sepsis

    PubMed Central

    Amland, Robert C.; Hahn-Cover, Kristin E.

    2014-01-01

    Sepsis is an inflammatory response triggered by infection, with a high in-hospital mortality rate. Early recognition and treatment can reverse the inflammatory response, with evidence of improved patient outcomes. One challenge clinicians face is identifying the inflammatory syndrome against the background of the patient’s infectious illness and comorbidities. An approach to this problem is implementation of computerized early warning tools for sepsis. This multicenter retrospective study sought to determine clinimetric performance of a cloud-based computerized sepsis clinical decision support system (CDS), understand the epidemiology of sepsis, and identify opportunities for quality improvement. Data encompassed 6200 adult hospitalizations from 2012 through 2013. Of 13% patients screened-in, 51% were already suspected to have an infection when the system activated. This study focused on a patient cohort screened-in before infection was suspected; median time from arrival to CDS activation was 3.5 hours, and system activation to diagnostic collect was another 8.6 hours. PMID:25385815

  5. The evaluation of a rectal cancer decision aid and the factors influencing its implementation in clinical practice.

    PubMed

    Wu, Robert; Boushey, Robin; Potter, Beth; Stacey, Dawn

    2014-03-21

    Colorectal cancer is common in North America. Two surgical options exist for rectal cancer patients: low anterior resection with re-establishment of bowel continuity, and abdominoperineal resection with a permanent stoma. A rectal cancer decision aid was developed using the International Patient Decision Aid Standards to facilitate patients being more actively involved in making this decision with the surgeon. The overall aim of this study is to evaluate this decision aid and explore barriers and facilitators to implementing in clinical practice. First, a pre- and post- study will be guided by the Ottawa Decision Support Framework. Eligible patients from a colorectal cancer center include: 1) adult patients diagnosed with rectal cancer, 2) tumour at a maximum of 10 cm from anal verge, and 3) surgeon screened candidates eligible to consider both low anterior resection and abdominoperineal resection. Patients will be given a paper-version and online link to the decision aid to review at home. Using validated tools, the primary outcomes will be decisional conflict and knowledge of surgical options. Secondary outcomes will be patient's preference, values associated with options, readiness for decision-making, acceptability of the decision aid, and feasibility of its implementation in clinical practice. Proposed analysis includes paired t-test, Wilcoxon, and descriptive statistics. Second, a survey will be conducted to identify the barriers and facilitators of using the decision aid in clinical practice. Eligible participants include Canadian surgeons working with rectal cancer patients. Surgeons will be given a pre-notification, questionnaire, and three reminders. The survey package will include the patient decision aid and a facilitators and barriers survey previously validated among physicians and nurses. Principal component analysis will be performed to determine common themes, and logistic regression will be used to identify variables associated with the intention

  6. Issues of trust and ethics in computerized clinical decision support systems.

    PubMed

    Alexander, Gregory L

    2006-01-01

    Clinical decision support systems are computer technologies that model and provide support for human decision-making processes. Decision support mechanisms facilitate and enhance a clinician's ability to make decisions at the point of care. Decisions are facilitated through technology by using automated mechanisms that provide alerts or messages to clinicians about a potential patient problem. A clinician's level of trust in these technologies to support decision making is affected by how knowledge is represented in these tools, their ability to make reasonable decisions, and how they are designed. Furthermore, ethical tensions occur if these systems do not promote standards, if clinicians do not understand how to use these systems, and when professional relationships are affected. Issues of trust and ethical concerns will be examined in this article, using a research study of midwestern nursing homes that implemented a clinical decision support system.

  7. Decision Making in the PICU: An Examination of Factors Influencing Participation Decisions in Phase III Randomized Clinical Trials

    PubMed Central

    Slosky, Laura E.; Burke, Natasha L.; Siminoff, Laura A.

    2014-01-01

    Background. In stressful situations, decision making processes related to informed consent may be compromised. Given the profound levels of distress that surrogates of children in pediatric intensive care units (PICU) experience, it is important to understand what factors may be influencing the decision making process beyond the informed consent. The purpose of this study was to evaluate the role of clinician influence and other factors on decision making regarding participation in a randomized clinical trial (RCT). Method. Participants were 76 children under sedation in a PICU and their surrogate decision makers. Measures included the Post Decision Clinician Survey, observer checklist, and post-decision interview. Results. Age of the pediatric patient was related to participation decisions in the RCT such that older children were more likely to be enrolled. Mentioning the sponsoring institution was associated with declining to participate in the RCT. Type of health care provider and overt recommendations to participate were not related to enrollment. Conclusion. Decisions to participate in research by surrogates of children in the PICU appear to relate to child demographics and subtleties in communication; however, no modifiable characteristics were related to increased participation, indicating that the informed consent process may not be compromised in this population. PMID:25161672

  8. Does clinical decision support reduce unwarranted variation in yield of CT pulmonary angiogram?

    PubMed

    Prevedello, Luciano M; Raja, Ali S; Ip, Ivan K; Sodickson, Aaron; Khorasani, Ramin

    2013-11-01

    The study objective was to determine whether previously documented effects of clinical decision support on computed tomography for pulmonary embolism in the emergency department (ie, decreased use and increased yield) are due to a decrease in unwarranted variation. We evaluated clinical decision support effect on intra- and inter-physician variability in the yield of pulmonary embolism computed tomography (PE-CT) in this setting. The study was performed in an academic adult medical center emergency department with 60,000 annual visits. We enrolled all patients who had PE-CT performed 18 months pre- and post-clinical decision support implementation. Intra- and inter-physician variability in yield (% PE-CT positive for acute pulmonary embolism) were assessed. Yield variability was measured using logistic regression accounting for patient characteristics. A total of 1542 PE-CT scans were performed before clinical decision support, and 1349 PE-CT scans were performed after clinical decision support. Use of PE-CT decreased from 26.5 to 24.3 computed tomography scans/1000 patient visits after clinical decision support (P < .02); yield increased from 9.2% to 12.6% (P < .01). Crude inter-physician variability in yield ranged from 2.6% to 20.5% before clinical decision support and from 0% to 38.1% after clinical decision support. After controlling for patient characteristics, the post-clinical decision support period showed significant inter-physician variability (P < .04). Intra-physician variability was significant in 3 of the 25 physicians (P < .04), all with increased yield post-clinical decision support. Overall PE-CT yield increased after clinical decision support implementation despite significant heterogeneity among physicians. Increased inter-physician variability in yield after clinical decision support was not explained by patient characteristics alone and may be due to variable physician acceptance of clinical decision support. Clinical decision support alone is

  9. Which clinical decisions benefit from automation? A task complexity approach.

    PubMed

    Sintchenko, Vitali; Coiera, Enrico W

    2003-07-01

    To describe a model for analysing complex medical decision making tasks and for evaluating their suitability for automation. Assessment of a decision task's complexity in terms of the number of elementary information processes (EIPs) and the potential for cognitive effort reduction through EIP minimisation using an automated decision aid. The model consists of five steps: (1) selection of the domain and relevant tasks; (2) evaluation of the knowledge complexity for tasks selected; (3) identification of cognitively demanding tasks; (4) assessment of unaided and aided effort requirements for this task accomplishment; and (5) selection of computational tools to achieve this complexity reduction. The model is applied to the task of antibiotic prescribing in critical care and the most complex components of the task identified. Decision aids to support these components can provide a significant reduction of cognitive effort suggesting this is a decision task worth automating. We view the role of decision support for complex decision to be one of task complexity reduction, and the model described allows for task automation without lowering decision quality and can assist decision support systems developers.

  10. Decision analysis and cost-effectiveness analysis for comparative effectiveness research--a primer.

    PubMed

    Sher, David J; Punglia, Rinaa S

    2014-01-01

    Although the analysis of real-world data is the foundation of comparative effectiveness analysis, not all clinical questions are easily approached with patient-derived information. Decision analysis is a set of modeling and analytic tools that simulate treatment and disease processes, including the incorporation of patient preferences, thus generating optimal treatment strategies for varying patient, disease, and treatment conditions. Although decision analysis is informed by evidence-derived outcomes, its ability to test treatment strategies under different conditions that are realistic but not necessarily reported in the literature makes it a useful and complementary technique to more standard data analysis. Similarly, cost-effectiveness analysis is a discipline in which the relative costs and benefits of treatment alternatives are rigorously compared. With the well-recognized increase in highly technical, costly radiation therapy technologies, the cost-effectiveness of these different treatments would come under progressively more scrutiny. In this review, we discuss the theoretical and practical aspects of decision analysis and cost-effectiveness analysis, providing examples that highlight their methodology and utility.

  11. 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

  12. Depression: a decision-theoretic analysis.

    PubMed

    Huys, Quentin J M; Daw, Nathaniel D; Dayan, Peter

    2015-07-08

    The manifold symptoms of depression are common and often transient features of healthy life that are likely to be adaptive in difficult circumstances. It is when these symptoms enter a seemingly self-propelling spiral that the maladaptive features of a disorder emerge. We examine this malignant transformation from the perspective of the computational neuroscience of decision making, investigating how dysfunction of the brain's mechanisms of evaluation might lie at its heart. We start by considering the behavioral implications of pessimistic evaluations of decision variables. We then provide a selective review of work suggesting how such pessimism might arise via specific failures of the mechanisms of evaluation or state estimation. Finally, we analyze ways that miscalibration between the subject and environment may be self-perpetuating. We employ the formal framework of Bayesian decision theory as a foundation for this study, showing how most of the problems arise from one of its broad algorithmic facets, namely model-based reasoning.

  13. Enhancing Nurse and Physician Collaboration in Clinical Decision Making Through High-fidelity Interdisciplinary Simulation Training

    PubMed Central

    Maxson, Pamela M.; Dozois, Eric J.; Holubar, Stefan D.; Wrobleski, Diane M.; Dube, Joyce A. Overman; Klipfel, Janee M.; Arnold, Jacqueline J.

    2011-01-01

    OBJECTIVE: To determine whether interdisciplinary simulation team training can positively affect registered nurse and/or physician perceptions of collaboration in clinical decision making. PARTICIPANTS AND METHODS: Between March 1 and April 21, 2009, a convenience sample of volunteer nurses and physicians was recruited to undergo simulation training consisting of a team response to 3 clinical scenarios. Participants completed the Collaboration and Satisfaction About Care Decisions (CSACD) survey before training and at 2 weeks and 2 months after training. Differences in CSACD summary scores between the time points were assessed with paired t tests. RESULTS: Twenty-eight health care professionals (19 nurses, 9 physicians) underwent simulation training. Nurses were of similar age to physicians (27.3 vs 34.5 years; p=.82), were more likely to be women (95.0% vs 12.5%; p<.001), and were less likely to have undergone prior simulation training (0% vs 37.5%; p=.02). The pretest showed that physicians were more likely to perceive that open communication exists between nurses and physicians (p=.04) and that both medical and nursing concerns influence the decision-making process (p=.02). Pretest CSACD analysis revealed that most participants were dissatisfied with the decision-making process. The CSACD summary score showed significant improvement from baseline to 2 weeks (4.2 to 5.1; p<.002), a trend that persisted at 2 months (p<.002). CONCLUSION: Team training using high-fidelity simulation scenarios promoted collaboration between nurses and physicians and enhanced the patient care decision-making process. PMID:21193653

  14. Population-based clinical decision support: a clinical and economic evaluation.

    PubMed

    Eisenstein, Eric L; Anstrom, Kevin J; Edwards, Rex; Willis, Janese M; Simo, Jessica; Lobach, David F

    2012-01-01

    Governments are investing in health information technologies (HIT) to improve care quality and reduce medical costs. However, evidence of these benefits is limited. We conducted a randomized trial of three clinical decision support (CDS) interventions in 20,180 patients: email to care managers (n=3329), reports to primary care administrators (n=3368), letters to patients (n=3401), and controls (10,082). At 7-month follow-up, the letters to patients group had greater use of outpatient services and higher outpatient and total medical costs; whereas, the other groups had no change in clinical events or medical costs. As our CDS interventions were associated with no change or an increase in medical costs, it appears that investments in HIT without consideration for organizational context may not be sufficient to achieve improvements in clinical and economic outcomes.

  15. 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.

  16. Surrogate decision making: reconciling ethical theory and clinical practice.

    PubMed

    Berger, Jeffrey T; DeRenzo, Evan G; Schwartz, Jack

    2008-07-01

    The care of adult patients without decision-making abilities is a routine part of medical practice. Decisions for these patients are typically made by surrogates according to a process governed by a hierarchy of 3 distinct decision-making standards: patients' known wishes, substituted judgments, and best interests. Although this framework offers some guidance, it does not readily incorporate many important considerations of patients and families and does not account for the ways in which many patients and surrogates prefer to make decisions. In this article, the authors review the research on surrogate decision making, compare it with normative standards, and offer ways in which the 2 can be reconciled for the patient's benefit.

