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Sample records for clinical decision analysis

  1. Economic aspects of clinical decision making: applications of clinical decision analysis.

    PubMed

    Crane, V S

    1988-03-01

    Clinical decision analysis as a basic tool for decision making is described, and potential applications of decision analysis in six areas of clinical practice are identified. Clinical decision analysis is a systematic method of describing clinical problems in a quantitative fashion, identifying possible courses of action, assessing the probability and value of outcomes, and then making a calculation to select the ultimate course of action. Clinical decision analysis provides a structure for clinical decision problems, helps clarify medical controversies, and encourages decision makers to speak a common language. Applications of clinical decision analysis in the areas of diagnostic testing, patient management, product and program selection, research and education, patient preferences, and health-care-policy evaluation are described. Decision analysis offers health professionals a tool for making quantifiable, cost-effective clinical decisions, especially in terms of clinical outcomes. PMID:3285672

  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. Clinical Decision Analysis and Markov Modeling for Surgeons: An Introductory Overview.

    PubMed

    Hogendoorn, Wouter; Moll, Frans L; Sumpio, Bauer E; Hunink, M G Myriam

    2016-08-01

    This study addresses the use of decision analysis and Markov models to make contemplated decisions for surgical problems. Decision analysis and decision modeling in surgical research are increasing, but many surgeons are unfamiliar with the techniques and are skeptical of the results. The goal of this review is to familiarize surgeons with techniques and terminology used in decision analytic papers, to provide the reader a practical guide to read these papers, and to ensure that surgeons can critically appraise the quality of published clinical decision models and draw well founded conclusions from such reports.First, a brief explanation of decision analysis and Markov models is presented in simple steps, followed by an overview of the components of a decision and Markov model. Subsequently, commonly used terms and definitions are described and explained, including quality-adjusted life-years, disability-adjusted life-years, discounting, half-cycle correction, cycle length, probabilistic sensitivity analysis, incremental cost-effectiveness ratio, and the willingness-to-pay threshold.Finally, the advantages and limitations of research with Markov models are described, and new modeling techniques and future perspectives are discussed. It is important that surgeons are able to understand conclusions from decision analytic studies and are familiar with the specific definitions of the terminology used in the field to keep up with surgical research. Decision analysis can guide treatment strategies when complex clinical questions need to be answered and is a necessary and useful addition to the surgical research armamentarium. PMID:26756750

  4. 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).

  5. A decision-analysis methodology for consideration of morbidity factors in clinical decision-making.

    PubMed

    Corder, M P; Ellwein, L B

    1984-02-01

    An explicit and systematic means of incorporation of good medical practice plus individual patient preferences (utilities) for pretreatment and treatment options for a serious but curable neoplastic disease has been investigated. The methodology allows important quality-of-life information to be transmitted to patients, with the goal of providing an improved basis for informed consent. The example of Hodgkin's lymphoma staging and treatment selection is used. Individual patient utilities can be expressed and incorporated into a formal decision analysis for those who face the option of selecting MOPP chemotherapy or of pursuing the staging process in order to obtain a chance of being treated appropriately with irradiation. Equal survival probabilities for the two options are assumed, thus the short- and long-term toxicities (quality of Life) are the determinants of the decision. Patient-derived utilities can be developed for the 15 categories of anticipated toxicity. This, together with probabilistic inputs regarding toxicity severity and duration, will yield expected utilities for each of the decision options. Three physicians were studied and evaluated in the role of a patient. The physicians' toxicity preferences were different and because of this the management option of choice was different for each. This methodology allows explicit patient preferences to be incorporated into medical decisions without the requirement for detailed patient understanding of testing and/or treatment morbidity frequency and severity. PMID:6546469

  6. 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

  7. Visual cluster analysis in support of clinical decision intelligence.

    PubMed

    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

  8. 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

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

    PubMed

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

    2003-07-01

    Because of increasing demand for publicly funded elective cosmetic surgery, clinical decision guidelines have been developed to select those patients who should receive it. The aims of this study were to identify: the main characteristics of such guidelines; whether and how they influence clinical decision making; and ways in which they should be improved. UK health authorities were asked for their current guidelines for elective cosmetic surgery and, in a single plastic surgery unit, we examined the impact of its guidelines by observing consultations and interviewing surgeons and managers. Of 115 authorities approached, 32 reported using guidelines and provided sufficient information for analysis. Guidelines mostly concerned arbitrary sets of cosmetic procedures and lacked reference to an evidence base. They allowed surgery for specified anatomical, functional or symptomatic reasons, but these indications varied between guidelines. Most guidelines also permitted surgery 'exceptionally' for psychological reasons. The guidelines that were studied in detail did not appreciably influence surgeons' decisions, which reflected criteria that were not cited in the guidelines, including cost of the procedure and whether patients sought restoration or improvement of their appearance. Decision guidelines in this area have several limitations. Future guidelines should: include all cosmetic procedures; be informed by a broad range of evidence; and, arguably, include several nonclinical criteria that currently inform surgeons' decision-making. PMID:12890455

  10. Legal Considerations in Clinical Decision Making.

    ERIC Educational Resources Information Center

    Ursu, Samuel C.

    1992-01-01

    Discussion of legal issues in dental clinical decision making looks at the nature and elements of applicable law, especially malpractice, locus of responsibility, and standards of care. Greater use of formal decision analysis in clinical dentistry and better research on diagnosis and treatment are recommended, particularly in light of increasing…

  11. How clinical decisions are made

    PubMed Central

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

    2012-01-01

    There is much variation in the implementation of the best available evidence into clinical practice. These gaps between evidence and practice are often a result of multiple individual decisions. When making a decision, there is so much potentially relevant information available, it is impossible to know or process it all (so called ‘bounded rationality’). Usually, a limited amount of information is selected to reach a sufficiently satisfactory decision, a process known as satisficing. There are two key processes used in decision making: System 1 and System 2. System 1 involves fast, intuitive decisions; System 2 is a deliberate analytical approach, used to locate information which is not instantly recalled. Human beings unconsciously use System 1 processing whenever possible because it is quicker and requires less effort than System 2. In clinical practice, gaps between evidence and practice can occur when a clinician develops a pattern of knowledge, which is then relied on for decisions using System 1 processing, without the activation of a System 2 check against the best available evidence from high quality research. The processing of information and decision making may be influenced by a number of cognitive biases, of which the decision maker may be unaware. Interventions to encourage appropriate use of System 1 and System 2 processing have been shown to improve clinical decision making. Increased understanding of decision making processes and common sources of error should help clinical decision makers to minimize avoidable mistakes and increase the proportion of decisions that are better. PMID:22738381

  12. 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…

  13. Development of a formal structure for clinical management decisions: a mathematical analysis.

    PubMed

    Card, W I

    1975-01-01

    Decision theory and the calculating power of the computer now enables us to contemplate the development of formal methods for making decisions about clinical management. In the simplest model, it is first necessary to define all treatment decisions as an exhaustive and mutually exclusive set and similarly to define the set of consequences or outcomes of treatment. The probability of each outcome conditional on treatment has to be estimated and this consequent state of health has to be quantified as a utility. Possible methods of estimating utilities of states of health are discussed and the construction of a unidimensional utility function based on a sequence of wagers. The states of health consequent on severe brain damage can only be described multidimensionally and the model has to be extended to include this case. While such a model would allow simple treatment decisions to be formalized, it could not decide whether the cost of treatment was worth while nor whether it would pay to carry out further investigative tests and thus buy more evidence. If these additional variables are to be included in the model, it is necessary to introduce the motion of an equivalence between monetary values and utilities. This implies attaching a monetary value to any given state of health. PMID:1045996

  14. 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

  15. 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

  16. 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

  17. 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

  18. 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

  19. Clinical elements that predict outcome after traumatic brain injury: a prospective multicenter recursive partitioning (decision-tree) analysis.

    PubMed

    Brown, Allen W; Malec, James F; McClelland, Robyn L; Diehl, Nancy N; Englander, Jeffrey; Cifu, David X

    2005-10-01

    Traumatic brain injury (TBI) often presents clinicians with a complex combination of clinical elements that can confound treatment and make outcome prediction challenging. Predictive models have commonly used acute physiological variables and gross clinical measures to predict mortality and basic outcome endpoints. The primary goal of this study was to consider all clinical elements available concerning a survivor of TBI admitted for inpatient rehabilitation, and identify those factors that predict disability, need for supervision, and productive activity one year after injury. The Traumatic Brain Injury Model Systems (TBIMS) database was used for decision tree analysis using recursive partitioning (n = 3463). Outcome measures included the Functional Independence Measure(), the Disability Rating Scale, the Supervision Rating Scale, and a measure of productive activity. Predictor variables included all physical examination elements, measures of injury severity (initial Glasgow Coma Scale score, duration of post-traumatic amnesia [PTA], length of coma, CT scan pathology), gender, age, and years of education. The duration of PTA, age, and most elements of the physical examination were predictive of early disability. The duration of PTA alone was selected to predict late disability and independent living. The duration of PTA, age, sitting balance, and limb strength were selected to predict productive activity at 1 year. The duration of PTA was the best predictor of outcome selected in this model for all endpoints and elements of the physical examination provided additional predictive value. Valid and reliable measures of PTA and physical impairment after TBI are important for accurate outcome prediction. PMID:16238482

  20. 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

  1. 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

  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. PMID:25927513

  3. 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)

  4. Stochastic decision analysis

    NASA Technical Reports Server (NTRS)

    Lacksonen, Thomas A.

    1994-01-01

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

  5. 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…

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

    PubMed

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

    2013-10-01

    Integration of clinical decision support services (CDSS) into electronic health records (EHRs) may be integral to widespread dissemination and use of clinical prediction rules in the emergency department (ED). However, the best way to design such services to maximize their usefulness in such a complex setting is poorly understood. We conducted a multi-site cross-sectional qualitative study whose aim was to describe the sociotechnical environment in the ED to inform the design of a CDSS intervention to implement the Pediatric Emergency Care Applied Research Network (PECARN) clinical prediction rules for children with minor blunt head trauma. Informed by a sociotechnical model consisting of eight dimensions, we conducted focus groups, individual interviews and workflow observations in 11 EDs, of which 5 were located in academic medical centers and 6 were in community hospitals. A total of 126 ED clinicians, information technology specialists, and administrators participated. We clustered data into 19 categories of sociotechnical factors through a process of thematic analysis and subsequently organized the categories into a sociotechnical matrix consisting of three high-level sociotechnical dimensions (workflow and communication, organizational factors, human factors) and three themes (interdisciplinary assessment processes, clinical practices related to prediction rules, EHR as a decision support tool). Design challenges that emerged from the analysis included the need to use structured data fields to support data capture and re-use while maintaining efficient care processes, supporting interdisciplinary communication, and facilitating family-clinician interaction for decision-making. PMID:23892207

  7. 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

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

    PubMed Central

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

    2008-01-01

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

  9. Grand challenges in clinical decision support.

    PubMed

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

    2008-04-01

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

  10. 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.

  11. 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

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

    PubMed

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

    2016-02-01

    The primary aim of this performance improvement project was to determine whether the electronic health record implementation of stroke-specific nursing documentation flowsheet templates and clinical decision support alerts improved the nursing documentation of eligible stroke patients in seven stroke-certified emergency departments. Two system enhancements were introduced into the electronic record in an effort to improve nursing documentation: disease-specific documentation flowsheets and clinical decision support alerts. Using a pre-post design, project measures included six stroke management goals as defined by the National Institute of Neurological Disorders and Stroke and three clinical decision support measures based on entry of orders used to trigger documentation reminders for nursing: (1) the National Institutes of Health's Stroke Scale, (2) neurological checks, and (3) dysphagia screening. Data were reviewed 6 months prior (n = 2293) and 6 months following the intervention (n = 2588). Fisher exact test was used for statistical analysis. Statistical significance was found for documentation of five of the six stroke management goals, although effect sizes were small. Customizing flowsheets to meet the needs of nursing workflow showed improvement in the completion of documentation. The effects of the decision support alerts on the completeness of nursing documentation were not statistically significant (likely due to lack of order entry). For example, an order for the National Institutes of Health Stroke Scale was entered only 10.7% of the time, which meant no alert would fire for nursing in the postintervention group. Future work should focus on decision support alerts that trigger reminders for clinicians to place relevant orders for this population. PMID:26679006

  13. 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

  14. 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.

  15. 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…

  16. 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. PMID:19606659

  17. Modelling and Decision Support of Clinical Pathways

    NASA Astrophysics Data System (ADS)

    Gabriel, Roland; Lux, Thomas

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

  18. 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

  19. 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. PMID:25571435

  20. Clinical Decision Support Systems for Ambulatory Care

    PubMed Central

    Lloyd, Stephen C.

    1984-01-01

    This conference serves to further the state of the art in the application of computers to medical care via a forum for the intercommunication of ideas. Papers discuss the experiences of diverse research projects. It is the purpose of this article to review the major developments in ambulatory care decision support. From this vantage point, the major impediments to broad applicability of information systems are discussed. The DUCHESS Medical Information Management System is then described as a step towards overcoming these obstacles. Two distinct but often overlapping issues are the representation of the data and its subsequent manipulation: records vs. knowledge. The complexity of the medical record requires state-of-the-art computer science. Clinical decision support requires flexible means for representing medical knowledge and the ability to input “rules.” Artificial intelligence has provided tools for simulating the decision making processes. A sample of the major systems are contrasted and compared. In the realm of medical records COSTAR, TMR, SCAMP, HELP, and STOR are considered. In clinical decision support CADEUCUS, REGENSTRIEF, PKC, and DUCHESS are reviewed.

  1. 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

  2. Improving clinical decision support using data mining techniques

    NASA Astrophysics Data System (ADS)

    Burn-Thornton, Kath E.; Thorpe, Simon I.

    1999-02-01

    Physicians, in their ever-demanding jobs, are looking to decision support systems for aid in clinical diagnosis. However, clinical decision support systems need to be of sufficiently high accuracy that they help, rather than hinder, the physician in his/her diagnosis. Decision support systems with accuracies, of patient state determination, of greater than 80 percent, are generally perceived to be sufficiently accurate to fulfill the role of helping the physician. We have previously shown that data mining techniques have the potential to provide the underpinning technology for clinical decision support systems. In this paper, an extension of the work in reverence 2, we describe how changes in data mining methodologies, for the analysis of 12-lead ECG data, improve the accuracy by which data mining algorithms determine which patients are suffering from heart disease. We show that the accuracy of patient state prediction, for all the algorithms, which we investigated, can be increased by up to 6 percent, using the combination of appropriate test training ratios and 5-fold cross-validation. The use of cross-validation greater than 5-fold, appears to reduce the improvement in algorithm classification accuracy gained by the use of this validation method. The accuracy of 84 percent in patient state predictions, obtained using the algorithm OCI, suggests that this algorithm will be capable of providing the required accuracy for clinical decision support systems.

  3. [Clinical decisions in a philosophical perspective].

    PubMed

    Wulff, H R

    1993-09-20

    Medicine is both a scientific and a humanistic discipline. The foundation for clinical decisions has four components (two scientific and two humanistic). 1) The biological component (reasoning based on biological theory). Biological thinking is currently being revolutionised, partly through the development of systems theory. 2) The empirical component (reasoning based on experience from earlier patients), which comprises both uncontrolled and controlled experience. 3) The empathic-hermeneutic component (reasoning based on an understanding of the patient as a fellow human being). Empathy requires hermeneutic knowledge which can be acquired through personal experience and by qualitative research. 4) The ethical component which comprises both utilitarian and deontological considerations. PMID:8211903

  4. 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).

  5. Driving and dementia: a clinical decision pathway

    PubMed Central

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

    2015-01-01

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

  6. The relationship between patient data and pooled clinical management decisions.

    PubMed

    Ludbrook, G I; O'Loughlin, E J; Corcoran, T B; Grant, C

    2013-01-01

    A strong relationship between patient data and preoperative clinical decisions could potentially be used to support clinical decisions in preoperative management. The aim of this exploratory study was to determine the relationship between key patient data and pooled clinical opinions on management. In a previous study, panels of anaesthetists compared the quality of computer-assisted patient health assessments with outpatient consultations and made decisions on the need for preoperative tests, no preoperative outpatient assessment, possible postoperative intensive care unit/high dependency unit requirements and aspiration prophylaxis. In the current study, the relationship between patient data and these decisions was examined using binomial logistic regression analysis. Backward stepwise regression was used to identify independent predictors of each decision (at P >0.15), which were then incorporated into a predictive model. The number of factors related to each decision varied: blood picture (four factors), biochemistry (six factors), coagulation studies (three factors), electrocardiography (eight factors), chest X-ray (seven factors), preoperative outpatient assessment (17 factors), intensive care unit requirement (eight factors) and aspiration prophylaxis (one factor). The factor types also varied, but included surgical complexity, age, gender, number of medications or comorbidities, body mass index, hypertension, central nervous system condition, heart disease, sleep apnoea, smoking, persistent pain and stroke. Models based on these relationships usually demonstrated good sensitivity and specificity, with receiver operating characteristics in the following areas under curve: blood picture (0.75), biochemistry (0.86), coagulation studies (0.71), electrocardiography (0.90), chest X-ray (0.85), outpatient assessment (0.85), postoperative intensive care unit requirement (0.88) and aspiration prophylaxis (0.85). These initial results suggest modelling of patient

  7. 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

  8. 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.

  9. 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…

  10. 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

  11. Outpatient diabetes clinical decision support: current status and future directions.

    PubMed

    O'Connor, P J; Sperl-Hillen, J M; Fazio, C J; Averbeck, B M; Rank, B H; Margolis, K L

    2016-06-01

    Outpatient clinical decision support systems have had an inconsistent impact on key aspects of diabetes care. A principal barrier to success has been low use rates in many settings. Here, we identify key aspects of clinical decision support system design, content and implementation that are related to sustained high use rates and positive impacts on glucose, blood pressure and lipid management. Current diabetes clinical decision support systems may be improved by prioritizing care recommendations, improving communication of treatment-relevant information to patients, using such systems for care coordination and case management and integrating patient-reported information and data from remote devices into clinical decision algorithms and interfaces. PMID:27194173

  12. Supporting patients in shared decision making in clinical practice.

    PubMed

    Madsen, Claire; Fraser, Aileen

    2015-04-01

    This article defines shared decision making in patient care and describes the background to this philosophy. The shared decision making approach is part of a wider initiative to promote patient-centred care and increase patient involvement in clinical decisions. Shared decision making recognises patients' rights to make decisions about their care and is used to assist them to make informed and individualised decisions about care and treatment. As well as reviewing the principles of shared decision making, the article offers practical guidance on how nurses can implement this initiative, including information on sharing expertise, agenda setting, assessing risks and benefits, setting goals, and support and follow up. PMID:25828022

  13. Phenotyping, endotyping and clinical decision-making.

    PubMed

    Fokkens, W J

    2016-06-01

    We have exiting times in the treatment of chronic rhinosinusitis (CRS). The last year has brought us a number of new ideas and publications to help in decision-making in daily practice. In the first issue of this year, Claire Hopkins and co-authors identified the most important outcomes for patients, public and practitioners that should be evaluated in studies on health interventions for CRS. In this issue of the journal, a group of experts tried to define appropriateness criteria for endoscopic sinus surgery during management of uncomplicated adult chronic rhinosinusitis. Appropriate indications for endoscopic sinus surgery (ESS) are currently poorly defined and the lack of clear surgical indications for ESS likely contributes to the large geographic variation in surgical rates. Using the Delphi method a total of 624 clinical scenarios (half CRSsNP and half CRSwNP) were ranked. The study clearly states that this group of experts indicates that ESS can only be indicated after medical treatment has failed with patients still having significant symptoms (SNOT-22 over 20) and at least some abnormalities at CT scan. PMID:27236249

  14. Web-based health services and clinical decision support.

    PubMed

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

    2004-01-01

    The purpose of this study was the development of a Web-based e-health service for comprehensive assistance and clinical decision support. The service structure consists of a Web server, a PHP-based Web interface linked to a clinical SQL database, Java applets for interactive manipulation and visualization of signals and a Matlab server linked with signal and data processing algorithms implemented by Matlab programs. The service ensures diagnostic signal- and image analysis-sbased clinical decision support. By using the discussed methodology, a pilot service for pathology specialists for automatic calculation of the proliferation index has been developed. Physicians use a simple Web interface for uploading the pictures under investigation to the server; subsequently a Java applet interface is used for outlining the region of interest and, after processing on the server, the requested proliferation index value is calculated. There is also an "expert corner", where experts can submit their index estimates and comments on particular images, which is especially important for system developers. These expert evaluations are used for optimization and verification of automatic analysis algorithms. Decision support trials have been conducted for ECG and ophthalmology ultrasonic investigations of intraocular tumor differentiation. Data mining algorithms have been applied and decision support trees constructed. These services are under implementation by a Web-based system too. The study has shown that the Web-based structure ensures more effective, flexible and accessible services compared with standalone programs and is very convenient for biomedical engineers and physicians, especially in the development phase. PMID:15718591

  15. 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. PMID:23603536

  16. Identifying the Basis for Clinical Decisions - A Feasibility Study.

    PubMed

    Hurlen, Petter; Ofstad, Eirik; Gulbrandsen, Pål

    2016-01-01

    This study explored the possibility of defining a set of terms to describe and identify the basis for clinical decisions in a set of transcriptions from clinical encounters with previously identified decisions. The paper presents the considerations behind the exploratory study and considerations for further work. PMID:27577435

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

    PubMed Central

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

    2016-01-01

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

  18. 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

  19. 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

  20. 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…

  1. Decision analysis with approximate probabilities

    NASA Technical Reports Server (NTRS)

    Whalen, Thomas

    1992-01-01

    This paper concerns decisions under uncertainty in which the probabilities of the states of nature are only approximately known. Decision problems involving three states of nature are studied. This is due to the fact that some key issues do not arise in two-state problems, while probability spaces with more than three states of nature are essentially impossible to graph. The primary focus is on two levels of probabilistic information. In one level, the three probabilities are separately rounded to the nearest tenth. This can lead to sets of rounded probabilities which add up to 0.9, 1.0, or 1.1. In the other level, probabilities are rounded to the nearest tenth in such a way that the rounded probabilities are forced to sum to 1.0. For comparison, six additional levels of probabilistic information, previously analyzed, were also included in the present analysis. A simulation experiment compared four criteria for decisionmaking using linearly constrained probabilities (Maximin, Midpoint, Standard Laplace, and Extended Laplace) under the eight different levels of information about probability. The Extended Laplace criterion, which uses a second order maximum entropy principle, performed best overall.

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

    ERIC Educational Resources Information Center

    Grembowski, David; And Others

    1989-01-01

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

  3. NASA program decisions using reliability analysis.

    NASA Technical Reports Server (NTRS)

    Steinberg, A.

    1972-01-01

    NASA made use of the analytical outputs of reliability people to make management decisions on the Apollo program. Such decisions affected the amount of the incentive fees, how much acceptance testing was necessary, how to optimize development testing, whether to approve engineering changes, and certification of flight readiness. Examples of such analysis are discussed and related to programmatic decisions.-

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

    PubMed Central

    Wright, Adam; Sittig, Dean F.

