Gathering Real World Evidence with Cluster Analysis for Clinical Decision Support.
Xia, Eryu; Liu, Haifeng; Li, Jing; Mei, Jing; Li, Xuejun; Xu, Enliang; Li, Xiang; Hu, Gang; Xie, Guotong; Xu, Meilin
2017-01-01
Clinical decision support systems are information technology systems that assist clinical decision-making tasks, which have been shown to enhance clinical performance. Cluster analysis, which groups similar patients together, aims to separate patient cases into phenotypically heterogenous groups and defining therapeutically homogeneous patient subclasses. Useful as it is, the application of cluster analysis in clinical decision support systems is less reported. Here, we describe the usage of cluster analysis in clinical decision support systems, by first dividing patient cases into similar groups and then providing diagnosis or treatment suggestions based on the group profiles. This integration provides data for clinical decisions and compiles a wide range of clinical practices to inform the performance of individual clinicians. We also include an example usage of the system under the scenario of blood lipid management in type 2 diabetes. These efforts represent a step toward promoting patient-centered care and enabling precision medicine.
Gillespie, Mary
2010-11-01
Nurses' clinical decision-making is a complex process that holds potential to influence the quality of care provided and patient outcomes. The evolution of nurses' decision-making that occurs with experience has been well documented. In addition, literature includes numerous strategies and approaches purported to support development of nurses' clinical decision-making. There has been, however, significantly less attention given to the process of assessing nurses' clinical decision-making and novice clinical educators are often challenged with knowing how to best support nurses and nursing students in developing their clinical decision-making capacity. The Situated Clinical Decision-Making framework is presented for use by clinical educators: it provides a structured approach to analyzing nursing students' and novice nurses' decision-making in clinical nursing practice, assists educators in identifying specific issues within nurses' clinical decision-making, and guides selection of relevant strategies to support development of clinical decision-making. A series of questions is offered as a guide for clinical educators when assessing nurses' clinical decision-making. The discussion presents key considerations related to analysis of various decision-making components, including common sources of challenge and errors that may occur within nurses' clinical decision-making. An exemplar illustrates use of the framework and guiding questions. Implications of this approach for selection of strategies that support development of clinical decision-making are highlighted. Copyright © 2010 Elsevier Ltd. All rights reserved.
Decision analysis in clinical cardiology: When is coronary angiography required in aortic stenosis
DOE Office of Scientific and Technical Information (OSTI.GOV)
Georgeson, S.; Meyer, K.B.; Pauker, S.G.
1990-03-15
Decision analysis offers a reproducible, explicit approach to complex clinical decisions. It consists of developing a model, typically a decision tree, that separates choices from chances and that specifies and assigns relative values to outcomes. Sensitivity analysis allows exploration of alternative assumptions. Cost-effectiveness analysis shows the relation between dollars spent and improved health outcomes achieved. In a tutorial format, this approach is applied to the decision whether to perform coronary angiography in a patient who requires aortic valve replacement for critical aortic stenosis.
Accuracy of intuition in clinical decision-making among novice clinicians.
Price, Amanda; Zulkosky, Kristen; White, Krista; Pretz, Jean
2017-05-01
To assess the reliance on intuitive and analytical approaches during clinical decision-making among novice clinicians and whether that reliance is associated with accurate decision-making. Nurse educators and managers tend to emphasize analysis over intuition during clinical decision-making though nurses typically report some reliance on intuition in their practice. We hypothesized that under certain conditions, reliance on intuition would support accurate decision-making, even among novices. This study utilized an experimental design with clinical complication (familiar vs. novel) and decision phase (cue acquisition, diagnosis and action) as within-subjects' factors, and simulation role (observer, family, auxiliary nurse and primary nurse) as between-subjects' factor. We examined clinical decision-making accuracy among final semester pre-licensure nursing students in a simulation experience. Students recorded their reasoning about emerging clinical complications with their patient during two distinct points in the simulation; one point involved a familiar complication and the other a relatively novel complication. All data were collected during Spring 2015. Although most participants relied more heavily on analysis than on intuition, use of intuition during the familiar complication was associated with more accurate decision-making, particularly in guiding attention to relevant cues. With the novel complication, use of intuition appeared to hamper decision-making, particularly for those in an observer role. Novice clinicians should be supported by educators and nurse managers to note when their intuitions are likely to be valid. Our findings emphasize the integrated nature of intuition and analysis in clinical decision-making. © 2016 John Wiley & Sons Ltd.
Wolf, Lisa
2013-02-01
To explore the relationship between multiple variables within a model of critical thinking and moral reasoning. A quantitative descriptive correlational design using a purposive sample of 200 emergency nurses. Measured variables were accuracy in clinical decision-making, moral reasoning, perceived care environment, and demographics. Analysis was by bivariate correlation using Pearson's product-moment correlation coefficients, chi square and multiple linear regression analysis. The elements as identified in the integrated ethically-driven environmental model of clinical decision-making (IEDEM-CD) corrected depict moral reasoning and environment of care as factors significantly affecting accuracy in decision-making. The integrated, ethically driven environmental model of clinical decision making is a framework useful for predicting clinical decision making accuracy for emergency nurses in practice, with further implications in education, research and policy. A diagnostic and therapeutic framework for identifying and remediating individual and environmental challenges to accurate clinical decision making. © 2012, The Author. International Journal of Nursing Knowledge © 2012, NANDA International.
Midwives׳ clinical reasoning during second stage labour: Report on an interpretive study.
Jefford, Elaine; Fahy, Kathleen
2015-05-01
clinical reasoning was once thought to be the exclusive domain of medicine - setting it apart from 'non-scientific' occupations like midwifery. Poor assessment, clinical reasoning and decision-making skills are well known contributors to adverse outcomes in maternity care. Midwifery decision-making models share a common deficit: they are insufficiently detailed to guide reasoning processes for midwives in practice. For these reasons we wanted to explore if midwives actively engaged in clinical reasoning processes within their clinical practice and if so to what extent. The study was conducted using post structural, feminist methodology. to what extent do midwives engage in clinical reasoning processes when making decisions in the second stage labour? twenty-six practising midwives were interviewed. Feminist interpretive analysis was conducted by two researchers guided by the steps of a model of clinical reasoning process. Six narratives were excluded from analysis because they did not sufficiently address the research question. The midwives narratives were prepared via data reduction. A theoretically informed analysis and interpretation was conducted. using a feminist, interpretive approach we created a model of midwifery clinical reasoning grounded in the literature and consistent with the data. Thirteen of the 20 participant narratives demonstrate analytical clinical reasoning abilities but only nine completed the process and implemented the decision. Seven midwives used non-analytical decision-making without adequately checking against assessment data. over half of the participants demonstrated the ability to use clinical reasoning skills. Less than half of the midwives demonstrated clinical reasoning as their way of making decisions. The new model of Midwifery Clinical Reasoning includes 'intuition' as a valued way of knowing. Using intuition, however, should not replace clinical reasoning which promotes through decision-making can be made transparent and be consensually validated. Copyright © 2015 Elsevier Ltd. All rights reserved.
User-centered design to improve clinical decision support in primary care.