  17. 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.

  18. Clinical assessment of decision-making capacity in acquired brain injury with personality change.

    PubMed

    Owen, Gareth S; Freyenhagen, Fabian; Martin, Wayne; David, Anthony S

    2017-01-01

    Assessment of decision-making capacity (DMC) can be difficult in acquired brain injury (ABI) particularly with the syndrome of organic personality disorder (OPD) (the "frontal lobe syndrome"). Clinical neuroscience may help but there are challenges translating its constructs to the decision-making abilities considered relevant by law and ethics. An in-depth interview study of DMC in OPD was undertaken. Six patients were purposefully sampled and rich interview data were acquired for scrutiny using interpretative phenomenological analysis. Interview data revealed that awareness of deficit and thinking about psychological states can be present. However, the awareness of deficit may not be "online" and effectively integrated into decision-making. Without this online awareness of deficit the ability to appreciate or use and weigh information in the process of deciding some matters appeared absent. We argue that the decision-making abilities discussed are: (1) necessary for DMC, (2) threatened by ABI , and (3) assessable at interview. Some advice for practically incorporating these abilities within assessments of DMC in patients with OPD is outlined.

  19. Clinical assessment of decision-making capacity in acquired brain injury with personality change

    PubMed Central

    Owen, Gareth S.; Freyenhagen, Fabian; Martin, Wayne; David, Anthony S.

    2017-01-01

    Assessment of decision-making capacity (DMC) can be difficult in acquired brain injury (ABI) particularly with the syndrome of organic personality disorder (OPD) (the “frontal lobe syndrome”). Clinical neuroscience may help but there are challenges translating its constructs to the decision-making abilities considered relevant by law and ethics. An in-depth interview study of DMC in OPD was undertaken. Six patients were purposefully sampled and rich interview data were acquired for scrutiny using interpretative phenomenological analysis. Interview data revealed that awareness of deficit and thinking about psychological states can be present. However, the awareness of deficit may not be “online” and effectively integrated into decision-making. Without this online awareness of deficit the ability to appreciate or use and weigh information in the process of deciding some matters appeared absent. We argue that the decision-making abilities discussed are: (1) necessary for DMC, (2) threatened by ABI , and (3) assessable at interview. Some advice for practically incorporating these abilities within assessments of DMC in patients with OPD is outlined. PMID:26088818

  20. Clinical decision support tools for osteoporosis disease management: a systematic review of randomized controlled trials.

    PubMed

    Kastner, Monika; Straus, Sharon E

    2008-12-01

    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. To systematically review the literature to identify and describe the effectiveness of tools that support clinical decision making in osteoporosis disease management. Medline, EMBASE, CINAHL, and EBM Reviews (CDSR, DARE, CCTR, and ACP J Club), and contact with experts in the field. 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. 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). Multi-component tools that are targeted to physicians and patients may be effective for supporting clinical decision making in osteoporosis disease management.

  1. 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

  2. Seniority and Superiority: A Case Analysis of Chinese Decision Making.

    ERIC Educational Resources Information Center

    Chen, Guo-Ming

    Employing participant observation methodology, this paper analyzes a 4-hour meeting held among the representatives of a large religious organization in Taiwan. The analysis focuses on the influence of seniority on the Chinese decision making process. Five components of decision making proposed by Stewart (1985) and Kume (1985) were used for the…

  3. Decision theory and the evaluation of risks and benefits of clinical trials.

    PubMed

    Bernabe, Rosemarie D C; van Thiel, Ghislaine J M W; Raaijmakers, Jan A M; van Delden, Johannes J M

    2012-12-01

    Research ethics committees (RECs) are tasked to assess the risks and the benefits of a clinical trial. In previous studies, it was shown that RECs find this task difficult, if not impossible, to do. The current approaches to benefit-risk assessment (i.e. Component Analysis and the Net Risk Test) confound the various risk-benefit tasks, and as such, make balancing impossible. In this article, we show that decision theory, specifically through the expected utility theory and multiattribute utility theory, enable for an explicit and ethically weighted risk-benefit evaluation. This makes a balanced ethical justification possible, and thus a more rationally defensible decision making. Copyright © 2012 Elsevier Ltd. All rights reserved.

  4. Test Case Selection in Pre-Deployment Testing of Complex Clinical Decision Support Systems

    PubMed Central

    Tso, Geoffrey J.; Yuen, Kaeli; Martins, Susana; Tu, Samson W.; Ashcraft, Michael; Heidenreich, Paul; Hoffman, Brian B.; Goldstein, Mary K.

    2016-01-01

    Clinical decision support (CDS) systems with complex logic are being developed. Ensuring the quality of CDS is imperative, but there is no consensus on testing standards. We tested ATHENA-HTN CDS after encoding updated hypertension guidelines into the system. A logic flow and a complexity analysis of the encoding were performed to guide testing. 100 test cases were selected to test the major pathways in the CDS logic flow, and the effectiveness of the testing was analyzed. The encoding contained 26 decision points and 3120 possible output combinations. The 100 cases selected tested all of the major pathways in the logic, but only 1% of the possible output combinations. Test case selection is one of the most challenging aspects in CDS testing and has a major impact on testing coverage. A test selection strategy should take into account the complexity of the system, identification of major logic pathways, and available resources. PMID:27570678

  5. 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:

  6. Assessing the sensibility of two clinical decision support systems.

    PubMed

    Graham, Timothy A D; Bullard, Michael J; Kushniruk, Andre W; Holroyd, Brian R; Rowe, Brian H

    2008-10-01

    Clinicians in Emergency Medicine (EM) are increasingly exposed to guidelines and treatment recommendations. To help access and recall these recommendations, electronic Clinical Decision Support Systems (CDSS) have been developed. This study examined the use and sensibility of two CDSS designed for emergency physicians. CDDS for community acquired pneumonia (CAP) and neutropenic fever (NF) were developed by multidisciplinary teams and have been accessed via an intranet-based homepage (eCPG) for several years. Sensibility is a term coined by Feinstein that describes common sense aspects of a survey instrument. It was modified by emergency researchers to include four main headings: (1) Appropriateness; (2) Objectivity; (3) Content; and (4) Discriminative Power. Sensibility surveys were developed using an iterative approach for both the CAP and NF CDSS and distributed to all 25 emergency physicians at one Canadian site. The overall response rate was 88%. Respondents were 88% male and 83% were less than 40; all were attending EM physicians with specialty designations. A number reported never having used the CAP (21%) or NF (33%) CDSS; 54% (CAP) and 21% (NF) of respondents had used the respective CDSS less than 10 times. Overall, both CDSS were rated highly by users with a mean response of 4.95 (SD 0.56) for CAP and 5.62 (SD 0.62) for NF on a seven-point Likert scale. The majority or respondents (CAP 59%, NF 80%) felt that the NF CDSS was more likely than the CAP CDSS to decrease the chances of making a medical error in medication dose, antibiotic choice or patient disposition (4.61 vs. 5.81, p=0.008). Despite being in place for several years, CDSS for CAP and NF are not used by all EM clinicians. Users were generally satisfied with the CDSS and felt that the NF was more likely than the CAP CDSS to decrease medical errors. Additional research is required to determine the barriers to CDSS use.

  7. 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.

  8. The utility of decision support, clinical guidelines, and financial incentives as tools to achieve improved clinical performance.

    PubMed

    Goldfarb, S

    1999-03-01

    Whether one seeks to reduce inappropriate utilization of resources, improve diagnostic accuracy, increase utilization of effective therapies, or reduce the incidence of complications, the key to change is physician involvement in change. Unfortunately, a simple approach to the problem of inducing change in physician behavior is not available. There is a generally accepted view that expert, best-practice guidelines will improve clinical performance. However, there may be a bias to report positive results and a lack of careful analysis of guideline usage in routine practice in a "postmarketing" study akin to that seen in the pharmaceutical industry. Systems that allow the reliable assessment of quality of outcomes, efficiency of resource utilization, and accurate assessment of the risks associated with the care of given patient populations must be widely available before deciding whether an incentive-based system for providing the full range of medical care is feasible. Decision support focuses on providing information, ideally at the "point of service" and in the context of a particular clinical situation. Rules are self-imposed by physicians and are therefore much more likely to be adopted. As health care becomes corporatized, with increasing numbers of physicians employed by large organizations with the capacity to provide detailed information on the nature and quality of clinical care, it is possible that properly constructed guidelines, appropriate financial incentives, and robust forms of decision support will lead to a physician-led, process improvement approach to more rational and affordable health care.

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

    PubMed

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

    2017-06-01

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

  10. Integrating complex business processes for knowledge-driven clinical decision support systems.

    PubMed

    Kamaleswaran, Rishikesan; McGregor, Carolyn

    2012-01-01

    This paper presents in detail the component of the Complex Business Process for Stream Processing framework that is responsible for integrating complex business processes to enable knowledge-driven Clinical Decision Support System (CDSS) recommendations. CDSSs aid the clinician in supporting the care of patients by providing accurate data analysis and evidence-based recommendations. However, the incorporation of a dynamic knowledge-management system that supports the definition and enactment of complex business processes and real-time data streams has not been researched. In this paper we discuss the process web service as an innovative method of providing contextual information to a real-time data stream processing CDSS.

  11. Modeling access, cost, and perceived quality: computer simulation benefits orthodontic clinic staffing decisions.

    PubMed

    Montgomery, J B; LaFrancois, G G; Perry, M J

    2000-02-01

    Given limited financial resources, simulation permits a financial analysis of the optimum staffing levels for orthodontists and dental assistants in an orthodontic clinic. A computer simulation provides the information for managerial review. This study, by building a computer simulation of an orthodontic service, set out to determine the most efficient mix between providers and support staff to maximize access, maximize perceived quality, and minimize expenditures. Six combinations of providers and support staff were compared during an animated, computer-generated what-if analysis. Based on the clinic workload and size, on the cost per patient, and on the cost per quality point, the research team recommended a staffing mix of one orthodontist and three assistants. This study shows that computer simulation is an enormous asset as a decision support tool for management.

  12. Assessing clinical decision making: is the ideal system feasible?

    PubMed

    Dubois, R W; Brook, R H

    1988-01-01

    While caring for patients, physicians make a variety of decisions. Can current methods adequately determine whether these decisions are correct? If not, what improvements are needed? This paper begins with a review of several explicit methods to assess physician decision making. It then describes a more comprehensive system that would use Bayesian logic to assess whether a physician responded appropriately to the needs of an individual patient. Although sophisticated branching logic may be theoretically desirable, it may not be feasible. The paper concludes by proposing an explicit, potentially practical method that would judiciously use branching logic.

  13. 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.

  14. Representation of Clinical Practice Guidelines in Conventional and Augmented Decision Tables

    PubMed Central

    Shiffman, Richard N.

    1997-01-01

    Abstract Objective: To develop a knowledge representation model for clinical practice guidelines that is linguistically adequate, comprehensible, reusable, and maintainable. Design: Decision tables provide the basic framework for the proposed knowledge representation model. Guideline logic is represented as rules in conventional decision tables. These tables are augmented by layers where collateral information is recorded in slots beneath the logic. Results: Decision tables organize rules into cohesive rule sets wherein complex logic is clarified. Decision table rule sets may be verified to assure completeness and consistency. Optimization and display of rule sets as sequential decision trees may enhance the comprehensibility of the logic. The modularity of the rule formats may facilitate maintenance. The augmentation layers provide links to descriptive language, information sources, decision variable characteristics, costs and expected values of policies, and evidence sources and quality. Conclusion: Augmented decision tables can serve as a unifying knowledge representation for developers and implementers of clinical practice guidelines. PMID:9292844

  15. Exploring the use of large clinical data to inform patients for shared decision making.

    PubMed

    Hill, Brent; Proulx, Joshua; Zeng-Treitler, Qing

    2013-01-01

    Barriers to patient participation in the shared decision making process prevent patients from fully participating in evaluating treatment options and treatment selection. Patients who use a decision aid are more informed and engaged in the shared decision making process. Patient decision aids do not use real clinical data for patient information and may not represent the data well. We designed an interface, for a shared decision making aid, that leverages clinical data to inform risk ratios and create patient stories, or vignettes, and present a visual representation of quantified treatment outcomes data. Usability testing was conducted with experts to evaluate the interface and the utility of using real clinical information that patients can explore. The experts' comments were transcribed and coded for themes. Themes were quantified and comments were interpreted for refinement and modification to the patient decision aid interface and data visualization.