    2008-01-01

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

  5. 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

  6. 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

  7. 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…

  8. 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…

  9. Details of a Successful Clinical Decision Support System

    PubMed Central

    Friedlin, Jeff; Dexter, Paul R.; Overhage, J. Marc

    2007-01-01

    Computerized physician order entry (CPOE) with clinical decision support (CDS) is regarded as one of the most effective ways to improve the quality of health care and increase patient safety. As electronic medical records become more available, such systems will increasingly become the method of choice to achieve these goals. Creating a CPOE/CDS system is a complex task, and some fail despite time consuming and expensive development. The CPOE system at the Regenstrief Institute incorporates sophisticated CDS and is one of the oldest and most successful in the U.S. Many years in development, it is currently used by hundreds of providers. Our well established, successful system can serve as a template or model for the future development of similar systems. We recently completed a full analysis of our CPOE/CDS system and present details of its structure, functionality and contents. PMID:18693837

  10. Clinical implementation of RNA signatures for pharmacogenomic decision-making

    PubMed Central

    Tang, Weihua; Hu, Zhiyuan; Muallem, Hind; Gulley, Margaret L

    2011-01-01

    RNA profiling is increasingly used to predict drug response, dose, or toxicity based on analysis of drug pharmacokinetic or pharmacodynamic pathways. Before implementing multiplexed RNA arrays in clinical practice, validation studies are carried out to demonstrate sufficient evidence of analytic and clinical performance, and to establish an assay protocol with quality assurance measures. Pathologists assure quality by selecting input tissue and by interpreting results in the context of the input tissue as well as the technologies that were used and the clinical setting in which the test was ordered. A strength of RNA profiling is the array-based measurement of tens to thousands of RNAs at once, including redundant tests for critical analytes or pathways to promote confidence in test results. Instrument and reagent manufacturers are crucial for supplying reliable components of the test system. Strategies for quality assurance include careful attention to RNA preservation and quality checks at pertinent steps in the assay protocol, beginning with specimen collection and proceeding through the various phases of transport, processing, storage, analysis, interpretation, and reporting. Specimen quality is checked by probing housekeeping transcripts, while spiked and exogenous controls serve as a check on analytic performance of the test system. Software is required to manipulate abundant array data and present it for interpretation by a laboratory physician who reports results in a manner facilitating therapeutic decision-making. Maintenance of the assay requires periodic documentation of personnel competency and laboratory proficiency. These strategies are shepherding genomic arrays into clinical settings to provide added value to patients and to the larger health care system. PMID:23226056

  11. 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

  12. A Cost-effectiveness Analysis Comparing a Clinical Decision Rule Versus Usual Care to Risk Stratify Children for Intraabdominal Injury After Blunt Torso Trauma

    PubMed Central

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

    2014-01-01

    Objectives Recently a clinical decision rule (CDR) to identify children at very low risk for intraabdominal injury needing acute intervention (IAI) following blunt torso trauma was developed. Potential benefits of a CDR include more appropriate abdominal computed tomography (CT) use and decreased hospital costs. The objective of this study was to compare the cost-effectiveness of implementing the CDR compared to usual care for the evaluation of children with blunt torso trauma. The hypothesis was that compared to usual care, implementation of the CDR would result in lower CT use and hospital costs. Methods A cost-effectiveness decision analytic model was constructed comparing the costs and outcomes of implementation of the CDR to usual care in the evaluation of children with blunt torso trauma. Probabilities from a multicenter cohort study of children with blunt torso trauma were derived; estimated costs were based on those at the study coordinating site. Outcome measures included missed IAI, number of abdominal CT scans, total costs, and incremental cost-effectiveness ratios. Sensitivity analyses varying imputed probabilities, costs, and scenarios were conducted. Results Using a hypothetical cohort of 1,000 children with blunt torso trauma, the base case model projected that the implementation of the CDR would result in 0.50 additional missed IAIs, a total cost savings of $54,527, and 104 fewer abdominal CT scans compared to usual care. The usual care strategy would cost $108,110 to prevent missing one additional IAI. Findings were robust under multiple sensitivity analyses. Conclusions Compared to usual care, implementation of the CDR in the evaluation of children with blunt torso trauma would reduce hospital costs and abdominal CT imaging, with a slight increase in the risk of missed intraabdominal IAI. PMID:24238315

  13. 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

  14. Data Decision Analysis: Project Shoal

    SciTech Connect

    Forsgren, Frank; Pohll, Greg; Tracy, John

    1999-01-01

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

  15. 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

  16. Consensus, clinical decision making, and unsettled cases.

    PubMed

    Adams, David M; Winslade, William J

    2011-01-01

    The model of clinical ethics consultation (CEC) defended in the ASBH Core Competencies report has gained significant traction among scholars and healthcare providers. On this model, the aim of CEC is to facilitate deliberative reflection and thereby resolve conflicts and clarify value uncertainty by invoking and pursuing a process of consensus building. It is central to the model that the facilitated consensus falls within a range of allowable options, defined by societal values: prevailing legal requirements, widely endorsed organizational policies, and professional standards of practice and codes of conduct. Moreover, the model stipulates that ethics consultants must refrain from giving substantive recommendations regarding how parties to a moral disagreement in the clinic should evaluate their options. We argue that this model of CEC is incomplete, because it wrongly assumes that what counts as the proper set of allowable options among which the parties are to deliberate will itself always be clearly discernible. We illustrate this problem with a recent case on which one of us consulted-a neonate born with trisomy 18 (T18). We try to show that law, policy, and standards of practice reveal no clear answer to the question posed by the case: namely, whether forgoing gastrostomy tube feedings for a baby with T18 is allowable. We suggest there may be other kinds of cases in which it may simply be unsettled whether a given choice falls within the set of allowable options within which consensus is to be facilitated. What should an ethicist do when confronting such unsettled cases? We agree with the facilitation model that an ethicist should remain neutral among the allowable options, when it is clear what the allowable options are. But, in unsettled cases, the role of a consultant should be expanded to include a process of moral inquiry into what the allowable options should be. We end by raising the issue of whether this means an ethicist should share his or her own

  17. 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

  18. 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...

  19. The thinking doctor: clinical decision making in contemporary medicine.

    PubMed

    Trimble, Michael; Hamilton, Paul

    2016-08-01

    Diagnostic errors are responsible for a significant number of adverse events. Logical reasoning and good decision-making skills are key factors in reducing such errors, but little emphasis has traditionally been placed on how these thought processes occur, and how errors could be minimised. In this article, we explore key cognitive ideas that underpin clinical decision making and suggest that by employing some simple strategies, physicians might be better able to understand how they make decisions and how the process might be optimised. PMID:27481378

  20. 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

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

    PubMed Central

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

    2004-01-01

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

  2. 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

  3. Improving Congestive Heart Failure Care with a Clinical Decision Unit.

    PubMed

    Carpenter, Jo Ellen; Short, Nancy; Williams, Tracy E; Yandell, Ben; Bowers, Margaret T

    2015-01-01

    Evidence supporting the development of Clinical Decision Units (CDUs) to impact congestive heart failure readmission rates comes from several categories of the literature. In this study, a pre-post design with comparison group was used to evaluate the impact of the CDU. Early changes in clinical and financial outcome indicators are encouraging. Nurse leaders seek ways to improve clinical outcomes while managing the current financially challenging environment. Implementation of a CDU provides many opportunities for nurse leaders to positively impact clinical care and financial performance within their institutions. PMID:26625578

  4. 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. PMID:23932101

  5. 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

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

    ERIC Educational Resources Information Center

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

    2002-01-01

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

  7. Using Clinical Decision Support Software in Health Insurance Company

    NASA Astrophysics Data System (ADS)

    Konovalov, R.; Kumlander, Deniss

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

  8. 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

  9. 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

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

    PubMed

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

    2014-01-01

    The research world is undergoing a transformation into one in which data, on massive levels, is freely shared. In the clinical world, the capture of data on a consistent basis has only recently begun. We propose an operational vision for a digitally based care system that incorporates data-based clinical decision making. The system would aggregate individual patient electronic medical data in the course of care; query a universal, de-identified clinical database using modified search engine technology in real time; identify prior cases of sufficient similarity as to be instructive to the case at hand; and populate the individual patient's electronic medical record with pertinent decision support material such as suggested interventions and prognosis, based on prior outcomes. Every individual's course, including subsequent outcomes, would then further populate the population database to create a feedback loop to benefit the care of future patients. PMID:25600664

  11. Dynamic Clinical Data Mining: Search Engine-Based Decision Support

    PubMed Central

    Zimolzak, Andrew J; Stone, David J

    2014-01-01

    The research world is undergoing a transformation into one in which data, on massive levels, is freely shared. In the clinical world, the capture of data on a consistent basis has only recently begun. We propose an operational vision for a digitally based care system that incorporates data-based clinical decision making. The system would aggregate individual patient electronic medical data in the course of care; query a universal, de-identified clinical database using modified search engine technology in real time; identify prior cases of sufficient similarity as to be instructive to the case at hand; and populate the individual patient's electronic medical record with pertinent decision support material such as suggested interventions and prognosis, based on prior outcomes. Every individual's course, including subsequent outcomes, would then further populate the population database to create a feedback loop to benefit the care of future patients. PMID:25600664

  12. How decision analysis can further nanoinformatics.

    PubMed

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

    2015-01-01

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

  13. Which Bisphosphonate? It's the Compliance!: Decision Analysis

    PubMed Central

    Lee, You Jin; Park, Chan Ho; Ha, Yong-Chan; Koo, Kyung-Hoi

    2016-01-01

    Background The best options of several bisphosphonates for prevention of osteoporotic fractures in postmenopausal women remain controversial. We determined which bisphosphonate provides better efficacy in prevention of osteoporotic fractures using a decision analysis tool, in terms of quality of life. Methods A decision analysis model was constructed containing final outcome score and the probability of vertebral and hip fracture within 1 year. Final outcome was defined as health-related quality of life, and was used as an utility in the decision tree. Probabilities were obtained by literature review, and health-related quality of life was evaluated by consensus committee. A roll back tool was used to determine the best bisphosphonate, and sensitivity analysis was performed to compensate for decision model uncertainty. Results The decision model favored bisphosphonate with higher compliance in terms of quality of life. In one-way sensitivity analysis, ibandronate was more beneficial than the others, when probability of compliance on ibandronate was above 0.589. Conclusions In terms of quality of life, the decision analysis model showed that compliance was most important for patients in real world, regardless of type of bisphosphonate.

  14. Assessment of cervical lymph node metastasis for therapeutic decision-making in squamous cell carcinoma of buccal mucosa: a prospective clinical analysis

    PubMed Central

    2012-01-01

    Background Cervical metastasis has a tremendous impact on the prognosis in patients with carcinomas of the head and neck and the frequency of such spread is greater than 20% for most squamous cell carcinomas. With emerging evidence, focus is shifting to conservative neck procedures aimed at achieving good shoulder function without compromising oncologic safety. The purpose of this study was to analyze the pattern of nodal metastasis in patients presenting with squamous cell carcinoma of buccal mucosa. Materials and methods This was a prospective clinical analysis of patients who were histologically diagnosed with squamous cell carcinoma of the buccal cavity and clinically N1 and had not received treatment anywhere else. Patients were analyzed for age and sex distribution, tumor staging, location, and metastasis. Results The incidence of metastatic lymph node in T4 (n=44) was the highest, that is, level I was 100% (44/44), level II was 43.18% (19/44), level III was 15.90% (7/44), and level IV was 4.5% (2/44). Level V was free of metastasis. Among T3 (n=10) lesions, incidence of metastasis in level I was 100% (10/10), level II was 20% (2/10), and level III, IV, and V were free of metastasis. Among T2 (n=6) lesions, incidence of lymph node metastasis in level I was 100% (6/6) and all other levels of lymph nodes were found free of metastasis. Conclusion Lymphatic spread from carcinoma of the buccal mucosa is low. Involvement of level IV is seen in only 3% of patients. A more conservative approach to the neck in patients with carcinoma of the buccal mucosa is recommended. PMID:23173732

  15. Ethical decision-making challenges in clinical practice.

    PubMed

    Horowitz, Beverly P

    2003-01-01

    Today's health care environment requires professionals to pay increasing attention to efficiencies and functional outcomes. Today's patients are hospitalized for short stays, and those needing rehabilitation often have multiple diagnoses and goals. Cost effective strategies support fast paced occupational therapy programs and professionals who are adept multi-task specialists and problem solvers. Practitioners have multiple resources and strategies for clinical reasoning and decision-making; however, ethical decision-making requires use of additional resources and strategies. This paper provides strategies to examine everyday ethical problems and dilemmas, including application of The American Occupational Therapy's Code of Ethics, to support ethical decision-making in practice settings (American Occupational Therapy Association, 2000a). PMID:23930704

  16. The effects of clinical decision making on nurse practitioners' clinical productivity.

    PubMed

    Chumbler, N R; Geller, J M; Weier, A W

    2000-09-01

    The degree of clinical decision making and clinical productivity among nurse practitioners (NPs) is of great interest to policy makers and planners involved in providing appropriate outpatient primary care services. The authors performed a statewide mailed survey of all NPs practicing either full-time or part-time in Wisconsin (response rate of 72.1%) to address the following research questions: Do the demographic characteristics, practice attributes, and primary practice settings of NPs impact their level of clinical decision making (e.g., the autonomy to order laboratory and radiological tests or to refer a patient to a physician specialist other than their collaborating physician)? Do NPs' levels of clinical decision making correlate with their outpatient clinical productivity, adjusting for demographic characteristics, practice attributes, and primary practice settings? The multiple linear regression results indicated that having more years in practice as an NP, practicing in the family specialty area (vs. a combined other category, which included pediatrics, acute care, geriatrics, neonatal, and school), treating patients according to clinical guidelines, practicing in settings with a fewer number of physicians, and practicing in a multispecialty group practice versus a single-specialty group practice were associated with greater levels of clinical decision making. However, NPs who primarily practiced in a hospital/facility-based practice, as compared with a single-specialty group practice, had lower levels of clinical decision making. After adjusting for demographic characteristics, practice attributes, and primary practice settings, NPs with greater clinical decision-making authority had greater outpatient clinical productivity. The conclusions discuss the policy implications of the findings. PMID:11067192

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

    PubMed

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

    2015-01-01

    Pharmacogenomics (PGx) guidelines contain drug-gene relationships, therapeutic and clinical recommendations from which clinical decision support (CDS) rules can be extracted, rendered and then delivered through clinical decision support systems (CDSS) to provide clinicians with just-in-time information at the point of care. Several tools exist that can be used to generate CDS rules that are based on computer interpretable guidelines (CIG), but none have been previously applied to the PGx domain. We utilized the Unified Modeling Language (UML), the Health Level 7 virtual medical record (HL7 vMR) model, and standard terminologies to represent the semantics and decision logic derived from a PGx guideline, which were then mapped to the Health eDecisions (HeD) schema. The modeling and extraction processes developed here demonstrate how structured knowledge representations can be used to support the creation of shareable CDS rules from PGx guidelines. PMID:26958298

  18. 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

  19. Clinical decision support systems: data quality management and governance.

    PubMed

    Liaw, Siaw-Teng

    2013-01-01

    This chapter examines data quality management (DQM) and information governance (IG) of electronic decision support (EDS) systems so that they are safe and fit for use by clinicians and patients and their carers. This is consistent with the ISO definition of data quality as being fit for purpose. The scope of DQM & IG should range from data creation and collection in clinical settings, through cleaning and, where obtained from multiple sources, linkage, storage, use by the EDS logic engine and algorithms, knowledge base and guidance provided, to curation and presentation. It must also include protocols and mechanisms to monitor the safety of EDS, which will feedback into DQM & IG activities. Ultimately, DQM & IG must be integrated across the data cycle to ensure that the EDS systems provide guidance that leads to safe and effective clinical decisions and care. PMID:24018528

  20. 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

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

    PubMed Central

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

    2006-01-01

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

  2. 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. PMID:22874282

  3. [ Preventing adverse drug events using clinical decision support systems].

    PubMed

    Salili, Ali Reza; Hammann, Felix; Taegtmeyer, Anne B

    2015-12-01

    Adverse drug events pose a great risk to patients, are an everyday clinical problem and can have potential/ega/ consequences. Computerized physician order entry or computerized provider order entry (CPOE} in combination with clinical decision support systems {CDSS) are popular and aim to reduce prescribing errors as well as identifying potentially harmful drug drug interactions. The quantifiable benejit these systems bring to patients, has however, yet to be definitively proven. This article focusses on the current standpoint of CPOE-/CDSS, their risks and benefits, the potential for improvement and their perspectives for the future. PMID:26654813

  4. Mechanistic biomarkers for clinical decision making in rheumatic diseases

    PubMed Central

    Robinson, William H.; Lindstrom, Tamsin M.; Cheung, Regina K.; Sokolove, Jeremy

    2013-01-01

    The use of biomarkers is becoming increasingly intrinsic to the practice of medicine and holds great promise for transforming the practice of rheumatology. Biomarkers have the potential to aid clinical diagnosis when symptoms are present or to provide a means of detecting early signs of disease when they are not. Some biomarkers can serve as early surrogates of eventual clinical outcomes or guide therapeutic decision making by enabling identification of individuals likely to respond to a specific therapy. Using biomarkers might reduce the costs of drug development by enabling individuals most likely to respond to be enrolled in clinical trials, thereby minimizing the number of participants required. In this Review, we discuss the current use and the potential of biomarkers in rheumatology and in select fields at the forefront of biomarker research. We emphasize the value of different types of biomarkers, addressing the concept of ‘actionable’ biomarkers, which can be used to guide clinical decision making, and ‘mechanistic’ biomarkers, a subtype of actionable biomarker that is embedded in disease pathogenesis and, therefore, represents a superior biomarker. We provide examples of actionable and mechanistic biomarkers currently available, and discuss how development of such biomarkers could revolutionize clinical practice and drug development. PMID:23419428

  5. Neural networks and psychiatry: candidate applications in clinical decision making.

    PubMed

    Florio, T; Einfeld, S; Levy, F

    1994-12-01

    Neural networks comprise a fundamentally new type of computer system inspired by the functioning of neurons in the brain. Such networks are good at solving problems that involve pattern recognition and categorisation. An important difference between a neural network and a traditional computer system is that in developing an application, a neural network is not programmed; instead, it is trained to solve a particular type of problem. This ability to learn to solve a problem makes neural networks adaptable to solving a wide variety of problems, some of which have proved intractable using a traditional computing approach. Neural networks are particularly suited to tasks involving the categorisation of patterns of information, such as is required in diagnosis and clinical decision making. In the last three years reports of applications involving neural networks have begun to appear in the medical literature, and these are described in this paper. However, a comprehensive search of the literature has shown that there have not as yet been reports of any applications in psychiatry. This paper discusses the nature of clinical decision making, outlines the sorts of problems in psychiatry which neural networks applications might be developed to address, and gives examples of candidate applications in clinical decision making. PMID:7794209

  6. Priority oral health research identification for clinical decision-making.

    PubMed

    Worthington, Helen; Clarkson, Jan; Weldon, Jo

    2015-09-01

    The Cochrane Library is a core resource for clinical decision-making globally, by clinicians, guideline developers, healthcare providers and patients.The publication of Cochrane Library systematic reviews concerning oral health conditions has grown exponentially to over 215 individual titles (as of 20 June 2015) during the past 20 years.Consequently, maintaining updates of the most clinically important reviews to provide up-to-date and accurate sources of evidence for decision-making has become a pressing concern for the editorial group behind their production, Cochrane Oral Health Group.To identify priority research required by oral health decision-makers, the Cochrane OHG embarked on a consultation process across eight defined areas of dentistry (periodontology, operative (including endodontics) and prosthodontics, paediatric dentistry, dental public health, oral and maxillofacial surgery, oral medicine, orthodontics, cleft lip and/or palate) with existing authors (by email), with members of the public (by online survey), and established internationally clinically expert panels for each area of defined area of dentistry to discuss and ratify (by teleconference) a core portfolio of priority evidence to be produced and maintained on the Cochrane Library.The resulting portfolio of priority research encompasses 81 existing titles to be maintained, and an additional 15 new systematic reviews to be developed by the Cochrane OHG in due course.The Cochrane OHG has actively responded to the outcomes of this prioritisation process by allocating resources to primarily supporting the maintenance of identified priority evidence for the Cochrane Library. PMID:26492797

  7. 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.

  8. 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.

  9. 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…

  10. 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

  11. Cancer diagnostics: decision criteria for marker utilization in the clinic.

    PubMed

    Taube, Sheila E; Jacobson, James W; Lively, Tracy G

    2005-01-01

    A new diagnostic tool must pass three major tests before it is adopted for routine clinical use. First, the tool must be robust and reproducible; second, the clinical value of the tool must be proven, i.e. the tool should reliably trigger a clinical decision that results in patient benefit; and, third, the clinical community has to be convinced of the need for this tool and the benefits it affords. Another factor that can influence the adoption of new tools relates to the cost and the vagaries of insurance reimbursement. The Cancer Diagnosis Program (CDP) of the US National Cancer Institute (NCI) launched the Program for the Assessment of Clinical Cancer Tests (PACCT) in 2000 to develop a process for moving the results of new technologies and new understanding of cancer biology more efficiently and effectively into clinical practice. PACCT has developed an algorithm that incorporates the iterative nature of assay development into an evaluation process that includes developers and end users. The effective introduction of new tests into clinical practice has been hampered by a series of common problems that are best described using examples of successes and failures. The successful application of the PACCT algorithm is described in the discussion of the recent development of the OncotypeDX assay and plan for a prospective trial of this assay by the NCI-supported Clinical Trials Cooperative Groups. The assay uses reverse transcription (RT)-PCR evaluation of a set of 16 genes that were shown to strongly associate with the risk of recurrence of breast cancer in women who presented with early stage disease (hormone responsive, and no involvement of the auxiliary lymph nodes). The test is highly reproducible. It provides information to aid the physician and patient in making important clinical decisions, including the aggressiveness of the therapy that should be recommended. A trial is planned to test whether OncotypeDX can be used as a standalone trigger for specific

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

    PubMed

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

    2010-01-01

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

  13. Computer-Based Medical Decision Support System based on guidelines, clinical pathways and decision nodes.

    PubMed

    Tomaszewski, Wiesław

    2012-01-01

    A continuous and dynamic development of medical sciences which is currently taking place all over the world is associated with a considerable increase in the number of scientific reports and papers of importance in enhancing the effectiveness of treatment and quality of medical care. However, it is difficult, or, indeed, impossible, for physicians to regularly follow all recent innovations in medical knowledge and to apply the latest research findings to their daily clinical practice. More and more studies conducted both in Poland and worldwide as well as experience from clinical practice in various countries provide convincing evidence that various systems supporting medical decision-making by physicians or other medical professionals visibly improve the quality of medical care. The use of such systems is already possible and recently has been developing especially dynamically, as the level of knowledge and information and communication technology now permits their effective implementation. Currently, electronic knowledge bases, together with inference procedures, form intelligent medical information systems, which offer many possibilities for the support of medical decision-making, mainly in regard to interactive diagnostic work-up, but also the selection of the most suitable treatment plan (clinical pathway). Regardless of their scale and area of application, these systems are referred to as Computer-Based Medical Decision Support Systems (CBMDSS). PMID:22741924

  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. 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

  16. 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

  17. Clinical decision making in restorative dentistry, endodontics, and antibiotic prescription.

    PubMed

    Zadik, Yehuda; Levin, Liran

    2008-01-01

    The purpose of this study was to evaluate the influence of geographic location of graduation (Israel, Eastern Europe, Latin America) on decision making regarding management of dental caries, periapical lesions, and antibiotic prescribing routines. A questionnaire was given to ninety-eight general practitioners regarding demographic and work habits. Photographs of lesions were shown on a screen. Participants reported recommended treatment and whether they would routinely prescribe antibiotics following regular endodontic treatment, retreatment, and impacted third molar surgical extraction in healthy patients. There was a 94 percent (n=92) response rate, of which eighty-five responses were used in the data analysis. Surgical treatment of asymptomatic enamel caries lesions was not recommended by most of the subjects, and surgery was recommended for DEJ caries lesions in low or moderate caries risk patients, both without significant differences between geographic regions of dental school graduation. Israelis had a lower frequency of retreatment in asymptomatic teeth that demonstrated periapical radiolucency with post restoration (without crown) compared to Latin Americans and East Europeans. Most of the participants would not retreat asymptomatic teeth that demonstrated periapical radiolucency with post and crown. After third molar surgery, 46 percent of participants routinely prescribed antibiotics. Significantly more Latin American graduates prescribed antibiotics following endodontic treatment, retreatment, and third molar extractions (p<0.05). Overmedication (antibiotics) and overtreatment (caries) among young practitioners reflect failure of undergraduate education in proper use of antibiotics and management of the carious lesions according to the patient's clinical presentation and caries risk assessment rather than routinely undertaking surgical caries treatment. PMID:18172239

  18. 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

  19. Clinical decision support for physician order-entry: design challenges.

    PubMed

    Broverman, C A; Clyman, J I; Schlesinger, J M; Want, E

    1996-01-01

    We report on a joint development effort between ALLTEL Information Services Health Care Division and IBM Worldwide Healthcare Industry to demonstrate concurrent clinical decision support using Arden Syntax at order-entry time. The goal of the partnership is to build a high performance CDS toolkit that may be easily customized for multiple health care enterprises. Our work uses and promotes open technologies and health care standards while building a generalizable interface to a legacy patient-care system and clinical database. This paper identifies four areas of design challenges and solutions unique to a concurrent order-entry environment: the clinical information model, the currency of the patient virtual chart, the granularity of event triggers and rule evaluation context, and performance. PMID:8947731

  20. 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.