Brunner, Julian; Chuang, Emmeline; Goldzweig, Caroline; Cain, Cindy L; Sugar, Catherine; Yano, Elizabeth M
2017-08-01
A growing literature has demonstrated the ability of user-centered design to make clinical decision support systems more effective and easier to use. However, studies of user-centered design have rarely examined more than a handful of sites at a time, and have frequently neglected the implementation climate and organizational resources that influence clinical decision support. The inclusion of such factors was identified by a systematic review as "the most important improvement that can be made in health IT evaluations." (1) Identify the prevalence of four user-centered design practices at United States Veterans Affairs (VA) primary care clinics and assess the perceived utility of clinical decision support at those clinics; (2) Evaluate the association between those user-centered design practices and the perceived utility of clinical decision support. We analyzed clinic-level survey data collected in 2006-2007 from 170 VA primary care clinics. We examined four user-centered design practices: 1) pilot testing, 2) provider satisfaction assessment, 3) formal usability assessment, and 4) analysis of impact on performance improvement. We used a regression model to evaluate the association between user-centered design practices and the perceived utility of clinical decision support, while accounting for other important factors at those clinics, including implementation climate, available resources, and structural characteristics. We also examined associations separately at community-based clinics and at hospital-based clinics. User-centered design practices for clinical decision support varied across clinics: 74% conducted pilot testing, 62% conducted provider satisfaction assessment, 36% conducted a formal usability assessment, and 79% conducted an analysis of impact on performance improvement. Overall perceived utility of clinical decision support was high, with a mean rating of 4.17 (±.67) out of 5 on a composite measure. "Analysis of impact on performance improvement" was the only user-centered design practice significantly associated with perceived utility of clinical decision support, b=.47 (p<.001). This association was present in hospital-based clinics, b=.34 (p<.05), but was stronger at community-based clinics, b=.61 (p<.001). Our findings are highly supportive of the practice of analyzing the impact of clinical decision support on performance metrics. This was the most common user-centered design practice in our study, and was the practice associated with higher perceived utility of clinical decision support. This practice may be particularly helpful at community-based clinics, which are typically less connected to VA medical center resources. Published by Elsevier B.V.
Legal Considerations in Clinical Decision Making.
ERIC Educational Resources Information Center
Ursu, Samuel C.
1992-01-01
Discussion of legal issues in dental clinical decision making looks at the nature and elements of applicable law, especially malpractice, locus of responsibility, and standards of care. Greater use of formal decision analysis in clinical dentistry and better research on diagnosis and treatment are recommended, particularly in light of increasing…
Dowie, J.
2001-01-01
Most references to "leadership" and "learning" as sources of quality improvement in medical care reflect an implicit commitment to the decision technology of "clinical judgement". All attempts to sustain this waning decision technology by clinical guidelines, care pathways, "evidence based practice", problem based curricula, and other stratagems only increase the gap between what is expected of doctors in today's clinical situation and what is humanly possible, hence the morale, stress, and health problems they are increasingly experiencing. Clinical guidance programmes based on decision analysis represent the coming decision technology, and proactive adaptation will produce independent doctors who can deliver excellent evidence based and preference driven care while concentrating on the human aspects of the therapeutic relation, having been relieved of the unbearable burdens of knowledge and information processing currently laid on them. History is full of examples of the incumbents of dominant technologies preferring to die than to adapt, and medicine needs both learning and leadership if it is to avoid repeating this mistake. Key Words: decision technology; clinical guidance programmes; decision analysis PMID:11700381
Pulleyblank, Ryan; Chuma, Jefter; Gilbody, Simon M; Thompson, Carl
2013-09-01
For a test to be considered useful for making treatment decisions, it is necessary that making treatment decisions based on the results of the test be a preferable strategy to making treatment decisions without the test. Decision curve analysis is a framework for assessing when a test would be expected to be useful, which integrates evidence of a test's performance characteristics (sensitivity and specificity), condition prevalence among at-risk patients, and patient preferences for treatment. We describe decision curve analysis generally and illustrate its potential through an application to tests for prodromal psychosis. Clinical psychosis is often preceded by a prodromal phase, but not all those with prodromal symptoms proceed to develop full psychosis. Patients identified as at risk for developing psychosis may be considered for proactive treatment to mitigate development of clinically defined psychosis. Tests exist to help identify those at-risk patients most likely to develop psychosis, but it is uncertain when these tests would be considered useful for making proactive treatment decisions. We apply decision curve analysis to results from a systematic review of studies investigating clinical tests for predicting the development of psychosis in at-risk populations, and present resulting decision curves that illustrate when the tests may be expected to be useful for making proactive treatment decisions.
Huang, Vivian W; Prosser, Connie; Kroeker, Karen I; Wang, Haili; Shalapay, Carol; Dhami, Neil; Fedorak, Darryl K; Halloran, Brendan; Dieleman, Levinus A; Goodman, Karen J; Fedorak, Richard N
2015-06-01
Infliximab is an effective therapy for inflammatory bowel disease (IBD). However, more than 50% of patients lose response. Empiric dose intensification is not effective for all patients because not all patients have objective disease activity or subtherapeutic drug level. The aim was to determine how an objective marker of disease activity or therapeutic drug monitoring affects clinical decisions regarding maintenance infliximab therapy in outpatients with IBD. Consecutive patients with IBD on maintenance infliximab therapy were invited to participate by providing preinfusion stool and blood samples. Fecal calprotectin (FCP) and infliximab trough levels (ITLs) were measured by enzyme linked immunosorbent assay. Three decisions were compared: (1) actual clinical decision, (2) algorithmic FCP or ITL decisions, and (3) expert panel decision based on (a) clinical data, (b) clinical data plus FCP, and (c) clinical data plus FCP plus ITL. In secondary analysis, Receiver-operating curves were used to assess the ability of FCP and ITL in predicting clinical disease activity or remission. A total of 36 sets of blood and stool were available for analysis; median FCP 191.5 μg/g, median ITLs 7.3 μg/mL. The actual clinical decision differed from the hypothetical decision in 47.2% (FCP algorithm); 69.4% (ITL algorithm); 25.0% (expert panel clinical decision); 44.4% (expert panel clinical plus FCP); 58.3% (expert panel clinical plus FCP plus ITL) cases. FCP predicted clinical relapse (area under the curve [AUC] = 0.417; 95% confidence interval [CI], 0.197-0.641) and subtherapeutic ITL (AUC = 0.774; 95% CI, 0.536-1.000). ITL predicted clinical remission (AUC = 0.498; 95% CI, 0.254-0.742) and objective remission (AUC = 0.773; 95% CI, 0.622-0.924). Using FCP and ITLs in addition to clinical data results in an increased number of decisions to optimize management in outpatients with IBD on stable maintenance infliximab therapy.
