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Sample records for clinical decision analysis

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

    PubMed Central

    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. PMID:8563289

  2. Decision analysis in the clinical neurosciences: a systematic review of the literature.

    PubMed

    Dippel, D W; Habbema, J D

    1995-12-01

    Clinical decision analysis can be a useful scientific tool for individual patient management, for planning of clinical research and for reaching consensus about clinical problems. We systematically reviewed the decision analytic studies in the clinical neurosciences that were published between 1975 and July 1994. All studies were assessed on aspects of clinical applicability: presence of case and context description, completeness of the analysed strategies from a clinical point of view, extendibility of the analyses to different patient profiles, and up-to-date-ness. Fifty-nine decision analyses of twenty-eight different clinical problems were identified. Twenty-eight analyses were based on the theory of subjective expected utility, twelve on cost-effectiveness analysis. Four studies used ROC analysis, and fifteen were risk-, or risk-benefit analyses. At least six studies could have been improved by more elaborately disclosing the context of the clinical problem that was addressed. In eleven studies, the effect of different, yet plausible assumptions was not explored, and in eighteen studies the reader was not informed how to extend the results of the analysis to patients with (slightly) different clinical characterisitics. All studies had, by nature, the potential to promote insight into the clinical problem and focus the discussion on clinically important aspects, and gave clinically useful advice. We conclude that clinical decision analysis, as an explicit, quantitative approach to uncertainty in decision making in the clinical neurosciences will fulfill a growing need in the near future. PMID:24283779

  3. 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).

  4. Shared clinical decision making

    PubMed Central

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

    2015-01-01

    Objectives: To determine preferences of patients regarding their involvement in the clinical decision making process and the related factors in Saudi Arabia. Methods: 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. Results: 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). Conclusion: 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. PMID:26620990

  5. Visual Cluster Analysis in Support of Clinical Decision Intelligence

    PubMed Central

    Gotz, David; Sun, Jimeng; Cao, Nan; Ebadollahi, Shahram

    2011-01-01

    Electronic health records (EHRs) contain a wealth of information about patients. In addition to providing efficient and accurate records for individual patients, large databases of EHRs contain valuable information about overall patient populations. While statistical insights describing an overall population are beneficial, they are often not specific enough to use as the basis for individualized patient-centric decisions. To address this challenge, we describe an approach based on patient similarity which analyzes an EHR database to extract a cohort of patient records most similar to a specific target patient. Clusters of similar patients are then visualized to allow interactive visual refinement by human experts. Statistics are then extracted from the refined patient clusters and displayed to users. The statistical insights taken from these refined clusters provide personalized guidance for complex decisions. This paper focuses on the cluster refinement stage where an expert user must interactively (a) judge the quality and contents of automatically generated similar patient clusters, and (b) refine the clusters based on his/her expertise. We describe the DICON visualization tool which allows users to interactively view and refine multidimensional similar patient clusters. We also present results from a preliminary evaluation where two medical doctors provided feedback on our approach. PMID:22195102

  6. Clinical decision support systems.

    PubMed

    Beeler, Patrick Emanuel; Bates, David Westfall; Hug, Balthasar Luzius

    2014-01-01

    Clinical decision support (CDS) systems link patient data with an electronic knowledge base in order to improve decision-making and computerised physician order entry (CPOE) is a requirement to set up electronic CDS. The medical informatics literature suggests categorising CDS tools into medication dosing support, order facilitators, point-of-care alerts and reminders, relevant information display, expert systems and workflow support. To date, CDS has particularly been recognised for improving processes. CDS successfully fostered prevention of deep-vein thrombosis, improved adherence to guidelines, increased the use of vaccinations, and decreased the rate of serious medication errors. However, CDS may introduce errors, and therefore the term "e-iatrogenesis" has been proposed to address unintended consequences. At least two studies reported severe treatment delays due to CPOE and CDS. In addition, the phenomenon of "alert fatigue" - arising from a high number of CDS alerts of low clinical significance - may facilitate overriding of potentially critical notifications. The implementation of CDS needs to be carefully planned, CDS interventions should be thoroughly examined in pilot wards only, and then stepwise introduced. A crucial feature of CPOE in combination with CDS is speed, since time consumption has been found to be a major factor determining failure. In the near future, the specificity of alerts will be improved, notifications will be prioritised and offer detailed advice, customisation of CDS will play an increasing role, and finally, CDS is heading for patient-centred decision support. The most important research question remains whether CDS is able to improve patient outcomes beyond processes.

  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. PMID:24041118

  8. A Mixed Methodological Analysis of the Role of Culture in the Clinical Decision-Making Process

    ERIC Educational Resources Information Center

    Hays, Danica G.; Prosek, Elizabeth A.; McLeod, Amy L.

    2010-01-01

    Even though literature indicates that particular cultural groups receive more severe diagnoses at disproportionate rates, there has been minimal research that addresses how culture interfaces specifically with clinical decision making. This mixed methodological study of 41 counselors indicated that cultural characteristics of both counselors and…

  9. 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

  10. The basics of decision analysis.

    PubMed

    Kent, D L

    1992-12-01

    Historically, decision analysis (DA) arose from economics, psychology, and statistics. Medical and dental applications have developed over the past two decades. While decision psychology explores how people make their decisions, the DA process involves construction of a model and development of insights into the strengths and uncertainties about recommendations derived from analysis of model outputs. Uncertainties are represented as probabilities and values are assigned to desirable or adverse outcomes according to preferences expressed by the decision maker. The model unifies probabilities and values by calculation of the expected value for each decision choice. The decision maker can improve his or her insight into uncertainties in the model by conducting sensitivity analyses, and can take action based on this improved insight. The DA process is illustrated using the decision to take or skip influenza vaccination. People's decision making behavior for this problem has also been analyzed using methods from decision psychology. Distinctions between clinical DA and cost-effectiveness analysis are given, as are caveats about especially complicated subtopics in decision analysis for medical problems. In closing, opportunities for further study of decision analysis are presented. PMID:1487581

  11. 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

  12. Recommendations for standardizing glucose reporting and analysis to optimize clinical decision making in diabetes: the ambulatory glucose profile.

    PubMed

    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.

  13. Recommendations for standardizing glucose reporting and analysis to optimize clinical decision making in diabetes: the Ambulatory Glucose Profile (AGP).

    PubMed

    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

    2013-03-01

    Abstract 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. 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 standardization of analysis and presentation of glucose monitoring data, with the initial focus on data derived from CGM systems. The panel members were introduced to a universal software report, the Ambulatory Glucose Profile (AGP), and asked to provide feedback on its content and functionality, both as a research tool and in clinical settings. This paper 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.

  14. 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

  15. 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. PMID:26969668

  16. 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. PMID:26630606

  17. Multicriteria decision analysis in oncology

    PubMed Central

    Adunlin, Georges; Diaby, Vakaramoko; Montero, Alberto J.; Xiao, Hong

    2015-01-01

    Background There has been a growing interest in the development and application of alternative decision-making frameworks within health care, including multicriteria decision analysis (MCDA). Even though the literature includes several reviews on MCDA methods, applications of MCDA in oncology are lacking. Aim The aim of this paper is to discuss a rationale for the use of MCDA in oncology. In this context, the following research question emerged: How can MCDA be used to develop a clinical decision support tool in oncology? Methods In this paper, a brief background on decision making is presented, followed by an overview of MCDA methods and process. The paper discusses some applications of MCDA, proposes research opportunities in the context of oncology and presents an illustrative example of how MCDA can be applied to oncology. Findings Decisions in oncology involve trade-offs between possible benefits and harms. MCDA can help analyse trade-off preferences. A wide range of MCDA methods exist. Each method has its strengths and weaknesses. Choosing the appropriate method varies depending on the source and nature of information used to inform decision making. The literature review identified eight studies. The analytical hierarchy process (AHP) was the most often used method in the identified studies. Conclusion Overall, MCDA appears to be a promising tool that can be used to assist clinical decision making in oncology. Nonetheless, field testing is desirable before MCDA becomes an established decision-making tool in this field. PMID:24635949

  18. 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. PMID:26066306

  19. Decision Analysis Using Spreadsheets.

    ERIC Educational Resources Information Center

    Sounderpandian, Jayavel

    1989-01-01

    Discussion of decision analysis and its importance in a business curriculum focuses on the use of spreadsheets instead of commercial software packages for computer assisted instruction. A hypothetical example is given of a company drilling for oil, and suggestions are provided for classroom exercises using spreadsheets. (seven references) (LRW)

  20. 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

  1. Isabel, a clinical decision support system.

    PubMed

    Vardell, Emily; Moore, Mary

    2011-01-01

    A clinical decision support system (CDSS) is an interactive tool designed to assist clinicians in making decisions, such as determining a diagnosis. The Isabel Database is a CDSS featuring a clinical checklist and topic-specific knowledge components. This column contains an overview of the database, provides searching tips, and places Isabel within the context of the CDSS field. PMID:21534115

  2. 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.

  3. Decision support for clinical laboratory capacity planning.

    PubMed

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

    1995-01-01

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

  4. 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…

  5. 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.

  6. The Impact of Multispectral Digital Skin Lesion Analysis on German Dermatologist Decisions to Biopsy Atypical Pigmented Lesions with Clinical Characteristics of Melanoma

    PubMed Central

    Winkelmann, Richard R.; Hauschild, Axel; Tucker, Natalie; White, Richard; Rigel, Darrell S.

    2015-01-01

    Objective: To determine the impact of multispectral digital skin lesion analysis on German dermatologist biopsy decisions of atypical pigmented skin lesions. Design: Participants were shown high-resolution clinical images of 12 atypical pigmented skin lesions previously analyzed by multispectral digital skin lesion analysis. Participants were asked if they would biopsy the lesion based on clinical images and high-resolution dermoscopy images and again when subsequently shown multispectral digital skin lesion analysis probability information. Setting/participants: Forty-one dermatologists at a skin cancer conference in Germany in September 2014. Measurements: Sensitivity, specificity, diagnostic accuracy, percent biopsying all melanomas, and overall biopsy rates. Results: Sensitivity for the detection of melanoma following clinical evaluation was 64 percent. After receipt of multispectral digital skin lesion analysis probability information, sensitivity decreased nonsignificantly to 62 percent. Specificity with clinical evaluation was 57 percent and increased to 73 percent using multispectral digital skin lesion analysis. Overall biopsy accuracy increased from 60 percent with clinical evaluation to 68 percent with multispectral digital skin lesion analysis. The percentage of low-grade dysplastic nevi chosen for biopsy decreased from 43 percent after clinical evaluation to 27 percent with multispectral digital skin lesion analysis. Finally, the overall percentage of lesions biopsied decreased from 52 percent with clinical evaluation to 42 percent after multispectral digital skin lesion analysis. Conclusion: Multispectral digital skin lesion analysis can be used reliably to detect melanoma as well as clinical evaluation. Dermatologists can confidently use multispectral digital skin lesion analysis to significantly improve specificity and reduce their overall number of biopsies while increasing overall diagnostic accuracy. PMID:26557216

  7. 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.

  8. Multi-National, Multi-Institutional Analysis of Clinical Decision Support Data Needs to Inform Development of the HL7 Virtual Medical Record Standard

    PubMed Central

    Kawamoto, Kensaku; Del Fiol, Guilherme; Strasberg, Howard R.; Hulse, Nathan; Curtis, Clayton; Cimino, James J.; Rocha, Beatriz H.; Maviglia, Saverio; Fry, Emory; Scherpbier, Harm J.; Huser, Vojtech; Redington, Patrick K.; Vawdrey, David K.; Dufour, Jean-Charles; Price, Morgan; Weber, Jens H.; White, Thomas; Hughes, Kevin S.; McClay, James C.; Wood, Carla; Eckert, Karen; Bolte, Scott; Shields, David; Tattam, Peter R.; Scott, Peter; Liu, Zhijing; McIntyre, Andrew K.

    2010-01-01

    An important barrier to the widespread dissemination of clinical decision support (CDS) is the heterogeneity of information models and terminologies used across healthcare institutions, health information systems, and CDS resources such as knowledge bases. To address this problem, the Health Level 7 (HL7) Virtual Medical Record project (an open, international standards development effort) is developing community consensus on the clinical information exchanged between CDS engines and clinical information systems. As a part of this effort, the HL7 CDS Work Group embarked on a multinational, collaborative effort to identify a representative set of clinical data elements required for CDS. Based on an analysis of CDS systems from 20 institutions representing 4 nations, 131 data elements were identified as being currently utilized for CDS. These findings will inform the development of the emerging HL7 Virtual Medical Record standard and will facilitate the achievement of scalable, standards-based CDS. PMID:21347004

  9. Multi-National, Multi-Institutional Analysis of Clinical Decision Support Data Needs to Inform Development of the HL7 Virtual Medical Record Standard.

    PubMed

    Kawamoto, Kensaku; Del Fiol, Guilherme; Strasberg, Howard R; Hulse, Nathan; Curtis, Clayton; Cimino, James J; Rocha, Beatriz H; Maviglia, Saverio; Fry, Emory; Scherpbier, Harm J; Huser, Vojtech; Redington, Patrick K; Vawdrey, David K; Dufour, Jean-Charles; Price, Morgan; Weber, Jens H; White, Thomas; Hughes, Kevin S; McClay, James C; Wood, Carla; Eckert, Karen; Bolte, Scott; Shields, David; Tattam, Peter R; Scott, Peter; Liu, Zhijing; McIntyre, Andrew K

    2010-11-13

    An important barrier to the widespread dissemination of clinical decision support (CDS) is the heterogeneity of information models and terminologies used across healthcare institutions, health information systems, and CDS resources such as knowledge bases. To address this problem, the Health Level 7 (HL7) Virtual Medical Record project (an open, international standards development effort) is developing community consensus on the clinical information exchanged between CDS engines and clinical information systems. As a part of this effort, the HL7 CDS Work Group embarked on a multinational, collaborative effort to identify a representative set of clinical data elements required for CDS. Based on an analysis of CDS systems from 20 institutions representing 4 nations, 131 data elements were identified as being currently utilized for CDS. These findings will inform the development of the emerging HL7 Virtual Medical Record standard and will facilitate the achievement of scalable, standards-based CDS.

  10. 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.

  11. 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.

  12. 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. PMID:27209183

  13. Helping novice nurses make effective clinical decisions: the situated clinical decision-making framework.

    PubMed

    Gillespie, Mary; Peterson, Barbara L

    2009-01-01

    The nature of novice nurses' clinical decision-making has been well documented as linear, based on limited knowledge and experience in the profession, and frequently focused on single tasks or problems. Theorists suggest that, with sufficient experience in the clinical setting, novice nurses will move from reliance on abstract principles to the application of concrete experience and to view a clinical situation within its context and as a whole. In the current health care environment, novice nurses frequently work with few clinical supports and mentors while facing complex patient situations that demand skilled decision-making. The Situated Clinical Decision-Making Framework is presented for use by educators and novice nurses to support development of clinical decision-making. It provides novice nurses with a tool that a) assists them in making decisions; b) can be used to guide retrospective reflection on decision-making processes and outcomes; c) socializes them to an understanding of the nature of decision-making in nursing; and d) fosters the development of their knowledge, skill, and confidence as nurses. This article provides an overview of the framework, including its theoretical foundations and a schematic representation of its components. A case exemplar illustrates one application of the framework in assisting novice nurses in developing their decision-making skills. Future directions regarding the use and study of this framework in nursing education are considered.

  14. 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…

  15. DocBot: a novel clinical decision support algorithm.

    PubMed

    Ninh, Andrew Q

    2014-01-01

    DocBot is a web-based clinical decision support system (CDSS) that uses patient interaction and electronic health record analytics to assist medical practitioners with decision making. It consists of two distinct HTML interfaces: a preclinical form wherein a patient inputs symptomatic and demographic information, and an interface wherein a medical practitioner views patient information and analysis. DocBot comprises an improved software architecture that uses patient information, electronic health records, and etiologically relevant binary decision questions (stored in a knowledgebase) to provide medical practitioners with information including, but not limited to medical assessments, treatment plans, and specialist referrals.

  16. 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

  17. Clinical decision making of nurses working in hospital settings.

    PubMed

    Bjørk, Ida Torunn; Hamilton, Glenys A

    2011-01-01

    This study analyzed nurses' perceptions of clinical decision making (CDM) in their clinical practice and compared differences in decision making related to nurse demographic and contextual variables. A cross-sectional survey was carried out with 2095 nurses in four hospitals in Norway. A 24-item Nursing Decision Making Instrument based on cognitive continuum theory was used to explore how nurses perceived their CDM when meeting an elective patient for the first time. Data were analyzed with descriptive frequencies, t-tests, Chi-Square test, and linear regression. Nurses' decision making was categorized into analytic-systematic, intuitive-interpretive, and quasi-rational models of CDM. Most nurses reported the use of quasi-rational models during CDM thereby supporting the tenet that cognition most often includes properties of both analysis and intuition. Increased use of intuitive-interpretive models of CDM was associated with years in present job, further education, male gender, higher age, and working in predominantly surgical units.

  18. 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

  19. A clinical model for decision-making

    PubMed Central

    Martin, Richard M

    1978-01-01

    Richard Martin's aim in this paper is to present a critical method of making ethical decisions in a medical context. He feels that such a reflective method provides the best means of making the appropriate decisions in given situations. It is based on Dr Martin's experience in applying ethical theory while collaborating with physicians in the daily course of clinical practice. Through his giving of a functional definition of medical ethics, his descriptions of an analytical model, the significance of values for clinical decision-making and the advocacy role of medical ethicists and their relationships with clinicians, Richard Martin sets out his own value-intention as regards an ideal decision process. He stresses that his argument is of particular importance to his fellow ethicists who should continuously and vigorously examine the creative interaction of faith and fact in their own inquiry and action. Dr Martin concludes by stating that physicians and ethicists can work together to accomplish their common aim, which is, of course, the health and well-being of the patient. PMID:739517

  20. Latent effects decision analysis

    DOEpatents

    Cooper, J. Arlin; Werner, Paul W.

    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).

  1. 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.

  2. 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.

  3. 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

  4. Computerised clinical decision support for suspected PE.

    PubMed

    Jiménez, David; Resano, Santiago; Otero, Remedios; Jurkojc, Carolina; Portillo, Ana Karina; Ruiz-Artacho, Pedro; Corres, Jesús; Vicente, Agustina; den Exter, Paul L; Huisman, Menno V; Moores, Lisa; Yusen, Roger D

    2015-09-01

    This study aimed to determine the effect of an evidence-based clinical decision support (CDS) algorithm on the use and yield of CT pulmonary angiography (CTPA) and on outcomes of patients evaluated in the emergency department (ED) for suspected PE. The study included 1363 consecutive patients evaluated for suspected PE in an ED during 12 months before and 12 months after initiation of CDS use. Introduction of CDS was associated with decreased CTPA use (55% vs 49%; absolute difference (AD), 6.3%; 95% CI 1.0% to 11.6%; p=0.02). The use of CDS was associated with fewer symptomatic venous thromboembolic events during follow-up in patients with an initial negative diagnostic evaluation for PE (0.7% vs 3.2%; AD 2.5%; 95% CI 0.9% to 4.6%; p<0.01).

  5. 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

  6. 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…

  7. 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

  8. 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

  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.

  10. Lung function tests in clinical decision-making.

    PubMed

    Puente Maestú, Luis; García de Pedro, Julia

    2012-05-01

    In this article, we review the utility of the most common lung function tests (spirometry, reversibility test, peak expiratory flow, lung volumes, maximal respiratory pressure, carbon monoxide transference, arterial blood gas, 6-minute walk test and desaturation with exercise and ergospirometry) related to the most frequent pathologies (dyspnea of undetermined origin, chronic cough, asthma, COPD, neuromuscular diseases, interstitial diseases, pulmonary vascular diseases, pre-operative evaluation and disability evaluation). Our analysis has been developed from the perspective of decision-making, clinical interpretation or aspects that the physician should take into account with their use. Consequently, the paper does not deal with aspects of quality, technique or equipment, with the exception of when regarding costs as we believe that this is an important element in the decision-making process. The document is extensively supported by references from the literature.

  11. 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…

  12. 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

    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

  13. 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

  14. 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

  15. An exploration of clinical decision making in mental health triage.

    PubMed

    Sands, Natisha

    2009-08-01

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

  16. Artificial neural networks for decision support in clinical medicine.

    PubMed

    Forsström, J J; Dalton, K J

    1995-10-01

    Connectionist models such as neural networks are alternatives to linear, parametric statistical methods. Neural networks are computer-based pattern recognition methods with loose similarities with the nervous system. Individual variables of the network, usually called 'neurones', can receive inhibitory and excitatory inputs from other neurones. The networks can define relationships among input data that are not apparent when using other approaches, and they can use these relationships to improve accuracy. Thus, neural nets have substantial power to recognize patterns even in complex datasets. Neural network methodology has outperformed classical statistical methods in cases where the input variables are interrelated. Because clinical measurements usually derive from multiple interrelated systems it is evident that neural networks might be more accurate than classical methods in multivariate analysis of clinical data. This paper reviews the use of neural networks in medical decision support. A short introduction to the basics of neural networks is given, and some practical issues in applying the networks are highlighted. The current use of neural networks in image analysis, signal processing and laboratory medicine is reviewed. It is concluded that neural networks have an important role in image analysis and in signal processing. However, further studies are needed to determine the value of neural networks in the analysis of laboratory data.

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

    PubMed

    Morris, A H

    2000-03-01

    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. PMID:10691588

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

    PubMed

    Morris, A H

    2000-03-01

    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.

  19. Better clinical decision making and reducing diagnostic error.

    PubMed

    Croskerry, P; Nimmo, G R

    2011-06-01

    A major amount of our time working in clinical practice involves thinking and decision making. Perhaps it is because decision making is such a commonplace activity that it is assumed we can all make effective decisions. However, this is not the case and the example of diagnostic error supports this assertion. Until quite recently there has been a general nihilism about the ability to change the way that we think, but it is now becoming accepted that if we can think about, and understand, our thinking processes we can improve our decision making, including diagnosis. In this paper we review the dual process model of decision making and highlight ways in which decision making can be improved through the application of this model to our day-to-day practice and by the adoption of de-biasing strategies and critical thinking. PMID:21677922

  20. 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…

  1. 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.

  2. 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…

  3. 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...

  4. Endodontic retreatment. Aspects of decision making and clinical outcome.

    PubMed

    Kvist, T

    2001-01-01

    Epidemiological surveys have reported that 25%-35% of root filled teeth are associated with periapical radiolucencies. Descriptive studies have demonstrated that clinicians' decision making regarding such teeth are subject to substantial variation. A coherent model to explain the observed variation has not been produced. In the present thesis a "Praxis Concept theory" was proposed. The theory suggests that dentists perceive periapical lesions of varying sizes as different stages on a continuous health scale. Interindividual variations can then be regarded as the result of the choice of different cut-off points on the continuum for prescribing retreatment. In the present study experiments among novice and expert decision makers gave evidence in favour of the theory. Data also suggested that the choice of retreatment criterion is affected by values, costs of retreatment and technical quality of original treatment. From a prescriptive point of view, the presence of a persistent periapical radiolucency has often been used as a criterion of endodontic "failure" and as an indication for endodontic retreatment. As an alternative decision strategy, the use of decision analysis has been proposed. Logical display of decision alternatives, values of probabilities, utility values (U-values) of the different outcomes and calculation of optimal decision strategy are features of this theory. The implementation of this approach is impeded by the uncertainty of outcome probabilities and lack of investigations concerning U-values. U-values of two periapical health states in root filled teeth (with and without a periapical lesion respectively) were investigated in a group of 82 dental students and among 16 Swedish endodontists. Two methods were used to elicit U-values: Standard gamble and Visual Analogue Scale. Large interindividual variation for both health states were recorded. The difference in U-values between the two health states was found to be statistically significant

  5. Clinical Decision Support Tools: The Evolution of a Revolution.

    PubMed

    Mould, D R; D'Haens, G; Upton, R N

    2016-04-01

    Dashboard systems for clinical decision support integrate data from multiple sources. These systems, the newest in a long line of dose calculators and other decision support tools, utilize Bayesian approaches to fully individualize dosing using information gathered through therapeutic drug monitoring. In the treatment of inflammatory bowel disease patients with infliximab, dashboards may reduce therapeutic failures and treatment costs. The history and future development of modern Bayesian dashboard systems is described. PMID:26785109

  6. Improving Clinical Decisions on T2DM Patients Integrating Clinical, Administrative and Environmental Data.

    PubMed

    Segagni, Daniele; Sacchi, Lucia; Dagliati, Arianna; Tibollo, Valentina; Leporati, Paola; De Cata, Pasqale; Chiovato, Luca; Bellazzi, Riccardo

    2015-01-01

    This work describes an integrated informatics system developed to collect and display clinically relevant data that can inform physicians and researchers about Type 2 Diabetes Mellitus (T2DM) patient clinical pathways and therapy adherence. The software we developed takes data coming from the electronic medical record (EMR) of the IRCCS Fondazione Maugeri (FSM) hospital of Pavia, Italy, and combines the data with administrative, pharmacy drugs (purchased from the local healthcare agency (ASL) of the Pavia area), and open environmental data of the same region. By using different use cases, we explain the importance of gathering and displaying the data types through a single informatics tool: the use of the tool as a calculator of risk factors and indicators to improve current detection of T2DM, a generator of clinical pathways and patients' behaviors from the point of view of the hospital care management, and a decision support tool for follow-up visits. The results of the performed data analysis report how the use of the dashboard displays meaningful clinical decisions in treating complex chronic diseases and might improve health outcomes. PMID:26262138

  7. 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

  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. PMID:26262260

  9. 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.

  10. 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

  11. 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.

  12. 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. PMID:23975905

  13. 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

  14. 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.

  15. Examining the Relationship between Clinical Decision Support and Performance Measurement

    PubMed Central

    Haggstrom, David A.; Saleem, Jason J.; Militello, Laura G.; Arbuckle, Nicole; Flanagan, Mindy; Doebbeling, Bradley N.

    2009-01-01

    In concept and practice, clinical decision support (CDS) and performance measurement represent distinct approaches to organizational change, yet these two organizational processes are interrelated. We set out to better understand how the relationship between the two is perceived, as well as how they jointly influence clinical practice. To understand the use of CDS at benchmark institutions, we conducted semistructured interviews with key managers, information technology personnel, and clinical leaders during a qualitative field study. Improved performance was frequently cited as a rationale for the use of clinical reminders. Pay-for-performance efforts also appeared to provide motivation for the use of clinical reminders. Shared performance measures were associated with shared clinical reminders. The close link between clinical reminders and performance measurement causes these tools to have many of the same implementation challenges. PMID:20351854

  16. 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

  17. 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).

  18. Decisions, decisions: analysis of age, cohort, and time of testing on framing of risky decision options.

    PubMed

    Mayhorn, Christopher B; Fisk, Arthur D; Whittle, Justin D

    2002-01-01

    Decision making in uncertain environments is a daily challenge faced by adults of all ages. Framing decision options as either gains or losses is a common method of altering decision-making behavior. In the experiment reported here, benchmark decision-making data collected in the 1970s by Tversky and Kahneman (1981, 1988) were compared with data collected from current samples of young and older adults to determine whether behavior was consistent across time. Although differences did emerge between the benchmark and the present samples, the effect of framing on decision behavior was relatively stable. The present findings suggest that adults of all ages are susceptible to framing effects. Results also indicated that apparent age differences might be better explained by an analysis of cohort and time-of-testing effects. Actual or potential applications of this research include an understanding of how framing might influence the decision-making behavior of people of all ages in a number of applied contexts, such as product warning interactions and medical decision scenarios.

  19. 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

  20. 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 PMID:27631861

  1. 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.

  2. Temporal pattern mining for multivariate clinical decision support.

    PubMed

    Saini, Sheetal; Dua, Sumeet

    2013-01-01

    Multivariate temporal data are collections of contiguous data values that reflect complex temporal changes over a given duration. Technological advances have resulted in significant amounts of such data in high-throughput disciplines, including EEG and iEEG data for effective and efficient healthcare informatics, and decision support. Most data analytics and data-mining algorithms are effective in capturing global trends, but fail to capture localized behavioral changes in large temporal data sets. We present a two-step algorithmic methodology to uncover temporal patterns and exploiting them for an efficient and accurate decision support system. This methodology aids the discovery of previously unknown, nontrivial, and potentially useful temporal patterns for enhanced patient-specific clinical decision support with high degrees of sensitivity and specificity. Classification results on multivariate time series iEEG data for epileptic seizure detection also demonstrate the efficacy and accuracy of the technique to uncover interesting and effective domain class-specific temporal patterns.

  3. 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.

  4. Standardization of clinical decision making for the conduct of credible clinical research in complicated medical environments.

    PubMed Central

    Morris, A. H.; East, T. D.; Wallace, C. J.; Franklin, M.; Heerman, L.; Kinder, T.; Sailor, M.; Carlson, D.; Bradshaw, R.

    1996-01-01

    The likelihood that past experience will produce correct guides to current practice depends on the signal-to-noise ratio for the clinical problem of interest. If the signal-to-noise ratio is high, the decision will be sound and patient benefit likely to occur. If the signal-to-noise ratio is low, as is commonly the case with difficult clinical decisions, then personal experience and the best intentions will not assure sound clinical decisions. When the probability of benefit cannot be quantified, clinicians in complex settings are in danger of being misled by data and experience. Quantifiable probabilities established by group experiment or observation will be necessary for clinical decisions that can be expected to confer benefit on the patient. Explicit methods are necessary for interventions that can be replicated in experiments or in practice. Computerized protocols force the articulation of explicit clinical care methods and standardize clinical decision making. We have developed explicit, rule-based protocols, implemented them in our hospital, exported them to other hospitals, and successfully achieved a rigorous experimental environment in the clinical ICU. Exportation of such explicit methods may narrow the gap between efficacy (university hospital) and effectiveness (community hospital) research results. PMID:8947700

  5. 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…

  6. 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. PMID:27618499

  7. 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

  8. 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

  9. Knowledge-analytics synergy in Clinical Decision Support.

    PubMed

    Slonim, Noam; Carmeli, Boaz; Goldsteen, Abigail; Keller, Oliver; Kent, Carmel; Rinott, Ruty

    2012-01-01

    Clinical Decision Support (CDS) systems hold tremendous potential for improving patient care. Most existing systems are knowledge-based tools that rely on relatively simple rules. More recent approaches rely on analytics techniques to automatically mine EHR data to reveal meaningful insights. Here, we propose the Knowledge-Analytics Synergy paradigm for CDS, in which we synergistically combine existing relevant knowledge with analytics applied to EHR data. We propose a framework for implementing such a paradigm and demonstrate its principles over real-world clinical and genomic data of hypertensive patients.

  10. 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

  11. Reducing diagnostic error with computer-based clinical decision support.

    PubMed

    Greenes, Robert A

    2009-09-01

    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 making (Schiff). In addition, several other considerations relating to this topic are interesting to ponder. We are moving toward increased understanding of gene regulation and gene expression, identification of biomarkers, and the ability to predict patient response to disease and to tailor treatments to these individual variations-referred to as "personalized" or, more recently, "predictive" medicine. Consequently, diagnostic decision making is more and more linked to management decision making, and generic diagnostic labels like "diabetes" or "colon cancer" will no longer be sufficient, because they don't tell us what to do. Ultimately, if we have more complete data including more structured capture of phenomic data as well as the characterization of the patient's genome, direct prediction from responses of highly refined subsets of similar patients in a database can be used to select appropriate management, the effectiveness of which was demonstrated in projects in selected limited domains as early as the 1970s. In general, there are six classes of methodologies, including the above, which can be applied to delivering CDS. In addition, patients are becoming more knowledgeable and should be regarded as active participants, not only in helping to obtain data but also in their own status assessment and as recipients of decision support. With the above advances, this is a very promising time to be engaged in pursuit of methods of CDS. PMID:19669915

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

    PubMed

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

    2016-01-01

    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

  13. 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

  14. Bayesian model selection techniques as decision support for shaping a statistical analysis plan of a clinical trial: An example from a vertigo phase III study with longitudinal count data as primary endpoint

    PubMed Central

    2012-01-01

    Background A statistical analysis plan (SAP) is a critical link between how a clinical trial is conducted and the clinical study report. To secure objective study results, regulatory bodies expect that the SAP will meet requirements in pre-specifying inferential analyses and other important statistical techniques. To write a good SAP for model-based sensitivity and ancillary analyses involves non-trivial decisions on and justification of many aspects of the chosen setting. In particular, trials with longitudinal count data as primary endpoints pose challenges for model choice and model validation. In the random effects setting, frequentist strategies for model assessment and model diagnosis are complex and not easily implemented and have several limitations. Therefore, it is of interest to explore Bayesian alternatives which provide the needed decision support to finalize a SAP. Methods We focus on generalized linear mixed models (GLMMs) for the analysis of longitudinal count data. A series of distributions with over- and under-dispersion is considered. Additionally, the structure of the variance components is modified. We perform a simulation study to investigate the discriminatory power of Bayesian tools for model criticism in different scenarios derived from the model setting. We apply the findings to the data from an open clinical trial on vertigo attacks. These data are seen as pilot data for an ongoing phase III trial. To fit GLMMs we use a novel Bayesian computational approach based on integrated nested Laplace approximations (INLAs). The INLA methodology enables the direct computation of leave-one-out predictive distributions. These distributions are crucial for Bayesian model assessment. We evaluate competing GLMMs for longitudinal count data according to the deviance information criterion (DIC) or probability integral transform (PIT), and by using proper scoring rules (e.g. the logarithmic score). Results The instruments under study provide excellent

  15. 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

  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. 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. PMID:24278827

  18. Clinical utility of an electronic poisons information and clinical decision support tool.

    PubMed

    Watts, Martin; Fountain, John; Reith, David M; Herbison, Peter

    2003-08-01

    The objective of the study was to assess the use of a computer toxicology database/clinical decision aid by clinical practitioners. The study investigated the sources that Emergency Department (ED) personnel use to obtain toxicology information and performed a quality audit of the current database. A questionnaire survey of ED staff was used in departments with access to the New Zealand Poisons Centre Substance Database (NZSD), a toxicology CD ROM computer database. Outcome measures were reported use of alternative data sources when managing clinical toxicology presentations and the qualities of the NZSD. Computer databases are commonly used for the management of clinical toxicology cases and the toxicology computer database/clinical decision aid studied is well accepted and used in Emergency Medicine practice. The users of the NZSD assessed the usability and quality of the information of the database. PMID:12909152

  19. 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.

  20. 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. PMID:27026589

  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. PMID:8326214

  2. 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

  3. 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.

  4. Clinical Decision Support for Colon and Rectal Surgery: An Overview

    PubMed Central

    McCoy, Allison B.; Melton, Genevieve B.; Wright, Adam; Sittig, Dean F.

    2013-01-01

    Clinical decision support (CDS) has been shown to improve clinical processes, promote patient safety, and reduce costs in healthcare settings, and it is now a requirement for clinicians as part of the Meaningful Use Regulation. However, most evidence for CDS has been evaluated primarily in internal medicine care settings, and colon and rectal surgery (CRS) has unique needs with CDS that are not frequently described in the literature. The authors reviewed published literature in informatics and medical journals, combined with expert opinion to define CDS, describe the evidence for CDS, outline the implementation process for CDS, and present applications of CDS in CRS.CDS functionalities such as order sets, documentation templates, and order facilitation aids are most often described in the literature and most likely to be beneficial in CRS. Further research is necessary to identify and better evaluate additional CDS systems in the setting of CRS. PMID:24436644

  5. 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. PMID:26152955

  6. 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

  7. 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.

  8. 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

  9. 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. PMID:22819925

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

    PubMed

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

    2007-01-01

    This article reports on the International Patient Decision Aid Standards Symposium held in 2006 at the annual meeting of the Society for Medical Decision Making in Cambridge, Massachusetts. The symposium featured a debate regarding the proposition that "decision aids are the best way to improve clinical decision making.'' The formal debate addressed the theoretical problem of the appropriate gold standard for an improved decision, efficacy of decision aids, and prospects for implementation. Audience comments and questions focused on both theory and practice: the often unacknowledged roots of decision aids in expected utility theory and the practical problems of limited patient decision aid implementation in health care. The participants' vote on the proposition was approximately half for and half against. PMID:17873257

  11. 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.

  12. Helping patients make choices about breast reconstruction: a decision analysis approach.

    PubMed

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

    2014-10-01

    Decision analysis can help breast reconstruction patients and their surgeons to methodically evaluate clinical alternatives and make hard decisions. The purpose of this article 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 article aims to illustrate decision analysis techniques from the patient perspective, with an emphasis on her values and preferences. The authors introduce normative decision-making through a fictional breast reconstruction patient and systematically build the decision basis to help her make a good decision. The authors 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, the authors discuss how sensitivity analysis may test the robustness of the decision and how to evaluate the quality of decisions. The authors also present tools to help implement these concepts in practice. Finally, the authors examine limitations that hamper adoption of patient decision analysis in reconstructive surgery and health care in general. In particular, the authors emphasize the need for routine collection of quality-of-life information, out-of-pocket expense, and recovery time.

  13. A systematic review of clinical decision rules for epilepsy.

    PubMed

    Josephson, Colin B; Sandy, Sherry; Jette, Nathalie; Sajobi, Tolulope T; Marshall, Deborah; Wiebe, Samuel

    2016-04-01

    Clinical decision rules (CDRs) have been empirically demonstrated to improve patient satisfaction and enhance cost-effective care. The use of CDRs has not yet been robustly explored for epilepsy. We performed a systematic review of MEDLINE (from 1946) and Embase (from 1947) using Medical Subject Headings and keywords related to CDRs and epilepsy. We included original research of any language deriving, validating, or implementing a CDR using standardized definitions. Study quality was determined using a modified version of previously published criteria. A bivariate model was used to meta-analyze studies undergoing sequential derivation and validation studies. Of 2445 unique articles, 5 were determined to be relevant to this review. Three were derivation studies (three diagnostic and one therapeutic), one validation study, and one combined derivation and validation study. No implementation studies were identified. Study quality varied but was primarily of a moderate level. Two CDRs were validated and, thus, able to be meta-analyzed. Although initial measures of accuracy were high (sensitivity ~80% or above), they tended to diminish significantly in the validation studies. The pooled estimates of sensitivity and specificity both exhibited wide 95% confidence and prediction intervals that may limit their utility in routine practice. Despite the advances in therapeutic and diagnostic interventions for epilepsy, few CDRs have been developed to guide their use. Future CDRs should address common clinical scenarios such as efficient use of diagnostic tools and optimal clinical treatment decisions. Given their potential for advancing efficient, evidence-based, patient-centered healthcare, CDR development should be a priority in epilepsy. PMID:26922491

  14. 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.

  15. 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. PMID:20523217

  16. 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

  17. Analysis of obstetricians' decision making on CTG recordings.

    PubMed

    Spilka, Jiří; Chudáček, Václav; Janků, Petr; Hruban, Lukáš; Burša, Miroslav; Huptych, Michal; Zach, Lukáš; Lhotská, Lenka

    2014-10-01

    Interpretation of cardiotocogram (CTG) is a difficult task since its evaluation is complicated by a great inter- and intra-individual variability. Previous studies have predominantly analyzed clinicians' agreement on CTG evaluation based on quantitative measures (e.g. kappa coefficient) that do not offer any insight into clinical decision making. In this paper we aim to examine the agreement on evaluation in detail and provide data-driven analysis of clinical evaluation. For this study, nine obstetricians provided clinical evaluation of 634 CTG recordings (each ca. 60min long). We studied the agreement on evaluation and its dependence on the increasing number of clinicians involved in the final decision. We showed that despite of large number of clinicians the agreement on CTG evaluations is difficult to reach. The main reason is inherent inter- and intra-observer variability of CTG evaluation. Latent class model provides better and more natural way to aggregate the CTG evaluation than the majority voting especially for larger number of clinicians. Significant improvement was reached in particular for the pathological evaluation - giving a new insight into the process of CTG evaluation. Further, the analysis of latent class model revealed that clinicians unconsciously use four classes when evaluating CTG recordings, despite the fact that the clinical evaluation was based on FIGO guidelines where three classes are defined.

  18. 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.

  19. [HEALTH ECONOMIC ANALYSIS AND FAIR DECISION MAKING].

    PubMed

    Jeantet, Marine; Lopez, Alain

    2015-09-01

    Health technology assessment consists in evaluating the incremental cost-benefit ratio of a medicine, a medical device, a vaccine, a health strategy, in comparison to alternative health technologies. This form of socio-eoonomic evaluation aims at optimizing resource allocation within the health system. By setting the terms of valid alternatives, it is useful to highlight public choices, but it cannot in itself make the decision as regards the public funding of patient's access to the considered technology. The decision to include such technology in the basket of health goods and sercices covered, the levels and conditions of the coverage, also result from budget constraints, from economic situation and from a political vision about health policy, social protection and public expenditure. Accordingly, health economic analysis must be implemented on specific and targeted topics. The decision making process, with its health, economic and ethical stakes, calls for a public procedure and debate, based on shared information and argument. Otherwise, health system regulation, confronted with radical and costly innovations in the coming years, will become harder to handle. This requires the development of health economic research teams able to contribute to this assessment exercise. PMID:26619723

  20. 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. PMID:25385815

  1. Optimizing perioperative decision making: improved information for clinical workflow planning.

    PubMed

    Doebbeling, Bradley N; Burton, Matthew M; Wiebke, Eric A; Miller, Spencer; Baxter, Laurence; Miller, Donald; Alvarez, Jorge; Pekny, Joseph

    2012-01-01

    Perioperative care is complex and involves multiple interconnected subsystems. Delayed starts, prolonged cases and overtime are common. Surgical procedures account for 40-70% of hospital revenues and 30-40% of total costs. Most planning and scheduling in healthcare is done without modern planning tools, which have potential for improving access by assisting in operations planning support. We identified key planning scenarios of interest to perioperative leaders, in order to examine the feasibility of applying combinatorial optimization software solving some of those planning issues in the operative setting. Perioperative leaders desire a broad range of tools for planning and assessing alternate solutions. Our modeled solutions generated feasible solutions that varied as expected, based on resource and policy assumptions and found better utilization of scarce resources. Combinatorial optimization modeling can effectively evaluate alternatives to support key decisions for planning clinical workflow and improving care efficiency and satisfaction.

  2. A clinical flow cytometry data analysis assistant

    SciTech Connect

    Salzman, G.C. ); Stewart, C.C. ); Duque, R.E. ); Braylan, R.C. . Coll. of Medicine)

    1990-01-01

    A rule-based expert system is being developed to assist clinicians in the analysis of multivariate flow cytometry data for patients with leukemias or lymphomas. The cells are stained with fluorescently labeled monoclonal antibodies and the cell fluorescence is measured with a flow cytometer. Cluster analysis is used to isolate subpopulations in the data on which the clinical decisions are made. Symbolic facts for the expert system are instantiated using these numerical data and the knowledge of the clinicians and experts in flow cytometry. The first prototype used a decision tree and rigid rules. Is successfully classified only nine of eleven leukemia cases. A second prototype incorporating certainty factors into the rules is now being developed that should remove the need for a rigid decision tree. 9 refs.

  3. Requiring Clinical Justification to Override Repeat Imaging Decision Support: Impact on CT Use

    PubMed Central

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

    2014-01-01

    OBJECTIVE The purpose of this study was to determine the impact of requiring clinical justification to override decision support alerts on repeat use of CT. SUBJECTS AND METHODS 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. RESULTS 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. CONCLUSION 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. PMID:25341162

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

    PubMed Central

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

    2016-01-01

    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. PMID:25998518

  5. 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

  6. 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.

  7. 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…

  8. [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. PMID:26946752

  9. [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.

  10. 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.

  11. 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.

  12. 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.

  13. 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

  14. 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.

  15. Clinical decision-making in early breast cancer.

    PubMed Central

    Balch, C M; Singletary, S E; Bland, K I

    1993-01-01

    OBJECTIVE: This in-depth review of the multidisciplinary approach to early breast cancer treatment (in situ, stage I and II) will update the surgeon about the indications, risks, and benefits of breast surgery, radiation therapy, adjuvant chemotherapy and hormonal therapy, and the importance of breast reconstructive surgery. SUMMARY BACKGROUND DATA: Breast cancer will occur in one of eight women in the United States during their lifetime and is the second leading cause of death in women from cancer. The practice of multidisciplinary breast cancer treatment has become the standard of care for the majority of breast cancer patients. If the surgeon is to retain the primary coordinating role in breast cancer management, then he or she must fully understand all modalities of oncology therapy and know how to deploy them to benefit individual patients. CONCLUSIONS: This article provides a framework for making clinical decisions about the appropriate combination and sequence of treatment for various presentations of early breast cancer. Images Figure 4. PMID:8383953

  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. 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...

  19. Integrating Clinical Decision Support into EMR and PHR: a Case Study Using Anticoagulation.

    PubMed

    Chackery, Dave-Gregory; Keshavjee, Karim; Mirza, Kashif; Ghany, Ahmad; Holbrook, Anne M

    2015-01-01

    Clinical decision support (CDS) for atrial fibrillation is expected to ease the implementation of often-complex guidelines for atrial fibrillation and anticoagulation. Most clinical decision support systems (CDSS) for anticoagulation are stand-alone systems that do not integrate with electronic medical records (EMR). We have developed an architecture that consists of a computerized CDS that can integrate with multiple EMRs and multiple patient health records (PHRs). The design process revealed some significant issues that were resolved through systematic business/clinical analysis and creative clinical design in the diagnostic and treatment domains. Key issues identified and resolved include: 1) how to correctly allocate existing patients into various CDSS states (e.g., MAINTENANCE, HOLD, DISCONTINUE, etc), 2) identify when a patient becomes eligible for CDSS guidance over time, 3) how the CDSS maintains information about the patient's anticoagulation state and 4) how to transform vague human-readable concepts to explicit computable concepts. The management of anticoagulation for atrial fibrillation is no easy task and we believe our architecture will improve patient care at all levels and ultimately better balance the reduction of stroke risk while minimizing harms from major bleeding. In addition, the architecture presented is scalable to other treatment guidelines and is scalable to multiple EMRs and PHRs, making it suitable for use in a platform approach. PMID:25676955

  20. 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.