  1. 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

  2. Clinical Verification of A Clinical Decision Support System for Ventilator Weaning

    PubMed Central

    2013-01-01

    Background Weaning is typically regarded as a process of discontinuing mechanical ventilation in the daily practice of an intensive care unit (ICU). Among the ICU patients, 39%-40% need mechanical ventilator for sustaining their lives. The predictive rate of successful weaning achieved only 35-60% for decisions made by physicians. Clinical decision support systems (CDSSs) are promising in enhancing diagnostic performance and improve healthcare quality in clinical setting. To our knowledge, a prospective study has never been conducted to verify the effectiveness of the CDSS in ventilator weaning before. In this study, the CDSS capable of predicting weaning outcome and reducing duration of ventilator support for patients has been verified. Methods A total of 380 patients admitted to the respiratory care center of the hospital were randomly assigned to either control or study group. In the control group, patients were weaned with traditional weaning method, while in the study group, patients were weaned with CDSS monitored by physicians. After excluding the patients who transferred to other hospitals, refused further treatments, or expired the admission period, data of 168 and 144 patients in the study and control groups, respectively, were used for analysis. Results The results show that a sensitivity of 87.7% has been achieved, which is significantly higher (p<0.01) than the weaning determined by physicians (sensitivity: 61.4%). Furthermore, the days using mechanical ventilator for the study group (38.41 ± 3.35) is significantly (p<0.001) shorter than the control group (43.69 ± 14.89), with a decrease of 5.2 days in average, resulting in a saving of healthcare cost of NT$45,000 (US$1,500) per patient in the current Taiwanese National Health Insurance setting. Conclusions The CDSS is demonstrated to be effective in identifying the earliest time of ventilator weaning for patients to resume and sustain spontaneous breathing, thereby avoiding unnecessary prolonged

  3. A health examination system integrated with clinical decision support system.

    PubMed

    Kuo, Kuan-Liang; Fuh, Chiou-Shann

    2010-10-01

    Health examinations play a key role in preventive medicine. We propose a health examination system named Health Examination Automatic Logic System (HEALS) to assist clinical workers in improving the total quality of health examinations. Quality of automated inference is confirmed by the zero inference error where during 6 months and 14,773 cases. Automated inference time is less than one second per case in contrast to 2 to 5 min for physicians. The most significant result of efficiency evaluation is that 3,494 of 4,356 (80.2%) cases take less than 3 min per case for producing a report summary. In the evaluation of effectiveness, novice physicians got 18% improvement in making decisions with the assistance of our system. We conclude that a health examination system with a clinical decision system can greatly reduce the mundane burden on clinical workers and markedly improve the quality and efficiency of health examination tasks. PMID:20703626

  4. Multiple Perspectives on the Meaning of Clinical Decision Support

    PubMed Central

    Richardson, Joshua E.; Ash, Joan S.; Sittig, Dean F.; Bunce, Arwen; Carpenter, James; Dykstra, Richard H.; Guappone, Ken; McCormack, James; McMullen, Carmit K.; Shapiro, Michael; Wright, Adam; Middleton, Blackford

    2010-01-01

    Clinical Decision Support (CDS) is viewed as a means to improve safety and efficiency in health care. Yet the lack of consensus about what is meant by CDS represents a barrier to effective design, implementation, and utilization of CDS tools. We conducted a multi-site qualitative inquiry to understand how different people define and describe CDS. Using subjects’ multiple perspectives we were able to gain new insights as to what stakeholders want CDS to achieve and how to achieve it even when those perspectives are competing and conflicting. PMID:21347119

  5. Multiple Perspectives on the Meaning of Clinical Decision Support

    PubMed Central

    Richardson, Joshua E.; Ash, Joan S.; Sittig, Dean F.; Bunce, Arwen; Carpenter, James; Dykstra, Richard H.; Guappone, Ken; McMullen, Carmit K.; Shapiro, Michael; Wright, Adam

    2010-01-01

    Clinical Decision Support (CDS) is viewed as a means to improve safety and efficiency in health care. Yet the lack of a consensus around what is meant by CDS represents a barrier to effective design, use, and utilization of CDS tools. We conducted a multi-site qualitative inquiry to understand how different people define and describe CDS. Using subjects’ multiple perspectives we were able to gain new insights as to what stakeholders want CDS to achieve and how to achieve it; even at times when those perspectives are competing and conflicting. PMID:21347063

  6. 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

  7. 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

  8. Evaluation of RxNorm for Medication Clinical Decision Support.

    PubMed

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

    2014-01-01

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

  9. 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. PMID:24399281

  10. 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. PMID:26581731

  11. 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

  12. Practical clinical trials: increasing the value of clinical research for decision making in clinical and health policy.

    PubMed

    Tunis, Sean R; Stryer, Daniel B; Clancy, Carolyn M

    2003-09-24

    Decision makers in health care are increasingly interested in using high-quality scientific evidence to support clinical and health policy choices; however, the quality of available scientific evidence is often found to be inadequate. Reliable evidence is essential to improve health care quality and to support efficient use of limited resources. The widespread gaps in evidence-based knowledge suggest that systematic flaws exist in the production of scientific evidence, in part because there is no consistent effort to conduct clinical trials designed to meet the needs of decision makers. Clinical trials for which the hypothesis and study design are developed specifically to answer the questions faced by decision makers are called pragmatic or practical clinical trials (PCTs). The characteristic features of PCTs are that they (1) select clinically relevant alternative interventions to compare, (2) include a diverse population of study participants, (3) recruit participants from heterogeneous practice settings, and (4) collect data on a broad range of health outcomes. The supply of PCTs is limited primarily because the major funders of clinical research, the National Institutes of Health and the medical products industry, do not focus on supporting such trials. Increasing the supply of PCTs will depend on the development of a mechanism to establish priorities for these studies, significant expansion of an infrastructure to conduct clinical research within the health care delivery system, more reliance on high-quality evidence by health care decision makers, and a substantial increase in public and private funding for these studies. For these changes to occur, clinical and health policy decision makers will need to become more involved in all aspects of clinical research, including priority setting, infrastructure development, and funding. PMID:14506122

  13. 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

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

    ERIC Educational Resources Information Center

    Rittenhouse, Brian E.

    1994-01-01

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

  15. 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

  16. The impact of goal-directed transvaginal ultrasonography on clinical decision-making for emergency physicians.

    PubMed

    Sayrac, Neslihan; Bektas, Firat; Soyuncu, Secgin; Sayrac, Vefa

    2015-07-01

    The aim of study was to determine the impact of "goal-directed transvaginal ultrasonography" (TVUSG) on real-time clinical decision making of attending emergency physicians evaluating their level of certainty for preliminary diagnosis, admission, surgery, treatment, additional laboratory, and discharge in patients presenting with acute pelvic pain to the emergency department (ED). This prospective cross-sectional clinical study was conducted on sexually active female patients older than 18 years who presented with acute pelvic pain in the ED. The level of certainty of clinical decision making as mentioned above was measured by a visual analogue scale from 0 to 100 mm with 100 mm being most certain before and after TVUSG. Statistical analysis was performed on 88 patients. The mean age was 31.7 ±8.3 years with a median of 30 years. Among clinical decisions, there was a significant difference between pre-TVUSG and post-TVUSG certainty of the decision to perform preliminary diagnoses derived from patient's history and physical examination but not in the other outcomes (treatment, admission, surgery, and discharge). (P = .05). Of the patients included in the study, 11 (12.5%) were admitted to hospital, and 2 (2.3%) of them were operated on. The remaining 75 (85.2%) patients were discharged from the ED; of the patients that had been discharged, 18 (20.5%) patients later consulted another physician, and no further pathology could be discovered. In conclusion, US performed by attending emergency physicians may affect the certainty of their decisions in patients presenting with acute pelvic pain. This effect statistically significantly on the decision to determine preliminary diagnosis. PMID:25963680

  17. 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.

  18. 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

  19. Biostatistics in clinical decision making for cardiothoracic radiologists.

    PubMed

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

    2013-11-01

    Cardiothoracic radiologists are intuitively aware of sensitivity and specificity as they pertain to diagnostic tests involving clinical information. However, many cardiothoracic radiologists are unfamiliar with odds ratios, likelihood ratios, predictive values, and receiver operating characteristic (ROC) curves, which provide more information about the performance of a test. Our article will first review the fundamental concepts of sensitivity, specificity, predictive values, and likelihood ratios. The ROC curve methodology will be covered with an emphasis on creating a look-up table, a straightforward table that communicates important information to the clinician to aid in diagnosis. The article reviews sensitivity and specificity, as well as predictive values, logistic regression, and ROC curves, using conceptual principles without unnecessary mathematical rigor. We will apply principles of sensitivity and specificity to continuous measurements by constructing ROC curves in order to tie together key ideas in diagnostic decision making. Three clinical examples are presented to illustrate these fundamental statistical concepts: predictors of pulmonary embolism in children, use of dobutamine-cardiac magnetic resonance imaging to identify impaired ventricular function in patients who have suffered a myocardial infarction, and diagnostic accuracy of 64-multidetector row computed tomography to identify occluded vessels in adult patients with suspected coronary artery disease. In addition, a glossary is provided at the end of the article with key terms important in diagnostic imaging. An understanding of the concepts presented will assist cardiothoracic radiologists in critically discerning the usefulness of diagnostic tests and how these statistics can be applied to make judgments and decisions that are essential to clinical practice. PMID:23358369

  20. 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

  1. Defense against nuclear weapons: a decision analysis

    SciTech Connect

    Orient, J.M.

    1985-02-01

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

  2. 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

  3. Methodologic standards for interpreting clinical decision rules in emergency medicine: 2014 update.

    PubMed

    Green, Steven M; Schriger, David L; Yealy, Donald M

    2014-09-01

    Clinical decision rules are increasingly prominent in medicine, particularly in emergency care. The quality, use, and impact of current published decision rules widely vary, requiring clinicians to be critical consumers. We present an approach to assist in the appraisal of clinical decision rules and in judging when to use such rules. PMID:24530108

  4. 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. PMID:23690340

  5. Decision Analysis Tools for Volcano Observatories

    NASA Astrophysics Data System (ADS)

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

    2005-12-01

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

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

    PubMed Central

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

    2014-01-01

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

  7. 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. PMID:23304284

  8. Optimizing Perioperative Decision Making: Improved Information for Clinical Workflow Planning

    PubMed Central

    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. PMID:23304284

  9. 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.

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

    PubMed

    Chattopadhyay, Soumi; Banerjee, Ansuman; Banerjee, Nilanjan

    2015-01-01

    Clinical Decision Support systems (CDSS) have reached a fair level of sophistication and have emerged as the popular system of choice for their aid in clinical decision making. These decision support systems are based on rule engines navigate through a repertoire of clinical rules and multitudes of facts to assist a clinical expert to decide on the set of actuations in response to a medical situation. In this paper, we present the design of a scalable architecture for a rule engine based clinical decision system. PMID:26262249

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

    PubMed

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

    2014-07-01

    Drawing on wider sociologies of risk, this article examines the complexity of clinical risks and their management, focusing on risk management systems, expert decision-making and safety standards in health care. At the time of this study preventing venous thromboembolism (VTE) among in-patients was one of the top priorities for hospital safety in the English National Health Service (NHS). An analysis of 50 interviews examining hospital professionals' perceptions about VTE risks and prophylaxis illuminates how National Institute for Health and Clinical Excellence (NICE) guidelines influenced clinical decision-making in four hospitals in one NHS region. We examine four themes: the identification of new risks, the institutionalisation and management of risk, the relationship between risk and danger and the tensions between risk management systems and expert decision-making. The implementation of NICE guidelines for VTE prevention extended managerial control over risk management but some irreducible clinical dangers remained that were beyond the scope of the new VTE risk management systems. Linking sociologies of risk with the realities of hospital risk management reveals the capacity of these theories to illuminate both the possibilities and the limits of managerialism in health care. PMID:24635764

  12. SANDS - Sediment Analysis Network for Decision Support

    NASA Astrophysics Data System (ADS)

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

    2010-12-01

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

  13. Reducing inappropriate ESR testing with computerized clinical decision support

    PubMed Central

    Gottheil, Stephanie; Khemani, Ekta; Copley, Katherine; Keeney, Michael; Kinney, Jeff; Chin-Yee, Ian; Gob, Alan

    2016-01-01

    Laboratory test overutilization increases health care costs, leads to unwarranted investigations, and may have a negative impact on health outcomes. The American Society of Clinical Pathology, in its Choosing Wisely Campaign, advocates that inflammation be investigated with C-reactive protein (CRP) instead of Erythrocyte Sedimentation Rate (ESR). London Health Sciences Centre (LHSC), a tertiary care hospital organization in Ontario, Canada, set a goal to reduce inappropriate ESR orders by 50%. After developing appropriateness criteria for ESR, we used a series of PDSA cycles to reduce inappropriate ESR ordering and analyzed our results with an interrupted time series design. Our intervention began with an educational bulletin and moved to city-wide implementation of computerized Clinical Decision Support (CDS). After implementation, ESR orders decreased by 40% from 386 orders per week to 241 orders per week. Our results are supported by previous literature on the effectiveness of CDS in reducing overutilization and suggest that provider habit is a significant contributor to inappropriate ordering. PMID:27096092

  14. Reducing inappropriate ESR testing with computerized clinical decision support.

    PubMed

    Gottheil, Stephanie; Khemani, Ekta; Copley, Katherine; Keeney, Michael; Kinney, Jeff; Chin-Yee, Ian; Gob, Alan

    2016-01-01

    Laboratory test overutilization increases health care costs, leads to unwarranted investigations, and may have a negative impact on health outcomes. The American Society of Clinical Pathology, in its Choosing Wisely Campaign, advocates that inflammation be investigated with C-reactive protein (CRP) instead of Erythrocyte Sedimentation Rate (ESR). London Health Sciences Centre (LHSC), a tertiary care hospital organization in Ontario, Canada, set a goal to reduce inappropriate ESR orders by 50%. After developing appropriateness criteria for ESR, we used a series of PDSA cycles to reduce inappropriate ESR ordering and analyzed our results with an interrupted time series design. Our intervention began with an educational bulletin and moved to city-wide implementation of computerized Clinical Decision Support (CDS). After implementation, ESR orders decreased by 40% from 386 orders per week to 241 orders per week. Our results are supported by previous literature on the effectiveness of CDS in reducing overutilization and suggest that provider habit is a significant contributor to inappropriate ordering. PMID:27096092

  15. 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

  16. [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

  17. Evaluating clinical decision support rules as an intervention in clinician workflows with technology.

    PubMed

    Brokel, Jane M; Schwichtenberg, Tamara J; Wakefield, Douglas S; Ward, Marcia M; Shaw, Michael G; Kramer, J Michael

    2011-01-01

    The implementation of electronic health records in rural settings generated new challenges beyond those seen in urban hospitals. The preparation, implementation, and sustaining of clinical decision support rules require extensive attention to standards, content design, support resources, expert knowledge, and more. A formative evaluation was used to present progress and evolution of clinical decision support rule implementation and use within clinician workflows for application in an electronic health record. The rural hospital was able to use clinical decision support rules from five urban hospitals within its system to promote safety, prevent errors, establish evidence-based practices, and support communication. This article describes tools to validate initial 54 clinical decision support rules used in a rural referral hospital and 17 used in clinics. Since 2005, the study hospital has added specific system clinical decision support rules for catheter-acquired urinary tract infection, deep venous thrombosis, heart failure, and more. The findings validate the use of clinical decision support rules across sites and ability to use existing indicators to measure outcomes. Rural hospitals can rapidly overcome the barriers to prepare and implement as well as sustain use of clinical decision support rules with a systemized approach and support structures. A model for design and validation of clinical decision support rules into workflow processes is presented. The replication and reuse of clinical decision support rule templates with data specifications that follow data models can support reapplication of the rule intervention in subsequent rural and critical access hospitals through system support resources. PMID:21099543

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

    PubMed

    Kuo, Kuan-Liang; Fuh, Chiou-Shann

    2011-12-01

    Health examinations can obtain relatively complete health information and thus are important for the personal and public health management. For clinicians, one of the most important works in the health examinations is to interpret the health examination results. Continuously interpreting numerous health examination results of healthcare receivers is tedious and error-prone. This paper proposes a clinical decision support system to assist solving above problems. In order to customize the clinical decision support system intuitively and flexibly, this paper also proposes the rule syntax to implement computer-interpretable logic for health examinations. It is our purpose in this paper to describe the methodology of the proposed clinical decision support system. The evaluation was performed by the implementation and execution of decision rules on health examination results and a survey on clinical decision support system users. It reveals the efficiency and user satisfaction of proposed clinical decision support system. Positive impact of clinical data interpretation is also noted. PMID:20703517

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

    PubMed Central

    Brien, Sarah; Dibb, Bridget; Burch, Alex

    2011-01-01

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

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

    PubMed Central

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

    2015-01-01

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

  1. [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

  2. Clinical decision support, systems methodology, and telemedicine: their role in the management of chronic disease.

    PubMed

    Carson, E R; Cramp, D G; Morgan, A; Roudsari, A V

    1998-06-01

    In this paper, the design and evaluation of decision support systems, including those incorporating a telematic component, are considered. It is argued that effective design and evaluation are dependent upon the adoption of appropriate methodology set firmly within a systemic framework. Systems modeling is proposed as an approach to system design, with evaluation adopting an approach incorporating evaluability analysis and formative and summative evaluation, including the use of stakeholder matrix analysis. The relevance of such systemic methodology is demonstrated in the context of diabetes and end-stage renal disease as examples of the generic clinical problem of the management of chronic disease. PMID:10719517

  3. 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.

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

    PubMed

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

    2007-01-01

    Management implies decision-making and economics deals with efficiency which means to obtain the best possible results with the available resources, and to compare such results with those that were foreseen. The economic evaluation comprises a set of techniques aimed at comparing resource allocation on alternate courses of action and its consequences. In health care, these results are the overall well-being of the society. This paper summarizes the techniques that are customarily used in economic evaluation, and intends to serve as an introductory text to increasing the ability of the readers to grasp original articles in the field of health economics. PMID:17692169

  5. Clinical decision support must be useful, functional is not enough: a qualitative study of computer-based clinical decision support in primary care

    PubMed Central

    2012-01-01

    Background Health information technology, particularly electronic decision support systems, can reduce the existing gap between evidence-based knowledge and health care practice but professionals have to accept and use this information. Evidence is scant on which features influence the use of computer-based clinical decision support (eCDS) in primary care and how different professional groups experience it. Our aim was to describe specific reasons for using or not using eCDS among primary care professionals. Methods The setting was a Finnish primary health care organization with 48 professionals receiving patient-specific guidance at the point of care. Multiple data (focus groups, questionnaire and spontaneous feedback) were analyzed using deductive content analysis and descriptive statistics. Results The content of the guidance is a significant feature of the primary care professional’s intention to use eCDS. The decisive reason for using or not using the eCDS is its perceived usefulness. Functional characteristics such as speed and ease of use are important but alone these are not enough. Specific information technology, professional, patient and environment features can help or hinder the use. Conclusions Primary care professionals have to perceive eCDS guidance useful for their work before they use it. PMID:23039113

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

    ERIC Educational Resources Information Center

    Wilpert, B.; And Others

    1976-01-01

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

  7. Influence of Patients’ Socioeconomic Status on Clinical Management Decisions: A Qualitative Study

    PubMed Central

    Bernheim, Susannah M.; Ross, Joseph S.; Krumholz, Harlan M.; Bradley, Elizabeth H.

    2008-01-01

    PURPOSE Little is known about how patients’ socioeconomic status (SES) influences physicians’ clinical management decisions, although this information may have important implications for understanding inequities in health care quality. We investigated physician perspectives on how patients’ SES influences care. METHODS The study consisted of in-depth semistructured interviews with primary care physicians in Connecticut. Investigators coded interviews line by line and refined the coding structure and interview guide based on successive interviews. Recurrent themes emerged through iterative analysis of codes and tagged quotations. RESULTS We interviewed 18 physicians from varied practice settings, 6 female, 9 from minority racial backgrounds, and 3 of Hispanic ethnicity. Four themes emerged from our interviews: (1) physicians held conflicting views about the effect of patient SES on clinical management, (2) physicians believed that changes in clinical management based on the patient’s SES were made in the patient’s interest, (3) physicians varied in the degree to which they thought changes in clinical management influenced patient outcomes, and (4) physicians faced personal and financial strains when caring for patients of low SES. CONCLUSIONS Physicians indicated that patient SES did affect their clinical management decisions. As a result, physicians commonly undertook changes to their management plan in an effort to enhance patient outcomes, but they experienced numerous strains when trying to balance what they believed was feasible for the patient with what they perceived as established standards of care. PMID:18195315

  8. Clinical Decision Support for Early Recognition of Sepsis

    PubMed Central

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

    2014-01-01

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

  9. 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.

  10. 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

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

    PubMed Central

    2014-01-01

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

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

    PubMed Central

    Straus, Sharon E.

    2008-01-01

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

  13. 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.

  14. 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

  15. 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. PMID:24696645

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

    PubMed

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

    2016-03-01

    A clinical decision support system (CDSS) is a computer program, which is designed to assist health care professionals with decision making tasks. A well-developed CDSS weighs the benefits of therapy versus the cost in terms of loss of quality of life and financial loss and recommends the decision that can be expected to provide maximum overall benefit. This article provides an introduction to developing CDSSs using Bayesian networks, such CDSS can help with the often complex decisions involving transplants. First, we review Bayes theorem in the context of medical decision making. Then, we introduce Bayesian networks, which can model probabilistic relationships among many related variables and are based on Bayes theorem. Next, we discuss influence diagrams, which are Bayesian networks augmented with decision and value nodes and which can be used to develop CDSSs that are able to recommend decisions that maximize the expected utility of the predicted outcomes to the patient. By way of comparison, we examine the benefit and challenges of using the Kidney Donor Risk Index as the sole decision tool. Finally, we develop a schema for an influence diagram that models generalized kidney transplant decisions and show how the influence diagram approach can provide the clinician and the potential transplant recipient with a valuable decision support tool. PMID:26900809

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

    PubMed

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

    2013-09-01

    For a test to be considered useful for making treatment decisions, it is necessary that making treatment decisions based on the results of the test be a preferable strategy to making treatment decisions without the test. Decision curve analysis is a framework for assessing when a test would be expected to be useful, which integrates evidence of a test's performance characteristics (sensitivity and specificity), condition prevalence among at-risk patients, and patient preferences for treatment. We describe decision curve analysis generally and illustrate its potential through an application to tests for prodromal psychosis. Clinical psychosis is often preceded by a prodromal phase, but not all those with prodromal symptoms proceed to develop full psychosis. Patients identified as at risk for developing psychosis may be considered for proactive treatment to mitigate development of clinically defined psychosis. Tests exist to help identify those at-risk patients most likely to develop psychosis, but it is uncertain when these tests would be considered useful for making proactive treatment decisions. We apply decision curve analysis to results from a systematic review of studies investigating clinical tests for predicting the development of psychosis in at-risk populations, and present resulting decision curves that illustrate when the tests may be expected to be useful for making proactive treatment decisions. PMID:23544398

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

    PubMed

    Wright, Adam; Sittig, Dean F

    2008-12-01

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

  20. 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...

  1. 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

  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. 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

  4. Sequential decision analysis for nonstationary stochastic processes

    NASA Technical Reports Server (NTRS)

    Schaefer, B.

    1974-01-01

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

  5. 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

  6. 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

  7. 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.

  8. 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 ...

  9. Clinical decision rules for acute bacterial meningitis: current insights

    PubMed Central

    Viallon, Alain; Botelho-Nevers, Elisabeth; Zeni, Fabrice

    2016-01-01

    Acute community-acquired bacterial meningitis (BM) requires rapid diagnosis so that suitable treatment can be instituted within 60 minutes of admitting the patient. The cornerstone of diagnostic examination is lumbar puncture, which enables microbiological analysis and determination of the cerebrospinal fluid (CSF) cytochemical characteristics. However, microbiological testing is not sufficiently sensitive to rule out this diagnosis. With regard to the analysis of standard CSF cytochemical characteristics (polymorphonuclear count, CSF glucose and protein concentration, and CSF:serum glucose), this is often misleading. Indeed, the relatively imprecise nature of the cutoff values for these BM diagnosis markers can make their interpretation difficult. However, there are two markers that appear to be more efficient than the standard ones: CSF lactate and serum procalcitonin levels. Scores and predictive models are also available; however, they only define a clinical probability, and in addition, their use calls for prior validation on the population in which they are used. In this article, we review current methods of BM diagnosis. PMID:27307768

  10. Transient ischaemic attack clinic: an evaluation of diagnoses and clinical decision making.

    PubMed

    Lee, Will; Frayne, Judith

    2015-04-01

    The diagnosis of transient ischaemic attack (TIA) is based largely on the patient's symptom recall and clinical judgement. This decision-making process is highly subjective and the inter-observer reliability of TIA diagnosis is at best moderate, even among neurologists. The aim of this study is to examine the presenting features and final diagnoses of referrals to a TIA clinic and to evaluate characteristics that favoured the diagnosis of TIA over other TIA "mimics". Consecutive new referrals to a tertiary metropolitan hospital TIA clinic over a 9month period were examined. Characteristics between TIA and non-TIA diagnoses were compared and analysed. Eighty-two patients were recruited. Eighteen (22%) were given a final diagnosis of TIA or stroke. Major alternative diagnoses included migraine (n=17, 21%), presyncope/syncope (n=13, 16%) and anxiety (n=7, 9%). Four (5%) patients had unclassifiable symptoms with no clear final diagnosis. Mean age was 67±a standard deviation of 17years and patients diagnosed with TIA/stroke were on average older than those with non-TIA diagnoses (77±10 versus 64±17years, p=0.003). A diagnosis of TIA/stroke was favoured in the presence of moderate to severe weakness (p=0.032), dysphasia (p=0.037) or dysarthria (p=0.005). Unclassifiable symptoms (for example, palpitations, confusion, headache) were reported in 27 patients (33%) and their presence favoured non-TIA diagnoses (p=0.0003). TIA constituted a minority of the referrals to our clinic. Accurate clinical diagnosis of TIA facilitates early stroke prevention and avoids unnecessary investigations and prescriptions. Attempts to improve diagnostic accuracy of TIA should target improving the education and awareness of frontline medical practitioners. PMID:25669115

  11. 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

  12. 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

  13. Clinician Perspectives on the Quality of Patient Data Used for Clinical Decision Support: A Qualitative Study

    PubMed Central

    McCormack, James L.; Ash, Joan S.

