The clinical decision analysis (CDA) has used to overcome complexity and uncertainty in medical problems. The CDA is a tool allowing decision-makers to apply evidence-based medicine to make objective clinical decisions when faced with complex situations. The usefulness and limitation including six steps in conducting CDA were reviewed. The application of CDA results should be done under shared decision with patients' value.
The clinical decision analysis (CDA) has used to overcome complexity and uncertainty in medical problems. The CDA is a tool allowing decision-makers to apply evidence-based medicine to make objective clinical decisions when faced with complex situations. The usefulness and limitation including six steps in conducting CDA were reviewed. The application of CDA results should be done under shared decision with patients’ value. PMID:25358466
Nurses' clinical decision-making is a complex process that holds potential to influence the quality of care provided and patient outcomes. The evolution of nurses' decision-making that occurs with experience has been well documented. In addition, literature includes numerous strategies and approaches purported to support development of nurses' clinical decision-making. There has been, however, significantly less attention given to the process of assessing nurses' clinical decision-making and novice clinical educators are often challenged with knowing how to best support nurses and nursing students in developing their clinical decision-making capacity. The Situated Clinical Decision-Making framework is presented for use by clinical educators: it provides a structured approach to analyzing nursing students' and novice nurses' decision-making in clinical nursing practice, assists educators in identifying specific issues within nurses' clinical decision-making, and guides selection of relevant strategies to support development of clinical decision-making. A series of questions is offered as a guide for clinical educators when assessing nurses' clinical decision-making. The discussion presents key considerations related to analysis of various decision-making components, including common sources of challenge and errors that may occur within nurses' clinical decision-making. An exemplar illustrates use of the framework and guiding questions. Implications of this approach for selection of strategies that support development of clinical decision-making are highlighted.
Rashotte, Judy; Carnevale, F A
The aim of this article is to explore the complex forms of knowledge involved in diagnostic and interventional decision making by comparing the processes in medicine and nursing, including nurse practitioners. Many authors assert that the practice of clinical decision making involves the application of theoretical knowledge (acquired in the classroom and textbooks) as well as research evidence, upon concrete particular cases. This approach draws on various universal principles and algorithms to facilitate the task. On the other hand, others argue that this involves an intuitive form of judgement that is difficult to teach, one that is acquired principally through experience. In an exploration of these issues, this article consists of three sections. A clarification of terms commonly used when discussing decision making is provided in the first section. In the second section, an epistemological analysis of decision making is presented by examining several perspectives and comparing them for their use in the nursing and medical literature. Bunge's epistemological framework for decision making (based on scientific realism) is explored for its fit with the aims of medicine and nursing. The final section presents a discussion of knowledge utilization and decision making as it relates to the implications for the education and ongoing development of nurse practitioners. It is concluded that Donald Schön's conception of reflective practice best characterizes the skillful conduct of clinical decision making.
Wong, J B; Moskowitz, A J; Pauker, S G
Many difficult medical decisions involve uncertainty. Decision analysis-an explicit, normative and analytic approach to making decisions under uncertainty-provides a probabilistic framework for exploring difficult problems in nondeterministic domains. As the methodology has advanced, clinical decision analysis has been applied to increasingly complex medical problems and disseminated widely in the medical literature. Unfortunately, this approach imposes a heavy computational burden on analysts. Microcomputer-based decision-support software can ease this burden.
Pradhan, Malcolm; Liaw, Siaw Teng
This chapter gives an educational overview of: * The elements of a clinical decision; * The elements of decision making: prior probability, evidence (likelihood), posterior probability, actions, utility (value); * A framework for decision making, and support, encompassing validity, utility, importance and certainty; and * The required elements of a clinical decision support system. * The role of knowledge management in the construction and maintenance of clinical decision support.
Georgeson, S.; Meyer, K.B.; Pauker, S.G. )
Decision analysis offers a reproducible, explicit approach to complex clinical decisions. It consists of developing a model, typically a decision tree, that separates choices from chances and that specifies and assigns relative values to outcomes. Sensitivity analysis allows exploration of alternative assumptions. Cost-effectiveness analysis shows the relation between dollars spent and improved health outcomes achieved. In a tutorial format, this approach is applied to the decision whether to perform coronary angiography in a patient who requires aortic valve replacement for critical aortic stenosis.
Theodossi, A; Spiegelhalter, D J; McFarlane, I G; Williams, R
Twelve doctors with special training in hepatology independently reviewed two to five cases each from a group of seven cases of complicated hepatobiliary problems. A doctor's willingness to take risks to improve his patients' health was quantified by a wagering technique based on the probability of achieving a successful intervention. These probabilities were then used to calculate "utilities," which represented the average opinion of the doctors about the relative worth of each of six predefined states of health. The results showed that, in the context of risky decisions for severely ill patients, a year of life was considered by the doctors to be worth 44% of a full recovery; being mobile for that year increased this value to 57%. Survival for up to five years with restricted mobility was considered to be worth 70% of a full recovery and the ability to work during that period increased this value to 85%. It is concluded that in clinical decision making the uncertainty and preferences implicit in a course of action can be quantified and thus made explicit.
Miller, Deborah J; Spengler, Elliot S; Spengler, Paul M
The overconfidence bias occurs when clinicians overestimate the accuracy of their clinical judgments. This bias is thought to be robust leading to an almost universal recommendation by clinical judgment scholars for clinicians to temper their confidence in clinical decision making. An extension of the Meta-Analysis of Clinical Judgment (Spengler et al., 2009) project, the authors synthesized over 40 years of research from 36 studies, from 1970 to 2011, in which the confidence ratings of 1,485 clinicians were assessed in relation to the accuracy of their judgments about mental health (e.g., diagnostic decision making, violence risk assessment, prediction of treatment failure) or psychological issues (e.g., personality assessment). Using a random effects model a small but statistically significant effect (r = .15; CI = .06, .24) was found showing that confidence is better calibrated with accuracy than previously assumed. Approximately 50% of the total variance between studies was due to heterogeneity and not to chance. Mixed effects and meta-regression moderator analyses revealed that confidence is calibrated with accuracy least when there are repeated judgments, and more when there are higher base rate problems, when decisions are made with written materials, and for earlier published studies. Sensitivity analyses indicate a bias toward publishing smaller sample studies with smaller or negative confidence-accuracy effects. Implications for clinical judgment research and for counseling psychology training and practice are discussed.
Greer, Marianne L.; Kirk, Kenneth W.
A computerized, simulation-based instrument, consisting of four community practice clinical scenarios, collected information-searching data and the students' decisions. The appropriateness of the decisions, assessed by three clinical judges, and the focus of information search, based on the computer-collected process data, were the dependent…
Bate, Louise; Hutchinson, Andrew; Underhill, Jonathan; Maskrey, Neal
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.
Poucheret, Patrick; Fons, Françoise; Doré, Jean Christophe; Michelot, Didier; Rapior, Sylvie
Ninety percent of fatal higher fungus poisoning is due to amatoxin-containing mushroom species. In addition to absence of antidote, no chemotherapeutic consensus was reported. The aim of the present study is to perform a retrospective multidimensional multivariate statistic analysis of 2110 amatoxin poisoning clinical cases, in order to optimize therapeutic decision-making. Our results allowed to classify drugs as a function of their influence on one major parameter: patient survival. Active principles were classified as first intention, second intention, adjuvant or controversial pharmaco-therapeutic clinical intervention. We conclude that (1) retrospective multidimensional multivariate statistic analysis of complex clinical dataset might help future therapeutic decision-making and (2) drugs such as silybin, N-acetylcystein and putatively ceftazidime are clearly associated, in amatoxin poisoning context, with higher level of patient survival.
Yang, Yea-Huei Kao; Lu, Christine Y.
Background This study quantitatively evaluated the comparative efficacy and safety of new oral anticoagulants (dabigatran, rivaroxaban, and apizaban) and warfarin for treatment of nonvalvular atrial fibrillation. We also compared these agents under different scenarios, including population with high risk of stroke and for primary vs. secondary stroke prevention. Methods We used multiple criteria decision analysis (MCDA) to assess the benefit-risk of these medications. Our MCDA models contained criteria for benefits (prevention of ischemic stroke and systemic embolism) and risks (intracranial and extracranial bleeding). We calculated a performance score for each drug accounting for benefits and risks in comparison to treatment alternatives. Results Overall, new agents had higher performance scores than warfarin; in order of performance scores: dabigatran 150 mg (0.529), rivaroxaban (0.462), apixaban (0.426), and warfarin (0.191). For patients at a higher risk of stroke (CHADS2 score≥3), apixaban had the highest performance score (0.686); performance scores for other drugs were 0.462 for dabigatran 150 mg, 0.392 for dabigatran 110 mg, 0.271 for rivaroxaban, and 0.116 for warfarin. Dabigatran 150 mg had the highest performance score for primary stroke prevention, while dabigatran 110 mg had the highest performance score for secondary prevention. Conclusions Our results suggest that new oral anticoagulants might be preferred over warfarin. Selecting appropriate medicines according to the patient’s condition based on information from an integrated benefit-risk assessment of treatment options is crucial to achieve optimal clinical outcomes. PMID:25897861
712 A/B: GPS Decision Analysis Process Revised title:___________________________________________________________________ Presented in (input and Bold...JUN 2005 2. REPORT TYPE N/A 3. DATES COVERED - 4. TITLE AND SUBTITLE GPS Decision Analysis Process 5a. CONTRACT NUMBER 5b. GRANT NUMBER...Prescribed by ANSI Std Z39-18 GPS Decision Analysis Process Nisha Shah The Boeing Company 73rd MORS Symposium US Military Academy – West Point 21-23
Morgado, P J; Alfaro, R; Morgado, P J; León, P
A retrospective study is presented of 119 patients admitted to the Central Hospital of the Venezuelan Institute of Social Security, in Caracas, between 1982 and 1990, with the diagnosis of colon trauma. Several parameters including age, etiology, time elapsed between the accident or assault and hospital admission, preoperative and postoperative hemoglobin and diastolic blood pressure, associated lesions, procedure practiced, complication rate, and hospital mortality are reviewed. The second and third decades of life appear most often involved. Most patients reached the hospital within the first four hours of the accident or assault. Anemia, sustained diastolic hypotension, and number of organs involved in addition to the colon were important prognostic factors for complications. Apparently the surgical procedure, with simple suture or resection, mostly without "protective" colostomy, was not very relevant. Hospital mortality was 2.4 percent. A staging system based on clinical conditions for decision making in the operating room was used in an attempt to inject some objectivity into the surgical approach.
Zhao, Lili; Woodworth, George
Chen and Chaloner (Statist. Med. 2006; 25:2956-2966. DOI: 10.1002/sim.2429) present a Bayesian stopping rule for a single-arm clinical trial with a binary endpoint. In some cases, earlier stopping may be possible by basing the stopping rule on the time to a binary event. We investigate the feasibility of computing exact, Bayesian, decision-theoretic time-to-event stopping rules for a single-arm group sequential non-inferiority trial relative to an objective performance criterion. For a conjugate prior distribution, exponential failure time distribution, and linear and threshold loss structures, we obtain the optimal Bayes stopping rule by backward induction. We compute frequentist operating characteristics of including Type I error, statistical power, and expected run length. We also briefly address design issues.
Thompson-Leduc, Philippe; Turcotte, Stéphane; Labrecque, Michel; Légaré, France
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
Wiener, Renda Soylemez; Walkey, Allan J.
Rationale: Factors and outcomes associated with end-of-life decision-making among patients during clinical trials in the intensive care unit are unclear. Objectives: We sought to determine patterns and outcomes of Do Not Resuscitate (DNR) decisions among critically ill patients with acute respiratory distress syndrome (ARDS) enrolled in a clinical trial. Methods: We performed a secondary analysis of data from the ARDS Network Fluid and Catheter Treatment Trial (FACTT), collected between 2000 and 2005. We calculated mortality outcomes stratified by code status, and compared baseline characteristics of patients who became DNR during the trial with participants who remained full code. Measurements and Main Results: Among 809 FACTT participants with a code status recorded, 232 (28.7%) elected DNR status. Specifically, 37 (15.9%) chose to withhold cardiopulmonary resuscitation alone, 44 (19.0%) elected to withhold some life support measures in addition to cardiopulmonary resuscitation, and 151 (65.1%) had life support withdrawn. Admission severity of illness as measured by APACHE III score was strongly associated with election of DNR status (odds ratio, 2.2; 95% confidence interval, 1.85–2.62; P < 0.0001). Almost all (97.0%; 225 of 232) patients who selected DNR status died, and 79% (225 of 284) of patients who died during the trial were DNR. Among patients who chose DNR status but did not elect withdrawal of life support, 91% (74 of 81) died. Conclusions: The vast majority of deaths among clinical trial patients with ARDS were preceded by a DNR order. Unlike other studies of end-of-life decision-making in the intensive care unit, nearly all patients who became DNR died. The impact of variation of practice in end-of-life decision-making during clinical trials warrants further study. PMID:25386717
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.
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
Wylie, C E; Shaw, D J; Verheyen, K L P; Newton, J R
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.
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
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.
Lacksonen, Thomas A.
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
Allegue, Catarina; Coll, Mònica; Mates, Jesus; Campuzano, Oscar; Iglesias, Anna; Sobrino, Beatriz; Brion, Maria; Amigo, Jorge; Carracedo, Angel; Brugada, Pedro; Brugada, Josep; Brugada, Ramon
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
Hogan, A.; Michel, J.; Localio, A.R.; Karavite, D.; Song, L.; Ramos, M.J.; Fiks, A.G.; Lorch, S.; Grundmeier, R.W.
Background and Objectives Palivizumab can reduce hospitalizations due to respiratory syncytial virus (RSV), but many eligible infants fail to receive the full 5-dose series. The efficacy of clinical decision support (CDS) in fostering palivizumab receipt has not been studied. We sought a comprehensive solution for identifying eligible patients and addressing barriers to palivizumab administration. Methods We developed workflow and CDS tools targeting patient identification and palivizumab administration. We randomized 10 practices to receive palivizumab-focused CDS and 10 to receive comprehensive CDS for premature infants in a 3-year longitudinal cluster-randomized trial with 2 baseline and 1 intervention RSV seasons. Results There were 356 children eligible to receive palivizumab, with 194 in the palivizumab-focused group and 162 in the comprehensive CDS group. The proportion of doses administered to children in the palivizumab-focused intervention group increased from 68.4% and 65.5% in the two baseline seasons to 84.7% in the intervention season. In the comprehensive intervention group, proportions of doses administered declined during the baseline seasons (from 71.9% to 62.4%) with partial recovery to 67.9% during the intervention season. The palivizumab-focused group improved by 19.2 percentage points in the intervention season compared to the prior baseline season (p < 0.001), while the comprehensive intervention group only improved 5.5 percentage points (p = 0.288). The difference in change between study groups was significant (p = 0.05). Conclusions Workflow and CDS tools integrated in an EHR may increase the administration of palivizumab. The support focused on palivizumab, rather than comprehensive intervention, was more effective at improving palivizumab administration. PMID:26767069
Crowell, Karen; Vardell, Emily
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.
Jahanpour, Faezeh; Sharif, Farkhondeh; Salsali, Mahvash; Kaveh, Mohammad H; Williams, Leonie M
Clinical decision-making is the basis for professional nursing practice. This can be taught and learned through appropriate teaching and clinical experiences. Unfortunately, it has been observed that many graduates are unable to demonstrate suitable clinical decision-making skills. Research and study on the process of decision-making and factors influencing it assists educators to find the appropriate educational and clinical strategies to teach nursing students. To explore the experience of nursing students and their view points regarding the factors influencing their development of clinical decision-making skills. An exploratory qualitative approach utilizing grounded theory methods was used; focus group interviews were undertaken with 32 fourth year nursing students and data were analysed using constant comparative analysis. Four main themes emerged from the data: clinical instructor incompetency, low self-efficacy, unconducive clinical learning climate and experiencing stress. The data indicated that students could not make clinical decisions independently. The findings of this study support the need to reform aspects of the curriculum in Iran in order to increase theory-practice integration and prepare a conductive clinical learning climate that enhances learning clinical decision-making with less stress.
Seright, Teresa J.
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…
By effectively closing the loop between the data, analytics, processes, and methods supporting business and clinical decision making, a healthcare organization closes the loop between its knowledge generation activities and its actions at the bedside: knowledge guiding actions, actions generating knowledge.
Snethen, Julia A; Broome, Marion E; Knafl, Kathleen; Deatrick, Janet A; Angst, Denise B
The decision-making process related to a child's participation in clinical trials often involves multiple family members. The aim of this study was to compare family patterns of decision-making within and across family units in pediatric clinical trials. Participants for this secondary analysis included 14 families from a larger study of informed consent. Four distinct patterns of decision-making were identified: Exclusionary, informative, collaborative, and delegated. These patterns varied with regard to three dimensions of parents' decision-making goals, child level of involvement, and the parental role. These patterns of decision-making affect how parents and children communicate with health professionals and influence the effectiveness of health care providers interactions with the family related to the decision-making process.
Campbell, Stephen M; Renfrew, Megan R; Marceau, Lisa D; Roland, Martin; McKinlay, John B
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
Liu, Brent; Documet, Jorge; McNitt-Gray, Sarah; Requejo, Phil; McNitt-Gray, Jill
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.
Dunger, Christine; Schnell, Martin W; Bausewein, Claudia
Introduction Decision-making (DM) in healthcare can be understood as an interactive process addressing decision makers' reasoning as well as their visible behaviour after the decision is made. Other key elements of DM are ethical aspects and the role as well as the treatment options of the examined professions. Nurses' DM to choose interventions in situations of severe breathlessness is such interactions. They are also ethically relevant regarding the vulnerability of affected patients and possible restrictions or treatment options. The study aims to explore which factors influence nurses' DM to use nursing interventions in situations where patients suffer from severe breathlessness. Methods and analysis Qualitative study including nurses in German hospital wards and hospices. A triangulation of different methods of data collection—participant observation and qualitative expert interviews—and analysis merge in a reflexive grounded theory approach which integrates Goffman's framework analysis. It allows an analysis of nurses' self-statements about DM, their behaviour in relevant clinical situations and its influences. Data collection and analysis will be examined simultaneously. Ethics and dissemination Informed consent will be gained from all participants and the institutional stakeholders. Ongoing consent has to be ensured since observations will take place in healthcare institutions and many patients will be highly vulnerable. The study has been evaluated and approved by the Witten/Herdecke University Ethics Committee, Witten, Germany. Results of the study will be published at congresses and in journal papers.
Prince, John R.
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.
González-Ferrer, A; Peleg, M; Marcos, M; Maldonado, J A
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.
Clinical Decision Support 1 Introduction The goal of the Clinical Decision Support Track is to retrieve relevant biomedical articles given a patient record...queries: • Diagnosis: "diagnosis"[MeSH Terms] OR "diagnosis, oral"[MeSH Terms] OR "diagnostic equipment "[MeSH Terms] OR "diagnostic services"[MeSH Terms...particular biomedical domain or search strategy) that were created as part of the CISMeF project3. The Test query was manually created for 3These and
Njie, Gibril J.; Proia, Krista K.; Thota, Anilkrishna B.; Finnie, Ramona K.C.; Hopkins, David P.; Banks, Starr M.; Callahan, David B.; Pronk, Nicolaas P.; Rask, Kimberly J.; Lackland, Daniel T.; Kottke, Thomas E.
Context Clinical decision support systems (CDSSs) can help clinicians assess cardiovascular disease (CVD) risk and manage CVD risk factors by providing tailored assessments and treatment recommendations based on individual patient data. The goal of this systematic review was to examine the effectiveness of CDSSs in improving screening for CVD risk factors, practices for CVD-related preventive care services such as clinical tests and prescribed treatments, and management of CVD risk factors. Evidence acquisition An existing systematic review (search period, January 1975–January 2011) of CDSSs for any condition was initially identified. Studies of CDSSs that focused on CVD prevention in that review were combined with studies identified through an updated search (January 2011–October 2012). Data analysis was conducted in 2013. Evidence synthesis A total of 45 studies qualified for inclusion in the review. Improvements were seen for recommended screening and other preventive care services completed by clinicians, recommended clinical tests completed by clinicians, and recommended treatments prescribed by clinicians (median increases of 3.8, 4.0, and 2.0 percentage points, respectively). Results were inconsistent for changes in CVD risk factors such as systolic and diastolic blood pressure, total and low-density lipoprotein cholesterol, and hemoglobin A1C levels. Conclusions CDSSs are effective in improving clinician practices related to screening and other preventive care services, clinical tests, and treatments. However, more evidence is needed from implementation of CDSSs within the broad context of comprehensive service delivery aimed at reducing CVD risk and CVD-related morbidity and mortality. PMID:26477805
Boney, Jo; Baker, Jacqueline D.
Research and a literature review suggest that nurses lack skills for effective clinical decision making. An educational program that facilitated development of critical thinking focused on four qualities: determining accuracy of information, determining bias, identifying inconsistencies in reasoning, and evaluating the strength of an argument. (SK)
Query Reformulation for Clinical Decision Support Search Luca Soldaini, Arman Cohan, Andrew Yates, Nazli Goharian, Ophir Frieder Information...work, we present a query reformulation approach that addresses the unique formulation of case reports, making them suitable to be used on a general... reformulation approach does not directly take into account the generic question type (diagnosis, test, treatment) provided with each approach. To ameliorate
Toriello, Paul J.; Leierer, Stephen J.
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…
Cresswell, Kathrin M; Lee, Lisa; Slee, Ann; Coleman, Jamie; Bates, David W; Sheikh, Aziz
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
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
Cooper, J. Arlin; Werner, Paul W.
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).
Banerjee, A.; Jadhav, S. L.; Bhawalkar, J. S.
Few clinicians grasp the true concept of probability expressed in the ‘P value.’ For most, a statistically significant P value is the end of the search for truth. In fact, the opposite is the case. The present paper attempts to put the P value in proper perspective by explaining different types of probabilities, their role in clinical decision making, medical research and hypothesis testing. PMID:21234167
Walker, Paul; Lovat, Terry
This paper is predicated on the understanding that clinical encounters between clinicians and patients should be seen primarily as inter-relations among persons and, as such, are necessarily moral encounters. It aims to relocate the discussion to be had in challenging medical decision-making situations, including, for example, as the end of life comes into view, onto a more robust moral philosophical footing than is currently commonplace. In our contemporary era, those making moral decisions must be cognizant of the existence of perspectives other than their own, and be attuned to the demands of inter-subjectivity. Applicable to clinical practice, we propose and justify a Habermasian approach as one useful means of achieving what can be described as dialogic consensus. The Habermasian approach builds around, first, his discourse theory of morality as universalizable to all and, second, communicative action as a cooperative search for truth. It is a concrete way to ground the discourse which must be held in complex medical decision-making situations, in its actual reality. Considerations about the theoretical underpinnings of the application of dialogic consensus to clinical practice, and potential difficulties, are explored.
Tams, Carl G; Euliano, Neil R
Clinical decision support systems are vital for advances in improving patient therapeutic care. We share lessons learned from creating two respiratory clinical decisions support systems for ventilating patients in a critical care setting.
Costs 89 5.3 Discussion of Constrained TDY-to- School Resources 90 5.4 Summary and Recommendations 93 6. Sensitivity Analysis 94 6.1 Methods 94 6.2...Analyzer Training 34 4.1 The ISEM-P Model 68 TABLE OF TABLES TablePage 5.1 25% Reduction in TDY-to- School Costs 76 5.2 25% Reduction in ABR Attendance 77 5.3...AFS 328X4 Reduced TDY-to- School 79 5.4 25% Reduction in ABR 328X4 Student Flow 79 5.5 Example Representative Site Training Capacity Results 81 5.6
I have attempted to use Feinstein's model of clinimetric indexes and his criteria as a focus for further development of measures that in physical therapy are currently considered "soft" or "subjective". I feel this development will enhance the body of knowledge by objectifying a portion of clinical assessment (eg, the patient's complaints, "subjective" portion of the POMR's SOAP format) that is in tremendous need of quantification. By making these "soft" data "hard," I feel we will enhance the decision-making power of clinicians.
Wright, Adam; Phansalkar, Shobha; Bloomrosen, Meryl; Jenders, Robert A.; Bobb, Anne M.; Halamka, John D.; Kuperman, Gilad; Payne, Thomas H.; Teasdale, S.; Vaida, A. J.; Bates, D. W.
Background Evidence demonstrates that clinical decision support (CDS) is a powerful tool for improving healthcare quality and ensuring patient safety. However, implementing and maintaining effective decision support interventions presents multiple technical and organizational challenges. Purpose To identify best practices for CDS, using the domain of preventive care reminders as an example. Methods We assembled a panel of experts in CDS and held a series of facilitated online and inperson discussions. We analyzed the results of these discussions using a grounded theory method to elicit themes and best practices. Results Eight best practice themes were identified as important: deliver CDS in the most appropriate ways, develop effective governance structures, consider use of incentives, be aware of workflow, keep content current, monitor and evaluate impact, maintain high quality data, and consider sharing content. Keys themes within each of these areas were also described. Conclusion Successful implementation of CDS requires consideration of both technical and socio-technical factors. The themes identified in this study provide guidance on crucial factors that need consideration when CDS is implemented across healthcare settings. These best practice themes may be useful for developers, implementers, and users of decision support. PMID:21991299
Carter, Kirsty; Monaghan, Sophie; O'Brien, John; Teodorczuk, Andrew; Mosimann, Urs; Taylor, John-Paul
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
Maloney, F.L.; Feblowitz, J.; Samal, L.; Sato, L.; Wright, A.
Summary Objective Identify clinical opportunities to intervene to prevent a malpractice event and determine the proportion of malpractice claims potentially preventable by clinical decision support (CDS). Materials and Methods Cross-sectional review of closed malpractice claims over seven years from one malpractice insurance company and seven hospitals in the Boston area. For each event, clinical opportunities to intervene to avert the malpractice event and the presence or absence of CDS that might have a role in preventing the event, were assigned by a panel of expert raters. Compensation paid out to resolve a claim (indemnity), was associated with each CDS type. Results Of the 477 closed malpractice cases, 359 (75.3%) were categorized as substantiated and 195 (54%) had at least one opportunity to intervene. Common opportunities to intervene related to performance of procedure, diagnosis, and fall prevention. We identified at least one CDS type for 63% of substantiated claims. The 41 CDS types identified included clinically significant test result alerting, diagnostic decision support and electronic tracking of instruments. Cases with at least one associated intervention accounted for $40.3 million (58.9%) of indemnity. Discussion CDS systems and other forms of health information technology (HIT) are expected to improve quality of care, but their potential to mitigate risk had not previously been quantified. Our results suggest that, in addition to their known benefits for quality and safety, CDS systems within HIT have a potential role in decreasing malpractice payments. Conclusion More than half of malpractice events and over $40 million of indemnity were potentially preventable with CDS. PMID:25298814
Ditkowsky, Jared B; Schwartzman, Kevin
Novel tuberculosis vaccines are in varying stages of pre-clinical and clinical development. This study seeks to estimate the potential cost-effectiveness of a BCG booster vaccine, while accounting for costs of large-scale clinical trials, using the MVA85A vaccine as a case study for estimating potential costs. We conducted a decision analysis from the societal perspective, using a 10-year time frame and a 3% discount rate. We predicted active tuberculosis cases and tuberculosis-related costs for a hypothetical cohort of 960,763 South African newborns (total born in 2009). We compared neonatal vaccination with bacille Calmette-Guérin alone to vaccination with bacille Calmette-Guérin plus a booster vaccine at 4 months. We considered booster efficacy estimates ranging from 40% to 70%, relative to bacille Calmette-Guérin alone. We accounted for the costs of Phase III clinical trials. The booster vaccine was assumed to prevent progression to active tuberculosis after childhood infection, with protection decreasing linearly over 10 years. Trial costs were prorated to South Africa's global share of bacille Calmette-Guérin vaccination. Vaccination with bacille Calmette-Guérin alone resulted in estimated tuberculosis-related costs of $89.91 million 2012 USD, and 13,610 tuberculosis cases in the birth cohort, over the 10 years. Addition of the booster resulted in estimated cost savings of $7.69-$16.68 million USD, and 2,800-4,160 cases averted, for assumed efficacy values ranging from 40%-70%. A booster tuberculosis vaccine in infancy may result in net societal cost savings as well as fewer active tuberculosis cases, even if efficacy is relatively modest and large scale Phase III studies are required.
LIFE SMOKING: CANCER, EMPHYSEMA, SHORTENED LIFE BATHING: FALLING, ELECTROCUTION CONTRACEPTION: DEATH , ILLNESS PREGNANCY: DEATH , ILLNESS ABORTION ...economic effect is the one with the highest probability of causing my death . -13- EXPECTED NET SYSTEM DESIGN BENEFIT TO ME DEATH DEATH (r A(excluding death ...0-AO81 424 STANFORD UNIV CALIF DEPT OF ENGtNEERING-ECONOM!C SYSTEMS F/6 12/1 LIFE ANDI DEATH DECISION ANALYSIS.CU) DEC 79 R A HOWARD N0OOIN-79-C-0036
Carney, Timothy Jay
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…
Maltsberger, John T.
Maintains that traditional mental status examination and clinical intuition or empathetic judgment are insufficient to predict suicide. Describes five components involved in the formulation of suicide risk: analysis of the patient's past response to stress, assessment of vulnerability to life-threatening affects, assessment of exterior sustaining…
Kim, Jaewhan; Nelson, Richard; Biskupiak, Joseph
Decision analysis is a quantitative approach to decision making under uncertainty that explicitly states all relevant components of the decision, including statement of the problem, identification of the perspective of the decision maker, alternative courses of action and their consequences, and a model that illustrates the decision-making process. Decision trees and Markov models are used to provide a simplified version of complex clinical problems to help decision makers understand the risks and benefits of several clinical options. This article provides an introduction to decision analysis by describing the construction of decision trees and Markov models and employing examples from the recent literature.
Veroneze, Izelandia; Burgardt, Celia I.; Fragoso, Marta F.
Background: Computerized Provider Order Entry (CPOE) and Clinical Decision Support System (CDSS) help practitioners to choose evidence-based decisions, regarding patients’ needs. Despite its use in developed countries, in Brazil, the impact of a CPOE/CDSS to improve cefazolin use in surgical prophylaxis was not assessed yet. Objective: We aimed to evaluate the impact of a CDSS to improve the use of prophylactic cefazolin and to assess the cost savings associated to inappropriate prescribing. Methods: This is a cross-sectional study that compared two different scenarios: one prior CPOE/CDSS versus after software implementation. We conducted twelve years of data analysis (3 years prior and 9 years after CDSS implementation), where main outcomes from this study included: cefazolin Defined Daily Doses/100 bed-days (DDD), crude costs and product of costs-DDD (cost-DDD/100 bed-days). We applied a Spearman rho non-parametric test to assess the reduction of cefazolin consumption through the years. Results: In twelve years, 84,383 vials of cefazolin were dispensed and represented 38.89 DDD/100 bed-days or USD 44,722.99. Surgical wards were the largest drug prescribers and comprised >95% of our studied sample. While in 2002, there were 6.31 DDD/100 bed-days, 9 years later there was a reduction to 2.15 (p<0.05). In a scenario without CDSS, the hospital would have consumed 75.72 DDD/100 bed-days, which is equivalent to USD 116 998.07. It is estimated that CDSS provided USD 50,433.39 of cost savings. Conclusion: The implementation of a CPOE/CDSS helped to improve prophylactic cefazolin use by reducing its consumption and estimated direct costs. PMID:27785159
WaterlooClarke: TREC 2015 Clinical Decision Support Track Amira Ghenai1, Eldar Khalilov1, Pavel Valov1, and Charles L. A. Clarke1 1Department of...Abstract Clinical decision support systems help physicians with finding additional information about a partic- ular medical case. In this paper, we...develop a clinical decision support system that, based on a short medical case description, can recommend research articles to answer some common
Leist, James C.; Konen, Joseph C.
Four factors of clinical decision making identified by medical students include quality of care, cost, ethics, and legal concerns. This paper argues that physicians have two responsibilities in the clinical decision-making model: to be the primary advocate for quality health care and to ensure balance among the four factors, working in partnership…
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
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.
Kawamoto, Kensaku; Houlihan, Caitlin A; Balas, E Andrew; Lobach, David F
Objective To identify features of clinical decision support systems critical for improving clinical practice. Design Systematic review of randomised controlled trials. Data sources Literature searches via Medline, CINAHL, and the Cochrane Controlled Trials Register up to 2003; and searches of reference lists of included studies and relevant reviews. Study selection Studies had to evaluate the ability of decision support systems to improve clinical practice. Data extraction Studies were assessed for statistically and clinically significant improvement in clinical practice and for the presence of 15 decision support system features whose importance had been repeatedly suggested in the literature. Results Seventy studies were included. Decision support systems significantly improved clinical practice in 68% of trials. Univariate analyses revealed that, for five of the system features, interventions possessing the feature were significantly more likely to improve clinical practice than interventions lacking the feature. Multiple logistic regression analysis identified four features as independent predictors of improved clinical practice: automatic provision of decision support as part of clinician workflow (P < 0.00001), provision of recommendations rather than just assessments (P = 0.0187), provision of decision support at the time and location of decision making (P = 0.0263), and computer based decision support (P = 0.0294). Of 32 systems possessing all four features, 30 (94%) significantly improved clinical practice. Furthermore, direct experimental justification was found for providing periodic performance feedback, sharing recommendations with patients, and requesting documentation of reasons for not following recommendations. Conclusions Several features were closely correlated with decision support systems' ability to improve patient care significantly. Clinicians and other stakeholders should implement clinical decision support systems that incorporate these
König, Niklas; Singh, Navrag B.; Baumann, Christian R.; Taylor, William R.
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
Pestian, John; Spencer, Malik; Matykiewicz, Pawel; Zhang, Kejian; Vinks, Alexander A.; Glauser, Tracy
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
Pestian, John; Spencer, Malik; Matykiewicz, Pawel; Zhang, Kejian; Vinks, Alexander A; Glauser, Tracy
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.