  16. Decision Analysis of Dynamic Spectrum Access Rules

    SciTech Connect

    Juan D. Deaton; Luiz A. DaSilva; Christian Wernz

    2011-12-01

    A current trend in spectrum regulation is to incorporate spectrum sharing through the design of spectrum access rules that support Dynamic Spectrum Access (DSA). This paper develops a decision-theoretic framework for regulators to assess the impacts of different decision rules on both primary and secondary operators. We analyze access rules based on sensing and exclusion areas, which in practice can be enforced through geolocation databases. Our results show that receiver-only sensing provides insufficient protection for primary and co-existing secondary users and overall low social welfare. On the other hand, using sensing information between the transmitter and receiver of a communication link, provides dramatic increases in system performance. The performance of using these link end points is relatively close to that of using many cooperative sensing nodes associated to the same access point and large link exclusion areas. These results are useful to regulators and network developers in understanding in developing rules for future DSA regulation.

  17. Decision Analysis: State of the Field.

    DTIC Science & Technology

    1982-03-01

    fail. a large reservoir may break, a government reorganization may result in an unwieldy bureaucracy, or a new product ’wuld turn out to be an Edsel, The...lam. contrrol crucial aspects in the overall decis,.on-making proce., Tl, begin production and marketang opcr- ations in a new geographical area...For instance, a decision stralegy might suggest an initial test market for a new product and then, based on the results. either cancel the product

  18. Forecasting for energy and chemical decision analysis

    SciTech Connect

    Cazalet, E.G.

    1984-08-01

    This paper focuses on uncertainty and bias in forecasts used for major energy and chemical investment decisions. Probability methods for characterizing uncertainty in the forecast are reviewed. Sources of forecasting bias are classified based on the results of relevant psychology research. Examples are drawn from the energy and chemical industry to illustrate the value of explicit characterization of uncertainty and reduction of bias in forecasts.

  19. Decision analysis for fracture management in cattle.

    PubMed

    St Jean, Guy; Anderson, David E

    2014-03-01

    Bovine fractures are common and each bovine patient is unique, presents innumerable challenges, and requires careful judgment. In cattle the fracture repair usually should be of acceptable quality to not cause a decrease in milk or meat production or interfere with natural breeding. The decision to treat a fracture in cattle is made by evaluating the cost and success rates of the treatment, the value of the animal, and the location and type of fracture. Copyright © 2014 Elsevier Inc. All rights reserved.

  20. Decision theoretic analysis of improving epidemic detection.

    PubMed

    Izadi, Masoumeh T; Buckeridge, David L

    2007-10-11

    The potentially catastrophic impact of an epidemic specially these due to bioterrorist attack, makes developing effective detection methods essential for public health. Current detection methods trade off reliability of alarms for early detection of outbreaks. The performance of these methods can be improved by disease-specific modeling techniques that take into account the potential costs and effects of an attack to provide optimal warnings and the cost and effectiveness of interventions. We study this optimization problem in the framework of sequential decision making under uncertainty. Our approach relies on estimating the future benefit of true alarms and the costs of false alarms. Using these quantities it identifies optimal decisions regarding the credibility of outputs from a traditional detection method at each point in time. The key contribution of this paper is to apply Partially Observable Markov Decision Processes (POMDPs) on outbreak detection methods for improving alarm function in the case of anthrax. We present empirical evidence illustrating that at a fixed specificity, the performance of detection methods with respect to sensitivity and timeliness is improved significantly by utilizing POMDPs in detection of anthrax attacks.

  1. Valuing structured professional judgment: predictive validity, decision-making, and the clinical-actuarial conflict.

    PubMed

    Falzer, Paul R

    2013-01-01

    Structured professional judgment (SPJ) has received considerable attention as an alternative to unstructured clinical judgment and actuarial assessment, and as a means of resolving their ongoing conflict. However, predictive validity studies have typically relied on receiver operating characteristic (ROC) analysis, the same technique commonly used to validate actuarial assessment tools. This paper presents SPJ as distinct from both unstructured clinical judgment and actuarial assessment. A key distinguishing feature of SPJ is the contribution of modifiable factors, either dynamic or protective, to summary risk ratings. With modifiable factors, the summary rating scheme serves as a prognostic model rather than a classification procedure. However, prognostic models require more extensive and thorough predictive validity testing than can be provided by ROC analysis. It is proposed that validation should include calibration and reclassification techniques, as well as additional measures of discrimination. Several techniques and measures are described and illustrated. The paper concludes by tracing the limitations of ROC analysis to its philosophical foundation and its origin as a statistical theory of decision-making. This foundation inhibits the performance of crucial tasks, such as determining the sufficiency of a risk assessment and examining the evidentiary value of statistical findings. The paper closes by noting a current effort to establish a viable and complementary relationship between SPJ and decision-making theory.

  2. Extracting clinical information to support medical decision based on standards.

    PubMed

    Gomoi, Valentin; Vida, Mihaela; Stoicu-Tivadar, Lăcrămioara; Stoicu-Tivadar, Vasile

    2011-01-01

    The paper presents a method connecting medical databases to a medical decision system, and describes a service created to extract the necessary information that is transferred based on standards. The medical decision can be improved based on many inputs from different medical locations. The developed solution is described for a concrete case concerning the management for chronic pelvic pain, based on the information retrieved from diverse healthcare databases.

  3. Causal Analysis/Diagnosis Decision Information System (CADDIS)

    EPA Pesticide Factsheets

    The Causal Analysis/Diagnosis Decision Information System, or CADDIS, is a website developed to help scientists and engineers in the Regions, States, and Tribes conduct causal assessments in aquatic systems.

  4. SPATIAL ANALYSIS AND DECISION ASSISTANCE (SADA) TRAINING COURSE

    EPA Science Inventory

    Spatial Analysis and Decision Assistance (SADA) is a Windows freeware program that incorporates tools from environmental assessment into an effective problem-solving environment. SADA was developed by the Institute for Environmental Modeling at the University of Tennessee and inc...

  5. SPATIAL ANALYSIS AND DECISION ASSISTANCE (SADA) TRAINING COURSE

    EPA Science Inventory

    Spatial Analysis and Decision Assistance (SADA) is a Windows freeware program that incorporates tools from environmental assessment into an effective problem-solving environment. SADA was developed by the Institute for Environmental Modeling at the University of Tennessee and inc...

  6. A Representation for Gaining Insight into Clinical Decision Models

    PubMed Central

    Jimison, Holly B.

    1988-01-01

    For many medical domains uncertainty and patient preferences are important components of decision making. Decision theory is useful as a representation for such medical models in computer decision aids, but the methodology has typically had poor performance in the areas of explanation and user interface. The additional representation of probabilities and utilities as random variables serves to provide a framework for graphical and text insight into complicated decision models. The approach allows for efficient customization of a generic model that describes the general patient population of interest to a patient- specific model. Monte Carlo simulation is used to calculate the expected value of information and sensitivity for each model variable, thus providing a metric for deciding what to emphasize in the graphics and text summary. The computer-generated explanation includes variables that are sensitive with respect to the decision or that deviate significantly from what is typically observed. These techniques serve to keep the assessment and explanation of the patient's decision model concise, allowing the user to focus on the most important aspects for that patient.

  7. 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.

  8. 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.

  9. Modeling information flows in clinical decision support: key insights for enhancing system effectiveness.

    PubMed

    Medlock, Stephanie; Wyatt, Jeremy C; Patel, Vimla L; Shortliffe, Edward H; Abu-Hanna, Ameen

    2016-09-01

    A fundamental challenge in the field of clinical decision support is to determine what characteristics of systems make them effective in supporting particular types of clinical decisions. However, we lack such a theory of decision support itself and a model to describe clinical decisions and the systems to support them. This article outlines such a framework. We present a two-stream model of information flow within clinical decision-support systems (CDSSs): reasoning about the patient (the clinical stream), and reasoning about the user (the cognitive-behavioral stream). We propose that CDSS "effectiveness" be measured not only in terms of a system's impact on clinical care, but also in terms of how (and by whom) the system is used, its effect on work processes, and whether it facilitates appropriate decisions by clinicians and patients. Future research into which factors improve the effectiveness of decision support should not regard CDSSs as a single entity, but should instead differentiate systems based on their attributes, users, and the decision being supported. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  10. Thinking styles and decision making: A meta-analysis.

    PubMed

    Phillips, Wendy J; Fletcher, Jennifer M; Marks, Anthony D G; Hine, Donald W

    2016-03-01

    This meta-analysis examined whether tendencies to use reflective and intuitive thinking styles predicted decision performance (normatively correct responding) and decision experience (e.g., speed, enjoyment) on a range of decision-making tasks. A pooled sample of 17,704 participants (Mage = 25 years) from 89 samples produced small but significant weighted average effects for reflection on performance (r = .11) and experience (r = .14). Intuition was negatively associated with performance (r = -.09) but positively associated with experience (r = .06). Moderation analyses using 499 effect sizes revealed heterogeneity across task-theory match/mismatch, task type, description-based versus experience-based decisions, time pressure, age, and measure type. Effects of both thinking styles were strongest when the task matched the theoretical strengths of the thinking style (up to r = .29). Specific tasks that produced the largest thinking style effects (up to r = .35) were also consistent with system characteristics. Time pressure weakened the effects of reflection, but not intuition, on performance. Effect sizes for reflection on performance were largest for individuals aged either 12 to 18 years or 25+ (up to r = .18), and the effects of both reflection and intuition on experience were largest for adults aged 25+ (up to r = .27). Overall, our results indicate that associations between thinking styles and decision outcomes are context dependent. To improve decision performance and experience, decision architects and educators should carefully consider both individual differences in the decision maker and the nature of the decision task.

  11. The changing nature of clinical decision support systems: a focus on consumers, genomics, public health and decision safety.

    PubMed

    Coiera, E; Lau, A Y S; Tsafnat, G; Sintchenko, V; Magrabi, F

    2009-01-01

    To review the recent research literature in clinical decision support systems (CDSS). A review of recent literature was undertaken, focussing on CDSS evaluation, consumers and public health, the impact of translational bioinformatics on CDSS design, and CDSS safety. In recent years, researchers have concentrated much less on the development of decision technologies, and have focussed more on the impact of CDSS in the clinical world. Recent work highlights that traditional process measures of CDSS effectiveness, such as document relevance are poor proxy measures for decision outcomes. Measuring the dynamics of decision making, for example via decision velocity, may produce a more accurate picture of effectiveness. Another trend is the broadening of user base for CDSS beyond front line clinicians. Consumers are now a major focus for biomedical informatics, as are public health officials, tasked with detecting and managing disease outbreaks at a health system, rather than individual patient level. Bioinformatics is also changing the nature of CDSS. Apart from personalisation of therapy recommendations, translational bioinformatics is creating new challenges in the interpretation of the meaning of genetic data. Finally, there is much recent interest in the safety and effectiveness of computerised physician order entry (CPOE) systems, given that prescribing and administration errors are a significant cause of morbidity and mortality. Of note, there is still much controversy surrounding the contention that poorly designed, implemented or used CDSS may actually lead to harm. CDSS research remains an active and evolving area of research, as CDSS penetrate more widely beyond their traditional domain into consumer decision support, and as decisions become more complex, for example by involving sequence level genetic data.

  12. Chest pain for coronary heart disease in general practice: clinical judgement and a clinical decision rule

    PubMed Central

    Haasenritter, Jörg; Donner-Banzhoff, Norbert; Bösner, Stefan

    2015-01-01

    Background The Marburg Heart Score (MHS) is a simple, valid, and robust clinical decision rule assisting GPs in ruling out coronary heart disease (CHD) in patients presenting with chest pain. Aim To investigate whether using the rule adds to the GP’s clinical judgement. Design and setting A comparative diagnostic accuracy study was conducted using data from 832 consecutive patients with chest pain in general practice. Method Three diagnostic strategies were defined using the MHS: diagnosis based solely on the MHS; using the MHS as a triage test; and GP’s clinical judgement aided by the MHS. Their accuracy was compared with the GPs’ unaided clinical judgement. Results Sensitivity and specificity of the GPs’ unaided clinical judgement was 82.9% (95% confidence interval [CI] = 72.4 to 89.9) and 61.0% (95% CI = 56.7 to 65.2), respectively. In comparison, the sensitivity of the MHS was higher (difference 8.5%, 95% CI = −2.4 to 19.6) and the specificity was similar (difference −0.4%, 95% CI = −5.3 to 4.5); the sensitivity of the triage was similar (difference −1.5%, 95% CI = −9.8 to 7.0) and the specificity was higher (difference 11.6%, 95% CI = 7.8 to 15.4); and both the sensitivity and specificity of the aided clinical judgement were higher (difference 8.0%, 95% CI = −6.9 to 23.0 and 5.8%, 95% CI = −1.6 to 13.2, respectively). Conclusion Using the Marburg Heart Score for initial triage can improve the clinical diagnosis of CHD in general practice. PMID:26500322

  13. 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

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

    PubMed

    Zhou, Li; Karipineni, Neelima; Lewis, Janet; Maviglia, Saverio M; Fairbanks, Amanda; Hongsermeier, Tonya; Middleton, Blackford; Rocha, Roberto A

    2012-11-12

    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. 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. 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. 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.