    2012-01-01

    Objective: Clinical decision support (CDS), defined broadly as patient-specific information and knowledge provided at the point of care, depends on a foundation of high quality electronic patient data. Little is known about how clinicians perceive the quality and value of data used to support CDS within an electronic health record (EHR) environment. Methods: During a three-year research study, we collected ethnographic data from ten diverse organizations, including community hospitals, academic medical centers and ambulatory clinics. Results: An in-depth analysis of the theme “data as a foundation for CDS” yielded a descriptive framework incorporating five subthemes related to data quality: completeness, accessibility, context specificity, accuracy, and reliability. Conclusion: We identified several multi-dimensional models that might be used to conceptualize data quality characteristics for future research. These results could provide new insights to system designers and implementers on the importance clinicians place on specific data quality characteristics regarding electronic patient data for CDS. PMID:23304409

  14. 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

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

    PubMed Central

    Pfadt, A; Wheeler, D J

    1995-01-01

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

  16. 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

  17. Clinical capital equipment acquisition: decision-making at the executive level.

    PubMed

    Greisler, D S; Stupak, R J

    1999-01-01

    Capital investment in the United States health care industry is one of the components of the system that has historically fueled cost increases and complicated the quality/cost/access conundrum. This article is concerned with capital development focused on clinical equipment acquisition in acute care hospitals. The research findings suggest that decision-makers are abandoning two approaches to decision-making known as Quantitative Decision-Making and Mixed Scanning in favor of two models known as Rational Decision-Making and Political Decision-Making. While this is the case, a method of decision-making known as Idea Sets (developed and labeled by James March as Garbage Can Decision-Making) is the most widely used approach. Equipment acquisition criteria used by the decision-makers are shifting away from concerns of enhancing existing clinical programs and/or adding new clinical programs. Acquisition criteria are shifting toward procuring equipment which will decrease institutional expense, improve organizational efficiency, and galvanize operational effectiveness. In addition to the technical findings of the research, further insights about ourselves and our colleagues are gleaned. Accordingly, we understand more completely the human dynamics surrounding decisions and thus are able to dialogue more richly about issues. Meaningful dialogue such as this will have the dual benefit of advancing teamwork and facilitating decision-making. PMID:10848195

  18. 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

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

    PubMed

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

    2016-01-01

    Uveal melanoma management is challenging due to its metastatic propensity. DecisionDx-UM is a prospectively validated molecular test that interrogates primary tumor biology to provide objective information about metastatic potential that can be used in determining appropriate patient care. To evaluate the continued clinical validity and utility of DecisionDx-UM, beginning March 2010, 70 patients were enrolled in a prospective, multicenter, IRB-approved study to document patient management differences and clinical outcomes associated with low-risk Class 1 and high-risk Class 2 results indicated by DecisionDx-UM testing. Thirty-seven patients in the prospective study were Class 1 and 33 were Class 2. Class 1 patients had 100% 3-year metastasis-free survival compared to 63% for Class 2 (log rank test p = 0.003) with 27.3 median follow-up months in this interim analysis. Class 2 patients received significantly higher-intensity monitoring and more oncology/clinical trial referrals compared to Class 1 patients (Fisher's exact test p = 2.1 × 10(-13) and p = 0.04, resp.). The results of this study provide additional, prospective evidence in an independent cohort of patients that Class 1 and Class 2 patients are managed according to the differential metastatic risk indicated by DecisionDx-UM. The trial is registered with Clinical Application of DecisionDx-UM Gene Expression Assay Results (NCT02376920). PMID:27446211

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

    PubMed Central

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

    2016-01-01

    To provide personalized medicine, we not only must determine the treatments and other decisions most likely to be effective for a patient, but also consider the patient’s tradeoff between possible benefits of therapy versus possible loss of quality of life. There are numerous studies indicating that various treatments can negatively affect quality of life. Even if we have all information available for a given patient, it is an arduous task to amass the information to reach a decision that maximizes the utility of the decision to the patient. A clinical decision support system (CDSS) is a computer program, which is designed to assist healthcare professionals with decision making tasks. By utilizing emerging large datasets, we hold promise for developing CDSSs that can predict how treatments and other decisions can affect outcomes. However, we need to go beyond that; namely our CDSS needs to account for the extent to which these decisions can affect quality of life. This manuscript provides an introduction to developing CDSSs using Bayesian networks and influence diagrams. Such CDSSs are able to recommend decisions that maximize the expected utility of the predicted outcomes to the patient. By way of comparison, we examine the benefit and challenges of the Kidney Donor Risk Index (KDRI) as a decision support tool, and we discuss several difficulties with this index. Most importantly, the KDRI does not provide a measure of the expected quality of life if the kidney is accepted versus the expected quality of life if the patient stays on dialysis. Finally, we develop a schema for an influence diagram that models the kidney transplant decision, and show how the influence diagram approach can resolve these difficulties and provide the clinician and the potential transplant recipient with a valuable decision support tool. PMID:26900809

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

    ERIC Educational Resources Information Center

    Jeffrey, Aaron

    2012-01-01

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

  2. Translating shared decision-making into health care clinical practices: Proof of concepts

    PubMed Central

    Légaré, France; Elwyn, Glyn; Fishbein, Martin; Frémont, Pierre; Frosch, Dominick; Gagnon, Marie-Pierre; Kenny, David A; Labrecque, Michel; Stacey, Dawn; St-Jacques, Sylvie; van der Weijden, Trudy

    2008-01-01

    Background There is considerable interest today in shared decision-making (SDM), defined as a decision-making process jointly shared by patients and their health care provider. However, the data show that SDM has not been broadly adopted yet. Consequently, the main goal of this proposal is to bring together the resources and the expertise needed to develop an interdisciplinary and international research team on the implementation of SDM in clinical practice using a theory-based dyadic perspective. Methods Participants include researchers from Canada, US, UK, and Netherlands, representing medicine, nursing, psychology, community health and epidemiology. In order to develop a collaborative research network that takes advantage of the expertise of the team members, the following research activities are planned: 1) establish networking and on-going communication through internet-based forum, conference calls, and a bi-weekly e-bulletin; 2) hold a two-day workshop with two key experts (one in theoretical underpinnings of behavioral change, and a second in dyadic data analysis), and invite all investigators to present their views on the challenges related to the implementation of SDM in clinical practices; 3) conduct a secondary analyses of existing dyadic datasets to ensure that discussion among team members is grounded in empirical data; 4) build capacity with involvement of graduate students in the workshop and online forum; and 5) elaborate a position paper and an international multi-site study protocol. Discussion This study protocol aims to inform researchers, educators, and clinicians interested in improving their understanding of effective strategies to implement shared decision-making in clinical practice using a theory-based dyadic perspective. PMID:18194521

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

    PubMed

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

    2016-03-01

    Clinical decision support system, which uses advanced data mining techniques to help clinician make proper decisions, has received considerable attention recently. The advantages of clinical decision support system include not only improving diagnosis accuracy but also reducing diagnosis time. Specifically, with large amounts of clinical data generated everyday, naïve Bayesian classification can be utilized to excavate valuable information to improve a clinical decision support system. Although the clinical decision support system is quite promising, the flourish of the system still faces many challenges including information security and privacy concerns. In this paper, we propose a new privacy-preserving patient-centric clinical decision support system, which helps clinician complementary to diagnose the risk of patients' disease in a privacy-preserving way. In the proposed system, the past patients' historical data are stored in cloud and can be used to train the naïve Bayesian classifier without leaking any individual patient medical data, and then the trained classifier can be applied to compute the disease risk for new coming patients and also allow these patients to retrieve the top- k disease names according to their own preferences. Specifically, to protect the privacy of past patients' historical data, a new cryptographic tool called additive homomorphic proxy aggregation scheme is designed. Moreover, to leverage the leakage of naïve Bayesian classifier, we introduce a privacy-preserving top- k disease names retrieval protocol in our system. Detailed privacy analysis ensures that patient's information is private and will not be leaked out during the disease diagnosis phase. In addition, performance evaluation via extensive simulations also demonstrates that our system can efficiently calculate patient's disease risk with high accuracy in a privacy-preserving way. PMID:26960216

  4. 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.

  5. 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...

  6. 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

  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. [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. PMID:19852208

  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. 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

  13. 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

  14. Decisions in complex clinical situations: Prevalence and factors associated in general public.

    PubMed

    Gomez-Martinez, Maria D; Luna, Aurelio; Perez-Carceles, Maria D

    2016-01-01

    Many studies have focused on advanced directives. However, the type of treatment that citizens would choose in critical health situations and whether their decision varies with their sociodemographic characteristics and their experiences of life both within and outside the family context, are unknown. This study analyzes the factors associated with choosing or refusing life support treatment in hypothetical situations of differing clinical complexity. This transversal descriptive study was carried out by questionnaires given to 1051 participants from primary care centres. The Life Support Preferences Questionnaire (LSPQ) used to assess preferences of life-sustaining treatment, describes six scenarios with different prognoses. Analysis of the sociodemographic characteristics and life experiences of the subjects led to the following findings. In situations of very severe prognosis, treatment is mostly rejected. When there is chance of recovery, treatment is mostly accepted, especially in the least aggressive cases and when deciding for another person. A greater propensity to reject treatment was observed among subjects over 55 years, those in poor health and those who had observed a terminal illness in a family member. Practising Catholics are more likely to accept treatment in all medical situations described. Preferences for life support treatment are linked to sociodemographic characteristics and life experiences of patients. Physicians should bear in mind these characteristics when confronted with critical clinical situations, involving difficult decisions. PMID:26952384

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

    PubMed Central

    Waran, Eswaran; William, Leeroy

    2016-01-01

    Severe dementia is a life-limiting condition; hip fractures are more common in patients who have dementia. This study outlines the case of a 92-year-old female with severe dementia who sustained a hip fracture. Despite having a terminal diagnosis (severe dementia and hip fracture) and poor premorbid quality of life, she had a life-prolonging surgery. The report outlines issues around treatment options in such circumstances, informed consent and substitute decision-making. The authors propose a ‘goals of care’ approach to manage patients in whom the best treatment is unclear, during their attendance to the emergency department. It is suggested that utilization of such a model may help with substitute decision-making and true informed consent. PMID:26949537

  16. 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

  17. Clinical Analysis and Interpretation of Cancer Genome Data

    PubMed Central

    Van Allen, Eliezer M.; Wagle, Nikhil; Levy, Mia A.

    2013-01-01

    The scale of tumor genomic profiling is rapidly outpacing human cognitive capacity to make clinical decisions without the aid of tools. New frameworks are needed to help researchers and clinicians process the information emerging from the explosive growth in both the number of tumor genetic variants routinely tested and the respective knowledge to interpret their clinical significance. We review the current state, limitations, and future trends in methods to support the clinical analysis and interpretation of cancer genomes. This includes the processes of genome-scale variant identification, including tools for sequence alignment, tumor–germline comparison, and molecular annotation of variants. The process of clinical interpretation of tumor variants includes classification of the effect of the variant, reporting the results to clinicians, and enabling the clinician to make a clinical decision based on the genomic information integrated with other clinical features. We describe existing knowledge bases, databases, algorithms, and tools for identification and visualization of tumor variants and their actionable subsets. With the decreasing cost of tumor gene mutation testing and the increasing number of actionable therapeutics, we expect the methods for analysis and interpretation of cancer genomes to continue to evolve to meet the needs of patient-centered clinical decision making. The science of computational cancer medicine is still in its infancy; however, there is a clear need to continue the development of knowledge bases, best practices, tools, and validation experiments for successful clinical implementation in oncology. PMID:23589549

  18. Significant Labor Decisions--An Analysis

    ERIC Educational Resources Information Center

    Polhemus, Graig E.

    1977-01-01

    Major labor cases decided during 1976 did not project a clear or simple path for further Constitutional and statutory interpretation, but the year's labor decisions did reveal a new willingness on the part of the U.S. Supreme Court to depart from earlier views of Constitutional law. (JT)

  19. Using decision analysis techniques to deal with "unanswerable" questions in idiopathic thrombocytopenic purpura.

    PubMed

    Klaassen, Robert

    2003-12-01

    Idiopathic thrombocytopenic purpura (ITP) is a common disorder with rare adverse outcomes. This makes it a particularly difficult area in which to undertake conventional studies. An alternative method for solving clinical questions is decision analysis, which is in essence a computer-assisted synthesis of the literature. Using the example of a newly diagnosed ITP patient, the author attempts to answer the question of whether a bone marrow aspirate (BMA) is required prior to starting steroids. Using decision analysis methodology, the author determines that BMA is not essential prior to starting steroids. More importantly, three variables critical to the decision-making process are determined: the risk of death from the BMA procedure, the altered chance of survival for a patient with acute lymphoblastic leukemia (ALL) inappropriately given steroids, and how sensitive the complete blood count is at determining the risk of ALL. This scenario demonstrates the value of decision analysis and lays the groundwork for future endeavors. PMID:14668643

  20. Aneurysmal subarachnoid hemorrhage prognostic decision-making algorithm using classification and regression tree analysis

    PubMed Central

    Lo, Benjamin W. Y.; Fukuda, Hitoshi; Angle, Mark; Teitelbaum, Jeanne; Macdonald, R. Loch; Farrokhyar, Forough; Thabane, Lehana; Levine, Mitchell A. H.

    2016-01-01

    Background: Classification and regression tree analysis involves the creation of a decision tree by recursive partitioning of a dataset into more homogeneous subgroups. Thus far, there is scarce literature on using this technique to create clinical prediction tools for aneurysmal subarachnoid hemorrhage (SAH). Methods: The classification and regression tree analysis technique was applied to the multicenter Tirilazad database (3551 patients) in order to create the decision-making algorithm. In order to elucidate prognostic subgroups in aneurysmal SAH, neurologic, systemic, and demographic factors were taken into account. The dependent variable used for analysis was the dichotomized Glasgow Outcome Score at 3 months. Results: Classification and regression tree analysis revealed seven prognostic subgroups. Neurological grade, occurrence of post-admission stroke, occurrence of post-admission fever, and age represented the explanatory nodes of this decision tree. Split sample validation revealed classification accuracy of 79% for the training dataset and 77% for the testing dataset. In addition, the occurrence of fever at 1-week post-aneurysmal SAH is associated with increased odds of post-admission stroke (odds ratio: 1.83, 95% confidence interval: 1.56–2.45, P < 0.01). Conclusions: A clinically useful classification tree was generated, which serves as a prediction tool to guide bedside prognostication and clinical treatment decision making. This prognostic decision-making algorithm also shed light on the complex interactions between a number of risk factors in determining outcome after aneurysmal SAH. PMID:27512607

  1. HUMAN HEALTH METRICS FOR ENVIRONMENTAL DECISION SUPPORT TOOLS: LESSONS FROM HEALTH ECONOMICS AND DECISION ANALYSIS: PUBLISHED REPORT

    EPA Science Inventory

    NRMRL-CIN-1351A Hofstetter**, P., and Hammitt, J. K. Human Health Metrics for Environmental Decision Support Tools: Lessons from Health Economics and Decision Analysis. EPA/600/R-01/104 (NTIS PB2002-102119). Decision makers using environmental decision support tools are often ...

  2. 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.

  3. 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…

  4. 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…

  5. 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…

  6. Decision Theoretic Analysis of Improving Epidemic Detection

    PubMed Central

    Izadi, Masoumeh T.; Buckeridge, David L.

    2007-01-01

    The potentially catastrophic impact of an epidemic specially those due to bioterrorist attack, makes developing effective detection methods essential for public health. Current detection methods trade off reliability of alarms for early detection of outbreaks. The performance of these methods can be improved by disease-specific modeling techniques that take into account the potential costs and effects of an attack to provide optimal warnings and the cost and effectiveness of interventions. We study this optimization problem in the framework of sequential decision making under uncertainty. Our approach relies on estimating the future benefit of true alarms and the costs of false alarms. Using these quantities it identifies optimal decisions regarding the credibility of outputs from a traditional detection method at each point in time. The key contribution of this paper is to apply Partially Observable Markov Decision Processes (POMDPs) on outbreak detection methods for improving alarm function in the case of anthrax. We present empirical evidence illustrating that at a fixed specificity, the performance of detection methods with respect to sensitivity and timeliness is improved significantly by utilizing POMDPs in detection of anthrax attacks. PMID:18693857

  7. 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

  8. 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…

  9. 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...

  10. 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

  11. Statistics for critical clinical decision making based on readings of pairs of implanted sensors.

    PubMed

    Schmidtke, D W; Pishko, M V; Quinn, C P; Heller, A

    1996-09-01

    Low error rates are essential if lives of patients are to depend on readings of implanted sensors, such as glucose sensors in insulin-dependent diabetic patients. To verify the operation and to calibrate on demand an implanted sensor, it is necessary that calibration through a single, independent measurement involving withdrawal of only one sample of blood and its independent analysis be feasible. Such a one-point calibration must be accurate. Borrowing from nuclear reactor safety assurance, where a likelihood ratio test is applied to readings of pairs of pressure sensors for shutdown/no shutdown decisions, we apply a similar test to sensor pairs implanted in rats. We show, for five sets of glucose sensor pairs, calibrated in vivo by withdrawal of a single sample of blood, that application of the likelihood ratio test increases the fraction of the clinically correct readings from 92.4% for their averaged readings to 98.8%. PMID:8794921

  12. Recurrent Neural Networks in Computer-Based Clinical Decision Support for Laryngopathies: An Experimental Study

    PubMed Central

    Szkoła, Jarosław; Pancerz, Krzysztof; Warchoł, Jan

    2011-01-01

    The main goal of this paper is to give the basis for creating a computer-based clinical decision support (CDS) system for laryngopathies. One of approaches which can be used in the proposed CDS is based on the speech signal analysis using recurrent neural networks (RNNs). RNNs can be used for pattern recognition in time series data due to their ability of memorizing some information from the past. The Elman networks (ENs) are a classical representative of RNNs. To improve learning ability of ENs, we may modify and combine them with another kind of RNNs, namely, with the Jordan networks. The modified Elman-Jordan networks (EJNs) manifest a faster and more exact achievement of the target pattern. Validation experiments were carried out on speech signals of patients from the control group and with two kinds of laryngopathies. PMID:22007195

  13. 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. PMID:23304342

  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. Using multiple criteria decision analysis for supporting decisions of solid waste management.

    PubMed

    Cheng, Steven; Chan, Christine W; Huang, Guo H

    2002-01-01

    Design of solid-waste management systems requires consideration of multiple alternative solutions and evaluation criteria because the systems can have complex and conflicting impacts on different stakeholders. Multiple criteria decision analysis (MCDA) has been found to be a fruitful approach to solve this design problem. In this paper, the MCDA approach is applied to solve the landfill selection problem in Regina of Saskatchewan Canada. The systematic approach of MCDA helps decision makers select the most preferable decision and provides the basis of a decision support system. The techniques that are used in this study include: 1) Simple Weighted Addition method, 2) Weighted Product method, 3) TOPSIS, 4) cooperative game theory, and 5) ELECTRE. The results generated with these methods are compared and ranked so that the most preferable solution is identified. PMID:12090287

  16. Exploring use of images in clinical articles for decision support in evidence-based medicine

    NASA Astrophysics Data System (ADS)

    Antani, Sameer; Demner-Fushman, Dina; Li, Jiang; Srinivasan, Balaji V.; Thoma, George R.

    2008-01-01

    Essential information is often conveyed pictorially (images, illustrations, graphs, charts, etc.) in biomedical publications. A clinician's decision to access the full text when searching for evidence in support of clinical decision is frequently based solely on a short bibliographic reference. We seek to automatically augment these references with images from the article that may assist in finding evidence. In a previous study, the feasibility of automatically classifying images by usefulness (utility) in finding evidence was explored using supervised machine learning and achieved 84.3% accuracy using image captions for modality and 76.6% accuracy combining captions and image data for utility on 743 images from articles over 2 years from a clinical journal. Our results indicated that automatic augmentation of bibliographic references with relevant images was feasible. Other research in this area has determined improved user experience by showing images in addition to the short bibliographic reference. Multi-panel images used in our study had to be manually pre-processed for image analysis, however. Additionally, all image-text on figures was ignored. In this article, we report on developed methods for automatic multi-panel image segmentation using not only image features, but also clues from text analysis applied to figure captions. In initial experiments on 516 figure images we obtained 95.54% accuracy in correctly identifying and segmenting the sub-images. The errors were flagged as disagreements with automatic parsing of figure caption text allowing for supervised segmentation. For localizing text and symbols, on a randomly selected test set of 100 single panel images our methods reported, on the average, precision and recall of 78.42% and 89.38%, respectively, with an accuracy of 72.02%.

  17. Evaluating the use of a computerized clinical decision support system for asthma by pediatric pulmonologists

    PubMed Central

    Lomotan, Edwin A.; Hoeksema, Laura J.; Edmonds, Diana E.; Ramírez-Garnica, Gabriela; Shiffman, Richard N.; Horwitz, Leora I.

    2012-01-01

    Purpose To investigate use of a new guideline-based, computerized clinical decision support (CCDS) system for asthma in a pediatric pulmonology clinic of a large academic medical center. Methods We conducted a qualitative evaluation including review of electronic data, direct observation, and interviews with all nine pediatric pulmonologists in the clinic. Outcome measures included patterns of computer use in relation to patient care, and themes surrounding the relationship between asthma care and computer use. Results The pediatric pulmonologists entered enough data to trigger the decision support system in 397/445 (89.2%) of all asthma visits from January 2009 to May 2009. However, interviews and direct observations revealed use of the decision support system was limited to documentation activities after clinic sessions ended. Reasons for delayed use reflected barriers common to general medical care and barriers specific to subspecialty care. Subspecialist-specific barriers included the perceived high complexity of patients, the impact of subject matter expertise on the types of decision support needed, and unique workflow concerns such as the need to create letters to referring physicians. Conclusions Pediatric pulmonologists demonstrated low use of a computerized decision support system for asthma care because of a combination of general and subspecialist-specific factors. Subspecialist-specific factors should not be underestimated when designing guideline-based, computerized decision support systems for the subspecialty setting. PMID:22204897

  18. Managing risk: clinical decision-making in mental health services.

    PubMed

    Muir-Cochrane, Eimear; Gerace, Adam; Mosel, Krista; O'Kane, Debra; Barkway, Patricia; Curren, David; Oster, Candice

    2011-01-01

    Risk assessment and management is a major component of contemporary mental health practice. Risk assessment in health care exists within contemporary perspectives of management and risk aversive practices in health care. This has led to much discussion about the best approach to assessing possible risks posed by people with mental health problems. In addition, researchers and commentators have expressed concern that clinical practice is being dominated by managerial models of risk management at the expense of meeting the patient's health and social care needs. The purpose of the present study is to investigate the risk assessment practices of a multidisciplinary mental health service. Findings indicate that mental health professionals draw on both managerial and therapeutic approaches to risk management, integrating these approaches into their clinical practice. Rather than being dominated by managerial concerns regarding risk, the participants demonstrate professional autonomy and concern for the needs of their clients. PMID:22077745

  19. 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. PMID:26436538

  20. Characterizing the Access of Clinical Decision Support Offered by Immunization Information System in Minnesota

    PubMed Central

    Rajamani, Sripriya; Bieringer, Aaron; Muscoplat, Miriam

    2015-01-01

    Background: Healthy People 2020 aims to improve population health by increasing immunization rates to decrease vaccine-preventable infectious diseases. Amongst the many strategies, role of immunization information systems (IIS) are recognized by studies and taskforce reports. IIS are unique in their offering of clinical decision support for immunizations (CDSi) which are utilized by healthcare providers. Federal initiatives such as Meaningful Use (MU) and Affordable Care Act (ACA) aim to improve immunization rates through use of technology and expanding access to immunization services respectively. MU, the Electronic Health Record (EHR) incentive program includes use of IIS CDSi functionality as part of Stage 3. It is essential to understand access and use patterns of IIS CDSi, so as to utilize it better to improve immunization services. Objectives: To understand the utilization of clinical decision support for immunizations (CDSi) offered by immunization information system in Minnesota and to analyze the variability of its use across providers and EHR implementations. Methods: IIS in Minnesota (Minnesota Immunization Information Connection: MIIC) offers CDSi that is accessed through EHRs and branded as Alternate Access (AA). Data from MIIC and technical documents were reviewed to create details on organizations which implemented AA functionality. Data on EHR adoption in clinics and local health departments was obtained from Minnesota eHealth assessment reports. Data on access were tracked from January 2015 through mid-October 2015 through weekly specialized reports to track the queries by organization, volume and day of the week. Data were analyzed, findings were synthesized and reviewed with subject matter experts. Results: Currently 25 healthcare systems/organizations which represent 599 individual provider sites have implemented the AA functionality. Analysis of their EHR platform pointed to two EHRs (Epic and PH-Doc) as dominant products in Minnesota for

  1. Clinical decision making in seizures and status epilepticus.

    PubMed

    Teran, Felipe; Harper-Kirksey, Katrina; Jagoda, Andy

    2015-01-01

    Seizures and status epilepticus are frequent neurologic emergencies in the emergency department, accounting for 1% of all emergency department visits. The management of this time-sensitive and potentially life-threatening condition is challenging for both prehospital providers and emergency clinicians. The approach to seizing patients begins with differentiating seizure activity from mimics and follows with identifying potential secondary etiologies, such as alcohol-related seizures. The approach to the patient in status epilepticus and the patient with nonconvulsive status epilepticus constitutes a special clinical challenge. This review summarizes the best available evidence and recommendations regarding diagnosis and resuscitation of the seizing patient in the emergency setting. PMID:25902572

  2. 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. PMID:17583166

  3. A study of the use of past experiences in clinical decision making in emergency situations.

    PubMed

    Cioffi, J

    2001-10-01

    Making decisions to call emergency assistance to patients is an important dimension of nursing practice. Most usually these decision making situations are uncertain and it is expected nurses rely on past clinical experiences. This study, approved by the ethics committees of both a university and an area health service, aimed to describe nurses' reliance on past experiences and identify associated judgement strategies (heuristics). Thirty-two registered nurses with five or more years experience were interviewed. Main findings were: nurses did use their past experiences and these experiences were used in the form of the three "classic" heuristics, representativeness, availability and anchoring and adjustment. It can be concluded past experiences are intrinsic to decision making and this has implications for both the clinical components of nursing educational programs and staffing allocations made by administrators. Some nurses, however, did not include referral to past experiences in their decision-making accounts which may be a limitation of the study design. PMID:11524105

  4. [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

  5. An Entropy Approach for Utility Assignment in Decision Analysis

    NASA Astrophysics Data System (ADS)

    Abbas, Ali E.