Medicine is incorporating genetic services into all avenues of health-care, ranging from the rarest to the most common diseases. Cognitive theories of decision-making still dominate professionals' understanding of patient decision-making about how to use genetic information and whether to have testing. I discovered a conceptual model of decision-making while carrying out a phenomenological-hermeneutic descriptive study of a convenience sample of 12 couples who were interviewed while deciding whether to undergo prenatal genetic testing. Thirty-two interviews were conducted with 12 men and 12 women separately. Interviews were transcribed verbatim and all data were analyzed using three levels of coding that were sorted into 30 categories and then abstracted into three emergent meta-themes that described men's and women's attempts to make sense and find meaning in how to best use prenatal genetic technology. Their descriptions of how they thought about, communicated, and coped with their decision were so detailed it was possible to discern nine different types of thinking they engaged in while deciding to accept or decline testing. They believed that decision-making is a process of working through your own personal style of thinking. This might include only one or any combination of the following types of thinking: analytical, ethical, moral, reflective, practical, hypothetical, judgmental, scary, and second sight, as described in detail by these 12 couples.
CADDIS is an on-line decision support system that helps investigators in the regions, states and tribes find, access, organize, use and share information to produce causal evaluations in aquatic systems. It is based on the US EPA's Stressor Identification process which is a formal method for identifying causes of impairments in aquatic systems. CADDIS 2007 increases access to relevant information useful for causal analysis and provides methods and tools that practitioners can use to analyze their own data. The new Candidate Cause section provides overviews of commonly encountered causes of impairments to aquatic systems: metals, sediments, nutrients, flow alteration, temperature, ionic strength, and low dissolved oxygen. CADDIS includes new Conceptual Models that illustrate the relationships from sources to stressors to biological effects. An Interactive Conceptual Model for phosphorus links the diagram with supporting literature citations. The new Analyzing Data section helps practitioners analyze their data sets and interpret and use those results as evidence within the USEPA causal assessment process. Downloadable tools include a graphical user interface statistical package (CADStat), and programs for use with the freeware R statistical package, and a Microsoft Excel template. These tools can be used to quantify associations between causes and biological impairments using innovative methods such as species-sensitivity distributions, biological inferenc
Grembowski, David; And Others
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)
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...
Standridge, Shannon; Faist, Robert; Pestian, John; Glauser, Tracy; Ittenbach, Richard
We developed a content validated computerized epilepsy treatment clinical decision support system to assist clinicians with selecting the best antiepilepsy treatments. Before disseminating our computerized epilepsy treatment clinical decision support system, further rigorous validation testing was necessary. As reliability is a precondition of validity, we verified proof of reliability first. We evaluated the consistency of the epilepsy treatment clinical decision support system in three areas including the preferred antiepilepsy drug choice, the top three recommended choices, and the rank order of the three choices. We demonstrated 100% reliability on 15,000 executions involving a three-step process on five different common pediatric epilepsy syndromes. Evidence for the reliability of the epilepsy treatment clinical decision support system was essential for the long-term viability of the system, and served as a crucial component for the next phase of system validation.
Bélanger, Emmanuelle; Rodríguez, Charo; Groleau, Danielle; Légaré, France; MacDonald, Mary Ellen; Marchand, Robert
The participation of patients in making decisions about their care is especially important towards the end of life because palliative care decisions involve extensive uncertainty and are heavily influenced by personal values. Yet, there is a scarcity of studies directly observing clinical interactions between palliative patients and their health care providers. In this study, we aimed to understand how patient participation in palliative care decisions is constructed through discourse in a community hospital-based palliative care team. This qualitative study combined ethnographic observations of a palliative care team with discourse analysis. Eighteen palliative care patients with cancer diagnoses, six family physicians, and two nurses were involved in the study. Multiple interactions were observed between each patient and health care providers over the course of 1 year, for a total of 101 consultations, 24 of which were audio-recorded. The analysis consisted in looking for the interpretive repertoires (i.e., familiar lines of argument used to justify actions) that were used to justify patient participation in decision-making during clinical interactions, as well as exploring their implications for decision roles and end-of-life care. Patients and their health care providers seldom addressed their decision-making roles explicitly. Rather, they constructed patient participation in palliative care decisions in a covert manner. Four interpretive repertoires were used to justify patient participation: (1) exposing uncertainty, (2) co-constructing patient preferences, (3) affirming patient autonomy, and finally (4) upholding the authority of health care providers. The results demonstrate how patients and health care providers used these arguments to negotiate their respective roles in decision-making. In conclusion, patients and health care providers used a variety of interpretive repertoires to covertly negotiate their roles in decision-making, and to legitimize
Bélanger, Emmanuelle; Rodríguez, Charo; Groleau, Danielle; Légaré, France; MacDonald, Mary Ellen; Marchand, Robert
The participation of patients in making decisions about their care is especially important towards the end of life because palliative care decisions involve extensive uncertainty and are heavily influenced by personal values. Yet, there is a scarcity of studies directly observing clinical interactions between palliative patients and their health care providers. In this study, we aimed to understand how patient participation in palliative care decisions is constructed through discourse in a community hospital-based palliative care team. This qualitative study combined ethnographic observations of a palliative care team with discourse analysis. Eighteen palliative care patients with cancer diagnoses, six family physicians, and two nurses were involved in the study. Multiple interactions were observed between each patient and health care providers over the course of 1 year, for a total of 101 consultations, 24 of which were audio-recorded. The analysis consisted in looking for the interpretive repertoires (i.e., familiar lines of argument used to justify actions) that were used to justify patient participation in decision-making during clinical interactions, as well as exploring their implications for decision roles and end-of-life care. Patients and their health care providers seldom addressed their decision-making roles explicitly. Rather, they constructed patient participation in palliative care decisions in a covert manner. Four interpretive repertoires were used to justify patient participation: (1) exposing uncertainty, (2) co-constructing patient preferences, (3) affirming patient autonomy, and finally (4) upholding the authority of health care providers. The results demonstrate how patients and health care providers used these arguments to negotiate their respective roles in decision-making. In conclusion, patients and health care providers used a variety of interpretive repertoires to covertly negotiate their roles in decision-making, and to legitimize
Wright, Adam; Sittig, Dean F.
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
Forsgren, Frank; Pohll, Greg; Tracy, John
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
Morris, A H
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.
Greenes, Robert A.
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…
Gomoi, Valentin-Sergiu; Dragu, Daniel; Stoicu-Tivadar, Vasile
Development of clinical decision support systems (CDS) is a process which highly depends on the local databases, this resulting in low interoperability. To increase the interoperability of CDS a standard representation of clinical information is needed. The paper suggests a CDS architecture which integrates several HL7 standards and the new vMR (virtual Medical Record). The clinical information for the CDS systems (the vMR) is represented with Topic Maps technology. Beside the implementation of the vMR, the architecture integrates: a Data Manager, an interface, a decision making system (based on Egadss), a retrieving data module. Conclusions are issued.
Health care providers (HCP) and clinical scientists (CS) are generally most comfortable using evidence-based rational decision-making models. They become very frustrated when policymakers make decisions that, on the surface, seem irrational and unreasonable. However, such decisions usually make sense when analysed properly. The goal of this paper to provide a basic theoretical understanding of major policy models, to illustrate which models are most prevalent in publicly funded health care systems, and to propose a policy analysis framework to better understand the elements that drive policy decision-making. The proposed policy framework will also assist HCP and CS achieve greater success with their own proposals. PMID:28123917
Dunphy, Bruce C.; Cantwell, Robert; Bourke, Sid; Fleming, Mark; Smith, Bruce; Joseph, K. S.; Dunphy, Stacey L
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…
There are six strategic objectives for promoting adoption of clinical decision support: Use a standardized format for representing clinical data and CDS interventions. Ensure appropriate access to clinical data and CDS interventions. Provide support and incentives for providers to use CDS. Disseminate information about best practices for system design, CDS delivery, and CDS implementation. Continue national demonstrations and evaluation of CDS use. Leverage data interchange between EHRs.
Trimble, Michael; Hamilton, Paul
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.
Tso, Geoffrey J.; Tu, Samson W.; Oshiro, Connie; Martins, Susana; Ashcraft, Michael; Yuen, Kaeli W.; Wang, Dan; Robinson, Amy; Heidenreich, Paul A.; Goldstein, Mary K.
As utilization of clinical decision support (CDS) increases, it is important to continue the development and refinement of methods to accurately translate the intention of clinical practice guidelines (CPG) into a computable form. In this study, we validate and extend the 13 steps that Shiffman et al.5 identified for translating CPG knowledge for use in CDS. During an implementation project of ATHENA-CDS, we encoded complex CPG recommendations for five common chronic conditions for integration into an existing clinical dashboard. Major decisions made during the implementation process were recorded and categorized according to the 13 steps. During the implementation period, we categorized 119 decisions and identified 8 new categories required to complete the project. We provide details on an updated model that outlines all of the steps used to translate CPG knowledge into a CDS integrated with existing health information technology. PMID:28269916
Demner-Fushman, Dina; Chapman, Wendy W.; McDonald, Clement J.
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
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Chipchase, S Y; Chapman, H R; Bretherton, R
Aims To develop a measure of dentists' anxiety in clinical situations; to establish if dentists' anxiety in clinical situations affected their self-reported clinical decision-making; to establish if occupational stress, as demonstrated by burnout, is associated with anxiety in clinical situations and clinical decision-making; and to explore the relationship between decision-making style and the clinical decisions which are influenced by anxiety.Design Cross-sectional study.Setting Primary Dental Care.Subjects and methods A questionnaire battery [Maslach Burnout Inventory, measuring burnout; Melbourne Decision Making Questionnaire, measuring decision-making style; Dealing with Uncertainty Questionnaire (DUQ), measuring coping with diagnostic uncertainty; and a newly designed Dentists' Anxieties in Clinical Situations Scale, measuring dentists' anxiety (DACSS-R) and change of treatment (DACSS-C)] was distributed to dentists practicing in Nottinghamshire and Lincolnshire. Demographic data were collected and dentists gave examples of anxiety-provoking situations and their responses to them.Main outcome measure Respondents' self-reported anxiety in various clinical situations on a 11-point Likert Scale (DACSS-R) and self-reported changes in clinical procedures (Yes/No; DACSS-C). The DACSS was validated using multiple t-tests and a principal component analysis. Differences in DACSS-R ratings and burnout, decision-making and dealing with uncertainty were explored using Pearson correlations and multiple regression analysis. Qualitative data was subject to a thematic analysis.Results The DACSS-R revealed a four-factor structure and had high internal reliability (Cronbach's α = 0.94). Those with higher DACSS-R scores of anxiety were more likely to report changes in clinical procedures (DACSS-C scores). DACSS-R scores were associated with decision-making self-esteem and style as measured by the MDMQ and all burnout subscales, though not with scores on the DUQ scale
Hagbaghery, Mohsen Adib; Salsali, Mahvash; Ahmadi, Fazlolah
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
Hagbaghery, Mohsen Adib; Salsali, Mahvash; Ahmadi, Fazlolah
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.
Marco-Ruiz, Luis; Bellika, Johan Gustav
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.
Dolan, James G.
Current models of healthcare quality recommend that patient management decisions be evidence-based and patient-centered. Evidence-based decisions require a thorough understanding of current information regarding the natural history of disease and the anticipated outcomes of different management options. Patient-centered decisions incorporate patient preferences, values, and unique personal circumstances into the decision making process and actively involve both patients along with health care providers as much as possible. Fundamentally, therefore, evidence-based, patient-centered decisions are multi-dimensional and typically involve multiple decision makers. Advances in the decision sciences have led to the development of a number of multiple criteria decision making methods. These multi-criteria methods are designed to help people make better choices when faced with complex decisions involving several dimensions. They are especially helpful when there is a need to combine “hard data” with subjective preferences, to make trade-offs between desired outcomes, and to involve multiple decision makers. Evidence-based, patient-centered clinical decision making has all of these characteristics. This close match suggests that clinical decision support systems based on multi-criteria decision making techniques have the potential to enable patients and providers to carry out the tasks required to implement evidence-based, patient-centered care effectively and efficiently in clinical settings. The goal of this paper is to give readers a general introduction to the range of multi-criteria methods available and show how they could be used to support clinical decision-making. Methods discussed include the balance sheet, the even swap method, ordinal ranking methods, direct weighting methods, multi-attribute decision analysis, and the analytic hierarchy process (AHP) PMID:21394218
Lindsey, Tony; Shetye, Sandeep; Shaw, Tianna (Editor)
The Exploration Clinical Decision Support (ECDS) System project is intended to enhance the Exploration Medical Capability (ExMC) Element for extended duration, deep-space mission planning in HRP. A major development guideline is the Risk of "Adverse Health Outcomes & Decrements in Performance due to Limitations of In-flight Medical Conditions". ECDS attempts to mitigate that Risk by providing crew-specific health information, actionable insight, crew guidance and advice based on computational algorithmic analysis. The availability of inflight health diagnostic computational methods has been identified as an essential capability for human exploration missions. Inflight electronic health data sources are often heterogeneous, and thus may be isolated or not examined as an aggregate whole. The ECDS System objective provides both a data architecture that collects and manages disparate health data, and an active knowledge system that analyzes health evidence to deliver case-specific advice. A single, cohesive space-ready decision support capability that considers all exploration clinical measurements is not commercially available at present. Hence, this Task is a newly coordinated development effort by which ECDS and its supporting data infrastructure will demonstrate the feasibility of intelligent data mining and predictive modeling as a biomedical diagnostic support mechanism on manned exploration missions. The initial step towards ground and flight demonstrations has been the research and development of both image and clinical text-based computer-aided patient diagnosis. Human anatomical images displaying abnormal/pathological features have been annotated using controlled terminology templates, marked-up, and then stored in compliance with the AIM standard. These images have been filtered and disease characterized based on machine learning of semantic and quantitative feature vectors. The next phase will evaluate disease treatment response via quantitative linear
Thomson, Oliver P; Petty, Nicola J; Moore, Ann P
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.
Marcum, James A
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.
Carpenter, Jo Ellen; Short, Nancy; Williams, Tracy E; Yandell, Ben; Bowers, Margaret T
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.
Davis, Derik L; Morrison, James J
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
Higuchi, Kathryn A. Smith; Donald, Janet G.
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…
Hudson, Donna L.; Estrin, Thelma
A computerized rule-based expert system for chest pain analysis in the emergency room has been developed as a medical decision-making tool. The rules are based on a previously established criteria mapping procedure developed for evaluating emergency room decisions. The system is implemented in PASCAL, a standardized language, and hence is machine-independent, and also has modest memory requirements. The overall design permits usage by those unfamiliar with computers.
Dieterly, D. L.
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.
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Fan, Aihua; Tang, Yu
In this paper, we present the design of a clinical decision support system (CDSS) for monitoring comorbid conditions. Specifically, we address the architecture of a CDSS by characterizing it from three layers and discuss the algorithms in each layer. Also we address the applications of CDSSs in a few real scenarios and analyze the accuracy of a CDSS in consideration of the potential conflicts when using multiple clinical practice guidelines concurrently. Finally, we compare the system performance in our design with that in the other design schemes. Our study shows that our proposed design can achieve a clinical decision in a shorter time than the other designs, while ensuring a high level of system accuracy. PMID:28373881
Rüping, Stefan; Anguita, Alberto; Bucur, Anca; Cirstea, Traian Cristian; Jacobs, Björn; Torge, Antje
Clinical decision support (CDS) systems promise to improve the quality of clinical care by helping physicians to make better, more informed decisions efficiently. However, the design and testing of CDS systems for practical medical use is cumbersome. It has been recognized that this may easily lead to a problematic mismatch between the developers' idea of the system and requirements from clinical practice. In this paper, we will present an approach to reduce the complexity of constructing a CDS system. The approach is based on an ontological annotation of data resources, which improves standardization and the semantic processing of data. This, in turn, allows to use data mining tools to automatically create hypotheses for CDS models, which reduces the manual workload in the creation of a new model. The approach is implemented in the context of EU research project p-medicine. A proof of concept implementation on data from an existing Leukemia study is presented.
Celi, Leo Anthony; Zimolzak, Andrew J; Stone, David J
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.
Arzt, Noam H.
This article focuses on the requirements and current developments in clinical decision support technologies for immunizations (CDSi) in both the public health and clinical communities, with an emphasis on shareable solutions. The requirements of the Electronic Health Record Incentive Programs have raised some unique challenges for the clinical community, including vocabulary mapping, update of changing guidelines, single immunization schedule, and scalability. This article discusses new, collaborative approaches whose long-term goal is to make CDSi more sustainable for both the public and private sectors. PMID:27789956
Cilliers, J. J.
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…
Smala, Antje M; Spottke, E Annika; Machat, Olaf; Siebert, Uwe; Meyer, Dieter; Köhne-Volland, Rudolf; Reuther, Martin; DuChane, Janeen; Oertel, Wolfgang H; Berger, Karin B; Dodel, Richard C
We evaluated the incremental cost-effectiveness of cabergoline compared with levodopa monotherapy in patients with early Parkinson's disease (PD) in the German healthcare system. The study design was based on cost-effectiveness analysis using a Markov model with a 10-year time horizon. Model input data was based on a clinical trial "Early Treatment of PD with Cabergoline" as well as on cost data of a German hospital/office-based PD network. Direct and indirect medical and nonmedical costs were included. Outcomes were costs, disease stage, cumulative complication incidence, and mortality. An annual discount rate of 5% was applied and the societal perspective was chosen. The target population included patients in Hoehn and Yahr Stages I to III. It was found that the occurrence of motor complications was significantly lower in patients on cabergoline monotherapy. For patients aged >/=60 years of age, cabergoline monotherapy was cost effective when considering costs per decreased UPDRS score. Each point decrease in the UPDRS (I-IV) resulted in costs of euro;1,031. Incremental costs per additional motor complication-free patient were euro;104,400 for patients <60 years of age and euro;57,900 for patients >/=60 years of age. In conclusion, this decision-analytic model calculation for PD was based almost entirely on clinical and observed data with a limited number of assumptions. Although costs were higher in patients on cabergoline, the corresponding cost-effectiveness ratio for cabergoline was at least as favourable as the ratios for many commonly accepted therapies.
Baker, Richard; Esquenazi, Alberto; Benedetti, Maria G; Desloovere, Kaat
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.
Harrison, Roberta L; Lyerla, Frank
The Health Information Technology and Clinical Health Act (one component of the American Recovery and Reinvestment Act) is responsible for providing incentive payments to hospitals and eligible providers in an effort to support the adoption of electronic health records. Future penalties are planned for electronic health record noncompliance. In order to receive incentives and avoid penalties, hospitals and eligible providers must demonstrate "meaningful use" of their electronic health records. One of the meaningful-use objectives established by the Centers for Medicare & Medicaid Services involves the use of a clinical decision support rule that addresses a hospital-defined, high-priority condition. This article describes the Plan-Do-Study-Act process for creating and implementing a nursing clinical decision support system designed to improve guideline adherence for hypoglycemia management. This project identifies hypoglycemia management as the high-priority area. However, other facilities with different high-priority conditions may find the process presented in this article useful for implementing additional clinical decision support rules geared toward improving outcomes and meeting federal mandates.
Sun, J.; Knoop, S.; Shabo, A.; Carmeli, B.; Sow, D.; Syed-Mahmood, T.; Rapp, W.
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
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.
Query Modification through External Sources to Support Clinical Decisions Raymond Wan1, Jannifer Hiu-Kwan Man2, and Ting-Fung Chan1 1School of Life...query modifications that use either external data sources or a domain expert. While each method gave slightly different results, we discovered that...biomedical literature offers many possible paths of investigation, our study focused on modifications to the query using external data sources. We submitted 5
Keshavjee, K; Holbrook, AM; Lau, E; Esporlas-Jewer, I; Troyan, S
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.
Linan, Margaret K; Sottara, Davide; Freimuth, Robert R
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.
Linan, Margaret K.; Sottara, Davide; Freimuth, Robert R.
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
Kawamoto, Kensaku; Del Fiol, Guilherme; Orton, Charles; Lobach, David F
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
Kawamoto, Kensaku; Del Fiol, Guilherme; Orton, Charles; Lobach, David F
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.
Pang, Y-K; Ip, M; You, J H S
Early initiation of antifungal treatment for invasive candidiasis is associated with change in mortality. Beta-D-glucan (BDG) is a fungal cell wall component and a serum diagnostic biomarker of fungal infection. Clinical findings suggested an association between reduced invasive candidiasis incidence in intensive care units (ICUs) and BDG-guided preemptive antifungal therapy. We evaluated the potential cost-effectiveness of active BDG surveillance with preemptive antifungal therapy in patients admitted to adult ICUs from the perspective of Hong Kong healthcare providers. A Markov model was designed to simulate the outcomes of active BDG surveillance with preemptive therapy (surveillance group) and no surveillance (standard care group). Candidiasis-associated outcome measures included mortality rate, quality-adjusted life year (QALY) loss, and direct medical cost. Model inputs were derived from the literature. Sensitivity analyses were conducted to evaluate the robustness of model results. In base-case analysis, the surveillance group was more costly (1387 USD versus 664 USD) (1 USD = 7.8 HKD), with lower candidiasis-associated mortality rate (0.653 versus 1.426 per 100 ICU admissions) and QALY loss (0.116 versus 0.254) than the standard care group. The incremental cost per QALY saved by the surveillance group was 5239 USD/QALY. One-way sensitivity analyses found base-case results to be robust to variations of all model inputs. In probabilistic sensitivity analysis, the surveillance group was cost-effective in 50 % and 100 % of 10,000 Monte Carlo simulations at willingness-to-pay (WTP) thresholds of 7200 USD/QALY and ≥27,800 USD/QALY, respectively. Active BDG surveillance with preemptive therapy appears to be highly cost-effective to reduce the candidiasis-associated mortality rate and save QALYs in the ICU setting.
Dhami, Mandeep K; Mandel, David R; Mellers, Barbara A; Tetlock, Philip E
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.
Rittenhouse, Brian E.
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…
Bamber, J H; Evans, S A
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.
It is clear that current government policy places increasing emphasis on the need for flexible team working. This requires a shared understanding of roles and working practices. However, review of the current literature reveals that such a collaborative working environment has not as yet, been fully achieved. Role definitions and power bases based on traditional and historical boundaries continue to exist. This ethnographic study explores decision making between doctors and nurses in the intensive care environment in order to examine contemporary clinical roles in this clinical specialty. Three intensive care units were selected as field sites and data was collected through participant observation, ethnographic interviews and documentation. A key issue arising in this study is that whilst the nursing role in intensive care has changed, this has had little impact on how clinical decisions are made. Both medical and nursing staff identify conflict during patient management discussions. However, it is predominantly nurses who seek to redress this conflict area through developing specific behaviours for this clinical forum. Using this approach to resolve such team issues has grave implications if the government vision of interdisciplinary team working is to be realised.
CHEN, JONATHAN H; GOLDSTEIN, MARY K; ASCH, STEVEN M; ALTMAN, RUSS B
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
van Baalen, Sophie; Carusi, Annamaria; Sabroe, Ian; Kiely, David G
In recent years there has been growing attention to the epistemology of clinical decision-making, but most studies have taken the individual physicians as the central object of analysis. In this paper we argue that knowing in current medical practice has an inherently social character and that imaging plays a mediating role in these practices. We have analyzed clinical decision-making within a medical expert team involved in diagnosis and treatment of patients with pulmonary hypertension (PH), a rare disease requiring multidisciplinary team involvement in diagnosis and management. Within our field study, we conducted observations, interviews, video tasks, and a panel discussion. Decision-making in the PH clinic involves combining evidence from heterogeneous sources into a cohesive framing of a patient, in which interpretations of the different sources can be made consistent with each other. Because pieces of evidence are generated by people with different expertise and interpretation and adjustments take place in interaction between different experts, we argue that this process is socially distributed. Multidisciplinary team meetings are an important place where information is shared, discussed, interpreted, and adjusted, allowing for a collective way of seeing and a shared language to be developed. We demonstrate this with an example of image processing in the PH service, an instance in which knowledge is distributed over multiple people who play a crucial role in generating an evaluation of right heart function. Finally, we argue that images fulfill a mediating role in distributed knowing in 3 ways: first, as enablers or tools in acquiring information; second, as communication facilitators; and third, as pervasively framing the epistemic domain. With this study of clinical decision-making in diagnosis and treatment of PH, we have shown that clinical decision-making is highly social and mediated by technologies. The epistemology of clinical decision-making needs
Goldberg, Howard S; Paterno, Marilyn D; Rocha, Beatriz H; Schaeffer, Molly; Wright, Adam; Erickson, Jessica L; Middleton, Blackford
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
Habas, Piotr A.; Zurada, Jacek M.; Elmaghraby, Adel S.; Tourassi, Georgia D.
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
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.
Broverman, C A; Clyman, J I; Schlesinger, J M; Want, E
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.
Pizzorno, Joseph E
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.
Orient, J M
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.
Thomson, R.; Robinson, A.; Greenaway, J.; Lowe, P.
Background: There is an increasing move towards clinical decision making that engages the patient, which has led to the development and use of decision aids to support better decisions. The treatment of patients in atrial fibrillation (AF) with warfarin to prevent stroke is a decision that is sensitive to patient preferences as shown by a previous decision analysis. Aim: To develop a computerised decision support tool, building upon a previous decision analysis, which would engage individual patient preferences in reaching a shared decision on whether to take warfarin to prevent stroke. Methods: The development process had two main phases: (1) the development phase which employed focus groups and repeated interviews with GPs/practice nurses and patients alongside an iterative development of a computerised tool; (2) the training and testing phase in which GPs and practice nurses underwent training in the use of the tool, including the use of simulated patients. The tool was then used in a feasibility study in a small number of patients with AF to inform the design of a subsequent randomised controlled trial. Results: The prototype tool had three components: (1) derivation of an individual patient's values for relevant health states using a standard gamble; (2) presentation/discussion of a patient's risks of stroke using the Framingham equation and the benefits/risks of warfarin from a systematic literature review; and (3) decision making component incorporating the outcome of a Markov decision analysis model. Older patients could be taken through the decision analysis based computerised tool, and patients and clinicians welcomed information on risks and benefits of treatments. The tool required time and training to use. Patients' decisions in the feasibility phase did not necessarily coincide with the output of the decision analysis model, but decision conflict appeared to be reduced and both patients and GPs were satisfied with the process. Conclusions: It is
Sordo, Margarita; Rocha, Beatriz H; Morales, Alfredo A; Maviglia, Saverio M; Oglio, Elisa Dell'Oglio; Fairbanks, Amanda; Aroy, Teal; Dubois, David; Bouyer-Ferullo, Sharon; Rocha, Roberto A
Traditionally, rule interactions are handled at implementation time through rule task properties that control the order in which rules are executed. By doing so, knowledge about the behavior and interactions of decision rules is not captured at modeling time. We argue that this is important knowledge that should be integrated in the modeling phase. In this project, we build upon current work on a conceptual schema to represent clinical knowledge for decision support in the form of if
Hincks, T. H.; Aspinall, W.; Woo, G.
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.
Elting, Linda S; Martin, Charles G; Cantor, Scott B; Rubenstein, Edward B
Objective To examine the effect of the method of data display on physician investigators’ decisions to stop hypothetical clinical trials for an unplanned statistical analysis. Design Prospective, mixed model design with variables between subjects and within subjects (repeated measures). Setting Comprehensive cancer centre. Participants 34 physicians, stratified by academic rank, who were conducting clinical trials. Interventions Participants were shown tables, pie charts, bar graphs, and icon displays containing hypothetical data from a clinical trial and were asked to decide whether to continue the trial or stop for an unplanned statistical analysis. Main outcome measure Percentage of accurate decisions with each type of display. Results Accuracy of decisions was affected by the type of data display and positive or negative framing of the data. More correct decisions were made with icon displays than with tables, pie charts, and bar graphs (82% v 68%, 56%, and 43%, respectively; P=0.03) and when data were negatively framed rather than positively framed in tables (93% v 47%; P=0.004). Conclusions Clinical investigators’ decisions can be affected by factors unrelated to the actual data. In the design of clinical trials information systems, careful consideration should be given to the method by which data are framed and displayed in order to reduce the impact of these extraneous factors. Key messagesIn clinical trials formal interim monitoring points, at which statistical tests are conducted, are designated a priori, but investigators also conduct informal interim monitoring, when statistical tests are not usedThis study investigated the effect of the method of displaying results on clinical investigators’ decisions to conduct unplanned analyses of a hypothetical clinical trialThe method of displaying results significantly influenced the accuracy of decisions, as did the framing of these results (positive or negative)The display formats preferred by the
Bernabe, Rosemarie D C; van Thiel, Ghislaine J M W; Raaijmakers, Jan A M; van Delden, Johannes J M
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.
Martínez-Pérez, Borja; de la Torre-Díez, Isabel; López-Coronado, Miguel; Sainz-de-Abajo, Beatriz; Robles, Montserrat; García-Gómez, Juan Miguel
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.
Ash, Joan S.; Sittig, Dean F.; McMullen, Carmit K.; McCormack, James L.; Wright, Adam; Bunce, Arwen; Wasserman, Joseph; Mohan, Vishnu; Cohen, Deborah J.; Shapiro, Michael; Middleton, Blackford
In prior work, using a Rapid Assessment Process (RAP), we have investigated clinical decision support (CDS) in ambulatory clinics and hospitals. We realized that individuals in these settings provide only one perspective related to the CDS landscape, which also includes content vendors and electronic health record (EHR) vendors. To discover content vendors’ perspectives and their perceived challenges, we modified RAP for industrial settings. We describe how we employed RAP, and show its utility by describing two illustrative themes. We found that while the content vendors believe they provide unique much-needed services, the amount of labor involved in content development is underestimated by others. We also found that the content vendors believe their products are resources to be used by practitioners, so they are somewhat protected from liability issues. To promote adequate understanding about these issues, we recommend a “three way conversation” among content vendors, EHR vendors, and user organizations. PMID:22195058
Freimuth, Robert R.; Wix, Kelly; Zhu, Qian; Siska, Mark; Chute, Christopher G.
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
Gospodarowicz, Mary; O'Sullivan, Brian
The depiction of prognosis is one of the main activities and a mainstay in medical practice. In cancer, as in other diseases, the prognosis differs for a variety of situations and evolves with time and with medical interventions. Although most commonly described at diagnosis, prognosis may be defined at any time during the course of the disease and for any endpoint including response to therapy, failure of treatment, survival, or preservation of function, and so forth. To facilitate the accurate portrayal of the future, the prognosis should be defined within a specific setting, referred to as a 'management scenario'. In the concept of a management scenario, the prognosis is defined using systematically considered prognostic factors, interventions and the outcome of interest. A deliberate and careful determination of prognosis is essential to clinical decision making and patient care. We illustrate the use of the concept of management scenario in several clinical examples.
Ash, Joan S; Sittig, Dean F; McMullen, Carmit K; McCormack, James L; Wright, Adam; Bunce, Arwen; Wasserman, Joseph; Mohan, Vishnu; Cohen, Deborah J; Shapiro, Michael; Middleton, Blackford
In prior work, using a Rapid Assessment Process (RAP), we have investigated clinical decision support (CDS) in ambulatory clinics and hospitals. We realized that individuals in these settings provide only one perspective related to the CDS landscape, which also includes content vendors and electronic health record (EHR) vendors. To discover content vendors' perspectives and their perceived challenges, we modified RAP for industrial settings. We describe how we employed RAP, and show its utility by describing two illustrative themes. We found that while the content vendors believe they provide unique much-needed services, the amount of labor involved in content development is underestimated by others. We also found that the content vendors believe their products are resources to be used by practitioners, so they are somewhat protected from liability issues. To promote adequate understanding about these issues, we recommend a "three way conversation" among content vendors, EHR vendors, and user organizations.
Freimuth, Robert R; Wix, Kelly; Zhu, Qian; Siska, Mark; Chute, Christopher G
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.
Robinson, A; Thomson, R
The quality of patient care is dependent upon the quality of the multitude of decisions that are made daily in clinical practice. Increasingly, modern health care is seeking to pursue better decisions (including an emphasis on evidence-based practice) and to engage patients more in decisions on their care. However, many treatment decisions are made in the face of clinical uncertainty and may be critically dependent upon patient preferences. This has led to attempts to develop decision support tools that enable patients and clinicians to make better decisions. One approach that may be of value is decision analysis, which seeks to create a rational framework for evaluating complex medical decisions and to provide a systematic way of integrating potential outcomes with probabilistic information such as that generated by randomised controlled trials of interventions. This paper describes decision analysis and discusses the potential of this approach with reference to the clinical decision as to whether to treat patients in atrial fibrillation with warfarin to reduce their risk of stroke. (Quality in Health Care 2000;9:238–244) Key Words: decision analysis; quality of care; atrial fibrillation PMID:11101709
Dubos, F; Lamotte, B; Bibi‐Triki, F; Moulin, F; Raymond, J; Gendrel, D; Bréart, G; Chalumeau, M
Background Clinical decision rules have been derived to distinguish between bacterial and aseptic meningitis in the emergency room to avoid unnecessary antibiotic treatments and hospitalisations. Aims To evaluate the reproducibility and to compare the diagnostic performance of five clinical decision rules. Methods All children hospitalised for bacterial meningitis between 1995 and 2004 or aseptic meningitis between 2000 and 2004 have been included in a retrospective cohort study. Sensitivity and specificity were calculated by applying each rule to the patients. The best rule was a priori defined as the one yielding 100% sensitivity for bacterial meningitis, the highest specificity, and the greatest simplicity for a bedside application. Results Among the 166 patients included, 20 had bacterial meningitis and 146 had aseptic meningitis. Although three rules achieved 100% sensitivity (95% CI 84–100), one had a significantly lower specificity (13%, 95% CI 8–19) than those of the other two rules (57%, 95% CI 48–65; and 66%, 95% CI 57–73), which were not statistically different. The ease of manual computation of the rule developed by Nigrovic et al (a simple list of five items: seizure, blood neutrophil count, cerebrospinal fluid (CSF) Gram stain, CSF protein, CSF neutrophil count) was higher than the one developed by Bonsu and Harper. Conclusion On our population, the rule derived by Nigrovic et al had the best balance between accuracy and simplicity of manual computation and could help to avoid two thirds of unnecessary antibiotic treatments and hospitalisations. PMID:16595647
Hardin, D. M.; Hawkins, L.; He, M.; Ebersole, S.
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
analysis functionality. This will allow A2D to run an application in a controlled, virtual environment, and interact with it in ways similar to a human...extension. This new functionality installs and launches the application on 1 of several virtual machines (VMs) that sit on top of a simulation of a...standard network. The application will not be capable of reaching the wider Internet. As it runs, A2D will interact with the virtual phone and perform
Soukup, Tayana; Petrides, Konstantinos V.; Lamb, Benjamin W.; Sarkar, Somita; Arora, Sonal; Shah, Sujay; Darzi, Ara; Green, James S. A.; Sevdalis, Nick
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
Clinical and pharmacogenomic data mining: 2. A simple method for the combination of information from associations and multivariances to facilitate analysis, decision, and design in clinical research and practice.