Decision Analysis: Engineering Science or Clinical Art
1979-11-01
TECHNICAL REPORT TR 79-2-97 DECISION ANALYSIS: ENGINEERING SCIENCE OR CLINICAL ART ? by Dennis M. Buede Prepared for Defense Advanced Research...APPLICATIONS OF THE ENGINEER- ING SCIENCE AND CLINICAL ART EXTREMES 9 3.1 Applications of the Engineering Science Approach 9 3.1.1 Mexican electrical...DISCUSSION 29 4.1 Engineering Science versus Clinical Art : A Characterization of When Each is Most Attractive 30 4.2 The Implications of the Engineering
2012-01-01
Clinical decision rules are an increasingly common presence in the biomedical literature and represent one strategy of enhancing clinical-decision making with the goal of improving the efficiency and effectiveness of healthcare delivery. In the context of rehabilitation research, clinical decision rules have been predominantly aimed at classifying patients by predicting their treatment response to specific therapies. Traditionally, recommendations for developing clinical decision rules propose a multistep process (derivation, validation, impact analysis) using defined methodology. Research efforts aimed at developing a “diagnosis-based clinical decision rule” have departed from this convention. Recent publications in this line of research have used the modified terminology “diagnosis-based clinical decision guide.” Modifications to terminology and methodology surrounding clinical decision rules can make it more difficult for clinicians to recognize the level of evidence associated with a decision rule and understand how this evidence should be implemented to inform patient care. We provide a brief overview of clinical decision rule development in the context of the rehabilitation literature and two specific papers recently published in Chiropractic and Manual Therapies. PMID:22726639
Wright, Adam; Sittig, Dean F; Ash, Joan S; Erickson, Jessica L; Hickman, Trang T; Paterno, Marilyn; Gebhardt, Eric; McMullen, Carmit; Tsurikova, Ruslana; Dixon, Brian E; Fraser, Greg; Simonaitis, Linas; Sonnenberg, Frank A; Middleton, Blackford
2015-11-01
To identify challenges, lessons learned and best practices for service-oriented clinical decision support, based on the results of the Clinical Decision Support Consortium, a multi-site study which developed, implemented and evaluated clinical decision support services in a diverse range of electronic health records. Ethnographic investigation using the rapid assessment process, a procedure for agile qualitative data collection and analysis, including clinical observation, system demonstrations and analysis and 91 interviews. We identified challenges and lessons learned in eight dimensions: (1) hardware and software computing infrastructure, (2) clinical content, (3) human-computer interface, (4) people, (5) workflow and communication, (6) internal organizational policies, procedures, environment and culture, (7) external rules, regulations, and pressures and (8) system measurement and monitoring. Key challenges included performance issues (particularly related to data retrieval), differences in terminologies used across sites, workflow variability and the need for a legal framework. Based on the challenges and lessons learned, we identified eight best practices for developers and implementers of service-oriented clinical decision support: (1) optimize performance, or make asynchronous calls, (2) be liberal in what you accept (particularly for terminology), (3) foster clinical transparency, (4) develop a legal framework, (5) support a flexible front-end, (6) dedicate human resources, (7) support peer-to-peer communication, (8) improve standards. The Clinical Decision Support Consortium successfully developed a clinical decision support service and implemented it in four different electronic health records and four diverse clinical sites; however, the process was arduous. The lessons identified by the Consortium may be useful for other developers and implementers of clinical decision support services. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Kriston, Levente; Meister, Ramona
2014-03-01
Judging applicability (relevance) of meta-analytical findings to particular clinical decision-making situations remains challenging. We aimed to describe an evidence synthesis method that accounts for possible uncertainty regarding applicability of the evidence. We conceptualized uncertainty regarding applicability of the meta-analytical estimates to a decision-making situation as the result of uncertainty regarding applicability of the findings of the trials that were included in the meta-analysis. This trial-level applicability uncertainty can be directly assessed by the decision maker and allows for the definition of trial inclusion probabilities, which can be used to perform a probabilistic meta-analysis with unequal probability resampling of trials (adaptive meta-analysis). A case study with several fictitious decision-making scenarios was performed to demonstrate the method in practice. We present options to elicit trial inclusion probabilities and perform the calculations. The result of an adaptive meta-analysis is a frequency distribution of the estimated parameters from traditional meta-analysis that provides individually tailored information according to the specific needs and uncertainty of the decision maker. The proposed method offers a direct and formalized combination of research evidence with individual clinical expertise and may aid clinicians in specific decision-making situations. Copyright © 2014 Elsevier Inc. All rights reserved.
Muirhead, William
2012-04-01
Medical ethical analysis remains dominated by the principlist account first proposed by Beauchamp and Childress. This paper argues that the principlist model is unreflective of how ethical decisions are taken in clinical practice. Two kinds of medical ethical decisions are distinguished: biosocial ethics and clinical ethics. It is argued that principlism is an inappropriate model for clinical ethics as it is neither sufficiently action-guiding nor does it emphasise the professional integrity of the clinician. An alternative model is proposed for decision making in the realm of clinical ethics.
Clinical decision regret among critical care nurses: a qualitative analysis.
Arslanian-Engoren, Cynthia; Scott, Linda D
2014-01-01
Decision regret is a negative cognitive emotion associated with experiences of guilt and situations of interpersonal harm. These negative affective responses may contribute to emotional exhaustion in critical care nurses (CCNs), increased staff turnover rates and high medication error rates. Yet, little is known about clinical decision regret among CCNs or the conditions or situations (e.g., feeling sleepy) that may precipitate its occurrence. To examine decision regret among CCNs, with an emphasis on clinical decisions made when nurses were most sleepy. A content analytic approach was used to examine the narrative descriptions of clinical decisions by CCNs when sleepy. Six decision regret themes emerged that represented deviations in practice or performance behaviors that were attributed to fatigued CCNs. While 157 CCNs disclosed a clinical decision they made at work while sleepy, the prevalence may be underestimated and warrants further investigation. Copyright © 2014 Elsevier Inc. All rights reserved.
ERIC Educational Resources Information Center
Toriello, Paul J.; Leierer, Stephen J.
2005-01-01
In this study, the authors examined the relationship between the clinical orientations of substance abuse professionals (SAPs) and their clinical decisions. Cluster analysis grouped a sample of 245 SAPs on two clinical orientations that differed in their relative endorsement of traditional versus contemporary substance abuse counseling processes…
Ofstad, Eirik H; Frich, Jan C; Schei, Edvin; Frankel, Richard M; Gulbrandsen, Pål
2014-11-01
To identify and characterize physicians' statements that contained evidence of clinically relevant decisions in encounters with patients in different hospital settings. Qualitative analysis of 50 videotaped encounters from wards, the emergency room (ER) and outpatient clinics in a department of internal medicine at a Norwegian university hospital. Clinical decisions could be grouped in a temporal order: decisions which had already been made, and were brought into the encounter by the physician (preformed decisions), decisions made in the present (here-and-now decisions), and decisions prescribing future actions given a certain course of events (conditional decisions). Preformed decisions were a hallmark in the ward and conditional decisions a main feature of ER encounters. Clinical decisions related to a patient-physician encounter spanned a time frame exceeding the duration of the encounter. While a distribution of decisions over time and space fosters sharing and dilution of responsibility between providers, it makes the decision making process hard to access for patients. In order to plan when and how to involve patients in decisions, physicians need increased awareness of when clinical decisions are made, who usually makes them, and who should make them. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.
Hutchinson, Marie; Hurley, John; Kozlowski, Desirée; Whitehair, Leeann
2018-02-01
To explore clinical nurses' experiences of using emotional intelligence capabilities during clinical reasoning and decision-making. There has been little research exploring whether, or how, nurses employ emotional intelligence (EI) in clinical reasoning and decision-making. Qualitative phase of a larger mixed-methods study. Semistructured qualitative interviews with a purposive sample of registered nurses (n = 12) following EI training and coaching. Constructivist thematic analysis was employed to analyse the narrative transcripts. Three themes emerged: the sensibility to engage EI capabilities in clinical contexts, motivation to actively engage with emotions in clinical decision-making and incorporating emotional and technical perspectives in decision-making. Continuing to separate cognition and emotion in research, theorising and scholarship on clinical reasoning is counterproductive. Understanding more about nurses' use of EI has the potential to improve the calibre of decisions, and the safety and quality of care delivered. © 2017 John Wiley & Sons Ltd.
[Clinical reasoning in nursing, concept analysis].
Côté, Sarah; St-Cyr Tribble, Denise
2012-12-01
Nurses work in situations of complex care requiring great clinical reasoning abilities. In literature, clinical reasoning is often confused with other concepts and it has no consensual definition. To conduct a concept analysis of a nurse's clinical reasoning in order to clarify, define and distinguish it from the other concepts as well as to better understand clinical reasoning. Rodgers's method of concept analysis was used, after literature was retrieved with the use of clinical reasoning, concept analysis, nurse, intensive care and decision making as key-words. The use of cognition, cognitive strategies, a systematic approach of analysis and data interpretation, generating hypothesis and alternatives are attributes of clinical reasoning. The antecedents are experience, knowledge, memory, cues, intuition and data collection. The consequences are decision making, action, clues and problem resolution. This concept analysis helped to define clinical reasoning, to distinguish it from other concepts used synonymously and to guide future research.
A Benefit-Risk Analysis Approach to Capture Regulatory Decision-Making: Multiple Myeloma.
Raju, G K; Gurumurthi, Karthik; Domike, Reuben; Kazandjian, Dickran; Landgren, Ola; Blumenthal, Gideon M; Farrell, Ann; Pazdur, Richard; Woodcock, Janet
2018-01-01
Drug regulators around the world make decisions about drug approvability based on qualitative benefit-risk analysis. In this work, a quantitative benefit-risk analysis approach captures regulatory decision-making about new drugs to treat multiple myeloma (MM). MM assessments have been based on endpoints such as time to progression (TTP), progression-free survival (PFS), and objective response rate (ORR) which are different than benefit-risk analysis based on overall survival (OS). Twenty-three FDA decisions on MM drugs submitted to FDA between 2003 and 2016 were identified and analyzed. The benefits and risks were quantified relative to comparators (typically the control arm of the clinical trial) to estimate whether the median benefit-risk was positive or negative. A sensitivity analysis was demonstrated using ixazomib to explore the magnitude of uncertainty. FDA approval decision outcomes were consistent and logical using this benefit-risk framework. © 2017 American Society for Clinical Pharmacology and Therapeutics.