    2003-03-01

    A fundamental step in decision analysis is the elicitation of the decision-maker's preferences about the prospects of a decision situation in the form of utility values. However, this can be a difficult task to perform in practice as the number of prospects may be large, and eliciting a utility value for each prospect may be a time consuming and stressful task for the decision maker. To relieve some of the burden of this task, this paper presents a normative method to assign unbiased utility values when only incomplete preference information is available about the decision maker. We introduce the notion of a utility density function and propose a maximum entropy utility principle for utility assignment.

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

    PubMed

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

    2014-02-01

    Classic studies on social influence used simple perceptual decision-making tasks to examine how the opinions of others change individuals' judgments. Since then, one of the most fundamental questions in social psychology has been whether social influence can alter basic perceptual processes. To address this issue, we used a diffusion model analysis. Diffusion models provide a stochastic approach for separating the cognitive processes underlying speeded binary decisions. Following this approach, our study is the first to disentangle whether social influence on decision making is due to altering the uptake of available sensory information or due to shifting the decision criteria. In two experiments, we found consistent evidence for the idea that social influence alters the uptake of available sensory evidence. By contrast, participants did not adjust their decision criteria. PMID:24154917

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

    PubMed Central

    Lawrence, R E; Curlin, F A

    2010-01-01

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

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

    SciTech Connect

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

    2000-03-01

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

  9. Integrated risk assessment and feedback reporting for clinical decision making in a Medicare Risk plan.

    PubMed

    Schraeder, C; Britt, T; Shelton, P

    2000-10-01

    The challenge of tapping into the rich resource of population-based, aggregated data to inform and guide clinical processes remains one of the largely unrealized potentials of managed care. This article describes a multifaceted approach of using health-related data to support providers in clinical decision making as an adjunct to case management and primary care delivery. The goal is to provide data that can be used for clinical decision making that is population based, yet individualized for specific patient care situations. Information reporting holds great potential in the clinical care of patients because it can be used to identify persons who could benefit from early detection, intervention, or treatment. It has been suggested that one of the keys to success in managed Medicare is the timely use of information that is detailed, comprehensive, and real-time describing key parameters of clinical encounters. PMID:11067092

  10. Boosting standard order sets utilization through clinical decision support.

    PubMed

    Li, Haomin; Zhang, Yinsheng; Cheng, Haixia; Lu, Xudong; Duan, Huilong

    2013-01-01

    Well-designed standard order sets have the potential to integrate and coordinate care by communicating best practices through multiple disciplines, levels of care, and services. However, there are several challenges which certainly affected the benefits expected from standard order sets. To boost standard order sets utilization, a problem-oriented knowledge delivery solution was proposed in this study to facilitate access of standard order sets and evaluation of its treatment effect. In this solution, standard order sets were created along with diagnostic rule sets which can trigger a CDS-based reminder to help clinician quickly discovery hidden clinical problems and corresponding standard order sets during ordering. Those rule set also provide indicators for targeted evaluation of standard order sets during treatment. A prototype system was developed based on this solution and will be presented at Medinfo 2013. PMID:23920727

  11. Identifying ultrasound and clinical features of breast cancer molecular subtypes by ensemble decision.

    PubMed

    Zhang, Lei; Li, Jing; Xiao, Yun; Cui, Hao; Du, Guoqing; Wang, Ying; Li, Ziyao; Wu, Tong; Li, Xia; Tian, Jiawei

    2015-01-01

    Breast cancer is molecularly heterogeneous and categorized into four molecular subtypes: Luminal-A, Luminal-B, HER2-amplified and Triple-negative. In this study, we aimed to apply an ensemble decision approach to identify the ultrasound and clinical features related to the molecular subtypes. We collected ultrasound and clinical features from 1,000 breast cancer patients and performed immunohistochemistry on these samples. We used the ensemble decision approach to select unique features and to construct decision models. The decision model for Luminal-A subtype was constructed based on the presence of an echogenic halo and post-acoustic shadowing or indifference. The decision model for Luminal-B subtype was constructed based on the absence of an echogenic halo and vascularity. The decision model for HER2-amplified subtype was constructed based on the presence of post-acoustic enhancement, calcification, vascularity and advanced age. The model for Triple-negative subtype followed two rules. One was based on irregular shape, lobulate margin contour, the absence of calcification and hypovascularity, whereas the other was based on oval shape, hypovascularity and micro-lobulate margin contour. The accuracies of the models were 83.8%, 77.4%, 87.9% and 92.7%, respectively. We identified specific features of each molecular subtype and expanded the scope of ultrasound for making diagnoses using these decision models. PMID:26046791

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

    PubMed

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

    2014-01-01

    Evidence-based medical practice requires that clinical guidelines need to be documented in such a way that they represent a clinical workflow in its most accessible form. In order to optimize clinical processes to improve clinical outcomes, we propose a Service Oriented Architecture (SOA) based approach for implementing clinical guidelines that can be accessed from an Electronic Health Record (EHR) application with a Web Services enabled communication mechanism with the Enterprise Service Bus. We have used Business Process Modelling Notation (BPMN) for modelling and presenting the clinical pathway in the form of a workflow. The aim of this study is to produce spontaneous alerts in the healthcare workflow in the diagnosis of Chronic Obstructive Pulmonary Disease (COPD). The use of BPMN as a tool to automate clinical guidelines has not been previously employed for providing Clinical Decision Support (CDS). PMID:25160142

  13. 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

  14. 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.

  15. Integrating decision support, based on the Arden Syntax, in a clinical laboratory environment.

    PubMed Central

    Johansson, B.; Bergqvist, Y.

    1993-01-01

    A clinical decision support system prototype have been developed in the clinical laboratory environment. The knowledge base consists of Medical Logic Modules, written in the Arden Syntax, and the work describes how these modules can be written, evoked and executed in a system, that is integrated with a laboratory information system, and facilitate real time validation of laboratory data. Tools and methods for building a decision support system are described and design aspects, such as database access, system validation and platform independence, are discussed. PMID:8130502

  16. 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

  17. Rule-based analysis of pilot decisions

    NASA Technical Reports Server (NTRS)

    Lewis, C. M.

    1985-01-01

    The application of the rule identification technique to the analysis of human performance data is proposed. The relation between the language and identifiable consistencies is discussed. The advantages of production system models for the description of complex human behavior are studied. The use of a Monte Carlo significance testing procedure to assure the validity of the rule identification is examined. An example of the rule-based analysis of Palmer's (1983) data is presented.

  18. 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

  19. Operative Versus Nonoperative Treatment of Jones Fractures: A Decision Analysis Model.

    PubMed

    Bishop, Julius A; Braun, Hillary J; Hunt, Kenneth J

    2016-01-01

    Optimal management of metadiaphyseal fifth metatarsal fractures (Jones fractures) remains controversial. Decision analysis can optimize clinical decision-making based on available evidence and patient preferences. We conducted a study to establish the determinants of decision-making and to determine the optimal treatment strategy for Jones fractures using a decision analysis model. Probabilities for potential outcomes of operative and nonoperative treatment of Jones fractures were determined from a review of the literature. Patient preferences for outcomes were obtained by questionnaire completed by 32 healthy adults with no history of foot fracture. Derived values were used in the model as a measure of utility. A decision tree was constructed, and fold-back and sensitivity analyses were performed to determine optimal treatment. Nonoperative treatment was associated with a value of 7.74, and operative treatment with an intramedullary screw was associated with a value of 7.88 given the outcome probabilities and utilities studied, making operative treatment the optimal strategy. When parameters were varied, nonoperative treatment was favored when the likelihood of healing with nonoperative treatment rose above 82% and when the probability of healing after surgery fell below 92%. In this decision analysis model, operative fixation is the preferred management strategy for Jones fractures. PMID:26991586

  20. Telemonitoring in heart failure patients with clinical decision support to optimize medication doses based on guidelines.

    PubMed

    Kropf, Martin; Modre-Osprian, Robert; Hayn, Dieter; Fruhwald, Friedrich; Schreier, Günter

    2014-01-01

    The European Society of Cardiology guidelines for heart failure management are based on strong evidence that adherence to optimal medication is beneficial for heart failure patients. Telemonitoring with integrated clinical decision support enables physicians to adapt medication dose based on up to date vital parameters and reduces the number of hospital visits needed solely for up-titration of heart failure medication. Although keeping track of weight and blood pressure changes is recommended during unstable phases, e.g. post-discharge and during up-titration of medication, guidelines are rather vague regarding telehealth aspects. In this paper, we focus on the evaluation of a clinical decision support system for adaption of heart failure medication and for detecting early deteriorations through monitoring of blood pressure, heart rate and weight changes. This clinical decision support system is currently used in INTENSE-HF, a large scale telemonitoring trial with heart failure patients. The aim of this paper was to apply the decision support algorithm to an existing telemonitoring dataset, to assess the ability of the decision support concept to adhere to the guidelines and to discuss its limitations and potential improvements. PMID:25570663

  1. 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

  2. Decision analysis as a life support technology assessment capability.

    PubMed

    Ballin, M G

    1995-01-01

    Applied research and technology development is often characterized by uncertainty, risk, and significant delays before tangible returns are obtained. Decision making regarding which technologies to advance and what resources to devote to them is a challenging but essential task, especially in a resource-constrained environment. In the application of life support technology to future manned space flight, new technology concepts typically are characterized by rough approximations of technology performance, uncertain future flight program needs, and a complex, time-intensive process to develop technology to a flight-ready status. Decision analysis is a quantitative, logic-based discipline that imposes formalism and structure to complex problems confronting a decision maker. It also accounts for the limits of knowledge available at the time a decision is needed. The utility of decision analysis to life support technology R&D was evaluated by applying it to two case studies. The methodology was found to provide useful insight for making technology development resource allocation decisions. PMID:11538570

  3. 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)

  4. 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

  5. Closed-Loop Analysis of Soft Decisions for Serial Links

    NASA Technical Reports Server (NTRS)

    Lansdowne, Chatwin A.; Steele, Glen F.; Zucha, Joan P.; Schlesinger, Adam M.

    2013-01-01

    We describe the benefit of using closed-loop measurements for a radio receiver paired with a counterpart transmitter. We show that real-time analysis of the soft decision output of a receiver can provide rich and relevant insight far beyond the traditional hard-decision bit error rate (BER) test statistic. We describe a Soft Decision Analyzer (SDA) implementation for closed-loop measurements on single- or dual- (orthogonal) channel serial data communication links. The analyzer has been used to identify, quantify, and prioritize contributors to implementation loss in live-time during the development of software defined radios. This test technique gains importance as modern receivers are providing soft decision symbol synchronization as radio links are challenged to push more data and more protocol overhead through noisier channels, and software-defined radios (SDRs) use error-correction codes that approach Shannon's theoretical limit of performance.

  6. 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. PMID:23869557

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

    PubMed Central

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

    2016-01-01

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

  8. 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…

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

    PubMed

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

    2014-09-01

    This study evaluated second-, third-, and fourth-year dental students' ability to identify systemic conditions associated with periodontal disease, risk factors most important for referral, and medications with an effect on the periodontium and their ability to apply this knowledge to make clinical decisions regarding treatment and referral of periodontal patients. A twenty-one question survey was administered at one U.S. dental school in the spring semester of 2012 to elicit the students' knowledge and confidence regarding clinical reasoning. The response rate was 86 percent. Periodontal risk factors were accurately selected by at least 50 percent of students in all three classes; these were poorly controlled diabetes, ≥6 mm pockets posteriorly, and lack of response to previous non-surgical therapy. Confidence in knowledge, knowledge of risk factors, and knowledge of medications with an effect on the periodontium improved with training and were predictive of better referral decision making. The greatest impact of training was seen on the students' ability to make correct decisions about referral and treatment for seven clinical scenarios. Although the study found a large increase in the students' abilities from the second through fourth years, the mean of 4.6 (out of 7) for the fourth-year students shows that, on average, those students missed correct treatment or referral on more than two of seven clinical cases. These results suggest that dental curricula should emphasize more critical decision making with respect to referral and treatment criteria in managing the periodontal patient. PMID:25179920

  10. 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.…

  11. 78 FR 35937 - Food and Drug Administration Decisions for Investigational Device Exemption Clinical...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-06-14

    ... for Investigational Device Exemption (IDE) Clinical Investigations.'' This guidance document was... investigations to evaluate medical devices under FDA's IDE regulations. The guidance was also intended to provide... IDE and to provide a general explanation of the reasons for those decisions. This guidance has...

  12. Students' Stereotypes of Patients as Barriers to Clinical Decision-Making.

    ERIC Educational Resources Information Center

    Johnson, Shirley M.; And Others

    1986-01-01

    At the Michigan State University College of Osteopathic Medicine, a study was designed that graphically illustrated to beginning students that unconscious sociocultural stereotypes may influence clinical decision-making. Students were shown a videotape depicting five simulated patients, each with the same physical complaint. (Author/MLW)

  13. 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…

  14. The Impact of Reading a Clinical Study on Treatment Decisions of Physicians and Residents.

    ERIC Educational Resources Information Center

    Bergman, David A.; Pantell, Robert H.

    1986-01-01

    A study of the effect of reading a recent clinical study on pediatricians', pediatric residents', and family practitioners' decisions concerning treatment of a common, potentially serious problem revealed a considerable influence but physician difficulty in using probability data and reliance on intuition rather than calculation. (MSE)

  15. Transforming User Needs into Functional Requirements for an Antibiotic Clinical Decision Support System

    PubMed Central

    Bright, T.J.

    2013-01-01

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

  16. Decision analysis framework for evaluating CTBT seismic verification options

    SciTech Connect

    Judd, B.R.; Strait, R.S.; Younker, L.W.

    1986-09-01

    This report describes a decision analysis framework for evaluating seismic verification options for a Comprehensive Test Ban Treaty (CTBT). In addition to providing policy makers with insights into the relative merits of different options, the framework is intended to assist in formulating and evaluating political decisions - such as responses to evidence of violations - and in setting research priorities related to the options. To provide these broad analytical capabilities to decision makers, the framework incorporates a wide variety of issues. These include seismic monitoring capabilities, evasion possibilities, evidence produced by seismic systems, US response to the evidence, the dependence between US and Soviet decision-making, and the relative values of possible outcomes to the US and the Soviet Union. An added benefit of the framework is its potential use to improve communication about these CTBT verification issues among US experts and decision makers. The framework has been implemented on a portable microcomputer to facilitate this communication through demonstration and rapid evaluation of alternative judgments and policy choices. The report presents the framework and its application in four parts. The first part describes the decision analysis framework and the types of analytical results produced. In the second part, the framework is used to evaluate representative seismic verification options. The third part describes the results of sensitivity analyses that determine the relative importance of the uncertainties or subjective judgments that influence the evaluation of the options. The fourth (and final) part summaries conclusions and presents implications of the sample analytical results for further research and for policy-making related to CTBT verification. The fourth section also describes the next steps in the development and use of the decision analysis framework.

  17. Risk analysis in bioequivalence and biowaiver decisions.

    PubMed

    Kubbinga, Marlies; Langguth, Peter; Barends, Dirk

    2013-07-01

    This article evaluates the current biowaiver guidance documents published by the FDA, EU and WHO from a risk based perspective. The authors introduce the use of a Failure Mode and Effect Analysis (FMEA) risk calculation tool to show that current regulatory documents implicitly limit the risk for bioinequivalence after granting a biowaiver by reduction of the incidence, improving the detection and limiting the severity of any unforeseen bioinequivalent product. In addition, the authors use the risk calculation to expose yet unexplored options for future extension of comparative in vitro tools for biowaivers. PMID:23280474

  18. Placement Decisions and Disparities among Aboriginal Groups: An Application of the Decision Making Ecology through Multi-Level Analysis

    ERIC Educational Resources Information Center

    Fluke, John D.; Chabot, Martin; Fallon, Barbara; MacLaurin, Bruce; Blackstock, Cindy

    2010-01-01

    Objective: This paper examined the relative influence of clinical and organizational characteristics on the decision to place a child in out-of-home care at the conclusion of a child maltreatment investigation. It tested the hypothesis that extraneous factors, specifically, organizational characteristics, impact the decision to place a child in…

  19. 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.

  20. Bayesian imperfect information analysis for clinical recurrent data

    PubMed Central

    Chang, Chih-Kuang; Chang, Chi-Chang

    2015-01-01

    In medical research, clinical practice must often be undertaken with imperfect information from limited resources. This study applied Bayesian imperfect information-value analysis to realistic situations to produce likelihood functions and posterior distributions, to a clinical decision-making problem for recurrent events. In this study, three kinds of failure models are considered, and our methods illustrated with an analysis of imperfect information from a trial of immunotherapy in the treatment of chronic granulomatous disease. In addition, we present evidence toward a better understanding of the differing behaviors along with concomitant variables. Based on the results of simulations, the imperfect information value of the concomitant variables was evaluated and different realistic situations were compared to see which could yield more accurate results for medical decision-making. PMID:25565853

  1. Using real options analysis to support strategic management decisions

    NASA Astrophysics Data System (ADS)

    Kabaivanov, Stanimir; Markovska, Veneta; Milev, Mariyan

    2013-12-01

    Decision making is a complex process that requires taking into consideration multiple heterogeneous sources of uncertainty. Standard valuation and financial analysis techniques often fail to properly account for all these sources of risk as well as for all sources of additional flexibility. In this paper we explore applications of a modified binomial tree method for real options analysis (ROA) in an effort to improve decision making process. Usual cases of use of real options are analyzed with elaborate study on the applications and advantages that company management can derive from their application. A numeric results based on extending simple binomial tree approach for multiple sources of uncertainty are provided to demonstrate the improvement effects on management decisions.

  2. Hierarchical neural networks for autonomous data analysis and decision making

    NASA Technical Reports Server (NTRS)

    Eberlein, Susan; Yates, Gigi

    1988-01-01

    A neural network based data analysis and decision making system to increase the autonomy of a planetary rover or similar exploratory vehicle is presented. A hierarchical series of neural networks for real time analysis of scientific images is used. The system under development emphasizes analysis of multispectral images by classifier and feature detector neural networks, to provide information on the mineral composition of a scene. A hierarchy of alternating analysis and decision making networks is being developed to allow increasingly fine scale analysis in regions of the image that are potentially important. It is noted that this system will facilitate both the selection of high priorty scientific information for transmission to earth, and the autonomous collection of rocks and soil for sample return.

  3. 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. PMID:26262410

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

    PubMed

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

    2012-07-01

    One of the major concerns of research in integrated healthcare information systems is to enable decision support among clinicians across boundaries of organizations and regional workgroups. A necessary precursor, however, is to facilitate the construction of appropriate awareness of local clinical practices, including a clinician's actual cognitive capabilities, peculiar workplace circumstances, and specific patient-centered needs based on real-world clinical contexts across work settings. In this paper, a user-centered study aimed to investigate clinical practices across three different geographical areas-the U.K., the UAE and Nigeria-is presented. The findings indicate that differences in clinical practices among clinicians are associated with differences in local work contexts across work settings, but are moderated by adherence to best practice guidelines and the need for patient-centered care. The study further reveals that an awareness especially of the ontological, stereotypical, and situated practices plays a crucial role in adapting knowledge for cross-boundary decision support. The paper then outlines a set of design guidelines for the development of enterprise information systems for e-health. Based on the guidelines, the paper proposes the conceptual design of CaDHealth, a practice-centered framework for making sense of clinical practices across work settings for effective cross-boundary e-health decision support. PMID:22345549

  5. [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

  6. 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

  7. 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

  8. 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

  9. 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

  10. 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

  11. Annotated bibliography on decision analysis with applications to project management

    SciTech Connect

    Booker, J.M.; Bryson, M.C.

    1984-02-01

    The results of an extensive literature survey on decision analysis, with specific application to problems in research and development project management, are summarized in bibliographic form. Approximately 215 references are organized by subject matter and also summarized and annotated (several lines per reference) in a separate listing.

  12. 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…

  13. 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

  14. 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

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

    PubMed Central

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

    2014-01-01

    The risks associated with gestational diabetes (GD) can be reduced with an active treatment able to improve glycemic control. Advances in mobile health can provide new patient-centric models for GD to create personalized health care services, increase patient independence and improve patients’ self-management capabilities, and potentially improve their treatment compliance. In these models, decision-support functions play an essential role. The telemedicine system MobiGuide provides personalized medical decision support for GD patients that is based on computerized clinical guidelines and adapted to a mobile environment. The patient’s access to the system is supported by a smartphone-based application that enhances the efficiency and ease of use of the system. We formalized the GD guideline into a computer-interpretable guideline (CIG). We identified several workflows that provide decision-support functionalities to patients and 4 types of personalized advice to be delivered through a mobile application at home, which is a preliminary step to providing decision-support tools in a telemedicine system: (1) therapy, to help patients to comply with medical prescriptions; (2) monitoring, to help patients to comply with monitoring instructions; (3) clinical assessment, to inform patients about their health conditions; and (4) upcoming events, to deal with patients’ personal context or special events. The whole process to specify patient-oriented decision support functionalities ensures that it is based on the knowledge contained in the GD clinical guideline and thus follows evidence-based recommendations but at the same time is patient-oriented, which could enhance clinical outcomes and patients’ acceptance of the whole system. PMID:24876573

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

    PubMed

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

    2014-03-01

    The risks associated with gestational diabetes (GD) can be reduced with an active treatment able to improve glycemic control. Advances in mobile health can provide new patient-centric models for GD to create personalized health care services, increase patient independence and improve patients' self-management capabilities, and potentially improve their treatment compliance. In these models, decision-support functions play an essential role. The telemedicine system MobiGuide provides personalized medical decision support for GD patients that is based on computerized clinical guidelines and adapted to a mobile environment. The patient's access to the system is supported by a smartphone-based application that enhances the efficiency and ease of use of the system. We formalized the GD guideline into a computer-interpretable guideline (CIG). We identified several workflows that provide decision-support functionalities to patients and 4 types of personalized advice to be delivered through a mobile application at home, which is a preliminary step to providing decision-support tools in a telemedicine system: (1) therapy, to help patients to comply with medical prescriptions; (2) monitoring, to help patients to comply with monitoring instructions; (3) clinical assessment, to inform patients about their health conditions; and (4) upcoming events, to deal with patients' personal context or special events. The whole process to specify patient-oriented decision support functionalities ensures that it is based on the knowledge contained in the GD clinical guideline and thus follows evidence-based recommendations but at the same time is patient-oriented, which could enhance clinical outcomes and patients' acceptance of the whole system. PMID:24876573

  17. 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

  18. 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

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

    PubMed

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

    2014-01-01

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

  20. 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.

  1. 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.

  2. EULAR report on the use of ultrasonography in painful knee osteoarthritis. Part 2: Exploring decision rules for clinical utility

    PubMed Central

    Conaghan, P; D'Agostino, M; Ravaud, P; Baron, G; Le Bars, M; Grassi, W; Martin-Mola, E; Wakefield, R; Brasseur, J; So, A; Backhaus, M; Malaise, M; Burmester, G; Schmidely, N; Emery, P; Dougados, M

    2005-01-01

    Background: Synovial inflammation (as defined by hypertrophy and effusion) is common in osteoarthritis (OA) and may be important in both pain and structural progression. Objective: To determine if decision rules can be devised from clinical findings and ultrasonography (US) to allow recognition of synovial inflammation in patients with painful knee OA. Methods: A EULAR-ESCISIT cross sectional, multicentre study enrolled subjects with painful OA knee who had clinical, radiographic, and US evaluations. A classification and regression tree (CART) analysis was performed to find combinations of predictor variables that would provide high sensitivity and specificity for clinically detecting synovitis and effusion in individual subjects. A range of definitions for the two key US variables, synovitis and effusion (using different combinations of synovial thickness, depth, and appearance), were also included in exploratory analyses. Results: 600 patients with knee OA were included in the analysis. For both knee synovitis and joint effusion, the sensitivity and specificity were poor, yielding unsatisfactory likelihood ratios (75% sensitivity, 45% specificity, and positive LR of 1.36 for knee synovitis; 71.6% sensitivity, 43.2% specificity, and positive LR of 1.26 for joint effusion). The exploratory analyses did not improve the sensitivity and specificity (demonstrating positive LRs of between 1.26 and 1.57). Conclusion: Although it is possible to determine clinical and radiological predictors of OA inflammation in populations, CART analysis could not be used to devise useful clinical decision rules for an individual subject. Thus sensitive imaging techniques such as US remain the most useful tool for demonstrating synovial inflammation of the knee at the individual level. PMID:15878902

  3. 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

  4. Exposure Models for the Prior Distribution in Bayesian Decision Analysis for Occupational Hygiene Decision Making

    PubMed Central

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

    2015-01-01

    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

  5. Using Decision Analysis to Improve Malaria Control Policy Making

    PubMed Central

    Kramer, Randall; Dickinson, Katherine L.; Anderson, Richard M.; Fowler, Vance G.; Miranda, Marie Lynn; Mutero, Clifford M.; Saterson, Kathryn A.; Wiener, Jonathan B.