Robson, Barry; Mushlin, Richard
The physician and researcher must ultimately be able to combine qualitative and quantitative features from a variety of combinations of observations on data of many component items (i.e., many dimensions), and hence reach simple conclusions about interpretation, rational courses of action, and design. In the first paper of this series, it was noted that such needs are challenging the classical means of using statistics. Hence, the paper proposed the use of a Generalized Theory of Expected Information or "Zeta Theory". The conjoint event [a,b,c,..] is seen as a rule of association for a,b,c,.. associated with a rule strength I(a;b;c;...) = xi(s,o[a,b,c,..]) - xi (s,e[a,b,c,...]), where xi is the incomplete Zeta Function. Here, o[a,b,c,...] is the observed, and e[a,b,c,..] the expected, frequency of occurrence of conjoint event [a,b,c,...]. The present paper explores how output from this approach might be assembled in a form better suited for decision support. Related to this is the difficulty that the treatment of covariance and multivariance was previously rendered as a "fuzzy association" so that the output would fall into a similar form as the true associations, but this was a somewhat ad hoc approach in which only the final I( ) had any meaning. Users at clinical research sites had subsequently requested an alternative approach in which "effective frequencies" o[ ] and e[ ] calculated from the above variances and used to evaluate I( ) give some intuitive feeling analogous to the association treatment, and this is explored here. Though the present paper is theoretical, real examples are used to illustrate application. One clinical-genomic example illustrates experimental design by identifying data which is, or is not, statistically germane to the study. We also report on some impressions based on applying these techniques in studies of real, extensive patient record data which are now emerging, as well as on molecular design data originally studied in part to
Brehaut, Jamie C; Lott, Alison; Fergusson, Dean A; Shojania, Kaveh G; Kimmelman, Jonathan; Saginur, Raphael
Background Evidence shows that the standard process for obtaining informed consent in clinical trials can be inadequate, with study participants frequently not understanding even basic information fundamental to giving informed consent. Patient decision aids are effective decision support tools originally designed to help patients make difficult treatment or screening decisions. We propose that incorporating decision aids into the informed consent process will improve the extent to which participants make decisions that are informed and consistent with their preferences. A mixed methods study will test this proposal. Methods Phase one of this project will involve assessment of a stratified random sample of 50 consent documents from recently completed investigator-initiated clinical trials, according to existing standards for supporting good decision making. Phase two will involve interviews of a purposive sample of 50 trial participants (10 participants from each of five different clinical areas) about their experience of the informed consent process, and how it could be improved. In phase three, we will convert consent forms for two completed clinical trials into decision aids and pilot test these new tools using a user-centered design approach, an iterative development process commonly employed in computer usability literature. In phase four, we will conduct a pilot observational study comparing the new tools to standard consent forms, with potential recruits to two hypothetical clinical trials. Outcomes will include knowledge of key aspects of the decision, knowledge of the probabilities of different outcomes, decisional conflict, the hypothetical participation decision, and qualitative impressions of the experience. Discussion This work will provide initial evidence about whether a patient decision aid can improve the informed consent process. The larger goal of this work is to examine whether study recruitment can be improved from (barely) informed consent
Zurakowski, David; Johnson, Victor M; Lee, Edward Y
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.
Edelman, Emily A; Lin, Bruce K; Doksum, Teresa; Drohan, Brian; Edelson, Vaughn; Dolan, Siobhan M; Hughes, Kevin; O'Leary, James; Vasquez, Lisa; Copeland, Sara; Galvin, Shelley L; DeGroat, Nicole; Pardanani, Setul; Gregory Feero, W; Adams, Claire; Jones, Renee; Scott, Joan
"The Pregnancy and Health Profile" (PHP) is a free prenatal genetic screening and clinical decision support (CDS) software tool for prenatal providers. PHP collects family health history (FHH) during intake and provides point-of-care risk assessment for providers and education for patients. This pilot study evaluated patient and provider responses to PHP and effects of using PHP in practice. PHP was implemented in four clinics. Surveys assessed provider confidence and knowledge and patient and provider satisfaction with PHP. Data on the implementation process were obtained through semi-structured interviews with administrators. Quantitative survey data were analyzed using Chi square test, Fisher's exact test, paired t tests, and multivariate logistic regression. Open-ended survey questions and interviews were analyzed using qualitative thematic analysis. Of the 83% (513/618) of patients that provided feedback, 97% felt PHP was easy to use and 98% easy to understand. Thirty percent (21/71) of participating physicians completed both pre- and post-implementation feedback surveys [13 obstetricians (OBs) and 8 family medicine physicians (FPs)]. Confidence in managing genetic risks significantly improved for OBs on 2/6 measures (p values ≤0.001) but not for FPs. Physician knowledge did not significantly change. Providers reported value in added patient engagement and reported mixed feedback about the CDS report. We identified key steps, resources, and staff support required to implement PHP in a clinical setting. To our knowledge, this study is the first to report on the integration of patient-completed, electronically captured and CDS-enabled FHH software into primary prenatal practice. PHP is acceptable to patients and providers. Key to successful implementation in the future will be customization options and interoperability with electronic health records.
Wilpert, B.; And Others
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…
Rodríguez-Pimentel, Leticia; Silva-Romo, Rodolfo; Wacher-Rodarte, Niels
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.
called state variables (or environ- mental variables) since they define the state of the decision environment. Decision variables must be defined in such...Vaibeison Endlogetious STRUCTURAL MODELO Varabls ~State Variables* (INTERACTION MODEL) Outcome Variables’ (Either State or Prefeence$Decision...decisions and states of the environment. This type of model requires the decision maker to aggregate mentally the effects of the interactions among his
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.
Wanderer, Jonathan P; Ehrenfeld, Jesse M
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.
Wright, Adam; Sittig, Dean F.
Background A large body of evidence over many years suggests that clinical decision support systems can be helpful in improving both clinical outcomes and adherence to evidence-based guidelines. However, to this day, clinical decision support systems are not widely used outside of a small number of sites. One reason why decision support systems are not widely used is the relative difficulty of integrating such systems into clinical workflows and computer systems. Purpose To review and synthesize the history of clinical decision support systems, and to propose a model of various architectures for integrating clinical decision support systems with clinical systems. Methods The authors conducted an extensive review of the clinical decision support literature since 1959, sequenced the systems and developed a model. Results The model developed consists of four phases: standalone decision support systems, decision support integrated into clinical systems, standards for sharing clinical decision support content and service models for decision support. These four phases have not heretofore been identified, but they track remarkably well with the chronological history of clinical decision support, and show evolving and increasingly sophisticated attempts to ease integrating decision support systems into clinical workflows and other clinical systems. Conclusions Each of the four evolutionary approaches to decision support architecture has unique advantages and disadvantages. A key lesson was that there were common limitations that almost all the approaches faced, and no single approach has been able to entirely surmount: 1) fixed knowledge representation systems inherently circumscribe the type of knowledge that can be represented in them, 2) there are serious terminological issues, 3) patient data may be spread across several sources with no single source having a complete view of the patient, and 4) major difficulties exist in transferring successful interventions from one
Amland, Robert C; Hahn-Cover, Kristin E
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.
Wright, Adam; Sittig, Dean F.
A new architecture for clinical decision support called SANDS (Service-oriented Architecture for NHIN Decision Support) is introduced and its performance evaluated. The architecture provides a method for performing clinical decision support across a network, as in a health information exchange. Using the prototype we demonstrated that, first, a number of useful types of decision support can be carried out using our architecture; and, second, that the architecture exhibits desirable reliability and performance characteristics. PMID:18693950
Cornuz, Jacques; Junod, Noëlle; Pasche, Olivier; Guessous, Idris
Shared decision-making approach to uncertain clinical situations such as cancer screening seems more appropriate than ever. Shared decision making can be defined as an interactive process where physician and patient share all the stages of the decision making process. For patients who wish to be implicated in the management of their health conditions, physicians might express difficulty to do so. Use of patient decision aids appears to improve such process of shared decision making.
Boiko, Olga; Sheaff, Rod; Child, Susan; Gericke, Christian A
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.
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.
Fillmore, Christopher L; Rommel, Casey A; Welch, Brandon M; Zhang, Mingyuan; Kawamoto, Kensaku
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.
Hardin, D. M.; Keiser, K.; Graves, S. J.; Conover, H.; Ebersole, S.
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
Converse, Sarah J.; Moore, Clinton T.; Armstrong, Doug P.
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.
consequences of alternatives in terms of probabilities, Utility theory is used to quantify the values of decision makers for these conse- quences. Decision... utilities . The more common interpretation of decision theory is a sampling theor. involving statistical problems (see Waild 119501, Savage 119541. and...probability and utility , and Ramsey  was the first to suggest a theory of decision making based on these two ideas. Two centuries earlicer
Kuo, Kuan-Liang; Fuh, Chiou-Shann
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.
Nasirian, Hosain; TarvijEslami, Saeedeh; Matini, Esfandiar; Bayesh, Seyedehsara; Omaraee, Yasaman
PURPOSE: Group A streptococcal (GAS) pharyngitis is a common disease worldwide. We aimed to establish a pragmatic program as a clinical decision rule for GAS pharyngitis diagnosis. MATERIALS AND METHODS: This article derived from a research project on children aged 6–15 years. Five hundred and seventy-one children met the enrollment criteria on whom throat culture and validities of clinical findings were assessed in positive and negative throat culture groups. RESULTS: Positive GAS throat culture group included 99 (17.3%) patients with a positive culture. Negative GAS throat culture group included 472 (82.6%) patients. Exudate or enlarged tender nodes each one had 63% and 68% sensitivity and 31.5% and 37.5% specificity with a high percentage of negative predictive value (NPV) 80.54% and 85.09%, respectively. Sequence test revealed validities of exudate plus enlarged nodes at 43.62% sensitivity and 57.19% specificity with 83% NPV. CONCLUSIONS: High NPV of 83% indicated that similar prevalence in the absence of either exudate or enlarged tender lymph nodes. Probability of GAS negative throat cultures among children suspected of GAS pharyngitis was 83% and would correctly not receive inopportune antibiotics. PMID:28367027
Blanquer, Ignacio; Hernández, Vicente; Segrelles, Damià; Robles, Montserrat; García, Juan Miguel; Robledo, Javier Vicente
This paper presents an architecture defined for searching and executing Clinical Decision Support Systems (CDSS) in a LCG2/GT2 Grid environment, using web-based protocols. A CDSS is a system that provides a classification of the patient illness according to the knowledge extracted from clinical practice and using the patient's information in a structured format. The CDSS classification engines can be installed in any site and can be used by different medical users from a Virtual Organization (VO). All users in a VO can consult and execute different classification engines that have been installed in the Grid independently of the platform, architecture or site where the engines are installed or the users are located. The present paper present a solution to requirements such as short-job execution, reducing the response delay on LCG2 environments and providing grid-enabled authenticated access through web portals. Resource discovering and job submission is performed through web services, which are also described in the article.
Neapolitan, Richard; Jiang, Xia; Ladner, Daniela P; Kaplan, Bruce
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.
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.
Hajjaj, FM; Salek, MS; Basra, MKA; Finlay, AY
Summary This article reviews an aspect of daily clinical practice which is of critical importance in virtually every clinical consultation, but which is seldom formally considered. Non-clinical influences on clinical decision-making profoundly affect medical decisions. These influences include patient-related factors such as socioeconomic status, quality of life and patient's expectations and wishes, physician-related factors such as personal characteristics and interaction with their professional community, and features of clinical practice such as private versus public practice as well as local management policies. This review brings together the different strands of knowledge concerning non-clinical influences on clinical decision-making. This aspect of decision-making may be the biggest obstacle to the reality of practising evidence-based medicine. It needs to be understood in order to develop clinical strategies that will facilitate the practice of evidence-based medicine. PMID:20436026
Chen, Lu-Yen A; Fawcett, Tonks N
Several data-mining models have been embedded in the clinical environment to improve decision making and patient safety. Consequently, it is crucial to survey the principal data-mining strategies currently used in clinical decision making and to determine the disadvantages and advantages of using these strategies in data mining in clinical decision making. A literature review was conducted, which identified 21 relevant articles. The article findings showed that multiple models of data mining were used in clinical decision making. Although data mining is efficient and accurate, the models are limited with respect to disease and condition.
Wilk, Szymon; Michalowski, Wojtek; O'Sullivan, Dympna; Farion, Ken; Matwin, Stan
Computerized decision support for use at the point of care has to be comprehensive. It means that clinical information stored in electronic health records needs to be integrated with various forms of clinical knowledge (elicited from experts, discovered from data or summarized in systematic reviews of clinical trials). In order to provide such comprehensive support we created the MET-A3Support framework for constructing clinical applications aimed at various medical conditions. We employed the multiagent system paradigm and the O-MaSE methodology to define an engineering process involving three main activities: requirements engineering, analysis and design. Then we applied the process to build MET-A3Support. The paper describes the engineering process and its results, including models representing selected elements of our framework.
Wright, Adam; Bates, David W; Middleton, Blackford; Hongsermeier, Tonya; Kashyap, Vipul; Thomas, Sean M; Sittig, Dean F
Clinical decision support is a powerful tool for improving healthcare quality and patient safety. However, developing a comprehensive package of decision support interventions is costly and difficult. If used well, Web 2.0 methods may make it easier and less costly to develop decision support. Web 2.0 is characterized by online communities, open sharing, interactivity and collaboration. Although most previous attempts at sharing clinical decision support content have worked outside of the Web 2.0 framework, several initiatives are beginning to use Web 2.0 to share and collaborate on decision support content. We present case studies of three efforts: the Clinfowiki, a world-accessible wiki for developing decision support content; Partners Healthcare eRooms, web-based tools for developing decision support within a single organization; and Epic Systems Corporation's Community Library, a repository for sharing decision support content for customers of a single clinical system vendor. We evaluate the potential of Web 2.0 technologies to enable collaborative development and sharing of clinical decision support systems through the lens of three case studies; analyzing technical, legal and organizational issues for developers, consumers and organizers of clinical decision support content in Web 2.0. We believe the case for Web 2.0 as a tool for collaborating on clinical decision support content appears strong, particularly for collaborative content development within an organization.
Anuar, Nor Badrul; Shiraz, Muhammad; Haque, Israat Tanzeena
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
Whaiduzzaman, Md; Gani, Abdullah; Anuar, Nor Badrul; Shiraz, Muhammad; Haque, Mohammad Nazmul; Haque, Israat Tanzeena
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.
regarding continuation of life-sustaining vs. palliative care . Finally, using regret DCA, the optimal decision for the specific patient is suggested...is to develop an Evidence-based Clinical Decision Support (CDSS-EBM) system and make it available at the point of care to improve prognostication of...Analysis and Regret theory to compare multiple decision strategies based on the decision maker’s personal attitudes towards each strategy
Sim, Ida; Gorman, Paul; Greenes, Robert A.; Haynes, R. Brian; Kaplan, Bonnie; Lehmann, Harold; Tang, Paul C.
Background: The use of clinical decision support systems to facilitate the practice of evidence-based medicine promises to substantially improve health care quality. Objective: To describe, on the basis of the proceedings of the Evidence and Decision Support track at the 2000 AMIA Spring Symposium, the research and policy challenges for capturing research and practice-based evidence in machine-interpretable repositories, and to present recommendations for accelerating the development and adoption of clinical decision support systems for evidence-based medicine. Results: The recommendations fall into five broad areas—capture literature-based and practice-based evidence in machine-interpretable knowledge bases; develop maintainable technical and methodological foundations for computer-based decision support; evaluate the clinical effects and costs of clinical decision support systems and the ways clinical decision support systems affect and are affected by professional and organizational practices; identify and disseminate best practices for work flow–sensitive implementations of clinical decision support systems; and establish public policies that provide incentives for implementing clinical decision support systems to improve health care quality. Conclusions: Although the promise of clinical decision support system–facilitated evidence-based medicine is strong, substantial work remains to be done to realize the potential benefits. PMID:11687560
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.
Rolland, John S; Emanuel, Linda L; Torke, Alexia M
When patients are incapacitated and face serious illness, family members must make medical decisions for the patient. Medical decision sciences give only modest attention to the relationships among patients and their family members, including impact that these relationships have on the decision-making process. A review of the literature reveals little effort to systematically apply a theoretical framework to the role of family interactions in proxy decision making. A family systems perspective can provide a useful lens through which to understand the dynamics of proxy decision making. This article considers the mutual impact of family systems on the processes and outcomes of proxy decision making. The article first reviews medical decision science's evolution and focus on proxy decision making and then reviews a family systems approach, giving particular attention to Rolland's Family Systems Illness Model. A case illustrates how clinical practice and how research would benefit from bringing family systems thinking to proxy decisions. We recommend including a family systems approach in medical decision science research and clinical practices around proxy decisions making. We propose that clinical decisions could be less conflicted and less emotionally troubling for families and clinicians if family systems approaches were included. This perspective opens new directions for research and novel approaches to clinical care. (PsycINFO Database Record
Hruska, Pam; Hecker, Kent G.; Coderre, Sylvain; McLaughlin, Kevin; Cortese, Filomeno; Doig, Christopher; Beran, Tanya; Wright, Bruce; Krigolson, Olav
Clinical decision making requires knowledge, experience and analytical/non-analytical types of decision processes. As clinicians progress from novice to expert, research indicates decision-making becomes less reliant on foundational biomedical knowledge and more on previous experience. In this study, we investigated how knowledge and experience…
Amland, Robert C.; Hahn-Cover, Kristin E.
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
Alexander, Gregory L
Clinical decision support systems are computer technologies that model and provide support for human decision-making processes. Decision support mechanisms facilitate and enhance a clinician's ability to make decisions at the point of care. Decisions are facilitated through technology by using automated mechanisms that provide alerts or messages to clinicians about a potential patient problem. A clinician's level of trust in these technologies to support decision making is affected by how knowledge is represented in these tools, their ability to make reasonable decisions, and how they are designed. Furthermore, ethical tensions occur if these systems do not promote standards, if clinicians do not understand how to use these systems, and when professional relationships are affected. Issues of trust and ethical concerns will be examined in this article, using a research study of midwestern nursing homes that implemented a clinical decision support system.
Eisenstein, Eric L; Anstrom, Kevin J; Edwards, Rex; Willis, Janese M; Simo, Jessica; Lobach, David F
Governments are investing in health information technologies (HIT) to improve care quality and reduce medical costs. However, evidence of these benefits is limited. We conducted a randomized trial of three clinical decision support (CDS) interventions in 20,180 patients: email to care managers (n=3329), reports to primary care administrators (n=3368), letters to patients (n=3401), and controls (10,082). At 7-month follow-up, the letters to patients group had greater use of outpatient services and higher outpatient and total medical costs; whereas, the other groups had no change in clinical events or medical costs. As our CDS interventions were associated with no change or an increase in medical costs, it appears that investments in HIT without consideration for organizational context may not be sufficient to achieve improvements in clinical and economic outcomes.
Maxson, Pamela M.; Dozois, Eric J.; Holubar, Stefan D.; Wrobleski, Diane M.; Dube, Joyce A. Overman; Klipfel, Janee M.; Arnold, Jacqueline J.
OBJECTIVE: To determine whether interdisciplinary simulation team training can positively affect registered nurse and/or physician perceptions of collaboration in clinical decision making. PARTICIPANTS AND METHODS: Between March 1 and April 21, 2009, a convenience sample of volunteer nurses and physicians was recruited to undergo simulation training consisting of a team response to 3 clinical scenarios. Participants completed the Collaboration and Satisfaction About Care Decisions (CSACD) survey before training and at 2 weeks and 2 months after training. Differences in CSACD summary scores between the time points were assessed with paired t tests. RESULTS: Twenty-eight health care professionals (19 nurses, 9 physicians) underwent simulation training. Nurses were of similar age to physicians (27.3 vs 34.5 years; p=.82), were more likely to be women (95.0% vs 12.5%; p<.001), and were less likely to have undergone prior simulation training (0% vs 37.5%; p=.02). The pretest showed that physicians were more likely to perceive that open communication exists between nurses and physicians (p=.04) and that both medical and nursing concerns influence the decision-making process (p=.02). Pretest CSACD analysis revealed that most participants were dissatisfied with the decision-making process. The CSACD summary score showed significant improvement from baseline to 2 weeks (4.2 to 5.1; p<.002), a trend that persisted at 2 months (p<.002). CONCLUSION: Team training using high-fidelity simulation scenarios promoted collaboration between nurses and physicians and enhanced the patient care decision-making process. PMID:21193653
Wright, Adam; Sittig, Dean F
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:
Tso, Geoffrey J.; Yuen, Kaeli; Martins, Susana; Tu, Samson W.; Ashcraft, Michael; Heidenreich, Paul; Hoffman, Brian B.; Goldstein, Mary K.
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
Owen, Gareth S.; Freyenhagen, Fabian; Martin, Wayne; David, Anthony S.
Assessment of decision-making capacity (DMC) can be difficult in acquired brain injury (ABI) particularly with the syndrome of organic personality disorder (OPD) (the “frontal lobe syndrome”). Clinical neuroscience may help but there are challenges translating its constructs to the decision-making abilities considered relevant by law and ethics. An in-depth interview study of DMC in OPD was undertaken. Six patients were purposefully sampled and rich interview data were acquired for scrutiny using interpretative phenomenological analysis. Interview data revealed that awareness of deficit and thinking about psychological states can be present. However, the awareness of deficit may not be “online” and effectively integrated into decision-making. Without this online awareness of deficit the ability to appreciate or use and weigh information in the process of deciding some matters appeared absent. We argue that the decision-making abilities discussed are: (1) necessary for DMC, (2) threatened by ABI , and (3) assessable at interview. Some advice for practically incorporating these abilities within assessments of DMC in patients with OPD is outlined. PMID:26088818
Montgomery, J B; LaFrancois, G G; Perry, M J
Given limited financial resources, simulation permits a financial analysis of the optimum staffing levels for orthodontists and dental assistants in an orthodontic clinic. A computer simulation provides the information for managerial review. This study, by building a computer simulation of an orthodontic service, set out to determine the most efficient mix between providers and support staff to maximize access, maximize perceived quality, and minimize expenditures. Six combinations of providers and support staff were compared during an animated, computer-generated what-if analysis. Based on the clinic workload and size, on the cost per patient, and on the cost per quality point, the research team recommended a staffing mix of one orthodontist and three assistants. This study shows that computer simulation is an enormous asset as a decision support tool for management.
Berger, Jeffrey T; DeRenzo, Evan G; Schwartz, Jack
The care of adult patients without decision-making abilities is a routine part of medical practice. Decisions for these patients are typically made by surrogates according to a process governed by a hierarchy of 3 distinct decision-making standards: patients' known wishes, substituted judgments, and best interests. Although this framework offers some guidance, it does not readily incorporate many important considerations of patients and families and does not account for the ways in which many patients and surrogates prefer to make decisions. In this article, the authors review the research on surrogate decision making, compare it with normative standards, and offer ways in which the 2 can be reconciled for the patient's benefit.
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...
Kamaleswaran, Rishikesan; McGregor, Carolyn
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.
Graham, Timothy A D; Bullard, Michael J; Kushniruk, Andre W; Holroyd, Brian R; Rowe, Brian H
Clinicians in Emergency Medicine (EM) are increasingly exposed to guidelines and treatment recommendations. To help access and recall these recommendations, electronic Clinical Decision Support Systems (CDSS) have been developed. This study examined the use and sensibility of two CDSS designed for emergency physicians. CDDS for community acquired pneumonia (CAP) and neutropenic fever (NF) were developed by multidisciplinary teams and have been accessed via an intranet-based homepage (eCPG) for several years. Sensibility is a term coined by Feinstein that describes common sense aspects of a survey instrument. It was modified by emergency researchers to include four main headings: (1) Appropriateness; (2) Objectivity; (3) Content; and (4) Discriminative Power. Sensibility surveys were developed using an iterative approach for both the CAP and NF CDSS and distributed to all 25 emergency physicians at one Canadian site. The overall response rate was 88%. Respondents were 88% male and 83% were less than 40; all were attending EM physicians with specialty designations. A number reported never having used the CAP (21%) or NF (33%) CDSS; 54% (CAP) and 21% (NF) of respondents had used the respective CDSS less than 10 times. Overall, both CDSS were rated highly by users with a mean response of 4.95 (SD 0.56) for CAP and 5.62 (SD 0.62) for NF on a seven-point Likert scale. The majority or respondents (CAP 59%, NF 80%) felt that the NF CDSS was more likely than the CAP CDSS to decrease the chances of making a medical error in medication dose, antibiotic choice or patient disposition (4.61 vs. 5.81, p=0.008). Despite being in place for several years, CDSS for CAP and NF are not used by all EM clinicians. Users were generally satisfied with the CDSS and felt that the NF was more likely than the CAP CDSS to decrease medical errors. Additional research is required to determine the barriers to CDSS use.
Abrams, Michael N; Cummings, Simone; Hage, Dana
Care paths map the critical actions and decision points across a patient's course of medical treatment; their purpose is to guide physicians in the delivery of high-quality care while reducing care costs by avoiding services that do not contribute meaningfully to positive outcomes. Each care path development initiative should be led by a respected physician champion, whose specialty is in the area of the care episode being mapped, with the support of a clinician project manager. Once the care path has been developed and implemented, the finance leader's role begins in earnest with the tracking of financial and clinical data against care paths.
Medical ethical analysis remains dominated by the principlist account first proposed by Beauchamp and Childress. This paper argues that the principlist model is unreflective of how ethical decisions are taken in clinical practice. Two kinds of medical ethical decisions are distinguished: biosocial ethics and clinical ethics. It is argued that principlism is an inappropriate model for clinical ethics as it is neither sufficiently action-guiding nor does it emphasise the professional integrity of the clinician. An alternative model is proposed for decision making in the realm of clinical ethics.
Shiffman, Richard N.
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
Falzer, Paul R
Structured professional judgment (SPJ) has received considerable attention as an alternative to unstructured clinical judgment and actuarial assessment, and as a means of resolving their ongoing conflict. However, predictive validity studies have typically relied on receiver operating characteristic (ROC) analysis, the same technique commonly used to validate actuarial assessment tools. This paper presents SPJ as distinct from both unstructured clinical judgment and actuarial assessment. A key distinguishing feature of SPJ is the contribution of modifiable factors, either dynamic or protective, to summary risk ratings. With modifiable factors, the summary rating scheme serves as a prognostic model rather than a classification procedure. However, prognostic models require more extensive and thorough predictive validity testing than can be provided by ROC analysis. It is proposed that validation should include calibration and reclassification techniques, as well as additional measures of discrimination. Several techniques and measures are described and illustrated. The paper concludes by tracing the limitations of ROC analysis to its philosophical foundation and its origin as a statistical theory of decision-making. This foundation inhibits the performance of crucial tasks, such as determining the sufficiency of a risk assessment and examining the evidentiary value of statistical findings. The paper closes by noting a current effort to establish a viable and complementary relationship between SPJ and decision-making theory.
Sher, David J; Punglia, Rinaa S
Although the analysis of real-world data is the foundation of comparative effectiveness analysis, not all clinical questions are easily approached with patient-derived information. Decision analysis is a set of modeling and analytic tools that simulate treatment and disease processes, including the incorporation of patient preferences, thus generating optimal treatment strategies for varying patient, disease, and treatment conditions. Although decision analysis is informed by evidence-derived outcomes, its ability to test treatment strategies under different conditions that are realistic but not necessarily reported in the literature makes it a useful and complementary technique to more standard data analysis. Similarly, cost-effectiveness analysis is a discipline in which the relative costs and benefits of treatment alternatives are rigorously compared. With the well-recognized increase in highly technical, costly radiation therapy technologies, the cost-effectiveness of these different treatments would come under progressively more scrutiny. In this review, we discuss the theoretical and practical aspects of decision analysis and cost-effectiveness analysis, providing examples that highlight their methodology and utility.
Gomoi, Valentin; Vida, Mihaela; Stoicu-Tivadar, Lăcrămioara; Stoicu-Tivadar, Vasile
The paper presents a method connecting medical databases to a medical decision system, and describes a service created to extract the necessary information that is transferred based on standards. The medical decision can be improved based on many inputs from different medical locations. The developed solution is described for a concrete case concerning the management for chronic pelvic pain, based on the information retrieved from diverse healthcare databases.
Jimison, Holly B.
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.
Haasenritter, Jörg; Donner-Banzhoff, Norbert; Bösner, Stefan
Background The Marburg Heart Score (MHS) is a simple, valid, and robust clinical decision rule assisting GPs in ruling out coronary heart disease (CHD) in patients presenting with chest pain. Aim To investigate whether using the rule adds to the GP’s clinical judgement. Design and setting A comparative diagnostic accuracy study was conducted using data from 832 consecutive patients with chest pain in general practice. Method Three diagnostic strategies were defined using the MHS: diagnosis based solely on the MHS; using the MHS as a triage test; and GP’s clinical judgement aided by the MHS. Their accuracy was compared with the GPs’ unaided clinical judgement. Results Sensitivity and specificity of the GPs’ unaided clinical judgement was 82.9% (95% confidence interval [CI] = 72.4 to 89.9) and 61.0% (95% CI = 56.7 to 65.2), respectively. In comparison, the sensitivity of the MHS was higher (difference 8.5%, 95% CI = −2.4 to 19.6) and the specificity was similar (difference −0.4%, 95% CI = −5.3 to 4.5); the sensitivity of the triage was similar (difference −1.5%, 95% CI = −9.8 to 7.0) and the specificity was higher (difference 11.6%, 95% CI = 7.8 to 15.4); and both the sensitivity and specificity of the aided clinical judgement were higher (difference 8.0%, 95% CI = −6.9 to 23.0 and 5.8%, 95% CI = −1.6 to 13.2, respectively). Conclusion Using the Marburg Heart Score for initial triage can improve the clinical diagnosis of CHD in general practice. PMID:26500322
Background Efficient rule authoring tools are critical to allow clinical Knowledge Engineers (KEs), Software Engineers (SEs), and Subject Matter Experts (SMEs) to convert medical knowledge into machine executable clinical decision support rules. The goal of this analysis was to identify the critical success factors and challenges of a fully functioning Rule Authoring Environment (RAE) in order to define requirements for a scalable, comprehensive tool to manage enterprise level rules. Methods The authors evaluated RAEs in active use across Partners Healthcare, including enterprise wide, ambulatory only, and system specific tools, with a focus on rule editors for reminder and medication rules. We conducted meetings with users of these RAEs to discuss their general experience and perceived advantages and limitations of these tools. Results While the overall rule authoring process is similar across the 10 separate RAEs, the system capabilities and architecture vary widely. Most current RAEs limit the ability of the clinical decision support (CDS) interventions to be standardized, sharable, interoperable, and extensible. No existing system meets all requirements defined by knowledge management users. Conclusions A successful, scalable, integrated rule authoring environment will need to support a number of key requirements and functions in the areas of knowledge representation, metadata, terminology, authoring collaboration, user interface, integration with electronic health record (EHR) systems, testing, and reporting. PMID:23145874
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
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
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).
Pfadt, A; Wheeler, D J
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
Mathias, Patrick C.; Tarczy-Hornoch, Peter; Shirts, Brian H.
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
This article presents a quantitative way of modeling the interim decisions of clinical trials. While statistical approaches tend to focus on the epistemic aspects of statistical monitoring rules, often overlooking ethical considerations, ethical approaches tend to neglect the key epistemic dimension. The proposal is a second-order decision-analytic framework. The framework provides means for retrospective assessment of interim decisions based on a clear and consistent set of criteria that combines both ethical and epistemic considerations. The framework is broadly Bayesian and addresses a fundamental question behind many concerns about clinical trials: What does it take for an interim decision (e.g., whether to stop the trial or continue) to be a good decision? Simulations illustrating the modeling of interim decisions counterfactually are provided.
Hancock, Helen C; Durham, Lesley
As the extension of nursing into roles previously within the domain of medicine and the demand for evidence based practice continue to increase, the quality of decision making becomes imperative. Making accurate decisions is essential, both for the practitioner and for the patient, especially in the provision of critical care outreach (CCOR), to improve outcomes of care. With changes in health care delivery and increased accountability for practitioners' decisions, it is important to understand more about how clinical decisions are made and what factors influence them in order to inform practice. The previous paper outlined the theoretical background of clinical decision making and the knowledge that underpins practice in CCOR. In this paper, the authors, a Nurse Consultant in CCOR and a research fellow, examine the process of a practitioner's decision making in the practice of CCOR, through a collaborative reflective account of a case study. From this, recommendations are made about the future development of CCOR practitioners and services.
This article presents a quantitative way of modeling the interim decisions of clinical trials. While statistical approaches tend to focus on the epistemic aspects of statistical monitoring rules, often overlooking ethical considerations, ethical approaches tend to neglect the key epistemic dimension. The proposal is a second-order decision-analytic framework. The framework provides means for retrospective assessment of interim decisions based on a clear and consistent set of criteria that combines both ethical and epistemic considerations. The framework is broadly Bayesian and addresses a fundamental question behind many concerns about clinical trials: What does it take for an interim decision (e.g., whether to stop the trial or continue) to be a good decision? Simulations illustrating the modeling of interim decisions counterfactually are provided. PMID:27353825
McCullough, Laurence B
The professional medical ethics model of decision making may be applied to decisions clinicians and patients make under the conditions of clinical uncertainty that exist when evidence is low or very low. This model uses the ethical concepts of medicine as a profession, the professional virtues of integrity and candor and the patient's virtue of prudence, the moral management of medical uncertainty, and trial of intervention. These features combine to justifiably constrain clinicians' and patients' autonomy with the goal of preventing nondeliberative decisions of patients and clinicians. To prevent biased recommendations by the clinician that promote such nondeliberative decisions, medically reasonable alternatives supported by low or very low evidence should be offered but not recommended. The professional medical ethics model of decision making aims to improve the quality of decisions by reducing the unacceptable variation that can result from nondeliberative decision making by patients and clinicians when evidence is low or very low.