Palese, Alvisa; Cassone, Andrea; Kulla, Annamaria; Dorigo, Sabrina; Magee, Jesse; Artico, Marco; Camero, Francesco; Cassin, Catia; Cialdella, Sandra; Floridia, Giuseppe; Nadlišek, Boris; Palcic, Annamaria; Valle, Giulia; Sclauzero, Paola
2011-01-01
The clinical and research debate on the peripheral intravascular (PIV) catheter length of stay in situ is ongoing. The principal aim of this study was to explore the factors behind a nurse's decision to leave a PIV in place for more than 96 hours. The study focused on 7 northern Italian hospitals in 2009. A consequent sample of 269 PIV catheters was included. Direct observation and interviews were adopted. The time of the expected PIV replacement was fixed at 96 hours after its positioning, in accordance with the international guideline. Several factors were taken into account in regard to replacement of the PIV catheters by nurses, ranging from analysis based on their own clinical experience with PIV complications and analysis of the patient's clinical situation to the critical analysis of their own work situation. This clinical decision-making process is valuable: leaving the PIV in place for more than 96 hours is a complex decision and not simply a guideline violation.
Wyatt, Kirk D; Branda, Megan E; Inselman, Jonathan W; Ting, Henry H; Hess, Erik P; Montori, Victor M; LeBlanc, Annie
2014-09-02
Gender differences in communication styles between clinicians and patients have been postulated to impact patient care, but the extent to which the gender dyad structure impacts outcomes in shared decision making remains unclear. Participant-level meta-analysis of 775 clinical encounters within 7 randomized trials where decision aids, shared decision making tools, were used at the point of care. Outcomes analysed include decisional conflict scale scores, satisfaction with the clinical encounter, concordance between stated decision and action taken, and degree of patient engagement by the clinician using the OPTION scale. An estimated minimal important difference was used to determine if nonsignificant results could be explained by low power. We did not find a statistically significant interaction between clinician/patient gender mix and arm for decisional conflict, satisfaction with the clinical encounter or patient engagement. A borderline significant interaction (p = 0.05) was observed for one outcome: concordance between stated decision and action taken, where encounters with female clinician/male patient showed increased concordance in the decision aid arm compared to control (8% more concordant encounters). All other gender dyads showed decreased concordance with decision aid use (6% fewer concordant encounters for same-gender, 16% fewer concordant encounters for male clinician/female patient). In this participant-level meta-analysis of 7 randomized trials, decision aids used at the point of care demonstrated comparable efficacy across gender dyads. Purported barriers to shared decision making based on gender were not detected when tested for a minimum detected difference. ClinicalTrials.gov NCT00888537, NCT01077037, NCT01029288, NCT00388050, NCT00578981, NCT00949611, NCT00217061.
A problem solving and decision making toolbox for approaching clinical problems and decisions.
Margolis, C; Jotkowitz, A; Sitter, H
2004-08-01
In this paper, we begin by presenting three real patients and then review all the practical conceptual tools that have been suggested for systematically analyzing clinical problems. Each of these conceptual tools (e.g. Evidence-Based Medicine, Clinical Practice Guidelines, Decision Analysis) deals mainly with a different type or aspect of clinical problems. We suggest that all of these conceptual tools can be thought of as belonging in the clinician's toolbox for solving clinical problems and making clinical decisions. A heuristic for guiding the clinician in using the tools is proposed. The heuristic is then used to analyze management of the three patients presented at the outset. Copyright 2004 Birkhäuser Verlag, Basel
Mixture-based gatekeeping procedures in adaptive clinical trials.
Kordzakhia, George; Dmitrienko, Alex; Ishida, Eiji
2018-01-01
Clinical trials with data-driven decision rules often pursue multiple clinical objectives such as the evaluation of several endpoints or several doses of an experimental treatment. These complex analysis strategies give rise to "multivariate" multiplicity problems with several components or sources of multiplicity. A general framework for defining gatekeeping procedures in clinical trials with adaptive multistage designs is proposed in this paper. The mixture method is applied to build a gatekeeping procedure at each stage and inferences at each decision point (interim or final analysis) are performed using the combination function approach. An advantage of utilizing the mixture method is that it enables powerful gatekeeping procedures applicable to a broad class of settings with complex logical relationships among the hypotheses of interest. Further, the combination function approach supports flexible data-driven decisions such as a decision to increase the sample size or remove a treatment arm. The paper concludes with a clinical trial example that illustrates the methodology by applying it to develop an adaptive two-stage design with a mixture-based gatekeeping procedure.
Barbieri, Christopher E; Cha, Eugene K; Chromecki, Thomas F; Dunning, Allison; Lotan, Yair; Svatek, Robert S; Scherr, Douglas S; Karakiewicz, Pierre I; Sun, Maxine; Mazumdar, Madhu; Shariat, Shahrokh F
2012-03-01
• To employ decision curve analysis to determine the impact of nuclear matrix protein 22 (NMP22) on clinical decision making in the detection of bladder cancer using data from a prospective trial. • The study included 1303 patients at risk for bladder cancer who underwent cystoscopy, urine cytology and measurement of urinary NMP22 levels. • We constructed several prediction models to estimate risk of bladder cancer. The base model was generated using patient characteristics (age, gender, race, smoking and haematuria); cytology and NMP22 were added to the base model to determine effects on predictive accuracy. • Clinical net benefit was calculated by summing the benefits and subtracting the harms and weighting these by the threshold probability at which a patient or clinician would opt for cystoscopy. • In all, 72 patients were found to have bladder cancer (5.5%). In univariate analyses, NMP22 was the strongest predictor of bladder cancer presence (predictive accuracy 71.3%), followed by age (67.5%) and cytology (64.3%). • In multivariable prediction models, NMP22 improved the predictive accuracy of the base model by 8.2% (area under the curve 70.2-78.4%) and of the base model plus cytology by 4.2% (area under the curve 75.9-80.1%). • Decision curve analysis revealed that adding NMP22 to other models increased clinical benefit, particularly at higher threshold probabilities. • NMP22 is a strong, independent predictor of bladder cancer. • Addition of NMP22 improves the accuracy of standard predictors by a statistically and clinically significant margin. • Decision curve analysis suggests that integration of NMP22 into clinical decision making helps avoid unnecessary cystoscopies, with minimal increased risk of missing a cancer. © 2011 THE AUTHORS. BJU INTERNATIONAL © 2011 BJU INTERNATIONAL.
Lo, Benjamin W Y; Fukuda, Hitoshi; Angle, Mark; Teitelbaum, Jeanne; Macdonald, R Loch; Farrokhyar, Forough; Thabane, Lehana; Levine, Mitchell A H
2016-01-01
Classification and regression tree analysis involves the creation of a decision tree by recursive partitioning of a dataset into more homogeneous subgroups. Thus far, there is scarce literature on using this technique to create clinical prediction tools for aneurysmal subarachnoid hemorrhage (SAH). The classification and regression tree analysis technique was applied to the multicenter Tirilazad database (3551 patients) in order to create the decision-making algorithm. In order to elucidate prognostic subgroups in aneurysmal SAH, neurologic, systemic, and demographic factors were taken into account. The dependent variable used for analysis was the dichotomized Glasgow Outcome Score at 3 months. Classification and regression tree analysis revealed seven prognostic subgroups. Neurological grade, occurrence of post-admission stroke, occurrence of post-admission fever, and age represented the explanatory nodes of this decision tree. Split sample validation revealed classification accuracy of 79% for the training dataset and 77% for the testing dataset. In addition, the occurrence of fever at 1-week post-aneurysmal SAH is associated with increased odds of post-admission stroke (odds ratio: 1.83, 95% confidence interval: 1.56-2.45, P < 0.01). A clinically useful classification tree was generated, which serves as a prediction tool to guide bedside prognostication and clinical treatment decision making. This prognostic decision-making algorithm also shed light on the complex interactions between a number of risk factors in determining outcome after aneurysmal SAH.