    2013-01-01

    Malaria and other vector-borne diseases represent a significant and growing burden in many tropical countries. Successfully addressing these threats will require policies that expand access to and use of existing control methods, such as insecticide-treated bed nets and artemesinin combination therapies for malaria, while weighing the costs and benefits of alternative approaches over time. This paper argues that decision analysis provides a valuable framework for formulating such policies and combating the emergence and re-emergence of malaria and other diseases. We outline five challenges that policy makers and practitioners face in the struggle against malaria, and demonstrate how decision analysis can help to address and overcome these challenges. A prototype decision analysis framework for malaria control in Tanzania is presented, highlighting the key components that a decision support tool should include. Developing and applying such a framework can promote stronger and more effective linkages between research and policy, ultimately helping to reduce the burden of malaria and other vector-borne diseases. PMID:19356821

  6. HUMAN HEALTH METRICS FOR ENVIRONMENTAL DECISION SUPPORT TOOLS: LESSONS FROM HEALTH ECONOMICS AND DECISION ANALYSIS: JOURNAL ARTICLE

    EPA Science Inventory

    NRMRL-CIN-1351 Hofstetter**, P., and Hammitt, J. K. Human Health Metrics for Environmental Decision Support Tools: Lessons from Health Economics and Decision Analysis. Risk Analysis 600/R/01/104, Available: on internet, www.epa.gov/ORD/NRMRL/Pubs/600R01104, [NET]. 03/07/2001 D...

  7. 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. PMID:26667939

  8. Shared Decision Making Does Not Influence Physicians against Clinical Practice Guidelines

    PubMed Central

    Guerrier, Mireille; Légaré, France; Turcotte, Stéphane; Labrecque, Michel; Rivest, Louis-Paul

    2013-01-01

    Background While shared decision making (SDM) and adherence to clinical practice guidelines (CPGs) are important, some believe they are incompatible. This study explored the mutual influence between physicians’ intention to engage in SDM and their intention to follow CPGs. Methods Embedded within a clustered randomized trial to assess the impact of training physicians in SDM about using antibiotics to treat acute respiratory tract infections, this study evaluated physicians’ intentions to both engage in SDM and follow CPGs. A self-administered questionnaire based on the theory of planned behavior evaluated both behavioral intentions and their respective determinants (attitude, subjective norm and perceived behavioral control) at study entry and exit. We used path analysis to explore the relationships between the intentions. We conducted statistical analyses using the maximum likelihood method and the variance-covariance matrix. Goodness of fit indices encompassed the chi-square statistic, the comparative fit index and the root mean square error of approximation. Results We analyzed 244 responses at entry and 236 at exit. In the control group, at entry we observed that physicians’ intention to engage in SDM (r = 0, t = 0.03) did not affect their intention to follow CPGs; however, their intention to follow CPGs (r = −0.31 t = −2.82) did negatively influence their intention to engage in SDM. At exit, neither behavioral intention influenced the other. In the experimental group, at entry neither behavioral intention influenced the other; at exit, the intention to engage in SDM still did not influence the intention to use CPGs, although the intention to follow CPGs (r = −0.15 t = −2.02) slightly negatively influenced the intention to engage in SDM, but this was not clinically significant. Conclusion Physicians’ intention to engage in SDM does not affect their intention to adopt CPGs even after SDM training. Physicians’ intention

  9. 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…

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

    DOE PAGESBeta

    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. 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.

  12. Clinical Decision Support using a Terminology Server to improve Patient Safety.

    PubMed

    Garcia-Jimenez, Alba; Moreno-Conde, Alberto; Martínez-García, Alicia; Marín-León, Ignacio; Medrano-Ortega, Francisco Javier; Parra-Calderón, Carlos L

    2015-01-01

    Clinical Decision Support Systems (CDSS) are software applications that support clinicians in making healthcare decisions providing relevant information for individual patients about their specific conditions. The lack of integration between CDSS and Electronic Health Record (EHR) has been identified as a significant barrier to CDSS development and adoption. Andalusia Healthcare Public System (AHPS) provides an interoperable health information infrastructure based on a Service Oriented Architecture (SOA) that eases CDSS implementation. This paper details the deployment of a CDSS jointly with the deployment of a Terminology Server (TS) within the AHPS infrastructure. It also explains a case study about the application of decision support to thromboembolism patients and its potential impact on improving patient safety. We will apply the inSPECt tool proposal to evaluate the appropriateness of alerts in this scenario. PMID:25991120

  13. 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

  14. 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. PMID:12865746

  15. 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

  16. 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

  17. 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

  18. 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

  19. 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

  20. 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

  1. 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'. PMID:26979251

  2. Decision aid tools to support women's decision making in pregnancy and birth: a systematic review and meta-analysis.

    PubMed

    Dugas, Marylène; Shorten, Allison; Dubé, Eric; Wassef, Maggy; Bujold, Emmanuel; Chaillet, Nils

    2012-06-01

    Support for a model of shared medical decision making, where women and their care providers discuss risks and benefits of their different options, reveal their preferences, and jointly make a decision, is a growing expectation in obstetric care. The objective of this study was to conduct a systematic review and meta-analysis of randomized controlled trials evaluating the efficacy of different decision aid tools compared to regular care for women facing several options in the specific field of obstetric care. We included published studies about interventions designed to aid mothers' decision making and provide information about obstetrical treatment or screening options. Following a search of electronic databases for articles published in English and French from 1994 to 2010, we found ten studies that met the inclusion criteria. In this systematic review and meta-analysis we found that all decision aid tools, except for Decision Trees, facilitated significant increases in knowledge. The Computer-based Information Tool, the Decision Analysis Tools, Individual Counseling and Group Counseling intervention presented significant results in reducing anxiety levels. The Decision Analysis Tools and the Computer-based Information tool were associated with a reduction in levels of decisional conflict. The Decision Analysis Tool was the only tool that presented evidence of an impact on the final choice and final outcome. Decision aid tools can assist health professionals to provide information and counseling about choices during pregnancy and support women in shared decision making. The choice of a specific tool should depend on resources available to support their use as well as the specific decisions being faced by women, their health care setting and providers. PMID:22475401

  3. 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. PMID:25790510

  4. 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. PMID:10566470

  5. Editorial: The search for core symptoms - will this help clinical decision-making?

    PubMed

    Frazier Norbury, Courtenay

    2016-08-01

    Diagnosis is an important component of our clinical roles, and should also lead to particular treatment pathways. The diagnostic process may be challenged by co-occurring deficits that are neither specific nor universal to the diagnosis under consideration and may well be evident across a range of other clinical conditions. How important is it to refine our instruments so that they measure unique symptoms? Will this alter or improve intervention choices? This Editorial focuses on the extent to which fine tuning diagnostic instruments improves our decisions about treatment, in the context of articles published in this issue of JCPP. PMID:27445109

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

    PubMed

    Welie, Jos Vm; Ten Have, Henk Amj

    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

  7. Governance for clinical decision support: case studies and recommended practices from leading institutions

    PubMed Central

    Sittig, Dean F; Ash, Joan S; Bates, David W; Feblowitz, Joshua; Fraser, Greg; Maviglia, Saverio M; McMullen, Carmit; Nichol, W Paul; Pang, Justine E; Starmer, Jack; Middleton, Blackford

    2011-01-01

    Objective Clinical decision support (CDS) is a powerful tool for improving healthcare quality and ensuring patient safety; however, effective implementation of CDS requires effective clinical and technical governance structures. The authors sought to determine the range and variety of these governance structures and identify a set of recommended practices through observational study. Design Three site visits were conducted at institutions across the USA to learn about CDS capabilities and processes from clinical, technical, and organizational perspectives. Based on the results of these visits, written questionnaires were sent to the three institutions visited and two additional sites. Together, these five organizations encompass a variety of academic and community hospitals as well as small and large ambulatory practices. These organizations use both commercially available and internally developed clinical information systems. Measurements Characteristics of clinical information systems and CDS systems used at each site as well as governance structures and content management approaches were identified through extensive field interviews and follow-up surveys. Results Six recommended practices were identified in the area of governance, and four were identified in the area of content management. Key similarities and differences between the organizations studied were also highlighted. Conclusion Each of the five sites studied contributed to the recommended practices presented in this paper for CDS governance. Since these strategies appear to be useful at a diverse range of institutions, they should be considered by any future implementers of decision support. PMID:21252052

  8. A collaborative teaching strategy for enhancing learning of evidence-based clinical decision-making.

    PubMed

    Scott, P J; Altenburger, P A; Kean, J

    2011-01-01

    The educational literature cites a lack of student motivation to learn how to use research evidence in clinical decision-making because the students do not observe clinicians using evidence. This lack of motivation presents a challenge to educators as they seek to instill the value of evidence-based clinical decision-making (EBCD) in students. One problem is that students in entry-level programs do not have the experience needed to know what to look for, and secondly, clinical decision-making is contextually based in a patient problem. Our approach offers one solution to bridging the gap between classroom teaching and real-world implementation of EBCD through a three-phase collaborative approach. Occupational and physical therapy students are partnered with clinicians to find and appraise evidence to answer the real-world questions posed by these therapists. This paper describes the implementation of the partnership, teaching/learning outcomes, logistics, and implications for clinicians. We found this approach increased student motivation and greatly enhanced the learning experience. Future directions include implementing a framework which allows for the assessment of the strategy on the facility and creates opportunities to integrate the use of EBCD in all aspects of facility practice. PMID:21927777

  9. A study of clinical decision making by certified registered nurse anesthetists.

    PubMed

    Kremer, Michael J; Faut-Callahan, Margaret; Hicks, Frank D

    2002-10-01

    Anesthesia outcomes and related risk factors have been studied for more than 100 years. Varying sample sizes and research methods have been used, with research findings that were open to multiple interpretations. Research with closed malpractice claims demonstrates that American Society of Anesthesiologists physical status II patients undergoing elective procedures are most likely to experience damaging events intraoperatively with resultant postoperative adverse outcomes. The process of care, including clinical decision making, contributes to adverse outcomes. Clinical decision making can be difficult to assess and measure. In this study, the cognitive psychology framework of information-processing theory and literature pertaining to the use of heuristics, or rules of thumb, and clinical biases, were used to analyze cases from the AANA Foundation closed malpractice claims database. This database contains more than 300 files involving St Paul Fire and Marine Insurance Company-covered CRNAs from across the United States. These files were analyzed by 10 CRNA investigators on the AANA Closed Claims research team. Variables such as inadequate preinduction activities, e.g., incomplete preanesthetic assessments, and use of cognitive biases and inaccurate probability estimation were associated with adverse outcomes in this research sample. Teaching of decision science in basic and continuing nurse anesthesia education is advocated. PMID:12425129

  10. Pattern Analysis and Decision Support for Cancer through Clinico-Genomic Profiles

    NASA Astrophysics Data System (ADS)

    Exarchos, Themis P.; Giannakeas, Nikolaos; Goletsis, Yorgos; Papaloukas, Costas; Fotiadis, Dimitrios I.

    Advances in genome technology are playing a growing role in medicine and healthcare. With the development of new technologies and opportunities for large-scale analysis of the genome, genomic data have a clear impact on medicine. Cancer prognostics and therapeutics are among the first major test cases for genomic medicine, given that all types of cancer are related with genomic instability. In this paper we present a novel system for pattern analysis and decision support in cancer. The system integrates clinical data from electronic health records and genomic data. Pattern analysis and data mining methods are applied to these integrated data and the discovered knowledge is used for cancer decision support. Through this integration, conclusions can be drawn for early diagnosis, staging and cancer treatment.

  11. 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

  12. 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.

  13. 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

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

    PubMed Central

    2014-01-01

    Background Gender differences in communication styles between clinicians and patients have been postulated to impact patient care, but the extent to which the gender dyad structure impacts outcomes in shared decision making remains unclear. Methods Participant-level meta-analysis of 775 clinical encounters within 7 randomized trials where decision aids, shared decision making tools, were used at the point of care. Outcomes analysed include decisional conflict scale scores, satisfaction with the clinical encounter, concordance between stated decision and action taken, and degree of patient engagement by the clinician using the OPTION scale. An estimated minimal important difference was used to determine if nonsignificant results could be explained by low power. Results We did not find a statistically significant interaction between clinician/patient gender mix and arm for decisional conflict, satisfaction with the clinical encounter or patient engagement. A borderline significant interaction (p = 0.05) was observed for one outcome: concordance between stated decision and action taken, where encounters with female clinician/male patient showed increased concordance in the decision aid arm compared to control (8% more concordant encounters). All other gender dyads showed decreased concordance with decision aid use (6% fewer concordant encounters for same-gender, 16% fewer concordant encounters for male clinician/female patient). Conclusions In this participant-level meta-analysis of 7 randomized trials, decision aids used at the point of care demonstrated comparable efficacy across gender dyads. Purported barriers to shared decision making based on gender were not detected when tested for a minimum detected difference. Trial registrations ClinicalTrials.gov NCT00888537, NCT01077037, NCT01029288, NCT00388050, NCT00578981, NCT00949611, NCT00217061. PMID:25179289

  15. 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

  16. 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

  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. PMID:26133889

  18. Applying Multiple Criteria Decision Analysis to Comparative Benefit-Risk Assessment: Choosing among Statins in Primary Prevention.

    PubMed

    Tervonen, Tommi; Naci, Huseyin; van Valkenhoef, Gert; Ades, Anthony E; Angelis, Aris; Hillege, Hans L; Postmus, Douwe

    2015-10-01

    Decision makers in different health care settings need to weigh the benefits and harms of alternative treatment strategies. Such health care decisions include marketing authorization by regulatory agencies, practice guideline formulation by clinical groups, and treatment selection by prescribers and patients in clinical practice. Multiple criteria decision analysis (MCDA) is a family of formal methods that help make explicit the tradeoffs that decision makers accept between the benefit and risk outcomes of different treatment options. Despite the recent interest in MCDA, certain methodological aspects are poorly understood. This paper presents 7 guidelines for applying MCDA in benefit-risk assessment and illustrates their use in the selection of a statin drug for the primary prevention of cardiovascular disease. We provide guidance on the key methodological issues of how to define the decision problem, how to select a set of nonoverlapping evaluation criteria, how to synthesize and summarize the evidence, how to translate relative measures to absolute ones that permit comparisons between the criteria, how to define suitable scale ranges, how to elicit partial preference information from the decision makers, and how to incorporate uncertainty in the analysis. Our example on statins indicates that fluvastatin is likely to be the most preferred drug by our decision maker and that this result is insensitive to the amount of preference information incorporated in the analysis. PMID:25986470

  19. Clinical Recommendations in Medical Practice: A Proposed Framework to Reduce Bias and Improve the Quality of Medical Decisions.

    PubMed

    Alfandre, David

    2016-01-01

    Patients rely on, benefit from, and are strongly influenced by physicians' recommendations. In spite of the centrality and importance of physicians' recommendations to clinical care, there is only a scant literature describing the conceptual process of forming a clinical recommendation, and no discrete professional standards for making individual clinical recommendations. Evidence-based medicine and shared decision making together are intended to improve medical decision making, but there has been limited attention to how a recommendation is discretely formulated from either of those processes or how patients' preferences ought to be considered and how much weight they should hold. Moreover, physicians' bias has been reported to strongly influence how a recommendation is derived, thereby undermining the quality of healthcare decisions and patients' trust. To demonstrate a potential for improving the quality of decisions, this article proposes a conceptual framework for how physicians should reach a clinical recommendation and apply the process in practice. For preference-sensitive clinical decisions-that is, clinical decisions when patients' values and preferences are relevant-the process for reaching a recommendation should be transparent to patients and should be based solely on the medical evidence and patients' values and preferences. When patients' preferences for care do not prioritize health, physicians decide whether their recommendation will prioritize a welfare-enhancing versus an autonomy-enhancing approach. When there are gaps in understanding how physicians derive their clinical recommendations and how to further improve the quality of the decisions, the author calls for further empiric research. PMID:27045301

  20. Decision Analysis Tool to Compare Energy Pathways for Transportation

    SciTech Connect

    Bloyd, Cary N.; Stork, Kevin

    2011-02-01

    With the goals of reducing greenhouse gas emissions, oil imports, and energy costs, a wide variety of automotive technologies are proposed to replace the traditional gasoline-powered internal combustion engine (g-ICE). A prototype model, Analytica Transportation Energy Analysis Model (ATEAM), has been developed using the Analytica decision modeling environment, visualizing the structure as a hierarchy of influence diagrams. The report summarized the FY2010 ATEAM accomplishments.

  1. 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

  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. Entropy Methods For Univariate Distributions in Decision Analysis

    NASA Astrophysics Data System (ADS)

    Abbas, Ali E.

    2003-03-01

    One of the most important steps in decision analysis practice is the elicitation of the decision-maker's belief about an uncertainty of interest in the form of a representative probability distribution. However, the probability elicitation process is a task that involves many cognitive and motivational biases. Alternatively, the decision-maker may provide other information about the distribution of interest, such as its moments, and the maximum entropy method can be used to obtain a full distribution subject to the given moment constraints. In practice however, decision makers cannot readily provide moments for the distribution, and are much more comfortable providing information about the fractiles of the distribution of interest or bounds on its cumulative probabilities. In this paper we present a graphical method to determine the maximum entropy distribution between upper and lower probability bounds and provide an interpretation for the shape of the maximum entropy distribution subject to fractile constraints, (FMED). We also discuss the problems with the FMED in that it is discontinuous and flat over each fractile interval. We present a heuristic approximation to a distribution if in addition to its fractiles, we also know it is continuous and work through full examples to illustrate the approach.

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

    PubMed Central

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

    2011-01-01

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

  5. 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. PMID:3755759

  6. A Framework for Usable and Effective Clinical Decision Support: Experience from the iCPR Randomized Clinical Trial

    PubMed Central

    Kannry, Joseph; McCullagh, Lauren; Kushniruk, Andre; Mann, Devin; Edonyabo, Daniel; McGinn, Thomas

    2015-01-01

    Introduction: The promise of Clinical Decision Support (CDS) has always been to transform patient care and improve patient outcomes through the delivery of timely and appropriate recommendations that are patient specific and, more often than not, are appropriately actionable. However, the users of CDS—providers—are frequently bombarded with inappropriate and inapplicable CDS that often are not informational, not integrated into the workflow, not patient specific, and that may present out of date and irrelevant recommendations. Methods: The integrated clinical prediction rule (iCPR) project was a randomized clinical trial (RCT) conducted to determine if a novel form of CDS, i.e., clinical prediction rules (CPRs), could be efficiently integrated into workflow and result in changes in outcomes (e.g., antibiotic ordering) when embedded within a commercial electronic health record (EHR). We use the lessons learned from the iCPR project to illustrate a framework for constructing usable, useful, and effective actionable CDS while employing off-the-shelf functionality in a production system. Innovations that make up the framework combine the following: (1) active and actionable decision support, (2) multiple rounds of usability testing with iterative development for user acceptance, (3) numerous context sensitive triggers, (4) dedicated training and support for users of the CDS tool for user adoption, and (5) support from clinical and administrative leadership. We define “context sensitive triggers” as being workflow events (i.e., context) that result in a CDS intervention. Discussion: Success of the framework can be measured by CDS adoption (i.e., intervention is being used), acceptance (compliance with recommendations), and clinical outcomes (where appropriate). This framework may have broader implications for the deployment of Health Information Technology (HIT). Results and Conclusion: iCPR was well adopted(57.4% of users) and accepted (42.7% of users

  7. 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

  8. 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…

  9. 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

  10. Electronic medication ordering with integrated drug database and clinical decision support system.

    PubMed

    Cufar, Andreja; Droljc, Anže; Orel, Andrej

    2012-01-01

    Medication errors have been identified as one of the most important causes of adverse drug events. Computerized physician order-entry (CPOE) systems, coupled with decision support (Medication allergy checking, drug interactions, and dose calculations), are considered to be appropriate solutions for reducing medication errors and standardizing care. It is quite useful if clinical information system (CIS) supports order sets, which help with standardizing care, preventing omission errors, and expediting the ordering process. Order sets are predefined groups of orders pertinent to one or more specific clinical conditions or diagnoses. The article describes how a clinical information system can be used to support medication process (prescribing, ordering, dispensing, administration and monitoring) and offer participating medical teams real time warnings and key information regarding medications and patient status, thus reducing medication errors. Integrated electronic prescribing support system benefits for total parenteral nutrition (TPN) are discussed at the end. PMID:22874280

  11. Clinical Decisions: Determining When to Save or Remove an Ailing Implant.

    PubMed

    Tarnow, Dennis P; Chu, Stephen J; Fletcher, Paul D

    2016-04-01

    The basis for the decision to either save or remove an ailing implant is multifactorial, and, as such, it has become one of the more controversial topics in the field of dental implantology. While bone lost to peri-implant disease can now be augmented with increasing predictability, the degree of success still varies depending on the size and configuration of the osseous defect. Concurrently, with the development of improved high-reverse torque instrumentation, minimally invasive techniques can be used to easily remove an implant that is malpositioned, causing an esthetic problem, or showing advanced bone loss. Any eventual decision regarding the retention or removal of an ailing implant must also be balanced with the desires of the patient, who typically will have already invested significant time and money to have the implant initially placed and restored. This article will present the variables involved in the decision-making process for when to save or remove an ailing implant. Clinical examples illustrating the management for these factors will be offered, providing clinicians a variety of alternatives available for managing different clinical circumstances that may be encountered. PMID:27136118

  12. A UMLS-based Knowledge Acquisition Tool for Rule-based Clinical Decision Support System Development

    PubMed Central

    Achour, Soumeya L.; Dojat, Michel; Rieux, Claire; Bierling, Philippe; Lepage, Eric

    2001-01-01

    Decision support systems in the medical field have to be easily modified by medical experts themselves. The authors have designed a knowledge acquisition tool to facilitate the creation and maintenance of a knowledge base by the domain expert and its sharing and reuse by other institutions. The Unified Medical Language System (UMLS) contains the domain entities and constitutes the relations repository from which the expert builds, through a specific browser, the explicit domain ontology. The expert is then guided in creating the knowledge base according to the pre-established domain ontology and condition–action rule templates that are well adapted to several clinical decision-making processes. Corresponding medical logic modules are eventually generated. The application of this knowledge acquisition tool to the construction of a decision support system in blood transfusion demonstrates the value of such a pragmatic methodology for the design of rule-based clinical systems that rely on the highly progressive knowledge embedded in hospital information systems. PMID:11418542

  13. Understanding the impact of economic evidence on clinical decision making: a discrete choice experiment in cardiology.

    PubMed

    Torbica, Aleksandra; Fattore, Giovanni

    2010-05-01

    The present study aims to evaluate the impact of cost-effectiveness information on clinical decision making using discrete choice experiment (DCE) methodology. Data were collected through a self-completed questionnaire administered to Italian cardiologists in June 2007 (n = 129 respondents, 1143 observations). The questionnaire asked clinicians to make choices between paired scenarios, across which three key dimensions were identified and varied: (1) quality of clinical evidence, (2) size of health gain (reduction of relative and absolute risk), and (3) economic impact (incremental cost-effectiveness ratio). A random effects probit model was used to estimate clinicians' preferences for the different dimensions, while the heterogeneity of preferences was tested in a model with interaction terms. Dominance tests were used to assess the consistency of responses. The results indicate that Italian cardiologists regard economic impact (cost-effectiveness) as an important factor in their decision making. Economic evidence is valued more highly among clinicians with a higher self-assessed level of knowledge regarding economic evaluation techniques, as well as among younger professionals (age<45). While relevant study limitations should be acknowledged, our results suggest that DCEs can be used to elicit clinicians' decision-making criteria and to inform the allocation of resources for future research in a logical manner. Italian cardiologists appear to take cost-effectiveness information into account when deciding whether to use new treatments. PMID:20207466

  14. Clinical evaluation of the DIABETES expert system for decision support by multiple regimen insulin dose adjustment.

    PubMed

    Ambrosiadou, B V; Goulis, D G; Pappas, C

    1996-01-01

    A performance evaluation of the DIABETES rule-based expert system prototype for clinical decision making is presented. The system facilitates multiple insulin regimen and dose adjustment of insulin dependent Type I or II diabetic patients. The study was performed on 600 subjects from two diabetological centres and three diabetological offices of Greek hospitals. The responses of the attendant medical doctors were compared with those of the DIABETES system, with the aid of a specifically devised valuation range (0-5 degrees, 0 indicating full agreement and 5 full disagreement). The capabilities and the weakness of the system in terms of its practicality for decision support in assisting therapy of diabetes mellitus by blood glucose monitoring and subsequent insulin dose adjustment are discussed. The potential benefits of decision support systems for diabetic patient management are seen to be the cost saving they provide in terms of man-hours of verbal instruction by medical experts, the support in terms of objective and consistent decision making, as well as the recording of medical knowledge in the ill-defined field of insulin administration, thus aiding the education and training of medical personnel. PMID:8646833

  15. 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.

  16. 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

  17. 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.