  15. VisualDecisionLinc: a visual analytics approach for comparative effectiveness-based clinical decision support in psychiatry.

    PubMed

    Mane, Ketan K; Bizon, Chris; Schmitt, Charles; Owen, Phillips; Burchett, Bruce; Pietrobon, Ricardo; Gersing, Kenneth

    2012-02-01

    Comparative Effectiveness Research (CER) is designed to provide research evidence on the effectiveness and risks of different therapeutic options on the basis of data compiled from subpopulations of patients with similar medical conditions. Electronic Health Record (EHR) system contain large volumes of patient data that could be used for CER, but the data contained in EHR system are typically accessible only in formats that are not conducive to rapid synthesis and interpretation of therapeutic outcomes. In the time-pressured clinical setting, clinicians faced with large amounts of patient data in formats that are not readily interpretable often feel 'information overload'. Decision support tools that enable rapid access at the point of care to aggregate data on the most effective therapeutic outcomes derived from CER would greatly aid the clinical decision-making process and individualize patient care. In this manuscript, we highlight the role that visual analytics can play in CER-based clinical decision support. We developed a 'VisualDecisionLinc' (VDL) tool prototype that uses visual analytics to provide summarized CER-derived data views to facilitate rapid interpretation of large amounts of data. We highlight the flexibility that visual analytics offers to gain an overview of therapeutic options and outcomes and if needed, to instantly customize the evidence to the needs of the patient or clinician. The VDL tool uses visual analytics to help the clinician evaluate and understand the effectiveness and risk of different therapeutic options for different subpopulations of patients. Copyright © 2011 Elsevier Inc. All rights reserved.

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

    PubMed Central

    2011-01-01

    Background 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. Results 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. Conclusions We describe an implementation of

  17. 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

  18. Using statistical process control to make data-based clinical decisions.

    PubMed

    Pfadt, A; Wheeler, D J

    1995-01-01

    Applied behavior analysis is based on an investigation of variability due to interrelationships among antecedents, behavior, and consequences. This permits testable hypotheses about the causes of behavior as well as for the course of treatment to be evaluated empirically. Such information provides corrective feedback for making data-based clinical decisions. This paper considers how a different approach to the analysis of variability based on the writings of Walter Shewart and W. Edwards Deming in the area of industrial quality control helps to achieve similar objectives. Statistical process control (SPC) was developed to implement a process of continual product improvement while achieving compliance with production standards and other requirements for promoting customer satisfaction. SPC involves the use of simple statistical tools, such as histograms and control charts, as well as problem-solving techniques, such as flow charts, cause-and-effect diagrams, and Pareto charts, to implement Deming's management philosophy. These data-analytic procedures can be incorporated into a human service organization to help to achieve its stated objectives in a manner that leads to continuous improvement in the functioning of the clients who are its customers. Examples are provided to illustrate how SPC procedures can be used to analyze behavioral data. Issues related to the application of these tools for making data-based clinical decisions and for creating an organizational climate that promotes their routine use in applied settings are also considered.

  19. Using statistical process control to make data-based clinical decisions.

    PubMed Central

    Pfadt, A; Wheeler, D J

    1995-01-01

    Applied behavior analysis is based on an investigation of variability due to interrelationships among antecedents, behavior, and consequences. This permits testable hypotheses about the causes of behavior as well as for the course of treatment to be evaluated empirically. Such information provides corrective feedback for making data-based clinical decisions. This paper considers how a different approach to the analysis of variability based on the writings of Walter Shewart and W. Edwards Deming in the area of industrial quality control helps to achieve similar objectives. Statistical process control (SPC) was developed to implement a process of continual product improvement while achieving compliance with production standards and other requirements for promoting customer satisfaction. SPC involves the use of simple statistical tools, such as histograms and control charts, as well as problem-solving techniques, such as flow charts, cause-and-effect diagrams, and Pareto charts, to implement Deming's management philosophy. These data-analytic procedures can be incorporated into a human service organization to help to achieve its stated objectives in a manner that leads to continuous improvement in the functioning of the clients who are its customers. Examples are provided to illustrate how SPC procedures can be used to analyze behavioral data. Issues related to the application of these tools for making data-based clinical decisions and for creating an organizational climate that promotes their routine use in applied settings are also considered. PMID:7592154

  20. Derivation of a clinical decision rule for predictive factors for the development of pharyngocutaneous fistula postlaryngectomy.

    PubMed

    Cecatto, Suzana Boltes; Monteiro-Soares, Matilde; Henriques, Teresa; Monteiro, Eurico; Moura, Carla Isabel Ferreira Pinto

    2015-01-01

    Pharyngocutaneous fistula after larynx and hypopharynx cancer surgery can cause several damages. This study's aim was to derive a clinical decision rule to predict pharyngocutaneous fistula development after pharyngolaryngeal cancer surgery. A retrospective cohort study was conducted, including all patients performing total laryngectomy/pharyngolaryngectomy (n=171). Association between pertinent variables and pharyngocutaneous fistula development was assessed and a predictive model proposed. American Society of Anesthesiologists scale, chemoradiotherapy, and tracheotomy before surgery were associated with fistula in the univariate analysis. In the multivariate analysis, only American Society of Anesthesiologists maintained statistical significance. Using logistic regression, a predictive model including the following was derived: American Society of Anesthesiologists, alcohol, chemoradiotherapy, tracheotomy, hemoglobin and albumin pre-surgery, local extension, N-classification, and diabetes mellitus. The model's score area under the curve was 0.76 (95% CI 0.64-0.87). The high-risk group presented specificity of 93%, positive likelihood ratio of 7.10, and positive predictive value of 76%. Including the medium-low, medium-high, and high-risk groups, a sensitivity of 92%, negative likelihood ratio of 0.25, and negative predictive value of 89% were observed. A clinical decision rule was created to identify patients with high risk of pharyngocutaneous fistula development. Prognostic accuracy measures were substantial. Nevertheless, it is essential to conduct larger prospective studies for validation and refinement. Copyright © 2015 Associação Brasileira de Otorrinolaringologia e Cirurgia Cérvico-Facial. Published by Elsevier Editora Ltda. All rights reserved.

  1. Social influence and perceptual decision making: a diffusion model analysis.

    PubMed

    Germar, Markus; Schlemmer, Alexander; Krug, Kristine; Voss, Andreas; Mojzisch, Andreas

    2014-02-01

    Classic studies on social influence used simple perceptual decision-making tasks to examine how the opinions of others change individuals' judgments. Since then, one of the most fundamental questions in social psychology has been whether social influence can alter basic perceptual processes. To address this issue, we used a diffusion model analysis. Diffusion models provide a stochastic approach for separating the cognitive processes underlying speeded binary decisions. Following this approach, our study is the first to disentangle whether social influence on decision making is due to altering the uptake of available sensory information or due to shifting the decision criteria. In two experiments, we found consistent evidence for the idea that social influence alters the uptake of available sensory evidence. By contrast, participants did not adjust their decision criteria.

  2. 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

  3. The Use of Automated SNOMED CT Clinical Coding in Clinical Decision Support Systems for Preventive Care.

    PubMed

    Al-Hablani, Bader

    2017-01-01

    The objective of this study is to discuss and analyze the use of automated SNOMED CT clinical coding in clinical decision support systems (CDSSs) for preventive care. The central question that this study seeks to answer is whether the utilization of SNOMED CT in CDSSs can improve preventive care. PubMed, Google Scholar, and Cochrane Library were searched for articles published in English between 2001 and 2012 on SNOMED CT, CDSS, and preventive care. Outcome measures were the sensitivity or specificity of SNOMED CT coded data and the positive predictive value or negative predictive value of SNOMED CT coded data. Additionally, we documented the publication year, research question, study design, results, and conclusions of these studies. The reviewed studies suggested that SNOMED CT successfully represents clinical terms and negated clinical terms. The use of SNOMED CT in CDSS can be considered to provide an answer to the problem of medical errors as well as for preventive care in general. Enhancement of the modifiers and synonyms found in SNOMED CT will be necessary to improve the expected outcome of the integration of SNOMED CT with CDSS. Moreover, the application of the tree-augmented naïve (TAN) Bayesian network method can be considered the best technique to search SNOMED CT data and, consequently, to help improve preventive health services.

  4. The Use of Automated SNOMED CT Clinical Coding in Clinical Decision Support Systems for Preventive Care

    PubMed Central

    Al-Hablani, Bader

    2017-01-01

    Objective The objective of this study is to discuss and analyze the use of automated SNOMED CT clinical coding in clinical decision support systems (CDSSs) for preventive care. The central question that this study seeks to answer is whether the utilization of SNOMED CT in CDSSs can improve preventive care. Method PubMed, Google Scholar, and Cochrane Library were searched for articles published in English between 2001 and 2012 on SNOMED CT, CDSS, and preventive care. Outcome Measures Outcome measures were the sensitivity or specificity of SNOMED CT coded data and the positive predictive value or negative predictive value of SNOMED CT coded data. Additionally, we documented the publication year, research question, study design, results, and conclusions of these studies. Results The reviewed studies suggested that SNOMED CT successfully represents clinical terms and negated clinical terms. Conclusion The use of SNOMED CT in CDSS can be considered to provide an answer to the problem of medical errors as well as for preventive care in general. Enhancement of the modifiers and synonyms found in SNOMED CT will be necessary to improve the expected outcome of the integration of SNOMED CT with CDSS. Moreover, the application of the tree-augmented naïve (TAN) Bayesian network method can be considered the best technique to search SNOMED CT data and, consequently, to help improve preventive health services. PMID:28566995

  5. Multiple perspectives on clinical decision support: a qualitative study of fifteen clinical and vendor organizations.

    PubMed

    Ash, Joan S; Sittig, Dean F; McMullen, Carmit K; Wright, Adam; Bunce, Arwen; Mohan, Vishnu; Cohen, Deborah J; Middleton, Blackford

    2015-04-24

    Computerized clinical decision support (CDS) can help hospitals to improve healthcare. However, CDS can be problematic. The purpose of this study was to discover how the views of clinical stakeholders, CDS content vendors, and EHR vendors are alike or different with respect to challenges in the development, management, and use of CDS. We conducted ethnographic fieldwork using a Rapid Assessment Process within ten clinical and five health information technology (HIT) vendor organizations. Using an inductive analytical approach, we generated themes from the clinical, content vendor, and electronic health record vendor perspectives and compared them. The groups share views on the importance of appropriate manpower, careful knowledge management, CDS that fits user workflow, the need for communication among the groups, and for mutual strategizing about the future of CDS. However, views of usability, training, metrics, interoperability, product use, and legal issues differed. Recommendations for improvement include increased collaboration to address legal, manpower, and CDS sharing issues. The three groups share thinking about many aspects of CDS, but views differ in a number of important respects as well. Until these three groups can reach a mutual understanding of the views of the other stakeholders, and work together, CDS will not reach its potential.

  6. Clinical Performance and Management Outcomes with the DecisionDx-UM Gene Expression Profile Test in a Prospective Multicenter Study.

    PubMed

    Plasseraud, Kristen Meldi; Cook, Robert W; Tsai, Tony; Shildkrot, Yevgeniy; Middlebrook, Brooke; Maetzold, Derek; Wilkinson, Jeff; Stone, John; Johnson, Clare; Oelschlager, Kristen; Aaberg, Thomas M

    2016-01-01

    Uveal melanoma management is challenging due to its metastatic propensity. DecisionDx-UM is a prospectively validated molecular test that interrogates primary tumor biology to provide objective information about metastatic potential that can be used in determining appropriate patient care. To evaluate the continued clinical validity and utility of DecisionDx-UM, beginning March 2010, 70 patients were enrolled in a prospective, multicenter, IRB-approved study to document patient management differences and clinical outcomes associated with low-risk Class 1 and high-risk Class 2 results indicated by DecisionDx-UM testing. Thirty-seven patients in the prospective study were Class 1 and 33 were Class 2. Class 1 patients had 100% 3-year metastasis-free survival compared to 63% for Class 2 (log rank test p = 0.003) with 27.3 median follow-up months in this interim analysis. Class 2 patients received significantly higher-intensity monitoring and more oncology/clinical trial referrals compared to Class 1 patients (Fisher's exact test p = 2.1 × 10(-13) and p = 0.04, resp.). The results of this study provide additional, prospective evidence in an independent cohort of patients that Class 1 and Class 2 patients are managed according to the differential metastatic risk indicated by DecisionDx-UM. The trial is registered with Clinical Application of DecisionDx-UM Gene Expression Assay Results (NCT02376920).