Leidl, R; Jacobi, E; Knab, J; Schweikert, B
2006-04-01
Economic assessment of an additional psychological intervention in the rehabilitation of patients with chronic low-back pain and evaluation of results by decision makers. Piggy-back cost-utility analysis of a randomised clinical trial, including a bootstrap analysis. Costs were measured by using the cost accounting systems of the rehabilitation clinics and by surveying patients. Health-related quality of life was measured using the EQ-5D. Implications of different representations of the decision problem and corresponding decision rules concerning the cost-effectiveness plane are discussed. As compared with the 126 patients of the control arm, the 98 patients in the intervention arm gained 3.5 days in perfect health on average as well as 1219 euro cost saving. However, because of the uncertainty involved, the results of a bootstrap analysis cover all quadrants of the cost-effectiveness plane. Using maximum willingness-to-pay per effect unit gained, decision rules can be defined for parts of the cost-effectiveness plane. These have to be aggregated in a further valuation step. Study results show that decisions on stochastic economic evaluation results may require an additional valuation step aggregating the various parts of the cost-effectiveness plane.
Factors influencing the clinical decision-making of midwives: a qualitative study.
Daemers, Darie O A; van Limbeek, Evelien B M; Wijnen, Hennie A A; Nieuwenhuijze, Marianne J; de Vries, Raymond G
2017-10-06
Although midwives make clinical decisions that have an impact on the health and well-being of mothers and babies, little is known about how they make those decisions. Wide variation in intrapartum decisions to refer women to obstetrician-led care suggests that midwives' decisions are based on more than the evidence based medicine (EBM) model - i.e. clinical evidence, midwife's expertise, and woman's values - alone. With this study we aimed to explore the factors that influence clinical decision-making of midwives who work independently. We used a qualitative approach, conducting in-depth interviews with a purposive sample of 11 Dutch primary care midwives. Data collection took place between May and September 2015. The interviews were semi-structured, using written vignettes to solicit midwives' clinical decision-making processes (Think Aloud method). We performed thematic analysis on the transcripts. We identified five themes that influenced clinical decision-making: the pregnant woman as a whole person, sources of knowledge, the midwife as a whole person, the collaboration between maternity care professionals, and the organisation of care. Regarding the midwife, her decisions were shaped not only by her experience, intuition, and personal circumstances, but also by her attitudes about physiology, woman-centredness, shared decision-making, and collaboration with other professionals. The nature of the local collaboration between maternity care professionals and locally-developed protocols dominated midwives' clinical decision-making. When midwives and obstetricians had different philosophies of care and different practice styles, their collaborative efforts were challenged. Midwives' clinical decision-making is a more varied and complex process than the EBM framework suggests. If midwives are to succeed in their role as promoters and protectors of physiological pregnancy and birth, they need to understand how clinical decisions in a multidisciplinary context are actually made.
Prescott, Jeffrey William
2013-02-01
The importance of medical imaging for clinical decision making has been steadily increasing over the last four decades. Recently, there has also been an emphasis on medical imaging for preclinical decision making, i.e., for use in pharamaceutical and medical device development. There is also a drive towards quantification of imaging findings by using quantitative imaging biomarkers, which can improve sensitivity, specificity, accuracy and reproducibility of imaged characteristics used for diagnostic and therapeutic decisions. An important component of the discovery, characterization, validation and application of quantitative imaging biomarkers is the extraction of information and meaning from images through image processing and subsequent analysis. However, many advanced image processing and analysis methods are not applied directly to questions of clinical interest, i.e., for diagnostic and therapeutic decision making, which is a consideration that should be closely linked to the development of such algorithms. This article is meant to address these concerns. First, quantitative imaging biomarkers are introduced by providing definitions and concepts. Then, potential applications of advanced image processing and analysis to areas of quantitative imaging biomarker research are described; specifically, research into osteoarthritis (OA), Alzheimer's disease (AD) and cancer is presented. Then, challenges in quantitative imaging biomarker research are discussed. Finally, a conceptual framework for integrating clinical and preclinical considerations into the development of quantitative imaging biomarkers and their computer-assisted methods of extraction is presented.
Thomson, Oliver P; Petty, Nicola J; Moore, Ann P
2014-02-01
There is limited understanding of how osteopaths make decisions in relation to clinical practice. The aim of this research was to construct an explanatory theory of the clinical decision-making and therapeutic approaches of experienced osteopaths in the UK. Twelve UK registered osteopaths participated in this constructivist grounded theory qualitative study. Purposive and theoretical sampling was used to select participants. Data was collected using semi-structured interviews which were audio-recorded and transcribed. As the study approached theoretical sufficiency, participants were observed and video-recorded during a patient appointment, which was followed by a video-prompted interview. Constant comparative analysis was used to analyse and code data. Data analysis resulted in the construction of three qualitatively different therapeutic approaches which characterised participants and their clinical practice, termed; Treater, Communicator and Educator. Participants' therapeutic approach influenced their approach to clinical decision-making, the level of patient involvement, their interaction with patients, and therapeutic goals. Participants' overall conception of practice lay on a continuum ranging from technical rationality to professional artistry, and contributed to their therapeutic approach. A range of factors were identified which influenced participants' conception of practice. The findings indicate that there is variation in osteopaths' therapeutic approaches to practice and clinical decision-making, which are influenced by their overall conception of practice. This study provides the first explanatory theory of the clinical decision-making and therapeutic approaches of osteopaths. Copyright © 2013 Elsevier Ltd. All rights reserved.
Kwon, Sun-Hong; Park, Sun-Kyeong; Byun, Ji-Hye; Lee, Eui-Kyung
2017-08-01
In order to look beyond the cost-effectiveness analysis, this study used a multi-criteria decision analysis (MCDA), which reflects societal values with regard to reimbursement decisions. This study aims to elicit societal preferences of the reimbursement decision criteria for anti cancer drugs from public and healthcare professionals. Eight criteria were defined based on a literature review and focus group sessions: disease severity, disease population size, pediatrics targets, unmet needs, innovation, clinical benefits, cost-effectiveness, and budget impacts. Using quota sampling and purposive sampling, 300 participants from the Korean public and 30 healthcare professionals were selected for the survey. Preferences were elicited using an analytic hierarchy process. Both groups rated clinical benefits the highest, followed by cost-effectiveness and disease severity, but differed with regard to disease population size and unmet needs. Innovation was the least preferred criteria. Clinical benefits and other social values should be reflected appropriately with cost-effectiveness in healthcare coverage. MCDA can be used to assess decision priorities for complicated health policy decisions, including reimbursement decisions. It is a promising method for making logical and transparent drug reimbursement decisions that consider a broad range of factors, which are perceived as important by relevant stakeholders.
Schaafsma, Joanna D; van der Graaf, Yolanda; Rinkel, Gabriel J E; Buskens, Erik
2009-12-01
The lack of a standard methodology in diagnostic research impedes adequate evaluation before implementation of constantly developing diagnostic techniques. We discuss the methodology of diagnostic research and underscore the relevance of decision analysis in the process of evaluation of diagnostic tests. Overview and conceptual discussion. Diagnostic research requires a stepwise approach comprising assessment of test characteristics followed by evaluation of added value, clinical outcome, and cost-effectiveness. These multiple goals are generally incompatible with a randomized design. Decision-analytic models provide an important alternative through integration of the best available evidence. Thus, critical assessment of clinical value and efficient use of resources can be achieved. Decision-analytic models should be considered part of the standard methodology in diagnostic research. They can serve as a valid alternative to diagnostic randomized clinical trials (RCTs).