  1. 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.

  2. 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

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

    PubMed

    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

  4. 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.

  5. 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. PMID:23366138

  6. 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.

  7. 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 ...

  8. 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.

  9. 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.

  10. 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.

  11. 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

  12. 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

  13. 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.

  14. Barriers and facilitators to implementing shared decision-making in clinical practice: a systematic review of health professionals' perceptions

    PubMed Central

    Gravel, Karine; Légaré, France; Graham, Ian D

    2006-01-01

    Background Shared decision-making is advocated because of its potential to improve the quality of the decision-making process for patients and ultimately, patient outcomes. However, current evidence suggests that shared decision-making has not yet been widely adopted by health professionals. Therefore, a systematic review was performed on the barriers and facilitators to implementing shared decision-making in clinical practice as perceived by health professionals. Methods Covering the period from 1990 to March 2006, PubMed, Embase, CINHAL, PsycINFO, and Dissertation Abstracts were searched for studies in English or French. The references from included studies also were consulted. Studies were included if they reported on health professionals' perceived barriers and facilitators to implementing shared decision-making in their practices. Shared decision-making was defined as a joint process of decision making between health professionals and patients, or as decision support interventions including decision aids, or as the active participation of patients in decision making. No study design was excluded. Quality of the studies included was assessed independently by two of the authors. Using a pre-established taxonomy of barriers and facilitators to implementing clinical practice guidelines in practice, content analysis was performed. Results Thirty-one publications covering 28 unique studies were included. Eleven studies were from the UK, eight from the USA, four from Canada, two from the Netherlands, and one from each of the following countries: France, Mexico, and Australia. Most of the studies used qualitative methods exclusively (18/28). Overall, the vast majority of participants (n = 2784) were physicians (89%). The three most often reported barriers were: time constraints (18/28), lack of applicability due to patient characteristics (12/28), and lack of applicability due to the clinical situation (12/28). The three most often reported facilitators were: provider

  15. 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...

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

    PubMed

    Müller-Staub, Maria

    2006-10-01

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

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

    PubMed

    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

  19. 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

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

    PubMed Central

    Plasseraud, Kristen Meldi; 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). PMID:27446211

  1. Network Meta-analysis to Synthesize Evidence for Decision Making in Cardiovascular Research

    PubMed Central

    Roever, Leonardo; Biondi-Zoccai, Giuseppe

    2016-01-01

    Clinical decision-making requires synthesis of evidence from literature reviews focused on a specific theme. Evidence synthesis is performed with qualitative assessments and systematic reviews of randomized clinical trials, typically covering statistical pooling with pairwise meta-analyses. These methods include adjusted indirect comparison meta-analysis, network meta-analysis, and mixed-treatment comparison. These tools allow synthesis of evidence and comparison of effectiveness in cardiovascular research. PMID:27142793

  2. 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.

  3. 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

  4. EVIDENCE AND CLINICAL DECISIONS: Asking the Right Questions to Obtain Clinically Useful Answers

    PubMed Central

    Proffit, William R.

    2013-01-01

    Orthodontists need to know the effectiveness, efficiency and predictability of treatment approaches and methods, which can be learned only by carefully studying and evaluating treatment outcomes. The best data for outcomes come from randomized clinical trials (RCTs), but retrospective data can provide satisfactory evidence if the subjects were a well-defined patient group, all the patients were accounted for, and the percentages of patients with various possible outcomes are presented along with measures of the central tendency and variation. Meta-analysis of multiple RCTs done in a similar way and systematic reviews of the literature can strengthen clinically-useful evidence, but reviews that are too broadly based are more likely to blur than clarify the information clinicians need. Reviews that are tightly focused on seeking the answer to specific clinical questions and evaluating the quality of the evidence available to answer the question are much more likely to provide clinically useful data. PMID:24198455

  5. Depression: a decision-theoretic analysis.

    PubMed

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

    2015-07-01

    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. PMID:25705929

  6. Depression: a decision-theoretic analysis.

    PubMed

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

    2015-07-01

    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.

  7. 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…

  8. 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.

  9. 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…

  10. 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.…

  11. 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…

  12. [Locator or ball attachment: a guide for clinical decision making].

    PubMed

    Büttel, Adrian E; Bühler, Nico M; Marinello, Carlo P

    2009-01-01

    Various attachments are available to retain overdentures on natural roots or implants. Technical aspects, the clinical handling, the capability to adapt or repair and the costs are parameters to be considered when choosing the appropriate attachment. Ball attachments and bars are clinically established and well documented. Ball attachments as prefabricated, unsplinted units are easily replaceable and show hygienic advantages, while bars show favorable stability. The Locator is a newer, popular clinical alternative to these established attachments. The ball attachment and the Locator are compared from a technical and clinical point of view.

  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. 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.

  15. 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. PMID:26361268

  16. [Clinical gait analysis: user guide].

    PubMed

    Armand, Stéphane; Bonnefoy-Mazure, Alice; Hoffmeyer, Pierre; De Coulon, Geraldo

    2015-10-14

    Clinical gait analysis has become an indispensable medical examination for the management of patients with complex gait disorders. As its name suggests, the purpose of this examination is to assess patients whilst they are walking in a laboratory setting. Measurements include: 3 dimensional joint motion, forces applied to joints, and electromyographic muscle activity. This quantitative data allows identification of walking deviations and to deduce the likely causes of these deviations thanks to the clinical data available for each patient.

  17. 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.

  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. 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...

  20. 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…

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

    PubMed

    Buckingham, C D; Adams, A

    2000-10-01

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

  2. Electrochemical Sensors for Clinic Analysis

    PubMed Central

    Wang, You; Xu, Hui; Zhang, Jianming; Li, Guang

    2008-01-01

    Demanded by modern medical diagnosis, advances in microfabrication technology have led to the development of fast, sensitive and selective electrochemical sensors for clinic analysis. This review addresses the principles behind electrochemical sensor design and fabrication, and introduces recent progress in the application of electrochemical sensors to analysis of clinical chemicals such as blood gases, electrolytes, metabolites, DNA and antibodies, including basic and applied research. Miniaturized commercial electrochemical biosensors will form the basis of inexpensive and easy to use devices for acquiring chemical information to bring sophisticated analytical capabilities to the non-specialist and general public alike in the future.

  3. 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.

  4. The NIAID Division of AIDS enterprise information system: integrated decision support for global clinical research programs

    PubMed Central

    Gupta, Nitin; Varghese, Suresh; Virkar, Hemant

    2011-01-01

    The National Institute of Allergy and Infectious Diseases (NIAID) Division of AIDS (DAIDS) Enterprise Information System (DAIDS-ES) is a web-based system that supports NIAID in the scientific, strategic, and tactical management of its global clinical research programs for HIV/AIDS vaccines, prevention, and therapeutics. Different from most commercial clinical trials information systems, which are typically protocol-driven, the DAIDS-ES was built to exchange information with those types of systems and integrate it in ways that help scientific program directors lead the research effort and keep pace with the complex and ever-changing global HIV/AIDS pandemic. Whereas commercially available clinical trials support systems are not usually disease-focused, DAIDS-ES was specifically designed to capture and incorporate unique scientific, demographic, and logistical aspects of HIV/AIDS treatment, prevention, and vaccine research in order to provide a rich source of information to guide informed decision-making. Sharing data across its internal components and with external systems, using defined vocabularies, open standards and flexible interfaces, the DAIDS-ES enables NIAID, its global collaborators and stakeholders, access to timely, quality information about NIAID-supported clinical trials which is utilized to: (1) analyze the research portfolio, assess capacity, identify opportunities, and avoid redundancies; (2) help support study safety, quality, ethics, and regulatory compliance; (3) conduct evidence-based policy analysis and business process re-engineering for improved efficiency. This report summarizes how the DAIDS-ES was conceptualized, how it differs from typical clinical trial support systems, the rationale for key design choices, and examples of how it is being used to advance the efficiency and effectiveness of NIAID's HIV/AIDS clinical research programs. PMID:21816958

  5. The NIAID Division of AIDS enterprise information system: integrated decision support for global clinical research programs.

    PubMed

    Kagan, Jonathan M; Gupta, Nitin; Varghese, Suresh; Virkar, Hemant

    2011-12-01

    The National Institute of Allergy and Infectious Diseases (NIAID) Division of AIDS (DAIDS) Enterprise Information System (DAIDS-ES) is a web-based system that supports NIAID in the scientific, strategic, and tactical management of its global clinical research programs for HIV/AIDS vaccines, prevention, and therapeutics. Different from most commercial clinical trials information systems, which are typically protocol-driven, the DAIDS-ES was built to exchange information with those types of systems and integrate it in ways that help scientific program directors lead the research effort and keep pace with the complex and ever-changing global HIV/AIDS pandemic. Whereas commercially available clinical trials support systems are not usually disease-focused, DAIDS-ES was specifically designed to capture and incorporate unique scientific, demographic, and logistical aspects of HIV/AIDS treatment, prevention, and vaccine research in order to provide a rich source of information to guide informed decision-making. Sharing data across its internal components and with external systems, using defined vocabularies, open standards and flexible interfaces, the DAIDS-ES enables NIAID, its global collaborators and stakeholders, access to timely, quality information about NIAID-supported clinical trials which is utilized to: (1) analyze the research portfolio, assess capacity, identify opportunities, and avoid redundancies; (2) help support study safety, quality, ethics, and regulatory compliance; (3) conduct evidence-based policy analysis and business process re-engineering for improved efficiency. This report summarizes how the DAIDS-ES was conceptualized, how it differs from typical clinical trial support systems, the rationale for key design choices, and examples of how it is being used to advance the efficiency and effectiveness of NIAID's HIV/AIDS clinical research programs.

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

    ERIC Educational Resources Information Center

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

    2013-01-01

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

  7. Empirically and Clinically Useful Decision Making in Psychotherapy: Differential Predictions with Treatment Response Models

    ERIC Educational Resources Information Center

    Lutz, Wolfgang; Saunders, Stephen M.; Leon, Scott C.; Martinovich, Zoran; Kosfelder, Joachim; Schulte, Dietmar; Grawe, Klaus; Tholen, Sven

    2006-01-01

    In the delivery of clinical services, outcomes monitoring (i.e., repeated assessments of a patient's response to treatment) can be used to support clinical decision making (i.e., recurrent revisions of outcome expectations on the basis of that response). Outcomes monitoring can be particularly useful in the context of established practice research…

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

    NASA Astrophysics Data System (ADS)

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

    2016-10-01

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

  9. Using a service oriented architecture approach to clinical decision support: performance results from two CDS Consortium demonstrations.

    PubMed

    Paterno, Marilyn D; Goldberg, Howard S; Simonaitis, Linas; Dixon, Brian E; Wright, Adam; Rocha, Beatriz H; Ramelson, Harley Z; Middleton, Blackford

    2012-01-01

    The Clinical Decision Support Consortium has completed two demonstration trials involving a web service for the execution of clinical decision support (CDS) rules in one or more electronic health record (EHR) systems. The initial trial ran in a local EHR at Partners HealthCare. A second EHR site, associated with Wishard Memorial Hospital, Indianapolis, IN, was added in the second trial. Data were gathered during each 6 month period and analyzed to assess performance, reliability, and response time in the form of means and standard deviations for all technical components of the service, including assembling and preparation of input data. The mean service call time for each period was just over 2 seconds. In this paper we report on the findings and analysis to date while describing the areas for further analysis and optimization as we continue to expand our use of a Services Oriented Architecture approach for CDS across multiple institutions.

  10. A Three-Question Framework to Facilitate Clinical Decision Making

    ERIC Educational Resources Information Center

    Sibold, Jeremy

    2012-01-01

    Context: Highly developed critical thinking and the ability to discriminate among many possible therapeutic interventions is a core behavior for the practicing athletic trainer. However, while athletic training students receive a great deal of clinically applicable information, many are not explicitly trained in efficient methods for channeling…

  11. Detecting fast, online reasoning processes in clinical decision making.

    PubMed

    Flores, Amanda; Cobos, Pedro L; López, Francisco J; Godoy, Antonio

    2014-06-01

    In an experiment that used the inconsistency paradigm, experienced clinical psychologists and psychology students performed a reading task using clinical reports and a diagnostic judgment task. The clinical reports provided information about the symptoms of hypothetical clients who had been previously diagnosed with a specific mental disorder. Reading times of inconsistent target sentences were slower than those of control sentences, demonstrating an inconsistency effect. The results also showed that experienced clinicians gave different weights to different symptoms according to their relevance when fluently reading the clinical reports provided, despite the fact that all the symptoms were of equal diagnostic value according to the Diagnostic and Statistical Manual of Mental Disorders (4th ed., text rev.; American Psychiatric Association, 2000). The diagnostic judgment task yielded a similar pattern of results. In contrast to previous findings, the results of the reading task may be taken as direct evidence of the intervention of reasoning processes that occur very early, rapidly, and online. We suggest that these processes are based on the representation of mental disorders and that these representations are particularly suited to fast retrieval from memory and to making inferences. They may also be related to the clinicians' causal reasoning. The implications of these results for clinician training are also discussed. PMID:24274045

  12. Usability Testing and Adaptation of the Pediatric Cardiovascular Risk Reduction Clinical Decision Support Tool

    PubMed Central

    Furberg, Robert D; Bagwell, Jacqueline E; LaBresh, Kenneth A

    2016-01-01

    Background Cardiovascular disease (CVD) is 1 of the leading causes of death, years of life lost, and disability-adjusted years of life lost worldwide. CVD prevention for children and teens is needed, as CVD risk factors and behaviors beginning in youth contribute to CVD development. In 2012, the National Heart, Lung, and Blood Institute released their “Integrated Guidelines for Cardiovascular Health and Risk Reduction in Children and Adolescents” for clinicians, describing CVD risk factors they should address with patients at primary care preventative visits. However, uptake of new guidelines is slow. Clinical decision support (CDS) tools can improve guideline uptake. In this paper, we describe our process of testing and adapting a CDS tool to help clinicians evaluate patient risk, recommend behaviors to prevent development of risk, and complete complex calculations to determine appropriate interventions as recommended by the guidelines, using a user-centered design approach. Objective The objective of the study was to assess the usability of a pediatric CVD risk factor tool by clinicians. Methods The tool was tested using one-on-one in-person testing and a “think aloud” approach with 5 clinicians and by using the tool in clinical practice along with formal usability metrics with 14 pediatricians. Thematic analysis of the data from the in-person testing and clinical practice testing identified suggestions for change in 3 major areas: user experience, content refinement, and technical deployment. Descriptive statistical techniques were employed to summarize users’ overall experience with the tool. Results Data from testers showed that general reactions toward the CDS tool were positive. Clinical practice testers suggested revisions to make the application more user-friendly, especially for clinicians using the application on the iPhone, and called for refining recommendations to be more succinct and better tailored to the patient. Tester feedback was

  13. Dental patient preferences and choice in clinical decision-making.

    PubMed

    Fukai, Kakuhiro; Yoshino, Koichi; Ohyama, Atsushi; Takaesu, Yoshinori

    2012-01-01

    In economics, the concept of utility refers to the strength of customer preference. In health care assessment, the visual analogue scale (VAS), the standard gamble, and the time trade-off are used to measure health state utilities. These utility measurements play a key role in promoting shared decision-making in dental care. Individual preference, however, is complex and dynamic. The purpose of this study was to investigate the relationship between patient preference and educational intervention in the field of dental health. The data were collected by distributing questionnaires to employees of two companies in Japan. Participants were aged 18-65 years and consisted of 111 males and 93 females (204 in total). One company (Group A) had a dental program of annual check-ups and health education in the workplace, while the other company (Group B) had no such program. Statistical analyses were performed with the t-test and Chi-square test. The questionnaire items were designed to determine: (1) oral health-related quality of life, (2) dental health state utilities (using VAS), and (3) time trade-off for regular dental check-ups. The percentage of respondents in both groups who were satisfied with chewing function, appearance of teeth, and social function ranged from 23.1 to 42.4%. There were no significant differences between groups A and B in the VAS of decayed, filled, and missing teeth. The VAS of gum bleeding was 42.8 in Group A and 51.3 in Group B (p<0.05). The percentage of persons having a regular dental check-up every three months was 34.1 and 31.3% in Groups A and B respectively. These results suggest that low preference results from lack of opportunity or utilization of dental care in the worksite. Ascertaining the factors involved in patient preference may have significant potential benefits in shared decision-making.

  14. Dental patient preferences and choice in clinical decision-making.

    PubMed

    Fukai, Kakuhiro; Yoshino, Koichi; Ohyama, Atsushi; Takaesu, Yoshinori

    2012-01-01

    In economics, the concept of utility refers to the strength of customer preference. In health care assessment, the visual analogue scale (VAS), the standard gamble, and the time trade-off are used to measure health state utilities. These utility measurements play a key role in promoting shared decision-making in dental care. Individual preference, however, is complex and dynamic. The purpose of this study was to investigate the relationship between patient preference and educational intervention in the field of dental health. The data were collected by distributing questionnaires to employees of two companies in Japan. Participants were aged 18-65 years and consisted of 111 males and 93 females (204 in total). One company (Group A) had a dental program of annual check-ups and health education in the workplace, while the other company (Group B) had no such program. Statistical analyses were performed with the t-test and Chi-square test. The questionnaire items were designed to determine: (1) oral health-related quality of life, (2) dental health state utilities (using VAS), and (3) time trade-off for regular dental check-ups. The percentage of respondents in both groups who were satisfied with chewing function, appearance of teeth, and social function ranged from 23.1 to 42.4%. There were no significant differences between groups A and B in the VAS of decayed, filled, and missing teeth. The VAS of gum bleeding was 42.8 in Group A and 51.3 in Group B (p<0.05). The percentage of persons having a regular dental check-up every three months was 34.1 and 31.3% in Groups A and B respectively. These results suggest that low preference results from lack of opportunity or utilization of dental care in the worksite. Ascertaining the factors involved in patient preference may have significant potential benefits in shared decision-making. PMID:22790334

  15. [Knowledge management system for laboratory work and clinical decision support].

    PubMed

    Inada, Masanori; Sato, Mayumi; Yoneyama, Akiko

    2011-05-01

    This paper discusses a knowledge management system for clinical laboratories. In the clinical laboratory of Toranomon Hospital, we receive about 20 questions relevant to laboratory tests per day from medical doctors or co-medical staff. These questions mostly involve the essence to appropriately accomplish laboratory tests. We have to answer them carefully and suitably because an incorrect answer may cause a medical accident. Up to now, no method has been in place to achieve a rapid response and standardized answers. For this reason, the laboratory staff have responded to various questions based on their individual knowledge. We began to develop a knowledge management system to promote the knowledge of staff working for the laboratory. This system is a type of knowledge base for assisting the work, such as inquiry management, laboratory consultation, process management, and clinical support. It consists of several functions: guiding laboratory test information, managing inquiries from medical staff, reporting results of patient consultation, distributing laboratory staffs notes, and recording guidelines for laboratory medicine. The laboratory test information guide has 2,000 records of medical test information registered in the database with flexible retrieval. The inquiry management tool provides a methos to record all questions, answer easily, and retrieve cases. It helps staff to respond appropriately in a short period of time. The consulting report system treats patients' claims regarding medical tests. The laboratory staffs notes enter a file management system so they can be accessed to aid in clinical support. Knowledge sharing using this function can achieve the transition from individual to organizational learning. Storing guidelines for laboratory medicine will support EBM. Finally, it is expected that this system will support intellectual activity concerning laboratory work and contribute to the practice of knowledge management for clinical work support.

  16. [Knowledge management system for laboratory work and clinical decision support].

    PubMed

    Inada, Masanori; Sato, Mayumi; Yoneyama, Akiko

    2011-05-01

    This paper discusses a knowledge management system for clinical laboratories. In the clinical laboratory of Toranomon Hospital, we receive about 20 questions relevant to laboratory tests per day from medical doctors or co-medical staff. These questions mostly involve the essence to appropriately accomplish laboratory tests. We have to answer them carefully and suitably because an incorrect answer may cause a medical accident. Up to now, no method has been in place to achieve a rapid response and standardized answers. For this reason, the laboratory staff have responded to various questions based on their individual knowledge. We began to develop a knowledge management system to promote the knowledge of staff working for the laboratory. This system is a type of knowledge base for assisting the work, such as inquiry management, laboratory consultation, process management, and clinical support. It consists of several functions: guiding laboratory test information, managing inquiries from medical staff, reporting results of patient consultation, distributing laboratory staffs notes, and recording guidelines for laboratory medicine. The laboratory test information guide has 2,000 records of medical test information registered in the database with flexible retrieval. The inquiry management tool provides a methos to record all questions, answer easily, and retrieve cases. It helps staff to respond appropriately in a short period of time. The consulting report system treats patients' claims regarding medical tests. The laboratory staffs notes enter a file management system so they can be accessed to aid in clinical support. Knowledge sharing using this function can achieve the transition from individual to organizational learning. Storing guidelines for laboratory medicine will support EBM. Finally, it is expected that this system will support intellectual activity concerning laboratory work and contribute to the practice of knowledge management for clinical work support

  17. Advances in clinical analysis 2012.

    PubMed

    Couchman, Lewis; Mills, Graham A

    2013-01-01

    A report on the meeting organized by The Chromatographic Society and the Separation Science Group, Analytical Division of the Royal Society of Chemistry. Over 60 delegates and commercial exhibitors attended this event, held to celebrate the careers of Robert Flanagan and David Perrett, and acknowledge their extensive contributions in the field of clinical analysis. PMID:23330556

  18. 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.

  19. [Do clinical decision models improve the triage of acutely ill children?].

    PubMed

    Berger, Marjolein Y

    2015-01-01

    Acute infection is the most common presentation of children in primary care, with only a few having serious infections. To avoid complications, early recognition and appropriate referral are essential. Clinical decision models have the potential to improve diagnostic decision-making for these serious conditions. Although many models have been developed, few have proven cost-effective. A recent model developed in acutely ill children presenting in Belgian primary care and validated in a new cohort has been shown to adequately identify children that are hospitalised with acute infections. The results are impressive but raise questions about generalisability and cost-effectiveness. In conclusion, clinical decision models appear currently incapable of improving decision-making in acutely ill children. As an alternative, we should consider asking the general practitioner to perform telephone triage.

  20. Framework for securing personal health data in clinical decision support systems.

    PubMed

    Sandell, Protik

    2007-01-01

    If appropriate security mechanisms aren't in place, individuals and groups can get unauthorized access to personal health data residing in clinical decision support systems (CDSS). These concerns are well founded; there has been a dramatic increase in reports of security incidents. The paper provides a framework for securing personal health data in CDSS. The framework breaks down CDSS into data gathering, data management and data delivery functions. It then provides the vulnerabilities that can occur in clinical decision support activities and the measures that need to be taken to protect the data. The framework is applied to protect the confidentiality, integrity and availability of personal health data in a decision support system. Using the framework, project managers and architects can assess the potential risk of unauthorized data access in their decision support system. Moreover they can design systems and procedures to effectively secure personal health data.

  1. Three basic modes for patients' clinical decision-making in China.

    PubMed

    Li, En-Chang; Wang, Zhen; Zhang, Wen-Ying; Zhao, Liang-Yu

    2014-11-01

    In China, there are three basic clinical decision-making modes for patients, namely patients' autonomous decision-making mode, family decision-making mode and patient and family codetermination. They were produced under the unique background of Chinese medicine, Confucian philosophy and law in China. In this paper, the concepts, advantages and disadvantages of these three decision-making modes were analyzed. In addition, some suggestions were put forward for the improvement. The first is that we suggest to establish standards for choosing decision-making modes; the second is to further learn and publicize relevant laws; thirdly, the legal system needs to be further refined; and the last one is to carry out ethical ward round.

  2. Teleconsultation and Clinical Decision Making: a Systematic Review

    PubMed Central

    Deldar, Kolsoum; Bahaadinbeigy, Kambiz; Tara, Seyed Mahmood

    2016-01-01

    Background: The goal of teleconsultation is to omit geographical and functional distance between two or more geographically separated health care providers. The purpose of present study is to review and analyze physician-physician teleconsultations. Method: The PubMed electronic database was searched. The primary search was done on January 2015 and was updated on December 2015. A fetch and tag plan was designed by the researchers using an online Zotero library. Results: 174 full-text articles of 1702 records met inclusion criteria. Teleconsultation for pediatric patients accounts for 14.36 percent of accepted articles. Surgery and general medicine were the most prevalent medical fields in the adults and pediatrics, respectively. Most teleconsultations were inland experiences (no=135), and the USA, Italy and Australia were the three top countries in this group. Non-specialists health care providers/centers were the dominant group who requested teleconsultation (no=130). Real time, store and forward, and hybrid technologies were used in 50, 31, and 16.7 percent of articles, respectively. The teleconsultation were reported to result in change in treatment plan, referral or evacuation rate, change in diagnosis, educational effects, and rapid decision making. Use of structured or semi-structured template had been noticed only in a very few articles. Conclusion: The present study focused on the recent ten years of published articles on physician-physician teleconsultations. Our findings showed that although there are positive impacts of teleconsultation as improving patient management, still have gaps that need to be repaired. PMID:27708494

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

    PubMed

    Yu, Peter Paul

    2015-03-01

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

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

    PubMed

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

    2007-01-01

    Clinical decision support can be employed to increase patient safety and improve workflow efficiencies for physicians and other healthcare providers. Physician input into the design and deployment of clinical decision support systems can increase the utility of the alerts and reduce the likelihood of "alert fatigue." The Hospital for Special Surgery is a 146-bed orthopedic facility that performs approximately 18,000 surgeries a year Efficient work processes are a necessity. The facility began implementing a new electronic health record system in June 2005 and plan to go live in summer 2007. This article reports on some of the clinical decision support rules and alerts being incorporated into the facility's system in the following categories--high-risk, high-frequency scenarios, rules that provide efficiencies and value from the presciber perspective, and rules that relate to patient safety. PMID:17583164

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

    PubMed Central

    Deshpande, Saee; Lambade, Dipti; Chahande, Jayashree

    2015-01-01

    Purpose: Best practice strategies for helping students learn the reasoning skills of problem solving and critical thinking (CT) remain a source of conjecture, particularly with regard to CT. The dental education literature is fundamentally devoid of research on the cognitive components of clinical decision-making. Aim: This study was aimed to develop and evaluate the impact of blended learning module on clinical decision-making skills of dental graduates for planning prosthodontics rehabilitation. Methodology: An interactive teaching module consisting of didactic lectures on clinical decision-making and a computer-assisted case-based treatment planning software was developed Its impact on cognitive knowledge gain in clinical decision-making was evaluated using an assessment involving problem-based multiple choice questions and paper-based case scenarios. Results: Mean test scores were: Pretest (17 ± 1), posttest 1 (21 ± 2) and posttest 2 (43 ± 3). Comparison of mean scores was done with one-way ANOVA test. There was overall significant difference in between mean scores at all the three points (P < 0.001). A pair-wise comparison of mean scores was done with Bonferroni test. The mean difference is significant at the 0.05 level. The pair-wise comparison shows that posttest 2 score is significantly higher than posttest 1 and posttest 1 is significantly higher than pretest that is, pretest 2 > posttest 1 > pretest. Conclusion: Blended teaching methods employing didactic lectures on the clinical decision-making as well as computer assisted case-based learning can be used to improve quality of clinical decision-making in prosthodontic rehabilitation for dental graduates. PMID:26929504

  6. Sensitivity of a Clinical Decision Rule and Early Computed Tomography in Aneurysmal Subarachnoid Hemorrhage

    PubMed Central

    Mark, Dustin G.; Kene, Mamata V.; Udaltsova, Natalia; Vinson, David R.; Ballard, Dustin W.

    2015-01-01

    Introduction Application of a clinical decision rule for subarachnoid hemorrhage, in combination with cranial computed tomography (CT) performed within six hours of ictus (early cranial CT), may be able to reasonably exclude a diagnosis of aneurysmal subarachnoid hemorrhage (aSAH). This study’s objective was to examine the sensitivity of both early cranial CT and a previously validated clinical decision rule among emergency department (ED) patients with aSAH and a normal mental status. Methods Patients were evaluated in the 21 EDs of an integrated health delivery system between January 2007 and June 2013. We identified by chart review a retrospective cohort of patients diagnosed with aSAH in the setting of a normal mental status and performance of early cranial CT. Variables comprising the SAH clinical decision rule (age ≥40, presence of neck pain or stiffness, headache onset with exertion, loss of consciousness at headache onset) were abstracted from the chart and assessed for inter-rater reliability. Results One hundred fifty-five patients with aSAH met study inclusion criteria. The sensitivity of early cranial CT was 95.5% (95% CI [90.9–98.2]). The sensitivity of the SAH clinical decision rule was also 95.5% (95% CI [90.9–98.2]). Since all false negative cases for each diagnostic modality were mutually independent, the combined use of both early cranial CT and the clinical decision rule improved sensitivity to 100% (95% CI [97.6–100.0]). Conclusion Neither early cranial CT nor the SAH clinical decision rule demonstrated ideal sensitivity for aSAH in this retrospective cohort. However, the combination of both strategies might optimize sensitivity for this life-threatening disease. PMID:26587089

  7. Interface design principles for usable decision support: a targeted review of best practices for clinical prescribing interventions.

    PubMed

    Horsky, Jan; Schiff, Gordon D; Johnston, Douglas; Mercincavage, Lauren; Bell, Douglas; Middleton, Blackford

    2012-12-01

    Developing effective clinical decision support (CDS) systems for the highly complex and dynamic domain of clinical medicine is a serious challenge for designers. Poor usability is one of the core barriers to adoption and a deterrent to its routine use. We reviewed reports describing system implementation efforts and collected best available design conventions, procedures, practices and lessons learned in order to provide developers a short compendium of design goals and recommended principles. This targeted review is focused on CDS related to medication prescribing. Published reports suggest that important principles include consistency of design concepts across networked systems, use of appropriate visual representation of clinical data, use of controlled terminology, presenting advice at the time and place of decision making and matching the most appropriate CDS interventions to clinical goals. Specificity and contextual relevance can be increased by periodic review of trigger rules, analysis of performance logs and maintenance of accurate allergy, problem and medication lists in health records in order to help avoid excessive alerting. Developers need to adopt design practices that include user-centered, iterative design and common standards based on human-computer interaction (HCI) research methods rooted in ethnography and cognitive science. Suggestions outlined in this report may help clarify the goals of optimal CDS design but larger national initiatives are needed for systematic application of human factors in health information technology (HIT) development. Appropriate design strategies are essential for developing meaningful decision support systems that meet the grand challenges of high-quality healthcare.

  8. 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.

  9. Use of multicriteria decision analysis to address conservation conflicts.

    PubMed

    Davies, A L; Bryce, R; Redpath, S M

    2013-10-01

    Conservation conflicts are increasing on a global scale and instruments for reconciling competing interests are urgently needed. Multicriteria decision analysis (MCDA) is a structured, decision-support process that can facilitate dialogue between groups with differing interests and incorporate human and environmental dimensions of conflict. MCDA is a structured and transparent method of breaking down complex problems and incorporating multiple objectives. The value of this process for addressing major challenges in conservation conflict management is that MCDA helps in setting realistic goals; entails a transparent decision-making process; and addresses mistrust, differing world views, cross-scale issues, patchy or contested information, and inflexible legislative tools. Overall we believe MCDA provides a valuable decision-support tool, particularly for increasing awareness of the effects of particular values and choices for working toward negotiated compromise, although an awareness of the effect of methodological choices and the limitations of the method is vital before applying it in conflict situations.

  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. Comparison of Decision-Assist and Clinical Judgment of Experts for Prediction of Lifesaving Interventions.

    PubMed

    Mackenzie, Colin F; Gao, Cheng; Hu, Peter F; Anazodo, Amechi; Chen, Hegang; Dinardo, Theresa; Imle, P Cristina; Hartsky, Lauren; Stephens, Christopher; Menaker, Jay; Fouche, Yvette; Murdock, Karen; Galvagno, Samuel; Alcorta, Richard; Shackelford, Stacy

    2015-03-01

    Early recognition of hemorrhage during the initial resuscitation of injured patients is associated with improved survival in both civilian and military casualties. We tested a transfusion and lifesaving intervention (LSI) prediction algorithm in comparison with clinical judgment of expert trauma care providers. We collected 15 min of pulse oximeter photopletysmograph waveforms and extracted features to predict LSIs. We compared this with clinical judgment of LSIs by individual categories of prehospital providers, nurses, and physicians and a combined judgment of all three providers using the Area Under Receiver Operating Curve (AUROC). We obtained clinical judgment of need for LSI from 405 expert clinicians in135 trauma patients. The pulse oximeter algorithm predicted transfusion within 6 h (AUROC, 0.92; P < 0.003) more accurately than either physicians or prehospital providers and as accurately as nurses (AUROC, 0.76; P = 0.07). For prediction of surgical procedures, the algorithm was as accurate as the three categories of clinicians. For prediction of fluid bolus, the diagnostic algorithm (AUROC, 0.9) was significantly more accurate than prehospital providers (AUROC, 0.62; P = 0.02) and nurses (AUROC, 0.57; P = 0.04) and as accurate as physicians (AUROC, 0.71; P = 0.06). Prediction of intubation by the algorithm (AUROC, 0.92) was as accurate as each of the three categories of clinicians. The algorithm was more accurate (P < 0.03) for blood and fluid prediction than the combined clinical judgment of all three providers but no different from the clinicians in the prediction of surgery (P = 0.7) or intubation (P = 0.8). Automated analysis of 15 min of pulse oximeter waveforms predicts the need for LSIs during initial trauma resuscitation as accurately as judgment of expert trauma clinicians. For prediction of emergency transfusion and fluid bolus, pulse oximetry features were more accurate than these experts. Such automated decision support could assist

  12. Comparison of Decision-Assist and Clinical Judgment of Experts for Prediction of Lifesaving Interventions.

    PubMed

    Mackenzie, Colin F; Gao, Cheng; Hu, Peter F; Anazodo, Amechi; Chen, Hegang; Dinardo, Theresa; Imle, P Cristina; Hartsky, Lauren; Stephens, Christopher; Menaker, Jay; Fouche, Yvette; Murdock, Karen; Galvagno, Samuel; Alcorta, Richard; Shackelford, Stacy

    2015-03-01

    Early recognition of hemorrhage during the initial resuscitation of injured patients is associated with improved survival in both civilian and military casualties. We tested a transfusion and lifesaving intervention (LSI) prediction algorithm in comparison with clinical judgment of expert trauma care providers. We collected 15 min of pulse oximeter photopletysmograph waveforms and extracted features to predict LSIs. We compared this with clinical judgment of LSIs by individual categories of prehospital providers, nurses, and physicians and a combined judgment of all three providers using the Area Under Receiver Operating Curve (AUROC). We obtained clinical judgment of need for LSI from 405 expert clinicians in135 trauma patients. The pulse oximeter algorithm predicted transfusion within 6 h (AUROC, 0.92; P < 0.003) more accurately than either physicians or prehospital providers and as accurately as nurses (AUROC, 0.76; P = 0.07). For prediction of surgical procedures, the algorithm was as accurate as the three categories of clinicians. For prediction of fluid bolus, the diagnostic algorithm (AUROC, 0.9) was significantly more accurate than prehospital providers (AUROC, 0.62; P = 0.02) and nurses (AUROC, 0.57; P = 0.04) and as accurate as physicians (AUROC, 0.71; P = 0.06). Prediction of intubation by the algorithm (AUROC, 0.92) was as accurate as each of the three categories of clinicians. The algorithm was more accurate (P < 0.03) for blood and fluid prediction than the combined clinical judgment of all three providers but no different from the clinicians in the prediction of surgery (P = 0.7) or intubation (P = 0.8). Automated analysis of 15 min of pulse oximeter waveforms predicts the need for LSIs during initial trauma resuscitation as accurately as judgment of expert trauma clinicians. For prediction of emergency transfusion and fluid bolus, pulse oximetry features were more accurate than these experts. Such automated decision support could assist

  13. The Effect of Level of Patient Acuity, Critical Care Experience, and ACLS Certification on Clinical Decision Making: Implications for Computer Decision Support Systems

    PubMed Central

    Henry, Suzanne Bakken

    1990-01-01

    This study examined the effect of patient acuity, critical care experience, and ACLS certification on clinical decision making. Each subject (N=68) completed two computerized clinical simulations. Ventricular tachycardia (VT) represented the high acuity situation and atrial flutter (AF) the lower acuity situation. Clinical decision making was measured by proficiency score, patient outcome (cure/die), and amount of data collected. In the AF simulation, proficiency scores were higher (p=.000), more dysrhythmias were cured (p<.005), and more data were collected (p=.040) than in the VT simulation. Experienced and inexperienced nurses did not differ on proficiency score, however, inexperienced nurses collected more data (p=.048) and cured fewer atrial flutter simulations (p=.04). ACLS certified nurses had higher proficiency scores (p=.033) and collected less data (p=.048). Clinical decision making on two simulations was affected by patient acuity, critical care experience, and ACLS certification. These findings have implications for the design and implementation of clinical decision support systems.

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

    PubMed Central

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

    2015-01-01

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

  15. [Clinical research XXI. From the clinical judgment to survival analysis].

    PubMed

    Rivas-Ruiz, Rodolfo; Pérez-Rodríguez, Marcela; Palacios, Lino; Talavera, Juan O

    2014-01-01

    Decision making in health care implies knowledge of the clinical course of the disease. Knowing the course allows us to estimate the likelihood of occurrence of a phenomenon at a given time or its duration. Within the statistical models that allow us to have a summary measure to estimate the time of occurrence of a phenomenon in a given population are the linear regression (the outcome variable is continuous and normally distributed -time to the occurrence of the event-), logistic regression (outcome variable is dichotomous, and it is evaluated at one single interval), and survival curves (outcome event is dichotomous, and it can be evaluated at multiple intervals). The first reference we have of this type of analysis is the work of the astronomer Edmond Halley, an English physicist and mathematician, famous for the calculation of the appearance of the comet orbit, recognized as the first periodic comet (1P/Halley's Comet). Halley also contributed in the area of health to estimate the mortality rate for a Polish population. The survival curve allows us to estimate the probability of an event occurring at different intervals. Also, it leds us to estimate the median survival time of any phenomenon of interest (although the used term is survival, the outcome does not need to be death, it may be the occurrence of any other event).

  16. [Clinical research XXI. From the clinical judgment to survival analysis].

    PubMed

    Rivas-Ruiz, Rodolfo; Pérez-Rodríguez, Marcela; Palacios, Lino; Talavera, Juan O

    2014-01-01

    Decision making in health care implies knowledge of the clinical course of the disease. Knowing the course allows us to estimate the likelihood of occurrence of a phenomenon at a given time or its duration. Within the statistical models that allow us to have a summary measure to estimate the time of occurrence of a phenomenon in a given population are the linear regression (the outcome variable is continuous and normally distributed -time to the occurrence of the event-), logistic regression (outcome variable is dichotomous, and it is evaluated at one single interval), and survival curves (outcome event is dichotomous, and it can be evaluated at multiple intervals). The first reference we have of this type of analysis is the work of the astronomer Edmond Halley, an English physicist and mathematician, famous for the calculation of the appearance of the comet orbit, recognized as the first periodic comet (1P/Halley's Comet). Halley also contributed in the area of health to estimate the mortality rate for a Polish population. The survival curve allows us to estimate the probability of an event occurring at different intervals. Also, it leds us to estimate the median survival time of any phenomenon of interest (although the used term is survival, the outcome does not need to be death, it may be the occurrence of any other event). PMID:24878091

  17. 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.

  18. Clinical decision-making after endodontic instrument fracture.

    PubMed

    McGuigan, M B; Louca, C; Duncan, H F

    2013-04-01

    When a file fractures during root canal treatment there are several treatment options available to the clinician. The definitive management should be based on a thorough knowledge of the success rates of each treatment option, balanced against potential risks of removal or file retention. Although integration of modern techniques into endodontic practice has improved the clinician's ability to remove fractured files, removal may not always be possible or even desirable. The aim of the third and final review in this series was to analyse the literature with regard to the management of fractured files. Analysis of the literature demonstrated that the presence of a fractured instrument need not reduce the prognosis if the case is well treated and there is no evidence of apical disease. Therefore, in cases without apical disease removal of the file may not be necessary and retention or bypass should be considered. If apical disease is present, file fracture significantly reduces prognosis indicating a greater need to attempt file removal or bypass. A plethora of different methods have been employed to remove fractured instruments and although successful, these techniques usually require the use of the operating microscope and specialist care. Removal of a fractured file is not without considerable risk, particularly in the apical regions of the root canal, therefore, leaving the fragment in situ should be considered if referral is not possible. Finally, it is imperative that the patient is informed (accompanied by appropriate record keeping) if instrument fracture occurs during treatment or if a fractured file is discovered during a routine radiographic examination. PMID:23619858

  19. Paying more wisely: effects of payment reforms on evidence-based clinical decision-making.

    PubMed

    Lake, Timothy K; Rich, Eugene C; Valenzano, Christal Stone; Maxfield, Myles M

    2013-05-01

    This article reviews the recent research, policy and conceptual literature on the effects of payment policy reforms on evidence-based clinical decision-making by physicians at the point-of-care. Payment reforms include recalibration of existing fee structures in fee-for-service, pay-for-quality, episode-based bundled payment and global payments. The advantages and disadvantages of these reforms are considered in terms of their effects on the use of evidence in clinical decisions made by physicians and their patients related to the diagnosis, testing, treatment and management of disease. The article concludes with a recommended pathway forward for improving current payment incentives to better support evidence-based decision-making.

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

    ERIC Educational Resources Information Center

    Kunisch, Joseph Martin

    2012-01-01

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

  1. Evaluating the Effectiveness of Nurse-Focused Computerized Clinical Decision Support on Urinary Catheter Practice Guidelines

    ERIC Educational Resources Information Center

    Lang, Robin Lynn Neal

    2012-01-01

    A growing national emphasis has been placed on health information technology (HIT) with robust computerized clinical decision support (CCDS) integration into health care delivery. Catheter-associated urinary tract infection is the most frequent health care-associated infection in the United States and is associated with high cost, high volumes and…

  2. The Contribution of Polysyllabic Words in Clinical Decision Making about Children's Speech

    ERIC Educational Resources Information Center

    James, Deborah G. H.; van Doorn, Jan; McLeod, Sharynne

    2008-01-01

    Poor polysyllabic word (PSW) production seems to mark paediatric speech impairment as well as impairment in language, literacy and phonological processing. As impairment in these domains may only manifest in PSWs, PSW production may provide unique information that is often excluded from clinical decision making because insufficient PSWs are…

  3. 78 FR 35937 - Food and Drug Administration Decisions for Investigational Device Exemption Clinical...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-06-14

    ... HUMAN SERVICES Food and Drug Administration Food and Drug Administration Decisions for Investigational Device Exemption Clinical Investigations; Draft Guidance for Industry and Food and Drug Administration... revised and is being reissued for comment because the Food and Drug Administration Safety and...

  4. Cost-Effectiveness of an Electronic Medical Record Based Clinical Decision Support System

    PubMed Central

    Gilmer, Todd P; O'Connor, Patrick J; Sperl-Hillen, JoAnn M; Rush, William A; Johnson, Paul E; Amundson, Gerald H; Asche, Stephen E; Ekstrom, Heidi L

    2012-01-01

    Background and Objective Medical groups have invested billions of dollars in electronic medical records (EMRs), but few studies have examined the cost-effectiveness of EMR-based clinical decision support (CDS). This study examined the cost-effectiveness of EMR-based CDS for adults with diabetes from the perspective of the health care system. Data Sources/Setting Clinical outcome and cost data from a randomized clinical trial of EMR-based CDS were used as inputs into a diabetes simulation model. The simulation cohort included 1,092 patients with diabetes with A1c above goal at baseline. Study Design The United Kingdom Prospective Diabetes Study Outcomes Model, a validated simulation model of diabetes, was used to evaluate remaining life years, quality-adjusted life years (QALYs), and health care costs over patient lifetimes (40-year time horizon) from the health system perspective. Principal Findings Patients in the intervention group had significantly lowered A1c (0.26 percent, p = .014) relative to patients in the control arm. Intervention costs were $120 (SE = 45) per patient in the first year and $76 (SE = 45) per patient in the following years. In the base case analysis, EMR-based CDS increased lifetime QALYs by 0.04 (SE = 0.01) and increased lifetime costs by $112 (SE = 660), resulting in an incremental cost-effectiveness ratio of $3,017 per QALY. The cost-effectiveness of EMR-based CDS persisted in one-way, two-way, and probabilistic sensitivity analyses. Conclusions Widespread adoption of sophisticated EMR-based CDS has the potential to modestly improve the quality of care for patients with chronic conditions without substantially increasing costs to the health care system. PMID:22578085

  5. Philosophical Foundations for Curriculum Decision: A Reflective Analysis

    ERIC Educational Resources Information Center

    Belbase, Shashidhar

    2011-01-01

    This paper discusses the author's curriculum experiences under different philosophical, epistemological and theoretical backdrops. The analysis of different perspectives bridges epistemological and philosophical/theoretical lenses to my understanding of curriculum and different curricular decisions. This praxeological experience as a student and…

  6. Child Custody Decisions: Content Analysis of a Judicial Survey.

    ERIC Educational Resources Information Center

    Settle, Shirley A; Lowery, Carol R.

    1982-01-01

    Surveyed judges and trial commissioners (N=80) regarding child custody decisions in divorce. The content analysis described the responents' comments which clarified their reasons for attaching greater or lesser importance to a particular consideration or the method using in assessing a particular consideration during a court proceeding. (JAC)

  7. Decision framework for technology choice. Volume 2: decision analysis user's manual. [TCM computer code

    SciTech Connect

    Sicherman, A.; Keeney, R.L.