Ash, Joan S.; Chase, Dian; Wiesen, Jane F.; Murphy, Elizabeth V.; Marovich, Stacey
To determine how the Rapid Assessment Process (RAP) can be adapted to evaluate the readiness of primary care clinics for acceptance and use of computerized clinical decision support (CDS) related to clinical management of working patients, we used a unique blend of ethnographic methods for gathering data. First, knowledge resources, which were prototypes of CDS content areas (diabetes, lower back pain, and asthma) containing evidence-based information, decision logic, scenarios and examples of use, were developed by subject matter experts. A team of RAP researchers then visited five clinic settings to identify barriers and facilitators to implementing CDS about the health of workers in general and the knowledge resources specifically. Methods included observations, semi-structured qualitative interviews and graphic elicitation interviews about the knowledge resources. We used both template and grounded hermeneutic approaches to data analysis. Preliminary results indicate that the methods succeeded in generating specific actionable recommendations for CDS design. PMID:28269822
Ash, Joan S; Chase, Dian; Wiesen, Jane F; Murphy, Elizabeth V; Marovich, Stacey
To determine how the Rapid Assessment Process (RAP) can be adapted to evaluate the readiness of primary care clinics for acceptance and use of computerized clinical decision support (CDS) related to clinical management of working patients, we used a unique blend of ethnographic methods for gathering data. First, knowledge resources, which were prototypes of CDS content areas (diabetes, lower back pain, and asthma) containing evidence-based information, decision logic, scenarios and examples of use, were developed by subject matter experts. A team of RAP researchers then visited five clinic settings to identify barriers and facilitators to implementing CDS about the health of workers in general and the knowledge resources specifically. Methods included observations, semi-structured qualitative interviews and graphic elicitation interviews about the knowledge resources. We used both template and grounded hermeneutic approaches to data analysis. Preliminary results indicate that the methods succeeded in generating specific actionable recommendations for CDS design.
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…
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...
The Causal Analysis/Diagnosis Decision Information System, or CADDIS, is a website developed to help scientists and engineers in the Regions, States, and Tribes conduct causal assessments in aquatic systems.
Juan D. Deaton; Luiz A. DaSilva; Christian Wernz
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.
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…
Krumwiede, Kelly A.
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.…
strategies and mechanisms of judgment and choice as well as the phases of decision evaluation and the roles of feedback and learning in individual...o I14 - -4 C3 0 E H 41 -4 CJ EQ U) )4.w H Efl -- 40 H c 0 - 0 U) 4 E-1 0~ C44 P4 0 ca) V0- z LI, H Q) - 104. 00 -c -4Ln 4 I
Izadi, Masoumeh T; Buckeridge, David L
The potentially catastrophic impact of an epidemic specially these due to bioterrorist attack, makes developing effective detection methods essential for public health. Current detection methods trade off reliability of alarms for early detection of outbreaks. The performance of these methods can be improved by disease-specific modeling techniques that take into account the potential costs and effects of an attack to provide optimal warnings and the cost and effectiveness of interventions. We study this optimization problem in the framework of sequential decision making under uncertainty. Our approach relies on estimating the future benefit of true alarms and the costs of false alarms. Using these quantities it identifies optimal decisions regarding the credibility of outputs from a traditional detection method at each point in time. The key contribution of this paper is to apply Partially Observable Markov Decision Processes (POMDPs) on outbreak detection methods for improving alarm function in the case of anthrax. We present empirical evidence illustrating that at a fixed specificity, the performance of detection methods with respect to sensitivity and timeliness is improved significantly by utilizing POMDPs in detection of anthrax attacks.
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…
Phillips, Wendy J; Fletcher, Jennifer M; Marks, Anthony D G; Hine, Donald W
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.
Wright, Adam; Sittig, Dean F.
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
Hennessey, Adam; Setyono, Devy A; Lau, Wayne Bond; Fields, Jason Matthew
We report a patient with chest pain who was classified as having low risk for pulmonary embolism with clinical gestalt and accepted clinical decision rules. An inadvertently ordered D-dimer and abnormal result, however, led to the identification of a large saddle embolus. This case illustrates the fallibility of even well-validated decision aids and that an embolism missed by these tools is not necessarily low risk or indicative of a low clot burden.
Sousa, Vanessa E C; Lopez, Karen Dunn; Febretti, Alessandro; Stifter, Janet; Yao, Yingwei; Johnson, Andrew; Wilkie, Diana J; Keenan, Gail M
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.
Waran, Eswaran; William, Leeroy
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.
Narra, Lekha; Sahama, Tony; Stapleton, Peta
Large volumes of heterogeneous health data silos pose a big challenge when exploring for information to allow for evidence based decision making and ensuring quality outcomes. In this paper, we present a proof of concept for adopting data warehousing technology to aggregate and analyse disparate health data in order to understand the impact various lifestyle factors on obesity. We present a practical model for data warehousing with detailed explanation which can be adopted similarly for studying various other health issues.
Roszkowski, Krzysztof; Furtak, Jacek; Zurawski, Bogdan; Szylberg, Tadeusz; Lewandowska, Marzena A.
The IDH1/2 gene mutations, ATRX loss/mutation, 1p/19q status, and MGMT promoter methylation are increasingly used as prognostic or predictive biomarkers of gliomas. However, the effect of their combination on radiation therapy outcome is discussable. Previously, we demonstrated that the IDH1 c.G395A; p.R132H mutation was associated with longer survival in grade II astrocytoma and GBM (Glioblastoma). Here we analyzed the MGMT promoter methylation status in patients with a known mutation status in codon 132 of IDH1, followed by clinical and genetic data analysis based on the two statuses. After a subtotal tumor resection, the patients were treated using IMRT (Intensity-Modulated Radiation Therapy) with 6 MeV photons. The total dose was: 54 Gy for astrocytoma II, 60 Gy for astrocytoma III, 60 Gy for glioblastoma, 2 Gy per day, with 24 h intervals, five days per week. The patients with MGMT promoter methylation and IDH1 somatic mutation (OS = 40 months) had a better prognosis than those with MGMT methylation alone (OS = 18 months). In patients with astrocytoma anaplasticum (n = 7) with the IDH1 p.R132H mutation and hypermethylated MGMT, the prognosis was particularly favorable (median OS = 47 months). In patients with astrocytoma II meeting the above criteria, the prognosis was also better than in those not meeting those criteria. The IDH1 mutation appears more relevant for the prognosis than MGMT methylation. The IDH1 p.R132H mutation combined with MGMT hypermethylation seems to be the most advantageous for treatment success. Patients not meeting those criteria may require more aggressive treatments. PMID:27834917
Fusaro, Vincent A; Brownstein, Catherine; Wolf, Wendy; Clinton, Catherine; Savage, Sarah; Mandl, Kenneth D; Margulies, David; Manzi, Shannon
Advances in sequencing technology are making genomic data more accessible within the healthcare environment. Published pharmacogenetic guidelines attempt to provide a clinical context for specific genomic variants; however, the actual implementation to convert genomic data into a clinical report integrated within an electronic medical record system is a major challenge for any hospital. We created a two-part solution that integrates with the medical record system and converts genetic variant results into an interpreted clinical report based on published guidelines. We successfully developed a scalable infrastructure to support TPMT genetic testing and are currently testing approximately two individuals per week in our production version. We plan to release an online variant to clinical interpretation reporting system in order to facilitate translation of pharmacogenetic information into clinical practice.
Légaré, France; Witteman, Holly O
For many patients, the time spent meeting with their physician-the clinical encounter-is the most opportune moment for them to become engaged in their own health through the process of shared decision making. In the United States shared decision making is being promoted for its potential to improve the health of populations and individual patients, while also helping control care costs. In this overview we describe the three essential elements of shared decision making: recognizing and acknowledging that a decision is required; knowing and understanding the best available evidence; and incorporating the patient's values and preferences into the decision. To achieve the promise of shared decision making, more physicians need training in the approach, and more practices need to be reorganized around the principles of patient engagement. Additional research is also needed to identify the interventions that are most effective.
Ebadian, M.A.; Boudreaux, J.F.; Chinta, S.; Zanakis, S.H.
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.
Background Underuse and overuse of diagnostic tests have important implications for health outcomes and costs. Decision support technology purports to optimize the use of diagnostic tests in clinical practice. The objective of this review was to assess whether computerized clinical decision support systems (CCDSSs) are effective at improving ordering of tests for diagnosis, monitoring of disease, or monitoring of treatment. The outcome of interest was effect on the diagnostic test-ordering behavior of practitioners. Methods We conducted a decision-maker-researcher partnership systematic review. We searched MEDLINE, EMBASE, Ovid's EBM Reviews database, Inspec, and reference lists for eligible articles published up to January 2010. We included randomized controlled trials comparing the use of CCDSSs to usual practice or non-CCDSS controls in clinical care settings. Trials were eligible if at least one component of the CCDSS gave suggestions for ordering or performing a diagnostic procedure. We considered studies 'positive' if they showed a statistically significant improvement in at least 50% of test ordering outcomes. Results Thirty-five studies were identified, with significantly higher methodological quality in those published after the year 2000 (p = 0.002). Thirty-three trials reported evaluable data on diagnostic test ordering, and 55% (18/33) of CCDSSs improved testing behavior overall, including 83% (5/6) for diagnosis, 63% (5/8) for treatment monitoring, 35% (6/17) for disease monitoring, and 100% (3/3) for other purposes. Four of the systems explicitly attempted to reduce test ordering rates and all succeeded. Factors of particular interest to decision makers include costs, user satisfaction, and impact on workflow but were rarely investigated or reported. Conclusions Some CCDSSs can modify practitioner test-ordering behavior. To better inform development and implementation efforts, studies should describe in more detail potentially important factors such
among multiple objectives makes it valuable for government decision making. Within decision analysis, multiattribute utility theory is considered...involves multiple objectives – and this is almost always the case with important problems – multiattribute utility theory forms the basic...November 3, 2000). (3) “A preference function under uncertainty” ( Dyer and Sarin, 1979: 810). UTILITY THEORY – See EXPECTED UTILITY . TIER – See
Kagan, Jonathan M; Gupta, Nitin; Varghese, Suresh; Virkar, Hemant
The National Institute of Allergy and Infectious Diseases (NIAID) Division of AIDS (DAIDS) Enterprise Information System (DAIDS-ES) is a web-based system that supports NIAID in the scientific, strategic, and tactical management of its global clinical research programs for HIV/AIDS vaccines, prevention, and therapeutics. Different from most commercial clinical trials information systems, which are typically protocol-driven, the DAIDS-ES was built to exchange information with those types of systems and integrate it in ways that help scientific program directors lead the research effort and keep pace with the complex and ever-changing global HIV/AIDS pandemic. Whereas commercially available clinical trials support systems are not usually disease-focused, DAIDS-ES was specifically designed to capture and incorporate unique scientific, demographic, and logistical aspects of HIV/AIDS treatment, prevention, and vaccine research in order to provide a rich source of information to guide informed decision-making. Sharing data across its internal components and with external systems, using defined vocabularies, open standards and flexible interfaces, the DAIDS-ES enables NIAID, its global collaborators and stakeholders, access to timely, quality information about NIAID-supported clinical trials which is utilized to: (1) analyze the research portfolio, assess capacity, identify opportunities, and avoid redundancies; (2) help support study safety, quality, ethics, and regulatory compliance; (3) conduct evidence-based policy analysis and business process re-engineering for improved efficiency. This report summarizes how the DAIDS-ES was conceptualized, how it differs from typical clinical trial support systems, the rationale for key design choices, and examples of how it is being used to advance the efficiency and effectiveness of NIAID's HIV/AIDS clinical research programs.
Jiang, Jingchi; Zheng, Jichuan; Zhao, Chao; Su, Jia; Guan, Yi; Yu, Qiubin
In making clinical decisions, clinicians often review medical literature to ensure the reliability of diagnosis, test, and treatment because the medical literature can answer clinical questions and assist clinicians making clinical decisions. Therefore, finding the appropriate literature is a critical problem for clinical-decision support (CDS). First, the present study employs search engines to retrieve relevant literature about patient records. However, the result of the traditional method is usually unsatisfactory. To improve the relevance of the retrieval result, a medical literature network (MLN) based on these retrieved papers is constructed. Then, we show that this MLN has small-world and scale-free properties of a complex network. According to the structural characteristics of the MLN, we adopt two methods to further identify the potential relevant literature in addition to the retrieved literature. By integrating these potential papers into the MLN, a more comprehensive MLN is built to answer the question of actual patient records. Furthermore, we propose a re-ranking model to sort all papers by relevance. We experimentally find that the re-ranking model can improve the normalized discounted cumulative gain of the results. As participants of the Text Retrieval Conference 2015, our clinical-decision method based on the MLN also yields higher scores than the medians in most topics and achieves the best scores for topics: #11 and #12. These research results indicate that our study can be used to effectively assist clinicians in making clinical decisions, and the MLN can facilitate the investigation of CDS.
Lutz, Wolfgang; Saunders, Stephen M.; Leon, Scott C.; Martinovich, Zoran; Kosfelder, Joachim; Schulte, Dietmar; Grawe, Klaus; Tholen, Sven
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…
Bauer, Nerissa S.; Sturm, Lynne A.; Carroll, Aaron E.; Downs, Stephen M.
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…
Szkoła, Jarosław; Pancerz, Krzysztof; Warchoł, Jan
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.
Montibeller, Gilberto; von Winterfeldt, Detlof
Behavioral decision research has demonstrated that judgments and decisions of ordinary people and experts are subject to numerous biases. Decision and risk analysis were designed to improve judgments and decisions and to overcome many of these biases. However, when eliciting model components and parameters from decisionmakers or experts, analysts often face the very biases they are trying to help overcome. When these inputs are biased they can seriously reduce the quality of the model and resulting analysis. Some of these biases are due to faulty cognitive processes; some are due to motivations for preferred analysis outcomes. This article identifies the cognitive and motivational biases that are relevant for decision and risk analysis because they can distort analysis inputs and are difficult to correct. We also review and provide guidance about the existing debiasing techniques to overcome these biases. In addition, we describe some biases that are less relevant because they can be corrected by using logic or decomposing the elicitation task. We conclude the article with an agenda for future research.
Markov models (Multistate transition models) are mathematical tools to simulate a cohort of individuals followed over time to assess the prognosis resulting from different strategies. They are applied on the assumption that persons are in one of a finite number of states of health (Markov states). Each condition is given a transition probability as well as an incremental value. Probabilities may be chosen constant or varying over time due to predefined rules. Time horizon is divided into equal increments (Markov cycles). The model calculates quality-adjusted life expectancy employing real-life units and values and summing up the length of time spent in each health state adjusted for objective outcomes and subjective appraisal. This sort of modeling prognosis for a given patient is analogous to utility in common decision trees. Markov models can be evaluated by matrix algebra, probabilistic cohort simulation and Monte Carlo simulation. They have been applied to assess the relative benefits and risks of a limited number of diagnostic and therapeutic procedures in radiology. More interventions should be submitted to Markov analyses in order to elucidate their cost-effectiveness.
Corcoran, S; Narayan, S; Moreland, H
Although "thinking aloud" has been used as a research method to collect data about nurses' knowledge and cognitive processes, it has not been used widely for instruction. We suggest that thinking aloud can be an effective teaching strategy for staff development. Two techniques are described for incorporating thinking aloud into dialogue among experienced nurses and into mentoring activities between experts and novices. An excerpt from a transcript of one nurse's thinking aloud while making a triage decision is presented to illustrate the types of knowledge and cognitive processes that can be elicited and revealed by using this strategy. Potential educational benefits are identified, along with suggestions for implementing thinking aloud as an instructional method.
Furberg, Robert D; Bagwell, Jacqueline E; LaBresh, Kenneth A
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
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…
Banzi, Rita; González-Lorenzo, Marien; Kwag, Koren Hyogene; Bonovas, Stefanos; Moja, Lorenzo
Evidence-based healthcare requires the integration of the best research evidence with clinical expertise and patients' values. International publishers are developing evidence-based information services and resources designed to overcome the difficulties in retrieving, assessing and updating medical information as well as to facilitate a rapid access to valid clinical knowledge. Point-of-care information summaries are defined as web-based medical compendia that are specifically designed to deliver pre-digested, rapidly accessible, comprehensive, and periodically updated information to health care providers. Their validity must be assessed against marketing claims that they are evidence-based. We periodically evaluate the content development processes of several international point-of-care information summaries. The number of these products has increased along with their quality. The last analysis done in 2014 identified 26 products and found that three of them (Best Practice, Dynamed e Uptodate) scored the highest across all evaluated dimensions (volume, quality of the editorial process and evidence-based methodology). Point-of-care information summaries as stand-alone products or integrated with other systems, are gaining ground to support clinical decisions. The choice of one product over another depends both on the properties of the service and the preference of users. However, even the most innovative information system must rely on transparent and valid contents. Individuals and institutions should regularly assess the value of point-of-care summaries as their quality changes rapidly over time.
Inada, Masanori; Sato, Mayumi; Yoneyama, Akiko
This paper discusses a knowledge management system for clinical laboratories. In the clinical laboratory of Toranomon Hospital, we receive about 20 questions relevant to laboratory tests per day from medical doctors or co-medical staff. These questions mostly involve the essence to appropriately accomplish laboratory tests. We have to answer them carefully and suitably because an incorrect answer may cause a medical accident. Up to now, no method has been in place to achieve a rapid response and standardized answers. For this reason, the laboratory staff have responded to various questions based on their individual knowledge. We began to develop a knowledge management system to promote the knowledge of staff working for the laboratory. This system is a type of knowledge base for assisting the work, such as inquiry management, laboratory consultation, process management, and clinical support. It consists of several functions: guiding laboratory test information, managing inquiries from medical staff, reporting results of patient consultation, distributing laboratory staffs notes, and recording guidelines for laboratory medicine. The laboratory test information guide has 2,000 records of medical test information registered in the database with flexible retrieval. The inquiry management tool provides a methos to record all questions, answer easily, and retrieve cases. It helps staff to respond appropriately in a short period of time. The consulting report system treats patients' claims regarding medical tests. The laboratory staffs notes enter a file management system so they can be accessed to aid in clinical support. Knowledge sharing using this function can achieve the transition from individual to organizational learning. Storing guidelines for laboratory medicine will support EBM. Finally, it is expected that this system will support intellectual activity concerning laboratory work and contribute to the practice of knowledge management for clinical work support.
Davies, A L; Bryce, R; Redpath, S M
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.
Lansdowne, Chatwin A.; Steele, Glen F.; Zucha, Joan P.; Schlesinger, Adam M.
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.
Raju, G K; Gurumurthi, K; Domike, R
The analysis of benefit and risk is an important aspect of decision-making throughout the drug lifecycle. In this work, the use of a benefit-risk analysis approach to support decision-making was explored. The proposed approach builds on the qualitative US Food and Drug Administration (FDA) approach to include a more explicit analysis based on international standards and guidance that enables aggregation and comparison of benefit and risk on a common basis and a lifecycle focus. The approach is demonstrated on six decisions over the lifecycle (e.g., accelerated approval, withdrawal, and traditional approval) using two case studies: natalizumab for multiple sclerosis (MS) and bedaquiline for multidrug-resistant tuberculosis (MDR-TB).
Stanley, R Joe; De, Soumya; Demner-Fushman, Dina; Antani, Sameer; Thoma, George R
The illustrations in biomedical publications often provide useful information in aiding clinicians' decisions when full text searching is performed to find evidence in support of a clinical decision. In this research, image analysis and classification techniques are explored to automatically extract information for differentiating specific modalities to characterize illustrations in biomedical publications, which may assist in the evidence finding process. Global, histogram-based, and texture image illustration features were compared to basis function luminance histogram correlation features for modality-based discrimination over a set of 742 manually annotated images by modality (radiological, photo, etc.) selected from the 2004-2005 issues of the British Journal of Oral and Maxillofacial Surgery. Using a mean shifting supervised clustering technique, automatic modality-based discrimination results as high as 95.57% were obtained using the basis function features. These results compared favorably to other feature categories examined. The experimental results show that image-based features, particularly correlation-based features, can provide useful modality discrimination information.
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 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.
Lawrence, R E; Curlin, F A
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
Muir-Cochrane, Eimear; Gerace, Adam; Mosel, Krista; O'Kane, Debra; Barkway, Patricia; Curren, David; Oster, Candice
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.
Sordo, Margarita; Ogunyemi, Omolola; Boxwala, Aziz A.; Greenes, Robert A.
GELLO is a purpose-specific, object-oriented (OO) query and expression language . GELLO is the result of a concerted effort of the Decision Systems Group (DSG) working with the HL7 Clinical Decision Support Technical Committee (CDSTC) to provide the HL7 community with a common format for data encoding and manipulation. GELLO will soon be submitted for ballot to the HL7 CDSTC for consideration as a standard. PMID:14728515
CONTAINED A SIGNIFICANT NUMBER OF PAGES WHICH DO NOT REPRODUCE LEGIBLY. AFIT/GOR/AA/81 0-1 MADAM : MULTIPLE-ATTRIBUTE DECISION ANALYSIS MODEL VOLUME...11 T!IFSIS w T C AFIT/GOR/AA/81D-I Wayne A. Stimpson (J> CC’ T 2Lt USAFR ~~FEB 1 9 1982 AFITj,0R/AA/81 D-1 Thes is t", MADAM : MULTIPLE-ATTRIBUTE...objectives to be satisfied. The program is MADAM : Multiple-Attribute Decision Analysis Model, and it is written in FORTRAN V and is implemented on the
Sayyad Shirabad, Jelber; Wilk, Szymon; Michalowski, Wojtek; Farion, Ken
Clinical decision making is a complex multi-stage process. Decision support can play an important role at each stage of this process. At present, the majority of clinical decision support systems have been focused on supporting only certain stages. In this paper we present the design and implementation of MET3-a prototype multi-agent system providing an integrative decision support that spans over the entire decision making process. The system helps physicians with data collection, diagnosis formulation, treatment planning and finding supporting evidence. MET3 integrates with external hospital information systems via HL7 messages and runs on various computing platforms available at the point of care (e.g., tablet computers, mobile phones). Building MET3 required sophisticated and reliable software technologies. In the past decade the open source software movement has produced mature, stable, industrial strength software systems with a large user base. Therefore, one of the decisions that should be considered before developing or acquiring a decision support system is whether or not one could use open source technologies instead of proprietary ones. We believe MET3 shows that the answer to this question is positive.
Background Decision curve analysis has been introduced as a method to evaluate prediction models in terms of their clinical consequences if used for a binary classification of subjects into a group who should and into a group who should not be treated. The key concept for this type of evaluation is the "net benefit", a concept borrowed from utility theory. Methods We recall the foundations of decision curve analysis and discuss some new aspects. First, we stress the formal distinction between the net benefit for the treated and for the untreated and define the concept of the "overall net benefit". Next, we revisit the important distinction between the concept of accuracy, as typically assessed using the Youden index and a receiver operating characteristic (ROC) analysis, and the concept of utility of a prediction model, as assessed using decision curve analysis. Finally, we provide an explicit implementation of decision curve analysis to be applied in the context of case-control studies. Results We show that the overall net benefit, which combines the net benefit for the treated and the untreated, is a natural alternative to the benefit achieved by a model, being invariant with respect to the coding of the outcome, and conveying a more comprehensive picture of the situation. Further, within the framework of decision curve analysis, we illustrate the important difference between the accuracy and the utility of a model, demonstrating how poor an accurate model may be in terms of its net benefit. Eventually, we expose that the application of decision curve analysis to case-control studies, where an accurate estimate of the true prevalence of a disease cannot be obtained from the data, is achieved with a few modifications to the original calculation procedure. Conclusions We present several interrelated extensions to decision curve analysis that will both facilitate its interpretation and broaden its potential area of application. PMID:21696604
Kim, Heejun; Bian, Jiantao; Mostafa, Javed; Jonnalagadda, Siddhartha; Del Fiol, Guilherme
Motivation: Clinicians need up-to-date evidence from high quality clinical trials to support clinical decisions. However, applying evidence from the primary literature requires significant effort. Objective: To examine the feasibility of automatically extracting key clinical trial information from ClinicalTrials.gov. Methods: We assessed the coverage of ClinicalTrials.gov for high quality clinical studies that are indexed in PubMed. Using 140 random ClinicalTrials.gov records, we developed and tested rules for the automatic extraction of key information. Results: The rate of high quality clinical trial registration in ClinicalTrials.gov increased from 0.2% in 2005 to 17% in 2015. Trials reporting results increased from 3% in 2005 to 19% in 2015. The accuracy of the automatic extraction algorithm for 10 trial attributes was 90% on average. Future research is needed to improve the algorithm accuracy and to design information displays to optimally present trial information to clinicians. PMID:28269867
Kim, Heejun; Bian, Jiantao; Mostafa, Javed; Jonnalagadda, Siddhartha; Del Fiol, Guilherme
Motivation: Clinicians need up-to-date evidence from high quality clinical trials to support clinical decisions. However, applying evidence from the primary literature requires significant effort. Objective: To examine the feasibility of automatically extracting key clinical trial information from ClinicalTrials.gov. Methods: We assessed the coverage of ClinicalTrials.gov for high quality clinical studies that are indexed in PubMed. Using 140 random ClinicalTrials.gov records, we developed and tested rules for the automatic extraction of key information. Results: The rate of high quality clinical trial registration in ClinicalTrials.gov increased from 0.2% in 2005 to 17% in 2015. Trials reporting results increased from 3% in 2005 to 19% in 2015. The accuracy of the automatic extraction algorithm for 10 trial attributes was 90% on average. Future research is needed to improve the algorithm accuracy and to design information displays to optimally present trial information to clinicians.
Wang, You; Xu, Hui; Zhang, Jianming; Li, Guang
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. PMID:27879810
Fluke, John D.; Chabot, Martin; Fallon, Barbara; MacLaurin, Bruce; Blackstock, Cindy
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…
Rating Technique (SMART) as a direct response to Raiffa’s (1969) article on multiattribute utility theory , which Edwards found extremcy stimulating but...approaches such as multiattribute utility /value assessment and hierarchical analysis and have applied these techniques to a number of non-military... multiattributed ) outcomes O(l)...O(k), and if the utility function is denoted by u and the probabilities of the k events are p(l)...p(k), then the
Vahabzadeh, Massoud; Lin, Jia-Ling; Mezghanni, Mustapha; Contoreggi, Carlo; Leff, Michelle
A clinical recruiting management system with qualification decision support systems was developed to increase the efficiency of screening and evaluation of participants during a recruiting process whereby recruiting for various protocols are conducted at multiple sites by different groups with process interdependencies. This system is seamlessly integrated into our enterprise-scale Human Research Information System (HuRIS), encompassing research participants' electronic health records (EHR), with real-time access to the clinical trial data.
Yu, Peter Paul
One of the most important benefits of health information technology is to assist the cognitive process of the human mind in the face of vast amounts of health data, limited time for decision making, and the complexity of the patient with cancer. Clinical decision support tools are frequently cited as a technologic solution to this problem, but to date useful clinical decision support systems (CDSS) have been limited in utility and implementation. This article describes three unique sources of health data that underlie fundamentally different types of knowledge bases which feed into CDSS. CDSS themselves comprise a variety of models which are discussed. The relationship of knowledge bases and CDSS to rapid learning health systems design is critical as CDSS are essential drivers of rapid learning in clinical care.
Panzarasa, Silvia; Quaglini, Silvana; Cavallini, Anna; Micieli, Giuseppe; Pernice, Corrado; Pessina, Mauro; Stefanelli, Mario
Literature results and personal experience show that intrusive modalities of presenting suggestions of computerized clinical practice guidelines are detrimental to the routine use of an information system. This paper describes a solution for smoothly integrating a guideline-based decision support system into an existing computerized clinical chart for patients admitted to a Stroke Unit. Since many years, the healthcare personnel were using a commercial product for the ordinary patients’ data management, and they were satisfied with it. Thus, the decision support system has been integrated keeping attention to minimize changes and preserve existing human-computer interaction. Our decision support system is based on workflow technology. The paper illustrates the middleware layer developed to allow communication between the workflow management system and the clinical chart. At the same time, the consequent modification of the graphical users' interface is illustrated. PMID:17238415
Teran, Felipe; Harper-Kirksey, Katrina; Jagoda, Andy
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.
Deldar, Kolsoum; Bahaadinbeigy, Kambiz; Tara, Seyed Mahmood
Background: The goal of teleconsultation is to omit geographical and functional distance between two or more geographically separated health care providers. The purpose of present study is to review and analyze physician-physician teleconsultations. Method: The PubMed electronic database was searched. The primary search was done on January 2015 and was updated on December 2015. A fetch and tag plan was designed by the researchers using an online Zotero library. Results: 174 full-text articles of 1702 records met inclusion criteria. Teleconsultation for pediatric patients accounts for 14.36 percent of accepted articles. Surgery and general medicine were the most prevalent medical fields in the adults and pediatrics, respectively. Most teleconsultations were inland experiences (no=135), and the USA, Italy and Australia were the three top countries in this group. Non-specialists health care providers/centers were the dominant group who requested teleconsultation (no=130). Real time, store and forward, and hybrid technologies were used in 50, 31, and 16.7 percent of articles, respectively. The teleconsultation were reported to result in change in treatment plan, referral or evacuation rate, change in diagnosis, educational effects, and rapid decision making. Use of structured or semi-structured template had been noticed only in a very few articles. Conclusion: The present study focused on the recent ten years of published articles on physician-physician teleconsultations. Our findings showed that although there are positive impacts of teleconsultation as improving patient management, still have gaps that need to be repaired. PMID:27708494
Buring, Shauna; Cluxton, Robert
Objective. To implement and assess the effectiveness of a 2-course collaborative decision analysis project intended to help students understand the relevance of pharmacoeconomics to clinical pharmacy practice and provide them an opportunity to apply skills taught in pharmacoeconomics to a “real world” problem. Design. Students were assigned a pair of drugs, 1 commonly used as standard therapy and 1 newly approved, and conducted a decision analysis. The results were then used in a mock pharmacy and therapeutics (P&T) committee meeting. Assessment. Ninety-eight of 106 (92%) students completed a 4-question survey instrument. Ninety-six percent of students agreed or somewhat agreed that the decision analysis project met the learning objectives. Students felt the shared assignment influenced their choice of formulary drug, augmented understanding of factors influencing decisions, broadened their thinking about drug costs, and was a good approximation of a “real world” application. Conclusion. An innovative joint-course assignment proved to be a successful technique for teaching decision analysis. PMID:22919091
Eberlein, Susan; Yates, Gigi
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.
Engel, David W.
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.
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…
Background Opioid prescribing for chronic pain is common and controversial, but recommended clinical practices are followed inconsistently in many clinical settings. Strategies for increasing adherence to clinical practice guideline recommendations are needed to increase effectiveness and reduce negative consequences of opioid prescribing in chronic pain patients. Methods Here we describe the process and outcomes of a project to operationalize the 2003 VA/DOD Clinical Practice Guideline for Opioid Therapy for Chronic Non-Cancer Pain into a computerized decision support system (DSS) to encourage good opioid prescribing practices during primary care visits. We based the DSS on the existing ATHENA-DSS. We used an iterative process of design, testing, and revision of the DSS by a diverse team including guideline authors, medical informatics experts, clinical content experts, and end-users to convert the written clinical practice guideline into a computable algorithm to generate patient-specific recommendations for care based upon existing information in the electronic medical record (EMR), and a set of clinical tools. Results The iterative revision process identified numerous and varied problems with the initially designed system despite diverse expert participation in the design process. The process of operationalizing the guideline identified areas in which the guideline was vague, left decisions to clinical judgment, or required clarification of detail to insure safe clinical implementation. The revisions led to workable solutions to problems, defined the limits of the DSS and its utility in clinical practice, improved integration into clinical workflow, and improved the clarity and accuracy of system recommendations and tools. Conclusions Use of this iterative process led to development of a multifunctional DSS that met the approval of the clinical practice guideline authors, content experts, and clinicians involved in testing. The process and experiences described
Rodriguez-Loya, Salvador; Aziz, Ayesha; Chatwin, Chris
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).
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
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
Hruska, Pam; Hecker, Kent G; Coderre, Sylvain; McLaughlin, Kevin; Cortese, Filomeno; Doig, Christopher; Beran, Tanya; Wright, Bruce; Krigolson, Olav
Clinical decision making requires knowledge, experience and analytical/non-analytical types of decision processes. As clinicians progress from novice to expert, research indicates decision-making becomes less reliant on foundational biomedical knowledge and more on previous experience. In this study, we investigated how knowledge and experience were reflected in terms of differences in neural areas of activation. Novice and expert clinicians diagnosed simple or complex (easy, hard) cases while functional magnetic resonance imaging (fMRI) data were collected. Our results highlight key differences in the neural areas activated in novices and experts during the clinical decision-making process. fMRI data were collected from ten second year medical students (novices) and ten practicing gastroenterologists (experts) while they diagnosed sixteen (eight easy and eight hard) clinical cases via multiple-choice questions. Behavioral data were collected for diagnostic accuracy (correct/incorrect diagnosis) and time taken to assign a clinical diagnosis. Two analyses were performed with the fMRI data. First, data from easy and hard cases were compared within respective groups (easy > hard, hard > easy). Second, neural differences between novices and experts (novice > expert, expert > novice) were assessed. Experts correctly diagnosed more cases than novices and made their diagnoses faster than novices on both easy and hard cases (all p's < 0.05). Time taken to diagnose hard cases took significantly longer for both novices and experts. While similar neural areas were activated in both novices and experts during the decision making process, we identified significant hemispheric activation differences between novice and expert clinicians when diagnosing hard clinical cases. Specifically, novice clinicians had greater activations in the left anterior temporal cortex and left ventral lateral prefrontal cortex whereas expert clinicians had greater activations in the right
Crofts, Gillian; Padman, Rema; Maharaja, Nisha
Ultrasound is a low cost and efficient method of detecting diseases and abnormalities in the body. Yet there is a lack of precision and reliability associated with the technology, partly due to the operator dependent nature of ultrasound scanning. When scanning is performed to an agreed protocol, ultrasound has been shown to be highly reliable. This research aims to minimize these limitations that arise during ultrasound training, scanning and reporting by developing and evaluating an image analysis and decision support system that can aid the decision making process. We hypothesize that this intervention will likely increase the role of ultrasound in diagnosis when compared with other imaging technologies, particularly in low resource settings.
Backus, George A.; Siirola, John Daniel; Schoenwald, David Alan; Strip, David R.; Hirsch, Gary B.; Bastian, Mark S.; Braithwaite, Karl R.; Homer, Jack
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.
Engel, David W.; Dalton, Angela C.; Dale, Crystal; Jones, Edward; Thompson, J.
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.