Smith, Megan; Higgs, Joy; Ellis, Elizabeth
2010-02-01
This article investigates clinical decision making in acute care hospitals by cardiorespiratory physiotherapists with differing degrees of clinical experience. Participants were observed as they engaged in their everyday practice and were interviewed about their decision making. Texts of the data were interpreted by using a hermeneutic approach that involved repeated reading and analysis of fieldnotes and interview transcripts to develop an understanding of the effect of experience on clinical decision making. Participants were classified into categories of cardiorespiratory physiotherapy experience: less experienced (<2 years), intermediate experience (2.5-4 years), and more experienced (>7 years). Four dimensions characteristic of increasing experience in cardiorespiratory physiotherapy clinical decision making were identified: 1) an individual practice model, 2) refined approaches to clinical decision making, 3) working in context, and 4) social and emotional capability. Underpinning these dimensions was evidence of reflection on practice, motivation to achieve best practice, critique of new knowledge, increasing confidence, and relationships with knowledgeable colleagues. These findings reflect characteristics of physiotherapy expertise that have been described in the literature. This study adds knowledge about the field of cardiorespiratory physiotherapy to the existing body of research on clinical decision making and broadens the existing understanding of characteristics of physiotherapy expertise.
Decision-Making Phenomena Described by Expert Nurses Working in Urban Community Health Settings.
ERIC Educational Resources Information Center
Watkins, Mary P.
1998-01-01
Expert community health nurses (n=28) described crucial clinical situations. Content analysis revealed that decision making was both rational and intuitive. Eight themes were identified: decision-making focus, type, purpose, decision-maker characteristics, sequencing of events, data collection methods, facilitators/barriers, and decision-making…
Michelson, James D
2013-11-01
The development of a robust treatment algorithm for ankle fractures based on well-established stability criteria has been shown to be prognostic with respect to treatment and outcomes. In parallel with the development of improved understanding of the biomechanical rationale of ankle fracture treatment has been an increased emphasis on assessing the effectiveness of medical and surgical interventions. The purpose of this study was to investigate the use of using decision analysis in the assessment of the cost effectiveness of operative treatment of ankle fractures based on the existing clinical data in the literature. Using the data obtained from a previous structured review of the ankle fracture literature, decision analysis trees were constructed using standard software. The decision nodes for the trees were based on ankle fracture stability criteria previously published. The outcomes were assessed by calculated Quality-Adjusted Life Years (QALYs) assigned to achieving normal ankle function, developing posttraumatic arthritis, or sustaining a postoperative infection. Sensitivity analysis was undertaken by varying the patient's age, incidence of arthritis, and incidence or infection. Decision analysis trees captured the essential aspects of clinical decision making in ankle fracture treatment in a clinically useful manner. In general, stable fractures yielded better outcomes with nonoperative treatment, whereas unstable fractures had better outcomes with surgery. These were consistent results over a wide range of postoperative infection rates. Varying the age of the patient did not qualitatively change the results. Between the ages of 30 and 80 years, surgery yielded higher expected QALYs than nonoperative care for unstable fractures, and generated lower QALYs than nonoperative care for stable fractures. Using local cost estimates for operative and nonoperative treatment, the incremental cost of surgery for unstable fractures was less than $40,000 per QALY (the usual cutoff for the determination of cost effectiveness) for patients aged up to 90 years. Decision analysis is a useful methodology in developing treatment guidelines. Numerous previous studies have indicated superior clinical outcomes when unstable ankle fractures underwent operative reduction and stabilization. What has been lacking was an examination of the cost effectiveness of such an approach, particularly in older patients who have fewer expected years of life. In light of the evidence for satisfactory outcomes for surgery of severe ankle fractures in older people, the justification for operative intervention is an obvious question that can be asked in the current increasingly cost-conscious environment. Using a decision-tree decision analysis structured around the stability-based ankle fracture classification system, in conjunction with a relatively simple cost effectiveness analysis, this study was able to demonstrate that surgical treatment of unstable ankle fractures in elderly patients is in fact cost effective. The clinical implication of the present analysis is that these existing treatment protocols for ankle fracture treatment are also cost effective when quality of life outcome measures are taken into account. Economic Level II. See Instructions for Authors for a complete description of levels of evidence.
Decision making in asthma exacerbation: a clinical judgement analysis
Jenkins, John; Shields, Mike; Patterson, Chris; Kee, Frank
2007-01-01
Background Clinical decisions which impact directly on patient safety and quality of care are made during acute asthma attacks by individual doctors based on their knowledge and experience. Decisions include administration of systemic corticosteroids (CS) and oral antibiotics, and admission to hospital. Clinical judgement analysis provides a methodology for comparing decisions between practitioners with different training and experience, and improving decision making. Methods Stepwise linear regression was used to select clinical cues based on visual analogue scale assessments of the propensity of 62 clinicians to prescribe a short course of oral CS (decision 1), a course of antibiotics (decision 2), and/or admit to hospital (decision 3) for 60 “paper” patients. Results When compared by specialty, paediatricians' models for decision 1 were more likely to include level of alertness as a cue (54% vs 16%); for decision 2 they were more likely to include presence of crepitations (49% vs 16%) and less likely to include inhaled CS (8% vs 40%), respiratory rate (0% vs 24%) and air entry (70% vs 100%). When compared to other grades, the models derived for decision 3 by consultants/general practitioners were more likely to include wheeze severity as a cue (39% vs 6%). Conclusions Clinicians differed in their use of individual cues and the number included in their models. Patient safety and quality of care will benefit from clarification of decision‐making strategies as general learning points during medical training, in the development of guidelines and care pathways, and by clinicians developing self‐awareness of their own preferences. PMID:17428817
Clinical decision-making among new graduate nurses attending residency programs in Saudi Arabia.
Al-Dossary, Reem Nassar; Kitsantas, Panagiota; Maddox, P J
2016-02-01
This study examined the impact of residency programs on clinical decision-making of new Saudi graduate nurses who completed a residency program compared to new Saudi graduate nurses who did not participate in residency programs. This descriptive study employed a convenience sample (N=98) of new graduate nurses from three hospitals in Saudi Arabia. A self-administered questionnaire was used to collect data. Clinical decision-making skills were measured using the Clinical Decision Making in Nursing Scale. Descriptive statistics, independent t-tests, and multiple linear regression analysis were utilized to examine the effect of residency programs on new graduate nurses' clinical decision-making skills. On average, resident nurses had significantly higher levels of clinical decision-making skills than non-residents (t=23.25, p=0.000). Enrollment in a residency program explained 86.9% of the variance in total clinical decision making controlling for age and overall grade point average. The findings of this study support evidence in the nursing literature conducted primarily in the US and Europe that residency programs have a positive influence on new graduate nurses' clinical decision-making skills. This is the first study to examine the impact of residency programs on clinical decision-making among new Saudi graduate nurses who completed a residency program. The findings of this study underscore the need for the development and implementation of residency programs for all new nurses. Copyright © 2015 Elsevier Inc. All rights reserved.