    1982-03-01

    A computer program was developed to aid decision makers in choosing among alternatives. It facilitiates the implementation of the decision analysis approach to multiobjective decision-making problems. The program's main functions are to store the information and perform all the necessary computations required by the approach. The program is designed so that only a few basic commands need to be understood in order to use it effectively. The style of input can be both batch and interactively oriented. Detailed specification of preferences and alternatives is usually done in batch mode while sensitivity analysis can be performed interactively. The output consists of ranking, preference and alternative information displays. The program is quite general and should be applicable to a wide variety of problems. The code allows for an interface to user supplied models when that is desirable. It is designed to run on most computer systems without or with very minor system-specific modifications. This report presents a user's manual for the program that includes a simple illustrative example.

  8. From Value Assessment to Value Cocreation: Informing Clinical Decision-Making with Medical Claims Data.

    PubMed

    Thompson, Steven; Varvel, Stephen; Sasinowski, Maciek; Burke, James P

    2016-09-01

    Big data and advances in analytical processes represent an opportunity for the healthcare industry to make better evidence-based decisions on the value generated by various tests, procedures, and interventions. Value-based reimbursement is the process of identifying and compensating healthcare providers based on whether their services improve quality of care without increasing cost of care or maintain quality of care while decreasing costs. In this article, we motivate and illustrate the potential opportunities for payers and providers to collaborate and evaluate the clinical and economic efficacy of different healthcare services. We conduct a case study of a firm that offers advanced biomarker and disease state management services for cardiovascular and cardiometabolic conditions. A value-based analysis that comprised a retrospective case/control cohort design was conducted, and claims data for over 7000 subjects who received these services were compared to a matched control cohort. Study subjects were commercial and Medicare Advantage enrollees with evidence of CHD, diabetes, or a related condition. Analysis of medical claims data showed a lower proportion of patients who received biomarker testing and disease state management services experienced a MI (p < 0.01) or diabetic complications (p < 0.001). No significant increase in cost of care was found between the two cohorts. Our results illustrate the opportunity healthcare payers such as Medicare and commercial insurance companies have in terms of identifying value-creating healthcare interventions. However, payers and providers also need to pursue system integration efforts to further automate the identification and dissemination of clinically and economically efficacious treatment plans to ensure at-risk patients receive the treatments and interventions that will benefit them the most. PMID:27642718

  9. From Value Assessment to Value Cocreation: Informing Clinical Decision-Making with Medical Claims Data.

    PubMed

    Thompson, Steven; Varvel, Stephen; Sasinowski, Maciek; Burke, James P

    2016-09-01

    Big data and advances in analytical processes represent an opportunity for the healthcare industry to make better evidence-based decisions on the value generated by various tests, procedures, and interventions. Value-based reimbursement is the process of identifying and compensating healthcare providers based on whether their services improve quality of care without increasing cost of care or maintain quality of care while decreasing costs. In this article, we motivate and illustrate the potential opportunities for payers and providers to collaborate and evaluate the clinical and economic efficacy of different healthcare services. We conduct a case study of a firm that offers advanced biomarker and disease state management services for cardiovascular and cardiometabolic conditions. A value-based analysis that comprised a retrospective case/control cohort design was conducted, and claims data for over 7000 subjects who received these services were compared to a matched control cohort. Study subjects were commercial and Medicare Advantage enrollees with evidence of CHD, diabetes, or a related condition. Analysis of medical claims data showed a lower proportion of patients who received biomarker testing and disease state management services experienced a MI (p < 0.01) or diabetic complications (p < 0.001). No significant increase in cost of care was found between the two cohorts. Our results illustrate the opportunity healthcare payers such as Medicare and commercial insurance companies have in terms of identifying value-creating healthcare interventions. However, payers and providers also need to pursue system integration efforts to further automate the identification and dissemination of clinically and economically efficacious treatment plans to ensure at-risk patients receive the treatments and interventions that will benefit them the most.

  10. Exposure models for the prior distribution in bayesian decision analysis for occupational hygiene decision making.

    PubMed

    Lee, Eun Gyung; Kim, Seung Won; Feigley, Charles E; Harper, Martin

    2013-01-01

    This study introduces two semi-quantitative methods, Structured Subjective Assessment (SSA) and Control of Substances Hazardous to Health (COSHH) Essentials, in conjunction with two-dimensional Monte Carlo simulations for determining prior probabilities. Prior distribution using expert judgment was included for comparison. Practical applications of the proposed methods were demonstrated using personal exposure measurements of isoamyl acetate in an electronics manufacturing facility and of isopropanol in a printing shop. Applicability of these methods in real workplaces was discussed based on the advantages and disadvantages of each method. Although these methods could not be completely independent of expert judgments, this study demonstrated a methodological improvement in the estimation of the prior distribution for the Bayesian decision analysis tool. The proposed methods provide a logical basis for the decision process by considering determinants of worker exposure. PMID:23252451

  11. Exposure models for the prior distribution in bayesian decision analysis for occupational hygiene decision making.

    PubMed

    Lee, Eun Gyung; Kim, Seung Won; Feigley, Charles E; Harper, Martin

    2013-01-01

    This study introduces two semi-quantitative methods, Structured Subjective Assessment (SSA) and Control of Substances Hazardous to Health (COSHH) Essentials, in conjunction with two-dimensional Monte Carlo simulations for determining prior probabilities. Prior distribution using expert judgment was included for comparison. Practical applications of the proposed methods were demonstrated using personal exposure measurements of isoamyl acetate in an electronics manufacturing facility and of isopropanol in a printing shop. Applicability of these methods in real workplaces was discussed based on the advantages and disadvantages of each method. Although these methods could not be completely independent of expert judgments, this study demonstrated a methodological improvement in the estimation of the prior distribution for the Bayesian decision analysis tool. The proposed methods provide a logical basis for the decision process by considering determinants of worker exposure.

  12. Disciplined decision making in an interdisciplinary environment: some implications for clinical applications of statistical process control.

    PubMed Central

    Hantula, D A

    1995-01-01

    This paper explores some of the implications the statistical process control (SPC) methodology described by Pfadt and Wheeler (1995) may have for analyzing more complex performances and contingencies in human services or health care environments at an organizational level. Service delivery usually occurs in an organizational system that is characterized by functional structures, high levels of professionalism, subunit optimization, and organizational suboptimization. By providing a standard set of criteria and decision rules, SPC may provide a common interface for data-based decision making, may bring decision making under the control of the contigencies that are established by these rules rather than the immediate contingencies of data fluctuation, and may attenuate escalation of failing treatments. SPC is culturally consistent with behavior analysis, sharing an emphasis on data-based decisions, measurement over time, and graphic analysis of data, as well as a systemic view of organizations. PMID:7592155

  13. Accommodating complexity and human behaviors in decision analysis.

    SciTech Connect

    Backus, George A.; Siirola, John Daniel; Schoenwald, David Alan; Strip, David R.; Hirsch, Gary B.; Bastian, Mark S.; Braithwaite, Karl R.; Homer, Jack

    2007-11-01

    This is the final report for a LDRD effort to address human behavior in decision support systems. One sister LDRD effort reports the extension of this work to include actual human choices and additional simulation analyses. Another provides the background for this effort and the programmatic directions for future work. This specific effort considered the feasibility of five aspects of model development required for analysis viability. To avoid the use of classified information, healthcare decisions and the system embedding them became the illustrative example for assessment.

  14. Risk Analysis and Decision Making FY 2013 Milestone Report

    SciTech Connect

    Engel, David W.; Dalton, Angela C.; Dale, Crystal; Jones, Edward; Thompson, J.

    2013-06-01

    Risk analysis and decision making is one of the critical objectives of CCSI, which seeks to use information from science-based models with quantified uncertainty to inform decision makers who are making large capital investments. The goal of this task is to develop tools and capabilities to facilitate the development of risk models tailored for carbon capture technologies, quantify the uncertainty of model predictions, and estimate the technical and financial risks associated with the system. This effort aims to reduce costs by identifying smarter demonstrations, which could accelerate development and deployment of the technology by several years.

  15. A qualitative analysis of EHR clinical document synthesis by clinicians.

    PubMed

    Farri, Oladimeji; Pieckiewicz, David S; Rahman, Ahmed S; Adam, Terrence J; Pakhomov, Serguei V; Melton, Genevieve B

    2012-01-01

    Clinicians utilize electronic health record (EHR) systems during time-constrained patient encounters where large amounts of clinical text must be synthesized at the point of care. Qualitative methods may be an effective approach for uncovering cognitive processes associated with the synthesis of clinical documents within EHR systems. We utilized a think-aloud protocol and content analysis with the goal of understanding cognitive processes and barriers involved as medical interns synthesized patient clinical documents in an EHR system to accomplish routine clinical tasks. Overall, interns established correlations of significance and meaning between problem, symptom and treatment concepts to inform hypotheses generation and clinical decision-making. Barriers identified with synthesizing EHR documents include difficulty searching for patient data, poor readability, redundancy, and unfamiliar specialized terms. Our study can inform recommendations for future designs of EHR clinical document user interfaces to aid clinicians in providing improved patient care. PMID:23304398

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

    PubMed

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

    2015-01-01

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

  17. Design and application of a generic clinical decision support system for multiscale data.

    PubMed

    Mattila, Jussi; Koikkalainen, Juha; Virkki, Arho; van Gils, Mark; Lötjönen, Jyrki

    2012-01-01

    Medical research and clinical practice are currently being redefined by the constantly increasing amounts of multiscale patient data. New methods are needed to translate them into knowledge that is applicable in healthcare. Multiscale modeling has emerged as a way to describe systems that are the source of experimental data. Usually, a multiscale model is built by combining distinct models of several scales, integrating, e.g., genetic, molecular, structural, and neuropsychological models into a composite representation. We present a novel generic clinical decision support system, which models a patient's disease state statistically from heterogeneous multiscale data. Its goal is to aid in diagnostic work by analyzing all available patient data and highlighting the relevant information to the clinician. The system is evaluated by applying it to several medical datasets and demonstrated by implementing a novel clinical decision support tool for early prediction of Alzheimer's disease.

  18. Workshop on using natural language processing applications for enhancing clinical decision making: an executive summary

    PubMed Central

    Pai, Vinay M; Rodgers, Mary; Conroy, Richard; Luo, James; Zhou, Ruixia; Seto, Belinda

    2014-01-01

    In April 2012, the National Institutes of Health organized a two-day workshop entitled ‘Natural Language Processing: State of the Art, Future Directions and Applications for Enhancing Clinical Decision-Making’ (NLP-CDS). This report is a summary of the discussions during the second day of the workshop. Collectively, the workshop presenters and participants emphasized the need for unstructured clinical notes to be included in the decision making workflow and the need for individualized longitudinal data tracking. The workshop also discussed the need to: (1) combine evidence-based literature and patient records with machine-learning and prediction models; (2) provide trusted and reproducible clinical advice; (3) prioritize evidence and test results; and (4) engage healthcare professionals, caregivers, and patients. The overall consensus of the NLP-CDS workshop was that there are promising opportunities for NLP and CDS to deliver cognitive support for healthcare professionals, caregivers, and patients. PMID:23921193

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

    PubMed

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

    2009-01-01

    There are two essential reasons for the slow progress in the acceptance of clinical case retrieval and similarity search-based decision support systems; the especial complexity of clinical data making it difficult to define a meaningful and effective distance function on them and the lack of transparency and explanation ability in many existing clinical case retrieval decision support systems. In this paper, we try to address these two problems by introducing a novel technique for visualizing inter-patient similarity based on a node-link representation with neighborhood graphs and by considering two techniques for learning discriminative distance function that help to combine the power of strong "black box" learners with the transparency of case retrieval and nearest neighbor classification. PMID:19964399

  20. [The impact of guidelines, standards and economic restrictions on clinical decision-making processes].

    PubMed

    Linden, Michael

    2004-05-01

    Guidelines aim at improving clinical decision-making. Contrary to textbooks and reviews that want to improve medical knowledge, guidelines try to influence medical behaviour. Scientific models of clinical decision-making such as the action theory and empirical data on the effects of guidelines suggest that guidelines will not always reach their goals but can instead even lead to a deterioration in the quality of medical care. Therefore there is a need for controlled clinical trials to investigate whether guideline-exposed physicians yield better patient outcomes than guideline-naïve physicians. Guidelines should only be regarded as evidence-based if their positive effects have been empirically demonstrated. PMID:15250387

  1. The potential for meta-analysis to support decision analysis in ecology.

    PubMed

    Mengersen, Kerrie; MacNeil, M Aaron; Caley, M Julian

    2015-06-01

    Meta-analysis and decision analysis are underpinned by well-developed methods that are commonly applied to a variety of problems and disciplines. While these two fields have been closely linked in some disciplines such as medicine, comparatively little attention has been paid to the potential benefits of linking them in ecology, despite reasonable expectations that benefits would be derived from doing so. Meta-analysis combines information from multiple studies to provide more accurate parameter estimates and to reduce the uncertainty surrounding them. Decision analysis involves selecting among alternative choices using statistical information that helps to shed light on the uncertainties involved. By linking meta-analysis to decision analysis, improved decisions can be made, with quantification of the costs and benefits of alternate decisions supported by a greater density of information. Here, we briefly review concepts of both meta-analysis and decision analysis, illustrating the natural linkage between them and the benefits from explicitly linking one to the other. We discuss some examples in which this linkage has been exploited in the medical arena and how improvements in precision and reduction of structural uncertainty inherent in a meta-analysis can provide substantive improvements to decision analysis outcomes by reducing uncertainty in expected loss and maximising information from across studies. We then argue that these significant benefits could be translated to ecology, in particular to the problem of making optimal ecological decisions in the face of uncertainty.

  2. What can decision analysis do for invasive species management?

    PubMed

    Maguire, Lynn A

    2004-08-01

    Decisions about management of invasive species are difficult for all the reasons typically addressed by multiattribute decision analysis: uncertain outcomes, multiple and conflicting objectives, and many interested parties with differing views on both facts and values. This article illustrates how the tools of multiattribute analysis can improve management of invasive species, with an emphasis on making explicit the social values and preferences that must inform invasive species management. Risk assessment protocols developed previously for invasive species management typically suffer from two interacting flaws: (1) separating risk assessment from risk management, thus disrupting essential connections between the social values at stake in invasive species decisions and the scientific knowledge necessary to predict the likely impacts of management actions, and (2) relying on expert judgment about risk framed in qualitative and value-laden terms, inadvertently mixing the expert's judgment about what is likely to happen with personal preferences. Using the values structuring and probability-modeling elements of formal decision analysis can remedy these difficulties and make invasive species management responsive to both good science and public values. The management of feral pigs in Hawaiian ecosystems illustrates the need for such an integrated approach.

  3. What can decision analysis do for invasive species management?

    PubMed

    Maguire, Lynn A

    2004-08-01

    Decisions about management of invasive species are difficult for all the reasons typically addressed by multiattribute decision analysis: uncertain outcomes, multiple and conflicting objectives, and many interested parties with differing views on both facts and values. This article illustrates how the tools of multiattribute analysis can improve management of invasive species, with an emphasis on making explicit the social values and preferences that must inform invasive species management. Risk assessment protocols developed previously for invasive species management typically suffer from two interacting flaws: (1) separating risk assessment from risk management, thus disrupting essential connections between the social values at stake in invasive species decisions and the scientific knowledge necessary to predict the likely impacts of management actions, and (2) relying on expert judgment about risk framed in qualitative and value-laden terms, inadvertently mixing the expert's judgment about what is likely to happen with personal preferences. Using the values structuring and probability-modeling elements of formal decision analysis can remedy these difficulties and make invasive species management responsive to both good science and public values. The management of feral pigs in Hawaiian ecosystems illustrates the need for such an integrated approach. PMID:15357805

  4. The influence of actuarial risk assessment in clinical judgments and tribunal decisions about mentally disordered offenders in maximum security.

    PubMed

    Hilton, N Z; Simmons, J L

    2001-08-01

    Research has shown that actuarial assessments of violence risk are consistently more accurate than unaided judgments by clinicians, and it has been suggested that the availability of actuarial instruments will improve forensic decision making. This study examined clinical judgments and autonomous review tribunal decisions to detain forensic patients in maximum security. Variables included the availability of an actuarial risk report at the time of decision making, patient characteristics and history, and clinical presentation over the previous year. Detained and transferred patients did not differ in their actuarial risk of violent recidivism. The best predictor of tribunal decision was the senior clinician's testimony. There was also no significant association between the actuarial risk score and clinicians' opinions. Whether the actuarial report was available at the time of decision making did not alter the statistical model of either clinical judgments or tribunal decisions. Implications for the use of actuarial risk assessment in forensic decision making are discussed.

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

    PubMed

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

    2015-10-01

    The purpose of this article is to provide policy guidance on how to assess the capacity of minor adolescents for autonomous decision-making without a third party authorization, in the field of clinical care. In June 2014, a two-day meeting gathered 20 professionals from all continents, working in the field of adolescent medicine, neurosciences, developmental and clinical psychology, sociology, ethics, and law. Formal presentations and discussions were based on a literature search and the participants' experience. The assessment of adolescent decision-making capacity includes the following: (1) a review of the legal context consistent with the principles of the Convention on the Rights of the Child; (2) an empathetic relationship between the adolescent and the health care professional/team; (3) the respect of the adolescent's developmental stage and capacities; (4) the inclusion, if relevant, of relatives, peers, teachers, or social and mental health providers with the adolescent's consent; (5) the control of coercion and other social forces that influence decision-making; and (6) a deliberative stepwise appraisal of the adolescent's decision-making process. This stepwise approach, already used among adults with psychiatric disorders, includes understanding the different facets of the given situation, reasoning on the involved issues, appreciating the outcomes linked with the decision(s), and expressing a choice. Contextual and psychosocial factors play pivotal roles in the assessment of adolescents' decision-making capacity. The evaluation must be guided by a well-established procedure, and health professionals should be trained accordingly. These proposals are the first to have been developed by a multicultural, multidisciplinary expert panel. PMID:26281798

  6. Introducing pharmacogenetic testing with clinical decision support into primary care: a feasibility study

    PubMed Central

    Dawes, Martin; Aloise, Martin N.; Ang, J. Sidney; Cullis, Pieter; Dawes, Diana; Fraser, Robert; Liknaitzky, Gideon; Paterson, Andrea; Stanley, Paul; Suarez-Gonzalez, Adriana; Katzov-Eckert, Hagit

    2016-01-01

    Background: Inappropriate prescribing increases patient illness and death owing to adverse drug events. The inclusion of genetic information into primary care medication practices is one solution. Our aim was to assess the ability to obtain and genotype saliva samples and to determine the levels of use of a decision support tool that creates medication options adjusted for patient characteristics, drug-drug interactions and pharmacogenetics. Methods: We conducted a cohort study in 6 primary care settings (5 family practices and 1 pharmacy), enrolling 191 adults with at least 1 of 10 common diseases. Saliva samples were obtained in the physician's office or pharmacy and sent to our laboratory, where DNA was extracted and genotyped and reports were generated. The reports were sent directly to the family physician/pharmacist and linked to an evidence-based prescribing decision support system. The primary outcome was ability to obtain and genotype samples. The secondary outcomes were yield and purity of DNA samples, ability to link results to decision support software and use of the decision support software. Results: Genotyping resulted in linking of 189 patients (99%) with pharmacogenetic reports to the decision support program. A total of 96.8% of samples had at least 1 actionable genotype for medications included in the decision support system. The medication support system was used by the physicians and pharmacists 236 times over 3 months. Interpretation: Physicians and pharmacists can collect saliva samples of sufficient quantity and quality for DNA extraction, purification and genotyping. A clinical decision support system with integrated data from pharmacogenetic tests may enable personalized prescribing within primary care. Trial registration: ClinicalTrials.gov, NCT02383290. PMID:27730116

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

    PubMed

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

    2016-09-01

    Clinical errors occur in the psychotherapy decision-making process whenever a less-than-optimal treatment or approach is chosen when working with clients. A less-than-optimal approach may be one that a client is unwilling to try or fully invest in based on his/her expectations and preferences, or one that may have little chance of success based on contraindications and/or limited research support. The and the models are two decision-making models that are frequently used within psychology, but both are associated with an increased likelihood of errors in the treatment decision-making process. In particular, these models fail to integrate all three components of the definition of evidence-based practice in psychology (American Psychological Association, 2006). In this article we describe both models and provide examples of clinical errors that can occur in each. We then introduce the shared decision-making model as an alternative that is less prone to clinical errors. (PsycINFO Database Record PMID:27505457

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed Central

    Urquhart, C J; Hepworth, J B

    1996-01-01

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

  10. Decerns: A framework for multi-criteria decision analysis

    DOE PAGES

    Yatsalo, Boris; Didenko, Vladimir; Gritsyuk, Sergey; Sullivan, Terry

    2015-02-27

    A new framework, Decerns, for multicriteria decision analysis (MCDA) of a wide range of practical problems on risk management is introduced. Decerns framework contains a library of modules that are the basis for two scalable systems: DecernsMCDA for analysis of multicriteria problems, and DecernsSDSS for multicriteria analysis of spatial options. DecernsMCDA includes well known MCDA methods and original methods for uncertainty treatment based on probabilistic approaches and fuzzy numbers. As a result, these MCDA methods are described along with a case study on analysis of multicriteria location problem.

  11. The influence of providing a clinical practice guideline on dental students' decision making.

    PubMed

    van der Sanden, Wil J M; Mettes, Dirk G; Plasschaert, Alphons J M; Mulder, Jan; Verdonschot, Emiel H

    2004-02-01

    The aim of this study was to assess the effect of the provision of a clinical practice guideline (CPG) on dental students' decisions to remove asymptomatic, impacted lower third molars. All dental students, who in 2001 were in the 3rd, 4th or 5th (final) year of their study at the Nijmegen College of Dental Sciences, were invited to participate. A pre-test-post-test control group design was used. Given 36 patient cases, all dental students were asked to assess the need for removal of asymptomatic, impacted lower third molars. All pre-test respondents were randomly allocated to the control or intervention group. After the provision of a CPG to the intervention group, both groups were asked to assess the same cases again. Frequencies of decisions to remove the third molars were calculated. Chi-square tests and anova were used to test the influence of study year and gender on the drop-out rate and on the effect of the provision of a CPG on students' treatment decisions. The decrease in indications to remove third molars by the intervention group was statistically significant (P < 0.05). In the control group, no significant decrease was observed. It was concluded that the provision of a CPG significantly influences dental students' decision making about treatment in a third-molar decision task. Students who used the CPG showed more guideline-conformed decision making. PMID:14717683

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

    PubMed Central

    2012-01-01

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

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

    PubMed Central

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

    2016-01-01

    Background Knowledge translation (KT) interventions are attempts to change behavior in keeping with scientific evidence. While genetic tests are increasingly available to healthcare consumers in the clinic, evidence about their benefits is unclear and decisions about genetic testing are thus difficult for all parties. Objective We sought to identify KT interventions that involved decisions about genetic testing in the clinical context and to assess their effectiveness for improving decision making in terms of behavior change, increased knowledge and wellbeing. Methods We searched for trials assessing KT interventions in the context of genetic testing up to March 2014 in all systematic reviews (n = 153) published by two Cochrane review groups: Effective Practice and Organisation of Care (EPOC) and Consumers and Communication. Results We retrieved 2473 unique trials of which we retained only 28 (1%). Two EPOC reviews yielded two trials of KT interventions: audit and feedback (n = 1) and educational outreach (n = 1). Both targeted health professionals and the KT intervention they assessed was found to be effective. Four Consumers and Communication reviews yielded 26 trials: decision aids (n = 15), communication of DNA-based disease risk estimates (n = 7), personalized risk communication (n = 3) and mobile phone messaging (n = 1). Among these, 25 trials targeted only health consumers or patients and the KT interventions were found to be effective in four trials, partly effective in seven, and ineffective in four. Lastly, only one trial targeted both physicians and patients and was found to be effective. Conclusions More research on the effectiveness of KT interventions regarding genetic testing in the clinical context may contribute to patients making informed value-based decisions and drawing the maximum benefit from clinical applications of genetic and genomic innovations. PMID:26938633

  14. Clinical Decision Support Systems (CDSS) for preventive management of COPD patients

    PubMed Central

    2014-01-01

    Background The use of information and communication technologies to manage chronic diseases allows the application of integrated care pathways, and the optimization and standardization of care processes. Decision support tools can assist in the adherence to best-practice medicine in critical decision points during the execution of a care pathway. Objectives The objectives are to design, develop, and assess a clinical decision support system (CDSS) offering a suite of services for the early detection and assessment of chronic obstructive pulmonary disease (COPD), which can be easily integrated into a healthcare providers' work-flow. Methods The software architecture model for the CDSS, interoperable clinical-knowledge representation, and inference engine were designed and implemented to form a base CDSS framework. The CDSS functionalities were iteratively developed through requirement-adjustment/development/validation cycles using enterprise-grade software-engineering methodologies and technologies. Within each cycle, clinical-knowledge acquisition was performed by a health-informatics engineer and a clinical-expert team. Results A suite of decision-support web services for (i) COPD early detection and diagnosis, (ii) spirometry quality-control support, (iii) patient stratification, was deployed in a secured environment on-line. The CDSS diagnostic performance was assessed using a validation set of 323 cases with 90% specificity, and 96% sensitivity. Web services were integrated in existing health information system platforms. Conclusions Specialized decision support can be offered as a complementary service to existing policies of integrated care for chronic-disease management. The CDSS was able to issue recommendations that have a high degree of accuracy to support COPD case-finding. Integration into healthcare providers' work-flow can be achieved seamlessly through the use of a modular design and service-oriented architecture that connect to existing health

  15. A new tool for analysis of cleanup criteria decisions.

    PubMed

    Klemic, Gladys A; Bailey, Paul; Elcock, Deborah

    2003-08-01

    Radionuclides and other hazardous materials resulting from processes used in nuclear weapons production contaminate soil, groundwater, and buildings around the United States. Cleanup criteria for environmental contaminants are agreed on prior to remediation and underpin the scope and legacy of the cleanup process. Analysis of cleanup criteria can be relevant for future agreements and may also provide insight into a complex decision making process where science and policy issues converge. An Internet accessible database has been established to summarize cleanup criteria and related factors involved in U.S. Department of Energy remediation decisions. This paper reports on a new user interface for the database that is designed to integrate related information into graphic displays and tables with interactive features that allow exploratory data analysis of cleanup criteria. Analysis of 137Cs in surface soil is presented as an example.

  16. Clinical Decision Support for Whole Genome Sequence Information Leveraging a Service-Oriented Architecture: a Prototype

    PubMed Central

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

    2014-01-01

    Whole genome sequence (WGS) information could soon be routinely available to clinicians to support the personalized care of their patients. At such time, clinical decision support (CDS) integrated into the clinical workflow will likely be necessary to support genome-guided clinical care. Nevertheless, developing CDS capabilities for WGS information presents many unique challenges that need to be overcome for such approaches to be effective. In this manuscript, we describe the development of a prototype CDS system that is capable of providing genome-guided CDS at the point of care and within the clinical workflow. To demonstrate the functionality of this prototype, we implemented a clinical scenario of a hypothetical patient at high risk for Lynch Syndrome based on his genomic information. We demonstrate that this system can effectively use service-oriented architecture principles and standards-based components to deliver point of care CDS for WGS information in real-time. PMID:25954430

  17. Characterizing Decision-Analysis Performances of Risk Prediction Models Using ADAPT Curves

    PubMed Central

    Lee, Wen-Chung; Wu, Yun-Chun

    2016-01-01

    Abstract The area under the receiver operating characteristic curve is a widely used index to characterize the performance of diagnostic tests and prediction models. However, the index does not explicitly acknowledge the utilities of risk predictions. Moreover, for most clinical settings, what counts is whether a prediction model can guide therapeutic decisions in a way that improves patient outcomes, rather than to simply update probabilities. Based on decision theory, the authors propose an alternative index, the “average deviation about the probability threshold” (ADAPT). An ADAPT curve (a plot of ADAPT value against the probability threshold) neatly characterizes the decision-analysis performances of a risk prediction model. Several prediction models can be compared for their ADAPT values at a chosen probability threshold, for a range of plausible threshold values, or for the whole ADAPT curves. This should greatly facilitate the selection of diagnostic tests and prediction models. PMID:26765451

  18. Clinical Decision Support Tools for Selecting Interventions for Patients with Disabling Musculoskeletal Disorders: A Scoping Review.

    PubMed

    Gross, Douglas P; Armijo-Olivo, Susan; Shaw, William S; Williams-Whitt, Kelly; Shaw, Nicola T; Hartvigsen, Jan; Qin, Ziling; Ha, Christine; Woodhouse, Linda J; Steenstra, Ivan A

    2016-09-01

    Purpose We aimed to identify and inventory clinical decision support (CDS) tools for helping front-line staff select interventions for patients with musculoskeletal (MSK) disorders. Methods We used Arksey and O'Malley's scoping review framework which progresses through five stages: (1) identifying the research question; (2) identifying relevant studies; (3) selecting studies for analysis; (4) charting the data; and (5) collating, summarizing and reporting results. We considered computer-based, and other available tools, such as algorithms, care pathways, rules and models. Since this research crosses multiple disciplines, we searched health care, computing science and business databases. Results Our search resulted in 4605 manuscripts. Titles and abstracts were screened for relevance. The reliability of the screening process was high with an average percentage of agreement of 92.3 %. Of the located articles, 123 were considered relevant. Within this literature, there were 43 CDS tools located. These were classified into 3 main areas: computer-based tools/questionnaires (n = 8, 19 %), treatment algorithms/models (n = 14, 33 %), and clinical prediction rules/classification systems (n = 21, 49 %). Each of these areas and the associated evidence are described. The state of evidentiary support for CDS tools is still preliminary and lacks external validation, head-to-head comparisons, or evidence of generalizability across different populations and settings. Conclusions CDS tools, especially those employing rapidly advancing computer technologies, are under development and of potential interest to health care providers, case management organizations and funders of care. Based on the results of this scoping review, we conclude that these tools, models and systems should be subjected to further validation before they can be recommended for large-scale implementation for managing patients with MSK disorders.

  19. Designing a Clinical Framework to Guide Gross Motor Intervention Decisions for Infants and Young Children with Hypotonia

    ERIC Educational Resources Information Center

    Darrah, Johanna; O'Donnell, Maureen; Lam, Joyce; Story, Maureen; Wickenheiser, Diane; Xu, Kaishou; Jin, Xiaokun

    2013-01-01

    Clinical practice frameworks are a valuable component of clinical education, promoting informed clinical decision making based on the best available evidence and/or clinical experience. They encourage standardized intervention approaches and evaluation of practice. Based on an international project to support the development of an enhanced service…

  20. The future in clinical genetics: affective forecasting biases in patient and clinician decision making.

    PubMed

    Peters, S A; Laham, S M; Pachter, N; Winship, I M

    2014-04-01

    When clinicians facilitate and patients make decisions about predictive genetic testing, they often base their choices on the predicted emotional consequences of positive and negative test results. Research from psychology and decision making suggests that such predictions may often be biased. Work on affective forecasting-predicting one's future emotional states-shows that people tend to overestimate the impact of (especially negative) emotional events on their well-being; a phenomenon termed the impact bias. In this article, we review the causes and consequences of the impact bias in medical decision making, with a focus on applying such findings to predictive testing in clinical genetics. We also recommend strategies for reducing the impact bias and consider the ethical and practical implications of doing so.

  1. [Does evidence-based surgery harm autonomy in clinical decision making?].

    PubMed

    Loss, J; Nagel, E

    2005-02-01

    Evidence-based clinical guidelines in surgery are frequently confronted with scepticism by the medical staff, especially because a confinement of free decision making in therapy is expected. Considering that medicine is not merely natural science, but can as well be comprehended as social science or art, evidence-based medicine (EbM) may lead to an oversimplified and rigid standardization in medical care ("cook book medicine"). In addition, scientific progress might be prevented by inflexible guidelines. However, it is important for surgeons to engage in the development of evidence-based guidelines in order to put forward their interests, because it is the lack of medical guidelines that might threaten free decision making in surgery - by not confronting economical pressure with decisive minimal standards in medical care. Therapeutical freedom is a substantial principle in medicine, but it should be considered that according to occidental tradition, "freedom" is necessarily involving reason and conscientiousness.

  2. Multi-site evaluation of a clinical decision support system for radiation therapy

    NASA Astrophysics Data System (ADS)

    Deshpande, Ruchi; DeMarco, John; Kessel, Kerstin; Liu, Brent J.

    2016-03-01

    We have developed an imaging informatics based decision support system that learns from retrospective treatment plans to provide recommendations for healthy tissue sparing to prospective incoming patients. This system incorporates a model of best practices from previous cases, specific to tumor anatomy. Ultimately, our hope is to improve clinical workflow efficiency, patient outcomes and to increase clinician confidence in decision-making. The success of such a system depends greatly on the training dataset, which in this case, is the knowledge base that the data-mining algorithm employs. The size and heterogeneity of the database is essential for good performance. Since most institutions employ standard protocols and practices for treatment planning, the diversity of this database can be greatly increased by including data from different institutions. This work presents the results of incorporating cross-country, multi-institutional data into our decision support system for evaluation and testing.

  3. Medical versus nonmedical mental health referral: clinical decision-making by telephone access center staff.

    PubMed

    Pulier, Myron L; Ciccone, Donald S; Castellano, Cherie; Marcus, Karen; Schleifer, Steven J

    2003-01-01

    A database review investigated decisions of clinicians staffing a university-based telephone access center in referring new adult patients to nonpsychiatrists versus psychiatrists for initial ambulatory behavioral health care appointments. Systematically collected demographic and clinical data in a computer log of calls to highly trained care managers at the access center had limited predictive value with respect to their referral decisions. Furthermore, while 28% of the 610 study patients were initially referred to psychiatrists, billing data revealed that in-person therapists soon cross-referred at least 20% more to a psychiatrist. Care managers sent 56% of callers already taking psychotropic medications to nonpsychiatrists, 51% of whom were then cross-referred to psychiatrists. Predictive algorithms showed no potential to enhance efficiency of decisions about referral to a psychiatrist versus a nonpsychiatrist. Efforts to enhance such efficiency may not be cost-effective. It may be more fiscally efficient to assign less-experienced personnel as telephone care managers.

  4. The doctor-patient relationship as a toolkit for uncertain clinical decisions.

    PubMed

    Diamond-Brown, Lauren

    2016-06-01

    Medical uncertainty is a well-recognized problem in healthcare, yet how doctors make decisions in the face of uncertainty remains to be understood. This article draws on interdisciplinary literature on uncertainty and physician decision-making to examine a specific physician response to uncertainty: using the doctor-patient relationship as a toolkit. Additionally, I ask what happens to this process when the doctor-patient relationship becomes fragmented. I answer these questions by examining obstetrician-gynecologists' narratives regarding how they make decisions when faced with uncertainty in childbirth. Between 2013 and 2014, I performed 21 semi-structured interviews with obstetricians in the United States. Obstetricians were selected to maximize variation in relevant physician, hospital, and practice characteristics. I began with grounded theory and moved to analytical coding of themes in relation to relevant literature. My analysis renders it evident that some physicians use the doctor-patient relationship as a toolkit for dealing with uncertainty. I analyze how this process varies for physicians in different models of care by comparing doctors' experiences in models with continuous versus fragmented doctor-patient relationships. My key findings are that obstetricians in both models appealed to the ideal of patient-centered decision-making to cope with uncertain decisions, but in practice physicians in fragmented care faced a number of challenges to using the doctor-patient relationship as a toolkit for decision-making. These challenges led to additional uncertainties and in some cases to poor outcomes for doctors and/or patients; they also raised concerns about the reproduction of inequality. Thus organization of care delivery mitigates the efficacy of doctors' use of the doctor-patient relationship toolkit for uncertain decisions. These findings have implications for theorizing about decision-making under conditions of medical uncertainty, for understanding

  5. Multi-criteria decision analysis: Limitations, pitfalls, and practical difficulties

    SciTech Connect

    Kujawski, Edouard

    2003-02-01

    The 2002 Winter Olympics women's figure skating competition is used as a case study to illustrate some of the limitations, pitfalls, and practical difficulties of Multi-Criteria Decision Analysis (MCDA). The paper compares several widely used models for synthesizing the multiple attributes into a single aggregate value. The various MCDA models can provide conflicting rankings of the alternatives for a common set of information even under states of certainty. Analysts involved in MCDA need to deal with the following challenging tasks: (1) selecting an appropriate analysis method, and (2) properly interpreting the results. An additional trap is the availability of software tools that implement specific MCDA models that can beguile the user with quantitative scores. These conclusions are independent of the decision domain and they should help foster better MCDA practices in many fields including systems engineering trade studies.

  6. Guide to IDAP, Version 2: an interactive decision analysis procedure

    SciTech Connect

    Jusko, M.J.; Whitfield, R.G.

    1980-11-01

    This document is intended to serve as both a programmer's and user's guide to the current version of the IDAP; and to prompt interested individuals into making suggestions for the future development of IDAP. The majority of the sections pertain to the main IDA program rather than to the IDAIN procedure. A brief discussion is presented of the theory of decision analysis. The aspects of decision analysis that are relevant to the IDAP are discussed. A complete list and description of the commands used in the IDAP program is provided and, including three complete examples. This section may be considered a user's guide to the IDAP. The programmer's guide to the IDAP discusses the various technical aspects of the programs, and may be skipped by users not involved with programming the IDAP. A list of the error messages generated by the IDAP is presented. As the program is developed, error handling and messages will improve.

  7. Cost-Effectiveness of Clinical Decision Support System in Improving Maternal Health Care in Ghana

    PubMed Central

    Dalaba, Maxwell Ayindenaba; Akweongo, Patricia; Aborigo, Raymond Akawire; Saronga, Happiness Pius; Williams, John; Blank, Antje; Kaltschmidt, Jens; Sauerborn, Rainer; Loukanova, Svetla

    2015-01-01

    Objective This paper investigated the cost-effectiveness of a computer-assisted Clinical Decision Support System (CDSS) in the identification of maternal complications in Ghana. Methods A cost-effectiveness analysis was performed in a before- and after-intervention study. Analysis was conducted from the provider’s perspective. The intervention area was the Kassena- Nankana district where computer-assisted CDSS was used by midwives in maternal care in six selected health centres. Six selected health centers in the Builsa district served as the non-intervention group, where the normal Ghana Health Service activities were being carried out. Results Computer-assisted CDSS increased the detection of pregnancy complications during antenatal care (ANC) in the intervention health centres (before-intervention= 9 /1,000 ANC attendance; after-intervention= 12/1,000 ANC attendance; P-value=0.010). In the intervention health centres, there was a decrease in the number of complications during labour by 1.1%, though the difference was not statistically significant (before-intervention =107/1,000 labour clients; after-intervention= 96/1,000 labour clients; P-value=0.305). Also, at the intervention health centres, the average cost per pregnancy complication detected during ANC (cost –effectiveness ratio) decreased from US$17,017.58 (before-intervention) to US$15,207.5 (after-intervention). Incremental cost –effectiveness ratio (ICER) was estimated at US$1,142. Considering only additional costs (cost of computer-assisted CDSS), cost per pregnancy complication detected was US$285. Conclusions Computer –assisted CDSS has the potential to identify complications during pregnancy and marginal reduction in labour complications. Implementing computer-assisted CDSS is more costly but more effective in the detection of pregnancy complications compared to routine maternal care, hence making the decision to implement CDSS very complex. Policy makers should however be guided by whether

  8. Decision making and senior management: the implementation of change projects covering clinical management in SUS hospitals.

    PubMed

    Pacheco, José Márcio da Cunha; Gomes, Romeu

    2016-08-01

    This paper analyses the decision making process for senior management in public hospitals that are a part of the National Health Service in Brazil (hereafter SUS) in relation to projects aimed at changing clinical management. The methodological design of this study is qualitative in nature taking a hermeneutics-dialectics perspective in terms of results. Hospital directors noted that clinical management projects changed the state of hospitals through: improving their organizations, mobilizing their staff in order to increase a sense of order and systemizing actions and available resources. Technical rationality was the principal basis used in the decision making process for managers. Due to the reality of many hospitals having fragmented organizations, this fact impeded the use of aspects related to rationality, such as economic and financial factors in the decision making process. The incremental model and general politics also play a role in this area. We concluded that the decision making process embraces a large array of factors including rational aspects such as the use of management techniques and the ability to analyze, interpret and summarize. It also incorporates subjective elements such as how to select values and dealing with people's working experiences. We recognized that management problems are wide in scope, ambiguous, complex and do not come with a lot of structure in practice.

  9. A web-based intensive care clinical decision support system: from design to evaluation.

    PubMed

    Ozel, Deniz; Bilge, Ugur; Zayim, Nese; Cengiz, Melike

    2013-03-01

    The aim of this study is to develop and evaluate a web-based clinical decision support system (CDSS) containing clinical guidelines and protocols that will support intensive care unit (ICU) providers in making decisions more effectively and quickly. First, a survey was carried out with 38 physicians in order to determine their preferences, needs and concerns regarding decision support tools. After the survey, guidelines were prepared by a group of specialists in ICU, and a medical informatician converted the guidelines into algorithm forms. Ten CDSS were developed using the algorithms, and placed onto the Intensive Care Decision Support Website (ICDSW). In order to evaluation of the website, 15 physicians were asked to answer 10 questions in 10 different scenarios first using a paper-based approach, then with ICDSW. When the answers were analyzed, it was found that the answers given by using ICDSW were significantly better than the paper-based approach (p <  0.001). However, there was no significant difference in terms of the time needed to answer the questions (p =  0.138). The usability score of the website was 85.6 ±  8.89. The study demonstrated the successful implementation of an ICDSW within intensive care units.

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

    PubMed

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

    2011-04-01

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

  11. Decision making and senior management: the implementation of change projects covering clinical management in SUS hospitals.

    PubMed

    Pacheco, José Márcio da Cunha; Gomes, Romeu

    2016-08-01

    This paper analyses the decision making process for senior management in public hospitals that are a part of the National Health Service in Brazil (hereafter SUS) in relation to projects aimed at changing clinical management. The methodological design of this study is qualitative in nature taking a hermeneutics-dialectics perspective in terms of results. Hospital directors noted that clinical management projects changed the state of hospitals through: improving their organizations, mobilizing their staff in order to increase a sense of order and systemizing actions and available resources. Technical rationality was the principal basis used in the decision making process for managers. Due to the reality of many hospitals having fragmented organizations, this fact impeded the use of aspects related to rationality, such as economic and financial factors in the decision making process. The incremental model and general politics also play a role in this area. We concluded that the decision making process embraces a large array of factors including rational aspects such as the use of management techniques and the ability to analyze, interpret and summarize. It also incorporates subjective elements such as how to select values and dealing with people's working experiences. We recognized that management problems are wide in scope, ambiguous, complex and do not come with a lot of structure in practice. PMID:27557021

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

    PubMed Central

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

    2014-01-01

    Multidisciplinary team (MDT) meetings are becoming the model of care for cancer patients worldwide. While MDTs have improved the quality of cancer care, the meetings impose substantial time pressure on the members, who generally attend several such MDTs. We describe Lung Cancer Assistant (LCA), a clinical decision support (CDS) prototype designed to assist the experts in the treatment selection decisions in the lung cancer MDTs. A novel feature of LCA is its ability to provide rule-based and probabilistic decision support within a single platform. The guideline-based CDS is based on clinical guideline rules, while the probabilistic CDS is based on a Bayesian network trained on the English Lung Cancer Audit Database (LUCADA). We assess rule-based and probabilistic recommendations based on their concordances with the treatments recorded in LUCADA. Our results reveal that the guideline rule-based recommendations perform well in simulating the recorded treatments with exact and partial concordance rates of 0.57 and 0.79, respectively. On the other hand, the exact and partial concordance rates achieved with probabilistic results are relatively poorer with 0.27 and 0.76. However, probabilistic decision support fulfils a complementary role in providing accurate survival estimations. Compared to recorded treatments, both CDS approaches promote higher resection rates and multimodality treatments. PMID:24990290

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

    PubMed Central

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

    2014-01-01

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

  14. WHAT ARE 'BEST INTERESTS'? A CRITICAL EVALUATION OF 'BEST INTERESTS' DECISION-MAKING IN CLINICAL PRACTICE.

    PubMed

    Taylor, Helen J

    2016-01-01

    Obtaining the patient's consent is usually a prerequisite of any clinical intervention. However, some cognitively impaired patients may not be able to give valid consent. Following years of consultation and legislative review, the Mental Capacity Act 2005 (MCA) provides a statutory framework of 'best interests' decision-making on behalf of incapacitated individuals. However, confusion over the meaning and application of the 'best interests' standard persists. This paper explores the variation in judicial interpretation of the standard and the complexities of best interests decision-making in clinical practice. Prevailing confusion and risk-aversive practices mean that the rights and interests of cognitively impaired individuals continue to be compromised, with evidence to suggest that 'best interests' may be conflated with the clinician's evaluation of 'best medical interests'.

  15. How Qualitative Research Informs Clinical and Policy Decision Making in Transplantation: A Review.

    PubMed

    Tong, Allison; Morton, Rachael L; Webster, Angela C

    2016-09-01

    Patient-centered care is no longer just a buzzword. It is now widely touted as a cornerstone in delivering quality care across all fields of medicine. However, patient-centered strategies and interventions necessitate evidence about patients' decision-making processes, values, priorities, and needs. Qualitative research is particularly well suited to understanding the experience and perspective of patients, donors, clinicians, and policy makers on a wide range of transplantation-related topics including organ donation and allocation, adherence to prescribed therapy, pretransplant and posttransplant care, implementation of clinical guidelines, and doctor-patient communication. In transplantation, evidence derived from qualitative research has been integrated into strategies for shared decision-making, patient educational resources, process evaluations of trials, clinical guidelines, and policies. The aim of this article is to outline key concepts and methods used in qualitative research, guide the appraisal of qualitative studies, and assist clinicians to understand how qualitative research may inform their practice and policy. PMID:27479165

  16. Conflicts of interest in research: is clinical decision-making compromised? An opinion paper.

    PubMed

    Adibi, Shawn; Abidi, Shawn; Bebermeyer, Richard D

    2010-08-01

    Lack of transparency in funded research can compromise clinical decision-making in an evidence-based practice. Transparency can be defined as full disclosure of all financial assistance and support to authors and investigators. There is a perception that ethical principles are eroding and that research data can be biased due to conflicts of interest. These research outcomes biased or not, are used for clinical decision-making in the evidence-based practice. One suggested solution to this common ethical dilemma is to continue the dialogue on transparency in research and to create oversight bodies which include representatives from business and industry, private practice, academia, and research. There is increasing evidence of the need for more ethics education at all levels.