  18. Lunar mission architecture evaluation using a decision analysis approach

    NASA Technical Reports Server (NTRS)

    Gleave, Janet

    1990-01-01

    President Bush's call for a return to the Moon, followed by the human exploration of Mars, has spawned numerous ideas for implementing what has been called the Space Exploration Initiative (SEI). Because a return to the Moon has been designated as the first step of SEI, the time is rapidly approaching to select one of the many mission architectures proposed for the exploration, settlement, and exploitation of the Moon. The evaluation of alternative archictures, and the subsequent selection of the 'best' alternative will be critical to the success of this, and other, space programs. The following presentation discusses the application of systems analysis to the evaluation and selection of a Lunar outpost mission architecture. The role of a decision model in the evaluation/selection process is discussed, and different types of decision models are presented. These models are analyzed and discussed in terms of their applicability to the selection of a Lunar outpost mission architecture.

  19. 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

  20. 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

  1. 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. PMID:25698915

  2. 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...

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

    PubMed

    Kerr, Kathleen F; Brown, Marshall D; Zhu, Kehao; Janes, Holly

    2016-07-20

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

  4. Comparison of Computer-based Clinical Decision Support Systems and Content for Diabetes Mellitus

    PubMed Central

    Kantor, M.; Wright, A.; Burton, M.; Fraser, G.; Krall, M.; Maviglia, S.; Mohammed-Rajput, N.; Simonaitis, L.; Sonnenberg, F.; Middleton, B.

    2011-01-01

    Background Computer-based clinical decision support (CDS) systems have been shown to improve quality of care and workflow efficiency, and health care reform legislation relies on electronic health records and CDS systems to improve the cost and quality of health care in the United States; however, the heterogeneity of CDS content and infrastructure of CDS systems across sites is not well known. Objective We aimed to determine the scope of CDS content in diabetes care at six sites, assess the capabilities of CDS in use at these sites, characterize the scope of CDS infrastructure at these sites, and determine how the sites use CDS beyond individual patient care in order to identify characteristics of CDS systems and content that have been successfully implemented in diabetes care. Methods We compared CDS systems in six collaborating sites of the Clinical Decision Support Consortium. We gathered CDS content on care for patients with diabetes mellitus and surveyed institutions on characteristics of their site, the infrastructure of CDS at these sites, and the capabilities of CDS at these sites. Results The approach to CDS and the characteristics of CDS content varied among sites. Some commonalities included providing customizability by role or user, applying sophisticated exclusion criteria, and using CDS automatically at the time of decision-making. Many messages were actionable recommendations. Most sites had monitoring rules (e.g. assessing hemoglobin A1c), but few had rules to diagnose diabetes or suggest specific treatments. All sites had numerous prevention rules including reminders for providing eye examinations, influenza vaccines, lipid screenings, nephropathy screenings, and pneumococcal vaccines. Conclusion Computer-based CDS systems vary widely across sites in content and scope, but both institution-created and purchased systems had many similar features and functionality, such as integration of alerts and reminders into the decision-making workflow of the

  5. 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

  6. Teaching clinical decision-making to pediatric residents in an era of managed care.

    PubMed

    Chessare, J B

    1998-04-01

    The growth of managed care has brought a new focus on physician competency in the appropriate use of resources to help patients. The community of pediatric educators must improve residency curricula and teaching methodologies to ensure that graduates of their programs can effectively and efficiently meet the needs of children and their families. The educational approach in many pediatric residency programs is an implicit apprenticeship model, with which the residents follow the actions of attending physicians with little attention to scrutiny of the clinical evidence for and against diagnostic and treatment strategies. Evidence-based medicine stresses to the trainee the importance of the evaluation of evidence from clinical research and cautions against the use of intuition, unsystematic clinical experience, and untested pathophysiologic reasoning as sufficient for medical decision-making. Managed care also has helped to create a heightened awareness of the need to educate residents to incorporate the preferences of patients and families into diagnostic and treatment decisions. Trainees must know how to balance their duty to maximize the health of populations at the lowest resource use with their duty to each individual patient and family. Changes in the residency curriculum will bring change in educational settings and the structure of rotations. Potential barriers to implementation will include the need for faculty development and financial resources for information technology. PMID:9544180

  7. 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…

  8. Sources of non-compliance with clinical practice guidelines in trauma triage: a decision science study

    PubMed Central

    2012-01-01

    Background United States trauma system guidelines specify when to triage patients to specialty centers. Nonetheless, many eligible patients are not transferred as per guidelines. One possible reason is emergency physician decision-making. The objective of the study was to characterize sensory and decisional determinants of emergency physician trauma triage decision-making. Methods We conducted a decision science study using a signal detection theory-informed approach to analyze physician responses to a web-based survey of 30 clinical vignettes of trauma cases. We recruited a national convenience sample of emergency medicine physicians who worked at hospitals without level I/II trauma center certification. Using trauma triage guidelines as our reference standard, we estimated physicians’ perceptual sensitivity (ability to discriminate between patients who did and did not meet guidelines for transfer) and decisional threshold (tolerance for false positive or false negative decisions). Results We recruited 280 physicians: 210 logged in to the website (response rate 74%) and 168 (80%) completed the survey. The regression coefficient on American College of Surgeons – Committee on Trauma (ACS-COT) guidelines for transfer (perceptual sensitivity) was 0.77 (p<0.01, 95% CI 0.68 – 0.87) indicating that the probability of transfer weakly increased as the ACS-COT guidelines would recommend transfer. The intercept (decision threshold) was 1.45 (p<0.01, 95% CI 1.27 – 1.63), indicating that participants had a conservative threshold for transfer, erring on the side of not transferring patients. There was significant between-physician variability in perceptual sensitivity and decisional thresholds. No physician demographic characteristics correlated with perceptual sensitivity, but men and physicians working at non-trauma centers without a trauma-center affiliation had higher decisional thresholds. Conclusions On a case vignette-based questionnaire, both sensory and

  9. Using Computational Modeling to Assess the Impact of Clinical Decision Support on Cancer Screening within Community Health Centers

    PubMed Central

    Carney, Timothy Jay; Morgan, Geoffrey P.; Jones, Josette; McDaniel, Anna M.; Weaver, Michael; Weiner, Bryan; Haggstrom, David A.

    2014-01-01

    Our conceptual model demonstrates our goal to investigate the impact of clinical decision support (CDS) utilization on cancer screening improvement strategies in the community health care (CHC) setting. We employed a dual modeling technique using both statistical and computational modeling to evaluate impact. Our statistical model used the Spearman’s Rho test to evaluate the strength of relationship between our proximal outcome measures (CDS utilization) against our distal outcome measure (provider self-reported cancer screening improvement). Our computational model relied on network evolution theory and made use of a tool called Construct-TM to model the use of CDS measured by the rate of organizational learning. We employed the use of previously collected survey data from community health centers Cancer Health Disparities Collaborative (HDCC). Our intent is to demonstrate the added valued gained by using a computational modeling tool in conjunction with a statistical analysis when evaluating the impact a health information technology, in the form of CDS, on health care quality process outcomes such as facility-level screening improvement. Significant simulated disparities in organizational learning over time were observed between community health centers beginning the simulation with high and low clinical decision support capability. PMID:24953241

  10. 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. PMID:24256004

  11. 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

  12. 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

  13. 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

  14. 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

  15. A Component-Based Evaluation Protocol for Clinical Decision Support Interfaces

    PubMed Central

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

    2016-01-01

    In this paper we present our experience in designing and applying an evaluation protocol for assessing usability of a clinical decision support (CDS) system. The protocol is based on component-based usability testing, cognitive interviewing, and a rigorous coding scheme cross-referenced to a component library. We applied this protocol to evaluate alternate designs of a CDS interface for a nursing plan of care tool. The protocol allowed us to aggregate and analyze usability data at various granularity levels, supporting both validation of existing components and providing guidance for targeted redesign.

  16. 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

  17. 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

  18. Implementation of a Clinical Decision Support Alert for the Management of Clostridium difficile Infection

    PubMed Central

    Revolinski, Sara

    2015-01-01

    Clostridium difficile infections are common in hospitalized patients and can result in significant morbidity and mortality. It is imperative to optimize the management of C. difficile infections to help minimize disease complications. Antimicrobial stewardship techniques including guidelines, order sets and other clinical decision support functionalities may be utilized to assist with therapy optimization. We implemented a novel alert within our electronic medical record to direct providers to the C. difficile order set in order to assist with initiating therapy consistent with institutional guideline recommendations. The alert succeeded in significantly increasing order set utilization, but guideline compliance was unchanged. PMID:27025646

  19. 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.

  20. 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.

  1. Clinical decision making in response to performance validity test failure in a psychiatric setting.

    PubMed

    Marcopulos, Bernice A; Caillouet, Beth A; Bailey, Christopher M; Tussey, Chriscelyn; Kent, Julie-Ann; Frederick, Richard

    2014-01-01

    This study examined the clinical utility of a performance validity test (PVT) for screening consecutive referrals (N = 436) to a neuropsychology service at a state psychiatric hospital treating both civilly committed and forensic patients. We created a contingency table with Test of Memory Malingering (TOMM) pass/fail (355/81) and secondary gain present/absent (181/255) to examine pass rates associated with patient demographic, clinical and forensic status characteristics. Of the 81 failed PVTs, 48 had secondary gain defined as active criminal legal charges; 33 failed PVTs with no secondary gain. These individuals tended to be older, female, Caucasian, and civilly committed compared with the group with secondary gain who failed. From estimations of TOMM False Positive Rate and True Positive Rate we estimated base rates of neurocognitive malingering for our clinical population using the Test Validation Summary (TVS; Frederick & Bowden, 2009 ). Although PVT failure is clearly more common in a group with secondary gain (31%), there were a number of false positives (11%). Clinical ratings of patients without gain who failed suggested cognitive deficits, behavioral issues, and inattention. Low scores on PVTs in the absence of secondary gain provide useful information on test engagement and can inform clinical decisions about testing. PMID:24678658

  2. 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

  3. 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

  4. Ethics of Clinical Decision-Making for Older Drivers: Reporting Health-Related Driving Risk.

    PubMed

    Mazer, Barbara; Laliberté, Maude; Hunt, Matthew; Lemoignan, Josée; Gélinas, Isabelle; Vrkljan, Brenda; Naglie, Gary; Marshall, Shawn

    2016-06-01

    The number of older drivers will continue to increase as the population ages. Health care professionals have the responsibility of providing care and maintaining confidentiality for their patients while ensuring public safety. This article discusses the ethics of clinical decision-making pertaining to reporting health-related driving risk of older drivers to licensing authorities. Ethical considerations inherent in reporting driving risk, including autonomy, confidentiality, therapeutic relationships, and the uncertainty about determining individual driving safety and risk, are discussed. We also address the moral agency of reporting health-related driving risk and raise the question of whose responsibility it is to report. Issues of uncertainty surrounding clinical reasoning and concepts related to risk assessment are also discussed. Finally, we present two case studies to illustrate some of the issues and challenges faced by health care professionals as they seek to balance their responsibilities for their patients while ensuring road safety for all citizens. PMID:27117942

  5. Extraction Of Adverse Events From Clinical Documents To Support Decision Making Using Semantic Preprocessing.

    PubMed

    Gaebel, Jan; Kolter, Till; Arlt, Felix; Denecke, Kerstin

    2015-01-01

    Clinical documentation is usually stored in unstructured format in electronic health records (EHR). Processing the information is inconvenient and time consuming and should be enhanced by computer systems. In this paper, a rule-based method is introduced that identifies adverse events documented in the EHR that occurred during treatment. For this purpose, clinical documents are transformed into a semantic structure from which adverse events are extracted. The method is evaluated in a user study with neurosurgeons. In comparison to a bag of word classification using support vector machines, our approach achieved comparably good results of 65% recall and 78% precision. In conclusion, the rule-based method generates promising results that can support physicians' decision making. Because of the structured format the data can be reused for other purposes as well. PMID:26262330

  6. 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

  7. Video decision aids to assist with advance care planning: a systematic review and meta-analysis

    PubMed Central

    Jain, Ashu; Corriveau, Sophie; Quinn, Kathleen; Gardhouse, Amanda; Vegas, Daniel Brandt; You, John J

    2015-01-01

    Objective Advance care planning (ACP) can result in end-of-life care that is more congruent with patients’ values and preferences. There is increasing interest in video decision aids to assist with ACP. The objective of this study was to evaluate the impact of video decision aids on patients’ preferences regarding life-sustaining treatments (primary outcome). Design Systematic review and meta-analysis of randomised controlled trials. Data sources MEDLINE, EMBASE, PsycInfo, CINAHL, AMED and CENTRAL, between 1980 and February 2014, and correspondence with authors. Eligibility criteria for selecting studies Randomised controlled trials of adult patients that compared a video decision aid to a non-video-based intervention to assist with choices about use of life-sustaining treatments and reported at least one ACP-related outcome. Data extraction Reviewers worked independently and in pairs to screen potentially eligible articles, and to extract data regarding risk of bias, population, intervention, comparator and outcomes. Reviewers assessed quality of evidence (confidence in effect estimates) for each outcome using the Grading of Recommendations Assessment, Development and Evaluation framework. Results 10 trials enrolling 2220 patients were included. Low-quality evidence suggests that patients who use a video decision aid are less likely to indicate a preference for cardiopulmonary resuscitation (pooled risk ratio, 0.50 (95% CI 0.27 to 0.95); I2=65%). Moderate-quality evidence suggests that video decision aids result in greater knowledge related to ACP (standardised mean difference, 0.58 (95% CI 0.38 to 0.77); I2=0%). No study reported on the congruence of end-of-life treatments with patients’ wishes. No study evaluated the effect of video decision aids when integrated into clinical care. Conclusions Video decision aids may improve some ACP-related outcomes. Before recommending their use in clinical practice, more evidence is needed to confirm these findings and

  8. 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

  9. Implementing clinical practice guidelines about health promotion and disease prevention through shared decision making.

    PubMed

    Politi, Mary C; Wolin, Kathleen Y; Légaré, France

    2013-06-01

    Clinical practice guidelines aim to improve the health of patients by guiding individual care in clinical settings. Many guidelines specifically about health promotion or primary disease prevention are beginning to support informed patient choice, and suggest that clinicians and patients engage in shared discussions to determine how best to tailor guidelines to individuals. However, guidelines generally do not address how to translate evidence from the population to the individual in clinical practice, or how to engage patients in these discussions. In addition, they often fail to reconcile patients' preferences and social norms with best evidence. Shared decision making (SDM) is one solution to bridge guidelines about health promotion and disease prevention with clinical practice. SDM describes a collaborative process between patients and their clinicians to reach agreement about a health decision involving multiple medically appropriate treatment options. This paper discusses: 1) a brief overview of SDM; 2) the potential role of SDM in facilitating the implementation of prevention-focused practice guidelines for both preference-sensitive and effective care decisions; and 3) avenues for future empirical research to test how best to engage individual patients and clinicians in these complex discussions about prevention guidelines. We suggest that SDM can provide a structure for clinicians to discuss clinical practice guidelines with patients in a way that is evidence-based, patient-centered, and incorporates patients' preferences. In addition to providing a model for communicating about uncertainty at the individual level, SDM can provide a platform for engaging patients in a conversation. This process can help manage patients' and clinicians' expectations about health behaviors. SDM can be used even in situations with strong evidence for benefits at the level of the population, by helping patients and clinicians prioritize behaviors during time-pressured medical

  10. 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

  11. 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

  12. Application of a diagnosis-based clinical decision guide in patients with neck pain

    PubMed Central

    2011-01-01

    Background Neck pain (NP) is a common cause of disability. Accurate and efficacious methods of diagnosis and treatment have been elusive. 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 guide in applying 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 NP. Methods Demographic, diagnostic and baseline outcome measure data were gathered on a cohort of NP patients examined by one of three examiners trained in the application of the DBCDG. Results Data were gathered on 95 patients. Signs of visceral disease or potentially serious illness were found in 1%. Centralization signs were found in 27%, segmental pain provocation signs were found in 69% and radicular signs were found in 19%. Clinically relevant myofascial signs were found in 22%. Dynamic instability was found in 40%, oculomotor dysfunction in 11.6%, fear beliefs in 31.6%, central pain hypersensitivity in 4%, passive coping in 5% and depression in 2%. 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, oculomotor dysfunction, poor coping and depression, correlations and patterns among the diagnostic components of the DBCDG as well as inter-examiner reliability, validity and efficacy of treatment based on the DBCDG. PMID:21871119

  13. 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

  14. 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

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

    PubMed

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

    2016-06-01

    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. [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

  17. 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

  18. 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

  19. 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

  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. 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

  2. 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

  3. A proposed clinical decision support architecture capable of supporting whole genome sequence information.

    PubMed

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

    2014-04-01

    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

  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. 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. PMID:20949381

  6. 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

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

    PubMed Central

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

    2016-01-01

    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. PMID:26508168

  8. 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. PMID:25834725

  9. 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.

  10. Design, Development, and Initial Evaluation of a Terminology for Clinical Decision Support and Electronic Clinical Quality Measurement

    PubMed Central

    Lin, Yanhua; Staes, Catherine J; Shields, David E; Kandula, Vijay; Welch, Brandon M; Kawamoto, Kensaku

    2015-01-01

    When coupled with a common information model, a common terminology for clinical decision support (CDS) and electronic clinical quality measurement (eCQM) could greatly facilitate the distributed development and sharing of CDS and eCQM knowledge resources. To enable such scalable knowledge authoring and sharing, we systematically developed an extensible and standards-based terminology for CDS and eCQM in the context of the HL7 Virtual Medical Record (vMR) information model. The development of this terminology entailed three steps: (1) systematic, physician-curated concept identification from sources such as the Health Information Technology Standards Panel (HITSP) and the SNOMED-CT CORE problem list; (2) concept de-duplication leveraging the Unified Medical Language System (UMLS) MetaMap and Metathesaurus; and (3) systematic concept naming using standard terminologies and heuristic algorithms. This process generated 3,046 concepts spanning 68 domains. Evaluation against representative CDS and eCQM resources revealed approximately 50–70% concept coverage, indicating the need for continued expansion of the terminology. PMID:26958220

  11. Design, Development, and Initial Evaluation of a Terminology for Clinical Decision Support and Electronic Clinical Quality Measurement.

    PubMed

    Lin, Yanhua; Staes, Catherine J; Shields, David E; Kandula, Vijay; Welch, Brandon M; Kawamoto, Kensaku

    2015-01-01

    When coupled with a common information model, a common terminology for clinical decision support (CDS) and electronic clinical quality measurement (eCQM) could greatly facilitate the distributed development and sharing of CDS and eCQM knowledge resources. To enable such scalable knowledge authoring and sharing, we systematically developed an extensible and standards-based terminology for CDS and eCQM in the context of the HL7 Virtual Medical Record (vMR) information model. The development of this terminology entailed three steps: (1) systematic, physician-curated concept identification from sources such as the Health Information Technology Standards Panel (HITSP) and the SNOMED-CT CORE problem list; (2) concept de-duplication leveraging the Unified Medical Language System (UMLS) MetaMap and Metathesaurus; and (3) systematic concept naming using standard terminologies and heuristic algorithms. This process generated 3,046 concepts spanning 68 domains. Evaluation against representative CDS and eCQM resources revealed approximately 50-70% concept coverage, indicating the need for continued expansion of the terminology. PMID:26958220

  12. 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).

  13. Referring periodontal patients: clinical decision making by dental and dental hygiene students.

    PubMed

    Williams, Karen B; Burgardt, Grayson J; Rapley, John W; Bray, Kimberly K; Cobb, Charles M

    2014-03-01

    Referral of periodontal patients requires development of a complex set of decision making skills. This study was conducted to determine criteria used by dental and dental hygiene students regarding the referral of periodontal patients for specialty care. Using mixed methods, a thirteen-item survey was developed to elicit the students' perceptions of their knowledge, confidence regarding managing patients, and clinical reasoning related to periodontal patients. The instrument was administered during the summer prior to (T1) and at the end of the students' final year (T2) of training. Seventy-nine dental students (81 percent of total class) and thirty dental hygiene students (83 percent of total class) completed T1. At T2, forty-two dental (44 percent of total class) and twenty-six dental hygiene students (87 percent of total class) completed the questionnaire. While 90 percent of dental and 96 percent of dental hygiene respondents reported a willingness to refer patients with active disease to specialists, only 40 percent of dental and 36 percent of dental hygiene respondents reported confidence in diagnosing, treating, and appropriately referring such patients. The students' ability to recognize critical disease and risk factors influencing referral was good; however, clinical application of that knowledge indicated a gap between knowledge and applied reasoning. The students' attitudes about the importance of periodontal disease and their perceived competence to identify critical disease risk factors were not significantly related (p>0.05) to correct clinical decisions in the case scenarios. The study concludes that dental and dental hygiene curricula should emphasize both the acquisition and application of knowledge regarding criteria for referral of periodontal patients. PMID:24609346

  14. 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…

  15. 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

  16. 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

  17. 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

  18. 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.

  19. Perspectives on clinical possibility: elements of analysis.

    PubMed

    Chiffi, Daniele; Zanotti, Renzo

    2016-08-01

    Possibility is one of the most common modalities in reasoning and argumentation. Various kinds of modal concepts have been identified in philosophical and logical discussion of the metaphysics of modality. We focus here on the concept of clinical possibility. A critical analysis of what is intended as clinical possibility has not yet received sufficient examination, although the concept is extensively used in clinical reasoning. We present arguments to emphasize some desirable features associated with the concept of clinical possibility. We argue that almost all clinical possibilities are potentialities, that is, possibilities that may be actualized by effective, appropriate and feasible interventions. However, in some limited cases, even mere possibilities - which may or may not be actualized, since we do not have the required knowledge - may be involved in clinical reasoning, and we present some examples in this paper. We then introduce some basic views on the nature of possibility showing their validity and limitations when applied to the concept of clinical possibility. Lastly, we conjecture that clinical possibility is a normative modality that can be formalized in a multimodal system with epistemic and deontic logical operators. PMID:26314392

  20. 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

  1. Longitudinal feasibility of MINDSET: a clinic decision aid for epilepsy self-management.

    PubMed

    Begley, Charles; Shegog, Ross; Harding, Angelique; Goldsmith, Corey; Hope, Omotola; Newmark, Michael

    2015-03-01

    The purpose of this paper is to report on the development and feasibility of the longitudinal version of MINDSET, a clinical tool to assist patients and health-care providers in epilepsy self-management. A previous study described the feasibility of using MINDSET to identify and prioritize self-management issues during a clinic visit. This paper describes the development of the longitudinal version of MINDSET and feasibility test over multiple visits with a printed action plan for goal setting and the capacity for monitoring changes in self-management. Feasibility was assessed based on 1) postvisit patient and provider interviews addressing ease of use and usefulness, patient/provider communication, and shared decision-making and 2) the capacity of the tool to monitor epilepsy characteristics and self-management over time. Results indicate MINDSET feasibility for 1) identifying and facilitating discussion of self-management issues during clinic visits, 2) providing a printable list of prioritized issues and tailored self-management goals, and 3) tracking changes in epilepsy characteristics and self-management over time. PMID:25705825

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

    PubMed

    Cheng, Chih-Wen; 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

  3. 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. PMID:26669601

  4. 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. PMID:22342733

  5. 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.

  6. Identification of metabolic syndrome using decision tree analysis.

    PubMed

    Worachartcheewan, Apilak; Nantasenamat, Chanin; Isarankura-Na-Ayudhya, Chartchalerm; Pidetcha, Phannee; Prachayasittikul, Virapong

    2010-10-01

    This study employs decision tree as a decision support system for rapid and automated identification of individuals with metabolic syndrome (MS) among a Thai population. Results demonstrated strong predictivity of the decision tree in classification of individuals with and without MS, displaying an overall accuracy in excess of 99%. PMID:20619912

  7. 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…

  8. School-Leaving Decisions in Australia: A Cohort Analysis

    ERIC Educational Resources Information Center

    Le, Anh T.; Miller, Paul W.

    2004-01-01

    The decision to invest in education is influenced by a large number of economic, social, family, personal and institutional factors. Many of these changed in Australia during the 1970s and 1980s. Several of the more important of these changes, such as the Equal Pay for Equal Work decision of 1969, the Equal Pay for Work of Equal Value decision of…

  9. Shared Surgical Decision Making and Youth Resilience Correlates of Satisfaction With Clinical Outcomes.

    PubMed

    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

    2015-07-01

    The aim of this study was to identify factors associated with youth satisfaction with surgical procedures performed to address oral cleft or craniofacial conditions (CFCs). 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. A total of 203 youth between the ages of 11 and 18 years (mean age = 14.5, standard deviation = 2.0, 61% male participants, 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 < 0.001). 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

  10. 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.

  11. 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.

  12. 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. PMID:19361022

  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. PMID:25992507

  14. 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

  15. 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. PMID:25325996

  16. 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…

  17. Computerised clinical decision support systems to improve medication safety in long-term care homes: a systematic review

    PubMed Central

    Marasinghe, Keshini Madara

    2015-01-01

    Objectives Computerised clinical decision support systems (CCDSS) are used to improve the quality of care in various healthcare settings. This systematic review evaluated the impact of CCDSS on improving medication safety in long-term care homes (LTC). Medication safety in older populations is an important health concern as inappropriate medication use can elevate the risk of potentially severe outcomes (ie, adverse drug reactions, ADR). With an increasing ageing population, greater use of LTC by the growing ageing population and increasing number of medication-related health issues in LTC, strategies to improve medication safety are essential. Methods Databases searched included MEDLINE, EMBASE, Scopus and Cochrane Library. Three groups of keywords were combined: those relating to LTC, medication safety and CCDSS. One reviewer undertook screening and quality assessment. Results Overall findings suggest that CCDSS in LTC improved the quality of prescribing decisions (ie, appropriate medication orders), detected ADR, triggered warning messages (ie, related to central nervous system side effects, drug-associated constipation, renal insufficiency) and reduced injury risk among older adults. Conclusions CCDSS have received little attention in LTC, as attested by the limited published literature. With an increasing ageing population, greater use of LTC by the ageing population and increased workload for health professionals, merely relying on physicians’ judgement on medication safety would not be sufficient. CCDSS to improve medication safety and enhance the quality of prescribing decisions are essential. Analysis of review findings indicates that CCDSS are beneficial, effective and have potential to improve medication safety in LTC; however, the use of CCDSS in LTC is scarce. Careful assessment on the impact of CCDSS on medication safety and further modifications to existing CCDSS are recommended for wider acceptance. Due to scant evidence in the current literature

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

    PubMed Central

    Ambigapathy, Ranjini; Ng, Chirk Jenn

    2016-01-01

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

  19. 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

  20. 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

  1. 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.