  7. Critical care outreach: the need for effective decision-making in clinical practice (part 2).

    PubMed

    Hancock, Helen C; Durham, Lesley

    2007-04-01

    As the extension of nursing into roles previously within the domain of medicine and the demand for evidence based practice continue to increase, the quality of decision making becomes imperative. Making accurate decisions is essential, both for the practitioner and for the patient, especially in the provision of critical care outreach (CCOR), to improve outcomes of care. With changes in health care delivery and increased accountability for practitioners' decisions, it is important to understand more about how clinical decisions are made and what factors influence them in order to inform practice. The previous paper outlined the theoretical background of clinical decision making and the knowledge that underpins practice in CCOR. In this paper, the authors, a Nurse Consultant in CCOR and a research fellow, examine the process of a practitioner's decision making in the practice of CCOR, through a collaborative reflective account of a case study. From this, recommendations are made about the future development of CCOR practitioners and services.

  8. Quantitative Framework for Retrospective Assessment of Interim Decisions in Clinical Trials

    PubMed Central

    Stanev, Roger

    2016-01-01

    This article presents a quantitative way of modeling the interim decisions of clinical trials. While statistical approaches tend to focus on the epistemic aspects of statistical monitoring rules, often overlooking ethical considerations, ethical approaches tend to neglect the key epistemic dimension. The proposal is a second-order decision-analytic framework. The framework provides means for retrospective assessment of interim decisions based on a clear and consistent set of criteria that combines both ethical and epistemic considerations. The framework is broadly Bayesian and addresses a fundamental question behind many concerns about clinical trials: What does it take for an interim decision (e.g., whether to stop the trial or continue) to be a good decision? Simulations illustrating the modeling of interim decisions counterfactually are provided. PMID:27353825

  9. Quantitative Framework for Retrospective Assessment of Interim Decisions in Clinical Trials.

    PubMed

    Stanev, Roger

    2016-11-01

    This article presents a quantitative way of modeling the interim decisions of clinical trials. While statistical approaches tend to focus on the epistemic aspects of statistical monitoring rules, often overlooking ethical considerations, ethical approaches tend to neglect the key epistemic dimension. The proposal is a second-order decision-analytic framework. The framework provides means for retrospective assessment of interim decisions based on a clear and consistent set of criteria that combines both ethical and epistemic considerations. The framework is broadly Bayesian and addresses a fundamental question behind many concerns about clinical trials: What does it take for an interim decision (e.g., whether to stop the trial or continue) to be a good decision? Simulations illustrating the modeling of interim decisions counterfactually are provided.

  10. Modeling the costs of clinical decision support for genomic precision medicine

    PubMed Central

    Mathias, Patrick C.; Tarczy-Hornoch, Peter; Shirts, Brian H.

    2016-01-01

    Clinical decision support (CDS) within the electronic health record represents a promising mechanism to provide important genomic findings within clinical workflows. To better understand the current and possible future costs of genomic CDS, we leveraged our local CDS experience to assemble a simple model with inputs such as initial cost and numbers of patients, rules, and institutions. Our model assumed efficiencies of scale and allowed us to perform a one-way sensitivity analysis of the impact of each model input. The number of patients with genomic results per institution was the only single variable that could decrease the cost of CDS per useful alert below projected genomic sequencing costs. Because of the prohibitive upfront cost of sequencing large numbers of individuals, increasing the number of institutions using genomic CDS and improving the efficiency of sharing CDS infrastructure represent the most promising paths to making genomic CDS cost-effective. PMID:27570652

  11. Identifying best practices for clinical decision support and knowledge management in the field.

    PubMed

    Ash, Joan S; Sittig, Dean F; Dykstra, Richard; Wright, Adam; McMullen, Carmit; Richardson, Joshua; Middleton, Blackford

    2010-01-01

    To investigate best practices for implementing and managing clinical decision support (CDS) in community hospitals and ambulatory settings, we carried out a series of ethnographic studies to gather information from nine diverse organizations. Using the Rapid Assessment Process methodology, we conducted surveys, interviews, and observations over a period of two years in eight different geographic regions of the U.S.A. We first utilized a template organizing method for an expedited analysis of the data, followed by a deeper and more time consuming interpretive approach. We identified five major categories of best practices that require careful consideration while carrying out the planning, implementation, and knowledge management processes related to CDS. As more health care organizations implement clinical systems such as computerized provider order entry with CDS, descriptions of lessons learned by CDS pioneers can provide valuable guidance so that CDS can have optimal impact on health care quality.

  12. [Profitability analysis of clinical risk management].

    PubMed

    Banduhn, C; Schlüchtermann, J

    2013-05-01

    Medical treatment entails many risks. Increasingly, the negative impact of these risks on patients' health is revealed and corresponding cases are reported to hospital insurances. A systematic clinical risk management can reduce risks. This analysis is designed to demonstrate the financial profitability of implementing a clinical risk management. The decision analysis of a clinical risk management includes information from published articles and studies, publicly available data from the Federal Statistical Office and expert interviews and was conducted in 2 scenarios. The 2 scenarios result from a maximum and minimum value of preventable adverse events reported in Germany. The planning horizon was a 1-year ­period. The analysis was performed from a hospital's perspective. Subsequently, a threshold-analysis of the reduction of preventable adverse events as an effect of clinical risk management was executed. Furthermore, a static capital budgeting over a 5-year period was added, complemented by a risk analysis. Regarding the given assumptions, the implementation of clinical risk management would save about 53 000 € or 175 000 €, respectively, for an average hospital within the first year. Only if the reduction of preventable adverse events is as low as 5.6 or 2.8%, respectively, will the implementation of clinical risk management produce losses. According to a comprehensive risk simulation this happens in less than one out of 1 million cases. The investment in a clinical risk management, based on a 5-year period and an interest rate of 5%, has an annually pay off of 81 000 € or 211 000 €, respectively. The implementation of clinical risk management in a hospital pays off within the first year. In the subsequent years the surplus is even higher due to the elimination of implementation costs. © Georg Thieme Verlag KG Stuttgart · New York.

  13. [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.

  14. Evaluating Psychiatric Hospital Admission Decisions for Children in Foster Care: An Optimal Classification Tree Analysis

    ERIC Educational Resources Information Center

    Snowden, Jessica A.; Leon, Scott C.; Bryant, Fred B.; Lyons, John S.

    2007-01-01

    This study explored clinical and nonclinical predictors of inpatient hospital admission decisions across a sample of children in foster care over 4 years (N = 13,245). Forty-eight percent of participants were female and the mean age was 13.4 (SD = 3.5 years). Optimal data analysis (Yarnold & Soltysik, 2005) was used to construct a nonlinear…

  15. 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.

  16. Decision analysis for the selection of tank waste retrieval technology

    SciTech Connect

    DAVIS,FREDDIE J.; DEWEESE,GREGORY C.; PICKETT,WILLIAM W.

    2000-03-01

    The objective of this report is to supplement the C-104 Alternatives Generation and Analysis (AGA) by providing a decision analysis for the alternative technologies described therein. The decision analysis used the Multi-Attribute Utility Analysis (MUA) technique. To the extent possible information will come from the AGA. Where data are not available, elicitation of expert opinion or engineering judgment is used and reviewed by the authors of the AGA. A key element of this particular analysis is the consideration of varying perspectives of parties interested in or affected by the decision. The six alternatives discussed are: sluicing; sluicing with vehicle mounted transfer pump; borehole mining; vehicle with attached sluicing nozzle and pump; articulated arm with attached sluicing nozzle; and mechanical dry retrieval. These are evaluated using four attributes, namely: schedule, cost, environmental impact, and safety.

  17. Mental Workload as a Key Factor in Clinical Decision Making

    ERIC Educational Resources Information Center

    Byrne, Aidan

    2013-01-01

    The decision making process is central to the practice of a clinician and has traditionally been described in terms of the hypothetico-deductive model. More recently, models adapted from cognitive psychology, such as the dual process and script theories have proved useful in explaining patterns of practice not consistent with purely cognitive…

  18. Mental Workload as a Key Factor in Clinical Decision Making

    ERIC Educational Resources Information Center

    Byrne, Aidan

    2013-01-01

    The decision making process is central to the practice of a clinician and has traditionally been described in terms of the hypothetico-deductive model. More recently, models adapted from cognitive psychology, such as the dual process and script theories have proved useful in explaining patterns of practice not consistent with purely cognitive…

  19. 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.

  20. Clinical decision making and outcome in the routine care of people with severe mental illness across Europe (CEDAR).

    PubMed

    Puschner, B; Becker, T; Mayer, B; Jordan, H; Maj, M; Fiorillo, A; Égerházi, A; Ivánka, T; Munk-Jørgensen, P; Krogsgaard Bording, M; Rössler, W; Kawohl, W; Slade, M

    2016-02-01

    Shared decision making has been advocated as a means to improve patient-orientation and quality of health care. There is a lack of knowledge on clinical decision making and its relation to outcome in the routine treatment of people with severe mental illness. This study examined preferred and experienced clinical decision making from the perspectives of patients and staff, and how these affect treatment outcome. "Clinical Decision Making and Outcome in Routine Care for People with Severe Mental Illness" (CEDAR; ISRCTN75841675) is a naturalistic prospective observational study with bimonthly assessments during a 12-month observation period. Between November 2009 and December 2010, adults with severe mental illness were consecutively recruited from caseloads of community mental health services at the six study sites (Ulm, Germany; London, UK; Naples, Italy; Debrecen, Hungary; Aalborg, Denmark; and Zurich, Switzerland). Clinical decision making was assessed using two instruments which both have parallel patient and staff versions: (a) The Clinical Decision Making Style Scale (CDMS) measured preferences for decision making at baseline; and (b) the Clinical Decision Making Involvement and Satisfaction Scale (CDIS) measured involvement and satisfaction with a specific decision at all time points. Primary outcome was patient-rated unmet needs measured with the Camberwell Assessment of Need Short Appraisal Schedule (CANSAS). Mixed-effects multinomial regression was used to examine differences and course over time in involvement in and satisfaction with actual decision making. The effect of clinical decision making on the primary outcome was examined using hierarchical linear modelling controlling for covariates (study centre, patient age, duration of illness, and diagnosis). Analysis were also controlled for nesting of patients within staff. Of 708 individuals approached, 588 adults with severe mental illness (52% female, mean age = 41.7) gave informed consent. Paired

  1. Decision Analysis System for Selection of Appropriate Decontamination Technologies

    SciTech Connect

    Ebadian, M.A.; Boudreaux, J.F.; Chinta, S.; Zanakis, S.H.

    1998-01-01

    The principal objective for designing Decision Analysis System for Decontamination (DASD) is to support DOE-EM's endeavor to employ the most efficient and effective technologies for treating radiologically contaminated surfaces while minimizing personnel and environmental risks. DASD will provide a tool for environmental decision makers to improve the quality, consistency, and efficacy of their technology selection decisions. The system will facilitate methodical comparisons between innovative and baseline decontamination technologies and aid in identifying the most suitable technologies for performing surface decontamination at DOE environmental restoration sites.

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

    ERIC Educational Resources Information Center

    Hantula, Donald A.

    1995-01-01

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

  3. 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…

  4. 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.…

  5. 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.…

  6. 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…

  7. Measuring the Impact of Diagnostic Decision Support on the Quality of Clinical Decision Making: Development of a Reliable and Valid Composite Score

    PubMed Central

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

    2003-01-01

    Objective: 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. Design: 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. Measurements: 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. Results: 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 ρ 0.65, p < 0.01). The diagnostic and management scores for each episode showed moderate correlation (r = 0.51). Conclusion: 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. PMID:12925549

  8. 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…

  9. Developing Key-Feature Problems and Examinations to Assess Clinical Decision-Making Skills.

    ERIC Educational Resources Information Center

    Page, Gordon; And Others

    1995-01-01

    An approach to testing medical students' clinical decision-making skills identifies key features (critical steps in resolution of a clinical problem) and presents a clinical case scenario followed by questions focusing on those key features. Key-feature problems provide flexibility on issues of question format, multiple responses to questions, and…

  10. Studying Readiness for Clinical Decision Support for Worker Health Using the Rapid Assessment Process and Mixed Methods Interviews

    PubMed Central

    Ash, Joan S.; Chase, Dian; Wiesen, Jane F.; Murphy, Elizabeth V.; Marovich, Stacey

    2016-01-01

    To determine how the Rapid Assessment Process (RAP) can be adapted to evaluate the readiness of primary care clinics for acceptance and use of computerized clinical decision support (CDS) related to clinical management of working patients, we used a unique blend of ethnographic methods for gathering data. First, knowledge resources, which were prototypes of CDS content areas (diabetes, lower back pain, and asthma) containing evidence-based information, decision logic, scenarios and examples of use, were developed by subject matter experts. A team of RAP researchers then visited five clinic settings to identify barriers and facilitators to implementing CDS about the health of workers in general and the knowledge resources specifically. Methods included observations, semi-structured qualitative interviews and graphic elicitation interviews about the knowledge resources. We used both template and grounded hermeneutic approaches to data analysis. Preliminary results indicate that the methods succeeded in generating specific actionable recommendations for CDS design. PMID:28269822

  11. Studying Readiness for Clinical Decision Support for Worker Health Using the Rapid Assessment Process and Mixed Methods Interviews.