  17. A Legal Framework to Enable Sharing of Clinical Decision Support Knowledge and Services across Institutional Boundaries

    PubMed Central

    Hongsermeier, Tonya; Maviglia, Saverio; Tsurikova, Lana; Bogaty, Dan; Rocha, Roberto A.; Goldberg, Howard; Meltzer, Seth; Middleton, Blackford

    2011-01-01

    The goal of the CDS Consortium (CDSC) is to assess, define, demonstrate, and evaluate best practices for knowledge management and clinical decision support in healthcare information technology at scale – across multiple ambulatory care settings and Electronic Health Record technology platforms. In the course of the CDSC research effort, it became evident that a sound legal foundation was required for knowledge sharing and clinical decision support services in order to address data sharing, intellectual property, accountability, and liability concerns. This paper outlines the framework utilized for developing agreements in support of sharing, accessing, and publishing content via the CDSC Knowledge Management Portal as well as an agreement in support of deployment and consumption of CDSC developed web services in the context of a research project under IRB oversight. PMID:22195151

  18. How Qualitative Research Informs Clinical and Policy Decision Making in Transplantation: A Review.

    PubMed

    Tong, Allison; Morton, Rachael L; Webster, Angela C

    2016-09-01

    Patient-centered care is no longer just a buzzword. It is now widely touted as a cornerstone in delivering quality care across all fields of medicine. However, patient-centered strategies and interventions necessitate evidence about patients' decision-making processes, values, priorities, and needs. Qualitative research is particularly well suited to understanding the experience and perspective of patients, donors, clinicians, and policy makers on a wide range of transplantation-related topics including organ donation and allocation, adherence to prescribed therapy, pretransplant and posttransplant care, implementation of clinical guidelines, and doctor-patient communication. In transplantation, evidence derived from qualitative research has been integrated into strategies for shared decision-making, patient educational resources, process evaluations of trials, clinical guidelines, and policies. The aim of this article is to outline key concepts and methods used in qualitative research, guide the appraisal of qualitative studies, and assist clinicians to understand how qualitative research may inform their practice and policy.

  19. Clinical judgment and decision making in wound assessment and management: is experience enough?

    PubMed

    Logan, Gemma

    2015-03-01

    The assessment and management of wounds forms a large proportion of community nurses' workload, often requiring judgment and decision-making in complex, challenging and uncertain circumstances. The processes through which nurses form judgments and make decisions within this context are reviewed in this article against existing theories on these on these subjects. There is variability in wound assessment and management practice which may be attributed to uncertainties within the context, a lack of knowledge in appropriate treatment choices and the inability to correctly value the importance of the clinical information presented. Nurses may be required to draw on intuition to guide their judgments and decision-making by association with experience and expertise. In addition, a step-by-step analytical approach underpinned by an evidence base may be required to ensure accuracy in practice. Developing an understanding of the different theories of judgment and decision-making may facilitate nurses' abilities to reflect on their own decision tasks, thereby enhancing the care provided.

  20. A Serious Game for Teaching Nursing Students Clinical Reasoning and Decision-Making Skills.

    PubMed

    Johnsen, Hege Mari; Fossum, Mariann; Vivekananda-Schmidt, Pirashanthie; Fruhling, Ann; Slettebø, Åshild

    2016-01-01

    The aim of this study was to design and pilot-test a serious game for teaching nursing students clinical reasoning and decision-making skills in caring for patients with chronic obstructive pulmonary disease. A video-based serious game prototype was developed. A purposeful sample of six participants tested and evaluated the prototype. Usability issues were identified regarding functionality and user-computer interface. However, overall the serious game was perceived to be useful, usable and likable to use. PMID:27332402

  1. A Serious Game for Teaching Nursing Students Clinical Reasoning and Decision-Making Skills.

    PubMed

    Johnsen, Hege Mari; Fossum, Mariann; Vivekananda-Schmidt, Pirashanthie; Fruhling, Ann; Slettebø, Åshild

    2016-01-01

    The aim of this study was to design and pilot-test a serious game for teaching nursing students clinical reasoning and decision-making skills in caring for patients with chronic obstructive pulmonary disease. A video-based serious game prototype was developed. A purposeful sample of six participants tested and evaluated the prototype. Usability issues were identified regarding functionality and user-computer interface. However, overall the serious game was perceived to be useful, usable and likable to use.

  2. Decision analysis of polluted sites -- A fuzzy set approach

    SciTech Connect

    Mohamed, A.M.O.; Cote, K.

    1999-07-01

    A decision analysis based model (DAPS 1.0, Decision Analysis of Polluted Sites) has been developed to evaluate risks that polluted sites might pose to human health. Pollutants present in soils and sediments can potentially migrate from source to receptor(s), via different pathways. in the developed model, pathways are simulated via transport models (i.e., groundwater transport model, runoff-erosion model, air diffusion model, and sediment diffusion, and resuspension model in water bodies). Humans can be affected by pollutant migration through land and water use. health risks can arise from ingestion of and dermal contact with polluted water and soil, as well as through inhalation of polluted air. Quantitative estimates of risks are calculated for both carcinogenic and non-carcinogenic pollutants. Being very heterogeneous, soil and sediment systems are characterized by uncertain parameters. Concepts of fuzzy set theory have been adopted to account for uncertainty in the input parameters which are represented by fuzzy numbers. An inference model using fuzzy logic has been constructed for reasoning in the decision analysis.

  3. Decision analysis of treatment choices in the osteochondroses.

    PubMed

    Bunch, W H

    1981-01-01

    Physicians tend to decry the lack of data on which they can make decisions. This is commendable, and all should encourage the pursuit of better data and more precise analysis. But decisions must be made, and each physician must deal with what data are available and evaluate them against all the general uncertainties. Equally important are the values that we place on the outcome of treatment. Much of the disagreement among physicians about treatment protocols involves a difference in values. While this is not necessarily bad, it points to the need to consider explicitly the value we place on a result or the morbidity possibly accompanying that result. In the osteochondroses, consideration of values will protect patients from overzealous treatment. Finally, the formality of a decision process should not necessarily modify a plan of treatment based on fundamentally sound principles, intuition, and anecdotal experience. Regardless of which factors represent the basis for an individual surgeon's selection of a particular approach, evaluation of both desirable and undesirable aspects of each alternative prevents impulsive acceptance of the most recently described, often unproven operation. Salter's aphorism: "The decision is more important than the incision," is particularly applicable in treatment of the osteochondroses.

  4. Can a patient smart card improve decision making in a clinical setting?.

    PubMed

    Bérubé, J; Papillon, M J; Lavoie, G; Durant, P; Fortin, J P

    1995-01-01

    In the health field, clinical information is the raw material for the clinician delivering health services. Therefore, the clinical information available to the physician is often incomplete or even non¿existent upon consultation. Furthermore, the reconstruction of the medical history, which is the most important source of data for the clinician to establish a diagnosis and initiate a treatment, suffers from many constraints. The smart card, like the one used in Quebec's project, could ease the physician's decision-making by allowing fast access to accurate and pertinent data. The smart card is a major asset in the present health system.

  5. Discriminative distance functions and the patient neighborhood graph for clinical decision support.

    PubMed

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

    2010-01-01

    There are two essential reasons for the slow progress in the acceptance of clinical similarity search-based decision support systems (DSSs); the especial complexity of biomedical data making it difficult to define a meaningful and effective distance function and the lack of transparency and explanation ability in many existing DSSs. In this chapter, we address these two problems by introducing a novel technique for visualizing patient similarity with neighborhood graphs and by considering two techniques for learning discriminative distance functions. We present an experimental study and discuss our implementation of similarity visualization within a clinical DSS. PMID:20865536

  6. Personalized Clinical Decision Making in Gastrointestinal Malignancies: The Role of PET.

    PubMed

    Hess, Søren; Bjerring, Ole Steen; Pfeiffer, Per; Høilund-Carlsen, Poul Flemming

    2016-07-01

    Gastrointestinal malignancies comprise a heterogeneous group of diseases that include both common and rare diseases with very different presentations and prognoses. The mainstay of treatment is surgery in combination with preoperative and adjuvant chemotherapy depending on clinical presentation and initial stages. This article outlines the potential use of fluorodeoxyglucose-PET/CT in clinical decision making with special regard to preoperative evaluation and response assessment in gastric cancer (including the gastroesophageal junction), pancreatic cancer (excluding neuroendocrine tumors), colorectal cancer, and gastrointestinal stromal tumors. PMID:27321031

  7. A programmable rules engine to provide clinical decision support using HTML forms.

    PubMed

    Heusinkveld, J; Geissbuhler, A; Sheshelidze, D; Miller, R

    1999-01-01

    The authors have developed a simple method for specifying rules to be applied to information on HTML forms. This approach allows clinical experts, who lack the programming expertise needed to write CGI scripts, to construct and maintain domain-specific knowledge and ordering capabilities within WizOrder, the order-entry and decision support system used at Vanderbilt Hospital. The clinical knowledge base maintainers use HTML editors to create forms and spreadsheet programs for rule entry. A test environment has been developed which uses Netscape to display forms; the production environment displays forms using an embedded browser.

  8. The ethics of forgoing life-sustaining treatment: theoretical considerations and clinical decision making

    PubMed Central

    2014-01-01

    Withholding or withdrawing a life-sustaining treatment tends to be very challenging for health care providers, patients, and their family members alike. When a patient’s life seems to be nearing its end, it is generally felt that the morally best approach is to try a new intervention, continue all treatments, attempt an experimental course of action, in short, do something. In contrast to this common practice, the authors argue that in most instances, the morally safer route is actually to forgo life-sustaining treatments, particularly when their likelihood to effectuate a truly beneficial outcome has become small relative to the odds of harming the patient. The ethical analysis proceeds in three stages. First, the difference between neglectful omission and passive acquiescence is explained. Next, the two necessary conditions for any medical treatment, i.e., that it is medically indicated and that consent is obtained, are applied to life-sustaining interventions. Finally, the difference between withholding and withdrawing a life-sustaining treatment is discussed. In the second part of the paper the authors show how these theoretical-ethical considerations can guide clinical-ethical decision making. A case vignette is presented about a patient who cannot be weaned off the ventilator post-surgery. The ethical analysis of this case proceeds through three stages. First, it is shown that and why withdrawal of the ventilator in this case does not equate assistance in suicide or euthanasia. Next, the question is raised whether continued ventilation can be justified medically, or has become futile. Finally, the need for the health care team to obtain consent for the continuation of the ventilation is discussed. PMID:24618004

  9. Advances In Infection Surveillance and Clinical Decision Support With Fuzzy Sets and Fuzzy Logic.

    PubMed

    Koller, Walter; de Bruin, Jeroen S; Rappelsberger, Andrea; Adlassnig, Klaus-Peter

    2015-01-01

    By the use of extended intelligent information technology tools for fully automated healthcare-associated infection (HAI) surveillance, clinicians can be informed and alerted about the emergence of infection-related conditions in their patients. Moni--a system for monitoring nosocomial infections in intensive care units for adult and neonatal patients--employs knowledge bases that were written with extensive use of fuzzy sets and fuzzy logic, allowing the inherent un-sharpness of clinical terms and the inherent uncertainty of clinical conclusions to be a part of Moni's output. Thus, linguistic as well as propositional uncertainty became a part of Moni, which can now report retrospectively on HAIs according to traditional crisp HAI surveillance definitions, as well as support clinical bedside work by more complex crisp and fuzzy alerts and reminders. This improved approach can bridge the gap between classical retrospective surveillance of HAIs and ongoing prospective clinical-decision-oriented HAI support.

  10. Decision Consequence Model (DCM): Integrating environmental data and analysis into real time decision making

    SciTech Connect

    Cimorelli, A.J.; Stahl, C.H.; Chow, A.H.; Fernandez, C.

    1999-07-01

    A critical evaluation of the many environmental issues facing EPA Region 3 has established five major priorities: (1) ozone pollution (and its precursors); (2) impacts of acidification (acid deposition and acid mine drainage); (3) eutrophication of the Chesapeake Bay from atmospheric nitrogen deposition; (4) Cities/Urban Environment (ozone, particulate matter (PM), air toxics are some of the air components); and (5) Climate Change. Recognizing the complex nature of the systems controlling these issues, Region III's Air Protection Division (APD) is developing a decision support tool, i.e., the Decision Consequence Model (DCM), that will integrate and automate the analysis of environmental impacts in a manner that allows them to holistically address these regional priorities. Using this tool the authors intend to consider the interdependency of pollutants and their environmental impacts in order to support real-time decision making. The purpose of this paper is to outline the basic concept of the DCM and to present an example set of environmental indicators to illustrate how the DCM will be used to evaluate environmental impacts. The authors will discuss their process of indicator development, and present an example suite of indicators to provide a concrete example of the concepts presented above and, to illustrate the utility of the DCM to simultaneously evaluate multiple effects of a single pollutant. They will discuss the type of indicators chosen for this example as well as the general criteria the DCM indicators must satisfy. The framework that was developed to construct the indicators is discussed and used to calculate the example indicators. The yearly magnitudes of these example indicators are calculated for various multi-year periods to show their behavior over time.

  11. DISPLA: decision information system for procurement and logistics analysis

    NASA Astrophysics Data System (ADS)

    Calvo, Alberto B.; Danish, Alexander J.; Lamonakis, Gregory G.

    2002-08-01

    This paper describes an information-exchange system for Display systems acquisition and logistics support. DISPLA (Decision Information System for Procurement and Logistics Analysis) is an Internet-based system concept for bringing sellers (display system and component suppliers) and buyers (Government Program Offices and System Integrators) together in an electronic exchange to improve the acquisition and logistics analysis support of Flat Panel Displays for the military. A proof-of-concept demonstration is presented in this paper using sample data from vendor Web sites and Government data sources.

  12. Single-patient (n-of-1) trials: a pragmatic clinical decision methodology for patient-centered comparative effectiveness research

    PubMed Central

    Duan, Naihua; Kravitz, Richard L.; Schmid, Christopher H.

    2013-01-01

    Objective To raise awareness among clinicians and epidemiologists that single-patient (n-of-1) trials are potentially useful for informing personalized treatment decisions for patients with chronic conditions. Study Design and Setting We reviewed the clinical and statistical literature on methods and applications of single-patient trials and then critically evaluated the needs for further methodological developments. Results Existing literature reports application of 2,154 single-patient trials in 108 studies for diverse clinical conditions; various recent commentaries advocate for wider application of such trials in clinical decision making. Preliminary evidence from several recent pilot acceptability studies suggests that single-patient trials have the potential for widespread acceptance by patients and clinicians as an effective modality for increasing the therapeutic precision. Bayesian and adaptive statistical methods hold promise for increasing the informational yield of single-patient trials while reducing participant burden, but are not widely used. Personalized applications of single-patient trials can be enhanced through further development and application of methodologies on adaptive trial design, stopping rules, network meta-analysis, washout methods, and methods for communicating trial findings to patients and clinicians. Conclusions Single-patient trials may be poised to emerge as an important part of the methodological armamentarium for comparative effectiveness research and patient-centered outcomes research. By permitting direct estimation of individual treatment effects, they can facilitate finely graded individualized care, enhance therapeutic precision, improve patient outcomes, and reduce costs. PMID:23849149

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

    PubMed Central

    Bau, Cho-Tsan; Huang, Chung-Yi

    2014-01-01

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

  14. A Clinical Decision Support System for Integrating Tuberculosis and HIV Care in Kenya: A Human-Centered Design Approach

    PubMed Central

    Catalani, Caricia; Green, Eric; Owiti, Philip; Keny, Aggrey; Diero, Lameck; Yeung, Ada; Israelski, Dennis; Biondich, Paul

    2014-01-01

    With the aim of integrating HIV and tuberculosis care in rural Kenya, a team of researchers, clinicians, and technologists used the human-centered design approach to facilitate design, development, and deployment processes of new patient-specific TB clinical decision support system for medical providers. In Kenya, approximately 1.6 million people are living with HIV and have a 20-times higher risk of dying of tuberculosis. Although tuberculosis prevention and treatment medication is widely available, proven to save lives, and prioritized by the World Health Organization, ensuring that it reaches the most vulnerable communities remains challenging. Human-centered design, used in the fields of industrial design and information technology for decades, is an approach to improving the effectiveness and impact of innovations that has been scarcely used in the health field. Using this approach, our team followed a 3-step process, involving mixed methods assessment to (1) understand the situation through the collection and analysis of site observation sessions and key informant interviews; (2) develop a new clinical decision support system through iterative prototyping, end-user engagement, and usability testing; and, (3) implement and evaluate the system across 24 clinics in rural West Kenya. Through the application of this approach, we found that human-centered design facilitated the process of digital innovation in a complex and resource-constrained context. PMID:25170939

  15. A clinical decision support system for integrating tuberculosis and HIV care in Kenya: a human-centered design approach.

    PubMed

    Catalani, Caricia; Green, Eric; Owiti, Philip; Keny, Aggrey; Diero, Lameck; Yeung, Ada; Israelski, Dennis; Biondich, Paul

    2014-01-01

    With the aim of integrating HIV and tuberculosis care in rural Kenya, a team of researchers, clinicians, and technologists used the human-centered design approach to facilitate design, development, and deployment processes of new patient-specific TB clinical decision support system for medical providers. In Kenya, approximately 1.6 million people are living with HIV and have a 20-times higher risk of dying of tuberculosis. Although tuberculosis prevention and treatment medication is widely available, proven to save lives, and prioritized by the World Health Organization, ensuring that it reaches the most vulnerable communities remains challenging. Human-centered design, used in the fields of industrial design and information technology for decades, is an approach to improving the effectiveness and impact of innovations that has been scarcely used in the health field. Using this approach, our team followed a 3-step process, involving mixed methods assessment to (1) understand the situation through the collection and analysis of site observation sessions and key informant interviews; (2) develop a new clinical decision support system through iterative prototyping, end-user engagement, and usability testing; and, (3) implement and evaluate the system across 24 clinics in rural West Kenya. Through the application of this approach, we found that human-centered design facilitated the process of digital innovation in a complex and resource-constrained context.

  16. Interoperability of clinical decision-support systems and electronic health records using archetypes: a case study in clinical trial eligibility.

    PubMed

    Marcos, Mar; Maldonado, Jose A; Martínez-Salvador, Begoña; Boscá, Diego; Robles, Montserrat

    2013-08-01

    Clinical decision-support systems (CDSSs) comprise systems as diverse as sophisticated platforms to store and manage clinical data, tools to alert clinicians of problematic situations, or decision-making tools to assist clinicians. Irrespective of the kind of decision-support task CDSSs should be smoothly integrated within the clinical information system, interacting with other components, in particular with the electronic health record (EHR). However, despite decades of developments, most CDSSs lack interoperability features. We deal with the interoperability problem of CDSSs and EHRs by exploiting the dual-model methodology. This methodology distinguishes a reference model and archetypes. A reference model is represented by a stable and small object-oriented model that describes the generic properties of health record information. For their part, archetypes are reusable and domain-specific definitions of clinical concepts in the form of structured and constrained combinations of the entities of the reference model. We rely on archetypes to make the CDSS compatible with EHRs from different institutions. Concretely, we use archetypes for modelling the clinical concepts that the CDSS requires, in conjunction with a series of knowledge-intensive mappings relating the archetypes to the data sources (EHR and/or other archetypes) they depend on. We introduce a comprehensive approach, including a set of tools as well as methodological guidelines, to deal with the interoperability of CDSSs and EHRs based on archetypes. Archetypes are used to build a conceptual layer of the kind of a virtual health record (VHR) over the EHR whose contents need to be integrated and used in the CDSS, associating them with structural and terminology-based semantics. Subsequently, the archetypes are mapped to the EHR by means of an expressive mapping language and specific-purpose tools. We also describe a case study where the tools and methodology have been employed in a CDSS to support

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

    PubMed

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

    2015-09-01

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

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

    PubMed

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

    2015-09-01

    As a neo-liberal economy, India has become one of the new health tourism destinations, with commercial gestational surrogacy as an expanding market. Yet the Indian Assisted Reproductive Technology (ART) Bill has been pending for five years, and the guidelines issued by the Indian Council of Medical Research are somewhat vague and contradictory, resulting in self-regulated practices of fertility clinics. This paper broadly looks at clinical ethics in reproduction in the practice of surrogacy and decision-making in various procedures. Through empirical research in New Delhi, the capital of India, from December 2011 to November 2012, issues of decision-making on embryo transfer, fetal reduction, and mode of delivery were identified. Interviews were carried out with doctors in eighteen ART clinics, agents from four agencies, and fourteen surrogates. In aiming to fulfil the commissioning parents' demands, doctors were willing to go to the greatest extent possible in their medical practice. Autonomy and decision-making regarding choice of the number of embryos to transfer and the mode of delivery lay neither with commissioning parents nor surrogate mothers but mostly with doctors. In order to ensure higher success rates, surrogates faced the risk of multiple pregnancy and fetal reduction with little information regarding the risks involved. In the globalized market of commercial surrogacy in India, and with clinics compromising on ethics, there is an urgent need for formulation of regulative law for the clinical practice and maintenance of principles of reproductive ethics in order to ensure that the interests of surrogate mothers are safeguarded. PMID:26133889

  19. Thinking Processes in Social Workers' Use of a Clinical Decision Support System: A Qualitative Study

    ERIC Educational Resources Information Center

    Monnickendam, Menachem; Savaya, Riki; Waysman, Mark

    2005-01-01

    The authors examined the thinking processes in the use of a decision support system (DSS) by social workers in a human services agency to determine whether they used the system to improve their case reasoning. Information was obtained from in-depth interviews with eight social workers who used a DSS in their work and from content analysis of…

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

    PubMed

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

    2014-01-01

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

  1. Enabling health care decisionmaking through clinical decision support and knowledge management.

    PubMed Central

    Lobach, David; Sanders, Gillian D; Bright, Tiffani J; Wong, Anthony; Dhurjati, Ravi; Bristow, Erin; Bastian, Lori; Coeytaux, Remy; Samsa, Gregory; Hasselblad, Vic; Williams, John W; Wing, Liz; Musty, Michael; Kendrick, Amy S

    2012-01-01

    OBJECTIVES To catalogue study designs used to assess the clinical effectiveness of CDSSs and KMSs, to identify features that impact the success of CDSSs/KMSs, to document the impact of CDSSs/KMSs on outcomes, and to identify knowledge types that can be integrated into CDSSs/KMSs. DATA SOURCES MEDLINE(®), CINAHL(®), PsycINFO(®), and Web of Science(®). REVIEW METHODS We included studies published in English from January 1976 through December 2010. After screening titles and abstracts, full-text versions of articles were reviewed by two independent reviewers. Included articles were abstracted to evidence tables by two reviewers. Meta-analyses were performed for seven domains in which sufficient studies with common outcomes were included. RESULTS We identified 15,176 articles, from which 323 articles describing 311 unique studies including 160 reports on 148 randomized control trials (RCTs) were selected for inclusion. RCTs comprised 47.5 percent of the comparative studies on CDSSs/KMSs. Both commercially and locally developed CDSSs effectively improved health care process measures related to performing preventive services (n = 25; OR 1.42, 95% confidence interval [CI] 1.27 to 1.58), ordering clinical studies (n = 20; OR 1.72, 95% CI 1.47 to 2.00), and prescribing therapies (n = 46; OR 1.57, 95% CI 1.35 to 1.82). Fourteen CDSS/KMS features were assessed for correlation with success of CDSSs/KMSs across all endpoints. Meta-analyses identified six new success features: Integration with charting or order entry system. Promotion of action rather than inaction. No need for additional clinician data entry. Justification of decision support via research evidence. Local user involvement. Provision of decision support results to patients as well as providers. Three previously identified success features were confirmed: Automatic provision of decision support as part of clinician workflow. Provision of decision support at time and location of decisionmaking. Provision of a

  2. The xeroderma pigmentosum pathway: decision tree analysis of DNA quality.

    PubMed

    Naegeli, Hanspeter; Sugasawa, Kaoru

    2011-07-15

    The nucleotide excision repair (NER) system is a fundamental cellular stress response that uses only a handful of DNA binding factors, mutated in the cancer-prone syndrome xeroderma pigmentosum (XP), to detect an astounding diversity of bulky base lesions, including those induced by ultraviolet light, electrophilic chemicals, oxygen radicals and further genetic insults. Several of these XP proteins are characterized by a mediocre preference for damaged substrates over the native double helix but, intriguingly, none of them recognizes injured bases with sufficient selectivity to account for the very high precision of bulky lesion excision. Instead, substrate versatility as well as damage specificity and strand selectivity are achieved by a multistage quality control strategy whereby different subunits of the XP pathway, in succession, interrogate the DNA double helix for a distinct abnormality in its structural or dynamic parameters. Through this step-by-step filtering procedure, the XP proteins operate like a systematic decision making tool, generally known as decision tree analysis, to sort out rare damaged bases embedded in a vast excess of native DNA. The present review is focused on the mechanisms by which multiple XP subunits of the NER pathway contribute to the proposed decision tree analysis of DNA quality in eukaryotic cells. PMID:21684221

  3. The Aeronautical Data Link: Decision Framework for Architecture Analysis

    NASA Technical Reports Server (NTRS)

    Morris, A. Terry; Goode, Plesent W.

    2003-01-01

    A decision analytic approach that develops optimal data link architecture configuration and behavior to meet multiple conflicting objectives of concurrent and different airspace operations functions has previously been developed. The approach, premised on a formal taxonomic classification that correlates data link performance with operations requirements, information requirements, and implementing technologies, provides a coherent methodology for data link architectural analysis from top-down and bottom-up perspectives. This paper follows the previous research by providing more specific approaches for mapping and transitioning between the lower levels of the decision framework. The goal of the architectural analysis methodology is to assess the impact of specific architecture configurations and behaviors on the efficiency, capacity, and safety of operations. This necessarily involves understanding the various capabilities, system level performance issues and performance and interface concepts related to the conceptual purpose of the architecture and to the underlying data link technologies. Efficient and goal-directed data link architectural network configuration is conditioned on quantifying the risks and uncertainties associated with complex structural interface decisions. Deterministic and stochastic optimal design approaches will be discussed that maximize the effectiveness of architectural designs.

  4. Formative Evaluation of Clinician Experience with Integrating Family History-Based Clinical Decision Support into Clinical Practice

    PubMed Central

    Doerr, Megan; Edelman, Emily; Gabitzsch, Emily; Eng, Charis; Teng, Kathryn

    2014-01-01

    Family health history is a leading predictor of disease risk. Nonetheless, it is underutilized to guide care and, therefore, is ripe for health information technology intervention. To fill the family health history practice gap, Cleveland Clinic has developed a family health history collection and clinical decision support tool, MyFamily. This report describes the impact and process of implementing MyFamily into primary care, cancer survivorship and cancer genetics clinics. Ten providers participated in semi-structured interviews that were analyzed to identify opportunities for process improvement. Participants universally noted positive effects on patient care, including increases in quality, personalization of care and patient engagement. The impact on clinical workflow varied by practice setting, with differences observed in the ease of integration and the use of specific report elements. Tension between the length of the report and desired detail was appreciated. Barriers and facilitators to the process of implementation were noted, dominated by the theme of increased integration with the electronic medical record. These results fed real-time improvement cycles to reinforce clinician use. This model will be applied in future institutional efforts to integrate clinical genomic applications into practice and may be useful for other institutions considering the implementation of tools for personalizing medical management. PMID:25563219

  5. Toward image analysis and decision support for ultrasound technology.

    PubMed

    Crofts, Gillian; Padman, Rema; Maharaja, Nisha

    2013-01-01

    Ultrasound is a low cost and efficient method of detecting diseases and abnormalities in the body. Yet there is a lack of precision and reliability associated with the technology, partly due to the operator dependent nature of ultrasound scanning. When scanning is performed to an agreed protocol, ultrasound has been shown to be highly reliable. This research aims to minimize these limitations that arise during ultrasound training, scanning and reporting by developing and evaluating an image analysis and decision support system that can aid the decision making process. We hypothesize that this intervention will likely increase the role of ultrasound in diagnosis when compared with other imaging technologies, particularly in low resource settings. PMID:23920862

  6. Levels of Analysis in Mass Media Decision Making: A Taxonomy, Research Strategy, and Illustrative Data Analysis.

    ERIC Educational Resources Information Center

    Dimmick, John; Coit, Philip

    1982-01-01

    Presents a taxonomy of influences on decision making in mass media. Illustrates the use of the taxonomy and research strategy in a quantitative analysis of influences on the decision autonomy of reporters. Results indicate that reporters' experience plays the most important role in explaining their story selection/content autonomy. (PD)

  7. HUMAN HEALTH METRICS FOR ENVIRONMENTAL DECISION SUPPORT TOOLS: LESSONS FROM HEALTH ECONOMICS AND DECISION ANALYSIS

    EPA Science Inventory

    Decision makers using environmental decision support tools are often confronted with information that predicts a multitude of different human health effects due to environmental stressors. If these health effects need to be contrasted with costs or compared with alternative scena...

  8. An information theory analysis of spatial decisions in cognitive development

    PubMed Central

    Scott, Nicole M.; Sera, Maria D.; Georgopoulos, Apostolos P.

    2015-01-01

    Performance in a cognitive task can be considered as the outcome of a decision-making process operating across various knowledge domains or aspects of a single domain. Therefore, an analysis of these decisions in various tasks can shed light on the interplay and integration of these domains (or elements within a single domain) as they are associated with specific task characteristics. In this study, we applied an information theoretic approach to assess quantitatively the gain of knowledge across various elements of the cognitive domain of spatial, relational knowledge, as a function of development. Specifically, we examined changing spatial relational knowledge from ages 5 to 10 years. Our analyses consisted of a two-step process. First, we performed a hierarchical clustering analysis on the decisions made in 16 different tasks of spatial relational knowledge to determine which tasks were performed similarly at each age group as well as to discover how the tasks clustered together. We next used two measures of entropy to capture the gradual emergence of order in the development of relational knowledge. These measures of “cognitive entropy” were defined based on two independent aspects of chunking, namely (1) the number of clusters formed at each age group, and (2) the distribution of tasks across the clusters. We found that both measures of entropy decreased with age in a quadratic fashion and were positively and linearly correlated. The decrease in entropy and, therefore, gain of information during development was accompanied by improved performance. These results document, for the first time, the orderly and progressively structured “chunking” of decisions across the development of spatial relational reasoning and quantify this gain within a formal information-theoretic framework. PMID:25698915

  9. An information theory analysis of spatial decisions in cognitive development.

    PubMed

    Scott, Nicole M; Sera, Maria D; Georgopoulos, Apostolos P

    2015-01-01

    Performance in a cognitive task can be considered as the outcome of a decision-making process operating across various knowledge domains or aspects of a single domain. Therefore, an analysis of these decisions in various tasks can shed light on the interplay and integration of these domains (or elements within a single domain) as they are associated with specific task characteristics. In this study, we applied an information theoretic approach to assess quantitatively the gain of knowledge across various elements of the cognitive domain of spatial, relational knowledge, as a function of development. Specifically, we examined changing spatial relational knowledge from ages 5 to 10 years. Our analyses consisted of a two-step process. First, we performed a hierarchical clustering analysis on the decisions made in 16 different tasks of spatial relational knowledge to determine which tasks were performed similarly at each age group as well as to discover how the tasks clustered together. We next used two measures of entropy to capture the gradual emergence of order in the development of relational knowledge. These measures of "cognitive entropy" were defined based on two independent aspects of chunking, namely (1) the number of clusters formed at each age group, and (2) the distribution of tasks across the clusters. We found that both measures of entropy decreased with age in a quadratic fashion and were positively and linearly correlated. The decrease in entropy and, therefore, gain of information during development was accompanied by improved performance. These results document, for the first time, the orderly and progressively structured "chunking" of decisions across the development of spatial relational reasoning and quantify this gain within a formal information-theoretic framework.

  10. Is there a "magic" hemoglobin number? Clinical decision support promoting restrictive blood transfusion practices.

    PubMed

    Goodnough, Lawrence Tim; Shah, Neil

    2015-10-01

    Blood transfusion has been identified as one of the most frequently performed therapeutic procedures, with a significant percentage of transfusions identified to be inappropriate. Recent key clinical trials in adults have provided Level 1 evidence to support restrictive red blood cell (RBC) transfusion practices. However, some advocates have attempted to identify a "correct" Hb threshold for RBC transfusion; whereas others assert that management of anemia, including transfusion decisions, must take into account clinical patient variables, rather than simply one diagnostic laboratory test. The heterogeneity of guidelines for blood transfusion by a number of medical societies reflects this controversy. Clinical decision support (CDS) uses a Hb threshold number in a smart Best Practices Alert (BPA) upon physician order, to trigger a concurrent utilization self-review for whether blood transfusion therapy is appropriate. This review summarizes Level 1 evidence in seven key clinical trials in adults that support restrictive transfusion practices, along strategies made possible by CDS that have demonstrated value in improving blood utilization by promoting restrictive transfusion practices.

  11. Patient exposure in the basic science classroom enhances differential diagnosis formation and clinical decision-making.

    PubMed

    Peacock, Justin G; Grande, Joseph P

    2015-01-01

    Purpose. The authors proposed that introducing real patients into a pathology classroom early in medical education would help integrate fundamental principles and disease pathology with clinical presentation and medical history. Methods. Three patients with different pathologies described their history and presentation without revealing their diagnosis. Students were required to submit a differential diagnosis in writing, and then were able to ask questions to arrive at the correct diagnosis. Students were surveyed on the efficacy of patient-based learning. Results. Average student scores on the differential diagnosis assignments significantly improved 32% during the course. From the survey, 72% of students felt that patient encounters should be included in the pathology course next year. Seventy-four percent felt that the differential diagnosis assignments helped them develop clinical decision-making skills. Seventy-three percent felt that the experience helped them know what questions to ask patients. Eighty-six percent felt that they obtained a better understanding of patients' social and emotional challenges. Discussion. Having students work through the process of differential diagnosis formulation when encountering a real patient and their clinical presentation improved clinical decision-making skills and integrated fundamental concepts with disease pathology during a basic science pathology course.

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

    PubMed

    Edelen, Bonnie Gilbert; Bell, Alexandra Alice

    2011-08-01

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

  13. Students' stereotypes of patients as barriers to clinical decision-making.

    PubMed

    Johnson, S M; Kurtz, M E; Tomlinson, T; Howe, K R

    1986-09-01

    The ability to formulate quick, accurate clinical judgments is stressed in medical training. Speed is usually an asset when a physician sorts through his biomedical knowledge, but it is often a liability when the physician assesses the sociocultural context of a clinical encounter. At the Michigan State University College of Osteopathic Medicine, a study was designed which graphically illustrated to beginning students that unconscious sociocultural stereotypes may influence clinical decision-making. Three entering classes of students were shown a videotape depicting five simulated patients (attractive black woman, attractive white woman, professional man, middle-aged housewife, and elderly man), each presenting with the same physical complaint. Elements of positive and negative stereotypes were incorporated into each of the portrayals, and the students rated these patients on positive and negative characteristics. The results suggested that the students attributed both positive and negative characteristics to patients on the basis of irrelevant characteristics, such as attractiveness, and with little further justification for their attributions. Such stereotypic generalizations held by students may become barriers to the students' objective clinical decision-making.

  14. Genetic stratification in myeloid diseases: from risk assessment to clinical decision support tool.

    PubMed

    Ofran, Yishai

    2014-10-01

    Genetic aberrations have become a dominant factor in the stratification of myeloid malignancies. Cytogenetic and a few mutation studies are the backbone of risk assessment models of myeloid malignancies which are a major consideration in clinical decisions, especially patient assignment for allogeneic stem cell transplantation. Progress in our understanding of the genetic basis of the pathogenesis of myeloid malignancies and the growing capabilities of mass sequencing may add new roles for the clinical usage of genetic data. A few recently identified mutations recognized to be associated with specific diseases or clinical scenarios may soon become part of the diagnostic criteria of such conditions. Mutational studies may also advance our capabilities for a more efficient patient selection process, assigning the most effective therapy at the best timing for each patient. The clinical utility of genetic data is anticipated to advance further with the adoption of deep sequencing and next-generation sequencing techniques. We herein suggest some future potential applications of sequential genetic data to identify pending deteriorations at time points which are the best for aggressive interventions such as allogeneic stem cell transplantation. Genetics is moving from being mostly a prognostic factor to becoming a multitasking decision support tool for hematologists. Physicians must pay attention to advances in molecular hematology as it will soon be accessible and influential for most of our patients.

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

    PubMed

    Edwards, Ian; Richardson, Barbara

    2008-01-01

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

  16. A survey of the perceptions and behaviors of chiropractic interns pertaining to evidence-based principles in clinical decision making

    PubMed Central

    Dane, Dawn E.; Dane, Andrew B.; Crowther, Edward R.

    2016-01-01

    Objective: This study explored how chiropractic interns applied evidenced-based concepts, the sources of evidence they used, and how useful they perceived these sources to be in clinical decision making. Methods: A questionnaire containing 13 items in a Likert 5-point scale was administered to 28 chiropractic interns to gather information on the evidence types they commonly accessed and their perceived usefulness of these sources in clinical decision making. The interns were in the 8th semester of the training program. Results: There was a 93% (n = 26) response rate. Clinical guidelines were rated as the most helpful resource in clinical decision making (81%), followed by lecture materials (77%), journals (54%), databases (50%), and textbooks (35%). Students recognized scientific evidence as the most important aspect in clinical decision making. They found their personal experience and the views of their clinician to be equally important and patient preference the least. Conclusion: Interns routinely employed high-quality levels of evidence in clinical decision making. They also considered their early, limited clinical experience as important as that of their clinical supervisor in decision making. This finding should be investigated further. PMID:27389528

  17. Leadership Style, Decision Context, and the Poliheuristic Theory of Decision Making: An Experimental Analysis

    ERIC Educational Resources Information Center

    Keller, Jonathan W.; Yang, Yi Edward

    2008-01-01

    The poliheuristic (PH) theory of decision making has made important contributions to our understanding of political decision making but remains silent about certain key aspects of the decision process. Specifically, PH theory contends that leaders screen out politically unacceptable options, but it provides no guidance on (1) the crucial threshold…

  18. Derivation of Candidate Clinical Decision Rules to Identify Infants at Risk for Central Apnea

    PubMed Central

    Cunningham, Pádraig; Merchant, Sabrina; Walker, Nicholas; Heffner, Jacquelyn; Shanholtzer, Lucas; Rothenberg, Stephen J.

    2015-01-01

    BACKGROUND AND OBJECTIVES: Central apnea complicates, and may be the presenting complaint in, bronchiolitis. Our objective was to prospectively derive candidate clinical decision rules (CDRs) to identify infants in the emergency department (ED) who are at risk for central apnea. METHODS: We conducted a prospective observational study over 8 years. The primary outcome was central apnea subsequent to the initial ED visit. Infants were enrolled if they presented with central apnea or bronchiolitis. We excluded infants with obstructive apnea, neonatal jaundice, trauma, or suspected sepsis. We developed 3 candidate CDRs by using 3 techniques: (1) Poisson regression clustered on the individual, (2) classification and regression tree analysis (CART), and (3) a random forest (RF). RESULTS: We analyzed 990 ED visits for 892 infants. Central apnea subsequently occurred in the hospital in 41 (5%) patients. Parental report of apnea, previous history of apnea, congenital heart disease, birth weight ≤2.5 kg, lower weight, and age ≤6 weeks all identified a group at high risk for subsequent central apnea. All CDRs and RFs were 100% sensitive (95% confidence interval [CI] 91%–100%) and had a negative predictive value of 100% (95% CI 99%–100%) for the subsequent apnea. Specificity ranged from 61% to 65% (95% CI 58%–68%) for CDRs based on Poisson models; 65% to 77% (95% CI 62%–90%) for CART; and 81% to 91% (95% CI 78%–92%) for RF models. CONCLUSIONS: All candidate CDRs had a negative predictive value of 100% for subsequent central apnea. PMID:26482666

  19. Prioritizing groundwater remediation policies: a fuzzy compatibility analysis decision aid.

    PubMed

    Nasiri, Fuzhan; Huang, Gordon; Fuller, Norma

    2007-01-01

    The implementation of groundwater remediation strategies in contaminated areas includes not only a cost-benefit analysis and an environmental risk assessment but also another type of study called compatibility analysis. A compatibility analysis targets the interactions between remediation technologies and site characteristics, such as the types of active contaminants and their concentrations, soil composition and geological features, etc. The purpose of this analysis is to identify the most compatible remediation plan for the contaminated site. In this paper, we introduce a decision support system for the prioritization of remediation plans based on their estimated compatibility index. As this model receives data in terms of linguistic judgments and experts' opinions, we use fuzzy sets theory to deal with these uncertainties. First, we break down the concept of compatibility into the measurable factors. Then by using a multiple-attribute decision-making (MADM) outline, we compute a factorial, regional and overall compatibility indicator for each plan. Finally, by comparing these generated indicators, we rank the remediation policies.

  20. Medical informatics and clinical decision making: the science and the pragmatics.

    PubMed

    Shortliffe, E H

    1991-01-01

    There are important scientific and pragmatic synergies between the medical decision making field and the emerging discipline of medical informatics. In the 1970s, the field of medicine forced clinically oriented artificial intelligence (AI) researchers to develop ways to manage explicit statements of uncertainty in expert systems. Classic probability theory was considered and discussed, but it tended to be abandoned because of complexities that limited its use. In medical AI systems, uncertainty was handled by a variety of ad hoc models that simulated probabilistic considerations. To illustrate the scientific interactions between the fields, the author describes recent work in his laboratory that has attempted to show that formal normative models based on probability and decision theory can be practically melded with AI methods to deliver effective advisory tools. In addition, the practical needs of decision makers and health policy planners are increasingly necessitating collaborative efforts to develop a computing and communications infrastructure for the decision making and informatics communities. This point is illustrated with an example drawn from outcomes management research.

  1. The Utilization of a Clinical Decision Support System to Manage Adult Type 2 Diabetes: A Correlational Study

    ERIC Educational Resources Information Center

    Faught, I. Charie

    2012-01-01

    While the Institute of Medicine (2001) has promoted health information technology to improve the process of care such as compliance with clinical practice guidelines and quicker access to clinical information, diagnostic tests, and treatment results, very little was known about how a clinical decision support system can contribute to diabetes…

  2. ASSESSMENT OF UPPER EXTREMITY IMPAIRMENT, FUNCTION, AND ACTIVITY FOLLOWING STROKE: FOUNDATIONS FOR CLINICAL DECISION MAKING

    PubMed Central

    Lang, Catherine E.; Bland, Marghuretta D.; Bailey, Ryan R.; Schaefer, Sydney Y.; Birkenmeier, Rebecca L.

    2012-01-01

    The purpose of this review is to provide a comprehensive approach for assessing the upper extremity (UE) after stroke. First, common upper extremity impairments and how to assess them are briefly discussed. While multiple UE impairments are typically present after stroke, the severity of one impairment, paresis, is the primary determinant of UE functional loss. Second, UE function is operationally defined and a number of clinical measures are discussed. It is important to consider how impairment and loss of function affect UE activity outside of the clinical environment. Thus, this review also identifies accelerometry as an objective method for assessing UE activity in daily life. Finally, the role that each of these levels of assessment should play in clinical decision making is discussed in order to optimize the provision of stroke rehabilitation services. PMID:22975740

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

    PubMed Central

    2011-01-01

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

  4. A decision-theoretic framework for the application of cost-effectiveness analysis in regulatory processes.

    PubMed

    Baio, Gianluca; Russo, Pierluigi

    2009-01-01

    Cost-effectiveness analysis (CEA) represents the most important tool in the health economics literature to quantify and qualify the reasoning behind the optimal decision process in terms of the allocation of resources to a given health intervention. However, the practical application of CEA in the regulatory process is often limited by some critical barriers, and decisions in clinical practice are frequently influenced by factors that do not contribute to efficient resource allocation, leading to inappropriate drug prescription and utilization. Moreover, most of the time there is uncertainty about the real cost-effectiveness profile of an innovative intervention, with the consequence that it is usually impossible to obtain an immediate and perfect substitution of a product with another having a better cost-effectiveness ratio. The objective of this article is to propose a rational approach to CEA within regulatory processes, basing our analysis in a Bayesian decision-theoretic framework and proposing an extension of the application of well known tools (such as the expected value of information) to such cases. The regulator can use these tools to identify the economic value of reducing the uncertainty surrounding the cost-effectiveness profile of the several alternatives. This value can be compared with the one that is generated by the actual market share of the different treatment options: one that is the most cost effective and others in the same therapeutic category that, despite producing clinical benefits, are less cost effective.

  5. Soft Mathematical Aggregation in Safety Assessment and Decision Analysis

    SciTech Connect

    Cooper, J. Arlin

    1999-06-10

    This paper improves on some of the limitations of conventional safety assessment and decision analysis methods. It develops a top-down mathematical method for expressing imprecise individual metrics as possibilistic or fuzzy numbers and shows how they may be combined (aggregated) into an overall metric, also portraying the inherent uncertainty. Both positively contributing and negatively contributing factors are included. Metrics are weighted according to significance of the attribute and evaluated as to contribution toward the attribute. Aggregation is performed using exponential combination of the metrics, since the accumulating effect of such factors responds less and less to additional factors. This is termed soft mathematical aggregation. Dependence among the contributing factors is accounted for by incorporating subjective metrics on overlap of the factors and by correspondingly reducing the overall contribution of these combinations to the overall aggregation. Decisions corresponding to the meaningfulness of the results are facilitated in several ways. First, the results are compared to a soft threshold provided by a sigmoid function. Second, information is provided on input ''Importance'' and ''Sensitivity,'' in order to know where to place emphasis on controls that may be necessary. Third, trends in inputs and outputs are tracked in order to add important information to the decision process. The methodology has been implemented in software.