  2. Selection of diagnostic tests for clinical decision making and translation to a problem oriented medical record.

    PubMed

    Realdi, Giuseppe; Previato, Lorenzo; Vitturi, Nicola

    2008-07-01

    The leading function of the physician is the clinical reasoning, which involves appropriate investigation of the problems of the patient, formulation of a diagnostic suspect based on the patient's symptoms and signs, gathering of additional relevant information, to select necessary tests and administration of the most suitable therapy. The problems of the patient are expressed by symptoms or signs or abnormal test results, requested for a variety of reasons. The entire scientific, as well as diagnostic approach, is based on three steps: to stumble in a problem; to try a solution through a hypothesis; to disprove or to prove the hypothesis by a process of criticism. Clinicians use the information obtained from the history and physical examination to estimate initial (or pre-test) probability and then use the results from tests and other diagnostic procedures to modify this probability until the post-test probability is such that the suspected diagnosis is either confirmed or ruled out. When the pre-test probability of disease is high, tests characterized by high specificity will be preferred, in order to confirm the diagnostic suspect. When the pre-test probability of disease is low, a test with high sensitivity is advisable to exclude the hypothetical disease. The above mentioned process of decision making has been transferred to a problem oriented medical record that is currently employed in our Clinic. PMID:18420030

  3. 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. PMID:27139380

  4. 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

  5. A framework for genomic biomarker actionability and its use in clinical decision making

    PubMed Central

    Janku, Filip; Garrido-Laguna, Ignacio; Munoz, Javier; Schwab, Richard; Subbiah, Vivek; Rodon, Jordi; Kurzrock, Razelle

    2014-01-01

    The increasing scope and availability of genetic testing options for patients suffering from cancer has raised questions about how to use results of molecular diagnostics to inform patient care. For some biomarkers (e.g. BRAF mutations in melanoma), standards exist that outline treatments for individuals harboring aberrations in the biomarker; however for the vast majority of genomic abnormalities, few guidelines exist. Clinical decision making and the therapeutic approach for a patient with a given cancer characterized by aberrations in different genes may be aided by the use of a biomarker actionability framework that provides levels of evidence regarding whether and how a molecular abnormality can be considered a therapeutically relevant biomarker. A gene may be considered theoretically actionable if it has a basis of actionability, such that clinically available drugs can target a gene product that drives the cancer or is differentially expressed in tumor versus normal elements. Herein, we discuss a possible framework for developing guidelines for actionability, as they relate to genomically-based cancer therapeutics. PMID:25593991

  6. Clinical decision support for imaging in the era of the Patient Protection and Affordable Care Act.

    PubMed

    Zafar, Hanna M; Mills, Angela M; Khorasani, Ramin; Langlotz, Curtis P

    2012-12-01

    Imaging clinical decision support (CDS) systems provide evidence for or against imaging procedures ordered within a computerized physician order entry system at the time of the image order. Depending on the pertinent clinical history provided by the ordering clinician, CDS systems can optimize imaging by educating providers on appropriate image order entry and by alerting providers to the results of prior, potentially relevant imaging procedures, thereby reducing redundant imaging. The American Recovery and Reinvestment Act (ARRA) has expedited the adoption of computerized physician order entry and CDS systems in health care through the creation of financial incentives and penalties to promote the "meaningful use" of health IT. Meaningful use represents the latest logical next step in a long chain of legislation promoting the areas of appropriate imaging utilization, accurate reporting, and IT. It is uncertain if large-scale implementation of imaging CDS will lead to improved health care quality, as seen in smaller settings, or to improved patient outcomes. However, imaging CDS enables the correlation of existing imaging evidence with outcome measures, including morbidity, mortality, and short-term imaging-relevant management outcomes (eg, biopsy, chemotherapy). The purposes of this article are to review the legislative sequence relevant to imaging CDS and to give guidance to radiology practices focused on quality and financial performance improvement during this time of accelerating regulatory change. PMID:23206649

  7. [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. PMID:25666087

  8. 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

  9. 75 FR 35457 - Draft of the 2010 Causal Analysis/Diagnosis Decision Information System (CADDIS)

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-06-22

    ... AGENCY Draft of the 2010 Causal Analysis/Diagnosis Decision Information System (CADDIS) AGENCY... period for the draft Web site, ``2010 release of the Causal Analysis/Diagnosis Decision Information... analysis; examples and applications; a library of conceptual models; and an online application...

  10. 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...

  11. 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

  12. A clinical decision aid for the selection of antithrombotic therapy for the prevention of stroke due to atrial fibrillation

    PubMed Central

    LaHaye, Stephen Andrew; Gibbens, Sabra Lynn; Ball, David Gerald Andrew; Day, Andrew George; Olesen, Jonas Bjerring; Skanes, Allan Cameron

    2012-01-01

    Aims The availability of new antithrombotic agents, each with a unique efficacy and bleeding profile, has introduced a considerable amount of clinical uncertainty with physicians. We have developed a clinical decision aid in order to assist clinicians in determining an optimal antithrombotic regime for the prevention of stroke in patients who are newly diagnosed with non-valvular atrial fibrillation. Methods and results The CHA2DS2-VASc and HAS-BLED scoring systems were used to assess patients’ baseline risks of stroke and major bleeding, respectively. The relative risks of stroke and major bleeding for each antithrombotic agent were then used to identify the agent associated with the lowest net risk. Individual patient factors such as the treatment threshold, bleeding ratio, and cost threshold modified the recommendations in order to generate a final recommendation. By considering both patient factors and clinical research concurrently, this clinical decision aid is able to provide specific advice to clinicians regarding an optimal stroke prevention strategy. The resulting treatment recommendation tables are consistent with the recommendations of the European Society of Cardiology and Canadian Cardiovascular Society Guidelines, which can be incorporated into either a paper-based or electronic format to allow clinicians to have decision support at the point of care. Conclusion The use of a clinical decision aid that considers both patient factors and evidence-based medicine will serve to bridge the knowledge gap and provide practical guidance to clinicians in the prevention of stroke due to atrial fibrillation. PMID:22752615

  13. 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

  14. Eliminating Healthcare Disparities Via Mandatory Clinical Decision Support: The Venous Thromboembolism (VTE) Example

    PubMed Central

    Lau, Brandyn D.; Haider, Adil H.; Streiff, Michael B.; Lehmann, Christoph U.; Kraus, Peggy S.; Hobson, Deborah B.; Kraenzlin, Franca S.; Zeidan, Amer M.; Pronovost, Peter J.; Haut, Elliott R.

    2014-01-01

    Background All hospitalized patients should be assessed for VTE risk factors and prescribed appropriate prophylaxis. To improve best-practice VTE prophylaxis prescription for all hospitalized patients, we implemented a mandatory computerized clinical decision support (CCDS) tool. The tool requires completion of checklists to evaluate VTE risk factors and contraindications to pharmacologic prophylaxis, and then recommends the risk-appropriate VTE prophylaxis regimen. Objectives To examine the effect of a quality improvement intervention on race- and gender-based healthcare disparities across two distinct clinical services. Research Design Retrospective cohort study of a quality improvement intervention Subjects 1942 hospitalized medical patients and 1599 hospitalized adult trauma patients Measures Proportion of patients prescribed risk-appropriate, best-practice VTE prophylaxis Results Racial disparities existed in prescription of best-practice VTE prophylaxis in the pre-implementation period between black and white patients on both the trauma (70.1% vs. 56.6%, p=0.025) and medicine (69.5% vs. 61.7%, p=0.015) services. After implementation of the CCDS tool, compliance improved for all patients and disparities in best-practice prophylaxis prescription between black and white patients were eliminated on both services: trauma (84.5% vs. 85.5%, p=0.99) and medicine (91.8% vs. 88.0%, p=0.082). Similar findings were noted for gender disparities in the trauma cohort. Conclusions Despite the fact that risk-appropriate prophylaxis should be prescribed equally to all hospitalized patients regardless of race and gender, practice varied widely prior to our quality improvement intervention. Our CCDS tool eliminated racial disparities in VTE prophylaxis prescription across two distinct clinical services. Health information technology approaches to care standardization are effective to eliminate healthcare disparities. PMID:25373403

  15. 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

  16. 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. PMID:26718820

  17. Clinical benefits of a multivariable prediction model for bladder cancer: a decision analytic approach

    PubMed Central

    Vickers, Andrew J; Cronin, Angel M; Kattan, Michael W; Gonen, Mithat; Scardino, Peter T; Milowsky, Matthew I.; Dalbagni, Guido; Bochner, Bernard H.

    2009-01-01

    Background Multivariable prediction models have been shown to predict cancer outcomes more accurately than cancer stage. The effects on clinical management are unclear. We aimed to determine whether a published multivariable prediction model for bladder cancer (“bladder nomogram”) improves medical decision making, using referral for adjuvant chemotherapy as a model. Methods We analyzed data from an international cohort study of 4462 patients undergoing cystectomy without chemotherapy 1969 – 2004. The number of patients eligible for chemotherapy was determined using pathologic stage criteria (lymph node positive or stage pT3 or pT4), and for three cut-offs on the bladder nomogram (10%, 25% and 70% risk of recurrence with surgery alone). The number of recurrences was calculated by applying a relative risk reduction to eligible patients' baseline risk. Clinical net benefit was then calculated by combining recurrences and treatments, weighting the latter by a factor related to drug tolerability. Results A nomogram cut-off outperformed pathologic stage for chemotherapy for every scenario of drug effectiveness and tolerability. For a drug with a relative risk of 0.80, where clinicians would treat no more than 20 patients to prevent one recurrence, use of the nomogram was equivalent to a strategy that resulted in 60 fewer chemotherapy treatments per 1000 patients without any increase in recurrence rates. Conclusions Referring cystectomy patients to adjuvant chemotherapy on the basis of a multivariable model is likely to lead to better patient outcomes than the use of pathological stage. Further research is warranted to evaluate the clinical effects of multivariable prediction models. PMID:19823979

  18. 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

  19. 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

  20. Using Case Study Analysis and Case Writing to Structure Clinical Experiences in a Teacher Education Program

    ERIC Educational Resources Information Center

    Floyd, Deborah M.; Bodur, Yasar

    2005-01-01

    This study reports on the design and results of a two-semester study on the use of case study analysis and case writing in clinical experiences in an undergraduate teacher education program. Findings indicated that structured experiences with case studies and case writing increase preservice teachers' informed decision making on educational…

  1. NIPT in a clinical setting: an analysis of uptake in the first months of clinical availability.

    PubMed

    Taylor, Joanne B; Chock, Valerie Y; Hudgins, Louanne

    2014-02-01

    The objective of our study was to describe the clinical experience in offering noninvasive prenatal testing (NIPT) for aneuploidy to pregnant patients, highlighting the clinical utility, barriers to acceptance and limitations of this novel test. Data were collected from 961 patients offered NIPT from 3/1/12 to 9/30/12. Univariate and multivariate logistic regression analysis was performed. Twenty-eight percent of patients elected NIPT and 72 % declined. Women continue to elect less sensitive and less specific screening through biochemical markers and nuchal translucency. Women considering all options at average risk for aneuploidy were less likely to accept NIPT testing than women who had a risk adjustment from an ultrasound marker or routine screening test. In our multi-ethnic population, Filipina women were significantly less likely to elect NIPT compared to other ethnicities. Five percent of NIPT ordered failed analysis. Several chromosome abnormalities were detected through CVS or amniocentesis that would not have been detected by NIPT. Even though NIPT offers a non-invasive, highly sensitive and specific analysis for aneuploidy, the majority of women in our study declined this option. NIPT should be offered in the context of genetic counseling so that women understand the limitations of the testing and make an educated decision about the testing option best suited to their situation. PMID:23723049

  2. Impact of Health Information Exchange on Emergency Medicine Clinical Decision Making

    PubMed Central

    Gordon, Bradley D.; Bernard, Kyle; Salzman, Josh; Whitebird, Robin R.

    2015-01-01

    Introduction The objective of the study was to understand the immediate utility of health information exchange (HIE) on emergency department (ED) providers by interviewing them shortly after the information was retrieved. Prior studies of physician perceptions regarding HIE have only been performed outside of the care environment. Methods Trained research assistants interviewed resident physicians, physician assistants and attending physicians using a semi-structured questionnaire within two hours of making a HIE request. The responses were recorded, then transcribed for qualitative analysis. The transcribed interviews were analyzed for emerging qualitative themes. Results We analyzed 40 interviews obtained from 29 providers. Primary qualitative themes discovered included the following: drivers for requests for outside information; the importance of unexpected information; historical lab values as reference points; providing context when determining whether to admit or discharge a patient; the importance of information in refining disposition; improved confidence of provider; and changes in decisions for diagnostic imaging. Conclusion ED providers are driven to use HIE when they’re missing a known piece of information. This study finds two additional impacts not previously reported. First, providers sometimes find additional unanticipated useful information, supporting a workflow that lowers the threshold to request external information. Second, providers sometimes report utility when no changes to their existing plan are made as their confidence is increased based on external records. Our findings are concordant with previous studies in finding exchanged information is useful to provide context for interpreting lab results, making admission decisions, and prevents repeat diagnostic imaging. PMID:26759652

  3. 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…

  4. "Big data" needs an analysis of decision processes.

    PubMed

    Analytis, Pantelis P; Moussaïd, Mehdi; Artinger, Florian; Kämmer, Juliane E; Gigerenzer, Gerd

    2014-02-01

    We demonstrate by means of a simulation that the conceptual map presented by Bentley et al. is incomplete without taking into account people's decision processes. Within the same environment, two decision processes can generate strikingly different collective behavior; in two environments that fundamentally differ in transparency, a single process gives rise to virtually identical behavior. PMID:24572218

  5. 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

  6. 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....

  7. 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. ...

  8. 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. PMID:25630758

  9. Breath analysis: translation into clinical practice.

    PubMed

    Brodrick, Emma; Davies, Antony; Neill, Paul; Hanna, Louise; Williams, E Mark

    2015-06-01

    Breath analysis in respiratory disease is a non-invasive technique which has the potential to complement or replace current screening and diagnostic techniques without inconvenience or harm to the patient. Recent advances in ion mobility spectrometry (IMS) have allowed exhaled breath to be analysed rapidly, reliably and robustly thereby facilitating larger studies of exhaled breath profiles in clinical environments. Preliminary studies have demonstrated that volatile organic compound (VOC) breath profiles of people with respiratory disease can be distinguished from healthy control groups but there is a need to validate, standardise and ensure comparability between laboratories before real-time breath analysis becomes a clinical reality. It is also important that breath sampling procedures and methodologies are developed in conjunction with clinicians and the practicalities of working within the clinical setting are considered to allow the full diagnostic potential of these techniques to be realised. A protocol is presented, which has been developed over three years and successfully deployed for quickly and accurately collecting breath samples from 323 respiratory patients recruited from 10 different secondary health care clinics. PMID:25971863

  10. Risk Analysis Based Business Rule Enforcement for Intelligent Decision Support

    NASA Astrophysics Data System (ADS)

    Vasilecas, Olegas; Smaizys, Aidas; Brazinskas, Ramunas

    Intelligent information systems are acting by structured rules and do not deal with possible impact on the business environment or future consequences. That is the main reason why automated decisions based on such rules cannot take responsibility and requires involvement or approval of dedicated business people. This limits decision automation possibilities in information systems. However, business rules describe business policy and represent business logics. This can be used in intelligent information systems, together with risk assessment model to simulate real business environment and evaluate possible impact of automated decisions, to support intelligent decision automation. The chapter proposes risk and business rule model integration to provide full intelligent decision automation model used for business rule enforcement and implementation into intelligent software systems of information systems.

  11. Decision analysis for prioritizing recommended energy conservation options

    SciTech Connect

    Meadows, K.L. ); Brothers, P.W. )

    1989-01-01

    Knowledge engineering techniques were used to study the decision process for choosing which of a set of recommended energy conservation options would be implemented. Building management decision-makers from both the private and public sectors were interviewed to gain an understanding of the decision-making process. Decision objectives were identified and the process computerized. Results of the study are twofold. The first is a formalization of the decision-making process. The formalization enables both efficient treatment of large numbers of objectives and demonstration of optimality in meeting objectives. Second, the knowledge-based system produced is programmed in a conventional programming environment rather than a rule-based expert system shell, demonstrating the range of applicability of knowledge engineering techniques.

  12. 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.

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

    PubMed

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

    2016-06-01

    Depression and anxiety during pregnancy are common, and patients and providers are faced with complex decisions regarding various treatment modalities. A structured discussion of the risks and benefits of options with the patient and her support team is recommended to facilitate the decision-making process. This clinically focused review, with emphasis on the last 3 years of published study data, evaluates the major risk categories of medication treatments, namely pregnancy loss, physical malformations, growth impairment, behavioral teratogenicity, and neonatal toxicity. Nonpharmacological treatment options, including neuromodulation and psychotherapy, are also briefly reviewed. Specific recommendations, drawn from the literature and the authors' clinical experience, are also offered to help guide the clinician in decision-making. PMID:27091646

  14. Benefits of probabilistic sensitivity analysis – a review of NICE decisions

    PubMed Central

    Adalsteinsson, Erpur; Toumi, Mondher

    2013-01-01

    Objective Since 2004, the National Institute of Health and Clinical Excellence (NICE) has required manufacturers to conduct a probabilistic sensitivity analysis (PSA) in their technology appraisals. The objective of this review is to assess the cost-effectiveness of different technology appraisals and compare them with the actual decision made by the NICE based on PSA. Methods The search term ‘probabilistic sensitivity analysis’ was used on the NICE home page (25 January 2012). The appraisals identified in the search were assessed and subjected to further review, if a probability of being cost-effective was provided, regardless of the threshold indicated. If several probabilities were provided, the number provided by the evidence review group was used. If several scenarios were presented, the base case scenario was chosen. Finally, the probabilities of being cost-effective were compared with the actual decision made, which could result in two outcomes: recommended or not recommended. Results A total of 31 assessments were included for the final review. The results were plotted on a graph to illustrate whether there was a relationship between the PSA outcomes and the final recommendation. The assessments were ranked according to their probability of being cost-effective. Conclusion A higher probability of a technology being cost-effective was correlated with more positive decision-making. There appeared to be a clear threshold at which technologies with a 40% certainty of being cost-effective tended to be recommended, whereas those below the threshold were not recommended. The reports suggested that the incremental cost-effectiveness ratios (ICER) estimate was not a robust driver of decision-making. A NICE applicant should pay increased attention to the PSA in addition to the ICER estimate.

  15. 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…

  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. 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

  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. PMID:23304315

  19. 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

  20. 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, there is a need for better tools for decision making and validation of efficacy and safety of new compounds. Numerous biological markers (biomarkers) have been proposed either as adjunct to current clinical endpoints or as surrogates. Imaging biomarkers are among rapidly increasing biomarkers, being examined to expedite effective and rational drug development. Clinical imaging often involves a complex set of multi-modality data sets that require rapid and objective analysis, independent of reviewer's bias and training. In this chapter, an overview of imaging biomarkers for drug development is offered, along with challenges that necessitate quantitative and objective image analysis. Examples of automated and semi-automated analysis approaches are provided, along with technical review of such methods. These examples include the use of 3D MRI for osteoarthritis, ultrasound vascular imaging, and dynamic contrast enhanced MRI for oncology. Additionally, a brief overview of regulatory requirements is discussed. In conclusion, this chapter highlights key challenges and future directions in this area.

  1. 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

  2. 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

    2016-01-01

    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

  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. Use of probabilistic methods for analysis of cost and duration uncertainties in a decision analysis framework

    SciTech Connect

    Boak, D.M.; Painton, L.

    1995-12-08

    Probabilistic forecasting techniques have been used in many risk assessment and performance assessment applications on radioactive waste disposal projects such as Yucca Mountain and the Waste Isolation Pilot Plant (WIPP). Probabilistic techniques such as Monte Carlo and Latin Hypercube sampling methods are routinely used to treat uncertainties in physical parameters important in simulating radionuclide transport in a coupled geohydrologic system and assessing the ability of that system to comply with regulatory release limits. However, the use of probabilistic techniques in the treatment of uncertainties in the cost and duration of programmatic alternatives on risk and performance assessment projects is less common. Where significant uncertainties exist and where programmatic decisions must be made despite existing uncertainties, probabilistic techniques may yield important insights into decision options, especially when used in a decision analysis framework and when properly balanced with deterministic analyses. For relatively simple evaluations, these types of probabilistic evaluations can be made using personal computer-based software.

  5. Analysis of Search on Clinical Narrative within the EHR

    ERIC Educational Resources Information Center

    Natarajan, Karthik

    2012-01-01

    Electronic Health Records (EHRs) are used increasingly in the hospital and outpatient settings, and patients are amassing digitized clinical information. On one hand, aggregating all the patient's clinical information can greatly assist health care workers in making sound decisions. On the other hand, it can result in information overload,…

  6. 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.

  7. Clinical Decision Support System to Enhance Quality Control of Spirometry Using Information and Communication Technologies

    PubMed Central

    2014-01-01

    Background We recently demonstrated that quality of spirometry in primary care could markedly improve with remote offline support from specialized professionals. It is hypothesized that implementation of automatic online assessment of quality of spirometry using information and communication technologies may significantly enhance the potential for extensive deployment of a high quality spirometry program in integrated care settings. Objective The objective of the study was to elaborate and validate a Clinical Decision Support System (CDSS) for automatic online quality assessment of spirometry. Methods The CDSS was done through a three step process including: (1) identification of optimal sampling frequency; (2) iterations to build-up an initial version using the 24 standard spirometry curves recommended by the American Thoracic Society; and (3) iterations to refine the CDSS using 270 curves from 90 patients. In each of these steps the results were checked against one expert. Finally, 778 spirometry curves from 291 patients were analyzed for validation purposes. Results The CDSS generated appropriate online classification and certification in 685/778 (88.1%) of spirometry testing, with 96% sensitivity and 95% specificity. Conclusions Consequently, only 93/778 (11.9%) of spirometry testing required offline remote classification by an expert, indicating a potential positive role of the CDSS in the deployment of a high quality spirometry program in an integrated care setting. PMID:25600957

  8. 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

  9. Molecular profiling of liver tumors: classification and clinical translation for decision making.

    PubMed

    Pinyol, Roser; Nault, Jean Charles; Quetglas, Iris M; Zucman-Rossi, Jessica; Llovet, Josep M

    2014-11-01

    Hepatocellular carcinoma (HCC) is a complex disease with a dismal prognosis. Consequently, a translational approach is required to personalized clinical decision making to improve survival of HCC patients. Molecular signatures from cirrhotic livers and single nucleotide polymorphism have been linked with HCC occurrence. Identification of high-risk populations will be useful to design chemopreventive trials. In addition, molecular signatures derived from tumor and nontumor samples are associated with early tumor recurrence due to metastasis and late tumor recurrence due to de novo carcinogenesis after curative treatment, respectively. Identification of patients with a high risk of relapse will guide adjuvant randomized trials. The genetic landscape drawn by next-generation sequencing has highlighted the genomic diversity of HCC. Genetic drivers recurrently mutated belong to different signaling pathways including telomere maintenance, cell-cycle regulators, chromatin remodeling, Wnt/b-catenin, RAS/RAF/MAPK kinase, and AKT/mTOR pathway. These cancer genes will be ideally targeted by biotherapies as a paradigm of stratified medicine adapted to tumor biology. PMID:25369299

  10. Evolution of a knowledge base for a clinical decision support system encoded in the Arden Syntax.

    PubMed Central

    Jenders, R. A.; Huang, H.; Hripcsak, G.; Clayton, P. D.

    1998-01-01

    Clinical decision support systems (CDSS) are being used increasingly in medical practice. Thus, long-term maintenance of the knowledge bases (KB) of such systems becomes important. To quantify changes that occur as a KB evolves, we studied the KB at the Columbia-Presbyterian Medical Center. This KB has a total of 229 Medical Logic Modules (MLMs) encoded in the Arden Syntax. Eliminating those never used in practice, we retrospectively analyzed 156 MLMs developed over 78 months. We noted 2020 distinct versions of these MLMs that included 5528 changed statements over time. These changes occurred primarily in the logic slot (38.7% of all changes), the action slot (17.8%), in queries (15.0%) and in the data slot exclusive of queries (12.4%). We conclude that long-term maintenance of a KB for a CDSS requires significant changes over time. We discuss the implications of these results for the design of KB editors for the Arden Syntax. PMID:9929281

  11. 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

  12. 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 m