2014-01-01
Background Shared decision making represents a clinical consultation model where both clinician and service user are conceptualised as experts; information is shared bilaterally and joint treatment decisions are reached. Little previous research has been conducted to assess experience of this model in psychiatric practice. The current project therefore sought to explore the attitudes and experiences of consultant psychiatrists relating to shared decision making in the prescribing of antipsychotic medications. Methods A qualitative research design allowed the experiences and beliefs of participants in relation to shared decision making to be elicited. Purposive sampling was used to recruit participants from a range of clinical backgrounds and with varying length of clinical experience. A semi-structured interview schedule was utilised and was adapted in subsequent interviews to reflect emergent themes. Data analysis was completed in parallel with interviews in order to guide interview topics and to inform recruitment. A directed analysis method was utilised for interview analysis with themes identified being fitted to a framework identified from the research literature as applicable to the practice of shared decision making. Examples of themes contradictory to, or not adequately explained by, the framework were sought. Results A total of 26 consultant psychiatrists were interviewed. Participants expressed support for the shared decision making model, but also acknowledged that it was necessary to be flexible as the clinical situation dictated. A number of potential barriers to the process were perceived however: The commonest barrier was the clinician’s beliefs regarding the service users’ insight into their mental disorder, presented in some cases as an absolute barrier to shared decision making. In addition factors external to the clinician - service user relationship were identified as impacting on the decision making process, including; environmental factors, financial constraints as well as societal perceptions of mental disorder in general and antipsychotic medication in particular. Conclusions This project has allowed identification of potential barriers to shared decision making in psychiatric practice. Further work is necessary to observe the decision making process in clinical practice and also to identify means in which the identified barriers, in particular ‘lack of insight’, may be more effectively managed. PMID:24886121
Shepherd, Andrew; Shorthouse, Oliver; Gask, Linda
2014-05-01
Shared decision making represents a clinical consultation model where both clinician and service user are conceptualised as experts; information is shared bilaterally and joint treatment decisions are reached. Little previous research has been conducted to assess experience of this model in psychiatric practice. The current project therefore sought to explore the attitudes and experiences of consultant psychiatrists relating to shared decision making in the prescribing of antipsychotic medications. A qualitative research design allowed the experiences and beliefs of participants in relation to shared decision making to be elicited. Purposive sampling was used to recruit participants from a range of clinical backgrounds and with varying length of clinical experience. A semi-structured interview schedule was utilised and was adapted in subsequent interviews to reflect emergent themes.Data analysis was completed in parallel with interviews in order to guide interview topics and to inform recruitment. A directed analysis method was utilised for interview analysis with themes identified being fitted to a framework identified from the research literature as applicable to the practice of shared decision making. Examples of themes contradictory to, or not adequately explained by, the framework were sought. A total of 26 consultant psychiatrists were interviewed. Participants expressed support for the shared decision making model, but also acknowledged that it was necessary to be flexible as the clinical situation dictated. A number of potential barriers to the process were perceived however: The commonest barrier was the clinician's beliefs regarding the service users' insight into their mental disorder, presented in some cases as an absolute barrier to shared decision making. In addition factors external to the clinician - service user relationship were identified as impacting on the decision making process, including; environmental factors, financial constraints as well as societal perceptions of mental disorder in general and antipsychotic medication in particular. This project has allowed identification of potential barriers to shared decision making in psychiatric practice. Further work is necessary to observe the decision making process in clinical practice and also to identify means in which the identified barriers, in particular 'lack of insight', may be more effectively managed.
Decision curve analysis: a novel method for evaluating prediction models.
Vickers, Andrew J; Elkin, Elena B
2006-01-01
Diagnostic and prognostic models are typically evaluated with measures of accuracy that do not address clinical consequences. Decision-analytic techniques allow assessment of clinical outcomes but often require collection of additional information and may be cumbersome to apply to models that yield a continuous result. The authors sought a method for evaluating and comparing prediction models that incorporates clinical consequences,requires only the data set on which the models are tested,and can be applied to models that have either continuous or dichotomous results. The authors describe decision curve analysis, a simple, novel method of evaluating predictive models. They start by assuming that the threshold probability of a disease or event at which a patient would opt for treatment is informative of how the patient weighs the relative harms of a false-positive and a false-negative prediction. This theoretical relationship is then used to derive the net benefit of the model across different threshold probabilities. Plotting net benefit against threshold probability yields the "decision curve." The authors apply the method to models for the prediction of seminal vesicle invasion in prostate cancer patients. Decision curve analysis identified the range of threshold probabilities in which a model was of value, the magnitude of benefit, and which of several models was optimal. Decision curve analysis is a suitable method for evaluating alternative diagnostic and prognostic strategies that has advantages over other commonly used measures and techniques.
[Clinical reasoning in undergraduate nursing education: a scoping review].
Menezes, Sáskia Sampaio Cipriano de; Corrêa, Consuelo Garcia; Silva, Rita de Cássia Gengo E; Cruz, Diná de Almeida Monteiro Lopes da
2015-12-01
This study aimed at analyzing the current state of knowledge on clinical reasoning in undergraduate nursing education. A systematic scoping review through a search strategy applied to the MEDLINE database, and an analysis of the material recovered by extracting data done by two independent reviewers. The extracted data were analyzed and synthesized in a narrative manner. From the 1380 citations retrieved in the search, 23 were kept for review and their contents were summarized into five categories: 1) the experience of developing critical thinking/clinical reasoning/decision-making process; 2) teaching strategies related to the development of critical thinking/clinical reasoning/decision-making process; 3) measurement of variables related to the critical thinking/clinical reasoning/decision-making process; 4) relationship of variables involved in the critical thinking/clinical reasoning/decision-making process; and 5) theoretical development models of critical thinking/clinical reasoning/decision-making process for students. The biggest challenge for developing knowledge on teaching clinical reasoning seems to be finding consistency between theoretical perspectives on the development of clinical reasoning and methodologies, methods, and procedures in research initiatives in this field.
Cognitive continuum theory in interprofessional healthcare: A critical analysis.
Parker-Tomlin, Michelle; Boschen, Mark; Morrissey, Shirley; Glendon, Ian
2017-07-01
Effective clinical decision making is among the most important skills required by healthcare practitioners. Making sound decisions while working collaboratively in interprofessional healthcare teams is essential for modern healthcare planning, successful interventions, and patient care. The cognitive continuum theory (CCT) is a model of human judgement and decision making aimed at orienting decision-making processes. CCT has the potential to improve both individual health practitioner, and interprofessional team understanding about, and communication of, clinical decision-making processes. Examination of the current application of CCT indicates that this theory could strengthen interprofessional team clinical decision making (CDM). However, further research is needed before extending the use of this theoretical framework to a wider range of interprofessional healthcare team processes. Implications for research, education, practice, and policy are addressed.
Using Cluster Analysis to Examine Husband-Wife Decision Making
ERIC Educational Resources Information Center
Bonds-Raacke, Jennifer M.
2006-01-01
Cluster analysis has a rich history in many disciplines and although cluster analysis has been used in clinical psychology to identify types of disorders, its use in other areas of psychology has been less popular. The purpose of the current experiments was to use cluster analysis to investigate husband-wife decision making. Cluster analysis was…
NASA Astrophysics Data System (ADS)
Liu, Brent; Documet, Jorge; McNitt-Gray, Sarah; Requejo, Phil; McNitt-Gray, Jill
2011-03-01
Clinical decisions for improving motor function in patients both with disability as well as improving an athlete's performance are made through clinical and movement analysis. Currently, this analysis facilitates identifying abnormalities in a patient's motor function for a large amount of neuro-musculoskeletal pathologies. However definitively identifying the underlying cause or long-term consequences of a specific abnormality in the patient's movement pattern is difficult since this requires information from multiple sources and formats across different times and currently relies on the experience and intuition of the expert clinician. In addition, this data must be persistent for longitudinal outcomes studies. Therefore a multimedia ePR system integrating imaging informatics data could have a significant impact on decision support within this clinical workflow. We present the design and architecture of such an ePR system as well as the data types that need integration in order to develop relevant decision support tools. Specifically, we will present two data model examples: 1) A performance improvement project involving volleyball athletes and 2) Wheelchair propulsion evaluation of patients with disabilities. The end result is a new frontier area of imaging informatics research within rehabilitation engineering and biomechanics.