Mengersen, Kerrie; MacNeil, M Aaron; Caley, M Julian
Meta-analysis and decision analysis are underpinned by well-developed methods that are commonly applied to a variety of problems and disciplines. While these two fields have been closely linked in some disciplines such as medicine, comparatively little attention has been paid to the potential benefits of linking them in ecology, despite reasonable expectations that benefits would be derived from doing so. Meta-analysis combines information from multiple studies to provide more accurate parameter estimates and to reduce the uncertainty surrounding them. Decision analysis involves selecting among alternative choices using statistical information that helps to shed light on the uncertainties involved. By linking meta-analysis to decision analysis, improved decisions can be made, with quantification of the costs and benefits of alternate decisions supported by a greater density of information. Here, we briefly review concepts of both meta-analysis and decision analysis, illustrating the natural linkage between them and the benefits from explicitly linking one to the other. We discuss some examples in which this linkage has been exploited in the medical arena and how improvements in precision and reduction of structural uncertainty inherent in a meta-analysis can provide substantive improvements to decision analysis outcomes by reducing uncertainty in expected loss and maximising information from across studies. We then argue that these significant benefits could be translated to ecology, in particular to the problem of making optimal ecological decisions in the face of uncertainty.
Hirsh, Adam T.; Hollingshead, Nicole A.; Ashburn-Nardo, Leslie; Kroenke, Kurt
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
After the advent of DSM-III, operational diagnostic criteria, along with the classification of disorders using such criteria, received considerable attention, and many studies on the reliability and validity of psychiatric diagnosis were conducted worldwide. Operational methodology was applied to diagnosis and classification, especially, in the area of research, and has contributed greatly to advances in reliable and refined clinical research. Such methodology, however, has not necessarily been accepted as a guiding principle in the area of clinical practice by all psychiatrists. Rather, some psychiatrists, especially more experienced psychiatrists, took a somewhat negative attitude toward the use of operational methodology. The author contends that one of the causes for the relatively poor acceptance of operational methodology in the area of clinical practice lies in the "classification model" view of diagnosis that forms the implicit background for the methodology. From a clinical perspective, it is not from the "classification model" basis but rather, from the "decision-making model" basis that the actual process of clinical diagnosis in psychiatry is explained properly. This is a very important point, because the latter model is potentially more useful both to psychiatric patients and to researchers in psychiatry than the former model. There have been however, few reports in psychiatry that highlight the importance of this model as the clinical framework. The author analyzes the limitations of the "classification model" view, and then, based on this analysis, lists prerequisites that a model for the framework of clinical practice should possess. The prerequisites listed are: that clinical information not sufficient to meet the disease criteria should be used as effectively as possible, that diseases low in probability but high in seriousness should be considered by clinicians in the differential diagnoses; that diagnosis should be readily changed when necessary
Maguire, Lynn A
Decisions about management of invasive species are difficult for all the reasons typically addressed by multiattribute decision analysis: uncertain outcomes, multiple and conflicting objectives, and many interested parties with differing views on both facts and values. This article illustrates how the tools of multiattribute analysis can improve management of invasive species, with an emphasis on making explicit the social values and preferences that must inform invasive species management. Risk assessment protocols developed previously for invasive species management typically suffer from two interacting flaws: (1) separating risk assessment from risk management, thus disrupting essential connections between the social values at stake in invasive species decisions and the scientific knowledge necessary to predict the likely impacts of management actions, and (2) relying on expert judgment about risk framed in qualitative and value-laden terms, inadvertently mixing the expert's judgment about what is likely to happen with personal preferences. Using the values structuring and probability-modeling elements of formal decision analysis can remedy these difficulties and make invasive species management responsive to both good science and public values. The management of feral pigs in Hawaiian ecosystems illustrates the need for such an integrated approach.
Chernovita, H. P.; Manongga, D.; Iriani, A.
One of company activities to retain their business is marketing the products which include in acquisition management to get new customers. Insurance contract analysis using ID3 to produce decision tree and rules to be decision support for the insurance company. The decision tree shows 13 rules that lead to contract termination claim. This could be a guide for the insurance company in acquisition management to prevent contract binding with these contract condition because it has a big chance for the customer to terminate their insurance contract before its expired date. As the result, there are several strong points that could be the determinant of contract termination such as: 1) customer age whether too young or too old, 2) long insurance period (above 10 years), 3) big insurance amount, 4) big amount of premium charges, and 5) payment method.
Yatsalo, Boris; Didenko, Vladimir; Gritsyuk, Sergey; ...
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.
Friesen, Lynn Roosa; Walker, Mary P; Kisling, Rebecca E; Liu, Ying; Williams, Karen B
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.
Kunisch, Joseph Martin
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.…
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Chew, Keng Sheng; Durning, Steven J; van Merriënboer, Jeroen JG
INTRODUCTION Metacognition is a cognitive debiasing strategy that clinicians can use to deliberately detach themselves from the immediate context of a clinical decision, which allows them to reflect upon the thinking process. However, cognitive debiasing strategies are often most needed when the clinician cannot afford the time to use them. A mnemonic checklist known as TWED (T = threat, W = what else, E = evidence and D = dispositional factors) was recently created to facilitate metacognition. This study explores the hypothesis that the TWED checklist improves the ability of medical students to make better clinical decisions. METHODS Two groups of final-year medical students from Universiti Sains Malaysia, Malaysia, were recruited to participate in this quasi-experimental study. The intervention group (n = 21) received educational intervention that introduced the TWED checklist, while the control group (n = 19) received a tutorial on basic electrocardiography. Post-intervention, both groups received a similar assessment on clinical decision-making based on five case scenarios. RESULTS The mean score of the intervention group was significantly higher than that of the control group (18.50 ± 4.45 marks vs. 12.50 ± 2.84 marks, p < 0.001). In three of the five case scenarios, students in the intervention group obtained higher scores than those in the control group. CONCLUSION The results of this study support the use of the TWED checklist to facilitate metacognition in clinical decision-making. PMID:26778635
Lang, Robin Lynn Neal
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…
Bell, Gillian C; Crews, Kristine R; Wilkinson, Mark R; Haidar, Cyrine E; Hicks, J Kevin; Baker, Donald K; Kornegay, Nancy M; Yang, Wenjian; Cross, Shane J; Howard, Scott C; Freimuth, Robert R; Evans, William E; Broeckel, Ulrich; Relling, Mary V; Hoffman, James M
Background Active clinical decision support (CDS) delivered through an electronic health record (EHR) facilitates gene-based drug prescribing and other applications of genomics to patient care. Objective We describe the development, implementation, and evaluation of active CDS for multiple pharmacogenetic test results reported preemptively. Materials and methods Clinical pharmacogenetic test results accompanied by clinical interpretations are placed into the patient's EHR, typically before a relevant drug is prescribed. Problem list entries created for high-risk phenotypes provide an unambiguous trigger for delivery of post-test alerts to clinicians when high-risk drugs are prescribed. In addition, pre-test alerts are issued if a very-high risk medication is prescribed (eg, a thiopurine), prior to the appropriate pharmacogenetic test result being entered into the EHR. Our CDS can be readily modified to incorporate new genes or high-risk drugs as they emerge. Results Through November 2012, 35 customized pharmacogenetic rules have been implemented, including rules for TPMT with azathioprine, thioguanine, and mercaptopurine, and for CYP2D6 with codeine, tramadol, amitriptyline, fluoxetine, and paroxetine. Between May 2011 and November 2012, the pre-test alerts were electronically issued 1106 times (76 for thiopurines and 1030 for drugs metabolized by CYP2D6), and the post-test alerts were issued 1552 times (1521 for TPMT and 31 for CYP2D6). Analysis of alert outcomes revealed that the interruptive CDS appropriately guided prescribing in 95% of patients for whom they were issued. Conclusions Our experience illustrates the feasibility of developing computational systems that provide clinicians with actionable alerts for gene-based drug prescribing at the point of care. PMID:23978487
DesAutels, Spencer J.; Fox, Zachary E.; Giuse, Dario A.; Williams, Annette M.; Kou, Qing-hua; Weitkamp, Asli; Neal R, Patel; Bettinsoli Giuse, Nunzia
Clinical decision support (CDS) knowledge, embedded over time in mature medical systems, presents an interesting and complex opportunity for information organization, maintenance, and reuse. To have a holistic view of all decision support requires an in-depth understanding of each clinical system as well as expert knowledge of the latest evidence. This approach to clinical decision support presents an opportunity to unify and externalize the knowledge within rules-based decision support. Driven by an institutional need to prioritize decision support content for migration to new clinical systems, the Center for Knowledge Management and Health Information Technology teams applied their unique expertise to extract content from individual systems, organize it through a single extensible schema, and present it for discovery and reuse through a newly created Clinical Support Knowledge Acquisition and Archival Tool (CS-KAAT). CS-KAAT can build and maintain the underlying knowledge infrastructure needed by clinical systems. PMID:28269846
DesAutels, Spencer J; Fox, Zachary E; Giuse, Dario A; Williams, Annette M; Kou, Qing-Hua; Weitkamp, Asli; Neal R, Patel; Bettinsoli Giuse, Nunzia
Clinical decision support (CDS) knowledge, embedded over time in mature medical systems, presents an interesting and complex opportunity for information organization, maintenance, and reuse. To have a holistic view of all decision support requires an in-depth understanding of each clinical system as well as expert knowledge of the latest evidence. This approach to clinical decision support presents an opportunity to unify and externalize the knowledge within rules-based decision support. Driven by an institutional need to prioritize decision support content for migration to new clinical systems, the Center for Knowledge Management and Health Information Technology teams applied their unique expertise to extract content from individual systems, organize it through a single extensible schema, and present it for discovery and reuse through a newly created Clinical Support Knowledge Acquisition and Archival Tool (CS-KAAT). CS-KAAT can build and maintain the underlying knowledge infrastructure needed by clinical systems.
Thompson, Steven; Varvel, Stephen; Sasinowski, Maciek; Burke, James P
Big data and advances in analytical processes represent an opportunity for the healthcare industry to make better evidence-based decisions on the value generated by various tests, procedures, and interventions. Value-based reimbursement is the process of identifying and compensating healthcare providers based on whether their services improve quality of care without increasing cost of care or maintain quality of care while decreasing costs. In this article, we motivate and illustrate the potential opportunities for payers and providers to collaborate and evaluate the clinical and economic efficacy of different healthcare services. We conduct a case study of a firm that offers advanced biomarker and disease state management services for cardiovascular and cardiometabolic conditions. A value-based analysis that comprised a retrospective case/control cohort design was conducted, and claims data for over 7000 subjects who received these services were compared to a matched control cohort. Study subjects were commercial and Medicare Advantage enrollees with evidence of CHD, diabetes, or a related condition. Analysis of medical claims data showed a lower proportion of patients who received biomarker testing and disease state management services experienced a MI (p < 0.01) or diabetic complications (p < 0.001). No significant increase in cost of care was found between the two cohorts. Our results illustrate the opportunity healthcare payers such as Medicare and commercial insurance companies have in terms of identifying value-creating healthcare interventions. However, payers and providers also need to pursue system integration efforts to further automate the identification and dissemination of clinically and economically efficacious treatment plans to ensure at-risk patients receive the treatments and interventions that will benefit them the most.
Aragonès, Enric; Comín, Eva; Cavero, Myriam; Pérez, Víctor; Molina, Cristina; Palao, Diego
Despite its clinical relevance and its importance as a public health problem, there are major gaps in the management of depression. Evidence-based clinical guidelines are useful to improve processes and clinical outcomes. In order to make their implementation easier these guidelines have been transformed into computerised clinical decision support systems. In this article, a description is presented on the basics and characteristics of a new computerised clinical guideline for the management of major depression, developed in the public health system in Catalonia. This tool helps the clinician to establish reliable and accurate diagnoses of depression, to choose the best treatment a priori according to the disease and the patient characteristics. It also emphasises the importance of systematic monitoring to assess the clinical course, and to adjust therapeutic interventions to the patient's needs at all times.
McGovern, Amanda R.; Alexopoulos, George S.; Yuen, Genevieve S.; Morimoto, Sarah Shizuko; Gunning, Faith M.
Objective Impairment in reward processes has been found in individuals with depression and in the aging population. The purpose of this study was twofold: 1. To use an affective neuroscience probe to identify abnormalities in reward-related decision making in late-life depression. 2. To examine the relationship of reward-related decision making abnormalities in depressed, older adults to the clinical expression of apathy in depression. We hypothesized that relative to elderly, healthy subjects, depressed, elderly patients would exhibit impaired decision making and that apathetic, depressed patients would show greater impairment in decision making than non-apathetic, depressed patients. Methods We used the Iowa Gambling Task to examine reward-related decision making in 60 non-demented, elderly patients with non-psychotic major depression and 36 elderly, psychiatrically healthy participants. Apathy was quantified using the Apathy Evaluation Scale. Of those with major depression, 18 individuals reported clinically significant apathy whereas 42 participants did not have apathy. Results Older adults with depression and healthy comparison participants did not differ in their performance on the IGT. However, apathetic, depressed older adults adopted an advantageous strategy and selected cards from the conservative decks compared to non-apathetic, depressed older adults. Non-apathetic, depressed patients showed a failure to adopt a conservative strategy and persisted in making risky decisions throughout the task. Conclusions This study indicates that apathy in older, depressed adults is associated with a conservative response style on a behavioral probe of the systems involved in reward-related decision making. This conservative response style may be the result of reduced sensitivity to rewards in apathetic individuals. PMID:25306937
Pai, Vinay M; Rodgers, Mary; Conroy, Richard; Luo, James; Zhou, Ruixia; Seto, Belinda
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.
Mattila, Jussi; Koikkalainen, Juha; Virkki, Arho; van Gils, Mark; Lötjönen, Jyrki
Medical research and clinical practice are currently being redefined by the constantly increasing amounts of multiscale patient data. New methods are needed to translate them into knowledge that is applicable in healthcare. Multiscale modeling has emerged as a way to describe systems that are the source of experimental data. Usually, a multiscale model is built by combining distinct models of several scales, integrating, e.g., genetic, molecular, structural, and neuropsychological models into a composite representation. We present a novel generic clinical decision support system, which models a patient's disease state statistically from heterogeneous multiscale data. Its goal is to aid in diagnostic work by analyzing all available patient data and highlighting the relevant information to the clinician. The system is evaluated by applying it to several medical datasets and demonstrated by implementing a novel clinical decision support tool for early prediction of Alzheimer's disease.
ZHU, C.W.; LEIBMAN, C.; TOWNSEND, R.; MCLAUGHLIN, T.; SCARMEAS, N.; ALBERT, M.; BRANDT, J.; BLACKER, D.; SANO, M.; STERN, Y.
Aim While clinical endpoints provide important information on the efficacy of treatment in controlled conditions, they often are not relevant to decision makers trying to gauge the potential economic impact or value of new treatments. Therefore, it is often necessary to translate changes in cognition, function or behavior into changes in cost or other measures, which can be problematic if not conducted in a transparent manner. The Dependence Scale (DS), which measures the level of assistance a patient requires due to AD-related deficits, may provide a useful measure of the impact of AD progression in a way that is relevant to patients, providers and payers, by linking clinical endpoints to estimates of cost effectiveness or value. The aim of this analysis was to test the association of the DS to clinical endpoints and AD-related costs. Method The relationship between DS score and other endpoints was explored using the Predictors Study, a large, multi-center cohort of patients with probable AD followed annually for four years. Enrollment required a modified Mini-Mental State Examination (mMMS) score ≥30, equivalent to a score of approximately ≥16 on the MMSE. DS summated scores (range: 0–15) were compared to measures of cognition (MMSE), function (Blessed Dementia Rating Scale, BDRS, 0–17), behavior, extrapyramidal symptoms (EPS), and psychotic symptoms (illusions, delusions or hallucinations). Also, estimates for total cost (sum of direct medical cost, direct non-medical cost, and cost of informal caregivers’ time) were compared to DS scores. Results For the 172 patients in the analysis, mean baseline scores were: DS: 5.2 (SD: 2.0), MMSE: 23.0 (SD: 3.5), BDRS: 2.9 (SD: 1.3), EPS: 10.8%, behavior: 28.9% psychotic symptoms: 21.1%. After 4 years, mean scores were: DS: 8.9 (SD: 2.9), MMSE: 17.2 (SD: 4.7), BDRS: 5.2 (SD: 1.4), EPS: 37.5%, behavior: 60.0%, psychotic symptoms: 46.7%. At baseline, DS scores were significantly correlated with MMSE (r=−0.299, p<0
Adlassnig, Klaus-Peter; Fehre, Karsten; Rappelsberger, Andrea
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.
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.
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.
Jusko, M.J.; Whitfield, R.G.
This document is intended to serve as both a programmer's and user's guide to the current version of the IDAP; and to prompt interested individuals into making suggestions for the future development of IDAP. The majority of the sections pertain to the main IDA program rather than to the IDAIN procedure. A brief discussion is presented of the theory of decision analysis. The aspects of decision analysis that are relevant to the IDAP are discussed. A complete list and description of the commands used in the IDAP program is provided and, including three complete examples. This section may be considered a user's guide to the IDAP. The programmer's guide to the IDAP discusses the various technical aspects of the programs, and may be skipped by users not involved with programming the IDAP. A list of the error messages generated by the IDAP is presented. As the program is developed, error handling and messages will improve.
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
Rivas-Ruiz, Rodolfo; Pérez-Rodríguez, Marcela; Palacios, Lino; Talavera, Juan O
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).
Transactions on Systems, Man, and Cybernetics, Vol. SMC-7, No. 5, May, 1977. . 7. Farquhar, P.H., "A Survey of Multiattribute Utility Theory and...Multi-Attribute Decision Analysis Model. The theoretical underpinnings of MADAM involve portions of multi-attribute utility theory . This interactive...Attribute Utility Theory (MAUT) model is discussed in Section 2. The actual computer program modifications developed and then implemented in code
Bloyd, Cary N.; Stork, Kevin
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.
Hierarchical Goal Analysis of dynamic decision making in microworld experiments Vlad Zotov Renee Chow Defence R& D Canada Technical Memorandum DRDC...7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Defence R& D Canada - Toronto,1133 Sheppard Avenue West,PO Box 2000,Toronto, Ontario, Canada M3M...Defence R& D Canada – Toronto Technical Memorandum DRDC Toronto TM 2008-211 March 2009 Principal Author
Tervonen, Tommi; Naci, Huseyin; van Valkenhoef, Gert; Ades, Anthony E; Angelis, Aris; Hillege, Hans L; Postmus, Douwe
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.
Fabrikant, J.I.; Hilberg, A.W.
This paper reviews certain current concepts and methods relating to benefit-risk analysis, in terms of economic costs and raidation risks to health, in relation to the benefits from diagnostic radiology in clinical medicine.
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
Sim, Livvi Li Wei; Ban, Kenneth Hon Kim; Tan, Tin Wee; Sethi, Sunil Kumar; Loh, Tze Ping
Management of complex chronic diseases such as diabetes requires the assimilation and interpretation of multiple laboratory test results. Traditional electronic health records tend to display laboratory results in a piecemeal and segregated fashion. This makes the assembly and interpretation of results related to diabetes care challenging. We developed a diabetes-specific clinical decision support system (Diabetes Dashboard) interface for displaying glycemic, lipid and renal function results, in an integrated form with decision support capabilities, based on local clinical practice guidelines. The clinical decision support system included a dashboard feature that graphically summarized all relevant laboratory results and displayed them in a color-coded system that allowed quick interpretation of the metabolic control of the patients. An alert module informs the user of tests that are due for repeat testing. An interactive graph module was also developed for better visual appreciation of the trends of the laboratory results of the patient. In a pilot study involving case scenarios administered via an electronic questionnaire, the Diabetes Dashboard, compared to the existing laboratory reporting interface, significantly improved the identification of abnormal laboratory results, of the long-term trend of the laboratory tests and of tests due for repeat testing. However, the Diabetes Dashboard did not significantly improve the identification of patients requiring treatment adjustment or the amount of time spent on each case scenario. In conclusion, we have developed and shown that the use of the Diabetes Dashboard, which incorporates several decision support features, can improve the management of diabetes. It is anticipated that this dashboard will be most helpful when deployed in an outpatient setting, where physicians can quickly make clinical decisions based on summarized information and be alerted to pertinent areas of care that require additional attention.
Sim, Livvi Li Wei; Ban, Kenneth Hon Kim; Tan, Tin Wee; Sethi, Sunil Kumar; Loh, Tze Ping
Management of complex chronic diseases such as diabetes requires the assimilation and interpretation of multiple laboratory test results. Traditional electronic health records tend to display laboratory results in a piecemeal and segregated fashion. This makes the assembly and interpretation of results related to diabetes care challenging. We developed a diabetes-specific clinical decision support system (Diabetes Dashboard) interface for displaying glycemic, lipid and renal function results, in an integrated form with decision support capabilities, based on local clinical practice guidelines. The clinical decision support system included a dashboard feature that graphically summarized all relevant laboratory results and displayed them in a color-coded system that allowed quick interpretation of the metabolic control of the patients. An alert module informs the user of tests that are due for repeat testing. An interactive graph module was also developed for better visual appreciation of the trends of the laboratory results of the patient. In a pilot study involving case scenarios administered via an electronic questionnaire, the Diabetes Dashboard, compared to the existing laboratory reporting interface, significantly improved the identification of abnormal laboratory results, of the long-term trend of the laboratory tests and of tests due for repeat testing. However, the Diabetes Dashboard did not significantly improve the identification of patients requiring treatment adjustment or the amount of time spent on each case scenario. In conclusion, we have developed and shown that the use of the Diabetes Dashboard, which incorporates several decision support features, can improve the management of diabetes. It is anticipated that this dashboard will be most helpful when deployed in an outpatient setting, where physicians can quickly make clinical decisions based on summarized information and be alerted to pertinent areas of care that require additional attention. PMID
Légaré, France; Robitaille, Hubert; Gane, Claire; Hébert, Jessica; Labrecque, Michel; Rousseau, François
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
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
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
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
Cimorelli, A.J.; Stahl, C.H.; Chow, A.H.; Fernandez, C.
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.
Peters, S A; Laham, S M; Pachter, N; Winship, I M
When clinicians facilitate and patients make decisions about predictive genetic testing, they often base their choices on the predicted emotional consequences of positive and negative test results. Research from psychology and decision making suggests that such predictions may often be biased. Work on affective forecasting-predicting one's future emotional states-shows that people tend to overestimate the impact of (especially negative) emotional events on their well-being; a phenomenon termed the impact bias. In this article, we review the causes and consequences of the impact bias in medical decision making, with a focus on applying such findings to predictive testing in clinical genetics. We also recommend strategies for reducing the impact bias and consider the ethical and practical implications of doing so.
Deshpande, Ruchi; DeMarco, John; Kessel, Kerstin; Liu, Brent J.
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.
Garcia-Jimenez, Alba; Moreno-Conde, Alberto; Martínez-García, Alicia; Marín-León, Ignacio; Medrano-Ortega, Francisco Javier; Parra-Calderón, Carlos L
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.
Nierenberg, Andrew A; Smoller, Jordan W; Eidelman, Polina; Wu, Yelena P; Tilley, Claire A
Systematic biases in decision-making have been well characterized in medical and nonmedical fields but mostly ignored in clinical psychopharmacology. The purpose of this paper is to sensitize clinicians who prescribe psychiatric drugs to the issues of the psychology of risk, especially as they pertain to the risk of side effects. Specifically, the present analysis focuses on heuristic organization and framing effects that create cognitive biases in medical practice. Our purpose is to increase the awareness of how pharmaceutical companies may influence physicians by framing the risk of medication side effects to favor their products.
Darrah, Johanna; O'Donnell, Maureen; Lam, Joyce; Story, Maureen; Wickenheiser, Diane; Xu, Kaishou; Jin, Xiaokun
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…
Naegeli, Hanspeter; Sugasawa, Kaoru
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.
Morris, A. Terry; Goode, Plesent W.
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.
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...
van Ryn, Michelle; Burgess, Diana J; Dovidio, John F; Phelan, Sean M; Saha, Somnath; Malat, Jennifer; Griffin, Joan M; Fu, Steven S; Perry, Sylvia
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.
van Ryn, Michelle; Burgess, Diana J.; Dovidio, John F.; Phelan, Sean M.; Saha, Somnath; Malat, Jennifer; Griffin, Joan M.; Fu, Steven S.; Perry, Sylvia
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
Sesen, M. Berkan; Peake, Michael D.; Banares-Alcantara, Rene; Tse, Donald; Kadir, Timor; Stanley, Roz; Gleeson, Fergus; Brady, Michael
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
Stergiou, G S; Lourida, P; Tzamouranis, D
Oscillometric devices are being widely used for ambulatory, home and office blood pressure (BP) measurement, and several of them have been validated using established protocols. This cross-sectional study assessed the impact on antihypertensive treatment decisions of replacing the mercury sphygmomanometer by a validated oscillometric device. Consecutive subjects attending a hypertension clinic had triplicate simultaneous same-arm BP measurements using a mercury sphygmomanometer and a validated professional oscillometric device. For each device, uncontrolled hypertension was defined as average BP ≥140/90 mm Hg (systolic/diastolic). A total of 5108 simultaneous BP measurements were obtained from 763 subjects in 1717 clinic visits. In 24% of all visits, the mercury and the oscillometric BP measurements led to different conclusion regarding the diagnosis of uncontrolled hypertension. In 4.9% of the visits, the diagnostic disagreement was considered as 'clinically important' (BP exceeding the diagnostic threshold by >5 mm Hg). These data suggest that the replacement of the mercury sphygmomanometer by a validated professional oscillometric device will result into different treatment decisions in about 5% of the cases. Therefore, and because of the known problems when using mercury devices and the auscultatory technique in clinical practise, the oscillometric devices are regarded as reliable alternatives to the mercury sphygmomanometer for office use.
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.
Scott, Nicole M.; Sera, Maria D.; Georgopoulos, Apostolos P.
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
Scott, Nicole M; Sera, Maria D; Georgopoulos, Apostolos P
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.
Adibi, Shawn; Abidi, Shawn; Bebermeyer, Richard D
Lack of transparency in funded research can compromise clinical decision-making in an evidence-based practice. Transparency can be defined as full disclosure of all financial assistance and support to authors and investigators. There is a perception that ethical principles are eroding and that research data can be biased due to conflicts of interest. These research outcomes biased or not, are used for clinical decision-making in the evidence-based practice. One suggested solution to this common ethical dilemma is to continue the dialogue on transparency in research and to create oversight bodies which include representatives from business and industry, private practice, academia, and research. There is increasing evidence of the need for more ethics education at all levels.
Taylor, Helen J
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'.
Abid, Sidra; Keshavjee, Karim; Karim, Arsalan; Guergachi, Aziz
Health care continue to lag behind other industries, such as retail and financial services, in the use of decision-support-like tools. Amazon is particularly prolific in the use of advanced predictive and prescriptive analytics to assist its customers to purchase more, while increasing satisfaction, retention, repeat-purchases and loyalty. How can we do the same in health care? In this paper, we explore various elements of the Amazon website and Amazon's data science and big data practices to gather inspiration for re-designing clinical decision support in the health care sector. For each Amazon element we identified, we present one or more clinical applications to help us better understand where Amazon's.
Van Baalen, Mary; Tafreshi, Ali; Patel, Nimesh; Young, Millennia; Mason, Sara; Otto, Christian; Samuels, Brian; Koslovsky, Matthew; Schaefer, Caroline; Taiym, Wafa; Wear, Mary; Gibson, Charles; Tarver, William
Vision changes identified in long duration space fliers has led to a more comprehensive clinical monitoring protocol. Optical Coherence Tomography (OCT) was recently implemented on board the International Space Station in 2013. NASA is collaborating with Heidelberg Engineering to expand our current OCT data analysis capability by implementing a volumetric approach. Volumetric maps will be created by combining the circle scan, the disc block scan, and the radial scan. This assessment may provide additional information about the optic nerve and further characterize changes related microgravity exposure. We will discuss challenges with collection and analysis of OCT data, present the results of this reanalysis and outline the potential benefits and limitations of the additional data.
Keller, Jonathan W.; Yang, Yi Edward
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…
Fager, Susan; Bardach, Lisa; Russell, Susanne; Higginbotham, Jeff
Children with severe physical impairments require a variety of access options to augmentative and alternative communication (AAC) and computer technology. Access technologies have continued to develop, allowing children with severe motor control impairments greater independence and access to communication. This article will highlight new advances in access technology, including eye and head tracking, scanning, and access to mainstream technology, as well as discuss future advances. Considerations for clinical decision-making and implementation of these technologies will be presented along with case illustrations.
Johnsen, Hege Mari; Fossum, Mariann; Vivekananda-Schmidt, Pirashanthie; Fruhling, Ann; Slettebø, Åshild
The aim of this study was to design and pilot-test a serious game for teaching nursing students clinical reasoning and decision-making skills in caring for patients with chronic obstructive pulmonary disease. A video-based serious game prototype was developed. A purposeful sample of six participants tested and evaluated the prototype. Usability issues were identified regarding functionality and user-computer interface. However, overall the serious game was perceived to be useful, usable and likable to use.
Formea, CM; Hoffman, JM; Matey, E; Peterson, JF; Boyce, RD
The explosive growth of patient‐specific genomic information relevant to drug therapy will continue to be a defining characteristic of biomedical research. To implement drug‐based personalized medicine (PM) for patients, clinicians need actionable information incorporated into electronic health records (EHRs). New clinical decision support (CDS) methods and informatics infrastructure are required in order to comprehensively integrate, interpret, deliver, and apply the full range of genomic data for each patient.1 PMID:28109071
Nair, Bala G; Gabel, Eilon; Hofer, Ira; Schwid, Howard A; Cannesson, Maxime
With increasing adoption of anesthesia information management systems (AIMS), there is growing interest in utilizing AIMS data for intraoperative clinical decision support (CDS). CDS for anesthesia has the potential for improving quality of care, patient safety, billing, and compliance. Intraoperative CDS can range from passive and post hoc systems to active real-time systems that can detect ongoing clinical issues and deviations from best practice care. Real-time CDS holds the most promise because real-time alerts and guidance can drive provider behavior toward evidence-based standardized care during the ongoing case. In this review, we describe the different types of intraoperative CDS systems with specific emphasis on real-time systems. The technical considerations in developing and implementing real-time CDS are systematically covered. This includes the functional modules of a CDS system, development and execution of decision rules, and modalities to alert anesthesia providers concerning clinical issues. We also describe the regulatory aspects that affect development, implementation, and use of intraoperative CDS. Methods and measures to assess the effectiveness of intraoperative CDS are discussed. Last, we outline areas of future development of intraoperative CDS, particularly the possibility of providing predictive and prescriptive decision support.
Scott, P J; Altenburger, P A; Kean, J
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.
Bérubé, J; Papillon, M J; Lavoie, G; Durant, P; Fortin, J P
In the health field, clinical information is the raw material for the clinician delivering health services. Therefore, the clinical information available to the physician is often incomplete or even non¿existent upon consultation. Furthermore, the reconstruction of the medical history, which is the most important source of data for the clinician to establish a diagnosis and initiate a treatment, suffers from many constraints. The smart card, like the one used in Quebec's project, could ease the physician's decision-making by allowing fast access to accurate and pertinent data. The smart card is a major asset in the present health system.
Heusinkveld, J; Geissbuhler, A; Sheshelidze, D; Miller, R
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.
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
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
Koller, Walter; de Bruin, Jeroen S; Rappelsberger, Andrea; Adlassnig, Klaus-Peter
By the use of extended intelligent information technology tools for fully automated healthcare-associated infection (HAI) surveillance, clinicians can be informed and alerted about the emergence of infection-related conditions in their patients. Moni--a system for monitoring nosocomial infections in intensive care units for adult and neonatal patients--employs knowledge bases that were written with extensive use of fuzzy sets and fuzzy logic, allowing the inherent un-sharpness of clinical terms and the inherent uncertainty of clinical conclusions to be a part of Moni's output. Thus, linguistic as well as propositional uncertainty became a part of Moni, which can now report retrospectively on HAIs according to traditional crisp HAI surveillance definitions, as well as support clinical bedside work by more complex crisp and fuzzy alerts and reminders. This improved approach can bridge the gap between classical retrospective surveillance of HAIs and ongoing prospective clinical-decision-oriented HAI support.
Ma, Sisi; Galatzer-Levy, Isaac R; Wang, Xuya; Fenyö, David; Shalev, Arieh Y
PTSD is distressful and debilitating, following a non-remitting course in about 10% to 20% of trauma survivors. Numerous risk indicators of PTSD have been identified, but individual level prediction remains elusive. As an effort to bridge the gap between scientific discovery and practical application, we designed and implemented a clinical decision support pipeline to provide clinically relevant recommendation for trauma survivors. To meet the specific challenge of early prediction, this work uses data obtained within ten days of a traumatic event. The pipeline creates personalized predictive model for each individual, and computes quality metrics for each predictive model. Clinical recommendations are made based on both the prediction of the model and its quality, thus avoiding making potentially detrimental recommendations based on insufficient information or suboptimal model. The current pipeline outperforms the acute stress disorder, a commonly used clinical risk factor for PTSD development, both in terms of sensitivity and specificity. PMID:28269880
Cooper, J. Arlin
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.
Irwin, Elise R.; Kathryn, D.; Kennedy, Mickett
Adaptive management is different from other types of management in that it includes all stakeholders (versus only policy makers) in the process, uses resource optimization techniques to evaluate competing objectives, and recognizes and attempts to reduce uncertainty inherent in natural resource systems. Management actions are negotiated by stakeholders, monitored results are compared to predictions of how the system should respond, and management strategies are adjusted in a “monitor-compare-adjust” iterative routine. Many adaptive management projects fail because of the lack of stakeholder identification, engagement, and continued involvement. Primary reasons for this vary but are usually related to either stakeholders not having ownership (or representation) in decision processes or disenfranchisement of stakeholders after adaptive management begins. We present an example in which stakeholders participated fully in adaptive management of a southeastern regulated river. Structured decision analysis was used to define management objectives and stakeholder values and to determine initial flow prescriptions. The process was transparent, and the visual nature of the modeling software allowed stakeholders to see how their interests and values were represented in the decision process. The development of a stakeholder governance structure and communication mechanism has been critical to the success of the project.
Bau, Cho-Tsan; Huang, Chung-Yi
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
Catalani, Caricia; Green, Eric; Owiti, Philip; Keny, Aggrey; Diero, Lameck; Yeung, Ada; Israelski, Dennis; Biondich, Paul
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.
Catalani, Caricia; Green, Eric; Owiti, Philip; Keny, Aggrey; Diero, Lameck; Yeung, Ada; Israelski, Dennis; Biondich, Paul
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
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
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.