  6. Engaging stakeholders for adaptive management using structured decision analysis

    USGS Publications Warehouse

    Irwin, Elise R.; Kathryn, D.; Kennedy, Mickett

    2009-01-01

    Adaptive management is different from other types of management in that it includes all stakeholders (versus only policy makers) in the process, uses resource optimization techniques to evaluate competing objectives, and recognizes and attempts to reduce uncertainty inherent in natural resource systems. Management actions are negotiated by stakeholders, monitored results are compared to predictions of how the system should respond, and management strategies are adjusted in a “monitor-compare-adjust” iterative routine. Many adaptive management projects fail because of the lack of stakeholder identification, engagement, and continued involvement. Primary reasons for this vary but are usually related to either stakeholders not having ownership (or representation) in decision processes or disenfranchisement of stakeholders after adaptive management begins. We present an example in which stakeholders participated fully in adaptive management of a southeastern regulated river. Structured decision analysis was used to define management objectives and stakeholder values and to determine initial flow prescriptions. The process was transparent, and the visual nature of the modeling software allowed stakeholders to see how their interests and values were represented in the decision process. The development of a stakeholder governance structure and communication mechanism has been critical to the success of the project.

  7. Dynamic sensor action selection with Bayesian decision analysis

    NASA Astrophysics Data System (ADS)

    Kristensen, Steen; Hansen, Volker; Kondak, Konstantin

    1998-10-01

    The aim of this work is to create a framework for the dynamic planning of sensor actions for an autonomous mobile robot. The framework uses Bayesian decision analysis, i.e., a decision-theoretic method, to evaluate possible sensor actions and selecting the most appropriate ones given the available sensors and what is currently known about the state of the world. Since sensing changes the knowledge of the system and since the current state of the robot (task, position, etc.) determines what knowledge is relevant, the evaluation and selection of sensing actions is an on-going process that effectively determines the behavior of the robot. The framework has been implemented on a real mobile robot and has been proven to be able to control in real-time the sensor actions of the system. In current work we are investigating methods to reduce or automatically generate the necessary model information needed by the decision- theoretic method to select the appropriate sensor actions.

  8. Perforated mucinous cystadenoma of the vermiform appendix: an overview in reasoning clinical decisions

    PubMed Central

    Papadopoulos, Iordanis N; Christodoulou, Spyridon; Kokoropoulos, Panayiotis; Konstantudakis, George; Economopoulos, Nikolaos; Leontara, Vassilia

    2011-01-01

    Recent advances in the management of appendiceal mucinous neoplasms (AMN) such as peritonectomy combined with hyperthermic intraperitoneal chemotherapy have introduced new standards of care. However, many dilemmas are encountered in decision making as in the following patient. A 74-year-old woman was admitted with an appendiceal cystadenoma found in a preadmission CT scan. However, the tumour was not documented by the in hospital investigation due to its perforation and its reduction in size. Consequently, a series of management dilemmas were encountered that were solved by cautious evaluation of the pre and peroperative findings. She was submitted to a right hemicolectomy. A spontaneous perforation was suspected, but the accurate diagnosis was documented postoperatively by histopathology. This paradigm motivated this review which concluded that reasoning clinical decisions in the light of recent advances and appropriate care based on the disease-stage are essential for an optimal outcome in the management of AMN. PMID:22689271

  9. Constructing Clinical Decision Support Systems for Adverse Drug Event Prevention: A Knowledge-based Approach.

    PubMed

    Koutkias, Vassilis; Kilintzis, Vassilis; Stalidis, George; Lazou, Katerina; Collyda, Chrysa; Chazard, Emmanuel; McNair, Peter; Beuscart, Regis; Maglaveras, Nicos

    2010-11-13

    A knowledge-based approach is proposed that is employed for the construction of a framework suitable for the management and effective use of knowledge on Adverse Drug Event (ADE) prevention. The framework has as its core part a Knowledge Base (KB) comprised of rule-based knowledge sources, that is accompanied by the necessary inference and query mechanisms to provide healthcare professionals and patients with decision support services in clinical practice, in terms of alerts and recommendations on preventable ADEs. The relevant Knowledge Based System (KBS) is developed in the context of the EU-funded research project PSIP (Patient Safety through Intelligent Procedures in Medication). In the current paper, we present the foundations of the framework, its knowledge model and KB structure, as well as recent progress as regards the population of the KB, the implementation of the KBS, and results on the KBS verification in decision support operation.

  10. Patient electronic health data-driven approach to clinical decision support.

    PubMed

    Mane, Ketan K; Bizon, Chris; Owen, Phillips; Gersing, Ken; Mostafa, Javed; Schmitt, Charles

    2011-10-01

    This article presents a novel visual analytics (VA)-based clinical decision support (CDS) tool prototype that was designed as a collaborative work between Renaissance Computing Institute and Duke University. Using Major Depressive Disorder data from MindLinc electronic health record system at Duke, the CDS tool shows an approach to leverage data from comparative population (patients with similar medical profile) to enhance a clinicians' decision making process at the point of care. The initial work is being extended in collaboration with the University of North Carolina CTSA to address the key challenges of CDS, as well as to show the use of VA to derive insight from large volumes of Electronic Health Record patient data.

  11. Markov Modeling with Soft Aggregation for Safety and Decision Analysis

    SciTech Connect

    COOPER,J. ARLIN

    1999-09-01

    The methodology in this report improves on some of the limitations of many conventional safety assessment and decision analysis methods. A top-down mathematical approach is developed for decomposing systems and for expressing imprecise individual metrics as possibilistic or fuzzy numbers. A ''Markov-like'' model is developed that facilitates combining (aggregating) inputs into overall metrics and decision aids, also portraying the inherent uncertainty. A major goal of Markov modeling is to help convey the top-down system perspective. One of the constituent methodologies allows metrics to be weighted according to significance of the attribute and aggregated nonlinearly as to contribution. This aggregation is performed using exponential combination of the metrics, since the accumulating effect of such factors responds less and less to additional factors. This is termed ''soft'' mathematical aggregation. Dependence among the contributing factors is accounted for by incorporating subjective metrics on ''overlap'' of the factors as well as by correspondingly reducing the overall contribution of these combinations to the overall aggregation. Decisions corresponding to the meaningfulness of the results are facilitated in several ways. First, the results are compared to a soft threshold provided by a sigmoid function. Second, information is provided on input ''Importance'' and ''Sensitivity,'' in order to know where to place emphasis on considering new controls that may be necessary. Third, trends in inputs and outputs are tracked in order to obtain significant information% including cyclic information for the decision process. A practical example from the air transportation industry is used to demonstrate application of the methodology. Illustrations are given for developing a structure (along with recommended inputs and weights) for air transportation oversight at three different levels, for developing and using cycle information, for developing Importance and

  12. Fuzzy Multicriteria Decision Analysis for Adaptive Watershed Management

    NASA Astrophysics Data System (ADS)

    Chang, N.

    2006-12-01

    The dramatic changes of societal complexity due to intensive interactions among agricultural, industrial, and municipal sectors have resulted in acute issues of water resources redistribution and water quality management in many river basins. Given the fact that integrated watershed management is more a political and societal than a technical challenge, there is a need for developing a compelling method leading to justify a water-based land use program in some critical regions. Adaptive watershed management is viewed as an indispensable tool nowadays for providing step-wise constructive decision support that is concerned with all related aspects of the water consumption cycle and those facilities affecting water quality and quantity temporally and spatially. Yet the greatest challenge that decision makers face today is to consider how to leverage ambiguity, paradox, and uncertainty to their competitive advantage of management policy quantitatively. This paper explores a fuzzy multicriteria evaluation method for water resources redistribution and subsequent water quality management with respect to a multipurpose channel-reservoir system--the Tseng- Wen River Basin, South Taiwan. Four fuzzy operators tailored for this fuzzy multicriteria decision analysis depict greater flexibility in representing the complexity of various possible trade-offs among management alternatives constrained by physical, economic, and technical factors essential for adaptive watershed management. The management strategies derived may enable decision makers to integrate a vast number of internal weirs, water intakes, reservoirs, drainage ditches, transfer pipelines, and wastewater treatment facilities within the basin and bring up the permitting issue for transboundary diversion from a neighboring river basin. Experience gained indicates that the use of different types of fuzzy operators is highly instructive, which also provide unique guidance collectively for achieving the overarching goals

  13. Choices, choices: the application of multi-criteria decision analysis to a food safety decision-making problem.

    PubMed

    Fazil, A; Rajic, A; Sanchez, J; McEwen, S

    2008-11-01

    In the food safety arena, the decision-making process can be especially difficult. Decision makers are often faced with social and fiscal pressures when attempting to identify an appropriate balance among several choices. Concurrently, policy and decision makers in microbial food safety are under increasing pressure to demonstrate that their policies and decisions are made using transparent and accountable processes. In this article, we present a multi-criteria decision analysis approach that can be used to address the problem of trying to select a food safety intervention while balancing various criteria. Criteria that are important when selecting an intervention were determined, as a result of an expert consultation, to include effectiveness, cost, weight of evidence, and practicality associated with the interventions. The multi-criteria decision analysis approach we present is able to consider these criteria and arrive at a ranking of interventions. It can also provide a clear justification for the ranking as well as demonstrate to stakeholders, through a scenario analysis approach, how to potentially converge toward common ground. While this article focuses on the problem of selecting food safety interventions, the range of applications in the food safety arena is truly diverse and can be a significant tool in assisting decisions that need to be coherent, transparent, and justifiable. Most importantly, it is a significant contributor when there is a need to strike a fine balance between various potentially competing alternatives and/or stakeholder groups.

  14. Application of decision tree on land suitability analysis

    NASA Astrophysics Data System (ADS)

    Hou, Yajuan; Liu, Yaolin; Ren, Zhouqiao

    2008-12-01

    With increasing volume of data in modern science, there has been a rapid expansion of interests and researches on data mining, which is an increasingly popular tool in data analysis to obtain implicit knowledge. Decision Tree (DT), as one of widespread used classification approaches in data mining, is used successfully in many diverse areas. This paper attempts to show how to apply Decision Tree on land suitability analysis and make some conclusions for its application. Firstly, the approach of application of DT on Land Suitability and the popular learning algorithm is discussed. Then 3 towns' land units in Hainan province are selected as study case to demonstrate our approach by C4.5 implemented using C++ language, and the obtained results are compared to the results in the literature and are checked by random sample investigation. The major conclusion is that DT is suitable for land suitability analysis, by which a high veracity result can be obtained, and the obtained classifying knowledge is readable and can be interpreted well. In some sense, it can adjust knowledge by updated training dataset naturally and avoid the highly dependence with experience.

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

    PubMed

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

    2015-01-01

    One of the proposals for improving clinical practice is to introduce computerised decision support systems (CDSS) and integrate these with electronic medical records. Accordingly, this study sought to systematically review evidence on the effectiveness of CDSS in the management of depression. A search was performed in Medline, EMBASE and PsycInfo, in order to do this. The quality of quantitative studies was assessed using the SIGN method, and qualitative studies using the CASPe checklist. Seven studies were identified (3 randomised clinical trials, 3 non-randomised trials, and one qualitative study). The CDSS assessed incorporated content drawn from guidelines and other evidence-based products. In general, the CDSS had a positive impact on different aspects, such as the screening and diagnosis, treatment, improvement in depressive symptoms and quality of life, and referral of patients. The use of CDSS could thus serve to optimise care of depression in various scenarios by providing recommendations based on the best evidence available and facilitating decision-making in clinical practice. PMID:25500093

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

    PubMed

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

    2015-01-01

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

  17. An exploratory study of the sources of influence on the clinical decisions of community nurses.

    PubMed

    Luker, K A; Kenrick, M

    1992-04-01

    This paper reports a small exploratory study which identifies what community nurses consider to be the scope of their practice and the sources of influence on their clinical decisions. The study was stimulated by the emergence of the nurse prescribing initiative, which is likely to bring clinical decision making to the centre of professional debate. The study was carried out over a 5-month period and data were collected from 47 community nurses in four district health authorities. A qualitative method was employed and field work involved observation of 40 home visits and five nurse-run clinics, individual interviews and group discussions with the nurses, and scrutiny of nursing records. The data were content analysed and classified, and the categories were validated by practitioners. Findings suggest that although community nurses consider that a large proportion of their work requires a scientific basis, their practice is largely founded on experiential knowledge, and on the whole they are not positively disposed to research knowledge. The findings are discussed in the context of nurse prescribing. Questions are raised about the nature of a 'professional' knowledge base and the reclassification of scientific knowledge as nursing or experiential knowledge once it has diffused into practice.

  18. A diagnosis-based clinical decision rule for spinal pain part 2: review of the literature

    PubMed Central

    Murphy, Donald R; Hurwitz, Eric L; Nelson, Craig F

    2008-01-01

    Background Spinal pain is a common and often disabling problem. The research on various treatments for spinal pain has, for the most part, suggested that while several interventions have demonstrated mild to moderate short-term benefit, no single treatment has a major impact on either pain or disability. There is great need for more accurate diagnosis in patients with spinal pain. In a previous paper, the theoretical model of a diagnosis-based clinical decision rule was presented. The approach is designed to provide the clinician with a strategy for arriving at a specific working diagnosis from which treatment decisions can be made. It is based on three questions of diagnosis. In the current paper, the literature on the reliability and validity of the assessment procedures that are included in the diagnosis-based clinical decision rule is presented. Methods The databases of Medline, Cinahl, Embase and MANTIS were searched for studies that evaluated the reliability and validity of clinic-based diagnostic procedures for patients with spinal pain that have relevance for questions 2 (which investigates characteristics of the pain source) and 3 (which investigates perpetuating factors of the pain experience). In addition, the reference list of identified papers and authors' libraries were searched. Results A total of 1769 articles were retrieved, of which 138 were deemed relevant. Fifty-one studies related to reliability and 76 related to validity. One study evaluated both reliability and validity. Conclusion Regarding some aspects of the DBCDR, there are a number of studies that allow the clinician to have a reasonable degree of confidence in his or her findings. This is particularly true for centralization signs, neurodynamic signs and psychological perpetuating factors. There are other aspects of the DBCDR in which a lesser degree of confidence is warranted, and in which further research is needed. PMID:18694490

  19. Recommendations for Selecting Drug-Drug Interactions for Clinical Decision Support

    PubMed Central

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

    2016-01-01

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

  20. Systematic review of clinical decision support interventions with potential for inpatient cost reduction

    PubMed Central

    2013-01-01

    Background Healthcare costs are increasing rapidly and at an unsustainable rate in many countries, and inpatient hospitalizations are a significant driver of these costs. Clinical decision support (CDS) represents a promising approach to not only improve care but to reduce costs in the inpatient setting. The purpose of this study was to systematically review trials of CDS interventions with the potential to reduce inpatient costs, so as to identify promising interventions for more widespread implementation and to inform future research in this area. Methods To identify relevant studies, MEDLINE was searched up to July 2013. CDS intervention studies with the potential to reduce inpatient healthcare costs were identified through titles and abstracts, and full text articles were reviewed to make a final determination on inclusion. Relevant characteristics of the studies were extracted and summarized. Results Following a screening of 7,663 articles, 78 manuscripts were included. 78.2% of studies were controlled before-after studies, and 15.4% were randomized controlled trials. 53.8% of the studies were focused on pharmacotherapy. The majority of manuscripts were published during or after 2008. 70.5% of the studies resulted in statistically and clinically significant improvements in an explicit financial measure or a proxy financial measure. Only 12.8% of the studies directly measured the financial impact of an intervention, whereas the financial impact was inferred in the remainder of studies. Data on cost effectiveness was available for only one study. Conclusions Significantly more research is required on the impact of clinical decision support on inpatient costs. In particular, there is a remarkable gap in the availability of cost effectiveness studies required by policy makers and decision makers in healthcare systems. PMID:24344752

  1. Multisite Exploration of Clinical Decision-Making for Antibiotic Use by Emergency Medicine Providers Using Quantitative and Qualitative Methods

    PubMed Central

    Gudger, Glencora; Armstrong, Paige; Brooks, Gillian; Hinds, Pamela; Bhat, Rahul; Moran, Gregory J.; Schwartz, Lisa; Cosgrove, Sara E.; Klein, Eili Y.; Rothman, Richard E.; Rand, Cynthia

    2016-01-01

    Objectives To explore current practices and decision-making regarding antimicrobial prescribing among Emergency Department (ED) clinical providers. Methods We conducted a survey of ED providers recruited from eight sites in three cities. Using purposeful sampling, we then recruited 21 providers for in-depth interviews. Additionally, we observed ten patient-provider interactions at one of the ED sites. SAS 9.3 was used for descriptive and predictive statistics. Interviews were audio-recorded, transcribed and analyzed using a thematic, constructivist approach with consensus coding using NVivo 10.0. Field and interview notes collected during the observational study were aligned with themes identified through individual interviews. Results Of 150 survey respondents, 76% agreed or strongly agreed antibiotics are overused in the ED, while half believed they personally did not overprescribe. Eighty nine percent used a smartphone or tablet in the ED for antibiotic prescribing decisions. Several significant differences were found between attending and resident physicians. Interview analysis identified 42 codes aggregated into the following themes: (1) resource and environmental factors that affect care; (2) access to and quality of care received outside of the ED consult; (3) patient-provider relationships; (4) clinical inertia; and (5) local knowledge generation. The observational study revealed limited patient understanding of antibiotic use. Providers relied heavily upon diagnostics and provided limited education to patients. Most patients denied a priori expectations of being prescribed antibiotics. Conclusions Patient, provider, and healthcare system factors should be considered when designing interventions to improve antimicrobial stewardship in the ED setting. PMID:25111919

  2. Development and validation of a tool to measure self-confidence and anxiety in nursing students during clinical decision making.

    PubMed

    White, Krista A

    2014-01-01

    Clinical decision making (CDM) is a cornerstone skill for nurses. Self-confidence and anxiety affect the learning and adeptness of CDM. This study aimed to develop and test a quantitative tool to assess undergraduate nursing students' self-confidence and anxiety during CDM. The 27-item Nursing Anxiety and Self-Confidence with Clinical Decision Making (NASC-CDM) scale is a 6-point, Likert-type tool with two subscales. Two samples of prelicensure associate and baccalaureate nursing students participated in the pilot (n = 303) and main testing (n = 242) phases of the study. Construct validity assessment, using exploratory factor analysis, produced a stable three-dimensional scale. Convergent validity assessment produced positive, moderate, and statistically significant correlations of the tool sub-scales with two existing instruments. Internal consistency reliability was assessed for each subscale (self-confidence, α = .97; anxiety, α = .96). The NASC-CDM scale may be a useful assessment tool for nurse educators to help novice clinicians improve CDM skills.

  3. Composite tissue allotransplantation of the face: Decision analysis model

    PubMed Central

    Cugno, Sabrina; Sprague, Sheila; Duku, Eric; Thoma, Achilleas

    2007-01-01

    BACKGROUND: Facial composite tissue allotransplantation is a potential reconstructive option for severe facial disfigurement. The purpose of the present investigation was to use decision analysis modelling to ascertain the expected quality-adjusted life years (QALYs) gained with face transplantation (versus remaining in a disfigured state) in an effort to assist surgeons with the decision of whether to adopt this procedure. STUDY DESIGN: The probabilities of potential complications associated with facial allotransplantation were identified by a comprehensive review of kidney and hand transplant literature. A decision analysis tree illustrating possible health states for face allotransplantation was then constructed. Utilities were obtained from 30 participants, using the standard gamble and time trade-off measures. The utilities were then translated into QALYs, and the expected QALYs gained with transplantation were computed. RESULTS: Severe facial deformity was associated with an average of 7.34 QALYs. Allotransplantation of the face imparted an expected gain in QALYs of between 16.2 and 27.3 years. CONCLUSIONS: The current debate within the medical community surrounding facial composite tissue allotransplantation has centred on the issue of inducing a state of immunocompromise in a physically healthy individual for a non-life-saving procedure. However, the latter must be weighed against the potential social and psychological benefits that transplantation would confer. As demonstrated by a gain of 26.9 QALYs, participants’ valuation of quality of life is notably greater for face transplantation with its side effects of immunosuppression than for a state of uncompromised physical health with severe facial disfigurement. PMID:19554146

  4. Mobile Clinical Decision Support Systems in Our Hands - Great Potential but also a Concern.

    PubMed

    Masic, Izet; Begic, Edin

    2016-01-01

    Due to the powerful computer resources as well as the availability of today's mobile devices, a special field of mobile systems for clinical decision support in medicine has been developed. The benefits of these applications (systems) are: availability of necessary hardware (mobile phones, tablets and phablets are widespread, and can be purchased at a relatively affordable price), availability of mobile applications (free or for a "small" amount of money) and also mobile applications are tailored for easy use and save time of clinicians in their daily work. In these systems lies a huge potential, and certainly a great economic benefit, so this issue must be approached multidisciplinary. PMID:27350467

  5. Performance of online drug information databases as clinical decision support tools in infectious disease medication management.

    PubMed

    Polen, Hyla H; Zapantis, Antonia; Clauson, Kevin A; Clauson, Kevin Alan; Jebrock, Jennifer; Paris, Mark

    2008-01-01

    Infectious disease (ID) medication management is complex and clinical decision support tools (CDSTs) can provide valuable assistance. This study evaluated scope and completeness of ID drug information found in online databases by evaluating their ability to answer 147 question/answer pairs. Scope scores produced highest rankings (%) for: Micromedex (82.3), Lexi-Comp/American Hospital Formulary Service (81.0), and Medscape Drug Reference (81.0); lowest includes: Epocrates Online Premium (47.0), Johns Hopkins ABX Guide (45.6), and PEPID PDC (40.8). PMID:18999059

  6. Mobile Clinical Decision Support Systems in Our Hands - Great Potential but also a Concern.

    PubMed

    Masic, Izet; Begic, Edin

    2016-01-01

    Due to the powerful computer resources as well as the availability of today's mobile devices, a special field of mobile systems for clinical decision support in medicine has been developed. The benefits of these applications (systems) are: availability of necessary hardware (mobile phones, tablets and phablets are widespread, and can be purchased at a relatively affordable price), availability of mobile applications (free or for a "small" amount of money) and also mobile applications are tailored for easy use and save time of clinicians in their daily work. In these systems lies a huge potential, and certainly a great economic benefit, so this issue must be approached multidisciplinary.

  7. Laboratory Medicine in the Clinical Decision Support for Treatment of Hypercholesterolemia: Pharmacogenetics of Statins.

    PubMed

    Ruaño, Gualberto; Seip, Richard; Windemuth, Andreas; Wu, Alan H B; Thompson, Paul D

    2016-09-01

    Statin responsiveness is an area of great research interest given the success of the drug class in the treatment of hypercholesterolemia and in primary and secondary prevention of cardiovascular disease. Interrogation of the patient's genome for gene variants will eventually guide anti-hyperlipidemic intervention. In this review, we discuss methodological approaches to discover genetic markers predictive of class-wide and drug-specific statin efficacy and safety. Notable pharmacogenetic findings are summarized from hypothesis-free genome wide and hypothesis-led candidate gene association studies. Physiogenomic models and clinical decision support systems will be required for DNA-guided statin therapy to reach practical use in medicine. PMID:27514463

  8. Laboratory Medicine in the Clinical Decision Support for Treatment of Hypercholesterolemia: Pharmacogenetics of Statins.

    PubMed

    Ruaño, Gualberto; Seip, Richard; Windemuth, Andreas; Wu, Alan H B; Thompson, Paul D

    2016-09-01

    Statin responsiveness is an area of great research interest given the success of the drug class in the treatment of hypercholesterolemia and in primary and secondary prevention of cardiovascular disease. Interrogation of the patient's genome for gene variants will eventually guide anti-hyperlipidemic intervention. In this review, we discuss methodological approaches to discover genetic markers predictive of class-wide and drug-specific statin efficacy and safety. Notable pharmacogenetic findings are summarized from hypothesis-free genome wide and hypothesis-led candidate gene association studies. Physiogenomic models and clinical decision support systems will be required for DNA-guided statin therapy to reach practical use in medicine.

  9. Magnetic resonance imaging of the vagina: an overview for radiologists with emphasis on clinical decision making*

    PubMed Central

    Ferreira, Daian Miranda; Bezerra, Régis Otaviano França; Ortega, Cinthia Denise; Blasbalg, Roberto; Viana, Públio César Cavalcante; de Menezes, Marcos Roberto; Rocha, Manoel de Souza

    2015-01-01

    Magnetic resonance imaging is a method with high contrast resolution widely used in the assessment of pelvic gynecological diseases. However, the potential of such method to diagnose vaginal lesions is still underestimated, probably due to the scarce literature approaching the theme, the poor familiarity of radiologists with vaginal diseases, some of them relatively rare, and to the many peculiarities involved in the assessment of the vagina. Thus, the authors illustrate the role of magnetic resonance imaging in the evaluation of vaginal diseases and the main relevant findings to be considered in the clinical decision making process. PMID:26379324

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed Central

    2010-01-01

    Background Computerized clinical decision support systems are information technology-based systems designed to improve clinical decision-making. As with any healthcare intervention with claims to improve process of care or patient outcomes, decision support systems should be rigorously evaluated before widespread dissemination into clinical practice. Engaging healthcare providers and managers in the review process may facilitate knowledge translation and uptake. The objective of this research was to form a partnership of healthcare providers, managers, and researchers to review randomized controlled trials assessing the effects of computerized decision support for six clinical application areas: primary preventive care, therapeutic drug monitoring and dosing, drug prescribing, chronic disease management, diagnostic test ordering and interpretation, and acute care management; and to identify study characteristics that predict benefit. Methods The review was undertaken by the Health Information Research Unit, McMaster University, in partnership with Hamilton Health Sciences, the Hamilton, Niagara, Haldimand, and Brant Local Health Integration Network, and pertinent healthcare service teams. Following agreement on information needs and interests with decision-makers, our earlier systematic review was updated by searching Medline, EMBASE, EBM Review databases, and Inspec, and reviewing reference lists through 6 January 2010. Data extraction items were expanded according to input from decision-makers. Authors of primary studies were contacted to confirm data and to provide additional information. Eligible trials were organized according to clinical area of application. We included randomized controlled trials that evaluated the effect on practitioner performance or patient outcomes of patient care provided with a computerized clinical decision support system compared with patient care without such a system. Results Data will be summarized using descriptive summary

  12. The Nijmegen Decision Tool for Chronic Low Back Pain. Development of a Clinical Decision Tool for Secondary or Tertiary Spine Care Specialists

    PubMed Central

    van Hooff, Miranda L.; van Loon, Jan; van Limbeek, Jacques; de Kleuver, Marinus

    2014-01-01

    Background In Western Europe, low back pain has the greatest burden of all diseases. When back pain persists, different medical specialists are involved and a lack of consensus exists among these specialists for medical decision-making in Chronic Low Back Pain (CLBP). Objective To develop a decision tool for secondary or tertiary spine care specialists to decide which patients with CLBP should be seen by a spine surgeon or by other non-surgical medical specialists. Methods A Delphi study was performed to identify indicators predicting the outcome of interventions. In the preparatory stage evidence from international guidelines and literature were summarized. Eligible studies were reviews and longitudinal studies. Inclusion criteria: surgical or non-surgical interventions and persistence of complaints, CLBP-patients aged 18–65 years, reported baseline measures of predictive indicators, and one or more reported outcomes had to assess functional status, quality of life, pain intensity, employment status or a composite score. Subsequently, a three-round Delphi procedure, to reach consensus on candidate indicators, was performed among a multidisciplinary panel of 29 CLBP-professionals (>five years CLBP-experience). The pre-set threshold for general agreement was ≥70%. The final indicator set was used to develop a clinical decision tool. Results A draft list with 53 candidate indicators (38 with conclusive evidence and 15 with inconclusive evidence) was included for the Delphi study. Consensus was reached to include 47 indicators. A first version of the decision tool was developed, consisting of a web-based screening questionnaire and a provisional decision algorithm. Conclusions This is the first clinical decision tool based on current scientific evidence and formal multidisciplinary consensus that helps referring the patient for consultation to a spine surgeon or a non-surgical spine care specialist. We expect that this tool considerably helps in clinical decision

  13. Analysis of medical-decision making and the use of standards of care in oncology.

    PubMed Central

    Holzer, S.; Fremgen, A. M.; Hundahl, S. A.; Dudeck, J.

    2000-01-01

    Guidelines in medicine have been proposed as a way to assist physicians in the clinical decision-making process. Increasingly, they form the basis for assessing accountability in the delivery of healthcare services. However, experiences with their evaluation, as the most important step in the continuous guidelines process, are rare. Patient Care Evaluation Studies have been developed by the Commission on Cancer in the United States. As they reflect the "real-world" medical practice they are helpful in evaluating the quality of diagnosis, therapy and follow-up of tumor diseases in hospitals and cancer center and the compliance with current standards of care. In this context, they can provide an infrastructure for the analysis of the decision-making process. PMID:11079906

  14. Recruiting faculty with clinical responsibilities: factors that influence a decision to accept an academic position.

    PubMed

    Grauer, Gregory F

    2005-01-01

    The current opportunities for veterinary clinical specialists in private practice and industry have made recruiting and retaining faculty a major focus for most clinical academic departments. To gain a better understanding of the importance of the various factors considered in accepting an academic position, an electronic survey was distributed to newly hired veterinary faculty with clinical responsibilities. The results suggest that the perceived climate and collegiality within the prospective hiring department is the most important factor influencing the decision to accept an academic position. Salary is the second most important factor. Institutional support for the newly hired faculty member and the reputation and quality of the prospective institution rank as more important than the perceived quality of the local community and the geographic location of the institution. The search process and administrative support are the least important factors. There were no differences between the responses of faculty hired into tenure-track positions and those of faculty hired into clinical-track positions. Focusing on the advantages of a collegial environment, enhancing compensation packages, and using creative and flexible appointments may improve faculty recruitment and retention in clinical academic departments.

  15. Shared Decision-Making Models Acknowledging an Interprofessional Approach: A Theory Analysis to Inform Nursing Practice.

    PubMed

    Lewis, Krystina B; Stacey, Dawn; Squires, Janet E; Carroll, Sandra

    2016-01-01

    Patient engagement in collaboration with health professionals is essential to deliver quality health care. A shared decision-making (SDM) approach requires that patients are involved in decisions regarding their health. SDM is expanding from the patient-physician dyad to incorporate an interprofessional perspective. Conceptual models can be used to better understand theoretical underpinnings for application in clinical practice. The aim of this article was to conduct a theory analysis of conceptual models using an interprofessional approach to SDM and discuss each model's relevance to nursing practice. Walker and Avant's theory analysis approach was used. Three conceptual models were eligible. For all models, the decision-making process was considered iterative. The development process was described for 1 model. All models were logical, parsimonious, and generalizable. One was supported by empirical testing. No model described how partnerships are enacted to achieve interprofessional SDM. Also, there was limited articulation as to how nurses' roles and contributions differ from other team members. This theory analysis highlights the need for a model that explains how partnerships among interprofessional team members are enacted to better understand the operationalization of interprofessional SDM. Implications for nursing practice at all system levels are offered and supported by the 3 models. PMID:27024998

  16. Shared Decision-Making Models Acknowledging an Interprofessional Approach: A Theory Analysis to Inform Nursing Practice.

    PubMed

    Lewis, Krystina B; Stacey, Dawn; Squires, Janet E; Carroll, Sandra

    2016-01-01

    Patient engagement in collaboration with health professionals is essential to deliver quality health care. A shared decision-making (SDM) approach requires that patients are involved in decisions regarding their health. SDM is expanding from the patient-physician dyad to incorporate an interprofessional perspective. Conceptual models can be used to better understand theoretical underpinnings for application in clinical practice. The aim of this article was to conduct a theory analysis of conceptual models using an interprofessional approach to SDM and discuss each model's relevance to nursing practice. Walker and Avant's theory analysis approach was used. Three conceptual models were eligible. For all models, the decision-making process was considered iterative. The development process was described for 1 model. All models were logical, parsimonious, and generalizable. One was supported by empirical testing. No model described how partnerships are enacted to achieve interprofessional SDM. Also, there was limited articulation as to how nurses' roles and contributions differ from other team members. This theory analysis highlights the need for a model that explains how partnerships among interprofessional team members are enacted to better understand the operationalization of interprofessional SDM. Implications for nursing practice at all system levels are offered and supported by the 3 models.

  17. Trustworthy patient decision aids: a qualitative analysis addressing the risk of competing interests

    PubMed Central

    Elwyn, Glyn; Dannenberg, Michelle; Blaine, Arianna; Poddar, Urbashi; Durand, Marie-Anne

    2016-01-01

    Objective Our aim in this study was to examine the competing interest policies and procedures of organisations who develop and maintain patient decision aids. Design Descriptive and thematic analysis of data collected from a cross-sectional survey of patient decision aid developer's competing interest policies and disclosure forms. Results We contacted 25 organisations likely to meet the inclusion criteria. 12 eligible organisations provided data. 11 organisations did not reply and 2 declined to participate. Most patient decision aid developers recognise the need to consider the issue of competing interests. Assessment processes vary widely and, for the most part, are insufficiently robust to minimise the risk of competing interests. Only half of the 12 organisations had competing interest policies. Some considered disclosure to be sufficient, while others imposed differing levels of exclusion. Conclusions Patient decision aid developers do not have a consistent approach to managing competing interests. Some have developed policies and procedures, while others pay no attention to the issue. As is the case for clinical practice guidelines, increasing attention will need to be given to how the competing interests of contributors of evidence-based publications may influence materials, especially if they are designed for patient use. PMID:27612542

  18. Spaceborne power systems preference analyses. Volume 2: Decision analysis

    NASA Technical Reports Server (NTRS)

    Smith, J. H.; Feinberg, A.; Miles, R. F., Jr.

    1985-01-01

    Sixteen alternative spaceborne nuclear power system concepts were ranked using multiattribute decision analysis. The purpose of the ranking was to identify promising concepts for further technology development and the issues associated with such development. Four groups were interviewed to obtain preference. The four groups were: safety, systems definition and design, technology assessment, and mission analysis. The highest ranked systems were the heat-pipe thermoelectric systems, heat-pipe Stirling, in-core thermionic, and liquid-metal thermoelectric systems. The next group contained the liquid-metal Stirling, heat-pipe Alkali Metal Thermoelectric Converter (AMTEC), heat-pipe Brayton, liquid-metal out-of-core thermionic, and heat-pipe Rankine systems. The least preferred systems were the liquid-metal AMTEC, heat-pipe thermophotovoltaic, liquid-metal Brayton and Rankine, and gas-cooled Brayton. The three nonheat-pipe technologies selected matched the top three nonheat-pipe systems ranked by this study.

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

    PubMed Central

    2013-01-01

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

  20. Clinical Growth: An Evolutionary Concept Analysis.

    PubMed

    Barkimer, Jessica

    2016-01-01

    Clinical growth is an essential component of nursing education, although challenging to evaluate. Considering the paradigm shift toward constructivism and student-centered learning, clinical growth requires an examination within contemporary practices. A concept analysis of clinical growth in nursing education produced defining attributes, antecedents, and consequences. Attributes included higher-level thinking, socialization, skill development, self-reflection, self-investment, interpersonal communication, and linking theory to practice. Identification of critical attributes allows educators to adapt to student-centered learning in the clinical environment. These findings allow educators to determine significant research questions, develop situation-specific theories, and identify strategies to enhance student learning in the clinical environment. PMID:27490885

  1. Diagnostic accuracy and receiver-operating characteristics curve analysis in surgical research and decision making.

    PubMed

    Søreide, Kjetil; Kørner, Hartwig; Søreide, Jon Arne

    2011-01-01

    In surgical research, the ability to correctly classify one type of condition or specific outcome from another is of great importance for variables influencing clinical decision making. Receiver-operating characteristic (ROC) curve analysis is a useful tool in assessing the diagnostic accuracy of any variable with a continuous spectrum of results. In order to rule a disease state in or out with a given test, the test results are usually binary, with arbitrarily chosen cut-offs for defining disease versus health, or for grading of disease severity. In the postgenomic era, the translation from bench-to-bedside of biomarkers in various tissues and body fluids requires appropriate tools for analysis. In contrast to predetermining a cut-off value to define disease, the advantages of applying ROC analysis include the ability to test diagnostic accuracy across the entire range of variable scores and test outcomes. In addition, ROC analysis can easily examine visual and statistical comparisons across tests or scores. ROC is also favored because it is thought to be independent from the prevalence of the condition under investigation. ROC analysis is used in various surgical settings and across disciplines, including cancer research, biomarker assessment, imaging evaluation, and assessment of risk scores.With appropriate use, ROC curves may help identify the most appropriate cutoff value for clinical and surgical decision making and avoid confounding effects seen with subjective ratings. ROC curve results should always be put in perspective, because a good classifier does not guarantee the expected clinical outcome. In this review, we discuss the fundamental roles, suggested presentation, potential biases, and interpretation of ROC analysis in surgical research.

  2. Multidisciplinary Modelling of Symptoms and Signs with Archetypes and SNOMED-CT for Clinical Decision Support.

    PubMed

    Marco-Ruiz, Luis; Maldonado, J Alberto; Karlsen, Randi; Bellika, Johan G

    2015-01-01

    Clinical Decision Support Systems (CDSS) help to improve health care and reduce costs. However, the lack of knowledge management and modelling hampers their maintenance and reuse. Current EHR standards and terminologies can allow the semantic representation of the data and knowledge of CDSS systems boosting their interoperability, reuse and maintenance. This paper presents the modelling process of respiratory conditions' symptoms and signs by a multidisciplinary team of clinicians and information architects with the help of openEHR, SNOMED and clinical information modelling tools for a CDSS. The information model of the CDSS was defined by means of an archetype and the knowledge model was implemented by means of an SNOMED-CT based ontology. PMID:25991115

  3. The contribution of polysyllabic words in clinical decision making about children's speech.

    PubMed

    James, Deborah G H; van Doorn, Jan; McLeod, Sharynne

    2008-01-01

    Poor polysyllabic word (PSW) production seems to mark paediatric speech impairment as well as impairment in language, literacy and phonological processing. As impairment in these domains may only manifest in PSWs, PSW production may provide unique information that is often excluded from clinical decision making because insufficient PSWs are included in speech tests. A 5-stage model of PSW acquisition is described. The model, grounded in optimality theory, expresses a reciprocal relationship between the relaxation of markedness constraints and the contraction of faithfulness constraints from 12 months of age to adolescence. The markedness constraints that persist to the age of 7;11 years are associated with non-final weak syllables and within-word consonant sequences. Output changes are argued to reflect increasing specification of phonological representations with age, liberating information for motor planning and execution, resulting in increasingly accurate output. The clinical implications of PSWs in assessment and therapy are discussed.

  4. The contribution of polysyllabic words in clinical decision making about children's speech.

    PubMed

    James, Deborah G H; van Doorn, Jan; McLeod, Sharynne

    2008-01-01

    Poor polysyllabic word (PSW) production seems to mark paediatric speech impairment as well as impairment in language, literacy and phonological processing. As impairment in these domains may only manifest in PSWs, PSW production may provide unique information that is often excluded from clinical decision making because insufficient PSWs are included in speech tests. A 5-stage model of PSW acquisition is described. The model, grounded in optimality theory, expresses a reciprocal relationship between the relaxation of markedness constraints and the contraction of faithfulness constraints from 12 months of age to adolescence. The markedness constraints that persist to the age of 7;11 years are associated with non-final weak syllables and within-word consonant sequences. Output changes are argued to reflect increasing specification of phonological representations with age, liberating information for motor planning and execution, resulting in increasingly accurate output. The clinical implications of PSWs in assessment and therapy are discussed. PMID:18415734

  5. Principles of educational outreach ('academic detailing') to improve clinical decision making.

    PubMed

    Soumerai, S B; Avorn, J

    1990-01-26

    With the efficacy and costs of medications rising rapidly, it is increasingly important to ensure that drugs be prescribed as rationally as possible. Yet, physicians' choices of drugs frequently fall short of the ideal of precise and cost-effective decision making. Evidence indicates that such decisions can be improved in a variety of ways. A number of theories and principles of communication and behavior changes can be found that underlie the success of pharmaceutical manufacturers in influencing prescribing practices. Based on this behavioral science and several field trials, it is possible to define the theory and practice of methods to improve physicians' clinical decision making to enhance the quality and cost-effectiveness of care. Some of the most important techniques of such "academic detailing" include (1) conducting interviews to investigate baseline knowledge and motivations for current prescribing patterns, (2) focusing programs on specific categories of physicians as well as on their opinion leaders, (3) defining clear educational and behavioral objectives, (4) establishing credibility through a respected organizational identity, referencing authoritative and unbiased sources of information, and presenting both sides of controversial issues, (5) stimulating active physician participation in educational interactions, (6) using concise graphic educational materials, (7) highlighting and repeating the essential messages, and (8) providing positive reinforcement of improved practices in follow-up visits. Used by the nonprofit sector, the above techniques have been shown to reduce inappropriate prescribing as well as unnecessary health care expenditures.

  6. Which factors play a role in clinical decision-making in subfertility?

    PubMed

    van der Steeg, Jan W; Steures, Pieternel; Eijkemans, Marinus J C; Habbema, J Dik F; Bossuyt, Patrick M M; Hompes, Peter G A; van der Veen, Fulco; Mol, Ben W J

    2006-04-01

    Sixteen vignettes of subfertile couples were constructed by varying fertility history, post-coital test, sperm motility, FSH concentration and Chlamydia antibody titre (CAT). Thirty-five gynaecologists estimated probabilities of treatment-independent pregnancy, intrauterine insemination (IUI) and IVF. Thereafter, they chose IUI, IVF or no treatment. The relative contribution of each factor to probability estimates and to subsequent treatment decisions was calculated. Duration of subfertility and maternal age were the most important contributors for gynaecologists' estimates of treatment-independent pregnancy [relative contribution (RC) 41, 26%]. Maternal age and FSH concentration were the most important contributors in the estimates for IUI (RC: 51, 25%) and for IVF (RC: 64, 31%). The decision to start IVF was mainly determined by maternal age, duration of subfertility, FSH concentration and CAT. The relative contribution of maternal age and duration of subfertility was in concordance with existing prediction models, whereas previous pregnancy and FSH concentration were under- and overestimated respectively. In conclusion, maternal age, duration of subfertility and FSH concentration are the main factors in clinical decision-making in subfertility. Gynaecologists overestimate the importance of FSH concentration, but underestimate that of a previous pregnancy, as compared with their importance reported in prediction models and guidelines. PMID:16740221

  7. The effect of the first office blood pressure reading on hypertension-related clinical decisions.

    PubMed

    Oladipo, Idris; Ayoade, Adedokun

    2012-09-01

    The effect of the first office blood pressure reading (FBPR) on hypertension-related decisions was evaluated using blood pressure (BP) readings taken with the BpTRU BPM-100 device. BP readings were grouped into three pairs: (1) single readings (first and second readings), (2) computed average of three readings (one including and one excluding the first reading), and (3) computed average of five readings (one including and one excluding the first reading). Categorisation of BP readings under JNC-7 classes and distribution into < 140/90 and ≥ 140/90 mmHg groups were selected as parameters guiding hypertension-related decisions. Readings including FBPR had strong positive correlations to those excluding FBPR (Pearson's correlation coefficient ranged from 0.86-1.00). Also, FBPR-included and FBPR-excluded readings did not differ statistically in JNC-7 categorisation or distribution into < 140/90 or ≥ 140/90 mmHg groups. Our findings suggest that exclusion of FBPR may have no significant impact on hypertension-related clinical decisions. PMID:23044502

  8. The role and position of passive intervertebral motion assessment within clinical reasoning and decision-making in manual physical therapy: a qualitative interview study.

    PubMed

    van Trijffel, Emiel; Plochg, Thomas; van Hartingsveld, Frank; Lucas, Cees; Oostendorp, Rob A B

    2010-06-01

    Passive intervertebral motion (PIVM) assessment is a characterizing skill of manual physical therapists (MPTs) and is important for judgments about impairments in spinal joint function. It is unknown as to why and how MPTs use this mobility testing of spinal motion segments within their clinical reasoning and decision-making. This qualitative study aimed to explore and understand the role and position of PIVM assessment within the manual diagnostic process. Eight semistructured individual interviews with expert MPTs and three subsequent group interviews using manual physical therapy consultation platforms were conducted. Line-by-line coding was performed on the transcribed data, and final main themes were identified from subcategories. Three researchers were involved in the analysis process. Four themes emerged from the data: contextuality, consistency, impairment orientedness, and subjectivity. These themes were interrelated and linked to concepts of professionalism and clinical reasoning. MPTs used PIVM assessment within a multidimensional, biopsychosocial framework incorporating clinical data relating to mechanical dysfunction as well as to personal factors while applying various clinical reasoning strategies. Interpretation of PIVM assessment and subsequent decisions on manipulative treatment were strongly rooted within practitioners' practical knowledge. This study has identified the specific role and position of PIVM assessment as related to other clinical findings within clinical reasoning and decision-making in manual physical therapy in The Netherlands. We recommend future research in manual diagnostics to account for the multivariable character of physical examination of the spine.

  9. Applications of decision analysis and related techniques to industrial engineering problems at KSC

    NASA Technical Reports Server (NTRS)

    Evans, Gerald W.

    1995-01-01

    This report provides: (1) a discussion of the origination of decision analysis problems (well-structured problems) from ill-structured problems; (2) a review of the various methodologies and software packages for decision analysis and related problem areas; (3) a discussion of how the characteristics of a decision analysis problem affect the choice of modeling methodologies, thus providing a guide as to when to choose a particular methodology; and (4) examples of applications of decision analysis to particular problems encountered by the IE Group at KSC. With respect to the specific applications at KSC, particular emphasis is placed on the use of the Demos software package (Lumina Decision Systems, 1993).