    PubMed

    Ash, Joan S; Chase, Dian; Wiesen, Jane F; Murphy, Elizabeth V; Marovich, Stacey

    2016-01-01

    To determine how the Rapid Assessment Process (RAP) can be adapted to evaluate the readiness of primary care clinics for acceptance and use of computerized clinical decision support (CDS) related to clinical management of working patients, we used a unique blend of ethnographic methods for gathering data. First, knowledge resources, which were prototypes of CDS content areas (diabetes, lower back pain, and asthma) containing evidence-based information, decision logic, scenarios and examples of use, were developed by subject matter experts. A team of RAP researchers then visited five clinic settings to identify barriers and facilitators to implementing CDS about the health of workers in general and the knowledge resources specifically. Methods included observations, semi-structured qualitative interviews and graphic elicitation interviews about the knowledge resources. We used both template and grounded hermeneutic approaches to data analysis. Preliminary results indicate that the methods succeeded in generating specific actionable recommendations for CDS design.

  12. TESTING MULTI-CRITERIA DECISION ANALYSIS FOR MORE TRANSPARENT RESOURCE-ALLOCATION DECISION MAKING IN COLOMBIA.

    PubMed

    Castro Jaramillo, Hector Eduardo; Goetghebeur, Mireille; Moreno-Mattar, Ornella

    2016-01-01

    In 2012, Colombia experienced an important institutional transformation after the establishment of the Health Technology Assessment Institute (IETS), the disbandment of the Regulatory Commission for Health and the reassignment of reimbursement decision-making powers to the Ministry of Health and Social Protection (MoHSP). These dynamic changes provided the opportunity to test Multi-Criteria Decision Analysis (MCDA) for systematic and more transparent resource-allocation decision-making. During 2012 and 2013, the MCDA framework Evidence and Value: Impact on Decision Making (EVIDEM) was tested in Colombia. This consisted of a preparatory stage in which the investigators conducted literature searches and produced HTA reports for four interventions of interest, followed by a panel session with decision makers. This method was contrasted with a current approach used in Colombia for updating the publicly financed benefits package (POS), where narrative health technology assessment (HTA) reports are presented alongside comprehensive budget impact analyses (BIAs). Disease severity, size of population, and efficacy ranked at the top among fifteen preselected relevant criteria. MCDA estimates of technologies of interest ranged between 71 to 90 percent of maximum value. The ranking of technologies was sensitive to the methods used. Participants considered that a two-step approach including an MCDA template, complemented by a detailed BIA would be the best approach to assist decision-making in this context. Participants agreed that systematic priority setting should take place in Colombia. This work may serve as the basis to the MoHSP on its interest of setting up a systematic and more transparent process for resource-allocation decision-making.

  13. 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

  14. Hip fractures and dementia: clinical decisions for the future.

    PubMed

    Waran, Eswaran; William, Leeroy

    2016-02-01

    Severe dementia is a life-limiting condition; hip fractures are more common in patients who have dementia. This study outlines the case of a 92-year-old female with severe dementia who sustained a hip fracture. Despite having a terminal diagnosis (severe dementia and hip fracture) and poor premorbid quality of life, she had a life-prolonging surgery. The report outlines issues around treatment options in such circumstances, informed consent and substitute decision-making. The authors propose a 'goals of care' approach to manage patients in whom the best treatment is unclear, during their attendance to the emergency department. It is suggested that utilization of such a model may help with substitute decision-making and true informed consent.

  15. [Decision analysis in radiology using Markov models].

    PubMed

    Golder, W

    2000-01-01

    Markov models (Multistate transition models) are mathematical tools to simulate a cohort of individuals followed over time to assess the prognosis resulting from different strategies. They are applied on the assumption that persons are in one of a finite number of states of health (Markov states). Each condition is given a transition probability as well as an incremental value. Probabilities may be chosen constant or varying over time due to predefined rules. Time horizon is divided into equal increments (Markov cycles). The model calculates quality-adjusted life expectancy employing real-life units and values and summing up the length of time spent in each health state adjusted for objective outcomes and subjective appraisal. This sort of modeling prognosis for a given patient is analogous to utility in common decision trees. Markov models can be evaluated by matrix algebra, probabilistic cohort simulation and Monte Carlo simulation. They have been applied to assess the relative benefits and risks of a limited number of diagnostic and therapeutic procedures in radiology. More interventions should be submitted to Markov analyses in order to elucidate their cost-effectiveness.

  16. Clinical data warehousing for evidence based decision making.

    PubMed

    Narra, Lekha; Sahama, Tony; Stapleton, Peta

    2015-01-01

    Large volumes of heterogeneous health data silos pose a big challenge when exploring for information to allow for evidence based decision making and ensuring quality outcomes. In this paper, we present a proof of concept for adopting data warehousing technology to aggregate and analyse disparate health data in order to understand the impact various lifestyle factors on obesity. We present a practical model for data warehousing with detailed explanation which can be adopted similarly for studying various other health issues.

  17. Cognitive and Motivational Biases in Decision and Risk Analysis.

    PubMed

    Montibeller, Gilberto; von Winterfeldt, Detlof

    2015-07-01

    Behavioral decision research has demonstrated that judgments and decisions of ordinary people and experts are subject to numerous biases. Decision and risk analysis were designed to improve judgments and decisions and to overcome many of these biases. However, when eliciting model components and parameters from decisionmakers or experts, analysts often face the very biases they are trying to help overcome. When these inputs are biased they can seriously reduce the quality of the model and resulting analysis. Some of these biases are due to faulty cognitive processes; some are due to motivations for preferred analysis outcomes. This article identifies the cognitive and motivational biases that are relevant for decision and risk analysis because they can distort analysis inputs and are difficult to correct. We also review and provide guidance about the existing debiasing techniques to overcome these biases. In addition, we describe some biases that are less relevant because they can be corrected by using logic or decomposing the elicitation task. We conclude the article with an agenda for future research.

  18. A patient with a large pulmonary saddle embolus eluding both clinical gestalt and validated decision rules.

    PubMed

    Hennessey, Adam; Setyono, Devy A; Lau, Wayne Bond; Fields, Jason Matthew

    2012-06-01

    We report a patient with chest pain who was classified as having low risk for pulmonary embolism with clinical gestalt and accepted clinical decision rules. An inadvertently ordered D-dimer and abnormal result, however, led to the identification of a large saddle embolus. This case illustrates the fallibility of even well-validated decision aids and that an embolism missed by these tools is not necessarily low risk or indicative of a low clot burden.

  19. Use of Simulation to Study Nurses' Acceptance and Nonacceptance of Clinical Decision Support Suggestions.

    PubMed

    Sousa, Vanessa E C; Lopez, Karen Dunn; Febretti, Alessandro; Stifter, Janet; Yao, Yingwei; Johnson, Andrew; Wilkie, Diana J; Keenan, Gail M

    2015-10-01

    Our long-term goal was to ensure nurse clinical decision support works as intended before full deployment in clinical practice. As part of a broader effort, this pilot project explored factors influencing acceptance/nonacceptance of eight clinical decision support suggestions displayed in an electronic health record-based nursing plan of care software prototype. A diverse sample of 21 nurses participated in this high-fidelity clinical simulation experience and completed a questionnaire to assess reasons for accepting/not accepting the clinical decision support suggestions. Of 168 total suggestions displayed during the experiment (eight for each of the 21 nurses), 123 (73.2%) were accepted, and 45 (26.8%) were not accepted. The mode number of acceptances by nurses was seven of eight, with only two of 21 nurses accepting all. The main reason for clinical decision support acceptance was the nurse's belief that the suggestions were good for the patient (100%), with other features providing secondary reinforcement. Reasons for nonacceptance were less clear, with fewer than half of the subjects indicating low confidence in the evidence. This study provides preliminary evidence that high-quality simulation and targeted questionnaires about specific clinical decision support selections offer a cost-effective means for testing before full deployment in clinical practice.

  20. Potential Role of Methylation Marker in Glioma Supporting Clinical Decisions

    PubMed Central

    Roszkowski, Krzysztof; Furtak, Jacek; Zurawski, Bogdan; Szylberg, Tadeusz; Lewandowska, Marzena A.

    2016-01-01

    The IDH1/2 gene mutations, ATRX loss/mutation, 1p/19q status, and MGMT promoter methylation are increasingly used as prognostic or predictive biomarkers of gliomas. However, the effect of their combination on radiation therapy outcome is discussable. Previously, we demonstrated that the IDH1 c.G395A; p.R132H mutation was associated with longer survival in grade II astrocytoma and GBM (Glioblastoma). Here we analyzed the MGMT promoter methylation status in patients with a known mutation status in codon 132 of IDH1, followed by clinical and genetic data analysis based on the two statuses. After a subtotal tumor resection, the patients were treated using IMRT (Intensity-Modulated Radiation Therapy) with 6 MeV photons. The total dose was: 54 Gy for astrocytoma II, 60 Gy for astrocytoma III, 60 Gy for glioblastoma, 2 Gy per day, with 24 h intervals, five days per week. The patients with MGMT promoter methylation and IDH1 somatic mutation (OS = 40 months) had a better prognosis than those with MGMT methylation alone (OS = 18 months). In patients with astrocytoma anaplasticum (n = 7) with the IDH1 p.R132H mutation and hypermethylated MGMT, the prognosis was particularly favorable (median OS = 47 months). In patients with astrocytoma II meeting the above criteria, the prognosis was also better than in those not meeting those criteria. The IDH1 mutation appears more relevant for the prognosis than MGMT methylation. The IDH1 p.R132H mutation combined with MGMT hypermethylation seems to be the most advantageous for treatment success. Patients not meeting those criteria may require more aggressive treatments. PMID:27834917

  1. Potential Role of Methylation Marker in Glioma Supporting Clinical Decisions.

    PubMed

    Roszkowski, Krzysztof; Furtak, Jacek; Zurawski, Bogdan; Szylberg, Tadeusz; Lewandowska, Marzena A

    2016-11-10

    The IDH1/2 gene mutations, ATRX loss/mutation, 1p/19q status, and MGMT promoter methylation are increasingly used as prognostic or predictive biomarkers of gliomas. However, the effect of their combination on radiation therapy outcome is discussable. Previously, we demonstrated that the IDH1 c.G395A; p.R132H mutation was associated with longer survival in grade II astrocytoma and GBM (Glioblastoma). Here we analyzed the MGMT promoter methylation status in patients with a known mutation status in codon 132 of IDH1, followed by clinical and genetic data analysis based on the two statuses. After a subtotal tumor resection, the patients were treated using IMRT (Intensity-Modulated Radiation Therapy) with 6 MeV photons. The total dose was: 54 Gy for astrocytoma II, 60 Gy for astrocytoma III, 60 Gy for glioblastoma, 2 Gy per day, with 24 h intervals, five days per week. The patients with MGMT promoter methylation and IDH1 somatic mutation (OS = 40 months) had a better prognosis than those with MGMT methylation alone (OS = 18 months). In patients with astrocytoma anaplasticum (n = 7) with the IDH1 p.R132H mutation and hypermethylated MGMT, the prognosis was particularly favorable (median OS = 47 months). In patients with astrocytoma II meeting the above criteria, the prognosis was also better than in those not meeting those criteria. The IDH1 mutation appears more relevant for the prognosis than MGMT methylation. The IDH1 p.R132H mutation combined with MGMT hypermethylation seems to be the most advantageous for treatment success. Patients not meeting those criteria may require more aggressive treatments.