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
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
Sheehan, Barbara; Kaufman, David; Stetson, Peter; Currie, Leanne M
Computerized decision support systems have been used to help ensure safe medication prescribing. However, the acceptance of these types of decision support has been reported to be low. It has been suggested that decreased acceptance may be due to lack of clinical relevance. Additionally, cognitive fit between the user interface and clinical task may impact the response of clinicians as they interact with the system. In order to better understand clinician responses to such decision support, we used cognitive task analysis methods to evaluate clinical alerts for antibiotic prescribing in a neonatal intensive care unit. Two methods were used: 1) a cognitive walkthrough; and 2) usability testing with a 'think-aloud' protocol. Data were analyzed for impact on cognitive effort according to categories of cognitive distance. We found that responses to alerts may be context specific and that lack of screen cues often increases cognitive effort required to use a system.
Sheehan, Barbara; Kaufman, David; Stetson, Peter; Currie, Leanne M.
Computerized decision support systems have been used to help ensure safe medication prescribing. However, the acceptance of these types of decision support has been reported to be low. It has been suggested that decreased acceptance may be due to lack of clinical relevance. Additionally, cognitive fit between the user interface and clinical task may impact the response of clinicians as they interact with the system. In order to better understand clinician responses to such decision support, we used cognitive task analysis methods to evaluate clinical alerts for antibiotic prescribing in a neonatal intensive care unit. Two methods were used: 1) a cognitive walkthrough; and 2) usability testing with a ‘think-aloud’ protocol. Data were analyzed for impact on cognitive effort according to categories of cognitive distance. We found that responses to alerts may be context specific and that lack of screen cues often increases cognitive effort required to use a system. PMID:20351922
Tanderup, Malene; Reddy, Sunita; Patel, Tulsi; Nielsen, Birgitte Bruun
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.
Ota, Toshio; Yoshida, Sumiko; Tsunashima, Sousuke; Totsuka, Takao; Watanabe, Takafumi; Toyoshima, Ryoichi
Psychiatrists often have to treat patients even when the clinical information is insufficient to make a definite diagnosis. This is the case especially when we are treating first-visit outpatients or inpatients who have just been admitted. One of the causes of information insufficiency is a delay in obtaining clinical information on the patient, and another is a lack of characteristic manifestations of the disease because of an immature developmental stage. Even in such situations, however, clinicians have to make reasonable judgements using the information that is available at that time. The framework for making judgements on such occasions, or "the framework of decision-making under imperfect-information conditions", is becoming more and more important in psychiatric clinical practice in Japan for the following reasons. First, team members in charge of a patient became very heterogeneous in terms of their career and motivation after the start of the new post-graduate clinical training system in Japan several years ago, resulting in a higher risk of miscommunication. Secondly, the need for precise explanation to patients and their families has become crucial in recent years as the result of various social changes. Ota T, one of the authors, once put forward the framework of decision-making under imperfect-information conditions on the basis of Bayesian statistics. In the present paper, in consideration of the above background, we devised a sheet for visualizing the above framework so that relevant staff could share the clinical decision-making process. Specifically, we visually arranged on a sheet of paper the components and variables of the framework, so that the staff could communicate with each other explicitly and precisely about the estimated probability of each possible disease, merits and demerits of each treatment option, etc. We employed the sheet on treating patients in our acute psychiatric ward, 2 of whom are presented in the paper. Discussions were
Lobach, David; Sanders, Gillian D; Bright, Tiffani J; Wong, Anthony; Dhurjati, Ravi; Bristow, Erin; Bastian, Lori; Coeytaux, Remy; Samsa, Gregory; Hasselblad, Vic; Williams, John W; Wing, Liz; Musty, Michael; Kendrick, Amy S
OBJECTIVES To catalogue study designs used to assess the clinical effectiveness of CDSSs and KMSs, to identify features that impact the success of CDSSs/KMSs, to document the impact of CDSSs/KMSs on outcomes, and to identify knowledge types that can be integrated into CDSSs/KMSs. DATA SOURCES MEDLINE(®), CINAHL(®), PsycINFO(®), and Web of Science(®). REVIEW METHODS We included studies published in English from January 1976 through December 2010. After screening titles and abstracts, full-text versions of articles were reviewed by two independent reviewers. Included articles were abstracted to evidence tables by two reviewers. Meta-analyses were performed for seven domains in which sufficient studies with common outcomes were included. RESULTS We identified 15,176 articles, from which 323 articles describing 311 unique studies including 160 reports on 148 randomized control trials (RCTs) were selected for inclusion. RCTs comprised 47.5 percent of the comparative studies on CDSSs/KMSs. Both commercially and locally developed CDSSs effectively improved health care process measures related to performing preventive services (n = 25; OR 1.42, 95% confidence interval [CI] 1.27 to 1.58), ordering clinical studies (n = 20; OR 1.72, 95% CI 1.47 to 2.00), and prescribing therapies (n = 46; OR 1.57, 95% CI 1.35 to 1.82). Fourteen CDSS/KMS features were assessed for correlation with success of CDSSs/KMSs across all endpoints. Meta-analyses identified six new success features: Integration with charting or order entry system. Promotion of action rather than inaction. No need for additional clinician data entry. Justification of decision support via research evidence. Local user involvement. Provision of decision support results to patients as well as providers. Three previously identified success features were confirmed: Automatic provision of decision support as part of clinician workflow. Provision of decision support at time and location of decisionmaking. Provision of a
1 Award Number: W81-XWH-09-2-0175 TITLE: Development of EBM-CDSS (Evidence-Based Clinical Decision Support System) to AIG Prognostication in...From - To) 25Sep2009 - 31Dec2015 4. TITLE AND SUBTITLE Development of EBM-CDSS (Evidence-Based Clinical Decision Support System) to AIG Prognostication...health.usf.edu 4 14. ABSTRACT Goal of the project is to develop an Evidence-based Clinical Decision Support (CDSS-EBM) system and make it available at the point
Coiera, Enrico; Westbrook, Johanna I.; Rogers, Kris
Objective To test whether the use of an evidence retrieval system that uses clinically targeted meta-search filters can enhance the rate at which clinicians make correct decisions, reduce the effort involved in locating evidence, and provide an intuitive match between clinical tasks and search filters. Design A laboratory experiment under controlled conditions asked 75 clinicians to answer eight randomly sequenced clinical questions, using one of two randomly assigned search engines. The first search engine Quick Clinical (QC) was equipped with meta-search filters (the combined use of meta-search and search filters) designed to answer typical clinical questions e.g., treatment, diagnosis, and the second ‘library model’ system (LM) offered free access to an identical evidence set with no filter support. Measurements Changes in clinical decision making were measured by the proportion of correct post-search answers provided to questions, the time taken to answer questions, and the number of searches and links to documents followed in a search session. The intuitive match between meta-search filters and clinical tasks was measured by the proportion and distribution of filters selected for individual clinical questions. Results Clinicians in the two groups performed equally well pre-search. Post search answers improved overall by 21%, with 52.2% of answers correct with QC and 54.7% with LM (χ2 = 0.33, df = 1, p > 0.05). Users of QC obtained a significantly greater percentage of their correct answers within the first two minutes of searching compared to LM users (QC 58.2%; LM 32.9%; χ2 = 19.203, df = 1, p < 0.001). There was a statistical difference for QC and LM survival curves, which plotted overall time to answer questions, irrespective of answer (Wilcoxon, p = 0.019) and for the average time to provide a correct answer (Wilcoxon, p = 0.006). The QC system users conducted significantly fewer searches per scenario (m = 3.0 SD = 1.15 versus m = 5.5 SD1.97, t = 6
Marcos, Mar; Maldonado, Jose A; Martínez-Salvador, Begoña; Boscá, Diego; Robles, Montserrat
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
Dane, Dawn E.; Dane, Andrew B.; Crowther, Edward R.
Objective: This study explored how chiropractic interns applied evidenced-based concepts, the sources of evidence they used, and how useful they perceived these sources to be in clinical decision making. Methods: A questionnaire containing 13 items in a Likert 5-point scale was administered to 28 chiropractic interns to gather information on the evidence types they commonly accessed and their perceived usefulness of these sources in clinical decision making. The interns were in the 8th semester of the training program. Results: There was a 93% (n = 26) response rate. Clinical guidelines were rated as the most helpful resource in clinical decision making (81%), followed by lecture materials (77%), journals (54%), databases (50%), and textbooks (35%). Students recognized scientific evidence as the most important aspect in clinical decision making. They found their personal experience and the views of their clinician to be equally important and patient preference the least. Conclusion: Interns routinely employed high-quality levels of evidence in clinical decision making. They also considered their early, limited clinical experience as important as that of their clinical supervisor in decision making. This finding should be investigated further. PMID:27389528
Evaluation of Diagnostic Tests and Decision Analysis. Applications of Probability and Statistics to Medicine. Modules and Monographs in Undergraduate Mathematics and Its Applications. UMAP Module 377.
The material looks at: 1) Choosing a Clinical Test; 2) Evaluation of Diagnostic Tests; 3) Multi-Disease and Multi-Test Analysis; and 4) Medical Decision Analysis. It is felt users will be able to: 1) calculate the predictive value of a positive or negative test result in model clinical situations; 2) estimate the sensitivity and specificity…
Goodnough, Lawrence Tim; Shah, Neil
Blood transfusion has been identified as one of the most frequently performed therapeutic procedures, with a significant percentage of transfusions identified to be inappropriate. Recent key clinical trials in adults have provided Level 1 evidence to support restrictive red blood cell (RBC) transfusion practices. However, some advocates have attempted to identify a "correct" Hb threshold for RBC transfusion; whereas others assert that management of anemia, including transfusion decisions, must take into account clinical patient variables, rather than simply one diagnostic laboratory test. The heterogeneity of guidelines for blood transfusion by a number of medical societies reflects this controversy. Clinical decision support (CDS) uses a Hb threshold number in a smart Best Practices Alert (BPA) upon physician order, to trigger a concurrent utilization self-review for whether blood transfusion therapy is appropriate. This review summarizes Level 1 evidence in seven key clinical trials in adults that support restrictive transfusion practices, along strategies made possible by CDS that have demonstrated value in improving blood utilization by promoting restrictive transfusion practices.
Clinical decision-making (CDM) is key in learning to be a doctor as the defining activity in their clinical work. CDM is often portrayed in the literature as similar to 'trail blazing'; the doctor as the core agent, clearing away obstacles on the path towards diagnosis and treatment. However, in a fieldwork of young doctors in Denmark, it was difficult connect their practice to this image. This paper presents the exploration of this discrepancy in the heart of medical practice and how an alternative image emerged; that of a 'jam session'. The exploration is represented as a case-based hypothesis-testing: first, a theoretically and empirically informed hypothesis (H0) of how doctors perform CDM is developed. In H0, CDM is a stepwise process of reasoning about clinical data, often influenced by outside contextual factors. Then, H0 is tested against a case from ethnographic fieldwork with doctors going through internship. Although the case is chosen for characteristics that make it 'most likely' to verify the hypothesis, verification proves difficult. The case challenges preconceptions in CDM literature about chronology, context, objectivity, cognition, agency, and practice. The young doctor is found not to make decisions, but rather to participate in CDM; an activity akin to the dynamics found in a jam session. Their participation circles in and through four concurrent interrelated constructions that suggest a new conceptualization of CDM; a starting point for a deeper understanding of actual practice in a changing clinical environment.
Nicholson, W Reg
Objective: To demonstrate how the findings of surface electromyography (S.E.M.G.) were integrated into the clinical decision-making process. Clinical Features: This is a retrospective review of the file of a 27-year-old male suffering from mechanical low back pain. He was evaluated on 3 separate occasions over a 3 year period. History, radiography, functional outcome studies, visual-numerical pain score, pain drawing, physical examination and surface electromyography were utilized in evaluating this patient. Intervention and Outcome: The two clinical interventions of spinal manipulative therapy (S.M.T.) had positive results in that the patient achieved an asymptomatic state and returned to his position of employment. The S.E.M.G. data collected during the industrial assessment, did not provide the outcome that the patient had anticipated. Conclusion: Surface electromyography is a useful clinical tool in the author’s decision-making process for the treatment of mechanical lower back pain. Therapeutic intervention by S.M.T., therapeutic exercises and rating risk factors were influenced by the S.E.M.G. findings.
Edelen, Bonnie Gilbert; Bell, Alexandra Alice
The purpose of this study was to address the need for effective educational interventions to promote students' clinical decision making (CDM) within clinical practice environments. Researchers used a quasi-experimental, non-equivalent groups, posttest-only design to assess differences in CDM ability between intervention group students who participated in analogy-guided learning activities and control group students who participated in traditional activities. For the intervention, analogy-guided learning activities were incorporated into weekly group discussions, reflective journal writing, and questioning with clinical faculty. The researcher-designed Assessment of Clinical Decision Making Rubric was used to assess indicators of CDM ability in all students' reflective journal entries. Results indicated that the intervention group demonstrated significantly higher levels of CDM ability in their journals compared with the control group (ES(sm) = 0.52). Recommendations provide nurse educators with strategies to maximize students' development of CDM ability, better preparing students for the demands they face when they enter the profession.
Considine, Julie; Botti, Mari; Thomas, Shane
The use of supplemental oxygen by emergency nurses has important implications for patient outcomes, yet there is significant variability in oxygen administration practises. Specific education related to oxygen administration increases factual knowledge in this domain; however, the impact of knowledge acquisition on nurses' clinical decisions is poorly understood. This study aimed to examine the effect of educational preparation on 20 emergency nurses' decisions regarding the assessment of oxygenation and the use of supplemental oxygen. A pre-test/post-test, quasi-experimental design was used. The intervention was a written, self-directed learning package. The major effects of the completion of the learning package included no change in the number or types of parameters used by nurses to assess oxygenation, a significant decrease in the selection of simple masks, a significant increase in the selection of air entrainment masks, fewer hypothetical outcomes of unresolved respiratory distress and more hypothetical outcomes of decreased respiratory distress. As many nursing education programs are aimed at increasing factual knowledge, while experience remains relatively constant, a greater understanding of the relationship between factual knowledge and clinical decisions is needed if educational interventions are to improve patient outcomes.
Tarnow, Dennis P; Chu, Stephen J; Fletcher, Paul D
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.
Borbolla, Damian; Otero, Carlos; Lobach, David F; Kawamoto, Kensaku; Gomez Saldaño, Ana M; Staccia, Gustavo; Lopez, Gastón; Figar, Silvana; Luna, Daniel; Bernaldo de Quiros, Fernan Gonzalez
Numerous studies have shown that the quality of health care is inadequate, and healthcare organizations are increasingly turning to clinical decision support systems (CDSS) to address this problem. In implementing CDSS, a highly promising architectural approach is the use of decision support services. However, there are few reported examples of successful implementations of operational CDSS using this approach. Here, we describe how Hospital Italiano de Buenos Aires evaluated the feasibility of using the SEBASTIAN clinical decision support Web service to implement a CDSS integrated with its electronic medical record system. The feasibility study consisted of three stages: first, end-user acceptability testing of the proposed CDSS through focus groups; second, the design and implementation of the system through integration of SEBASTIAN and the authoring of new rules; and finally, validation of system performance and accuracy. Through this study, we found that it is feasible to implement CDSS using a service-based approach. The CDSS is now under evaluation in a randomized controlled trial. The processes and lessons learned from this initiative are discussed.
Cunningham, Pádraig; Merchant, Sabrina; Walker, Nicholas; Heffner, Jacquelyn; Shanholtzer, Lucas; Rothenberg, Stephen J.
BACKGROUND AND OBJECTIVES: Central apnea complicates, and may be the presenting complaint in, bronchiolitis. Our objective was to prospectively derive candidate clinical decision rules (CDRs) to identify infants in the emergency department (ED) who are at risk for central apnea. METHODS: We conducted a prospective observational study over 8 years. The primary outcome was central apnea subsequent to the initial ED visit. Infants were enrolled if they presented with central apnea or bronchiolitis. We excluded infants with obstructive apnea, neonatal jaundice, trauma, or suspected sepsis. We developed 3 candidate CDRs by using 3 techniques: (1) Poisson regression clustered on the individual, (2) classification and regression tree analysis (CART), and (3) a random forest (RF). RESULTS: We analyzed 990 ED visits for 892 infants. Central apnea subsequently occurred in the hospital in 41 (5%) patients. Parental report of apnea, previous history of apnea, congenital heart disease, birth weight ≤2.5 kg, lower weight, and age ≤6 weeks all identified a group at high risk for subsequent central apnea. All CDRs and RFs were 100% sensitive (95% confidence interval [CI] 91%–100%) and had a negative predictive value of 100% (95% CI 99%–100%) for the subsequent apnea. Specificity ranged from 61% to 65% (95% CI 58%–68%) for CDRs based on Poisson models; 65% to 77% (95% CI 62%–90%) for CART; and 81% to 91% (95% CI 78%–92%) for RF models. CONCLUSIONS: All candidate CDRs had a negative predictive value of 100% for subsequent central apnea. PMID:26482666
Background A real-time clinical decision support system (RTCDSS) with interactive diagrams enables clinicians to instantly and efficiently track patients' clinical records (PCRs) and improve their quality of clinical care. We propose a RTCDSS to process online clinical informatics from multiple databases for clinical decision making in the treatment of prostate cancer based on Web Model-View-Controller (MVC) architecture, by which the system can easily be adapted to different diseases and applications. Methods We designed a framework upon the Web MVC-based architecture in which the reusable and extractable models can be conveniently adapted to other hospital information systems and which allows for efficient database integration. Then, we determined the clinical variables of the prostate cancer treatment based on participating clinicians' opinions and developed a computational model to determine the pretreatment parameters. Furthermore, the components of the RTCDSS integrated PCRs and decision factors for real-time analysis to provide evidence-based diagrams upon the clinician-oriented interface for visualization of treatment guidance and health risk assessment. Results The resulting system can improve quality of clinical treatment by allowing clinicians to concurrently analyze and evaluate the clinical markers of prostate cancer patients with instantaneous clinical data and evidence-based diagrams which can automatically identify pretreatment parameters. Moreover, the proposed RTCDSS can aid interactions between patients and clinicians. Conclusions Our proposed framework supports online clinical informatics, evaluates treatment risks, offers interactive guidance, and provides real-time reference for decision making in the treatment of prostate cancer. The developed clinician-oriented interface can assist clinicians in conveniently presenting evidence-based information to patients and can be readily adapted to an existing hospital information system and be easily
Faught, I. Charie
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…
Evans, Gerald W.
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).
Robertson, Maggie; Moir, Jim; Skelton, John; Dowell, Jon; Cowan, Sue
Although shared decision making (SDM) in general practice continues to be promoted as a highly desirable means of conducting consultations it is rarely observed in practice. The aim of this study is to identify the discursive features and conversational strategies particular to the negotiation and sharing of treatment decisions in order to understand why SDM is not yet embedded into routine practice. Consultations from Scottish general practices were examined using discourse analysis. Two themes were identified as key components for when the doctor and the patient were intent on sharing decisions: the generation of patient involvement using first-person pronouns, and successful and unsuccessful patient requesting practices. This article identifies a number of conversational activities found to be successful in supporting doctors' agendas and reducing their responsibility for decisions made. Doctor's use of 'partnership talk' was found to minimize resistance and worked to invite consensus rather than involvement. The information from this study provides new insight into the consultation process by identifying how treatment decisions are arrived at through highlighting the complexities involved. Notably, shared decision making does not happen with the ease implied by current models and appears to work to maintain a biomedical 'GP as expert' approach rather than one in which the patient is truly involved in partnership. We suggest that further research on the impact of conversational activities is likely to benefit our understanding of shared decision making and hence training in and the practice of SDM.
Holzer, S.; Fremgen, A. M.; Hundahl, S. A.; Dudeck, J.
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
van Zon, Kees; Lord, William P; Lagor, Charles; Theiss, Stephan; Brosig, Torge; Siebler, Mario
The Stroke Navigator is a clinical decision support system aimed at improving the diagnosis and treatment of acute stroke. It combines an audit trail, a differential diagnosis window, an interactive stroke protocol map, and a list of recommendations for hospital staff. It provides a patient-specific overview of the workflow status and of the available clinical findings, with the goal of improving the continuity of care. For this purpose, it uses a workflow engine that was specifically designed to meet the demands of clinical practice. The Stroke Navigator furthermore calculates and displays the probabilities of various stroke differential diagnoses. The demonstration will introduce these and other features by means of a hypothetical patient case. It will also summarize the status of alpha-testing the first prototype.
Elwyn, Glyn; Dannenberg, Michelle; Blaine, Arianna; Poddar, Urbashi; Durand, Marie-Anne
Objective Our aim in this study was to examine the competing interest policies and procedures of organisations who develop and maintain patient decision aids. Design Descriptive and thematic analysis of data collected from a cross-sectional survey of patient decision aid developer's competing interest policies and disclosure forms. Results We contacted 25 organisations likely to meet the inclusion criteria. 12 eligible organisations provided data. 11 organisations did not reply and 2 declined to participate. Most patient decision aid developers recognise the need to consider the issue of competing interests. Assessment processes vary widely and, for the most part, are insufficiently robust to minimise the risk of competing interests. Only half of the 12 organisations had competing interest policies. Some considered disclosure to be sufficient, while others imposed differing levels of exclusion. Conclusions Patient decision aid developers do not have a consistent approach to managing competing interests. Some have developed policies and procedures, while others pay no attention to the issue. As is the case for clinical practice guidelines, increasing attention will need to be given to how the competing interests of contributors of evidence-based publications may influence materials, especially if they are designed for patient use. PMID:27612542
Lewis, Krystina B; Stacey, Dawn; Squires, Janet E; Carroll, Sandra
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.
van Rooij, Tibor; Rix, Serena; Moore, James B; Marsh, Sharon
Background: Mobile applications (apps) providing clinical decision support (CDS) may show the greatest promise when created by and for frontline clinicians. Our aim was to create a generic model enabling healthcare providers to direct the development of CDS apps. Methods: We combined Change Management with a three-tier information technology architecture to stimulate CDS app development. Results: A Bridging Opportunities Work-frame model was developed. A test case was used to successfully develop an app. Conclusion: Healthcare providers can re-use this globally applicable model to actively create and manage regional decision support applications to translate evidence-based medicine in the use of emerging medication or novel treatment regimens. PMID:28031883
Chatterjee, Krishnendu; Doyen, Laurent; Henzinger, Thomas A.
We study observation-based strategies for partially-observable Markov decision processes (POMDPs) with parity objectives. An observation-based strategy relies on partial information about the history of a play, namely, on the past sequence of observations. We consider qualitative analysis problems: given a POMDP with a parity objective, decide whether there exists an observation-based strategy to achieve the objective with probability 1 (almost-sure winning), or with positive probability (positive winning). Our main results are twofold. First, we present a complete picture of the computational complexity of the qualitative analysis problem for POMDPs with parity objectives and its subclasses: safety, reachability, Büchi, and coBüchi objectives. We establish several upper and lower bounds that were not known in the literature. Second, we give optimal bounds (matching upper and lower bounds) for the memory required by pure and randomized observation-based strategies for each class of objectives.
Smith, J. H.; Feinberg, A.; Miles, R. F., Jr.
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.
Hilbig, Benjamin E.; Pohl, Rudiger F.
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…
Klecker, Beverly M.; Austin, Jerry L.; Burns, Leonard T.
This report describes the implementation of School-Based Decision-Making (SBDM) Councils. The research drew on a stratified random sample of high schools, middle and junior high schools, and elementary schools geographically distributed throughout the eight service regions of Kentucky. The paper also details the types of decisions being made by…
Kim, Hyungyung; Kim, Insook; Chae, Yougmoon
This study a methodological study; to acquire knowledge on the nursing process by steps of knowledge definition, collection, and representation; then, to design a data warehouse and nursing process clinical decision support system.
Background Osteoporosis affects over 200 million people worldwide at a high cost to healthcare systems. Although guidelines are available, patients are not receiving appropriate diagnostic testing or treatment. Findings from a systematic review of osteoporosis interventions and a series of focus groups were used to develop a functional multifaceted tool that can support clinical decision-making in osteoporosis disease management at the point of care. The objective of our study was to assess how well the prototype met functional goals and usability needs. Methods We conducted a usability study for each component of the tool--the Best Practice Recommendation Prompt (BestPROMPT), the Risk Assessment Questionnaire (RAQ), and the Customised Osteoporosis Education (COPE) sheet--using the framework described by Kushniruk and Patel. All studies consisted of one-on-one sessions with a moderator using a standardised worksheet. Sessions were audio- and video-taped and transcribed verbatim. Data analysis consisted of a combination of qualitative and quantitative analyses. Results In study 1, physicians liked that the BestPROMPT can provide customised recommendations based on risk factors identified from the RAQ. Barriers included lack of time to use the tool, the need to alter clinic workflow to enable point-of-care use, and that the tool may disrupt the real reason for the visit. In study 2, patients completed the RAQ in a mean of 6 minutes, 35 seconds. Of the 42 critical incidents, 60% were navigational and most occurred when the first nine participants were using the stylus pen; no critical incidents were observed with the last six participants that used the touch screen. Patients thought that the RAQ questions were easy to read and understand, but they found it difficult to initiate the questionnaire. Suggestions for improvement included improving aspects of the interface and navigation. The results of study 3 showed that most patients were able to understand and describe
Welch, Brandon M; Kawamoto, Kensaku
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.
Convertino, Matteo; Valverde, L James
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
Convertino, Matteo; Valverde, L. James
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
Triñanes, Yolanda; Atienza, Gerardo; Louro-González, Arturo; de-las-Heras-Liñero, Elena; Alvarez-Ariza, María; Palao, Diego J
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.
Chessare, J B
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.
White, Krista A
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.
Drew, David A; Lok, Charmaine E; Cohen, Joshua T; Wagner, Martin; Tangri, Navdeep; Weiner, Daniel E
Hemodialysis vascular access recommendations promote arteriovenous (AV) fistulas first; however, it may not be the best approach for all hemodialysis patients, because likelihood of successful fistula placement, procedure-related and subsequent costs, and patient survival modify the optimal access choice. We performed a decision analysis evaluating AV fistula, AV graft, and central venous catheter (CVC) strategies for patients initiating hemodialysis with a CVC, a scenario occurring in over 70% of United States dialysis patients. A decision tree model was constructed to reflect progression from hemodialysis initiation. Patients were classified into one of three vascular access choices: maintain CVC, attempt fistula, or attempt graft. We explicitly modeled probabilities of primary and secondary patency for each access type, with success modified by age, sex, and diabetes. Access-specific mortality was incorporated using preexisting cohort data, including terms for age, sex, and diabetes. Costs were ascertained from the 2010 USRDS report and Medicare for procedure costs. An AV fistula attempt strategy was found to be superior to AV grafts and CVCs in regard to mortality and cost for the majority of patient characteristic combinations, especially younger men without diabetes. Women with diabetes and elderly men with diabetes had similar outcomes, regardless of access type. Overall, the advantages of an AV fistula attempt strategy lessened considerably among older patients, particularly women with diabetes, reflecting the effect of lower AV fistula success rates and lower life expectancy. These results suggest that vascular access-related outcomes may be optimized by considering individual patient characteristics.
Drew, David A.; Lok, Charmaine E.; Cohen, Joshua T.; Wagner, Martin; Tangri, Navdeep
Hemodialysis vascular access recommendations promote arteriovenous (AV) fistulas first; however, it may not be the best approach for all hemodialysis patients, because likelihood of successful fistula placement, procedure-related and subsequent costs, and patient survival modify the optimal access choice. We performed a decision analysis evaluating AV fistula, AV graft, and central venous catheter (CVC) strategies for patients initiating hemodialysis with a CVC, a scenario occurring in over 70% of United States dialysis patients. A decision tree model was constructed to reflect progression from hemodialysis initiation. Patients were classified into one of three vascular access choices: maintain CVC, attempt fistula, or attempt graft. We explicitly modeled probabilities of primary and secondary patency for each access type, with success modified by age, sex, and diabetes. Access-specific mortality was incorporated using preexisting cohort data, including terms for age, sex, and diabetes. Costs were ascertained from the 2010 USRDS report and Medicare for procedure costs. An AV fistula attempt strategy was found to be superior to AV grafts and CVCs in regard to mortality and cost for the majority of patient characteristic combinations, especially younger men without diabetes. Women with diabetes and elderly men with diabetes had similar outcomes, regardless of access type. Overall, the advantages of an AV fistula attempt strategy lessened considerably among older patients, particularly women with diabetes, reflecting the effect of lower AV fistula success rates and lower life expectancy. These results suggest that vascular access-related outcomes may be optimized by considering individual patient characteristics. PMID:25063436
Omitaomu, Olufemi A; Parish, Esther S; Nugent, Philip J
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.
O'Shea, E; Cusack, S; O'Sullivan, I
Clinical decision units (CDUs) are areas within an emergency department (ED) providing care for the patient who may benefit from an extended observation period, usually for a maximum of twenty-four hours. A retrospective patient record audit was performed to determine the characteristics of patients admitted to the Cork University Hospital (CUH) CDU over 12 months. The average length of stay of a patient in the CDU was 29 hours. The most common diagnoses admitted to the CDU were chest pain (9.5%) and headache (7.2%). The research implies that the CDU provided a means for CUH to save approximately €2 million annually.
Ruaño, Gualberto; Seip, Richard; Windemuth, Andreas; Wu, Alan H B; Thompson, Paul D
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.
Ferreira, Daian Miranda; Bezerra, Régis Otaviano França; Ortega, Cinthia Denise; Blasbalg, Roberto; Viana, Públio César Cavalcante; de Menezes, Marcos Roberto; Rocha, Manoel de Souza
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
Polen, Hyla H; Zapantis, Antonia; Clauson, Kevin A; Clauson, Kevin Alan; Jebrock, Jennifer; Paris, Mark
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).
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
Worachartcheewan, Apilak; Nantasenamat, Chanin; Isarankura-Na-Ayudhya, Chartchalerm; Pidetcha, Phannee; Prachayasittikul, Virapong
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%.
Le, Anh T.; Miller, Paul W.
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…
Cost-effectiveness of different interferon beta products for relapsing-remitting and secondary progressive multiple sclerosis: Decision analysis based on long-term clinical data and switchable treatments
Background Multiple sclerosis (MS) is a highly debilitating immune mediated disorder and the second most common cause of neurological disability in young and middle-aged adults. Iran is amongst high MS prevalence countries (50/100,000). Economic burden of MS is a topic of important deliberation in economic evaluations study. Therefore determining of cost-effectiveness interferon beta (INF β) and their copied biopharmaceuticals (CBPs) and biosimilars products is significant issue for assessment of affordability in Lower-middle-income countries (LMICs). Methods A literature-based Markov model was developed to assess the cost-effectiveness of three INF βs products compared with placebo for managing a hypothetical cohort of patients diagnosed with relapsing remitting MS (RRMS) in Iran from a societal perspective. Health states were based on the Kurtzke Expanded Disability Status Scale (EDSS). Disease progression transition probabilities for symptom management and INF β therapies were obtained from natural history studies and multicenter randomized controlled trials and their long term follow up for RRMS and secondary progressive MS (SPMS). A cross sectional study has been developed to evaluate cost and utility. Transitions among health states occurred in 2-years cycles for fifteen cycles and switching to other therapies was allowed. Calculations of costs and utilities were established by attachment of decision trees to the overall model. The incremental cost effectiveness ratio (ICER) of cost/quality adjusted life year (QALY) for all available INF β products (brands, biosimilars and CBPs) were considered. Both costs and utilities were discounted. Sensitivity analyses were done to assess robustness of model. Results ICER for Avonex, Rebif and Betaferon was 18712, 11832, 15768 US Dollars ($) respectively when utility attained from literature review has been considered. ICER for available CBPs and biosimilars in Iran was $847, $6964 and $11913. Conclusions The Markov
Samalin, Ludovic; Garnier, Marion; Auclair, Candy; Llorca, Pierre-Michel
The purpose of this study was to identify clinician characteristics associated with higher prescription rates of long-acting injectable (LAI) antipsychotics, as well as the sources that influence medical decision-making regarding the treatment of schizophrenia. We surveyed 202 psychiatrists during six regional French conferences (Bordeaux, Lyon, Marseille, Nice, Paris, and Strasbourg). Data on the characteristics of practice, prescription rates of antipsychotic, and information sources about their clinical decisions were collected. Most psychiatrists used second-generation antipsychotics (SGAs), and preferentially an oral formulation, in the treatment of schizophrenia. LAI SGAs were prescribed to 30.4% of schizophrenic patients. The duration and type of practice did not influence the class or formulation of antipsychotics used. The clinicians following the higher percentage of schizophrenic patients were associated with a higher use of LAI antipsychotics and a lower use of oral SGAs. Personal experience, government regulatory approval, and guidelines for the treatment of schizophrenia were the three main contributing factors guiding clinicians’ decision-making regarding the treatment of schizophrenia. The more clinicians follow schizophrenic patients, the more they use LAI antipsychotics. The development of specialized programs with top specialists should lead to better use of LAI antipsychotics in the treatment of schizophrenia. PMID:27869767
Samalin, Ludovic; Garnier, Marion; Auclair, Candy; Llorca, Pierre-Michel
The purpose of this study was to identify clinician characteristics associated with higher prescription rates of long-acting injectable (LAI) antipsychotics, as well as the sources that influence medical decision-making regarding the treatment of schizophrenia. We surveyed 202 psychiatrists during six regional French conferences (Bordeaux, Lyon, Marseille, Nice, Paris, and Strasbourg). Data on the characteristics of practice, prescription rates of antipsychotic, and information sources about their clinical decisions were collected. Most psychiatrists used second-generation antipsychotics (SGAs), and preferentially an oral formulation, in the treatment of schizophrenia. LAI SGAs were prescribed to 30.4% of schizophrenic patients. The duration and type of practice did not influence the class or formulation of antipsychotics used. The clinicians following the higher percentage of schizophrenic patients were associated with a higher use of LAI antipsychotics and a lower use of oral SGAs. Personal experience, government regulatory approval, and guidelines for the treatment of schizophrenia were the three main contributing factors guiding clinicians' decision-making regarding the treatment of schizophrenia. The more clinicians follow schizophrenic patients, the more they use LAI antipsychotics. The development of specialized programs with top specialists should lead to better use of LAI antipsychotics in the treatment of schizophrenia.
Dempsey, Paula J.; Handschuh, Robert F.; Afjeh, Abdollah A.
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.