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

    PubMed Central

    2011-01-01

    Background Low back pain (LBP) is common and costly. Development of accurate and efficacious methods of diagnosis and treatment has been identified as a research priority. A diagnosis-based clinical decision guide (DBCDG; previously referred to as a diagnosis-based clinical decision rule) has been proposed which attempts to provide the clinician with a systematic, evidence-based means to apply the biopsychosocial model of care. The approach is based on three questions of diagnosis. The purpose of this study is to present the prevalence of findings using the DBCDG in consecutive patients with LBP. Methods Demographic, diagnostic and baseline outcome measure data were gathered on a cohort of LBP patients examined by one of three examiners trained in the application of the DBCDG. Results Data were gathered on 264 patients. Signs of visceral disease or potentially serious illness were found in 2.7%. Centralization signs were found in 41%, lumbar and sacroiliac segmental signs in 23% and 27%, respectively and radicular signs were found in 24%. Clinically relevant myofascial signs were diagnosed in 10%. Dynamic instability was diagnosed in 63%, fear beliefs in 40%, central pain hypersensitivity in 5%, passive coping in 3% and depression in 3%. Conclusion The DBCDG can be applied in a busy private practice environment. Further studies are needed to investigate clinically relevant means to identify central pain hypersensitivity, poor coping and depression, correlations and patterns among the diagnostic components of the DBCDG as well as inter-examiner reliability and efficacy of treatment based on the DBCDG. PMID:22018026

  11. Ignorance- versus Evidence-Based Decision Making: A Decision Time Analysis of the Recognition Heuristic

    ERIC Educational Resources Information Center

    Hilbig, Benjamin E.; Pohl, Rudiger F.

    2009-01-01

    According to part of the adaptive toolbox notion of decision making known as the recognition heuristic (RH), the decision process in comparative judgments--and its duration--is determined by whether recognition discriminates between objects. By contrast, some recently proposed alternative models predict that choices largely depend on the amount of…

  12. Portfolio Decision Analysis Framework for Value-Focused Ecosystem Management.

    PubMed

    Convertino, Matteo; Valverde, L James

    2013-01-01

    Management of natural resources in coastal ecosystems is a complex process that is made more challenging by the need for stakeholders to confront the prospect of sea level rise and a host of other environmental stressors. This situation is especially true for coastal military installations, where resource managers need to balance conflicting objectives of environmental conservation against military mission. The development of restoration plans will necessitate incorporating stakeholder preferences, and will, moreover, require compliance with applicable federal/state laws and regulations. To promote the efficient allocation of scarce resources in space and time, we develop a portfolio decision analytic (PDA) framework that integrates models yielding policy-dependent predictions for changes in land cover and species metapopulations in response to restoration plans, under different climate change scenarios. In a manner that is somewhat analogous to financial portfolios, infrastructure and natural resources are classified as human and natural assets requiring management. The predictions serve as inputs to a Multi Criteria Decision Analysis model (MCDA) that is used to measure the benefits of restoration plans, as well as to construct Pareto frontiers that represent optimal portfolio allocations of restoration actions and resources. Optimal plans allow managers to maintain or increase asset values by contrasting the overall degradation of the habitat and possible increased risk of species decline against the benefits of mission success. The optimal combination of restoration actions that emerge from the PDA framework allows decision-makers to achieve higher environmental benefits, with equal or lower costs, than those achievable by adopting the myopic prescriptions of the MCDA model. The analytic framework presented here is generalizable for the selection of optimal management plans in any ecosystem where human use of the environment conflicts with the needs of

  13. Portfolio Decision Analysis Framework for Value-Focused Ecosystem Management

    PubMed Central

    Convertino, Matteo; Valverde, L. James

    2013-01-01

    Management of natural resources in coastal ecosystems is a complex process that is made more challenging by the need for stakeholders to confront the prospect of sea level rise and a host of other environmental stressors. This situation is especially true for coastal military installations, where resource managers need to balance conflicting objectives of environmental conservation against military mission. The development of restoration plans will necessitate incorporating stakeholder preferences, and will, moreover, require compliance with applicable federal/state laws and regulations. To promote the efficient allocation of scarce resources in space and time, we develop a portfolio decision analytic (PDA) framework that integrates models yielding policy-dependent predictions for changes in land cover and species metapopulations in response to restoration plans, under different climate change scenarios. In a manner that is somewhat analogous to financial portfolios, infrastructure and natural resources are classified as human and natural assets requiring management. The predictions serve as inputs to a Multi Criteria Decision Analysis model (MCDA) that is used to measure the benefits of restoration plans, as well as to construct Pareto frontiers that represent optimal portfolio allocations of restoration actions and resources. Optimal plans allow managers to maintain or increase asset values by contrasting the overall degradation of the habitat and possible increased risk of species decline against the benefits of mission success. The optimal combination of restoration actions that emerge from the PDA framework allows decision-makers to achieve higher environmental benefits, with equal or lower costs, than those achievable by adopting the myopic prescriptions of the MCDA model. The analytic framework presented here is generalizable for the selection of optimal management plans in any ecosystem where human use of the environment conflicts with the needs of

  14. Decision support systems for clinical radiological practice — towards the next generation

    PubMed Central

    Stivaros, S M; Gledson, A; Nenadic, G; Zeng, X-J; Keane, J; Jackson, A

    2010-01-01

    The huge amount of information that needs to be assimilated in order to keep pace with the continued advances in modern medical practice can form an insurmountable obstacle to the individual clinician. Within radiology, the recent development of quantitative imaging techniques, such as perfusion imaging, and the development of imaging-based biomarkers in modern therapeutic assessment has highlighted the need for computer systems to provide the radiological community with support for academic as well as clinical/translational applications. This article provides an overview of the underlying design and functionality of radiological decision support systems with examples tracing the development and evolution of such systems over the past 40 years. More importantly, we discuss the specific design, performance and usage characteristics that previous systems have highlighted as being necessary for clinical uptake and routine use. Additionally, we have identified particular failings in our current methodologies for data dissemination within the medical domain that must be overcome if the next generation of decision support systems is to be implemented successfully. PMID:20965900

  15. Functional Assessment of Genetic Variants with Outcomes Adapted to Clinical Decision-Making

    PubMed Central

    Thouvenot, Pierre; Ben Yamin, Barbara; Fourrière, Lou; Lescure, Aurianne; Boudier, Thomas; Del Nery, Elaine; Chauchereau, Anne; Goldgar, David E.; Stoppa-Lyonnet, Dominique; Nicolas, Alain; Millot, Gaël A.

    2016-01-01

    Understanding the medical effect of an ever-growing number of human variants detected is a long term challenge in genetic counseling. Functional assays, based on in vitro or in vivo evaluations of the variant effects, provide essential information, but they require robust statistical validation, as well as adapted outputs, to be implemented in the clinical decision-making process. Here, we assessed 25 pathogenic and 15 neutral missense variants of the BRCA1 breast/ovarian cancer susceptibility gene in four BRCA1 functional assays. Next, we developed a novel approach that refines the variant ranking in these functional assays. Lastly, we developed a computational system that provides a probabilistic classification of variants, adapted to clinical interpretation. Using this system, the best functional assay exhibits a variant classification accuracy estimated at 93%. Additional theoretical simulations highlight the benefit of this ready-to-use system in the classification of variants after functional assessment, which should facilitate the consideration of functional evidences in the decision-making process after genetic testing. Finally, we demonstrate the versatility of the system with the classification of siRNAs tested for human cell growth inhibition in high throughput screening. PMID:27272900

  16. Decision support systems for clinical radiological practice -- towards the next generation.

    PubMed

    Stivaros, S M; Gledson, A; Nenadic, G; Zeng, X-J; Keane, J; Jackson, A

    2010-11-01

    The huge amount of information that needs to be assimilated in order to keep pace with the continued advances in modern medical practice can form an insurmountable obstacle to the individual clinician. Within radiology, the recent development of quantitative imaging techniques, such as perfusion imaging, and the development of imaging-based biomarkers in modern therapeutic assessment has highlighted the need for computer systems to provide the radiological community with support for academic as well as clinical/translational applications. This article provides an overview of the underlying design and functionality of radiological decision support systems with examples tracing the development and evolution of such systems over the past 40 years. More importantly, we discuss the specific design, performance and usage characteristics that previous systems have highlighted as being necessary for clinical uptake and routine use. Additionally, we have identified particular failings in our current methodologies for data dissemination within the medical domain that must be overcome if the next generation of decision support systems is to be implemented successfully.

  17. [The role of PET/CT in decision-making during cancer treatment. Clinical experience].

    PubMed

    Sinkó, Dániel; Landherr, László

    2012-12-01

    Nowadays PET/CT examinations have got more and more important role during cancer treatment. It has importance not only in diagnostic examination and staging but also in the radiation planning process and measuring the therapeutic effect. From November 2006 to November 2010 there were 153 PET/CT examinations requested by the Oncology Outpatient Clinic, Uzsoki Hospital. Nine patients were excluded from the examination. In the clinical trial we have aimed to measure what the correlation between the oncologists' questions and the PET/CT results was, in how many cases the PET/CT had influence on therapeutic decision-making. In the case of the patients waiting for the operation we compared the results of the pathological examinations to the results of the PET/CT. The oncologists got the expected answers in 79 cases, while in 45 cases the answers were negative. In 10 cases there were no definite answers. Ten cases proved to be false negative or false positive based on the later pathological examination. As a result of the PET/CT findings the originally planned therapeutic decisions or the therapies in process have been modified in 77 cases. To sum up, the PET/CT gave the expected answers to the oncologists' questions in more than half of the cases (54.9%) and modified the originally prescribed therapy in 53.5% of the cases. PMID:23236592

  18. Clinical decision aids for chest pain in the emergency department: identifying low-risk patients

    PubMed Central

    Alley, William; Mahler, Simon A

    2015-01-01

    Chest pain is one of the most common presenting complaints in the emergency department, though only a small minority of patients are subsequently diagnosed with acute coronary syndrome (ACS). However, missing the diagnosis has potential for significant morbidity and mortality. ACS presentations can be atypical, and their workups are often prolonged and costly. In order to risk-stratify patients and better direct the workup and care given, many decision aids have been developed. While each may have merit in certain clinical settings, the most useful aid in the emergency department is one that finds all cases of ACS while also identifying a substantial subset of patients at low risk who can be discharged without stress testing or coronary angiography. This review describes several of the chest pain decision aids developed and studied through the recent past, starting with the thrombolysis in myocardial infarction (TIMI) risk score and Global Registry of Acute Coronary Events (GRACE) scores, which were developed as prognostic aids for patients already diagnosed with ACS, then subsequently validated in the undifferentiated chest pain population. Asia-Pacific Evaluation of Chest Pain Trial (ASPECT); Accelerated Diagnostic Protocol to Assess Patients With Chest Pain Symptoms Using Contemporary Troponins (ADAPT); North American Chest Pain Rule (NACPR); and History, Electrocardiogram, Age, Risk factors, Troponin (HEART) score have been developed exclusively for use in the undifferentiated chest pain population as well, with improved performance compared to their predecessors. This review describes the relative merits and limitations of these decision aids so that providers can determine which tool fits the needs of their clinical practice setting. PMID:27147894

  19. A distance-based uncertainty analysis approach to multi-criteria decision analysis for water resource decision making.

    PubMed

    Hyde, K M; Maier, H R; Colby, C B

    2005-12-01

    The choice among alternative water supply sources is generally based on the fundamental objective of maximising the ratio of benefits to costs. There is, however, a need to consider sustainability, the environment and social implications in regional water resources planning, in addition to economics. In order to achieve this, multi-criteria decision analysis (MCDA) techniques can be used. Various sources of uncertainty exist in the application of MCDA methods, including the selection of the MCDA method, elicitation of criteria weights and assignment of criteria performance values. The focus of this paper is on the uncertainty in the criteria weights. Sensitivity analysis can be used to analyse the effects of uncertainties associated with the criteria weights. Two existing sensitivity methods are described in this paper and a new distance-based approach is proposed which overcomes limitations of these methods. The benefits of the proposed approach are the concurrent alteration of the criteria weights, the applicability of the method to a range of MCDA techniques and the identification of the most critical criteria weights. The existing and proposed methods are applied to three case studies and the results indicate that simultaneous consideration of the uncertainty in the criteria weights should be an integral part of the decision making process.

  20. Lung cancer patients' decisions about clinical trials and the theory of planned behavior.

    PubMed

    Quinn, Gwendolyn P; Pratt, Christie L; Bryant-George, Kathy; Caraway, Vicki D; Paternoster, Bonnie; Roldan, Tere; Shaffer, Andrea; Shimizu, Cynthia O; Vaughn, Elizabeth J; Williams, Charles; Bepler, Gerold

    2011-12-01

    The theory of planned behavior explores the relationship between behavior, beliefs, attitudes, and intentions presupposing that behavioral intention is influenced by a person's attitude about the behavior and beliefs about whether individuals, who are important to them, approve or disapprove of the behavior (subjective norm). An added dimension to the theory is the idea of perceived behavioral control, or the belief that one has control over performing the behavior. The theory of planned behavior suggests that people may make greater efforts to perform a behavior if they feel they have a high level of control over it. In this examination of data, we explored the application of the theory of planned behavior to patient's decisions about participating in a clinic trial. Twelve respondents in this study had previously participated in a clinical trial for lung cancer and nine respondents had declined a clinical trial for lung cancer. The data were analyzed with regard to the four constructs associated with the theory of planned behavior: behavioral intention, attitude, subjective norm, and perceived behavioral control. Results indicate that the theory of planned behavior may be a useful tool to examine psychosocial needs in relation to behavioral intention of clinical trial participation.

  1. A Proposed Clinical Decision Support Architecture Capable of Supporting Whole Genome Sequence Information

    PubMed Central

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

    2014-01-01

    Whole genome sequence (WGS) information may soon be widely available to help clinicians personalize the care and treatment of patients. However, considerable barriers exist, which may hinder the effective utilization of WGS information in a routine clinical care setting. Clinical decision support (CDS) offers a potential solution to overcome such barriers and to facilitate the effective use of WGS information in the clinic. However, genomic information is complex and will require significant considerations when developing CDS capabilities. As such, this manuscript lays out a conceptual framework for a CDS architecture designed to deliver WGS-guided CDS within the clinical workflow. To handle the complexity and breadth of WGS information, the proposed CDS framework leverages service-oriented capabilities and orchestrates the interaction of several independently-managed components. These independently-managed components include the genome variant knowledge base, the genome database, the CDS knowledge base, a CDS controller and the electronic health record (EHR). A key design feature is that genome data can be stored separately from the EHR. This paper describes in detail: (1) each component of the architecture; (2) the interaction of the components; and (3) how the architecture attempts to overcome the challenges associated with WGS information. We believe that service-oriented CDS capabilities will be essential to using WGS information for personalized medicine. PMID:25411644

  2. Myocardial strain imaging: how useful is it in clinical decision making?

    PubMed

    Smiseth, Otto A; Torp, Hans; Opdahl, Anders; Haugaa, Kristina H; Urheim, Stig

    2016-04-14

    Myocardial strain is a principle for quantification of left ventricular (LV) function which is now feasible with speckle-tracking echocardiography. The best evaluated strain parameter is global longitudinal strain (GLS) which is more sensitive than left ventricular ejection fraction (LVEF) as a measure of systolic function, and may be used to identify sub-clinical LV dysfunction in cardiomyopathies. Furthermore, GLS is recommended as routine measurement in patients undergoing chemotherapy to detect reduction in LV function prior to fall in LVEF. Intersegmental variability in timing of peak myocardial strain has been proposed as predictor of risk of ventricular arrhythmias. Strain imaging may be applied to guide placement of the LV pacing lead in patients receiving cardiac resynchronization therapy. Strain may also be used to diagnose myocardial ischaemia, but the technology is not sufficiently standardized to be recommended as a general tool for this purpose. Peak systolic left atrial strain is a promising supplementary index of LV filling pressure. The strain imaging methodology is still undergoing development, and further clinical trials are needed to determine if clinical decisions based on strain imaging result in better outcome. With this important limitation in mind, strain may be applied clinically as a supplementary diagnostic method.

  3. Pilot Program Using Medical Simulation in Clinical Decision-Making Training for Internal Medicine Interns

    PubMed Central

    Miloslavsky, Eli M.; Hayden, Emily M.; Currier, Paul F.; Mathai, Susan K.; Contreras-Valdes, Fernando; Gordon, James A.

    2012-01-01

    Background The use of high-fidelity medical simulation in cognitive skills training within internal medicine residency programs remains largely unexplored. Objective To design a pilot study to introduce clinical decision-making training using simulation into a large internal medicine residency program, explore the practicability of using junior and senior residents as facilitators, and examine the feasibility of using the program to improve interns' clinical skills. Methods Interns on outpatient rotations participated in a simulation curriculum on a voluntary basis. The curriculum consisted of 8 cases focusing on acute clinical scenarios encountered on the wards. One-hour sessions were offered twice monthly from August 2010 to February 2011. Internal medicine residents and simulation faculty served as facilitators. Results A total of 36 of 75 total interns volunteered to participate in the program, with 42% attending multiple sessions. Of all participants, 88% rated the sessions as “excellent,” 97% felt that the program improved their ability to function as an intern and generate a plan, and 81% reported improvement in differential diagnosis skills. Conclusions Simulation training was well received by the learners and improved self-reported clinical skills. Using residents as facilitators, supervised by faculty, was well received by the learners and enabled the implementation of the curriculum in a large training program. Simulation can provide opportunities for deliberate practice, and learners perceive this modality to be effective. PMID:24294427

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

    PubMed Central

    2012-01-01

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

  5. A clinical decision support system with an integrated EMR for diagnosis of peripheral neuropathy.

    PubMed

    Kunhimangalam, Reeda; Ovallath, Sujith; Joseph, Paul K

    2014-04-01

    The prevalence of peripheral neuropathy in general population is ever increasing. The diagnosis and classification of peripheral neuropathies is often difficult as it involves careful clinical and electro-diagnostic examination by an expert neurologist. In developing countries a large percentage of the disease remains undiagnosed due to lack of adequate number of experts. In this study a novel clinical decision support system has been developed using a fuzzy expert system. The study was done to provide a solution to the demand of systems that can improve health care by accurate diagnosis in limited time, in the absence of specialists. It employs a graphical user interface and a fuzzy logic controller with rule viewer for identification of the type of peripheral neuropathy. An integrated medical records database is also developed for the storage and retrieval of the data. The system consists of 24 input fields, which includes the clinical values of the diagnostic test and the clinical symptoms. The output field is the disease diagnosis, whether it is Motor (Demyelinating/Axonopathy) neuropathy, sensory (Demyelinating/Axonopathy) neuropathy, mixed type or a normal case. The results obtained were compared with the expert's opinion and the system showed 93.27 % accuracy. The study aims at showing that Fuzzy Expert Systems may prove useful in providing diagnostic and predictive medical opinions. It enables the clinicians to arrive at a better diagnosis as it keeps the expert knowledge in an intelligent system to be used efficiently and effectively.

  6. Use of Simulation to Study Nurses Acceptance and Non-Acceptance of Clinical Decision Support Suggestions

    PubMed Central

    Sousa, Vanessa E. C.; Lopez, Karen Dunn; Febretti, Alessandro; Stifter, Janet; Yao, Yingwei; Johnson, Andrew; Wilkie, Diana J.; Keenan, Gail M.

    2015-01-01

    Our long term goal is to ensure nurse clinical decision support (CDS) works as intended before full deployment in clinical practice. As part of a broader effort, this pilot explores factors influencing acceptance/non-acceptance of 8 CDS suggestions displayed through selecting a blinking red button in an electronic health record (EHR) 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 CDS suggestions. Of 168 total suggestions displayed during the experiment (8 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 7 of 8 with only 2 of 21 nurses accepting all. The main reason for CDS acceptance was the nurse’s belief that the suggestions were good for the patient (n=100%) with other features being secondarily reinforcing. Reasons for non-acceptance were less clear, with under half of the subjects indicating low confidence in the evidence. This study provides preliminary evidence that high quality simulation and targeted questionnaires about specific CDS selections offers a cost effective means for testing before full deployment in clinical practice. PMID:26361268

  7. Integration and Evaluation of Clinical Decision Support Systems for Diagnosis Idopathics Pulmonary Fibrosis (IPF)

    PubMed Central

    Chae, Youngmoon; Jeon, Sungwan

    2010-01-01

    Objectives The purpose of this study was to develop clinical decision support systems (CDSS) that are integrated with hospital information systems for the differential diagnosis of idiopathic pulmonary fibrosis (IPF). Methods The integrated CDSS were validated and evaluated by physicians. Knowledge modeling for diagnosing IPF was performed by knowledge working groups, composed of radiologists and respiratory specialists. In order to develop the model for CDSS diagnosis, the clinical cases were collected from 290 cases from Seoul National University Hospital and Sevrance Hospital of Yonsei University. For the evaluation of integrated CDSS, interviews were conducted with respiratory specialists and radiologist 2 weeks after applying CDSSs in clinical settings. The CDSS was integrated with the computer vision system (CVS) and diffuse parenchymal lung diseases (DPLD), CDSS developed in our previous project. Results Eighteen cases diagnosed as IPF were applied to the collection of diagnostic knowledge and the refined knowledge, the former diagnosed 1 case (6%) and the latter diagnosed 14 cases (78%). Therefore, the refined knowledge performed better than collected knowledge. The validation results of integrated CDSSs showed that 81 cases (74.3%) were diagnosed correctly. Conclusions There were 109 cases of IPF diagnosed and initiated on treatment. The significance of this study is in developing integrated CDSS with PACS by acquiring and redefining the knowledge needed for IPF diagnosis. In addition, it is significant for the integration of CDSS to verification and clinical evaluation. PMID:21818445

  8. A Decision Analysis Tool for Climate Impacts, Adaptations, and Vulnerabilities

    SciTech Connect

    Omitaomu, Olufemi A; Parish, Esther S; Nugent, Philip J

    2016-01-01

    Climate change related extreme events (such as flooding, storms, and drought) are already impacting millions of people globally at a cost of billions of dollars annually. Hence, there are urgent needs for urban areas to develop adaptation strategies that will alleviate the impacts of these extreme events. However, lack of appropriate decision support tools that match local applications is limiting local planning efforts. In this paper, we present a quantitative analysis and optimization system with customized decision support modules built on geographic information system (GIS) platform to bridge this gap. This platform is called Urban Climate Adaptation Tool (Urban-CAT). For all Urban-CAT models, we divide a city into a grid with tens of thousands of cells; then compute a list of metrics for each cell from the GIS data. These metrics are used as independent variables to predict climate impacts, compute vulnerability score, and evaluate adaptation options. Overall, the Urban-CAT system has three layers: data layer (that contains spatial data, socio-economic and environmental data, and analytic data), middle layer (that handles data processing, model management, and GIS operation), and application layer (that provides climate impacts forecast, adaptation optimization, and site evaluation). The Urban-CAT platform can guide city and county governments in identifying and planning for effective climate change adaptation strategies.

  9. Vascular access choice in incident hemodialysis patients: a decision analysis.

    PubMed

    Drew, David A; Lok, Charmaine E; Cohen, Joshua T; Wagner, Martin; Tangri, Navdeep; Weiner, Daniel E

    2015-01-01

    Hemodialysis vascular access recommendations promote arteriovenous (AV) fistulas first; however, it may not be the best approach for all hemodialysis patients, because likelihood of successful fistula placement, procedure-related and subsequent costs, and patient survival modify the optimal access choice. We performed a decision analysis evaluating AV fistula, AV graft, and central venous catheter (CVC) strategies for patients initiating hemodialysis with a CVC, a scenario occurring in over 70% of United States dialysis patients. A decision tree model was constructed to reflect progression from hemodialysis initiation. Patients were classified into one of three vascular access choices: maintain CVC, attempt fistula, or attempt graft. We explicitly modeled probabilities of primary and secondary patency for each access type, with success modified by age, sex, and diabetes. Access-specific mortality was incorporated using preexisting cohort data, including terms for age, sex, and diabetes. Costs were ascertained from the 2010 USRDS report and Medicare for procedure costs. An AV fistula attempt strategy was found to be superior to AV grafts and CVCs in regard to mortality and cost for the majority of patient characteristic combinations, especially younger men without diabetes. Women with diabetes and elderly men with diabetes had similar outcomes, regardless of access type. Overall, the advantages of an AV fistula attempt strategy lessened considerably among older patients, particularly women with diabetes, reflecting the effect of lower AV fistula success rates and lower life expectancy. These results suggest that vascular access-related outcomes may be optimized by considering individual patient characteristics.

  10. Clinical decision support systems for improving diagnostic accuracy and achieving precision medicine.

    PubMed

    Castaneda, Christian; Nalley, Kip; Mannion, Ciaran; Bhattacharyya, Pritish; Blake, Patrick; Pecora, Andrew; Goy, Andre; Suh, K Stephen

    2015-01-01

    , and logistical concerns. Ensuring data security and protection of patient rights while simultaneously facilitating standardization is paramount to maintaining public support. The capabilities of supercomputing need to be applied strategically. A standardized, methodological implementation must be applied to developed artificial intelligence systems with the ability to integrate data and information into clinically relevant knowledge. Ultimately, the integration of bioinformatics and clinical data in a clinical decision support system promises precision medicine and cost effective and personalized patient care.

  11. Towards a controlled sensitivity analysis of model development decisions

    NASA Astrophysics Data System (ADS)

    Clark, Martyn; Nijssen, Bart

    2016-04-01

    The current generation of hydrologic models have followed a myriad of different development paths, making it difficult for the community to test underlying hypotheses and identify a clear path to model improvement. Model comparison studies have been undertaken to explore model differences, but these studies have not been able to meaningfully attribute inter-model differences in predictive ability to individual model components because there are often too many structural and implementation differences among the models considered. As a consequence, model comparison studies to date have provided limited insight into the causes of differences in model behavior, and model development has often relied on the inspiration and experience of individual modelers rather than a systematic analysis of model shortcomings. This presentation will discuss a unified approach to process-based hydrologic modeling to enable controlled and systematic analysis of multiple model representations (hypotheses) of hydrologic processes and scaling behavior. Our approach, which we term the Structure for Unifying Multiple Modeling Alternatives (SUMMA), formulates a general set of conservation equations, providing the flexibility to experiment with different spatial representations, different flux parameterizations, different model parameter values, and different time stepping schemes. We will discuss the use of SUMMA to systematically analyze different model development decisions, focusing on both analysis of simulations for intensively instrumented research watersheds as well as simulations across a global dataset of FLUXNET sites. The intent of the presentation is to demonstrate how the systematic analysis of model shortcomings can help identify model weaknesses and inform future model development priorities.

  12. School Board Decision Making: An Analysis of the Process

    ERIC Educational Resources Information Center

    Crum, Karen S.

    2007-01-01

    The goal of this study was to analyze the characteristics in the school board decision-making process and to discover whether school board members are aware of the characteristics surrounding the school board's decision-making process. Specifically, this study examines the decision-making process of a school board in Virginia, and it provides…

  13. A Speedy Cardiovascular Diseases Classifier Using Multiple Criteria Decision Analysis

    PubMed Central

    Lee, Wah Ching; Hung, Faan Hei; Tsang, Kim Fung; Tung, Hoi Ching; Lau, Wing Hong; Rakocevic, Veselin; Lai, Loi Lei

    2015-01-01

    Each year, some 30 percent of global deaths are caused by cardiovascular diseases. This figure is worsening due to both the increasing elderly population and severe shortages of medical personnel. The development of a cardiovascular diseases classifier (CDC) for auto-diagnosis will help address solve the problem. Former CDCs did not achieve quick evaluation of cardiovascular diseases. In this letter, a new CDC to achieve speedy detection is investigated. This investigation incorporates the analytic hierarchy process (AHP)-based multiple criteria decision analysis (MCDA) to develop feature vectors using a Support Vector Machine. The MCDA facilitates the efficient assignment of appropriate weightings to potential patients, thus scaling down the number of features. Since the new CDC will only adopt the most meaningful features for discrimination between healthy persons versus cardiovascular disease patients, a speedy detection of cardiovascular diseases has been successfully implemented. PMID:25587978

  14. Transmission Bearing Damage Detection Using Decision Fusion Analysis

    NASA Technical Reports Server (NTRS)

    Dempsey, Paula J.; Lewicki, David G.; Decker, Harry J.

    2004-01-01

    A diagnostic tool was developed for detecting fatigue damage to rolling element bearings in an OH-58 main rotor transmission. Two different monitoring technologies, oil debris analysis and vibration, were integrated using data fusion into a health monitoring system for detecting bearing surface fatigue pitting damage. This integrated system showed improved detection and decision-making capabilities as compared to using individual monitoring technologies. This diagnostic tool was evaluated by collecting vibration and oil debris data from tests performed in the NASA Glenn 500 hp Helicopter Transmission Test Stand. Data was collected during experiments performed in this test rig when two unanticipated bearing failures occurred. Results show that combining the vibration and oil debris measurement technologies improves the detection of pitting damage on spiral bevel gears duplex ball bearings and spiral bevel pinion triplex ball bearings in a main rotor transmission.

  15. Climate policy decisions require policy-based lifecycle analysis.

    PubMed

    Bento, Antonio M; Klotz, Richard

    2014-05-20

    Lifecycle analysis (LCA) metrics of greenhouse gas emissions are increasingly being used to select technologies supported by climate policy. However, LCAs typically evaluate the emissions associated with a technology or product, not the impacts of policies. Here, we show that policies supporting the same technology can lead to dramatically different emissions impacts per unit of technology added, due to multimarket responses to the policy. Using a policy-based consequential LCA, we find that the lifecycle emissions impacts of four US biofuel policies range from a reduction of 16.1 gCO2e to an increase of 24.0 gCO2e per MJ corn ethanol added by the policy. The differences between these results and representative technology-based LCA measures, which do not account for the policy instrument driving the expansion in the technology, illustrate the need for policy-based LCA measures when informing policy decision making.

  16. Spiral Bevel Gear Damage Detection Using Decision Fusion Analysis

    NASA Technical Reports Server (NTRS)

    Dempsey, Paula J.; Handschuh, Robert F.; Afjeh, Abdollah A.

    2002-01-01

    A diagnostic tool for detecting damage to spiral bevel gears was developed. Two different monitoring technologies, oil debris analysis and vibration, were integrated using data fusion into a health monitoring system for detecting surface fatigue pitting damage on gears. This integrated system showed improved detection and decision-making capabilities as compared to using individual monitoring technologies. This diagnostic tool was evaluated by collecting vibration and oil debris data from fatigue tests performed in the NASA Glenn Spiral Bevel Gear Fatigue Rigs. Data was collected during experiments performed in this test rig when pitting damage occurred. Results show that combining the vibration and oil debris measurement technologies improves the detection of pitting damage on spiral bevel gears.

  17. The Potential for Meta-Analysis to Support Decision Analysis in Ecology

    ERIC Educational Resources Information Center

    Mengersen, Kerrie; MacNeil, M. Aaron; Caley, M. Julian

    2015-01-01

    Meta-analysis and decision analysis are underpinned by well-developed methods that are commonly applied to a variety of problems and disciplines. While these two fields have been closely linked in some disciplines such as medicine, comparatively little attention has been paid to the potential benefits of linking them in ecology, despite reasonable…

  18. The anatomy of clinical decision-making in multidisciplinary cancer meetings: A cross-sectional observational study of teams in a natural context.

    PubMed

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

    2016-06-01

    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 disciplines. Evidence of dual-task interference was

  19. Validation of decision-making models and analysis of decision variables in the rat basal ganglia.

    PubMed

    Ito, Makoto; Doya, Kenji

    2009-08-01

    Reinforcement learning theory plays a key role in understanding the behavioral and neural mechanisms of choice behavior in animals and humans. Especially, intermediate variables of learning models estimated from behavioral data, such as the expectation of reward for each candidate choice (action value), have been used in searches for the neural correlates of computational elements in learning and decision making. The aims of the present study are as follows: (1) to test which computational model best captures the choice learning process in animals and (2) to elucidate how action values are represented in different parts of the corticobasal ganglia circuit. We compared different behavioral learning algorithms to predict the choice sequences generated by rats during a free-choice task and analyzed associated neural activity in the nucleus accumbens (NAc) and ventral pallidum (VP). The major findings of this study were as follows: (1) modified versions of an action-value learning model captured a variety of choice strategies of rats, including win-stay-lose-switch and persevering behavior, and predicted rats' choice sequences better than the best multistep Markov model; and (2) information about action values and future actions was coded in both the NAc and VP, but was less dominant than information about trial types, selected actions, and reward outcome. The results of our model-based analysis suggest that the primary role of the NAc and VP is to monitor information important for updating choice behaviors. Information represented in the NAc and VP might contribute to a choice mechanism that is situated elsewhere.

  20. Evaluation of User Interface and Workflow Design of a Bedside Nursing Clinical Decision Support System

    PubMed Central

    Yuan, Michael Juntao; Finley, George Mike; Mills, Christy; Johnson, Ron Kim

    2013-01-01

    Background Clinical decision support systems (CDSS) are important tools to improve health care outcomes and reduce preventable medical adverse events. However, the effectiveness and success of CDSS depend on their implementation context and usability in complex health care settings. As a result, usability design and validation, especially in real world clinical settings, are crucial aspects of successful CDSS implementations. Objective Our objective was to develop a novel CDSS to help frontline nurses better manage critical symptom changes in hospitalized patients, hence reducing preventable failure to rescue cases. A robust user interface and implementation strategy that fit into existing workflows was key for the success of the CDSS. Methods Guided by a formal usability evaluation framework, UFuRT (user, function, representation, and task analysis), we developed a high-level specification of the product that captures key usability requirements and is flexible to implement. We interviewed users of the proposed CDSS to identify requirements, listed functions, and operations the system must perform. We then designed visual and workflow representations of the product to perform the operations. The user interface and workflow design were evaluated via heuristic and end user performance evaluation. The heuristic evaluation was done after the first prototype, and its results were incorporated into the product before the end user evaluation was conducted. First, we recruited 4 evaluators with strong domain expertise to study the initial prototype. Heuristic violations were coded and rated for severity. Second, after development of the system, we assembled a panel of nurses, consisting of 3 licensed vocational nurses and 7 registered nurses, to evaluate the user interface and workflow via simulated use cases. We recorded whether each session was successfully completed and its completion time. Each nurse was asked to use the National Aeronautics and Space Administration

  1. icuARM-An ICU Clinical Decision Support System Using Association Rule Mining

    PubMed Central

    Chanani, Nikhil; Venugopalan, Janani; Maher, Kevin; Wang, May Dongmei

    2013-01-01

    The rapid development of biomedical monitoring technologies has enabled modern intensive care units (ICUs) to gather vast amounts of multimodal measurement data about their patients. However, processing large volumes of complex data in real-time has become a big challenge. Together with ICU physicians, we have designed and developed an ICU clinical decision support system icuARM based on associate rule mining (ARM), and a publicly available research database MIMIC-II (Multi-parameter Intelligent Monitoring in Intensive Care II) that contains more than 40,000 ICU records for 30,000+patients. icuARM is constructed with multiple association rules and an easy-to-use graphical user interface (GUI) for care providers to perform real-time data and information mining in the ICU setting. To validate icuARM, we have investigated the associations between patients' conditions such as comorbidities, demographics, and medications and their ICU outcomes such as ICU length of stay. Coagulopathy surfaced as the most dangerous co-morbidity that leads to the highest possibility (54.1%) of prolonged ICU stay. In addition, women who are older than 50 years have the highest possibility (38.8%) of prolonged ICU stay. For clinical conditions treatable with multiple drugs, icuARM suggests that medication choice can be optimized based on patient-specific characteristics. Overall, icuARM can provide valuable insights for ICU physicians to tailor a patient's treatment based on his or her clinical status in real time. PMID:27170860

  2. Clinical decision support systems for brain tumor characterization using advanced magnetic resonance imaging techniques.

    PubMed

    Tsolaki, Evangelia; Kousi, Evanthia; Svolos, Patricia; Kapsalaki, Efthychia; Theodorou, Kyriaki; Kappas, Constastine; Tsougos, Ioannis

    2014-04-28

    In recent years, advanced magnetic resonance imaging (MRI) techniques, such as magnetic resonance spectroscopy, diffusion weighted imaging, diffusion tensor imaging and perfusion weighted imaging have been used in order to resolve demanding diagnostic problems such as brain tumor characterization and grading, as these techniques offer a more detailed and non-invasive evaluation of the area under study. In the last decade a great effort has been made to import and utilize intelligent systems in the so-called clinical decision support systems (CDSS) for automatic processing, classification, evaluation and representation of MRI data in order for advanced MRI techniques to become a part of the clinical routine, since the amount of data from the aforementioned techniques has gradually increased. Hence, the purpose of the current review article is two-fold. The first is to review and evaluate the progress that has been made towards the utilization of CDSS based on data from advanced MRI techniques. The second is to analyze and propose the future work that has to be done, based on the existing problems and challenges, especially taking into account the new imaging techniques and parameters that can be introduced into intelligent systems to significantly improve their diagnostic specificity and clinical application.

  3. The Arden Syntax standard for clinical decision support: experiences and directions.

    PubMed

    Samwald, Matthias; Fehre, Karsten; de Bruin, Jeroen; Adlassnig, Klaus-Peter

    2012-08-01

    Arden Syntax is a widely recognized standard for representing clinical and scientific knowledge in an executable format. It has a history that reaches back until 1989 and is currently maintained by the Health Level 7 (HL7) organization. We created a production-ready development environment, compiler, rule engine and application server for Arden Syntax. Over the course of several years, we have applied this Arden - Syntax - based CDS system in a wide variety of clinical problem domains, such as hepatitis serology interpretation, monitoring of nosocomial infections or the prediction of metastatic events in melanoma patients. We found the Arden Syntax standard to be very suitable for the practical implementation of CDS systems. Among the advantages of Arden Syntax are its status as an actively developed HL7 standard, the readability of the syntax, and various syntactic features such as flexible list handling. A major challenge we encountered was the technical integration of our CDS systems in existing, heterogeneous health information systems. To address this issue, we are currently working on incorporating the HL7 standard GELLO, which provides a standardized interface and query language for accessing data in health information systems. We hope that these planned extensions of the Arden Syntax might eventually help in realizing the vision of a global, interoperable and shared library of clinical decision support knowledge.

  4. Using clinical decision support as a means of implementing a universal postpartum depression screening program.

    PubMed

    Loudon, Holly; Nentin, Farida; Silverman, Michael E

    2016-06-01

    A major barrier to the diagnosis of postpartum depression (PPD) includes symptom detection. The lack of awareness and understanding of PPD among new mothers, the variability in clinical presentation, and the various diagnostic strategies can increase this further. The purpose of this study was to test the feasibility of adding clinical decision support (CDS) to the electronic health record (EHR) as a means of implementing a universal standardized PPD screening program within a large, at high risk, population. All women returning to the Mount Sinai Hospital OB/GYN Ambulatory Practice for postpartum care between 2010 and 2013 were presented with the Edinburgh Postnatal Depression Scale (EPDS) in response to a CDS "hard stop" built into the EHR. Of the 2102 women who presented for postpartum care, 2092 women (99.5 %) were screened for PPD in response to a CDS hard stop module. Screens were missing on ten records (0.5 %) secondary to refusal, language barrier, or lack of clarity in the EHR. Technology is becoming increasingly important in addressing the challenges faced by health care providers. While the identification of PPD has become the recent focus of public health concerns secondary to the significant social burden, numerous barriers to screening still exist within the clinical setting. The utility of adding CDS in the form of a hard stop, requiring clinicians to enter a standardized PPD mood assessment score to the patient EHR, offers a sufficient way to address a primary barrier to PPD symptom identification at the practitioner level.

  5. Decision-theoretic analysis of forensic sampling criteria using bayesian decision networks.

    PubMed

    Biedermann, A; Bozza, S; Garbolino, P; Taroni, F

    2012-11-30

    Sampling issues represent a topic of ongoing interest to the forensic science community essentially because of their crucial role in laboratory planning and working protocols. For this purpose, forensic literature described thorough (bayesian) probabilistic sampling approaches. These are now widely implemented in practice. They allow, for instance, to obtain probability statements that parameters of interest (e.g., the proportion of a seizure of items that present particular features, such as an illegal substance) satisfy particular criteria (e.g., a threshold or an otherwise limiting value). Currently, there are many approaches that allow one to derive probability statements relating to a population proportion, but questions on how a forensic decision maker--typically a client of a forensic examination or a scientist acting on behalf of a client--ought actually to decide about a proportion or a sample size, remained largely unexplored to date. The research presented here intends to address methodology from decision theory that may help to cope usefully with the wide range of sampling issues typically encountered in forensic science applications. The procedures explored in this paper enable scientists to address a variety of concepts such as the (net) value of sample information, the (expected) value of sample information or the (expected) decision loss. All of these aspects directly relate to questions that are regularly encountered in casework. Besides probability theory and bayesian inference, the proposed approach requires some additional elements from decision theory that may increase the efforts needed for practical implementation. In view of this challenge, the present paper will emphasise the merits of graphical modelling concepts, such as decision trees and bayesian decision networks. These can support forensic scientists in applying the methodology in practice. How this may be achieved is illustrated with several examples. The graphical devices invoked

  6. Shared Surgical Decision-Making and Youth Resilience: Correlates of Satisfaction with Clinical Outcomes

    PubMed Central

    Kapp-Simon, Kathleen A; Edwards, Todd; Ruta, Caroline; Bellucci, Claudia Crilly; Aspirnall, Cassandra L.; Strauss, Ronald P; Topolski, Tari D.; Rumsey, Nichola J; Patrick, Donald L

    2015-01-01

    The aim of this study was to identify factors associated with youth satisfaction with surgical procedures performed to address oral cleft or craniofacial conditions (CFC). It was hypothesized that youth mental health, participation in decision-making, perceived consequences of living with a CFC, and coping strategies would be associated with satisfaction with past surgeries. Two hundred and three youth between the ages of 11 and 18 (Mean age = 14.5. SD = 2.0; 61% male; 78% oral cleft) completed a series of questionnaires measuring depression, self-esteem, participation in decision-making, condition severity, negative and positive consequences of having a CFC, coping, and satisfaction with past surgeries. Multiple Regression Analysis using boot-strapping techniques found that youth participation in decision making, youth perception of positive consequences of having a CFC, and coping accounted for 32% of the variance in satisfaction with past surgeries (p < .001). Youth age, sex, and assessment of condition severity were not significantly associated with satisfaction with surgical outcome. Depression, self-esteem, and negative consequences of having a CFC were not associated with satisfaction with past surgeries. Youth should be actively involved in the decision for craniofacial surgery. Youth who were more satisfied with their surgical outcomes also viewed themselves as having gained from the experience of living with a CFC. They felt that having a CFC made them stronger people and they believed that they were more accepting of others and more in touch with others’ feelings because of what they had been through. PMID:26114527

  7. Enhancement of International Dermatologists’ Pigmented Skin Lesion Biopsy Decisions Following Dermoscopy with Subsequent Integration of Multispectral Digital Skin Lesion Analysis

    PubMed Central

    Farberg, Aaron S.; Tucker, Natalie; White, Richard; Rigel, Darrell S.

    2016-01-01

    Background: Early detection and subsequent management of melanoma are critical for patient survival. New technologies have been developed to augment clinician analysis of suspicious pigmented skin lesions. Objective: To determine how information provided by a multispectral digital skin lesion analysis device affects the biopsy decisions of international dermatologists following clinical and dermoscopic pigmented skin lesion evaluation. Methods: Participants at a dermoscopy conference in Vienna, Austria, were shown 12 clinical and dermoscopic images of pigmented skin lesions (2 melanomas in situ, 3 invasive melanomas, and 7 low-grade dysplastic nevi) previously analyzed by multispectral digital skin lesion analysis. Participants were asked if they would biopsy the lesion based on clinical images, again after observing high-resolution dermoscopy images, and again when subsequently shown multispectral digital skin lesion analysis information. Results: Data were analyzed from a total of 70 international dermatologists. Overall, sensitivity was 58 percent after clinical evaluation (C) and 59 percent post-dermoscopy (D), but 74 percent after multispectral digital skin lesion analysis. Participant specificity was 56 percent (C) decreasing to 51 percent (D), but increasing to 61 percent with multispectral digital skin lesion analysis. Diagnostic accuracy was 57 percent (C) decreasing to 54 percent (D), but increasing to 67 percent for dermatologists after integrating the multispectral digital skin lesion analysis data into the biopsy decision. The overall number of lesions biopsied increased from 50 percent (C) to 53 percent (D), rising to 54 percent after multispectral digital skin lesion analysis. Conclusion: Decisions to biopsy melanocytic lesions were more sensitive and specific when multispectral digital skin lesion analysis information was provided with no significant increase in the number of biopsies recommended. Providing multispectral digital skin lesion analysis

  8. Enhancement of International Dermatologists’ Pigmented Skin Lesion Biopsy Decisions Following Dermoscopy with Subsequent Integration of Multispectral Digital Skin Lesion Analysis

    PubMed Central

    Farberg, Aaron S.; Tucker, Natalie; White, Richard; Rigel, Darrell S.