  2. Critical thinking and clinical decision making in critical care nursing: a pilot study.

    PubMed

    Hicks, Frank D; Merritt, Sharon L; Elstein, Arthur S

    2003-01-01

    This pilot study examined the relationship of education level, years of critical care nursing experience, and critical thinking (CT) ability (skills and dispositions) to consistency in clinical decision making among critical care nurses. Consistency was defined as the degree to which intuitive and analytical decision processes resulted in similar selection of interventions in tasks of low and high complexity. The study was nonexperimental and correlational. Critical care nurses (n = 54) from adult critical care units in 3 private teaching hospitals. The majority of nurses held a BSN or MSN and had an average of 9 years of direct clinical experience in the care of the critically ill. Decision-making consistency decreased significantly between low-complexity and high-complexity tasks. Both intuitive and analytical decision processes produced clear intervention selections in the low-complexity task, although the analytical process resulted in a more complete specification of interventions. In the high-complexity task, however, only the intuitive process resulted in a clear, plausible, and safe specification of interventions. Education and experience were not related to CT ability, nor was CT ability related to decision-making consistency. Only greater years of critical care nursing experience increased the likelihood of decision-making consistency. Overall, intuitive decision processes resulted in more clinically consistent selection of interventions across tasks. More investigation is needed to examine the influence of decision heuristics, and the conceptualization and measurement of CT abilities among practicing nurses.

  3. Computer-assisted categorizing of head computed tomography reports for clinical decision rule research.

    PubMed

    Wall, Stephen P; Mayorga, Oliver; Banfield, Christine E; Wall, Mark E; Aisic, Ilan; Auerbach, Carl; Gennis, Paul

    2006-11-01

    To develop software that categorizes electronic head computed tomography (CT) reports into groups useful for clinical decision rule research. Data were obtained from the Second National Emergency X-Radiography Utilization Study, a cohort of head injury patients having received head CT. CT reports were reviewed manually for presence or absence of clinically important subdural or epidural hematoma, defined as greater than 1.0 cm in width or causing mass effect. Manual categorization was done by 2 independent researchers blinded to each other's results. A third researcher adjudicated discrepancies. A random sample of 300 reports with radiologic abnormalities was selected for software development. After excluding reports categorized manually or by software as indeterminate (neither positive nor negative), we calculated sensitivity and specificity by using manual categorization as the standard. System efficiency was defined as the percentage of reports categorized as positive or negative, regardless of accuracy. Software was refined until analysis of the training data yielded sensitivity and specificity approximating 95% and efficiency exceeding 75%. To test the system, we calculated sensitivity, specificity, and efficiency, using the remaining 1,911 reports. Of the 1,911 reports, 160 had clinically important subdural or epidural hematoma. The software exhibited good agreement with manual categorization of all reports, including indeterminate ones (weighted kappa 0.62; 95% confidence interval [CI] 0.58 to 0.65). Sensitivity, specificity, and efficiency of the computerized system for identifying manual positives and negatives were 96% (95% CI 91% to 98%), 98% (95% CI 98% to 99%), and 79% (95% CI 77% to 80%), respectively. Categorizing head CT reports by computer for clinical decision rule research is feasible.

  4. 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.

  5. Closed-Loop Analysis of Soft Decisions for Serial Links

    NASA Technical Reports Server (NTRS)

    Lansdowne, Chatwin A.; Steele, Glen F.; Zucha, Joan P.; Schlesinger, Adam M.

    2013-01-01

    We describe the benefit of using closed-loop measurements for a radio receiver paired with a counterpart transmitter. We show that real-time analysis of the soft decision output of a receiver can provide rich and relevant insight far beyond the traditional hard-decision bit error rate (BER) test statistic. We describe a Soft Decision Analyzer (SDA) implementation for closed-loop measurements on single- or dual- (orthogonal) channel serial data communication links. The analyzer has been used to identify, quantify, and prioritize contributors to implementation loss in live-time during the development of software defined radios. This test technique gains importance as modern receivers are providing soft decision symbol synchronization as radio links are challenged to push more data and more protocol overhead through noisier channels, and software-defined radios (SDRs) use error-correction codes that approach Shannon's theoretical limit of performance.

  6. Benefit-Risk Analysis for Decision-Making: An Approach.

    PubMed

    Raju, G K; Gurumurthi, K; Domike, R

    2016-12-01

    The analysis of benefit and risk is an important aspect of decision-making throughout the drug lifecycle. In this work, the use of a benefit-risk analysis approach to support decision-making was explored. The proposed approach builds on the qualitative US Food and Drug Administration (FDA) approach to include a more explicit analysis based on international standards and guidance that enables aggregation and comparison of benefit and risk on a common basis and a lifecycle focus. The approach is demonstrated on six decisions over the lifecycle (e.g., accelerated approval, withdrawal, and traditional approval) using two case studies: natalizumab for multiple sclerosis (MS) and bedaquiline for multidrug-resistant tuberculosis (MDR-TB).

  7. Development of a scalable pharmacogenomic clinical decision support service.

    PubMed

    Fusaro, Vincent A; Brownstein, Catherine; Wolf, Wendy; Clinton, Catherine; Savage, Sarah; Mandl, Kenneth D; Margulies, David; Manzi, Shannon

    2013-01-01

    Advances in sequencing technology are making genomic data more accessible within the healthcare environment. Published pharmacogenetic guidelines attempt to provide a clinical context for specific genomic variants; however, the actual implementation to convert genomic data into a clinical report integrated within an electronic medical record system is a major challenge for any hospital. We created a two-part solution that integrates with the medical record system and converts genetic variant results into an interpreted clinical report based on published guidelines. We successfully developed a scalable infrastructure to support TPMT genetic testing and are currently testing approximately two individuals per week in our production version. We plan to release an online variant to clinical interpretation reporting system in order to facilitate translation of pharmacogenetic information into clinical practice.

  8. Complexity perspectives on clinical decision making in an intensive care unit.

    PubMed

    de Bock, Ben A; Willems, Dick L; Weinstein, Henry C

    2017-08-01

    How to clarify the implications of complexity thinking for decision making in the intensive care unit (ICU)? Retrospective qualitative empirical research. Practitioners in an ICU were interviewed on how their decisions were made regarding a particular patient in a difficult, clinical situation. Transcriptions of these interviews were coded and retrieved in Maxqda, a software program. Assisted by complexity thinking, researchers focused on the decision-making process and the shift from analytic approaches to complex approaches. Originally, practitioners took their decisions with negligible transdisciplinary interactivity, drawing on analytical knowledge. Later on, they shifted to transdisciplinary practices, paying attention to more participation in their decision-making processes within their complex environment. Complexity thinking demonstrates that this is a better model towards understanding transdisciplinary decision making then most analytical methodologies. © 2017 John Wiley & Sons, Ltd.

  9. Shared decision making: examining key elements and barriers to adoption into routine clinical practice.

    PubMed

    Légaré, France; Witteman, Holly O

    2013-02-01

    For many patients, the time spent meeting with their physician-the clinical encounter-is the most opportune moment for them to become engaged in their own health through the process of shared decision making. In the United States shared decision making is being promoted for its potential to improve the health of populations and individual patients, while also helping control care costs. In this overview we describe the three essential elements of shared decision making: recognizing and acknowledging that a decision is required; knowing and understanding the best available evidence; and incorporating the patient's values and preferences into the decision. To achieve the promise of shared decision making, more physicians need training in the approach, and more practices need to be reorganized around the principles of patient engagement. Additional research is also needed to identify the interventions that are most effective.

  10. Employing Conjoint Analysis in Making Compensation Decisions.

    ERIC Educational Resources Information Center

    Kienast, Philip; And Others

    1983-01-01

    Describes a method employing conjoint analysis that generates utility/cost ratios for various elements of the compensation package. Its superiority to simple preference surveys is examined. Results of a study of the use of this method in fringe benefit planning in a large financial institution are reported. (Author/JAC)

  11. 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

  12. Clinical decision support system for early detection of prostate cancer from benign hyperplasia of prostate.

    PubMed

    Ghaderzadeh, Mustafa

    2013-01-01

    There has been a growing research interest in the use of intelligent methods in medical informatics studies. Intelligent computer programs were implemented to aid physicians and other medical professionals in making difficult medical decisions. Prostate Neoplasia problems including benign hyperplasia and cancer of prostate are very common and cause significant delay in recovery and often require costly investigations before coming to its diagnosis. The conventional approach to build medical diagnostic system requires the formulation of rules by which the input data can be analyzed. But the formulation of such rules is very difficult with large sets of input data. Realizing the difficulty, a number of quantitative mathematical and statistical models including pattern classification technique such as Artificial neural networks (ANN), rolled based system, discriminate analysis and regression analysis has been applied as an alternative to conventional clinical and medical diagnostic. Among the mathematical and statistical modeling techniques used in medical decision support, Artificial neural networks attract many attentions in recent studies and in the last decade, the use of neural networks has become widely accepted in medical applications. This is manifested by an increasing number of medical devices currently available on the market with embedded AI algorithms, together with an accelerating pace of publication in medical journals, with over 500 academic publications year featuring Artificial Neural Networks (ANNs).

  13. Nottingham Prognostic Index Plus (NPI+): a modern clinical decision making tool in breast cancer

    PubMed Central

    Rakha, E A; Soria, D; Green, A R; Lemetre, C; Powe, D G; Nolan, C C; Garibaldi, J M; Ball, G; Ellis, I O

    2014-01-01

    Background: Current management of breast cancer (BC) relies on risk stratification based on well-defined clinicopathologic factors. Global gene expression profiling studies have demonstrated that BC comprises distinct molecular classes with clinical relevance. In this study, we hypothesised that molecular features of BC are a key driver of tumour behaviour and when coupled with a novel and bespoke application of established clinicopathologic prognostic variables can predict both clinical outcome and relevant therapeutic options more accurately than existing methods. Methods: In the current study, a comprehensive panel of biomarkers with relevance to BC was applied to a large and well-characterised series of BC, using immunohistochemistry and different multivariate clustering techniques, to identify the key molecular classes. Subsequently, each class was further stratified using a set of well-defined prognostic clinicopathologic variables. These variables were combined in formulae to prognostically stratify different molecular classes, collectively known as the Nottingham Prognostic Index Plus (NPI+). The NPI+ was then used to predict outcome in the different molecular classes. Results: Seven core molecular classes were identified using a selective panel of 10 biomarkers. Incorporation of clinicopathologic variables in a second-stage analysis resulted in identification of distinct prognostic groups within each molecular class (NPI+). Outcome analysis showed that using the bespoke NPI formulae for each biological BC class provides improved patient outcome stratification superior to the traditional NPI. Conclusion: This study provides proof-of-principle evidence for the use of NPI+ in supporting improved individualised clinical decision making. PMID:24619074

  14. MADAM: Multiple-Attribute Decision Analysis Model. Volume 2

    DTIC Science & Technology

    1981-12-01

    CONTAINED A SIGNIFICANT NUMBER OF PAGES WHICH DO NOT REPRODUCE LEGIBLY. AFIT/GOR/AA/81 0-1 MADAM : MULTIPLE-ATTRIBUTE DECISION ANALYSIS MODEL VOLUME...11 T!IFSIS w T C AFIT/GOR/AA/81D-I Wayne A. Stimpson (J> CC’ T 2Lt USAFR ~~FEB 1 9 1982 AFITj,0R/AA/81 D-1 Thes is t", MADAM : MULTIPLE-ATTRIBUTE...objectives to be satisfied. The program is MADAM : Multiple-Attribute Decision Analysis Model, and it is written in FORTRAN V and is implemented on the

  15. Clinical Decision Support Systems and Prevention: A Community Guide Cardiovascular Disease Systematic Review.

    PubMed

    Njie, Gibril J; Proia, Krista K; Thota, Anilkrishna B; Finnie, Ramona K C; Hopkins, David P; Banks, Starr M; Callahan, David B; Pronk, Nicolaas P; Rask, Kimberly J; Lackland, Daniel T; Kottke, Thomas E

    2015-11-01

    Clinical decision support systems (CDSSs) can help clinicians assess cardiovascular disease (CVD) risk and manage CVD risk factors by providing tailored assessments and treatment recommendations based on individual patient data. The goal of this systematic review was to examine the effectiveness of CDSSs in improving screening for CVD risk factors, practices for CVD-related preventive care services such as clinical tests and prescribed treatments, and management of CVD risk factors. An existing systematic review (search period, January 1975-January 2011) of CDSSs for any condition was initially identified. Studies of CDSSs that focused on CVD prevention in that review were combined with studies identified through an updated search (January 2011-October 2012). Data analysis was conducted in 2013. A total of 45 studies qualified for inclusion in the review. Improvements were seen for recommended screening and other preventive care services completed by clinicians, recommended clinical tests completed by clinicians, and recommended treatments prescribed by clinicians (median increases of 3.8, 4.0, and 2.0 percentage points, respectively). Results were inconsistent for changes in CVD risk factors such as systolic and diastolic blood pressure, total and low-density lipoprotein cholesterol, and hemoglobin A1C levels. CDSSs are effective in improving clinician practices related to screening and other preventive care services, clinical tests, and treatments. However, more evidence is needed from implementation of CDSSs within the broad context of comprehensive service delivery aimed at reducing CVD risk and CVD-related morbidity and mortality. Published by Elsevier Inc.