Bento, Antonio M; Klotz, Richard
Lifecycle analysis (LCA) metrics of greenhouse gas emissions are increasingly being used to select technologies supported by climate policy. However, LCAs typically evaluate the emissions associated with a technology or product, not the impacts of policies. Here, we show that policies supporting the same technology can lead to dramatically different emissions impacts per unit of technology added, due to multimarket responses to the policy. Using a policy-based consequential LCA, we find that the lifecycle emissions impacts of four US biofuel policies range from a reduction of 16.1 gCO2e to an increase of 24.0 gCO2e per MJ corn ethanol added by the policy. The differences between these results and representative technology-based LCA measures, which do not account for the policy instrument driving the expansion in the technology, illustrate the need for policy-based LCA measures when informing policy decision making.
Bloyd, Cary N.
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). Biomass is seen as an important domestic energy feedstock, and there are multiple pathways in which it can be linked to the transport sector. Contenders include the use of cellulosic ethanol from biomass to replace gasoline or the use of a biomass-fueled combined cycle electrical power generation facility in conjunction plug-in hybrid electric vehicles (PHEVs). This paper reviews a project that is developing a scenario decision analysis tool to assist policy makers, program managers, and others to obtain a better understanding of these uncertain possibilities and how they may interact over time.
Lee, Wah Ching; Hung, Faan Hei; Tsang, Kim Fung; Tung, Hoi Ching; Lau, Wing Hong; Rakocevic, Veselin; Lai, Loi Lei
Each year, some 30 percent of global deaths are caused by cardiovascular diseases. This figure is worsening due to both the increasing elderly population and severe shortages of medical personnel. The development of a cardiovascular diseases classifier (CDC) for auto-diagnosis will help address solve the problem. Former CDCs did not achieve quick evaluation of cardiovascular diseases. In this letter, a new CDC to achieve speedy detection is investigated. This investigation incorporates the analytic hierarchy process (AHP)-based multiple criteria decision analysis (MCDA) to develop feature vectors using a Support Vector Machine. The MCDA facilitates the efficient assignment of appropriate weightings to potential patients, thus scaling down the number of features. Since the new CDC will only adopt the most meaningful features for discrimination between healthy persons versus cardiovascular disease patients, a speedy detection of cardiovascular diseases has been successfully implemented. PMID:25587978
Dempsey, Paula J.; Lewicki, David G.; Decker, Harry J.
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.
Mengersen, Kerrie; MacNeil, M. Aaron; Caley, M. Julian
Meta-analysis and decision analysis are underpinned by well-developed methods that are commonly applied to a variety of problems and disciplines. While these two fields have been closely linked in some disciplines such as medicine, comparatively little attention has been paid to the potential benefits of linking them in ecology, despite reasonable…
This research compares, on a variety of clinical and contextual factors, case episodes in which Clinical Social Workers decided to certify patients for involuntary hospitalization with those episodes where they decided not to certify them. A cross-sectional exploratory design was developed, and descriptive data was collected using a modified critical incident technique and a structured interview schedule. Among certified cases, the dangerousness of the patient was the major reason for certification, especially dangerousness to others. Lack of dangerousness to others and use of alternatives to involuntary hospitalization were major factors in the decision not to certify. Schizophrenic disorders were most frequently identified in certified patients; depressive and neurotic conditions in non-certified cases.
Grunow, Martin; Günther, Hans-Otto; Yang, Gang
Clinical studies for the development of new drugs in the pharmaceutical industry consist of a number of individual tasks which have to be carried out in a pre-defined chronological order. Each task requires certain types of medical personnel. This paper investigates the scheduling of clinical studies to be performed during a short-term planning horizon, the allocation of workforce between the studies, and the assignment of individual employees to tasks. Instead of developing a complex monolithic decision model, a hierarchical modelling approach is suggested. In the first stage, a compact integer optimization model is solved in order to determine the start-off times of the studies and the required staffing while taking the limited availability of personnel into account. The objective is to minimize total staffing costs. The assignment of individual employees to tasks is then made in the second stage of the procedure using a binary optimization model.
Marco-Ruiz, Luis; Maldonado, J Alberto; Karlsen, Randi; Bellika, Johan G
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.
Xu, Richard H; Wong, Eliza LY
Objective This study is a preliminary exploration of the association between patient involvement in decision-making and patient socioeconomic characteristics and experience in specialist outpatient clinics (SOPCs) in Hong Kong. Methods Cross-sectional telephone interviews were conducted using the Specialist Outpatient Experience Questionnaire (SOPEQ) in 26 Hospital Authority public SOPCs in Hong Kong. The SOPEQ was designed by The School of Public Health and Primary Care at The Chinese University of Hong Kong, fully taking into account both literature review and the local context of the public specialist outpatient system in Hong Kong. A total of 22,525 eligible participants were recruited for the study. Results There were 13,966 valid responses. The results indicated that the patients who had more involvement in decision-making were younger (odds ratio [OR] =2.10; 95% CI 1.75, 2.53), more highly educated (OR =1.67; 95% CI 1.45, 1.93), less likely to be receiving a government allowance (OR =0.61; 95% CI 0.57, 0.65), and less likely to be in the new case group (OR =0.84; 95% CI 0.78, 0.92). Participants living with their families (OR =3.38; 95% CI 2.03, 5.63) or who were unemployed (OR =1.10; 95% CI 1.01, 1.21) had a more decisive role in the decision- making process. Those participants who had been more involved in decision-making and wanted to continue being more involved had greater levels of satisfaction (mean =7.94; P<0.001) and a better health status (OR =0.49; 95% CI 0.41, 0.58). Conclusion Engaging patients in their health care management remains a challenge in improving patient-centered care. Our results suggest that patient engagement is associated with perceived health status and the experience of using a health service. Understanding patients’ characteristics and roles facilitates the development of preferred styles in the decision-making model. PMID:28331297
Bos-Touwen, Irene D.; Trappenburg, Jaap C. A.; van der Wulp, Ineke; Schuurmans, Marieke J.; de Wit, Niek J.
Background and aim Self-management support is an integral part of current chronic care guidelines. The success of self-management interventions varies between individual patients, suggesting a need for tailored self-management support. Understanding the role of patient factors in the current decision making of health professionals can support future tailoring of self-management interventions. The aim of this study is to identify the relative importance of patient factors in health professionals’ decision making regarding self-management support. Method A factorial survey was presented to primary care physicians and nurses. The survey consisted of clinical vignettes (case descriptions), in which 11 patient factors were systematically varied. Each care provider received a set of 12 vignettes. For each vignette, they decided whether they would give this patient self-management support and whether they expected this support to be successful. The associations between respondent decisions and patient factors were explored using ordered logit regression. Results The survey was completed by 60 general practitioners and 80 nurses. Self-management support was unlikely to be provided in a third of the vignettes. The most important patient factor in the decision to provide self-management support as well as in the expectation that self-management support would be successful was motivation, followed by patient-provider relationship and illness perception. Other factors, such as depression or anxiety, education level, self-efficacy and social support, had a small impact on decisions. Disease, disease severity, knowledge of disease, and age were relatively unimportant factors. Conclusion This is the first study to explore the relative importance of patient factors in decision making and the expectations regarding the provision of self-management support to chronic disease patients. By far, the most important factor considered was patient’s motivation; unmotivated patients
Van Belle, Vanya M. C. A.; Van Calster, Ben; Timmerman, Dirk; Bourne, Tom; Bottomley, Cecilia; Valentin, Lil; Neven, Patrick; Van Huffel, Sabine; Suykens, Johan A. K.; Boyd, Stephen
Background Over time, methods for the development of clinical decision support (CDS) systems have evolved from interpretable and easy-to-use scoring systems to very complex and non-interpretable mathematical models. In order to accomplish effective decision support, CDS systems should provide information on how the model arrives at a certain decision. To address the issue of incompatibility between performance, interpretability and applicability of CDS systems, this paper proposes an innovative model structure, automatically leading to interpretable and easily applicable models. The resulting models can be used to guide clinicians when deciding upon the appropriate treatment, estimating patient-specific risks and to improve communication with patients. Methods and Findings We propose the interval coded scoring (ICS) system, which imposes that the effect of each variable on the estimated risk is constant within consecutive intervals. The number and position of the intervals are automatically obtained by solving an optimization problem, which additionally performs variable selection. The resulting model can be visualised by means of appealing scoring tables and color bars. ICS models can be used within software packages, in smartphone applications, or on paper, which is particularly useful for bedside medicine and home-monitoring. The ICS approach is illustrated on two gynecological problems: diagnosis of malignancy of ovarian tumors using a dataset containing 3,511 patients, and prediction of first trimester viability of pregnancies using a dataset of 1,435 women. Comparison of the performance of the ICS approach with a range of prediction models proposed in the literature illustrates the ability of ICS to combine optimal performance with the interpretability of simple scoring systems. Conclusions The ICS approach can improve patient-clinician communication and will provide additional insights in the importance and influence of available variables. Future challenges
Ito, Makoto; Doya, Kenji
Reinforcement learning theory plays a key role in understanding the behavioral and neural mechanisms of choice behavior in animals and humans. Especially, intermediate variables of learning models estimated from behavioral data, such as the expectation of reward for each candidate choice (action value), have been used in searches for the neural correlates of computational elements in learning and decision making. The aims of the present study are as follows: (1) to test which computational model best captures the choice learning process in animals and (2) to elucidate how action values are represented in different parts of the corticobasal ganglia circuit. We compared different behavioral learning algorithms to predict the choice sequences generated by rats during a free-choice task and analyzed associated neural activity in the nucleus accumbens (NAc) and ventral pallidum (VP). The major findings of this study were as follows: (1) modified versions of an action-value learning model captured a variety of choice strategies of rats, including win-stay-lose-switch and persevering behavior, and predicted rats' choice sequences better than the best multistep Markov model; and (2) information about action values and future actions was coded in both the NAc and VP, but was less dominant than information about trial types, selected actions, and reward outcome. The results of our model-based analysis suggest that the primary role of the NAc and VP is to monitor information important for updating choice behaviors. Information represented in the NAc and VP might contribute to a choice mechanism that is situated elsewhere.
Exley, Catherine E; Rousseau, Nikki S; Steele, Jimmy; Finch, Tracy; Field, James; Donaldson, Cam; Thomason, J Mark; May, Carl R; Ellis, Janice S
Background The aim of this study is to examine how clinicians and patients negotiate clinical need and treatment decisions within a context of finite resources. Dental implant treatment is an effective treatment for missing teeth, but is only available via the NHS in some specific clinical circumstances. The majority of people who receive this treatment therefore pay privately, often at substantial cost to themselves. People are used to paying towards dental treatment costs. However, dental implant treatment is much more expensive than existing treatments – such as removable dentures. We know very little about how dentists make decisions about whether to offer such treatments, or what patients consider when deciding whether or not to pay for them. Methods/Design Mixed methods will be employed to provide insight and understanding into how clinical need is determined, and what influences people's decision making processes when deciding whether or not to pursue a dental implant treatment. Phase 1 will use a structured scoping questionnaire with all the General dental practitioners (GDPs) in three Primary Care Trust areas (n = 300) to provide base-line data about existing practice in relation to dental implant treatment, and to provide data to develop a systematic sampling procedure for Phase 2. Phases 2 (GDPs) and 3 (patients) use qualitative focused one to one interviews with a sample of these practitioners (up to 30) and their patients (up to 60) to examine their views and experiences of decision making in relation to dental implant treatment. Purposive sampling for phases 2 and 3 will be carried out to ensure participants represent a range of socio-economic circumstances, and choices made. Discussion Most dental implant treatment is conducted in primary care. Very little information was available prior to this study about the quantity and type of treatment carried out privately. It became apparent during phase 2 that ISOD treatment was an unusual treatment in
Background Widespread application of research findings to improve patient outcomes remains inadequate, and failure to routinely translate research findings into daily clinical practice is a major barrier for the implementation of any evidence-based guideline. Strategies to increase guideline uptake in primary care pediatric practices and to facilitate adherence to recommendations are required. Objective Our objective was to operationalize the US National Heart, Lung, and Blood Institute’s Integrated Guidelines for Cardiovascular Health and Risk Reduction in Children and Adolescents into a mobile clinical decision support (CDS) system for healthcare providers, and to describe the process development and outcomes. Methods To overcome the difficulty of translating clinical practice guidelines into a computable form that can be used by a CDS system, we used a multilayer framework to convert the evidence synthesis into executable knowledge. We used an iterative process of design, testing, and revision through each step in the translation of the guidelines for use in a CDS tool to support the development of 4 validated modules: an integrated risk assessment; a blood pressure calculator; a body mass index calculator; and a lipid management instrument. Results The iterative revision process identified several opportunities to improve the CDS tool. Operationalizing the integrated guideline identified numerous areas in which the guideline was vague or incorrect and required more explicit operationalization. Iterative revisions led to workable solutions to problems and understanding of the limitations of the tool. Conclusions The process and experiences described provide a model for other mobile CDS systems that translate written clinical practice guidelines into actionable, real-time clinical recommendations. PMID:28270384
Chih-Wen Cheng; Hang Wu; Thompson, Pamela J; Taylor, Julie R; Zehnbauer, Barbara A; Wilson, Karlyn K; Wang, May D
Patients with certain clotting disorders or conditions have a greater risk of developing arterial or venous clots and downstream embolisms, strokes, and arterial insufficiency. These patients need prescription anticoagulant drugs to reduce the possibility of clot formation. However, historically, the clinical decision making workflow in determining the correct type and dosage of anticoagulant(s) is part science and part art. To address this problem, we developed Anticoagulation Manager, an intelligent clinical decision workflow management system on iOS-based mobile devices to help clinicians effectively choose the most appropriate and helpful follow-up clotting tests for patients with a common clotting profile. The app can provide physicians guidance to prescribe the most appropriate medication for patients in need of anticoagulant drugs. This intelligent app was jointly designed and developed by medical professionals in CDC and engineers at Georgia Tech, and will be evaluated by physicians for ease-of-use, robustness, flexibility, and scalability. Eventually, it will be deployed and shared in both physician community and developer community.
Burns, Scott A; Mintken, Paul E; Austin, Gary P
The prevalence of lumbar and hip pathology is on the rise; however, treatment outcomes have not improved, highlighting the difficulty in identifying and treating the correct impairments. The purpose of this case report is to describe the clinical decision making in the examination and treatment of an individual with secondary hip-spine syndrome. Our case study was a 62-year-old male with low back pain with concomitant right hip pain. His Oswestry Disability Index (ODI) was 18%, back numeric pain rating scale (NPRS) was 4/10, fear avoidance beliefs questionnaire (FABQ) work subscale was 0, FABQ physical activity subscale was 18, and patient specific functional scale (PSFS) was 7.33. Physical examination revealed findings consistent with secondary hip-spine syndrome. He was treated for four visits with joint mobilization/manipulation and strengthening exercises directed at the hip. At discharge, all standardized outcome measures achieved full resolution. Clinical decision making in the presence of lumbopelvic-hip pain is often difficult. Previous literature has shown that some patients with lumbopelvic-hip pain respond favorably to manual therapy and exercise targeting regions adjacent to the lumbar spine. The findings of this case report suggest that individuals with a primary complaint of LBP with hip impairments may benefit from interventions to reduce hip impairments.
Pang, Justine; Feblowitz, Joshua C; Maloney, Francine L; Wilcox, Allison R; McLoughlin, Karen Sax; Ramelson, Harley; Schneider, Louise; Bates, David W
Background Accurate clinical problem lists are critical for patient care, clinical decision support, population reporting, quality improvement, and research. However, problem lists are often incomplete or out of date. Objective To determine whether a clinical alerting system, which uses inference rules to notify providers of undocumented problems, improves problem list documentation. Study Design and Methods Inference rules for 17 conditions were constructed and an electronic health record-based intervention was evaluated to improve problem documentation. A cluster randomized trial was conducted of 11 participating clinics affiliated with a large academic medical center, totaling 28 primary care clinical areas, with 14 receiving the intervention and 14 as controls. The intervention was a clinical alert directed to the provider that suggested adding a problem to the electronic problem list based on inference rules. The primary outcome measure was acceptance of the alert. The number of study problems added in each arm as a pre-specified secondary outcome was also assessed. Data were collected during 6-month pre-intervention (11/2009–5/2010) and intervention (5/2010–11/2010) periods. Results 17 043 alerts were presented, of which 41.1% were accepted. In the intervention arm, providers documented significantly more study problems (adjusted OR=3.4, p<0.001), with an absolute difference of 6277 additional problems. In the intervention group, 70.4% of all study problems were added via the problem list alerts. Significant increases in problem notation were observed for 13 of 17 conditions. Conclusion Problem inference alerts significantly increase notation of important patient problems in primary care, which in turn has the potential to facilitate quality improvement. Trial Registration ClinicalTrials.gov: NCT01105923. PMID:22215056
Johns, Ellis B; Halpenny, Barbara; Saunders, Toni-Ann; Brzozowski, Jane; Del Fiol, Guilherme; Berry, Donna L; Braun, Ilana M; Finn, Kathleen; Wolfe, Joanne; Abrahm, Janet L; Cooley, Mary E
Background Management of uncontrolled symptoms is an important component of quality cancer care. Clinical guidelines are available for optimal symptom management, but are not often integrated into the front lines of care. The use of clinical decision support (CDS) at the point-of-care is an innovative way to incorporate guideline-based symptom management into routine cancer care. Objective The objective of this study was to develop and evaluate a rule-based CDS system to enable management of multiple symptoms in lung cancer patients at the point-of-care. Methods This study was conducted in three phases involving a formative evaluation, a system evaluation, and a contextual evaluation of clinical use. In Phase 1, we conducted iterative usability testing of user interface prototypes with patients and health care providers (HCPs) in two thoracic oncology clinics. In Phase 2, we programmed complex algorithms derived from clinical practice guidelines into a rules engine that used Web services to communicate with the end-user application. Unit testing of algorithms was conducted using a stack-traversal tree-spanning methodology to identify all possible permutations of pathways through each algorithm, to validate accuracy. In Phase 3, we evaluated clinical use of the system among patients and HCPs in the two clinics via observations, structured interviews, and questionnaires. Results In Phase 1, 13 patients and 5 HCPs engaged in two rounds of formative testing, and suggested improvements leading to revisions until overall usability scores met a priori benchmarks. In Phase 2, symptom management algorithms contained between 29 and 1425 decision nodes, resulting in 19 to 3194 unique pathways per algorithm. Unit testing required 240 person-hours, and integration testing required 40 person-hours. In Phase 3, both patients and HCPs found the system usable and acceptable, and offered suggestions for improvements. Conclusions A rule-based CDS system for complex symptom management
van Os, Erim; Noordam, Cees; Hart, W Peter; Draaisma, Jos M T
A 14-year-old boy presented with fatigue and abdominal pain. Laboratory tests revealed a primary hypothyroidism with circulating auto-antibodies against thyroid peroxidase (TPO), anaemia and an elevated level of creatine kinase (CK). A diagnosis of auto-immune hypothyroidism with associated anaemia and myopathy was made. Thyroid hormone replacement therapy was started. However, six months later, he still complained of fatigue. He had unexpectedly varying thyroid function tests and the anaemia and the elevated level of CK persisted. Analysis of the other hormonal axes demonstrated a secondary adrenal insufficiency which was treated with hydrocortisone suppletion therapy. If a patient suffering from hypothyroidism does not respond appropriately to therapy or even deteriorates, adrenal insufficiency should always be considered. Patients with one type of auto-immune endocrinopathy have a greater risk at developing other types of auto-immune endocrinopathies.
Kunhimangalam, Reeda; Ovallath, Sujith; Joseph, Paul K
The prevalence of peripheral neuropathy in general population is ever increasing. The diagnosis and classification of peripheral neuropathies is often difficult as it involves careful clinical and electro-diagnostic examination by an expert neurologist. In developing countries a large percentage of the disease remains undiagnosed due to lack of adequate number of experts. In this study a novel clinical decision support system has been developed using a fuzzy expert system. The study was done to provide a solution to the demand of systems that can improve health care by accurate diagnosis in limited time, in the absence of specialists. It employs a graphical user interface and a fuzzy logic controller with rule viewer for identification of the type of peripheral neuropathy. An integrated medical records database is also developed for the storage and retrieval of the data. The system consists of 24 input fields, which includes the clinical values of the diagnostic test and the clinical symptoms. The output field is the disease diagnosis, whether it is Motor (Demyelinating/Axonopathy) neuropathy, sensory (Demyelinating/Axonopathy) neuropathy, mixed type or a normal case. The results obtained were compared with the expert's opinion and the system showed 93.27 % accuracy. The study aims at showing that Fuzzy Expert Systems may prove useful in providing diagnostic and predictive medical opinions. It enables the clinicians to arrive at a better diagnosis as it keeps the expert knowledge in an intelligent system to be used efficiently and effectively.
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
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.
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
Esophageal perforation is a rare and potentially life-threatening condition. Early clinical suspicion and imaging is important for case management to achieve a good outcome. However, recent studies continue to report high morbidity and mortality greater than 20% from esophageal perforation. At least half of the perforations are iatrogenic, mostly related to endoscopic instrumentation used in the upper gastrointestinal tract, while about a third are spontaneous perforations. Surgical treatment remains an important option for many patients, but a non-operative approach, with or without use of an endoscopic stent or placement of internal or external drains, should be considered when the clinical situation allows for a less invasive approach. The rarity of this emergency makes it difficult for a physician to obtain extensive individual clinical experience; it is also challenging to obtain firm scientific evidence that informs patient management and clinical decision-making. Improved attention to non-specific symptoms and signs and early diagnosis based on imaging may translate into better outcomes for this group of patients, many of whom are elderly with significant comorbidity. PMID:22035338
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...
Chatterji, Gano B.; Sridhar, Banavar; Kim, Douglas
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.
Olyazadeh, Roya; van Westen, Cees; Bakker, Wim H.; Aye, Zar Chi; Jaboyedoff, Michel; Derron, Marc-Henri
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
Williams, Karen B; Burgardt, Grayson J; Rapley, John W; Bray, Kimberly K; Cobb, Charles M
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.
Urinary tract infection (UTI) is a common and important clinical problem in children. Follow up imaging is indicated in some cases to reduce the risk of long-term harm from UTI and sometimes to help guide acute management. Overuse of imaging may be harmful due to radiation exposure, as well as increasing demand on services and budgets. On the other hand under-use of imaging may leave children vulnerable to renal damage and long-term morbidity. Accepted standards propose an imaging strategy specific to age and type of UTI. The complexity of the guideline makes compliance with the standards challenging. The aim of this project was to assess current practice for imaging of children with UTI managed at The Royal Oldham Hospital and to improve compliance with accepted standards through the use of a proforma to aid clinical decision making, supported by an education programme. A retrospective audit was performed over a 6 month period both prior to and after the intervention. The baseline audit found 57.7% of children treated for UTI (n=26) had imaging compliant with the accepted standards, which improved to 75.9% (n=29) on post-measurement. The percentage of inappropriate investigations reduced from 52.4% to 10.5%. The percentage of missed investigations reduced from 35.0% to 32.0%. The proforma was used and filed in 40% of cases where practice was in line with accepted standards. It was not used in any of the cases where practice deviated. In conclusion, a clear clinical decision aid, supported by an education programme, can significantly improve compliance with accepted standards for imaging of children with UTI. This may also be transferable to other scenarios where guidelines exist but have reduced efficacy due to complexity and/or lack of understanding.
Polaschek, Jeanette X.; Lenert, Leslie A.; Garber, Alan M.
The majority of patients with coronary artery disease do not fall into the well defined populations from randomized clinical trials. Observational databases contain a rich source of information that could be used by practicing physicians to evaluate treatment alternatives for their patients. We describe a computer system, the CABG Kibitzer, which uses an integrated approach to evaluate the treatment alternatives for CAD patients. We combine a statistical multivariate model for calculating survival advantages with DA techniques for assessing patient preferences and sensitivity analysis, to create one tool that physicians find easy to use in daily clinical practice. The development of tools of this kind is a necessary step in making the data of outcome studies accessible to practicing physicians.
Kargi, Atil Y.; Bustamante, Marcela Perez; Gulec, Seza
In recent years there has been an increased awareness of the genetic alterations underlying both benign and malignant neoplasms of the thyroid. Next-generation sequencing (NGS) is an emerging technology that allows for rapid detection of a large number of genetic mutations in thyroid fine-needle aspiration (FNA) specimens. NGS for targeted mutational analysis in thyroid tumors has been proposed as a tool to assist in the diagnosis of thyroid nodules with indeterminate FNA cytology. Results of genomic testing of thyroid nodules and thyroid cancers could also have prognostic implications and play a role in determining optimal treatment strategies including targeted therapies. We provide a critical review of existing studies assessing the performance of the ThyroSeq NGS test for the diagnosis and management of patients with thyroid nodules with indeterminate cytopathology and discuss the applicability of findings from these studies to clinical practice. While there are early indications to suggest a possible utility of data obtained from NGS to aid in prognostication and therapeutic decision-making in thyroid cancer, we recommend judicious use and cautious interpretation of such molecular testing until results of ongoing clinical trials become available. Lastly, we discuss recommendations provided from clinical practice guidelines regarding the use of mutation detection via NGS in the diagnostic evaluation of thyroid nodules. PMID:28117287
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
The aim of this study was to identify factors associated with youth satisfaction with surgical procedures performed to address oral cleft or craniofacial conditions (CFC). It was hypothesized that youth mental health, participation in decision-making, perceived consequences of living with a CFC, and coping strategies would be associated with satisfaction with past surgeries. Two hundred and three youth between the ages of 11 and 18 (Mean age = 14.5. SD = 2.0; 61% male; 78% oral cleft) completed a series of questionnaires measuring depression, self-esteem, participation in decision-making, condition severity, negative and positive consequences of having a CFC, coping, and satisfaction with past surgeries. Multiple Regression Analysis using boot-strapping techniques found that youth participation in decision making, youth perception of positive consequences of having a CFC, and coping accounted for 32% of the variance in satisfaction with past surgeries (p < .001). Youth age, sex, and assessment of condition severity were not significantly associated with satisfaction with surgical outcome. Depression, self-esteem, and negative consequences of having a CFC were not associated with satisfaction with past surgeries. Youth should be actively involved in the decision for craniofacial surgery. Youth who were more satisfied with their surgical outcomes also viewed themselves as having gained from the experience of living with a CFC. They felt that having a CFC made them stronger people and they believed that they were more accepting of others and more in touch with others’ feelings because of what they had been through. PMID:26114527
Yuan, Michael Juntao; Finley, George Mike; Mills, Christy; Johnson, Ron Kim
Background Clinical decision support systems (CDSS) are important tools to improve health care outcomes and reduce preventable medical adverse events. However, the effectiveness and success of CDSS depend on their implementation context and usability in complex health care settings. As a result, usability design and validation, especially in real world clinical settings, are crucial aspects of successful CDSS implementations. Objective Our objective was to develop a novel CDSS to help frontline nurses better manage critical symptom changes in hospitalized patients, hence reducing preventable failure to rescue cases. A robust user interface and implementation strategy that fit into existing workflows was key for the success of the CDSS. Methods Guided by a formal usability evaluation framework, UFuRT (user, function, representation, and task analysis), we developed a high-level specification of the product that captures key usability requirements and is flexible to implement. We interviewed users of the proposed CDSS to identify requirements, listed functions, and operations the system must perform. We then designed visual and workflow representations of the product to perform the operations. The user interface and workflow design were evaluated via heuristic and end user performance evaluation. The heuristic evaluation was done after the first prototype, and its results were incorporated into the product before the end user evaluation was conducted. First, we recruited 4 evaluators with strong domain expertise to study the initial prototype. Heuristic violations were coded and rated for severity. Second, after development of the system, we assembled a panel of nurses, consisting of 3 licensed vocational nurses and 7 registered nurses, to evaluate the user interface and workflow via simulated use cases. We recorded whether each session was successfully completed and its completion time. Each nurse was asked to use the National Aeronautics and Space Administration
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.
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. ...
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....
Stokes, Jacqueline; Schmidt, Glen
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…
Mohammed, Jalal; North, Nicola; Ashton, Toni
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
A decision support computer program (DSP) was used by the emergency room physician as a diagnostic tool on patients admitted with acute chest pain to guide the referral of these patients either to the Coronary Care Unit (CCU) or general ward. The DSP used Bayes' theorem on 38 anamnestic and clinical variables to classify patients into one of nine diagnoses. During a six months trial period 32 physicians used the DSP to diagnose 493 patients admitted with acute chest pain. The physicians referred the patients to CCU or general ward based on their clinical judgements, the ECG findings and the diagnostic estimates given by the DSP. The program correctly diagnosed 150 (84%) of 178 patients with acute myocardial infarction and 63 of 112 patients with unstable angina. However, acute ischemic heart disease (acute myocardial infarction or unstable angina) was correctly classified by the DSP for 259 (89%) of 290 patients. By using the DSP, the number of patients unnecessarily referred to CCU was reduced from 35% to 19% and the number of patients in need of CCU observation misallocated to general ward was reduced from 13% to 10%. Thus, use of the DSP in the emergency room on easily available anamnestic and clinical variables may improve referrals to the CCU, optimize therapy and resource use.
Begley, Charles; Shegog, Ross; Harding, Angelique; Goldsmith, Corey; Hope, Omotola; Newmark, Michael
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.
Chanani, Nikhil; Venugopalan, Janani; Maher, Kevin; Wang, May Dongmei
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
Samwald, Matthias; Fehre, Karsten; de Bruin, Jeroen; Adlassnig, Klaus-Peter
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.
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.
Brondum, Matthew C; Collier, Zachary A; Luke, Christopher S; Goatcher, Buddy L; Linkov, Igor
Wild pigs are a widespread invasive species that pose significant environmental and social risks. A number of wild pig eradication and control measures exist, but many eradication campaigns are ultimately unsuccessful. Decision making regarding how to design and execute an eradication plan is difficult because of multiple costs and benefits spanning various decision criteria that are associated with different eradication and control countermeasures. Moreover, multiple stakeholders are often involved with differing and sometimes competing objectives, and wild pigs are adaptive adversaries, meaning that the ideal countermeasure may change over time. In this paper, we propose the use of formal decision analytic tools which can structure decision problems into a set of relevant criteria, countermeasures, and stakeholder preferences to facilitate the evaluation of tradeoffs. We operationalize this method in a simple Excel-based decision tool and conclude with a path forward regarding how to successfully implement such tools for effective wild pig control.
Since 2003, the following tools have been implemented in Belgium for improving the access of general practioners to the EBM literature: the Digital Library for Health and the evidence-linker of the CEBAM, the portal EBMPracticeNet.be and the multidimensional electronic clinical decision support EBMeDS. The aim of this article is to show the progress achieved in the information dissemination toward the belgian general practioners, particularly the access from the electronic health record. From the literature published these last years, the opportunities cited by the users are for using EBM and the strong willingness for using these literature access in the future; the limits are the medical data coding, the irrelevance of the search results, the alerts fatigue induced by EBMeDS. The achievements done and planned for the new EBMPracticeNet guidelines portal and the EBMeDS system are explained in the aim of informing belgian healthcare professionals. These projects are claiming for lauching a participatory process in the production and dissemination of EBM information. The discussion is focused on the belgian healthcare system advantages, the solutions for a reasonable implementation of these projects and for increasing the place of an evidence-based information in the healthcare decision process. Finally the input of these projects to the continuing medical education and to the healthcare quality are discussed, in a context of multifactorial interaction healthcare design (complexity design).
Williams, Leanne M; Hermens, Daniel F; Thein, Thida; Clark, C Richard; Cooper, Nicholas J; Clarke, Simon D; Lamb, Chris; Gordon, Evian; Kohn, Michael R
Measures of cognition support diagnostic and treatment decisions in attention deficit hyperactivity disorder. We used an integrative neuroscience framework to assess cognition and associated brain-function correlates in large attention deficit hyperactivity disorder and healthy groups. Matched groups of 175 attention deficit hyperactivity disorder children/adolescents and 175 healthy control subjects were assessed clinically, with the touch screen-based cognitive assessment battery "IntegNeuro" (Brain Resource Ltd., Sydney, Australia) and the "LabNeuro" (Brain Resource Ltd., Sydney, Australia) platform for psychophysiologic recordings of brain function and body arousal. IntegNeuro continuous performance task measures of sustained attention classified 68% of attention deficit hyperactivity disorder patients with 76% specificity, consistent with previous reports. Our additional cognitive measures of impulsivity, intrusive errors, inhibition, and response variability improved sensitivity to 88%, and specificity to 91%. Positive predictive power was 96%, and negative predictive power, 88%. These metrics were stable across attention deficit hyperactivity disorder subtypes and age. Consistent with their brain-based validity, cognitive measures were correlated with corresponding brain-function and body-arousal measures. We propose a combination of candidate cognitive "markers" that define a signature for attention deficit hyperactivity disorder: "sustained attention," "impulsivity," "inhibition," "intrusions," and "response variability." These markers offer a frame of reference to support diagnostic and treatment decisions, and an objective benchmark for monitoring outcomes of interventions.
Loya, Salvador Rodriguez; Kawamoto, Kensaku; Chatwin, Chris; Huser, Vojtech
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.
Wu, Min; Yang, Jinqiu; Liu, Lingying; Ye, Benlan
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.
Eisenstein, Eric L; Willis, Janese M; Edwards, Rex; Anstrom, Kevin J; Kawamoto, Kensaku; Fiol, Guilherme Del; Johnson, Fred S; Lobach, David F
Medicaid beneficiaries in 6 North Carolina counties were randomly assigned to 1 of 3 clinical decision support (CDS) care transition strategies: (1) usual care (Control), (2) CDS messaging to patients and their medical homes (Reports), or (3) CDS messaging to patients, their medical homes, and their care managers (Reports+). We included 7146 Medicaid patients and evaluated transitions from specialist visit, ER and hospital encounters back to the patient's medical home. Patients enrolled in Medicare and Medicaid were not eligible. The number of care manager contacts was greater for patients in the Reports+ Group than in the Control Group. However, there were no treatment-related differences in emergency department (ED) encounter rates, or in the secondary outcomes of outpatient and hospital encounter rates and medical costs. Study monitors found study intervention documentation in approximately 60% of patient charts. These results highlight the importance of effectively integrating information interventions into healthcare delivery workflow systems.
Fuller, Shannon M; Koester, Kimberly A; Guinness, Ryan R; Steward, Wayne T
Shared decision-making (SDM) is considered best practice in health care. Prior studies have explored attitudes and barriers/facilitators to SDM, with few specific to HIV care. We interviewed 53 patients in HIV primary care clinics in California to understand the factors and situations that may promote or hinder engagement in SDM. Studies in other populations have found that patients' knowledge about their diseases and their trust in providers facilitated SDM. We found these features to be more nuanced for HIV. Perceptions of personal agency, knowledge about one's disease, and trust in provider were factors that could work for or against SDM. Overall, we found that participants described few experiences of SDM, especially among those with no comorbidities. Opportunities for SDM in routine HIV care (e.g., determining antiretroviral therapy) may arise infrequently because of treatment advances. These findings yield considerations for adapting SDM to fit the context of HIV care.