    2016-01-01

    Background: Early detection and subsequent management of melanoma are critical for patient survival. New technologies have been developed to augment clinician analysis of suspicious pigmented skin lesions. Objective: To determine how information provided by a multispectral digital skin lesion analysis device affects the biopsy decisions of international dermatologists following clinical and dermoscopic pigmented skin lesion evaluation. Methods: Participants at a dermoscopy conference in Vienna, Austria, were shown 12 clinical and dermoscopic images of pigmented skin lesions (2 melanomas in situ, 3 invasive melanomas, and 7 low-grade dysplastic nevi) previously analyzed by multispectral digital skin lesion analysis. Participants were asked if they would biopsy the lesion based on clinical images, again after observing high-resolution dermoscopy images, and again when subsequently shown multispectral digital skin lesion analysis information. Results: Data were analyzed from a total of 70 international dermatologists. Overall, sensitivity was 58 percent after clinical evaluation (C) and 59 percent post-dermoscopy (D), but 74 percent after multispectral digital skin lesion analysis. Participant specificity was 56 percent (C) decreasing to 51 percent (D), but increasing to 61 percent with multispectral digital skin lesion analysis. Diagnostic accuracy was 57 percent (C) decreasing to 54 percent (D), but increasing to 67 percent for dermatologists after integrating the multispectral digital skin lesion analysis data into the biopsy decision. The overall number of lesions biopsied increased from 50 percent (C) to 53 percent (D), rising to 54 percent after multispectral digital skin lesion analysis. Conclusion: Decisions to biopsy melanocytic lesions were more sensitive and specific when multispectral digital skin lesion analysis information was provided with no significant increase in the number of biopsies recommended. Providing multispectral digital skin lesion analysis

  9. Implementing a decision-theoretic design in clinical trials: why and how?

    PubMed

    Palmer, Christopher R; Shahumyan, Harutyun

    2007-11-30

    This paper addresses two main questions: first, why should Bayesian and other innovative, data-dependent design models be put into practice and, secondly, given the past dearth of actual applications, how might one example of such a design be implemented in a genuine example trial? Clinical trials amalgamate theory, practice and ethics, but this last point has become relegated to the background, rather than taking often a more appropriate primary role. Trial practice has evolved but has its roots in R. A. Fisher's randomized agricultural field trials of the 1920s. Reasons for, and consequences of, this are discussed from an ethical standpoint, drawing on an under-used dichotomy introduced by French authors Lellouch and Schwartz (Int. Statist. Rev. 1971; 39:27-36). Plenty of ethically motivated designs for trials, including Bayesian designs have been proposed, but have found little application thus far. One reason for this is a lack of awareness of such alternative designs among trialists, while another reason is a lack of user-friendly software to allow study simulations. To encourage implementation, a new C++ program called 'Daniel' is introduced, offering much potential to assist the design of today's randomized controlled trials. Daniel evaluates a particular decision-theoretic method suitable for coping with either two or three Bernoulli response treatments with input features allowing user-specified choices of: patient horizon (number to be treated before and after the comparative stages of the trial); an arbitrary fixed trial truncation size (to allow ready comparison with traditional designs or to cope with practical constraints); anticipated success rates and a measure of their uncertainty (a matter ignored in standard power calculations); and clinically relevant, and irrelevant, differences in treatment effect sizes. Error probabilities and expected trial durations can be thoroughly explored via simulation, it being better by far to harm 'computer patients

  10. Antecedents of ethical decision-making: intercollegiate sporting environments as clinical education and practice settings.

    PubMed

    Caswell, Shane V; Ambegaonkar, Jatin P; Caswell, Amanda M; Gould, Trenton E

    2009-01-01

    Unique among allied health care professions, athletic training is predominately practiced amid competitive intercollegiate sports. Competitive sporting environments have been suggested to adversely impact morality, ethical decision-making (EDM), and behavior. The purposes of this study were to (1) investigate the effect of institutional National Collegiate Athletic Association (NCAA) participation level on preferred ethical ideologies and EDM, (2) determine the relationship between professional status (athletic training student [ATS] or certified athletic trainer [ATC]) and ethical ideology preferences and EDM, and (3) examine whether preferred ethical ideology is related to differences in EDM. A nationally representative sample of 610 ATSs and ATCs from 30 athletic training education programs, stratified by NCAA division level, participated in the study. All participants completed a demographic survey, the Ethics Position Questionnaire, and the Dilemmas in Athletic Training Questionnaire. No significant relationships were noted between NCAA participation level and respondents' ethical ideology preferences. However, ATSs and ATCs demonstrated significant preferences for specific ethical ideologies, with students adopting the subjectivist ideology more than expected and the exceptionist ideology less than expected and ATCs adopting the exceptionist ideology more than expected and the situationist ideology less than expected. In contrast to some previous research, our results suggest that competitive sporting environments do not affect ATSs' and ATCs' ethical ideology and EDM abilities at the collegiate level. These findings serve as a baseline for future research examining the ethical ideologies and ethical decision-making levels of athletic training practitioners and other allied health professionals across clinical settings.

  11. [From library to clinical decision support systems: access of general practitioner to quality information].

    PubMed

    Fauquert, B

    2012-09-01

    Since 2003, the following tools have been implemented in Belgium for improving the access of general practioners to the EBM literature: the Digital Library for Health and the evidence-linker of the CEBAM, the portal EBMPracticeNet.be and the multidimensional electronic clinical decision support EBMeDS. The aim of this article is to show the progress achieved in the information dissemination toward the belgian general practioners, particularly the access from the electronic health record. From the literature published these last years, the opportunities cited by the users are for using EBM and the strong willingness for using these literature access in the future; the limits are the medical data coding, the irrelevance of the search results, the alerts fatigue induced by EBMeDS. The achievements done and planned for the new EBMPracticeNet guidelines portal and the EBMeDS system are explained in the aim of informing belgian healthcare professionals. These projects are claiming for lauching a participatory process in the production and dissemination of EBM information. The discussion is focused on the belgian healthcare system advantages, the solutions for a reasonable implementation of these projects and for increasing the place of an evidence-based information in the healthcare decision process. Finally the input of these projects to the continuing medical education and to the healthcare quality are discussed, in a context of multifactorial interaction healthcare design (complexity design).

  12. An Investigation of Factors Influencing Nurses' Clinical Decision-Making Skills.

    PubMed

    Wu, Min; Yang, Jinqiu; Liu, Lingying; Ye, Benlan

    2016-08-01

    This study aims to investigate the influencing factors on nurses' clinical decision-making (CDM) skills. A cross-sectional nonexperimental research design was conducted in the medical, surgical, and emergency departments of two university hospitals, between May and June 2014. We used a quantile regression method to identify the influencing factors across different quantiles of the CDM skills distribution and compared the results with the corresponding ordinary least squares (OLS) estimates. Our findings revealed that nurses were best at the skills of managing oneself. Educational level, experience, and the total structural empowerment had significant positive impacts on nurses' CDM skills, while the nurse-patient relationship, patient care and interaction, formal empowerment, and information empowerment were negatively correlated with nurses' CDM skills. These variables explained no more than 30% of the variance in nurses' CDM skills and mainly explained the lower quantiles of nurses' CDM skills distribution. PMID:26906246

  13. A secure communication using cascade chaotic computing systems on clinical decision support.

    PubMed

    Koksal, Ahmet Sertol; Er, Orhan; Evirgen, Hayrettin; Yumusak, Nejat

    2016-06-01

    Clinical decision support systems (C-DSS) provide supportive tools to the expert for the determination of the disease. Today, many of the support systems, which have been developed for a better and more accurate diagnosis, have reached a dynamic structure due to artificial intelligence techniques. However, in cases when important diagnosis studies should be performed in secret, a secure communication system is required. In this study, secure communication of a DSS is examined through a developed double layer chaotic communication system. The developed communication system consists of four main parts: random number generator, cascade chaotic calculation layer, PCM, and logical mixer layers. Thanks to this system, important patient data created by DSS will be conveyed to the center through a secure communication line.

  14. Service oriented architecture for clinical decision support: a systematic review and future directions.

    PubMed

    Loya, Salvador Rodriguez; Kawamoto, Kensaku; Chatwin, Chris; Huser, Vojtech

    2014-12-01

    The use of a service-oriented architecture (SOA) has been identified as a promising approach for improving health care by facilitating reliable clinical decision support (CDS). A review of the literature through October 2013 identified 44 articles on this topic. The review suggests that SOA related technologies such as Business Process Model and Notation (BPMN) and Service Component Architecture (SCA) have not been generally adopted to impact health IT systems' performance for better care solutions. Additionally, technologies such as Enterprise Service Bus (ESB) and architectural approaches like Service Choreography have not been generally exploited among researchers and developers. Based on the experience of other industries and our observation of the evolution of SOA, we found that the greater use of these approaches have the potential to significantly impact SOA implementations for CDS.

  15. An extended SQL for temporal data management in clinical decision-support systems.

    PubMed

    Das, A K; Tu, S W; Purcell, G P; Musen, M A

    1992-01-01

    We are developing a database implementation to support temporal data management for the T-HELPER physician workstation, an advice system for protocol-based care of patients who have HIV disease. To understand the requirements for the temporal database, we have analyzed the types of temporal predicates found in clinical-trial protocols. We extend the standard relational data model in three ways to support these querying requirements. First, we incorporate timestamps into the two-dimensional relational table to store the temporal dimension of both instant- and interval-based data. Second, we develop a set of operations on timepoints and intervals to manipulate timestamped data. Third, we modify the relational query language SQL so that its underlying algebra supports the specified operations on timestamps in relational tables. We show that our temporal extension to SQL meets the temporal data-management needs of protocol-directed decision support.

  16. Clinical decision support and acute low back pain: evidence-based order sets.

    PubMed

    Forseen, Scott E; Corey, Amanda S

    2012-10-01

    Low back pain is one of the most common reasons for visits to physicians in the ambulatory care setting. Estimated medical expenditures related to low back pain have increased disproportionately relative to the more modest increase in the prevalence of self-reported low back pain in the past decade. The increase in spine care expenditures has not been associated with improved patient outcomes. Evidence-based order templates presented in this article are designed to assist practitioners through the process of managing patients with acute low back pain. A logical method of choosing, developing, and implementing clinical decision support interventions is presented that is based on the best available scientific evidence. These templates may be reasonably expected to improve patient care, decrease inappropriate imaging utilization, reduce the inappropriate use of steroids and narcotics, and potentially decrease the number of inappropriate invasive procedures. PMID:23025864

  17. An Investigation of Factors Influencing Nurses' Clinical Decision-Making Skills.

    PubMed

    Wu, Min; Yang, Jinqiu; Liu, Lingying; Ye, Benlan

    2016-08-01

    This study aims to investigate the influencing factors on nurses' clinical decision-making (CDM) skills. A cross-sectional nonexperimental research design was conducted in the medical, surgical, and emergency departments of two university hospitals, between May and June 2014. We used a quantile regression method to identify the influencing factors across different quantiles of the CDM skills distribution and compared the results with the corresponding ordinary least squares (OLS) estimates. Our findings revealed that nurses were best at the skills of managing oneself. Educational level, experience, and the total structural empowerment had significant positive impacts on nurses' CDM skills, while the nurse-patient relationship, patient care and interaction, formal empowerment, and information empowerment were negatively correlated with nurses' CDM skills. These variables explained no more than 30% of the variance in nurses' CDM skills and mainly explained the lower quantiles of nurses' CDM skills distribution.

  18. Analysis of ETMS Data Quality for Traffic Flow Management Decisions

    NASA Technical Reports Server (NTRS)

    Chatterji, Gano B.; Sridhar, Banavar; Kim, Douglas

    2003-01-01

    The data needed for air traffic flow management decision support tools is provided by the Enhanced Traffic Management System (ETMS). This includes both the tools that are in current use and the ones being developed for future deployment. Since the quality of decision support provided by all these tools will be influenced by the quality of the input ETMS data, an assessment of ETMS data quality is needed. Motivated by this desire, ETMS data quality is examined in this paper in terms of the unavailability of flight plans, deviation from the filed flight plans, departure delays, altitude errors and track data drops. Although many of these data quality issues are not new, little is known about their extent. A goal of this paper is to document the magnitude of data quality issues supported by numerical analysis of ETMS data. Guided by this goal, ETMS data for a 24-hour period were processed to determine the number of aircraft with missing flight plan messages at any given instant of time. Results are presented for aircraft above 18,000 feet altitude and also at all altitudes. Since deviation from filed flight plan is also a major cause of trajectory-modeling errors, statistics of deviations are presented. Errors in proposed departure times and ETMS-generated vertical profiles are also shown. A method for conditioning the vertical profiles for improving demand prediction accuracy is described. Graphs of actual sector counts obtained using these vertical profiles are compared with those obtained using the Host data for sectors in the Fort Worth Center to demonstrate the benefit of preprocessing. Finally, results are presented to quantify the extent of data drops. A method for propagating track positions during ETMS data drops is also described.

  19. Should I Pack My Umbrella? Clinical versus Statistical Prediction of Mental Health Decisions

    ERIC Educational Resources Information Center

    Aegisdottir, Stefania; Spengler, Paul M.; White, Michael J.

    2006-01-01

    In this rejoinder, the authors respond to the insightful commentary of Strohmer and Arm, Chwalisz, and Hilton, Harris, and Rice about the meta-analysis on statistical versus clinical prediction techniques for mental health judgments. The authors address issues including the availability of statistical prediction techniques for real-life psychology…

  20. Clinical Analysis of Intracranial Hemangiopericytoma

    PubMed Central

    Park, Byoung-Joo; Hong, Yong-Kil; Jeun, Sin-Soo; Lee, Kwan-Sung; Lee, Youn-Soo

    2013-01-01

    Objective Intracranial hemangiopericytomas (HPCs) are rare tumors with aggressive behavior, including local recurrence and distant metastasis. We conducted this retrospective study to evaluate the efficacy of grossly total resection and adjuvant radiotherapy (RT) for these tumors. Methods A total of 13 patients treated for intracranial HPC from January 1995 through May 2013 were included in this retrospective study. We analyzed the clinical presentations, radiologic appearances, treatment results, and follow-up outcomes, as well as reviewed other studies. Results The ages of the patients at the time of diagnosis ranged from 26 to 73 years (mean : 48 years). The majority of the patients were male (92.3%), and the majority of the tumors were located in the parasagittal and falx. The ratio of intracranial HPCs to meningiomas was 13 : 598 in same period, or 2.2%. Seven patients (53.8%) had anaplastic HPCs. Nine patients (69.2%) underwent gross total tumor resection in the first operation without mortality. Eleven patients (84.6%) underwent postoperative adjuvant RT. Follow-up period ranged from 13 to 185 months (mean : 54.3 months). The local recurrence rate was 46.2% (6/13), and there were no distant metastases. The 10-year survival rate after initial surgery was 83.9%. The initial mean Karnofsky performance scale (KPS) was 70.8 and the final mean KPS was 64.6. Conclusion Gross total tumor resection upon initial surgery is very important. We believe that adjuvant RT is helpful even with maximal tumor resection. Molecular biologic analyses and chemotherapy studies are required to achieve better outcomes in recurrent intracranial HPCs. PMID:24294454

  1. Multiobjective Integrated Decision Analysis System (MIDAS): Volume 1, Model overview: Final report

    SciTech Connect

    Farber, M.; Brusger, E.; Gerber, M.

    1988-04-01

    MIDAS (Multiobjective Integrated Decision Analysis System) is an innovative utility planning tool that facilitates the analysis of risk. Three features distinguish this framework from other planning models: it incorporates a generalized decision analysis approach; it includes a completely integrated planning model for demand-supply evaluation; and the complete model runs on a microcomputer. 24 figs.

  2. EPA Growing DASEES (Decision Analysis For A Sustainable Environment, Economy & Society) - To Aid In Making Decisions On Complex Environmental Issues

    EPA Science Inventory

    Having a framework and tools to help sort through complicated environmental issues in an objective way would be useful to communities and risk managers, and all the stakeholders affected by these issues. This is one need that DASEES (Decision Analysis for a Sustainable En...

  3. SIDEKICK: Genomic data driven analysis and decision-making framework

    PubMed Central

    2010-01-01

    Background Scientists striving to unlock mysteries within complex biological systems face myriad barriers in effectively integrating available information to enhance their understanding. While experimental techniques and available data sources are rapidly evolving, useful information is dispersed across a variety of sources, and sources of the same information often do not use the same format or nomenclature. To harness these expanding resources, scientists need tools that bridge nomenclature differences and allow them to integrate, organize, and evaluate the quality of information without extensive computation. Results Sidekick, a genomic data driven analysis and decision making framework, is a web-based tool that provides a user-friendly intuitive solution to the problem of information inaccessibility. Sidekick enables scientists without training in computation and data management to pursue answers to research questions like "What are the mechanisms for disease X" or "Does the set of genes associated with disease X also influence other diseases." Sidekick enables the process of combining heterogeneous data, finding and maintaining the most up-to-date data, evaluating data sources, quantifying confidence in results based on evidence, and managing the multi-step research tasks needed to answer these questions. We demonstrate Sidekick's effectiveness by showing how to accomplish a complex published analysis in a fraction of the original time with no computational effort using Sidekick. Conclusions Sidekick is an easy-to-use web-based tool that organizes and facilitates complex genomic research, allowing scientists to explore genomic relationships and formulate hypotheses without computational effort. Possible analysis steps include gene list discovery, gene-pair list discovery, various enrichments for both types of lists, and convenient list manipulation. Further, Sidekick's ability to characterize pairs of genes offers new ways to approach genomic analysis that

  4. Medical decision analysis for first-line therapy of chronic myeloid leukemia.

    PubMed

    Rochau, Ursula; Sroczynski, Gaby; Wolf, Dominik; Schmidt, Stefan; Conrads-Frank, Annette; Jahn, Beate; Saverno, Kim; Brixner, Diana; Radich, Jerald; Gastl, Guenther; Siebert, Uwe

    2014-08-01

    Several tyrosine kinase inhibitors (TKIs) are approved for the treatment of chronic myeloid leukemia (CML). Our goal was to develop a clinical decision-analytic model for evaluation of the long-term effectiveness of different therapy regimens. We developed a Markov cohort model with a lifelong time horizon for first-line treatment with imatinib, dasatinib or nilotinib. Seven strategies including combinations of TKIs, chemotherapy and stem cell transplant were evaluated. The model was parameterized using published trial data, the Austrian CML registry and practice patterns estimated by experts. Health outcomes evaluated were life-years (LYs) and quality-adjusted LYs (QALYs). Based on our decision analysis, dasatinib following nilotinib failure was the most effective treatment in terms of LYs (19.8 LYs) and QALYs (16.1 QALYs). Sensitivity analyses showed that the ranking of strategies was mostly influenced by the duration of first- and second-line therapies. Our results may support decision-making regarding the sequential application of TKIs. PMID:24160847

  5. The 2013 symposium on pathology data integration and clinical decision support and the current state of field

    PubMed Central

    Baron, Jason M.; Dighe, Anand S.; Arnaout, Ramy; Balis, Ulysses J.; Black-Schaffer, W. Stephen; Carter, Alexis B.; Henricks, Walter H.; Higgins, John M.; Jackson, Brian R.; Kim, JiYeon; Klepeis, Veronica E.; Le, Long P.; Louis, David N.; Mandelker, Diana; Mermel, Craig H.; Michaelson, James S.; Nagarajan, Rakesh; Platt, Mihae E.; Quinn, Andrew M.; Rao, Luigi; Shirts, Brian H.; Gilbertson, John R.

    2014-01-01

    Background: Pathologists and informaticians are becoming increasingly interested in electronic clinical decision support for pathology, laboratory medicine and clinical diagnosis. Improved decision support may optimize laboratory test selection, improve test result interpretation and permit the extraction of enhanced diagnostic information from existing laboratory data. Nonetheless, the field of pathology decision support is still developing. To facilitate the exchange of ideas and preliminary studies, we convened a symposium entitled: Pathology data integration and clinical decision support. Methods: The symposium was held at the Massachusetts General Hospital, on May 10, 2013. Participants were selected to represent diverse backgrounds and interests and were from nine different institutions in eight different states. Results: The day included 16 plenary talks and three panel discussions, together covering four broad areas. Summaries of each presentation are included in this manuscript. Conclusions: A number of recurrent themes emerged from the symposium. Among the most pervasive was the dichotomy between diagnostic data and diagnostic information, including the opportunities that laboratories may have to use electronic systems and algorithms to convert the data they generate into more useful information. Differences between human talents and computer abilities were described; well-designed symbioses between humans and computers may ultimately optimize diagnosis. Another key theme related to the unique needs and challenges in providing decision support for genomics and other emerging diagnostic modalities. Finally, many talks relayed how the barriers to bringing decision support toward reality are primarily personnel, political, infrastructural and administrative challenges rather than technological limitations. PMID:24672737

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

    PubMed

    Gorini, Alessandra; Mazzocco, Ketti; Pravettoni, Gabriella

    2015-01-01

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

  7. Counseling About Medication-Induced Birth Defects with Clinical Decision Support in Primary Care

    PubMed Central

    Parisi, Sara M.; Handler, Steven M.; Koren, Gideon; Shevchik, Grant; Fischer, Gary S.

    2013-01-01

    Abstract Background We evaluated how computerized clinical decision support (CDS) affects the counseling women receive when primary care physicians (PCPs) prescribe potential teratogens and how this counseling affects women's behavior. Methods Between October 2008 and April 2010, all women aged 18–50 years visiting one of three community-based family practice clinics or an academic general internal medicine clinic were invited to complete a survey 5–30 days after their clinic visit. Women who received prescriptions were asked if they were counseled about teratogenic risks or contraception and if they used contraception at last intercourse. Results Eight hundred one women completed surveys; 27% received a prescription for a potential teratogen. With or without CDS, women prescribed potential teratogens were more likely than women prescribed safer medications to report counseling about teratogenic risks. However, even with CDS 43% of women prescribed potential teratogens reported no counseling. In multivariable models, women were more likely to report counseling if they saw a female PCP (odds ratio: 1.97; 95% confidence interval: 1.26–3.09). Women were least likely to report counseling if they received angiotensin-converting enzyme inhibitors or angiotensin receptor blockers. Women who were pregnant or trying to conceive were not more likely to report counseling. Nonetheless, women who received counseling about contraception or teratogenic risks were more likely to use contraception after being prescribed potential teratogens than women who received no counseling. Conclusions Physician counseling can reduce risk of medication-induced birth defects. However, efforts are needed to ensure that PCPs consistently inform women of teratogenic risks and provide access to highly effective contraception. PMID:23930947

  8. Multi-Criteria Decision Making for a Spatial Decision Support System on the Analysis of Changing Risk

    NASA Astrophysics Data System (ADS)

    Olyazadeh, Roya; van Westen, Cees; Bakker, Wim H.; Aye, Zar Chi; Jaboyedoff, Michel; Derron, Marc-Henri

    2014-05-01

    Natural hazard risk management requires decision making in several stages. Decision making on alternatives for risk reduction planning starts with an intelligence phase for recognition of the decision problems and identifying the objectives. Development of the alternatives and assigning the variable by decision makers to each alternative are employed to the design phase. Final phase evaluates the optimal choice by comparing the alternatives, defining indicators, assigning a weight to each and ranking them. This process is referred to as Multi-Criteria Decision Making analysis (MCDM), Multi-Criteria Evaluation (MCE) or Multi-Criteria Analysis (MCA). In the framework of the ongoing 7th Framework Program "CHANGES" (2011-2014, Grant Agreement No. 263953) of the European Commission, a Spatial Decision Support System is under development, that has the aim to analyse changes in hydro-meteorological risk and provide support to selecting the best risk reduction alternative. This paper describes the module for Multi-Criteria Decision Making analysis (MCDM) that incorporates monetary and non-monetary criteria in the analysis of the optimal alternative. The MCDM module consists of several components. The first step is to define criteria (or Indicators) which are subdivided into disadvantages (criteria that indicate the difficulty for implementing the risk reduction strategy, also referred to as Costs) and advantages (criteria that indicate the favorability, also referred to as benefits). In the next step the stakeholders can use the developed web-based tool for prioritizing criteria and decision matrix. Public participation plays a role in decision making and this is also planned through the use of a mobile web-version where the general local public can indicate their agreement on the proposed alternatives. The application is being tested through a case study related to risk reduction of a mountainous valley in the Alps affected by flooding. Four alternatives are evaluated in

  9. Clinical decision-making of cardiologists regarding admission and treatment of patients with suspected unstable angina or non-ST-elevation myocardial infarction: protocol of a clinical vignette study

    PubMed Central

    Engel, Josien; van der Wulp, Ineke; Poldervaart, Judith M; Reitsma, Johannes B; de Bruijne, Martine C; Wagner, Cordula

    2015-01-01

    Introduction Cardiologists face the difficult task of rapidly distinguishing cardiac-related chest pain from other conditions, and to thoroughly consider whether invasive diagnostic procedures or treatments are indicated. The use of cardiac risk-scoring instruments has been recommended in international cardiac guidelines. However, it is unknown to what degree cardiac risk scores and other clinical information influence cardiologists’ decision-making. This paper describes the development of a binary choice experiment using realistic descriptions of clinical cases. The study aims to determine the importance cardiologists put on different types of clinical information, including cardiac risk scores, when deciding on the management of patients with suspected unstable angina or non-ST-elevation myocardial infarction. Methods and analysis Cardiologists were asked, in a nationwide survey, to weigh different clinical factors in decision-making regarding patient admission and treatment using realistic descriptions of patients in which specific characteristics are varied in a systematic way (eg, web-based clinical vignettes). These vignettes represent patients with suspected unstable angina or non-ST-elevation myocardial infarction. Associations between several clinical characteristics, with cardiologists’ management decisions, will be analysed using generalised linear mixed models. Ethics and dissemination The study has received ethics approval and informed consent will be obtained from all participating cardiologists. The results of the study will provide insight into the relative importance of cardiac risk scores and other clinical information in cardiac decision-making. Further, the results indicate cardiologists’ adherence to the European Society of Cardiology guideline recommendations. In addition, the detailed description of the method of vignette development applied in this study could assist other researchers or clinicians in creating future choice experiments

  10. A review and classification of approaches for dealing with uncertainty in multi-criteria decision analysis for healthcare decisions.

    PubMed

    Broekhuizen, Henk; Groothuis-Oudshoorn, Catharina G M; van Til, Janine A; Hummel, J Marjan; IJzerman, Maarten J

    2015-05-01

    Multi-criteria decision analysis (MCDA) is increasingly used to support decisions in healthcare involving multiple and conflicting criteria. Although uncertainty is usually carefully addressed in health economic evaluations, whether and how the different sources of uncertainty are dealt with and with what methods in MCDA is less known. The objective of this study is to review how uncertainty can be explicitly taken into account in MCDA and to discuss which approach may be appropriate for healthcare decision makers. A literature review was conducted in the Scopus and PubMed databases. Two reviewers independently categorized studies according to research areas, the type of MCDA used, and the approach used to quantify uncertainty. Selected full text articles were read for methodological details. The search strategy identified 569 studies. The five approaches most identified were fuzzy set theory (45% of studies), probabilistic sensitivity analysis (15%), deterministic sensitivity analysis (31%), Bayesian framework (6%), and grey theory (3%). A large number of papers considered the analytic hierarchy process in combination with fuzzy set theory (31%). Only 3% of studies were published in healthcare-related journals. In conclusion, our review identified five different approaches to take uncertainty into account in MCDA. The deterministic approach is most likely sufficient for most healthcare policy decisions because of its low complexity and straightforward implementation. However, more complex approaches may be needed when multiple sources of uncertainty must be considered simultaneously.

  11. [Adequacy of clinical interventions in patients with advanced and complex disease. Proposal of a decision making algorithm].

    PubMed

    Ameneiros-Lago, E; Carballada-Rico, C; Garrido-Sanjuán, J A; García Martínez, A

    2015-01-01

    Decision making in the patient with chronic advanced disease is especially complex. Health professionals are obliged to prevent avoidable suffering and not to add any more damage to that of the disease itself. The adequacy of the clinical interventions consists of only offering those diagnostic and therapeutic procedures appropriate to the clinical situation of the patient and to perform only those allowed by the patient or representative. In this article, the use of an algorithm is proposed that should serve to help health professionals in this decision making process.

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

    PubMed Central

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

    2014-01-01

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

  13. Evaluating acceptance and user experience of a guideline-based clinical decision support system execution platform.

    PubMed

    Buenestado, David; Elorz, Javier; Pérez-Yarza, Eduardo G; Iruetaguena, Ander; Segundo, Unai; Barrena, Raúl; Pikatza, Juan M

    2013-04-01

    This study aims to determine what the initial disposition of physicians towards the use of Clinical Decision Support Systems (CDSS) based on Computerised Clinical Guidelines and Protocols (CCGP) is; and whether their prolonged utilisation has a positive effect on their intention to adopt them in the future. For a period of 3 months, 8 volunteer paediatricians monitored each up to 10 asthmatic patients using two CCGPs deployed in the-GuidesMed CDSS. A Technology Acceptance Model (TAM) questionnaire was supplied to them before and after using the system. Results from both questionnaires are analysed searching for significant improvements in opinion between them. An additional survey was performed to analyse the usability of the system. It was found that initial disposition of physicians towards e-GuidesMed is good. Improvement between the pre and post iterations of the TAM questionnaire has been found to be statistically significant. Nonetheless, slightly lower values in the Compatibility and Habit variables show that participants perceive possible difficulties to integrate e-GuidesMed into their daily routine. The variable Facilitators shows the highest correlation with the Intention to Use. Usability of the system has also been rated very high and, in this regard, no fundamental flaw has been detected. Initial views towards e-GuidesMed are positive, and become reinforced after continued utilisation of the system. In order to achieve an effective implementation, it becomes essential to facilitate conditions to integrate the system into the physician's daily routine.

  14. Clinical Decision Support for the Classification of Diabetic Retinopathy: A Comparison of Manual and Automated Results.

    PubMed

    Mitsch, Christoph; Fehre, Karsten; Prager, Sonja; Scholda, Christoph; Kriechbaum, Katharina; Wrba, Thomas; Schmidt-Erfurth, Ursula

    2016-01-01

    The management of diabetic retinopathy, a frequent ophthalmological manifestation of diabetes mellitus, consists of regular examinations and a standardized, manual classification of disease severity, which is used to recommend re-examination intervals. To evaluate the feasibility and safety of implementing automated, guideline-based diabetic retinopathy (DR) grading into clinical routine by applying established clinical decision support (CDS) technology. We compared manual with automated classification that was generated using medical documentation and an Arden server with a specific medical logic module. Of 7169 included eyes, 47% (n=3373) showed inter-method classification agreement, specifically 29.4% in mild DR, 38.3% in moderate DR, 27.6% in severe DR, and 65.7% in proliferative DR. We demonstrate that the implementation of a CDS system for automated disease severity classification in diabetic retinopathy is feasible but also that, due to the highly individual nature of medical documentation, certain important criteria for the used electronic health record system need to be met in order to achieve reliable results.

  15. Decision Analysis For A Sustainable Environment, Economy, & Society

    EPA Science Inventory

    Environmental decisions are often made without consideration of the roles that ecosystem services play. Most decision-makers do not currently have access to useful or usable methods and approaches when they are presented with choices that will have significant ecosystem impacts....

  16. Decentralisation of Health Services in Fiji: A Decision Space Analysis

    PubMed Central

    Mohammed, Jalal; North, Nicola; Ashton, Toni

    2016-01-01

    Background: Decentralisation aims to bring services closer to the community and has been advocated in the health sector to improve quality, access and equity, and to empower local agencies, increase innovation and efficiency and bring healthcare and decision-making as close as possible to where people live and work. Fiji has attempted two approaches to decentralisation. The current approach reflects a model of deconcentration of outpatient services from the tertiary level hospital to the peripheral health centres in the Suva subdivision. Methods: Using a modified decision space approach developed by Bossert, this study measures decision space created in five broad categories (finance, service organisation, human resources, access rules, and governance rules) within the decentralised services. Results: Fiji’s centrally managed historical-based allocation of financial resources and management of human resources resulted in no decision space for decentralised agents. Narrow decision space was created in the service organisation category where, with limited decision space created over access rules, Fiji has seen greater usage of its decentralised health centres. There remains limited decision space in governance. Conclusion: The current wave of decentralisation reveals that, whilst the workload has shifted from the tertiary hospital to the peripheral health centres, it has been accompanied by limited transfer of administrative authority, suggesting that Fiji’s deconcentration reflects the transfer of workload only with decision-making in the five functional areas remaining largely centralised. As such, the benefits of decentralisation for users and providers are likely to be limited. PMID:26927588

  17. Decision Analysis for a Sustainable Environment, Economy & Society

    EPA Science Inventory

    Environmental decisions are often made without consideration of the roles that ecosystem services play. Most decision-makers do not currently have access to useful or usable methods and approaches when they are presented with choices that will have significant ecosystem impacts. ...

  18. Child Protection Decision Making: A Factorial Analysis Using Case Vignettes

    ERIC Educational Resources Information Center

    Stokes, Jacqueline; Schmidt, Glen

    2012-01-01

    This study explored decision making by child protection social workers in the province of British Columbia, Canada. A factorial survey method was used in which case vignettes were constructed by randomly assigning a number of key characteristics associated with decision making in child protection. Child protection social workers (n = 118) assessed…

  19. The Morningside Initiative: Collaborative Development of a Knowledge Repository to Accelerate Adoption of Clinical Decision Support

    PubMed Central

    Greenes, Robert; Bloomrosen, Meryl; Brown-Connolly, Nancy E.; Curtis, Clayton; Detmer, Don E; Enberg, Robert; Fridsma, Douglas; Fry, Emory; Goldstein, Mary K; Haug, Peter; Hulse, Nathan; Hongsermeier, Tonya; Maviglia, Saverio; Robbins, Craig W; Shah, Hemant

    2010-01-01

    The Morningside Initiative is a public-private activity that has evolved from an August, 2007, meeting at the Morningside Inn, in Frederick, MD, sponsored by the Telemedicine and Advanced Technology Research Center (TATRC) of the US Army Medical Research Materiel Command. Participants were subject matter experts in clinical decision support (CDS) and included representatives from the Department of Defense, Veterans Health Administration, Kaiser Permanente, Partners Healthcare System, Henry Ford Health System, Arizona State University, and the American Medical Informatics Association (AMIA). The Morningside Initiative was convened in response to the AMIA Roadmap for National Action on Clinical Decision Support and on the basis of other considerations and experiences of the participants. Its formation was the unanimous recommendation of participants at the 2007 meeting which called for creating a shared repository of executable knowledge for diverse health care organizations and practices, as well as health care system vendors. The rationale is based on the recognition that sharing of clinical knowledge needed for CDS across organizations is currently virtually non-existent, and that, given the considerable investment needed for creating, maintaining and updating authoritative knowledge, which only larger organizations have been able to undertake, this is an impediment to widespread adoption and use of CDS. The Morningside Initiative intends to develop and refine (1) an organizational framework, (2) a technical approach, and (3) CDS content acquisition and management processes for sharing CDS knowledge content, tools, and experience that will scale with growing numbers of participants and can be expanded in scope of content and capabilities. Intermountain Healthcare joined the initial set of participants shortly after its formation. The efforts of the Morningside Initiative are intended to serve as the basis for a series of next steps in a national agenda for CDS. It

  20. Does accountability for reasonableness work? A protocol for a mixed methods study using an audit tool to evaluate the decision-making of clinical commissioning groups in England

    PubMed Central

    Kieslich, Katharina; Littlejohns, Peter

    2015-01-01

    Introduction Clinical commissioning groups (CCGs) in England are tasked with making difficult decisions on which healthcare services to provide against the background of limited budgets. The question is how to ensure that these decisions are fair and legitimate. Accounts of what constitutes fair and legitimate priority setting in healthcare include Daniels’ and Sabin's accountability for reasonableness (A4R) and Clark's and Weale's framework for the identification of social values. This study combines these accounts and asks whether the decisions of those CCGs that adhere to elements of such accounts are perceived as fairer and more legitimate by key stakeholders. The study addresses the empirical gap arising from a lack of research on whether frameworks such as A4R hold what they promise. It aims to understand the criteria that feature in CCG decision-making. Finally, it examines the usefulness of a decision-making audit tool (DMAT) in identifying the process and content criteria that CCGs apply when making decisions. Methods and analysis The adherence of a sample of CCGs to criteria emerging from theories of fair priority setting will be examined using the DMAT developed by PL. The results will be triangulated with data from semistructured interviews with key stakeholders in the CCG sample to ascertain whether there is a correlation between those CCGs that performed well in the DMAT exercise and those whose decisions are perceived positively by interviewees. Descriptive statistical methods will be used to analyse the DMAT data. A combination of quantitative and qualitative content analysis methods will be used to analyse the interview transcripts. Ethics and dissemination Full ethics approval was received by the King's College London Biomedical Sciences, Dentistry, Medicine and Natural and Mathematical Sciences Research Ethics Subcommittee. The results of the study will be disseminated through publications in peer review journals. PMID:26163034

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

    PubMed

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

    2013-09-01

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

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

    PubMed

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

    2013-09-01

    Decision making in health care has evolved substantially over the last century. Up until the late 1970s, medical decision making was predominantly intuitive and anecdotal. It was based on trial and error and involved high levels of problem solving. The 1980s gave way to empirical medicine, which was evidence based probabilistic, and involved pattern recognition and less problem solving. Although this represented a major advance in the quality of medical decision making, limitations existed. The advantages of the gold standard of the randomized controlled clinical trial (RCT) are well-known and this technique is irreplaceable in its ability to answer critical clinical questions. However, the RCT does have drawbacks. RCTs are expensive and can only capture a snapshot in time. As treatments change and new technologies emerge, new expensive clinical trials must be undertaken to reevaluate them. Furthermore, in order to best evaluate a single intervention, other factors must be controlled. In addition, the study population may not match that of another organization or provider. Although evidence-based medicine has provided powerful data for clinicians, effectively and efficiently tailoring it to the individual has not yet evolved. We are now in a period of transition from this evidence-based era to one dominated by the personalization and customization of care. It will be fueled by policy decisions to shift financial responsibility to the patient, creating a powerful and sophisticated consumer, unlike any patient we have known before. The challenge will be to apply medical evidence and personal preferences to medical decisions and deliver it efficiently in the increasingly busy clinical setting. In this article, we provide a robust review of the concepts of customized care and some of techniques to deliver it. We will illustrate this through a personalized decision model for the treatment decision after a first-time anterior shoulder dislocation. PMID:23924748

  3. Comparison of residents’ approaches to clinical decisions before and after the implementation of Evidence Based Medicine course

    PubMed Central

    KARIMIAN, ZAHRA; KOJURI, JAVAD; SAGHEB, MOHAMMAD MAHDI; MAHBOUDI, ALI; SABER, MAHBOOBEH; AMINI, MITRA; DEHGHANI, MOHAMMAD REZA

    2014-01-01

    Introduction: It has been found that the decision-making process in medicine is affected, to a large extent, by one’s experience, individual mentality, previous models, and common habitual approaches, in addition to scientific principles. Evidence-based medicine is an approach attempting to reinforce scientific, systematic and critical thinking in physicians and provide the ground for optimal decision making. In this connection, the purpose of the present study is to find out to what extent the education of evidence based medicine affects clinical decision making. Methods: The present quasi-experimental study was carried out on 110 clinical residents, who started their education in September, 2012 and finally 62 residents filled out the questionnaires. The instrument used was a researcher-made questionnaire containing items on four decision-making approaches. The questionnaire was used both as a pre-test and a post-test to assess the residents’ viewpoints on decision making approaches. The validity of the questionnaire was determined using medical education and clinical professionals’ viewpoints, and the reliability was calculated through Chronbach alpha; it was found to be 0.93. The results were analyzed by paired t-test using SPSS, version 14. Results: The results demonstrated that evidence-based medicine workshop significantly affected the residents’ decision-making approaches (p<0.001). The pre-test showed that principles-based, reference-based and routine model-based approaches were more preferred before the program (p<0.001). However, after the implementation of the program, the dominant approaches used by the residents in their decision making were evidence-based ones.  Conclusion: To develop the evidence-based approach, it is necessary for educational programs to continue steadily and goal-orientedly. In addition, the equipment infrastructure such as the Internet, access to data bases, scientific data, and clinical guides should develop more in the

  4. [Task analysis of clinical laboratory physician in acute hospital].

    PubMed

    Murakami, Junko

    2013-06-01

    Appropriate communications between clinical divisions and clinical laboratories are required to improve the quality of health care in hospitals. In this paper, the routine work of a clinical laboratory physician is presented. 1. In order to support attentive medical practice, we have established a consultation service system for handling questions from medical staff. The main clients are doctors and clinical laboratory technologists. 2. In order to improve the quality of infectious disease analysis, we have recommended obtaining two or more blood culture sets to achieve good sensitivity. The order rate of multiple blood culture sets increased 90% or more in 2011. 3. In order to provide appropriate blood transfusion, we intervene in inappropriate transfusion plans. 4. In order to support prompt decision making, we send E-mails to physicians regarding critical values. 5. We send reports on the morphology of cells(peripheral blood and bone marrow), IEP, flow cytometry, irregular antibodies, and so on. It has been realized that doctors want to know better solutions immediately rather than the best solution tomorrow morning. We would like to contribute to improving the quality of health care in Saitama Cooperative Hospital as clinical laboratory physicians.

  5. Selection of Representative Models for Decision Analysis Under Uncertainty

    NASA Astrophysics Data System (ADS)

    Meira, Luis A. A.; Coelho, Guilherme P.; Santos, Antonio Alberto S.; Schiozer, Denis J.

    2016-03-01

    The decision-making process in oil fields includes a step of risk analysis associated with the uncertainties present in the variables of the problem. Such uncertainties lead to hundreds, even thousands, of possible scenarios that are supposed to be analyzed so an effective production strategy can be selected. Given this high number of scenarios, a technique to reduce this set to a smaller, feasible subset of representative scenarios is imperative. The selected scenarios must be representative of the original set and also free of optimistic and pessimistic bias. This paper is devoted to propose an assisted methodology to identify representative models in oil fields. To do so, first a mathematical function was developed to model the representativeness of a subset of models with respect to the full set that characterizes the problem. Then, an optimization tool was implemented to identify the representative models of any problem, considering not only the cross-plots of the main output variables, but also the risk curves and the probability distribution of the attribute-levels of the problem. The proposed technique was applied to two benchmark cases and the results, evaluated by experts in the field, indicate that the obtained solutions are richer than those identified by previously adopted manual approaches. The program bytecode is available under request.

  6. Formative assessment and design of a complex clinical decision support tool for pulmonary embolism.

    PubMed

    Khan, Sundas; McCullagh, Lauren; Press, Anne; Kharche, Manish; Schachter, Andy; Pardo, Salvatore; McGinn, Thomas

    2016-02-01

    Electronic health record (EHR)-based clinical decision support (CDS) tools are rolled out with the urgency to meet federal requirements without time for usability testing and refinement of the user interface. As part of a larger project to design, develop and integrate a pulmonary embolism CDS tool for emergency physicians, we conducted a formative assessment to determine providers' level of interest and input on designs and content. This was a study to conduct a formative assessment of emergency medicine (EM) physicians that included focus groups and key informant interviews. The focus of this study was twofold, to determine the general attitude towards CDS tool integration and the ideal integration point into the clinical workflow. To accomplish this, we first approached EM physicians in a focus group, then, during key informant interviews, we presented workflow designs and gave a scenario to help the providers visualise how the CDS tool works. Participants were asked questions regarding the trigger location, trigger words, integration into their workflow, perceived utility and heuristic of the tool. Results from the participants' survey responses to trigger location, perceived utility and efficiency, indicated that the providers felt the tool would be more of a hindrance than an aid. However, some providers commented that they had not had exposure to CDS tools but had used online calculators, and thought the tools would be helpful at the point-of-care if integrated into the EHR. Furthermore, there was a preference for an order entry wireframe. This study highlights several factors to consider when designing CDS tools: (1) formative assessment of EHR functionality and clinical environment workflow, (2) focus groups and key informative interviews to incorporate providers' perceptions of CDS and workflow integration and/or (3) the demonstration of proposed workflows through wireframes to help providers visualise design concepts.

  7. Supporting clinical decision making during deep brain stimulation surgery by means of a stochastic dynamical model

    NASA Astrophysics Data System (ADS)

    Karamintziou, Sofia D.; Tsirogiannis, George L.; Stathis, Pantelis G.; Tagaris, George A.; Boviatsis, Efstathios J.; Sakas, Damianos E.; Nikita, Konstantina S.

    2014-10-01

    Objective. During deep brain stimulation (DBS) surgery for the treatment of advanced Parkinson's disease (PD), microelectrode recording (MER) in conjunction with functional stimulation techniques are commonly applied for accurate electrode implantation. However, the development of automatic methods for clinical decision making has to date been characterized by the absence of a robust single-biomarker approach. Moreover, it has only been restricted to the framework of MER without encompassing intraoperative macrostimulation. Here, we propose an integrated series of novel single-biomarker approaches applicable to the entire electrophysiological procedure by means of a stochastic dynamical model. Approach. The methods are applied to MER data pertinent to ten DBS procedures. Considering the presence of measurement noise, we initially employ a multivariate phase synchronization index for automatic delineation of the functional boundaries of the subthalamic nucleus (STN) and determination of the acceptable MER trajectories. By introducing the index into a nonlinear stochastic model, appropriately fitted to pre-selected MERs, we simulate the neuronal response to periodic stimuli (130 Hz), and examine the Lyapunov exponent as an indirect indicator of the clinical effectiveness yielded by stimulation at the corresponding sites. Main results. Compared with the gold-standard dataset of annotations made intraoperatively by clinical experts, the STN detection methodology demonstrates a false negative rate of 4.8% and a false positive rate of 0%, across all trajectories. Site eligibility for implantation of the DBS electrode, as implicitly determined through the Lyapunov exponent of the proposed stochastic model, displays a sensitivity of 71.43%. Significance. The suggested comprehensive method exhibits remarkable performance in automatically determining both the acceptable MER trajectories and the optimal stimulation sites, thereby having the potential to accelerate precise

  8. Addressing preference heterogeneity in public health policy by combining Cluster Analysis and Multi-Criteria Decision Analysis: Proof of Method.