  16. Inconsistencies in classification by experts of cardiotocograms and subsequent clinical decision.

    PubMed

    Ayres-de-Campos, D; Bernardes, J; Costa-Pereira, A; Pereira-Leite, L

    1999-12-01

    Inter-observer agreement in the interpretation according to the FIGO guidelines of 33 cardiotocographic tracings by experts and subsequent clinical decision was evaluated, using the kappa statistic (K) and the proportions of agreement (Pa). Overall agreement in the classification of tracings was fair (K = 0.48) and was better for normal (Pa = 0.62), than for suspicious (Pa = 0.42) or pathologic tracings (Pa = 0.25). Overall agreement on clinical decision was slightly higher (K = 0.59), but mostly was centred on the decision to take 'no action' (Pa = 0.79). Experts especially disagreed over the decisions to 'monitor closely' (Pa = 0.14) or to 'intervene immediately' (Pa = 0.38). These limitations should be taken into account in clinical audits and in medical jurisprudence.

  17. Multiattribute Decision Modeling Techniques: A Comparative Analysis

    DTIC Science & Technology

    1988-08-01

    Rating Technique (SMART) as a direct response to Raiffa’s (1969) article on multiattribute utility theory , which Edwards found extremcy stimulating but...approaches such as multiattribute utility /value assessment and hierarchical analysis and have applied these techniques to a number of non-military... multiattributed ) outcomes O(l)...O(k), and if the utility function is denoted by u and the probabilities of the k events are p(l)...p(k), then the

  18. Multiple criteria decision analysis for health technology assessment.

    PubMed

    Thokala, Praveen; Duenas, Alejandra

    2012-12-01

    Multicriteria decision analysis (MCDA) has been suggested by some researchers as a method to capture the benefits beyond quality adjusted life-years in a transparent and consistent manner. The objectives of this article were to analyze the possible application of MCDA approaches in health technology assessment and to describe their relative advantages and disadvantages. This article begins with an introduction to the most common types of MCDA models and a critical review of state-of-the-art methods for incorporating multiple criteria in health technology assessment. An overview of MCDA is provided and is compared against the current UK National Institute for Health and Clinical Excellence health technology appraisal process. A generic MCDA modeling approach is described, and the different MCDA modeling approaches are applied to a hypothetical case study. A comparison of the different MCDA approaches is provided, and the generic issues that need consideration before the application of MCDA in health technology assessment are examined. There are general practical issues that might arise from using an MCDA approach, and it is suggested that appropriate care be taken to ensure the success of MCDA techniques in the appraisal process. Copyright © 2012 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

  19. Patient-Centered Decision Support: Formative Usability Evaluation of Integrated Clinical Decision Support With a Patient Decision Aid for Minor Head Injury in the Emergency Department.

    PubMed

    Melnick, Edward R; Hess, Erik P; Guo, George; Breslin, Maggie; Lopez, Kevin; Pavlo, Anthony J; Abujarad, Fuad; Powsner, Seth M; Post, Lori A

    2017-05-19

    The Canadian Computed Tomography (CT) Head Rule, a clinical decision rule designed to safely reduce imaging in minor head injury, has been rigorously validated and implemented, and yet expected decreases in CT were unsuccessful. Recent work has identified empathic care as a key component in decreasing CT overuse. Health information technology can hinder the clinician-patient relationship. Patient-centered decision tools to support the clinician-patient relationship are needed to promote evidence-based decisions. Our objective is to formatively evaluate an electronic tool that not only helps clinicians at the bedside to determine the need for CT use based on the Canadian CT Head Rule but also promotes evidence-based conversations between patients and clinicians regarding patient-specific risk and patients' specific concerns. User-centered design with practice-based and participatory decision aid development was used to design, develop, and evaluate patient-centered decision support regarding CT use in minor head injury in the emergency department. User experience and user interface (UX/UI) development involved successive iterations with incremental refinement in 4 phases: (1) initial prototype development, (2) usability assessment, (3) field testing, and (4) beta testing. This qualitative approach involved input from patients, emergency care clinicians, health services researchers, designers, and clinical informaticists at every stage. The Concussion or Brain Bleed app is the product of 16 successive iterative revisions in accordance with UX/UI industry design standards. This useful and usable final product integrates clinical decision support with a patient decision aid. It promotes shared use by emergency clinicians and patients at the point of care within the emergency department context. This tablet computer app facilitates evidence-based conversations regarding CT in minor head injury. It is adaptable to individual clinician practice styles. The resultant tool

  20. Patient-Centered Decision Support: Formative Usability Evaluation of Integrated Clinical Decision Support With a Patient Decision Aid for Minor Head Injury in the Emergency Department

    PubMed Central

    Hess, Erik P; Guo, George; Breslin, Maggie; Lopez, Kevin; Pavlo, Anthony J; Abujarad, Fuad; Powsner, Seth M; Post, Lori A

    2017-01-01

    Background The Canadian Computed Tomography (CT) Head Rule, a clinical decision rule designed to safely reduce imaging in minor head injury, has been rigorously validated and implemented, and yet expected decreases in CT were unsuccessful. Recent work has identified empathic care as a key component in decreasing CT overuse. Health information technology can hinder the clinician-patient relationship. Patient-centered decision tools to support the clinician-patient relationship are needed to promote evidence-based decisions. Objective Our objective is to formatively evaluate an electronic tool that not only helps clinicians at the bedside to determine the need for CT use based on the Canadian CT Head Rule but also promotes evidence-based conversations between patients and clinicians regarding patient-specific risk and patients’ specific concerns. Methods User-centered design with practice-based and participatory decision aid development was used to design, develop, and evaluate patient-centered decision support regarding CT use in minor head injury in the emergency department. User experience and user interface (UX/UI) development involved successive iterations with incremental refinement in 4 phases: (1) initial prototype development, (2) usability assessment, (3) field testing, and (4) beta testing. This qualitative approach involved input from patients, emergency care clinicians, health services researchers, designers, and clinical informaticists at every stage. Results The Concussion or Brain Bleed app is the product of 16 successive iterative revisions in accordance with UX/UI industry design standards. This useful and usable final product integrates clinical decision support with a patient decision aid. It promotes shared use by emergency clinicians and patients at the point of care within the emergency department context. This tablet computer app facilitates evidence-based conversations regarding CT in minor head injury. It is adaptable to individual

  1. Usability Testing of a Complex Clinical Decision Support Tool in the Emergency Department: Lessons Learned.

    PubMed

    Press, Anne; McCullagh, Lauren; Khan, Sundas; Schachter, Andy; Pardo, Salvatore; McGinn, Thomas

    2015-09-10

    the Wells tool in assessing a patient for a PE diagnosis. Subjects described the tool as "well-organized" and "better than clinical judgment". Changes were made to improve tool placement into the EHR to make it optimal for decision-making, auto-populating boxes, and minimizing click fatigue. Phase II: After incorporating the changes noted in Phase 1, the participants noted tool improvements. There was less toggling between screens, they had all the clinical information required to complete the tool, and were able to complete the patient visit efficiently. However, an optimal location for triggering the tool remained controversial. This study successfully combined "think-aloud" protocol analysis with "near-live" clinical simulations in a usability evaluation of a CDS tool that will be implemented into the emergency room environment. Both methods proved useful in the assessment of the CDS tool and allowed us to refine tool usability and workflow.

  2. Clinical decision support tools: performance of personal digital assistant versus online drug information databases.

    PubMed

    Clauson, Kevin A; Polen, Hyla H; Marsh, Wallace A

    2007-12-01

    To evaluate personal digital assistant (PDA) drug information databases used to support clinical decision-making, and to compare the performance of PDA databases with their online versions. Prospective evaluation with descriptive analysis. Five drug information databases available for PDAs and online were evaluated according to their scope (inclusion of correct answers), completeness (on a 3-point scale), and ease of use; 158 question-answer pairs across 15 weighted categories of drug information essential to health care professionals were used to evaluate these databases. An overall composite score integrating these three measures was then calculated. Scores for the PDA databases and for each PDA-online pair were compared. Among the PDA databases, composite rankings, from highest to lowest, were as follows: Lexi-Drugs, Clinical Pharmacology OnHand, Epocrates Rx Pro, mobileMicromedex (now called Thomson Clinical Xpert), and Epocrates Rx free version. When we compared database pairs, online databases that had greater scope than their PDA counterparts were Clinical Pharmacology (137 vs 100 answers, p<0.001), Micromedex (132 vs 96 answers, p<0.001), Lexi-Comp Online (131 vs 119 answers, p<0.001), and Epocrates Online Premium (103 vs 98 answers, p=0.001). Only Micromedex online was more complete than its PDA version (p=0.008). Regarding ease of use, the Lexi-Drugs PDA database was superior to Lexi-Comp Online (p<0.001); however, Epocrates Online Premium, Epocrates Online Free, and Micromedex online were easier to use than their PDA counterparts (p<0.001). In terms of composite scores, only the online versions of Clinical Pharmacology and Micromedex demonstrated superiority over their PDA versions (p>0.01). Online and PDA drug information databases assist practitioners in improving their clinical decision-making. Lexi-Drugs performed significantly better than all of the other PDA databases evaluated. No PDA database demonstrated superiority to its online counterpart

  3. Initial Risk Analysis and Decision Making Framework

    SciTech Connect

    Engel, David W.

    2012-02-01

    Commercialization of new carbon capture simulation initiative (CCSI) technology will include two key elements of risk management, namely, technical risk (will process and plant performance be effective, safe, and reliable) and enterprise risk (can project losses and costs be controlled within the constraints of market demand to maintain profitability and investor confidence). Both of these elements of risk are incorporated into the risk analysis subtask of Task 7. Thus far, this subtask has developed a prototype demonstration tool that quantifies risk based on the expected profitability of expenditures when retrofitting carbon capture technology on a stylized 650 MW pulverized coal electric power generator. The prototype is based on the selection of specific technical and financial factors believed to be important determinants of the expected profitability of carbon capture, subject to uncertainty. The uncertainty surrounding the technical performance and financial variables selected thus far is propagated in a model that calculates the expected profitability of investments in carbon capture and measures risk in terms of variability in expected net returns from these investments. Given the preliminary nature of the results of this prototype, additional work is required to expand the scope of the model to include additional risk factors, additional information on extant and proposed risk factors, the results of a qualitative risk factor elicitation process, and feedback from utilities and other interested parties involved in the carbon capture project. Additional information on proposed distributions of these risk factors will be integrated into a commercial implementation framework for the purpose of a comparative technology investment analysis.

  4. Using real options analysis to support strategic management decisions

    NASA Astrophysics Data System (ADS)

    Kabaivanov, Stanimir; Markovska, Veneta; Milev, Mariyan

    2013-12-01

    Decision making is a complex process that requires taking into consideration multiple heterogeneous sources of uncertainty. Standard valuation and financial analysis techniques often fail to properly account for all these sources of risk as well as for all sources of additional flexibility. In this paper we explore applications of a modified binomial tree method for real options analysis (ROA) in an effort to improve decision making process. Usual cases of use of real options are analyzed with elaborate study on the applications and advantages that company management can derive from their application. A numeric results based on extending simple binomial tree approach for multiple sources of uncertainty are provided to demonstrate the improvement effects on management decisions.

  5. "Thinking aloud" as a strategy to improve clinical decision making.

    PubMed

    Corcoran, S; Narayan, S; Moreland, H

    1988-09-01

    Although "thinking aloud" has been used as a research method to collect data about nurses' knowledge and cognitive processes, it has not been used widely for instruction. We suggest that thinking aloud can be an effective teaching strategy for staff development. Two techniques are described for incorporating thinking aloud into dialogue among experienced nurses and into mentoring activities between experts and novices. An excerpt from a transcript of one nurse's thinking aloud while making a triage decision is presented to illustrate the types of knowledge and cognitive processes that can be elicited and revealed by using this strategy. Potential educational benefits are identified, along with suggestions for implementing thinking aloud as an instructional method.

  6. A knowledge authoring tool for clinical decision support.

    PubMed

    Dunsmuir, Dustin; Daniels, Jeremy; Brouse, Christopher; Ford, Simon; Ansermino, J Mark

    2008-06-01

    Anesthesiologists in the operating room are unable to constantly monitor all data generated by physiological monitors. They are further distracted by clinical and educational tasks. An expert system would ideally provide assistance to the anesthesiologist in this data-rich environment. Clinical monitoring expert systems have not been widely adopted, as traditional methods of knowledge encoding require both expert medical and programming skills, making knowledge acquisition difficult. A software application was developed for use as a knowledge authoring tool for physiological monitoring. This application enables clinicians to create knowledge rules without the need of a knowledge engineer or programmer. These rules are designed to provide clinical diagnosis, explanations and treatment advice for opt