Jensen, Jeff D; Durand, Daniel J
Recent legislation mandates the documentation of appropriateness criteria consultation when ordering advanced imaging for Medicare patients to remain eligible for reimbursement. Implementation of imaging clinical decision support (CDS) is a solution adopted by many systems to automate compliance with the new requirements. This article is intended to help radiologists who are employed by, contracted with, or otherwise affiliated with systems planning to implement CDS in the near future and ensure that they are able to understand and contribute to the process wherever possible. It includes an in-depth discussion of the legislation, evidence for and against the efficacy of imaging CDS, considerations for selecting a CDS vendor, tips for configuring CDS in a fashion consistent with departmental goals, and pointers for implementation and change management.
Palmer, Christopher R; Shahumyan, Harutyun
This paper addresses two main questions: first, why should Bayesian and other innovative, data-dependent design models be put into practice and, secondly, given the past dearth of actual applications, how might one example of such a design be implemented in a genuine example trial? Clinical trials amalgamate theory, practice and ethics, but this last point has become relegated to the background, rather than taking often a more appropriate primary role. Trial practice has evolved but has its roots in R. A. Fisher's randomized agricultural field trials of the 1920s. Reasons for, and consequences of, this are discussed from an ethical standpoint, drawing on an under-used dichotomy introduced by French authors Lellouch and Schwartz (Int. Statist. Rev. 1971; 39:27-36). Plenty of ethically motivated designs for trials, including Bayesian designs have been proposed, but have found little application thus far. One reason for this is a lack of awareness of such alternative designs among trialists, while another reason is a lack of user-friendly software to allow study simulations. To encourage implementation, a new C++ program called 'Daniel' is introduced, offering much potential to assist the design of today's randomized controlled trials. Daniel evaluates a particular decision-theoretic method suitable for coping with either two or three Bernoulli response treatments with input features allowing user-specified choices of: patient horizon (number to be treated before and after the comparative stages of the trial); an arbitrary fixed trial truncation size (to allow ready comparison with traditional designs or to cope with practical constraints); anticipated success rates and a measure of their uncertainty (a matter ignored in standard power calculations); and clinically relevant, and irrelevant, differences in treatment effect sizes. Error probabilities and expected trial durations can be thoroughly explored via simulation, it being better by far to harm 'computer patients
Meira, Luis A. A.; Coelho, Guilherme P.; Santos, Antonio Alberto S.; Schiozer, Denis J.
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.
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.
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
Davies, B J B; Macfarlane, F
In April 2006 a new contract was introduced that governed how NHS General Dental Practitioners would be funded for the services they provide. This study looks at the impact that the contract has had in the three years since its introduction, evaluating its influence on the clinical care that patients receive and the clinical decisions that dentists are making. This qualitative service evaluation involved interviewing 12 dentists representative of a range of NHS dentists involved with the new NHS dental contract using a semi-structured approach. We found evidence that the new contract has led to dentists making different decisions in their daily practice and sometimes altering their treatment plans and referral patterns to ensure that their business is not disadvantaged. Access to care for some patients without a regular dentist can be compromised by the new contract as it can be financially challenging for a dentist to accept to care for a new patient who has an unknown and potentially large need for treatment. Cherry-picking of potentially more profitable patients may be common. The incentive is to watch borderline problems rather than to treat if a treatment band threshold has already been crossed and treatment may be delayed until a later course of treatment for the same reason. Dentists often feel that complex treatments (for example, endodontic treatments) are financially unviable. Some dentists are referring difficult cases that might previously have been treated 'in house', such as extractions, to another provider, as this enables offloading of costs while potentially retaining full fees. Younger and less experienced dentists may be further pressured.
Shakespeare, Thomas P. . E-mail: ThomasShakespeare@gmail.com; Back, Michael F.; Lu, Jiade J.; Lee, Khai Mun; Mukherjee, Rahul K.
Purpose: The external audit of oncologist clinical practice is increasingly important because of the incorporation of audits into national maintenance of certification (MOC) programs. However, there are few reports of external audits of oncology practice or decision making. Our institution (The Cancer Institute, Singapore) was asked to externally audit an oncology department in a developing Asian nation, providing a unique opportunity to explore the feasibility of such a process. Methods and Materials: We audited 100 randomly selected patients simulated for radiotherapy in 2003, using a previously reported audit instrument assessing clinical documentation/quality assurance and medical decision making. Results: Clinical documentation/quality assurance, decision making, and overall performance criteria were adequate 74.4%, 88.3%, and 80.2% of the time, respectively. Overall 52.0% of cases received suboptimal management. Multivariate analysis revealed palliative intent was associated with improved documentation/clinical quality assurance (p = 0.07), decision making (p 0.007), overall performance (p = 0.003), and optimal treatment rates (p 0.07); non-small-cell lung cancer or central nervous system primary sites were associated with better decision making (p = 0.001), overall performance (p = 0.03), and optimal treatment rates (p = 0.002). Conclusions: Despite the poor results, the external audit had several benefits. It identified learning needs for future targeting, and the auditor provided facilitating feedback to address systematic errors identified. Our experience was also helpful in refining our national revalidation audit instrument. The feasibility of the external audit supports the consideration of including audit in national MOC programs.
Kaltoft, Mette Kjer; Turner, Robin; Cunich, Michelle; Salkeld, Glenn; Nielsen, Jesper Bo; Dowie, Jack
The use of subgroups based on biological-clinical and socio-demographic variables to deal with population heterogeneity is well-established in public policy. The use of subgroups based on preferences is rare, except when religion based, and controversial. If it were decided to treat subgroup preferences as valid determinants of public policy, a transparent analytical procedure is needed. In this proof of method study we show how public preferences could be incorporated into policy decisions in a way that respects both the multi-criterial nature of those decisions, and the heterogeneity of the population in relation to the importance assigned to relevant criteria. It involves combining Cluster Analysis (CA), to generate the subgroup sets of preferences, with Multi-Criteria Decision Analysis (MCDA), to provide the policy framework into which the clustered preferences are entered. We employ three techniques of CA to demonstrate that not only do different techniques produce different clusters, but that choosing among techniques (as well as developing the MCDA structure) is an important task to be undertaken in implementing the approach outlined in any specific policy context. Data for the illustrative, not substantive, application are from a Randomized Controlled Trial of online decision aids for Australian men aged 40-69 years considering Prostate-specific Antigen testing for prostate cancer. We show that such analyses can provide policy-makers with insights into the criterion-specific needs of different subgroups. Implementing CA and MCDA in combination to assist in the development of policies on important health and community issues such as drug coverage, reimbursement, and screening programs, poses major challenges -conceptual, methodological, ethical-political, and practical - but most are exposed by the techniques, not created by them.
Summary of the proceedings of the international forum 2016: "Imaging referral guidelines and clinical decision support - how can radiologists implement imaging referral guidelines in clinical routine?"
The International Forum is held once a year by the ESR and its international radiological partner societies with the aim to address and discuss selected subjects of global relevance in radiology. In 2016, the issue of implementing imaging referral guidelines in clinical routine was analysed. The legal environment in the USA requires that after January 1, 2017, physicians must consult government-approved, evidence-based appropriate-use criteria through a clinical decision support system when ordering advanced diagnostic imaging exams. The ESR and the National Decision Support Company are developing "ESR iGuide", a clinical decision support system for European imaging referral guidelines using ESR imaging referral guidelines based on ACR Appropriateness Criteria. In many regions of the world, the situation is different and quite diverse, depending on the specific features of health care systems in different countries, but there are, unlike in the USA and EU, no legal obligations to implement imaging referral guidelines into the clinical practice. Imaging referral guidelines and clinical decision support implementation is a complex issue everywhere and the legal environment surrounding it even more so; how they will be implemented into the clinical practice in different areas of the world needs yet to be decided.
Kieslich, Katharina; Littlejohns, Peter
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
Aegisdottir, Stefania; Spengler, Paul M.; White, Michael J.
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…
Ameneiros-Lago, E; Carballada-Rico, C; Garrido-Sanjuán, J A; García Martínez, A
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.
Rodríguez, Rosa M.; Martínez, Luis
It is common that experts involved in complex real-world decision problems use natural language for expressing their knowledge in uncertain frameworks. The language is inherent vague, hence probabilistic decision models are not very suitable in such cases. Therefore, other tools such as fuzzy logic and fuzzy linguistic approaches have been successfully used to model and manage such vagueness. The use of linguistic information implies to operate with such a type of information, i.e. processes of computing with words (CWW). Different schemes have been proposed to deal with those processes, and diverse symbolic linguistic computing models have been introduced to accomplish the linguistic computations. In this paper, we overview the relationship between decision making and CWW, and focus on symbolic linguistic computing models that have been widely used in linguistic decision making to analyse if all of them can be considered inside of the CWW paradigm.
Brocq, H; Liarte, A; Soriani, M-H; Desnuelle, C
Should a patient be forced to accept a treatment, especially when suffering from a neurodegenerative disease? We argue that physicians, nurses and care givers should instead accept his or her choice in accordance with the principle that every patient is an autonomous person able to make a choice, even in case of declined cognition. Beside the legal obligation, we suggest a theoretical approach and focus on the practical impacts of the patient's decision. Our objective is to promote the value of ethical doubt and attentive listening to individual opinions, so as to improve the quality of the medical staff's work and reduce patients' distress when affected by fatal diseases.
Keuken, Max C.; Müller-Axt, Christa; Langner, Robert; Eickhoff, Simon B.; Forstmann, Birte U.; Neumann, Jane
In the recent perceptual decision-making literature, a fronto-parietal network is typically reported to primarily represent the neural substrate of human perceptual decision-making. However, the view that only cortical areas are involved in perceptual decision-making has been challenged by several neurocomputational models which all argue that the basal ganglia play an essential role in perceptual decisions. To consolidate these different views, we conducted an Activation Likelihood Estimation (ALE) meta-analysis on the existing neuroimaging literature. The results argue in favor of the involvement of a frontal-parietal network in general perceptual decision-making that is possibly complemented by the basal ganglia, and modulated in substantial parts by task difficulty. In contrast, expectation of reward, an important aspect of many decision-making processes, shows almost no overlap with the general perceptual decision-making network. PMID:24994979
AHP, and how this information can be utilized, permitting U.S. and allied forces to execute efficient and effective military operations. A case study...military decision-maker who uses the AHP, and how this information can be utilized, permitting U.S. and allied forces to execute efficient and effective ...this information can be utilized, permitting U.S. and allied forces to execute efficient and effective military operations. A case study of a decision
Federer, Andrew E; Taylor, Dean C; Mather, Richard C
Decision making in health care has evolved substantially over the last century. Up until the late 1970s, medical decision making was predominantly intuitive and anecdotal. It was based on trial and error and involved high levels of problem solving. The 1980s gave way to empirical medicine, which was evidence based probabilistic, and involved pattern recognition and less problem solving. Although this represented a major advance in the quality of medical decision making, limitations existed. The advantages of the gold standard of the randomized controlled clinical trial (RCT) are well-known and this technique is irreplaceable in its ability to answer critical clinical questions. However, the RCT does have drawbacks. RCTs are expensive and can only capture a snapshot in time. As treatments change and new technologies emerge, new expensive clinical trials must be undertaken to reevaluate them. Furthermore, in order to best evaluate a single intervention, other factors must be controlled. In addition, the study population may not match that of another organization or provider. Although evidence-based medicine has provided powerful data for clinicians, effectively and efficiently tailoring it to the individual has not yet evolved. We are now in a period of transition from this evidence-based era to one dominated by the personalization and customization of care. It will be fueled by policy decisions to shift financial responsibility to the patient, creating a powerful and sophisticated consumer, unlike any patient we have known before. The challenge will be to apply medical evidence and personal preferences to medical decisions and deliver it efficiently in the increasingly busy clinical setting. In this article, we provide a robust review of the concepts of customized care and some of techniques to deliver it. We will illustrate this through a personalized decision model for the treatment decision after a first-time anterior shoulder dislocation.
Kane-Gill, Sandra L; Achanta, Archita; Kellum, John A; Handler, Steven M
Clinical decision support (CDS) systems with automated alerts integrated into electronic medical records demonstrate efficacy for detecting medication errors (ME) and adverse drug events (ADEs). Critically ill patients are at increased risk for ME, ADEs and serious negative outcomes related to these events. Capitalizing on CDS to detect ME and prevent adverse drug related events has the potential to improve patient outcomes. The key to an effective medication safety surveillance system incorporating CDS is advancing the signals for alerts by using trajectory analyses to predict clinical events, instead of waiting for these events to occur. Additionally, incorporating cutting-edge biomarkers into alert knowledge in an effort to identify the need to adjust medication therapy portending harm will advance the current state of CDS. CDS can be taken a step further to identify drug related physiological events, which are less commonly included in surveillance systems. Predictive models for adverse events that combine patient factors with laboratory values and biomarkers are being established and these models can be the foundation for individualized CDS alerts to prevent impending ADEs. PMID:27896144
Gungor, Faruk; Guven, Ramazan; Akyol, K. Can; Kozaci, Nalan; Kesapli, Mustafa
We assessed the effect of focused point of care ultrasound (POCUS) used for critical nontraumatic hypotensive patients presenting to the emergency department of our hospital on the clinical decisions of the physicians and whether it led to the modification of the treatment modality. This prospective clinical study was conducted at the Emergency Department of Antalya Training and Research Hospital. Nontraumatic patients aged 18 and older who presented to our emergency department and whose systolic blood pressure was <100 mmHg or shock index (heart rate/systolic blood pressure) was >1 were included in the study. While the most probable preliminary diagnosis established by the physician before POCUS was consistent with the definitive diagnosis in 60.6% (n = 109) of 180 patients included in the study, it was consistent with the definitive diagnosis in 85.0% (n = 153) of the patients after POCUS (p < 0.001). POCUS performed for critical hypotensive patients presenting to the emergency department is an appropriate diagnostic tool that can be used to enable the physicians to make the accurate preliminary diagnosis and start the appropriate treatment in a short time. PMID:28357139
McCoy, Allison B.; Thomas, Eric J.; Krousel-Wood, Marie; Sittig, Dean F.
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
Sheets, L; Callaghan, F.; Gavino, A.; Liu, F.; Fontelo, P.
Background Smartphones are increasingly important for clinical decision support, but smartphone and Internet use are limited by cost or coverage in many settings. txt2MEDLINE provides access to published medical evidence by text messaging. Previous studies have evaluated this approach, but we found no comparisons with other tools in this format. Objectives To compare txt2MEDLINE with other databases for answering clinical queries by text messaging in low-resource settings. Methods Using varied formats, we searched txt2MEDLINE and five other search portals (askMEDLINE, Cochrane, DynaMed, PubMed PICO, and UpToDate) to develop optimal strategies for each. We then searched each database again with five benchmark queries, using the customized search-optimization formats. We truncated the results to less than 480 characters each to simulate delivering them to a maximum of three text messages. Clinicians with practice experience in low-resource areas scored the results on a 5-point Likert scale. Results Median scores and standard deviations from 17 reviewers were: txt2M2MEDLINE, 3.2±0.82 (control); askMEDLINE, 3.2±0.90 (p = 0.918); Cochrane, 3.8±0.58 (p = 0.073); DynaMed, 3.6±0.65 (p = 0.105); PubMed PICO, 3.6±0.82 (p = 0.005); and UpToDate, 4.0±0.52 (p = 0.002). Our sample size was sufficiently powered to find differences of 1.0 point. Conclusions Comparing several possible sources for texting-based clinical-decision-support information, our results did not demonstrate one-point differences in usefulness on a scale of 1 to 5. PubMed PICO and UpToDate were significantly better than txt2MEDLINE, but with relatively small improvements in Likert score (0.4 and 0.8, respectively). In a texting-only setting, txt2MEDLINE is comparable to simulated alternatives based on established reference sources. PMID:23646080
Carlson, Murray Dean
In this thesis we provide insights into the behavior of financial managers of utility companies by studying their decisions to redeem callable preferred shares. In particular, we investigate whether or not an option pricing based model of the call decision, with managers who maximize shareholder value, does a better job of explaining callable preferred share prices and call decisions than do other models of the decision. In order to perform these tests, we extend an empirical technique introduced by Rust (1987) to include the use of information from preferred share prices in addition to the call decisions. The model we develop to value the option embedded in a callable preferred share differs from standard models in two ways. First, as suggested in Kraus (1983), we explicitly account for transaction costs associated with a redemption. Second, we account for state variables that are observed by the decision makers but not by the preferred shareholders. We interpret these unobservable state variables as the benefits and costs associated with a change in capital structure that can accompany a call decision. When we add this variable, our empirical model changes from one which predicts exactly when a share should be called to one which predicts the probability of a call as the function of the observable state. These two modifications of the standard model result in predictions of calls, and therefore of callable preferred share prices, that are consistent with several previously unexplained features of the data; we show that the predictive power of the model is improved in a statistical sense by adding these features to the model. The pricing and call probability functions from our model do a good job of describing call decisions and preferred share prices for several utilities. Using data from shares of the Pacific Gas and Electric Co. (PGE) we obtain reasonable estimates for the transaction costs associated with a call. Using a formal empirical test, we are able to
Krain, Amy L; Wilson, Amanda M; Arbuckle, Robert; Castellanos, F Xavier; Milham, Michael P
Converging evidence from human and animal studies suggests that decision-making relies upon a distributed neural network based in the frontal lobes. In particular, models of decision-making emphasize the involvement of orbitofrontal cortices (OFC) and the medial wall. While decision-making has been studied broadly as a class of executive function, recent models have suggested the differentiation between risky and ambiguous decision-making. Given recent emphasis on the role of OFC in affectively laden "hot" executive function and dorsolateral prefrontal cortex (DLPFC) in more purely cognitive "cool" executive function, we hypothesize that the neural substrates of decision-making may differ depending on the nature of the decision required. To test this hypothesis, we used recently developed meta-analytic techniques to examine the existent functional neuroimaging literature. An initial meta-analysis of decision-making, both risky and ambiguous, found significantly elevated probabilities of activation in frontal and parietal regions, thalamus, and caudate. Ambiguous decision-making was associated with activity in DLPFC, regions of dorsal and subcallosal anterior cingulate cortex (ACC), and parietal cortex. Risky decision-making was associated with activity in OFC, rostral portions of the ACC, and parietal cortex. Direct statistical comparisons revealed significant differences between risky and ambiguous decision-making in frontal regions, including OFC, DLPFC, and ACC, that were consistent with study hypotheses. These findings provide evidence for the dissociation of neural circuits underlying risky and ambiguous decision-making, reflecting differential involvement of affective "hot" and cognitive "cool" processes.
Kawamoto, Kensaku; Del Fiol, Guilherme; Lobach, David F.; Jenders, Robert A
Despite their potential to significantly improve health care, advanced clinical decision support (CDS) capabilities are not widely available in the clinical setting. An important reason for this limited availability of CDS capabilities is the application-specific and institution-specific nature of most current CDS implementations. Thus, a critical need for enabling CDS capabilities on a much larger scale is the development and adoption of standards that enable current and emerging CDS resources to be more effectively leveraged across multiple applications and care settings. Standards required for such effective scaling of CDS include (i) standard terminologies and information models to represent and communicate about health care data; (ii) standard approaches to representing clinical knowledge in both human-readable and machine-executable formats; and (iii) standard approaches for leveraging these knowledge resources to provide CDS capabilities across various applications and care settings. A number of standards do exist or are under development to meet these needs. However, many gaps and challenges remain, including the excessive complexity of many standards; the limited availability of easily accessible knowledge resources implemented using standard approaches; and the lack of tooling and other practical resources to enable the efficient adoption of existing standards. Thus, the future development and widespread adoption of current CDS standards will depend critically on the availability of tooling, knowledge bases, and other resources that make the adoption of CDS standards not only the right approach to take, but the cost-effective path to follow given the alternative of using a traditional, ad hoc approach to implementing CDS. PMID:21603283
Kawamoto, Kensaku; Del Fiol, Guilherme; Lobach, David F; Jenders, Robert A
Despite their potential to significantly improve health care, advanced clinical decision support (CDS) capabilities are not widely available in the clinical setting. An important reason for this limited availability of CDS capabilities is the application-specific and institution-specific nature of most current CDS implementations. Thus, a critical need for enabling CDS capabilities on a much larger scale is the development and adoption of standards that enable current and emerging CDS resources to be more effectively leveraged across multiple applications and care settings. Standards required for such effective scaling of CDS include (i) standard terminologies and information models to represent and communicate about health care data; (ii) standard approaches to representing clinical knowledge in both human-readable and machine-executable formats; and (iii) standard approaches for leveraging these knowledge resources to provide CDS capabilities across various applications and care settings. A number of standards do exist or are under development to meet these needs. However, many gaps and challenges remain, including the excessive complexity of many standards; the limited availability of easily accessible knowledge resources implemented using standard approaches; and the lack of tooling and other practical resources to enable the efficient adoption of existing standards. Thus, the future development and widespread adoption of current CDS standards will depend critically on the availability of tooling, knowledge bases, and other resources that make the adoption of CDS standards not only the right approach to take, but the cost-effective path to follow given the alternative of using a traditional, ad hoc approach to implementing CDS.
Danielson, Carla Kmett; Cohen, Joseph R; Adams, Zachary W; Youngstrom, Eric A; Soltis, Kathryn; Amstadter, Ananda B; Ruggiero, Kenneth J
The present study aimed to utilize a Receiver Operating Characteristic (ROC) approach in order to improve clinical decision-making for adolescents at risk for the development of psychopathology in the aftermath of a natural disaster. Specifically we assessed theoretically-driven individual, interpersonal, and event-related vulnerability factors to determine which indices were most accurate in forecasting PTSD. Furthermore, we aimed to translate these etiological findings by identifying clinical cut-off recommendations for relevant vulnerability factors. Our study consisted of structured phone-based clinical interviews with 2000 adolescent-parent dyads living within a 5-mile radius of tornados that devastated Joplin, MO, and northern Alabama in Spring 2011. Demographics, tornado incident characteristics, prior trauma, mental health, and family support and conflict were assessed. A subset of youth completed two behavioral assessment tasks online to assess distress tolerance and risk-taking behavior. ROC analyses indicated four variables that significantly improved PTSD diagnostic efficiency: Lifetime depression (AUC = .90), trauma history (AUC = .76), social support (AUC = .70), and family conflict (AUC = .72). Youth were 2-3 times more likely to have PTSD if they had elevated scores on any of these variables. Of note, event-related characteristics (e.g., property damage) were not related to PTSD diagnostic status. The present study adds to the literature by making specific recommendations for empirically-based, efficient disaster-related PTSD assessment for adolescents following a natural disaster. Implications for practice and future trauma-related developmental psychopathology research are discussed.
Karamintziou, Sofia D.; Tsirogiannis, George L.; Stathis, Pantelis G.; Tagaris, George A.; Boviatsis, Efstathios J.; Sakas, Damianos E.; Nikita, Konstantina S.
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
Khan, Sundas; McCullagh, Lauren; Press, Anne; Kharche, Manish; Schachter, Andy; Pardo, Salvatore; McGinn, Thomas
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.
Sheehan, B.; Kaufman, D.; Bakken, S.; Currie, L. M.
Background Clinical decision support systems (CDSS) are a method used to support prescribing accuracy when deployed within a computerized provider order entry system (CPOE). Divergence from using CDSS is exemplified by high alert override rates. Excessive cognitive load imposed by the CDSS may help to explain such high rates. Objectives: The aim of this study was to describe the cognitive impact of a CPOE-integrated CDSS by categorizing system use problems according to the type of mental processing required to resolve them. Methods A qualitative, descriptive design was used employing two methods; a cognitive walkthrough and a think-aloud protocol. Data analysis was guided by Norman’s Theory of Action and a theory of cognitive distances which is an extension to Norman’s theory. Results The most frequently occurring source of excess cognitive effort was poor information timing. Information presented by the CDSS was often presented after clinicians required the information for decision making. Additional sources of effort included use of language that was not clear to the user, vague icons, and lack of cues to guide users through tasks. Conclusions Lack of coordination between clinician’s task-related thought processes and those presented by a CDSS results in excessive cognitive work required to use the system. This can lead to alert overrides and user errors. Close attention to user’s cognitive processes as they carry out clinical tasks prior to CDSS development may provide key information for system design that supports clinical tasks and reduces cognitive effort. PMID:23616903
Williams, Robert L.; Romney, Crystal; Kano, Miria; Wright, Randy; Skipper, Betty; Getrich, Christina; Sussman, Andrew L.; Zyzanski, Stephen J.
Background and objectives Health care reform aims to increase evidence based, cost-conscious, and patient-centered care. Family medicine is seen as central to these aims in part due to evidence of lower cost, comparable quality care compared with other specialties. We sought evidence that senior medical students planning family medicine residency differ from peers entering other fields in decision-making patterns relevant to these health care reform aims. Methods We conducted a national, anonymous, internet-based survey of senior medical students. Students chose one of two equivalent management options for a set of patient vignettes based on preventive care, medication selection or initial chronic disease management scenarios, representing in turn, evidence-based care, cost-conscious care, and patient-centered care. We examined differences in student recommendations, comparing those planning to enter family medicine with all others using bivariate and weighted, multilevel, multivariable analyses. Results Among 4,656 surveys received from seniors at 84 participating medical schools, students entering family medicine were significantly more likely to recommend patient management options that were more cost-conscious (p=.01) and more patient-centered (p<.001). We did not find a significant difference between the student groups in recommendations for evidence-based care vignettes. Conclusions This study provides preliminary evidence suggesting that students planning to enter family practice may already have clinical decision-making patterns that support health care reform goals to a greater extent than their peers. If confirmed by additional studies, this could have implications for medical school admission and training processes. PMID:24915476
Choe, Howard C.; Kazakos, Demetrios
A distributed (or decentralized) multiple sensor system is considered under binary hypothesis environments. The system is deployed with a host sensor (HS) and multiple slave sensors (SSs). All sensors have their own independent decision makers which are capable of declaring local decisions based solely on their own observation of the environment. The communication between the HS and the SSs is conditional upon the HS's command. Each communication that takes place involves a communication cost which plays an important role in the approaches taken in this study. The conditional communication with the cost initiates the team strategy in making the final decisions at the HS. The objectives are not only to apply the team strategy method in the decision making process, but also to minimize the expected system cost (or the probability of error in making decisions) by optimizing thresholds in the HS> The analytical expression of the expected system cost (C) is numerically evaluated for Gaussian statistics over threshold locations in the HS to find an optimal threshold location for a given communication cost. The computer simulations of various sensor systems for Gaussian observations are also performed in order to understand the behavior of each system with respect to correct detections, false, alarms, and target misses.
Choe, Howard C.; Kazakos, Dimitri
A distributed (or decentralized) multiple sensor system is considered under binary hypothesis environments. The system is deployed with a host sensor and multiple slave sensors. All sensors have their own independent decision makers (DM) which are capable of declaring local decisions based only on their own observation of the environment. The communication between the host sensor (HS) and the slave sensors (SS) is conditional upon the host sensor's command. Each communication that takes place involves a communication cost which plays an important role in approaches taken in this study. The conditional communication with cost initiates the team strategy in making the final decisions at the host sensor. The objectives are not only to apply the team strategy method in the decision making process, but also to minimize the expected system cost (or the probability or error in making decisions) by optimizing thresholds in the host sensor. The analytical expression of the expected system cost is numerically evaluated for Gaussian statistics over threshold locations in the host sensor to find an optimal threshold location for a given communication cost. The computer simulations of various sensor systems for Gaussian observations are also performed to understand the behavior of each system with respect to correct detections, false alarms, and target misses.
Kariman, Nourossadat; Amerian, Maliheh; Jannati, Padideh; Salmani, Fatemeh
Background: Factors that influence men’s childbearing intentions have been relatively unexplored in the literature. Objective: This study aimed to determine the influencing factors about the first childbearing timing decisions of men. Materials and Methods: In this cross-sectional study, 300 men who were referred to private and governmental healthcare centers in Shahrood, Iran were randomly recruited from April to September 2014. Data were collected using a demographic questionnaire, the Quality of Life Questionnaire; ENRICH Marital Satisfaction Questionnaire, Synder’s Hope Scale, and the Multidimensional Scale of Perceived Social Support. Results: After removing the statistically insignificant paths, men’s age at marriage had the highest direct effect (β=0.86) on their first childbearing decision. Marital satisfaction (β=-0.09), social support (β=0.06), economic status (β=0.06), and quality of life (β=-0.08) were other effective factors on men’s first childbearing decisions. Moreover, marital satisfaction and social support had significant indirect effects on men’s childbearing decisions (β=-0.04 and -0.01, respectively). Conclusion: Many factors, including personal factors (age at marriage and quality of life), family factors (marital satisfaction), and social factors (social support), can affect men’s decision to have a child. Policymakers are hence required to develop strategies to promote the socioeconomic and family conditions of the couples and to encourage them to have as many children as they desire at an appropriate time. PMID:27738661
Havard, J D
The purpose of this lecture is to review the justification for legal interference in physicians' clinical decisions and the consequences of that interference to patients. Discussion covers contraception, abortion, negligence, and defensive medicine. Contraception is normally interpreted as the prevention or inhibition of fertilization or of implantation of the fertilized ovum in the uterus. The extra corporeal or in vitro fertilization program has raised the question of the legal and ethical status of the fertilized ovum before implantation. This is turn has raised questions about contraceptive devices or procedures whose purpose it is to prevent the implantation of a fertilized ovum, of which the IUd is the most common in use in the UK. Congressman Doonan of California moved to amend the US Constitution to provide that "life begins when a sperm cell fertilizes an egg." It may be assumed that this amendment is designed to prevent unacceptable experiments on spare embryos, but the consequences to family planning could be enormous unless some exception is included in favor of IUDs inserted for purposes of contraception. This leads to the issue of abortion and a reminder that until the 19th century it was not regarded as a crime in English common law to abort a fetus before "quickening" had occurred, as this was the point at which the embryo was regarded as having been animated. The Offenses Against the Person Act of 1861 established the current criminal offense of induced abortion to which the Abortion Act of 1967 now provides a defense. Recent developments in life support mechanisms have created difficulties over the extent to which such measures should be employed in the management of children born with life threatening abnormalities. A draft bill has been introduced requiring doctors to take all possible steps to feed defective neonates with life threatening abnormalities who are experiencing serious feeding problems. This means that these infants would have to be
Kawamoto, Kensaku; Lobach, David F.
To facilitate the provision of clinical decision support (CDS), the Unified Medical Language System (UMLS) was leveraged to implement a terminology Web service. Supported functions include inter-vocabulary translation and the identification of concepts subsumed by a parent concept. Currently, the service is being used to aid the specification of clinical concepts within CDS knowledge modules. Insights gained from this process are discussed, including the limitations of using the UMLS to fulfill CDS terminology needs. PMID:17238598
Çamlar, Seçil Arslansoyu; Deveci, Nazlı; Soylu, Alper; Türkmen, Mehmet Atilla; Özmen, Derya; Çapakaya, Gamze; Kavukçu, Salih
Hydronephrosis may be related to an obstructive cause, ureteropelvic/uretero-vesical junction obstruction or nonobstructive [vesicoureteral reflux (VUR)]. When an obstructive pathology is considered, dynamic renal scintigraphy may help to predict whether it is a true obstruction or not. In this study, we aimed to determine the contribution of dynamic renal scintigraphy with  mTc-MAG-3 to the clinical decision-making for surgery in hydronephrotic children. Files of the patients evaluated by MAG-3 scintigraphy for antenatal (AH)/postnatal (PH) hydronephrosis between 1992 and 2014 were reviewed. Gender, age, hydronephrosis (HN) grade by ultrasound (US), presence of VUR, MAG-3 result (obstructive vs. nonobstructive), ultimate diagnosis, and need for surgery were assessed. Cases with double collecting system and neurogenic bladder were excluded from the study. All of the patients had normal serum creatinine and eGFR. There were a total of 178 patients with 218 hydronephrotic renal units (mean age 34.7 ± 52.7 months; male/ female = 121/57, AH of 62%). MAG-3 was nonobstructive in 134 and obstructive in 84 hydronephrotic renal units. MAG-3 was obstructive in 47 of 121 (39%) males and 30 of 57 (53%) females (P = 0.058, odds ratio (OR) for obstruction was 1.9 for girls). MAG-3 was obstructive in 47 of 135 (35%) units with AH and 37 of 83 (45%) units with PH (P = 0.137). In 81 units with the society of fetal urology-4 HN by US, MAG-3 was obstructive in 55 (68%), and surgery was required in 52 of 55 (95%). Surgery was required for only two (7%) of the remaining 26 units with nonobstructive dilatation (P <0.001, sensitivity 96%, specificity 89%, OR 208). Antero-posterior diameter >16.5 mm was the best cutoff level for predicting obstruction by MAG-3 (sensitivity 75.2%; specificity 71%; OR 3.8). MAG-3 significantly affects clinical decision for surgery in HN. Hydronephrotic girls have more risk in terms of true obstruction. Combining MAG-3 with US improves the
Klann, Jeffrey G.
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…
Blount, Kamilah V.
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…
Santos, Adriano A; Moura, J Antão B; de Araújo, Joseana Macêdo Fechine Régis
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.
Berlin, Jonathan W; Lexa, Frank J
This article presents a financial model to analyze the buy-vs-lease decision. The model is constructed from the perspective of a lessee with an operating lease and uses the concept of net present value, which calculates the current value of predicted cash flows in the future. Predicted cash flows of an operating lease compared with buying are presented in the model, as is the after-tax borrowing rate, the appropriate discount rate used in a model of this type. The article also discusses nonfinancial factors that may influence the buy-vs-lease decision, including the need for flexibility in working capital and the anticipated technological obsolescence of equipment.
Miller, R E; Golaszewski, T J
Health newsletters are an important component of worksite wellness, and human resource program managers believe these publications motivate employees and promote health services. Research has identified employee segments more likely to read health newsletters as well as how these publications may contribute to better medical self-care decision making. Even so, virtually no data exist on the factors contributing to newsletter selection and purchase except proprietary, anecdotal information collected by commercial vendors. Therefore, the purpose of this research was to investigate how newsletter features are rated by decision makers and determine factors predicting intent to purchase a health newsletter.
Welch, Brandon M.; Kawamoto, Kensaku
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