    PubMed

    Kaltoft, Mette Kjer; Turner, Robin; Cunich, Michelle; Salkeld, Glenn; Nielsen, Jesper Bo; Dowie, Jack

    2015-01-01

    The use of subgroups based on biological-clinical and socio-demographic variables to deal with population heterogeneity is well-established in public policy. The use of subgroups based on preferences is rare, except when religion based, and controversial. If it were decided to treat subgroup preferences as valid determinants of public policy, a transparent analytical procedure is needed. In this proof of method study we show how public preferences could be incorporated into policy decisions in a way that respects both the multi-criterial nature of those decisions, and the heterogeneity of the population in relation to the importance assigned to relevant criteria. It involves combining Cluster Analysis (CA), to generate the subgroup sets of preferences, with Multi-Criteria Decision Analysis (MCDA), to provide the policy framework into which the clustered preferences are entered. We employ three techniques of CA to demonstrate that not only do different techniques produce different clusters, but that choosing among techniques (as well as developing the MCDA structure) is an important task to be undertaken in implementing the approach outlined in any specific policy context. Data for the illustrative, not substantive, application are from a Randomized Controlled Trial of online decision aids for Australian men aged 40-69 years considering Prostate-specific Antigen testing for prostate cancer. We show that such analyses can provide policy-makers with insights into the criterion-specific needs of different subgroups. Implementing CA and MCDA in combination to assist in the development of policies on important health and community issues such as drug coverage, reimbursement, and screening programs, poses major challenges -conceptual, methodological, ethical-political, and practical - but most are exposed by the techniques, not created by them.

  9. Valuing health for clinical and economic decisions: directions relevant for rheumatologists.

    PubMed

    Harrison, Mark J; Bansback, Nick J; Marra, Carlo A; Drummond, Michael; Tugwell, Peter S; Boonen, Annelies

    2011-08-01

    The quality-adjusted life-year (QALY) is a construct that integrates the value or preference for a health state over the period of time in that health state. The main use of QALY is in cost-utility analysis, to help make resource allocation decisions when faced with choices. Although the concept of the QALY is appealing, there is ongoing debate regarding their usefulness and approaches to deriving QALY. In 2008, OMERACT engaged in an effort to agree on QALY approaches that can be used in rheumatology. Based on a Web questionnaire and a subsequent meeting, rheumatologists questioned whether it was relevant for OMERACT (1) to investigate use of a QALY that represents the patients' perspective, (2) to explore the validity of the visual analog scale (VAS) to value health, and (3) to understand the validity of mapping health-specific instruments on existing preference instruments. This article discusses the pros and cons of these points in light of current insight from the point of view of health economics and decision-making theory. It also considers the further research agenda toward a QALY approach in rheumatology. PMID:21807800

  10. The Need for Clinical Decision Support Integrated with the Electronic Health Record for the Clinical Application of Whole Genome Sequencing Information

    PubMed Central

    Welch, Brandon M.; Kawamoto, Kensaku

    2013-01-01

    Whole genome sequencing (WGS) is rapidly approaching widespread clinical application. Technology advancements over the past decade, since the first human genome was decoded, have made it feasible to use WGS for clinical care. Future advancements will likely drive down the price to the point wherein WGS is routinely available for care. However, were this to happen today, most of the genetic information available to guide clinical care would go unused due to the complexity of genetics, limited physician proficiency in genetics, and lack of genetics professionals in the clinical workforce. Furthermore, these limitations are unlikely to change in the future. As such, the use of clinical decision support (CDS) to guide genome-guided clinical decision-making is imperative. In this manuscript, we describe the barriers to widespread clinical application of WGS information, describe how CDS can be an important tool for overcoming these barriers, and provide clinical examples of how genome-enabled CDS can be used in the clinical setting. PMID:25411643

  11. Multi-criteria decision analysis with probabilistic risk assessment for the management of contaminated ground water

    SciTech Connect

    Khadam, Ibrahim M.; Kaluarachchi, Jagath J

    2003-10-01

    Traditionally, environmental decision analysis in subsurface contamination scenarios is performed using cost-benefit analysis. In this paper, we discuss some of the limitations associated with cost-benefit analysis, especially its definition of risk, its definition of cost of risk, and its poor ability to communicate risk-related information. This paper presents an integrated approach for management of contaminated ground water resources using health risk assessment and economic analysis through a multi-criteria decision analysis framework. The methodology introduces several important concepts and definitions in decision analysis related to subsurface contamination. These are the trade-off between population risk and individual risk, the trade-off between the residual risk and the cost of risk reduction, and cost-effectiveness as a justification for remediation. The proposed decision analysis framework integrates probabilistic health risk assessment into a comprehensive, yet simple, cost-based multi-criteria decision analysis framework. The methodology focuses on developing decision criteria that provide insight into the common questions of the decision-maker that involve a number of remedial alternatives. The paper then explores three potential approaches for alternative ranking, a structured explicit decision analysis, a heuristic approach of importance of the order of criteria, and a fuzzy logic approach based on fuzzy dominance and similarity analysis. Using formal alternative ranking procedures, the methodology seeks to present a structured decision analysis framework that can be applied consistently across many different and complex remediation settings. A simple numerical example is presented to demonstrate the proposed methodology. The results showed the importance of using an integrated approach for decision-making considering both costs and risks. Future work should focus on the application of the methodology to a variety of complex field conditions to

  12. Principles and clinical applications of image analysis.

    PubMed

    Kisner, H J

    1988-12-01

    Image processing has traveled to the lunar surface and back, finding its way into the clinical laboratory. Advances in digital computers have improved the technology of image analysis, resulting in a wide variety of medical applications. Offering improvements in turnaround time, standardized systems, increased precision, and walkaway automation, digital image analysis has likely found a permanent home as a diagnostic aid in the interpretation of microscopic as well as macroscopic laboratory images.

  13. An analysis of symbolic linguistic computing models in decision making

    NASA Astrophysics Data System (ADS)

    Rodríguez, Rosa M.; Martínez, Luis

    2013-01-01

    It is common that experts involved in complex real-world decision problems use natural language for expressing their knowledge in uncertain frameworks. The language is inherent vague, hence probabilistic decision models are not very suitable in such cases. Therefore, other tools such as fuzzy logic and fuzzy linguistic approaches have been successfully used to model and manage such vagueness. The use of linguistic information implies to operate with such a type of information, i.e. processes of computing with words (CWW). Different schemes have been proposed to deal with those processes, and diverse symbolic linguistic computing models have been introduced to accomplish the linguistic computations. In this paper, we overview the relationship between decision making and CWW, and focus on symbolic linguistic computing models that have been widely used in linguistic decision making to analyse if all of them can be considered inside of the CWW paradigm.

  14. Discussing End-of-Life Decisions in a Clinical Ethics Committee: An Interview Study of Norwegian Doctors' Experience.

    PubMed

    Bahus, Marianne K; Førde, Reidun

    2016-09-01

    With disagreement, doubts, or ambiguous grounds in end-of-life decisions, doctors are advised to involve a clinical ethics committee (CEC). However, little has been published on doctors' experiences with discussing an end-of-life decision in a CEC. As part of the quality assurance of this work, we wanted to find out if clinicians have benefited from discussing end-of-life decisions in CECs and why. We will disseminate some Norwegian doctors' experiences when discussing end-of-life decisions in CECs, based on semi-structured interviews with fifteen Norwegian physicians who had brought an end-of-life decision case to a CEC. Almost half of the cases involved conflicts with the patients' relatives. In a majority of the cases, there was uncertainty about what would be the ethically preferable solution. Reasons for referring the case to the CEC were to get broader illumination of the case, to get perspective from people outside the team, to get advice, or to get moral backing on a decision already made. A great majority of the clinicians reported an overall positive experience with the CECs' discussions. In cases where there was conflict, the clinicians reported less satisfaction with the CECs' discussions. The study shows that most doctors who have used a CEC in an end-of-life decision find it useful to have ethical and/or legal aspects illuminated, and to have the dilemma scrutinized from a new perspective. A systematic discussion seems to be significant to the clinicians.

  15. Discussing End-of-Life Decisions in a Clinical Ethics Committee: An Interview Study of Norwegian Doctors' Experience.

    PubMed

    Bahus, Marianne K; Førde, Reidun

    2016-09-01

    With disagreement, doubts, or ambiguous grounds in end-of-life decisions, doctors are advised to involve a clinical ethics committee (CEC). However, little has been published on doctors' experiences with discussing an end-of-life decision in a CEC. As part of the quality assurance of this work, we wanted to find out if clinicians have benefited from discussing end-of-life decisions in CECs and why. We will disseminate some Norwegian doctors' experiences when discussing end-of-life decisions in CECs, based on semi-structured interviews with fifteen Norwegian physicians who had brought an end-of-life decision case to a CEC. Almost half of the cases involved conflicts with the patients' relatives. In a majority of the cases, there was uncertainty about what would be the ethically preferable solution. Reasons for referring the case to the CEC were to get broader illumination of the case, to get perspective from people outside the team, to get advice, or to get moral backing on a decision already made. A great majority of the clinicians reported an overall positive experience with the CECs' discussions. In cases where there was conflict, the clinicians reported less satisfaction with the CECs' discussions. The study shows that most doctors who have used a CEC in an end-of-life decision find it useful to have ethical and/or legal aspects illuminated, and to have the dilemma scrutinized from a new perspective. A systematic discussion seems to be significant to the clinicians. PMID:26922945

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

    ERIC Educational Resources Information Center

    Blount, Kamilah V.

    2013-01-01

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

  17. An Automated System for Generating Situation-Specific Decision Support in Clinical Order Entry from Local Empirical Data

    ERIC Educational Resources Information Center

    Klann, Jeffrey G.

    2011-01-01

    Clinical Decision Support is one of the only aspects of health information technology that has demonstrated decreased costs and increased quality in healthcare delivery, yet it is extremely expensive and time-consuming to create, maintain, and localize. Consequently, a majority of health care systems do not utilize it, and even when it is…

  18. Clinical information system services and capabilities desired for scalable, standards-based, service-oriented decision support: consensus assessment of the Health Level 7 clinical decision support Work Group.

    PubMed

    Kawamoto, Kensaku; Jacobs, Jason; Welch, Brandon M; Huser, Vojtech; Paterno, Marilyn D; Del Fiol, Guilherme; Shields, David; Strasberg, Howard R; Haug, Peter J; Liu, Zhijing; Jenders, Robert A; Rowed, David W; Chertcoff, Daryl; Fehre, Karsten; Adlassnig, Klaus-Peter; Curtis, A Clayton

    2012-01-01

    A standards-based, service-oriented architecture for clinical decision support (CDS) has the potential to significantly enhance CDS scalability and robustness. To enable such a CDS architecture, the Health Level 7 CDS Work Group reviewed the literature, hosted multi-stakeholder discussions, and consulted domain experts to identify and prioritize the services and capabilities required from clinical information systems (CISs) to enable service-oriented CDS. In addition, relevant available standards were identified. Through this process, ten CIS services and eight CIS capabilities were identified as being important for enabling scalable, service-oriented CDS. In particular, through a survey of 46 domain experts, five services and capabilities were identified as being especially critical: 1) the use of standard information models and terminologies; 2) the ability to leverage a Decision Support Service (DSS); 3) support for a clinical data query service; 4) support for an event subscription and notification service; and 5) support for a user communication service.

  19. Clinical Information System Services and Capabilities Desired for Scalable, Standards-Based, Service-oriented Decision Support: Consensus Assessment of the Health Level 7 Clinical Decision Support Work Group

    PubMed Central

    Kawamoto, Kensaku; Jacobs, Jason; Welch, Brandon M.; Huser, Vojtech; Paterno, Marilyn D.; Del Fiol, Guilherme; Shields, David; Strasberg, Howard R.; Haug, Peter J.; Liu, Zhijing; Jenders, Robert A.; Rowed, David W.; Chertcoff, Daryl; Fehre, Karsten; Adlassnig, Klaus-Peter; Curtis, A. Clayton

    2012-01-01

    A standards-based, service-oriented architecture for clinical decision support (CDS) has the potential to significantly enhance CDS scalability and robustness. To enable such a CDS architecture, the Health Level 7 CDS Work Group reviewed the literature, hosted multi-stakeholder discussions, and consulted domain experts to identify and prioritize the services and capabilities required from clinical information systems (CISs) to enable service-oriented CDS. In addition, relevant available standards were identified. Through this process, ten CIS services and eight CIS capabilities were identified as being important for enabling scalable, service-oriented CDS. In particular, through a survey of 46 domain experts, five services and capabilities were identified as being especially critical: 1) the use of standard information models and terminologies; 2) the ability to leverage a Decision Support Service (DSS); 3) support for a clinical data query service; 4) support for an event subscription and notification service; and 5) support for a user communication service. PMID:23304315

  20. Clinical decision-making: midwifery students' recognition of, and response to, post partum haemorrhage in the simulation environment

    PubMed Central

    2012-01-01

    Background This paper reports the findings of a study of how midwifery students responded to a simulated post partum haemorrhage (PPH). Internationally, 25% of maternal deaths are attributed to severe haemorrhage. Although this figure is far higher in developing countries, the risk to maternal wellbeing and child health problem means that all midwives need to remain vigilant and respond appropriately to early signs of maternal deterioration. Methods Simulation using a patient actress enabled the research team to investigate the way in which 35 midwifery students made decisions in a dynamic high fidelity PPH scenario. The actress wore a birthing suit that simulated blood loss and a flaccid uterus on palpation. The scenario provided low levels of uncertainty and high levels of relevant information. The student's response to the scenario was videoed. Immediately after, they were invited to review the video, reflect on their performance and give a commentary as to what affected their decisions. The data were analysed using Dimensional Analysis. Results The students' clinical management of the situation varied considerably. Students struggled to prioritise their actions where more than one response was required to a clinical cue and did not necessarily use mnemonics as heuristic devices to guide their actions. Driven by a response to single cues they also showed a reluctance to formulate a diagnosis based on inductive and deductive reasoning cycles. This meant they did not necessarily introduce new hypothetical ideas against which they might refute or confirm a diagnosis and thereby eliminate fixation error. Conclusions The students response demonstrated that a number of clinical skills require updating on a regular basis including: fundal massage technique, the use of emergency standing order drugs, communication and delegation of tasks to others in an emergency and working independently until help arrives. Heuristic devices helped the students to evaluate their

  1. The use of laser Doppler imaging as an aid in clinical management decision making in the treatment of vesicant burns.

    PubMed

    Brown, R F; Rice, P; Bennett, N J

    1998-12-01

    Vesicants are a group of chemicals recognised, under the terms of the Chemical Weapons Convention, as potential chemical warfare agents whose prime effect on the skin is to cause burns and blistering. Experience of the clinical management of these injuries is not readily available and therefore an accurate assessment of the severity of the lesion and extent of tissue involvement is an important factor when determining the subsequent clinical management strategy for such lesions. This study was performed to assess the use of laser Doppler imaging (LDI) as a noninvasive means of assessing wound microvascular perfusion following challenge with the vesicant agents (sulphur mustard or lewisite) by comparing the images obtained with histopathological analysis of the lesion. Large white pigs were challenged with sulphur mustard (1.91 mg cm(-2)) or lewisite (0.3 mg.cm(-2)) vapour for periods of up to 6 h At intervals of between 1 h and 7 days following vesicant challenge, LDI images were acquired and samples for routine histopathology were taken. The results from this study suggest that LDI was: (i) a simple, reproducible and noninvasive means of assessing changes in tissue perfusion, and hence tissue viability, in developing and healing vesicant burns; (ii) the LDI images correlates well with histopathological assessment of the resulting lesions and the technique was sufficiently sensitive enough to discriminate between skin lesions of different aetiology. These attributes suggest that LDI would be a useful investigative tool that could aid clinical management decision making in the early treatment of vesicant agent-induced skin burns.

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

    PubMed

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

    2015-01-01

    Mitigating uncertainty and risks faced by specialist physicians in analysis of rare clinical cases is something desired by anyone who needs health services. The number of clinical cases never seen by these experts, with little documentation, may introduce errors in decision-making. Such errors negatively affect well-being of patients, increase procedure costs, rework, health insurance premiums, and impair the reputation of specialists and medical systems involved. In this context, IT and Clinical Decision Support Systems (CDSS) play a fundamental role, supporting decision-making process, making it more efficient and effective, reducing a number of avoidable medical errors and enhancing quality of treatment given to patients. An investigation has been initiated to look into characteristics and solution requirements of this problem, model it, propose a general solution in terms of a conceptual risk-based, automated framework to support rare-case medical diagnostics and validate it by means of case studies. A preliminary validation study of the proposed framework has been carried out by interviews conducted with experts who are practicing professionals, academics, and researchers in health care. This paper summarizes the investigation and its positive results. These results motivate continuation of research towards development of the conceptual framework and of a software tool that implements the proposed model. PMID:26262173

  3. An ontology-driven, case-based clinical decision support model for removable partial denture design

    PubMed Central

    Chen, Qingxiao; Wu, Ji; Li, Shusen; Lyu, Peijun; Wang, Yong; Li, Miao

    2016-01-01

    We present the initial work toward developing a clinical decision support model for specific design of removable partial dentures (RPDs) in dentistry. We developed an ontological paradigm to represent knowledge of a patient’s oral conditions and denture component parts. During the case-based reasoning process, a cosine similarity algorithm was applied to calculate similarity values between input patients and standard ontology cases. A group of designs from the most similar cases were output as the final results. To evaluate this model, the output designs of RPDs for 104 randomly selected patients were compared with those selected by professionals. An area under the curve of the receiver operating characteristic (AUC-ROC) was created by plotting true-positive rates against the false-positive rate at various threshold settings. The precision at position 5 of the retrieved cases was 0.67 and at the top of the curve it was 0.96, both of which are very high. The mean average of precision (MAP) was 0.61 and the normalized discounted cumulative gain (NDCG) was 0.74 both of which confirmed the efficient performance of our model. All the metrics demonstrated the efficiency of our model. This methodology merits further research development to match clinical applications for designing RPDs. This paper is organized as follows. After the introduction and description of the basis for the paper, the evaluation and results are presented in Section 2. Section 3 provides a discussion of the methodology and results. Section 4 describes the details of the ontology, similarity algorithm, and application. PMID:27297679

  4. An ontology-driven, case-based clinical decision support model for removable partial denture design.

    PubMed

    Chen, Qingxiao; Wu, Ji; Li, Shusen; Lyu, Peijun; Wang, Yong; Li, Miao

    2016-06-14

    We present the initial work toward developing a clinical decision support model for specific design of removable partial dentures (RPDs) in dentistry. We developed an ontological paradigm to represent knowledge of a patient's oral conditions and denture component parts. During the case-based reasoning process, a cosine similarity algorithm was applied to calculate similarity values between input patients and standard ontology cases. A group of designs from the most similar cases were output as the final results. To evaluate this model, the output designs of RPDs for 104 randomly selected patients were compared with those selected by professionals. An area under the curve of the receiver operating characteristic (AUC-ROC) was created by plotting true-positive rates against the false-positive rate at various threshold settings. The precision at position 5 of the retrieved cases was 0.67 and at the top of the curve it was 0.96, both of which are very high. The mean average of precision (MAP) was 0.61 and the normalized discounted cumulative gain (NDCG) was 0.74 both of which confirmed the efficient performance of our model. All the metrics demonstrated the efficiency of our model. This methodology merits further research development to match clinical applications for designing RPDs. This paper is organized as follows. After the introduction and description of the basis for the paper, the evaluation and results are presented in Section 2. Section 3 provides a discussion of the methodology and results. Section 4 describes the details of the ontology, similarity algorithm, and application.

  5. An empirical analysis of the corporate call decision

    NASA Astrophysics Data System (ADS)

    Carlson, Murray Dean

    1998-12-01

    In this thesis we provide insights into the behavior of financial managers of utility companies by studying their decisions to redeem callable preferred shares. In particular, we investigate whether or not an option pricing based model of the call decision, with managers who maximize shareholder value, does a better job of explaining callable preferred share prices and call decisions than do other models of the decision. In order to perform these tests, we extend an empirical technique introduced by Rust (1987) to include the use of information from preferred share prices in addition to the call decisions. The model we develop to value the option embedded in a callable preferred share differs from standard models in two ways. First, as suggested in Kraus (1983), we explicitly account for transaction costs associated with a redemption. Second, we account for state variables that are observed by the decision makers but not by the preferred shareholders. We interpret these unobservable state variables as the benefits and costs associated with a change in capital structure that can accompany a call decision. When we add this variable, our empirical model changes from one which predicts exactly when a share should be called to one which predicts the probability of a call as the function of the observable state. These two modifications of the standard model result in predictions of calls, and therefore of callable preferred share prices, that are consistent with several previously unexplained features of the data; we show that the predictive power of the model is improved in a statistical sense by adding these features to the model. The pricing and call probability functions from our model do a good job of describing call decisions and preferred share prices for several utilities. Using data from shares of the Pacific Gas and Electric Co. (PGE) we obtain reasonable estimates for the transaction costs associated with a call. Using a formal empirical test, we are able to

  6. AALIM: a cardiac clinical decision support system powered by advanced multi-modal analytics.

    PubMed

    Amir, Arnon; Beymer, David; Grace, Julia; Greenspan, Hayit; Gruhl, Daniel; Hobbs, Allen; Pohl, Kilian; Syeda-Mahmood, Tanveer; Terdiman, Joseph; Wang, Fei

    2010-01-01

    Modern Electronic Medical Record (EMR) systems often integrate large amounts of data from multiple disparate sources. To do so, EMR systems must align the data to create consistency between these sources. The data should also be presented in a manner that allows a clinician to quickly understand the complete condition and history of a patient's health. We develop the AALIM system to address these issues using advanced multimodal analytics. First, it extracts and computes multiple features and cues from the patient records and medical tests. This additional metadata facilitates more accurate alignment of the various modalities, enables consistency check and empowers a clear, concise presentation of the patient's complete health information. The system further provides a multimodal search for similar cases within the EMR system, and derives related conditions and drugs information from them. We applied our approach to cardiac data from a major medical care organization and found that it produced results with sufficient quality to assist the clinician making appropriate clinical decisions.

  7. MACVIA clinical decision algorithm in adolescents and adults with allergic rhinitis.

    PubMed

    Bousquet, Jean; Schünemann, Holger J; Hellings, Peter W; Arnavielhe, Sylvie; Bachert, Claus; Bedbrook, Anna; Bergmann, Karl-Christian; Bosnic-Anticevich, Sinthia; Brozek, Jan; Calderon, Moises; Canonica, G Walter; Casale, Thomas B; Chavannes, Niels H; Cox, Linda; Chrystyn, Henry; Cruz, Alvaro A; Dahl, Ronald; De Carlo, Giuseppe; Demoly, Pascal; Devillier, Phillipe; Dray, Gérard; Fletcher, Monica; Fokkens, Wytske J; Fonseca, Joao; Gonzalez-Diaz, Sandra N; Grouse, Lawrence; Keil, Thomas; Kuna, Piotr; Larenas-Linnemann, Désirée; Lodrup Carlsen, Karin C; Meltzer, Eli O; Mullol, Jaoquim; Muraro, Antonella; Naclerio, Robert N; Palkonen, Susanna; Papadopoulos, Nikolaos G; Passalacqua, Giovanni; Price, David; Ryan, Dermot; Samolinski, Boleslaw; Scadding, Glenis K; Sheikh, Aziz; Spertini, François; Valiulis, Arunas; Valovirta, Erkka; Walker, Samantha; Wickman, Magnus; Yorgancioglu, Arzu; Haahtela, Tari; Zuberbier, Torsten

    2016-08-01

    The selection of pharmacotherapy for patients with allergic rhinitis (AR) depends on several factors, including age, prominent symptoms, symptom severity, control of AR, patient preferences, and cost. Allergen exposure and the resulting symptoms vary, and treatment adjustment is required. Clinical decision support systems (CDSSs) might be beneficial for the assessment of disease control. CDSSs should be based on the best evidence and algorithms to aid patients and health care professionals to jointly determine treatment and its step-up or step-down strategy depending on AR control. Contre les MAladies Chroniques pour un VIeillissement Actif en Languedoc-Roussillon (MACVIA-LR [fighting chronic diseases for active and healthy ageing]), one of the reference sites of the European Innovation Partnership on Active and Healthy Ageing, has initiated an allergy sentinel network (the MACVIA-ARIA Sentinel Network). A CDSS is currently being developed to optimize AR control. An algorithm developed by consensus is presented in this article. This algorithm should be confirmed by appropriate trials.

  8. Dose coefficients and derived guidance and clinical decision levels for contaminated wounds

    SciTech Connect

    Bertelli, Luiz; Toohey, Richard E

    2009-01-01

    The NCRP Wound Model describing the retention of selected radionuclides at the site of a contaminated wound and their uptake into the transfer compartment has been combined with the ICRP element-specific systemic models for those radionuclides to derive dose coefficients for intakes via contaminated wounds. Those coefficients have been used to generate derived guidance levels (i.e., the activity in a wound that would result in an effective dose of 20 or 50 mSv, or in some cases, a committed organ equivalent dose of 500 mSv), and clinical decision levels (i.e., activity levels that would indicate the need for consideration of medical intervention to remove activity from the wound site or administration of decorporation therapy or both), typically set at 5 times the derived guidance levels. Data are provided for the radionuclides commonly encountered at nuclear power plants and nuclear weapons, fuel fabrication or recycling, waste disposal, medical and research facilities. These include: {sup 60}Co, {sup 90}Sr, {sup 99m}Tc, {sup 131}I, {sup 137}Cs, {sup 192}Ir, {sup 210}Po, {sup 226,228}Ra, {sup 228,232}Th, {sup 235,238}U, {sup 237}Np, {sup 238,239}Pu, {sup 241}Am, {sup 242,244}Cm, and {sup 252}Cf.

  9. MACVIA clinical decision algorithm in adolescents and adults with allergic rhinitis.

    PubMed

    Bousquet, Jean; Schünemann, Holger J; Hellings, Peter W; Arnavielhe, Sylvie; Bachert, Claus; Bedbrook, Anna; Bergmann, Karl-Christian; Bosnic-Anticevich, Sinthia; Brozek, Jan; Calderon, Moises; Canonica, G Walter; Casale, Thomas B; Chavannes, Niels H; Cox, Linda; Chrystyn, Henry; Cruz, Alvaro A; Dahl, Ronald; De Carlo, Giuseppe; Demoly, Pascal; Devillier, Phillipe; Dray, Gérard; Fletcher, Monica; Fokkens, Wytske J; Fonseca, Joao; Gonzalez-Diaz, Sandra N; Grouse, Lawrence; Keil, Thomas; Kuna, Piotr; Larenas-Linnemann, Désirée; Lodrup Carlsen, Karin C; Meltzer, Eli O; Mullol, Jaoquim; Muraro, Antonella; Naclerio, Robert N; Palkonen, Susanna; Papadopoulos, Nikolaos G; Passalacqua, Giovanni; Price, David; Ryan, Dermot; Samolinski, Boleslaw; Scadding, Glenis K; Sheikh, Aziz; Spertini, François; Valiulis, Arunas; Valovirta, Erkka; Walker, Samantha; Wickman, Magnus; Yorgancioglu, Arzu; Haahtela, Tari; Zuberbier, Torsten

    2016-08-01

    The selection of pharmacotherapy for patients with allergic rhinitis (AR) depends on several factors, including age, prominent symptoms, symptom severity, control of AR, patient preferences, and cost. Allergen exposure and the resulting symptoms vary, and treatment adjustment is required. Clinical decision support systems (CDSSs) might be beneficial for the assessment of disease control. CDSSs should be based on the best evidence and algorithms to aid patients and health care professionals to jointly determine treatment and its step-up or step-down strategy depending on AR control. Contre les MAladies Chroniques pour un VIeillissement Actif en Languedoc-Roussillon (MACVIA-LR [fighting chronic diseases for active and healthy ageing]), one of the reference sites of the European Innovation Partnership on Active and Healthy Ageing, has initiated an allergy sentinel network (the MACVIA-ARIA Sentinel Network). A CDSS is currently being developed to optimize AR control. An algorithm developed by consensus is presented in this article. This algorithm should be confirmed by appropriate trials. PMID:27260321

  10. A Clinical Decision Support System for Femoral Peripheral Arterial Disease Treatment

    PubMed Central

    Yurtkuran, Alkın; Tok, Mustafa

    2013-01-01

    One of the major challenges of providing reliable healthcare services is to diagnose and treat diseases in an accurate and timely manner. Recently, many researchers have successfully used artificial neural networks as a diagnostic assessment tool. In this study, the validation of such an assessment tool has been developed for treatment of the femoral peripheral arterial disease using a radial basis function neural network (RBFNN). A data set for training the RBFNN has been prepared by analyzing records of patients who had been treated by the thoracic and cardiovascular surgery clinic of a university hospital. The data set includes 186 patient records having 16 characteristic features associated with a binary treatment decision, namely, being a medical or a surgical one. K-means clustering algorithm has been used to determine the parameters of radial basis functions and the number of hidden nodes of the RBFNN is determined experimentally. For performance evaluation, the proposed RBFNN was compared to three different multilayer perceptron models having Pareto optimal hidden layer combinations using various performance indicators. Results of comparison indicate that the RBFNN can be used as an effective assessment tool for femoral peripheral arterial disease treatment. PMID:24382983

  11. "Stemness" genomics law governs clinical behavior of human cancer: implications for decision making in disease management.

    PubMed

    Glinsky, Gennadi V

    2008-06-10

    One of the most significant accomplishments of translational oncogenomics is a realistic promise of efficient diagnostic tests that would facilitate implementation of the concept of individualized cancer therapies. Recent discovery of the BMI1 pathway rule indicates that gene expression signatures (GESs) associated with the "stemness" state of a cell might be informative as molecular predictors of cancer therapy outcome. We illustrate a potential clinical utility of this concept using GESs derived from genomic analysis of embryonic stem cells (ESCs) during transition from self-renewing, pluripotent state to differentiated phenotypes. Signatures of multiple stemness pathways (signatures of BMI1, Nanog/Sox2/Oct4, EED, and Suz12 pathways; transposon exclusion zones and ESC pattern 3 signatures; signatures of Polycomb-bound and bivalent chromatin domain transcription factors) seem informative in stratification of cancer patients into low- and high-intensity treatment groups on the basis of prediction of the long-term therapy outcome. A stemness cancer therapy outcome predictor (CTOP) algorithm combining scores of nine stemness signatures outperforms individual signatures and demonstrates a superior prognostic accuracy in retrospective supervised analysis of large cohorts of breast, prostate, lung, and ovarian cancer patients. Our analysis suggests that stemness genomics law governs clinical behavior of human malignancies and defines epigenetic boundaries of therapy-resistant and -sensitive tumors within distinct stemness/differentiation programs. One of the main conclusions of our analysis is that near-term progress in practical implementation of the concept of personalized cancer therapies would depend on timely delivery to practicing physicians of relevant scientific information regarding the outcome of prospective trials validating prognostic performance of CTOP tests in a clinical setting.

  12. Development of a Decision Support System for Analysis and Solutions of Prolonged Standing in the Workplace

    PubMed Central

    Halim, Isa; Arep, Hambali; Kamat, Seri Rahayu; Abdullah, Rohana; Omar, Abdul Rahman; Ismail, Ahmad Rasdan

    2014-01-01

    Background Prolonged standing has been hypothesized as a vital contributor to discomfort and muscle fatigue in the workplace. The objective of this study was to develop a decision support system that could provide systematic analysis and solutions to minimize the discomfort and muscle fatigue associated with prolonged standing. Methods The integration of object-oriented programming and a Model Oriented Simultaneous Engineering System were used to design the architecture of the decision support system. Results Validation of the decision support system was carried out in two manufacturing companies. The validation process showed that the decision support system produced reliable results. Conclusion The decision support system is a reliable advisory tool for providing analysis and solutions to problems related to the discomfort and muscle fatigue associated with prolonged standing. Further testing of the decision support system is suggested before it is used commercially. PMID:25180141

  13. Factors influencing first childbearing timing decisions among men: Path analysis

    PubMed Central

    Kariman, Nourossadat; Amerian, Maliheh; Jannati, Padideh; Salmani, Fatemeh

    2016-01-01

    Background: Factors that influence men’s childbearing intentions have been relatively unexplored in the literature. Objective: This study aimed to determine the influencing factors about the first childbearing timing decisions of men. Materials and Methods: In this cross-sectional study, 300 men who were referred to private and governmental healthcare centers in Shahrood, Iran were randomly recruited from April to September 2014. Data were collected using a demographic questionnaire, the Quality of Life Questionnaire; ENRICH Marital Satisfaction Questionnaire, Synder’s Hope Scale, and the Multidimensional Scale of Perceived Social Support. Results: After removing the statistically insignificant paths, men’s age at marriage had the highest direct effect (β=0.86) on their first childbearing decision. Marital satisfaction (β=-0.09), social support (β=0.06), economic status (β=0.06), and quality of life (β=-0.08) were other effective factors on men’s first childbearing decisions. Moreover, marital satisfaction and social support had significant indirect effects on men’s childbearing decisions (β=-0.04 and -0.01, respectively). Conclusion: Many factors, including personal factors (age at marriage and quality of life), family factors (marital satisfaction), and social factors (social support), can affect men’s decision to have a child. Policymakers are hence required to develop strategies to promote the socioeconomic and family conditions of the couples and to encourage them to have as many children as they desire at an appropriate time. PMID:27738661

  14. Impact of MammaPrint on Clinical Decision-Making in South African Patients with Early-Stage Breast Cancer.

    PubMed

    Pohl, Heinrich; Kotze, Maritha J; Grant, Kathleen A; van der Merwe, Lize; Pienaar, Fredrieka M; Apffelstaedt, Justus P; Myburgh, Ettienne J

    2016-07-01

    The aim of the study was to evaluate the impact of MammaPrint on treatment decision-making in patients with breast cancer. Clinicopathologic information of all breast cancer patients referred for MammaPrint testing in South Africa was collected from 2007 until 2014. A total of 107 patients (109 tumors) with estrogen receptor/progesterone receptor positive and human epidermal growth factor receptor-2 negative tumors were selected with tumors ≥10 mm, or when 1-3 nodes were involved without extra-nodal extension. None of the clinical indicators correlated significantly with the MammaPrint risk classification, which changed the decision for adjuvant chemotherapy in 52% of patients. Of 60 patients who were clinically high risk, 62% had a low-risk MammaPrint result and of the 47 clinically low -risk patients 40% had a high-risk MammaPrint result. This study indicates that MammaPrint could reduce the need for adjuvant chemotherapy by 17% using the selection criteria stipulated. The significant impact on treatment decisions confirmed the clinical utility of MammaPrint independent of standard clinicopathologic risk factors as supported by long-term clinical outcome studies.

  15. Impact of MammaPrint on Clinical Decision-Making in South African Patients with Early-Stage Breast Cancer.

    PubMed

    Pohl, Heinrich; Kotze, Maritha J; Grant, Kathleen A; van der Merwe, Lize; Pienaar, Fredrieka M; Apffelstaedt, Justus P; Myburgh, Ettienne J

    2016-07-01

    The aim of the study was to evaluate the impact of MammaPrint on treatment decision-making in patients with breast cancer. Clinicopathologic information of all breast cancer patients referred for MammaPrint testing in South Africa was collected from 2007 until 2014. A total of 107 patients (109 tumors) with estrogen receptor/progesterone receptor positive and human epidermal growth factor receptor-2 negative tumors were selected with tumors ≥10 mm, or when 1-3 nodes were involved without extra-nodal extension. None of the clinical indicators correlated significantly with the MammaPrint risk classification, which changed the decision for adjuvant chemotherapy in 52% of patients. Of 60 patients who were clinically high risk, 62% had a low-risk MammaPrint result and of the 47 clinically low -risk patients 40% had a high-risk MammaPrint result. This study indicates that MammaPrint could reduce the need for adjuvant chemotherapy by 17% using the selection criteria stipulated. The significant impact on treatment decisions confirmed the clinical utility of MammaPrint independent of standard clinicopathologic risk factors as supported by long-term clinical outcome studies. PMID:27079770

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

    PubMed

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

    2015-08-01

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

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

    PubMed

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

    1997-01-01

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

  18. Modeling the Innovation-Decision Process: Dissemination and Adoption of a Motivational Interviewing Preparatory Procedure In Addiction Outpatient Clinics.

    PubMed

    Walitzer, Kimberly S; Dermen, Kurt H; Barrick, Christopher; Shyhalla, Kathleen

    2015-10-01

    Widespread adoption of empirically-supported treatment innovations has the potential to improve effectiveness of treatment received by individuals with substance use disorders. However, the process of disseminating such innovations has been complex, slow, and difficult. We empirically describe the dissemination and adoption of a treatment innovation--an alcohol-treatment preparatory therapeutic procedure based on motivational interviewing (MI)--in the context of Rogers' (2003) five stages of innovation-decision process (knowledge, persuasion, decision, implementation and confirmation). To this end, 145 randomly-chosen outpatient addiction treatment clinics in New York State received an onsite visit from a project trainer delivering one of three randomly-assigned dissemination intensities: a 15-minute, a half-day or a full-day presentation. Across these clinics, 141 primary administrators and 837 clinicians completed questionnaires assessing aspects of five innovation-decision stages. At each clinic, questionnaire administration occurred immediately pre- and post-dissemination, as well as 1 and 6 months after dissemination. Consistent with Rogers' theory, earlier stages of the innovation-decision process predicted later stages. As hypothesized, dissemination intensity predicted clinicians' post-dissemination knowledge. Clinician baseline characteristics (including gender, pre-dissemination knowledge regarding the MI preparatory technique, education, case load, beliefs regarding the nature of alcohol problems, and beliefs and behavior with regard to therapeutic style) predicted knowledge and persuasion stage variables. One baseline clinic characteristic (i.e., clinic mean beliefs and behavior regarding an MI-consistent therapeutic style) predicted implementation stage variables. Findings suggest that dissemination strategies should accommodate clinician and clinic characteristics. PMID:25934460

  19. Modeling the Innovation-Decision Process: Dissemination and Adoption of a Motivational Interviewing Preparatory Procedure In Addiction Outpatient Clinics.

    PubMed

    Walitzer, Kimberly S; Dermen, Kurt H; Barrick, Christopher; Shyhalla, Kathleen

    2015-10-01

    Widespread adoption of empirically-supported treatment innovations has the potential to improve effectiveness of treatment received by individuals with substance use disorders. However, the process of disseminating such innovations has been complex, slow, and difficult. We empirically describe the dissemination and adoption of a treatment innovation--an alcohol-treatment preparatory therapeutic procedure based on motivational interviewing (MI)--in the context of Rogers' (2003) five stages of innovation-decision process (knowledge, persuasion, decision, implementation and confirmation). To this end, 145 randomly-chosen outpatient addiction treatment clinics in New York State received an onsite visit from a project trainer delivering one of three randomly-assigned dissemination intensities: a 15-minute, a half-day or a full-day presentation. Across these clinics, 141 primary administrators and 837 clinicians completed questionnaires assessing aspects of five innovation-decision stages. At each clinic, questionnaire administration occurred immediately pre- and post-dissemination, as well as 1 and 6 months after dissemination. Consistent with Rogers' theory, earlier stages of the innovation-decision process predicted later stages. As hypothesized, dissemination intensity predicted clinicians' post-dissemination knowledge. Clinician baseline characteristics (including gender, pre-dissemination knowledge regarding the MI preparatory technique, education, case load, beliefs regarding the nature of alcohol problems, and beliefs and behavior with regard to therapeutic style) predicted knowledge and persuasion stage variables. One baseline clinic characteristic (i.e., clinic mean beliefs and behavior regarding an MI-consistent therapeutic style) predicted implementation stage variables. Findings suggest that dissemination strategies should accommodate clinician and clinic characteristics.

  20. Modeling the Innovation-Decision Process: Dissemination and Adoption of a Motivational Interviewing Preparatory Procedure in Addiction Outpatient Clinics

    PubMed Central

    Walitzer, Kimberly S.; Dermen, Kurt H.; Barrick, Christopher; Shyhalla, Kathleen

    2015-01-01

    Widespread adoption of empirically-supported treatment innovations has the potential to improve effectiveness of treatment received by individuals with substance use disorders. However, the process of disseminating such innovations has been complex, slow, and difficult. We empirically describe the dissemination and adoption of a treatment innovation – an alcohol-treatment preparatory therapeutic procedure based on motivational interviewing (MI) – in the context of Rogers’ (2003) five stages of innovation-decision process (knowledge, persuasion, decision, implementation and confirmation). To this end, 145 randomly-chosen outpatient addiction treatment clinics in New York State received an onsite visit from a project trainer delivering one of three randomly-assigned dissemination intensities: a 15-minute, a half-day or a full-day presentation. Across these clinics, 141 primary administrators and 837 clinicians completed questionnaires assessing aspects of five innovation-decision stages. At each clinic, questionnaire administration occurred immediately pre- and post-dissemination, as well as one and six months after dissemination. Consistent with Rogers’ theory, earlier stages of the innovation-decision process predicted later stages. As hypothesized, dissemination intensity predicted clinicians’ post-dissemination knowledge. Clinician baseline characteristics (including gender, pre-dissemination knowledge regarding the MI preparatory technique, education, case load, beliefs regarding the nature of alcohol problems, and beliefs and behavior with regard to therapeutic style) predicted knowledge and persuasion stage variables. One baseline clinic characteristic (i.e., clinic mean beliefs and behavior regarding an MI-consistent therapeutic style) predicted implementation stage variables. Findings suggest that dissemination strategies should accommodate clinician and clinic characteristics. PMID:25934460

  1. Enabling cross-platform clinical decision support through Web-based decision support in commercial electronic health record systems: proposal and evaluation of initial prototype implementations.

    PubMed

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

    2013-01-01

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

  2. Enabling cross-platform clinical decision support through Web-based decision support in commercial electronic health record systems: proposal and evaluation of initial prototype implementations.

    PubMed

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

    2013-01-01

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

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

    PubMed Central

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

    2007-01-01

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

  4. Which test is best for Helicobacter pylori? A cost-effectiveness model using decision analysis.

    PubMed

    Elwyn, Glyn; Taubert, Mark; Davies, Shan; Brown, Ginevra; Allison, Miles; Phillips, Ceri

    2007-05-01

    GPs face a potential dilemma in deciding which test to use for detection of Helicobacter pylori. For patients with dyspepsia, the National Institute for Health and Clinical Excellence (NICE) advises primary care practitioners to adopt a 'test and treat' policy before considering a referral for gastroscopy. There are many ways of testing: serology, urea breath test, and faecal antigen test. NICE does not advocate any preferred single test for detecting H. pylori. In the current study a multi-stakeholder 2-day workshop was established to agree and populate a cost-effectiveness decision analysis model. The aim was to analyse the three types of tests available for H. pylori and to determine which is the most practical and cost effective. Agreement on the costs and diagnostic values to be entered into the decision-analytic model was achieved. Results indicate that the faecal antigen test was the most effective in terms of true outcomes and cost. One thousand virtual patients were allocated to each of the three tests. Serology had 903, urea breath test had 961, and the faecal antigen test had 968 true positive outcomes. Data indicate that the faecal antigen test is the preferable strategy for diagnosis of H. pylori in primary care. This has implications for implementing new testing processes and for commissioning new diagnostic pathways for use in primary care.

  5. Radiological emergency response for community agencies with cognitive task analysis, risk analysis, and decision support framework.

    PubMed

    Meyer, Travis S; Muething, Joseph Z; Lima, Gustavo Amoras Souza; Torres, Breno Raemy Rangel; del Rosario, Trystyn Keia; Gomes, José Orlando; Lambert, James H

    2012-01-01

    Radiological nuclear emergency responders must be able to coordinate evacuation and relief efforts following the release of radioactive material into populated areas. In order to respond quickly and effectively to a nuclear emergency, high-level coordination is needed between a number of large, independent organizations, including police, military, hazmat, and transportation authorities. Given the complexity, scale, time-pressure, and potential negative consequences inherent in radiological emergency responses, tracking and communicating information that will assist decision makers during a crisis is crucial. The emergency response team at the Angra dos Reis nuclear power facility, located outside of Rio de Janeiro, Brazil, presently conducts emergency response simulations once every two years to prepare organizational leaders for real-life emergency situations. However, current exercises are conducted without the aid of electronic or software tools, resulting in possible cognitive overload and delays in decision-making. This paper describes the development of a decision support system employing systems methodologies, including cognitive task analysis and human-machine interface design. The decision support system can aid the coordination team by automating cognitive functions and improving information sharing. A prototype of the design will be evaluated by plant officials in Brazil and incorporated to a future trial run of a response simulation.

  6. Radiological emergency response for community agencies with cognitive task analysis, risk analysis, and decision support framework.

    PubMed

    Meyer, Travis S; Muething, Joseph Z; Lima, Gustavo Amoras Souza; Torres, Breno Raemy Rangel; del Rosario, Trystyn Keia; Gomes, José Orlando; Lambert, James H

    2012-01-01

    Radiological nuclear emergency responders must be able to coordinate evacuation and relief efforts following the release of radioactive material into populated areas. In order to respond quickly and effectively to a nuclear emergency, high-level coordination is needed between a number of large, independent organizations, including police, military, hazmat, and transportation authorities. Given the complexity, scale, time-pressure, and potential negative consequences inherent in radiological emergency responses, tracking and communicating information that will assist decision makers during a crisis is crucial. The emergency response team at the Angra dos Reis nuclear power facility, located outside of Rio de Janeiro, Brazil, presently conducts emergency response simulations once every two years to prepare organizational leaders for real-life emergency situations. However, current exercises are conducted without the aid of electronic or software tools, resulting in possible cognitive overload and delays in decision-making. This paper describes the development of a decision support system employing systems methodologies, including cognitive task analysis and human-machine interface design. The decision support system can aid the coordination team by automating cognitive functions and improving information sharing. A prototype of the design will be evaluated by plant officials in Brazil and incorporated to a future trial run of a response simulation. PMID:22317163

  7. Quantitative Medical Image Analysis for Clinical Development of Therapeutics

    NASA Astrophysics Data System (ADS)

    Analoui, Mostafa

    There has been significant progress in development of therapeutics for prevention and management of several disease areas in recent years, leading to increased average life expectancy, as well as of quality of life, globally. However, due to complexity of addressing a number of medical needs and financial burden of development of new class of therapeutics,