Hoomans, Ties; Severens, Johan L; Evers, Silvia M A A; Ament, Andre J H A
2009-01-01
Decisions about clinical practice change, that is, which guidelines to adopt and how to implement them, can be made sequentially or simultaneously. Decision makers adopting a sequential approach first compare the costs and effects of alternative guidelines to select the best set of guideline recommendations for patient management and subsequently examine the implementation costs and effects to choose the best strategy to implement the selected guideline. In an integral approach, decision makers simultaneously decide about the guideline and the implementation strategy on the basis of the overall value for money in changing clinical practice. This article demonstrates that the decision to use a sequential v. an integral approach affects the need for detailed information and the complexity of the decision analytic process. More importantly, it may lead to different choices of guidelines and implementation strategies for clinical practice change. The differences in decision making and decision analysis between the alternative approaches are comprehensively illustrated using 2 hypothetical examples. We argue that, in most cases, an integral approach to deciding about change in clinical practice is preferred, as this provides more efficient use of scarce health-care resources.
Migliore, Alberto; Integlia, Davide; Bizzi, Emanuele; Piaggio, Tomaso
2015-10-01
There are plenty of different clinical, organizational and economic parameters to consider in order having a complete assessment of the total impact of a pharmaceutical treatment. In the attempt to follow, a holistic approach aimed to provide an evaluation embracing all clinical parameters in order to choose the best treatments, it is necessary to compare and weight multiple criteria. Therefore, a change is required: we need to move from a decision-making context based on the assessment of one single criteria towards a transparent and systematic framework enabling decision makers to assess all relevant parameters simultaneously in order to choose the best treatment to use. In order to apply the MCDA methodology to clinical decision making the best pharmaceutical treatment (or medical devices) to use to treat a specific pathology, we suggest a specific application of the Multiple Criteria Decision Analysis for the purpose, like a Clinical Multi-criteria Decision Assessment CMDA. In CMDA, results from both meta-analysis and observational studies are used by a clinical consensus after attributing weights to specific domains and related parameters. The decision will result from a related comparison of all consequences (i.e., efficacy, safety, adherence, administration route) existing behind the choice to use a specific pharmacological treatment. The match will yield a score (in absolute value) that link each parameter with a specific intervention, and then a final score for each treatment. The higher is the final score; the most appropriate is the intervention to treat disease considering all criteria (domain an parameters). The results will allow the physician to evaluate the best clinical treatment for his patients considering at the same time all relevant criteria such as clinical effectiveness for all parameters and administration route. The use of CMDA model will yield a clear and complete indication of the best pharmaceutical treatment to use for patients, helping physicians to choose drugs with a complete set of information, imputed in the model. Copyright © 2015 Elsevier Ltd. All rights reserved.
The use of decision analysis to examine ethical decision making by critical care nurses.
Hughes, K K; Dvorak, E M
1997-01-01
To examine the extent to which critical care staff nurses make ethical decisions that coincide with those recommended by a decision analytic model. Nonexperimental, ex post facto. Midwestern university-affiliated 500 bed tertiary care medical center. One hundred critical care staff nurses randomly selected from seven critical care units. Complete responses were obtained from 82 nurses (for a final response rate of 82%). The dependent variable--consistent decision making--was measured as staff nurses' abilities to make ethical decisions that coincided with those prescribed by the decision model. Subjects completed two instruments, the Ethical Decision Analytic Model, a computer-administered instrument designed to measure staff nurses' abilities to make consistent decisions about a chemically-impaired colleague; and a Background Inventory. The results indicate marked consensus among nurses when informal methods were used. However, there was little consistency between the nurses' informal decisions and those recommended by the decision analytic model. Although 50% (n = 41) of all nurses chose a course of action that coincided with the model's least optimal alternative, few nurses agreed with the model as to the most optimal course of action. The findings also suggest that consistency was unrelated (p > 0.05) to the nurses' educational background or years of clinical experience; that most subjects reported receiving little or no education in decision making during their basic nursing education programs; but that exposure to decision-making strategies was related to years of nursing experience (p < 0.05). The findings differ from related studies that have found a moderate degree of consistency between nurses and decision analytic models for strictly clinical decision tasks, especially when those tasks were less complex. However, the findings partially coincide with other findings that decision analysis may not be particularly well-suited to the critical care environment. Additional research is needed to determine whether critical care nurses use the same decision-making methods as do other nurses; and to clarify the effects of decision task (clinical versus ethical) on nurses' decision making. It should not be assumed that methods used to study nurses' clinical decision making are applicable for all nurses or all types of decisions, including ethical decisions.
Hajizadeh, Negin; Perez Figueroa, Rafael E; Uhler, Lauren M; Chiou, Erin; Perchonok, Jennifer E; Montague, Enid
2013-03-06
Computerized decision aids could facilitate shared decision-making at the point of outpatient clinical care. The objective of this study was to investigate whether a computerized shared decision aid would be feasible to implement in an inner-city clinic by evaluating the current practices in shared decision-making, clinicians' use of computers, patient and clinicians' attitudes and beliefs toward computerized decision aids, and the influence of time on shared decision-making. Qualitative data analysis of observations and semi-structured interviews with patients and clinicians at an inner-city outpatient clinic. The findings provided an exploratory look at the prevalence of shared decision-making and attitudes about health information technology and decision aids. A prominent barrier to clinicians engaging in shared decision-making was a lack of perceived patient understanding of medical information. Some patients preferred their clinicians make recommendations for them rather than engage in formal shared decision-making. Health information technology was an integral part of the clinic visit and welcomed by most clinicians and patients. Some patients expressed the desire to engage with health information technology such as viewing their medical information on the computer screen with their clinicians. All participants were receptive to the idea of a decision aid integrated within the clinic visit although some clinicians were concerned about the accuracy of prognostic estimates for complex medical problems. We identified several important considerations for the design and implementation of a computerized decision aid including opportunities to: bridge clinician-patient communication about medical information while taking into account individual patients' decision-making preferences, complement expert clinician judgment with prognostic estimates, take advantage of patient waiting times, and make tasks involved during the clinic visit more efficient. These findings should be incorporated into the design and implementation of a computerized shared decision aid at an inner-city hospital.
Interim analysis: A rational approach of decision making in clinical trial.
Kumar, Amal; Chakraborty, Bhaswat S
2016-01-01
Interim analysis of especially sizeable trials keeps the decision process free of conflict of interest while considering cost, resources, and meaningfulness of the project. Whenever necessary, such interim analysis can also call for potential termination or appropriate modification in sample size, study design, and even an early declaration of success. Given the extraordinary size and complexity today, this rational approach helps to analyze and predict the outcomes of a clinical trial that incorporate what is learned during the course of a study or a clinical development program. Such approach can also fill the gap by directing the resources toward relevant and optimized clinical trials between unmet medical needs and interventions being tested currently rather than fulfilling only business and profit goals.
Pope, Catherine; Halford, Susan; Turnbull, Joanne; Prichard, Jane
2014-06-01
This article draws on data collected during a 2-year project examining the deployment of a computerised decision support system. This computerised decision support system was designed to be used by non-clinical staff for dealing with calls to emergency (999) and urgent care (out-of-hours) services. One of the promises of computerised decisions support technologies is that they can 'hold' vast amounts of sophisticated clinical knowledge and combine it with decision algorithms to enable standardised decision-making by non-clinical (clerical) staff. This article draws on our ethnographic study of this computerised decision support system in use, and we use our analysis to question the 'automated' vision of decision-making in healthcare call-handling. We show that embodied and experiential (human) expertise remains central and highly salient in this work, and we propose that the deployment of the computerised decision support system creates something new, that this conjunction of computer and human creates a cyborg practice.
Cheung, Steven W; Aranda, Derick; Driscoll, Colin L W; Parsa, Andrew T
2010-02-01
Complex medical decision making obligates tradeoff assessments among treatment outcomes expectations, but an accessible tool to perform the necessary analysis is conspicuously absent. We aimed to demonstrate methodology and feasibility of adapting conjoint analysis for mapping clinical outcomes expectations to treatment decisions in vestibular schwannoma (VS) management. Prospective. Tertiary medical center and US-based otologists/neurotologists. Treatment preference profiles among VS stakeholders-61 younger and 74 older prospective patients, 61 observation patients, and 60 surgeons-were assessed for the synthetic VS case scenario of a 10-mm tumor in association with useful hearing and normal facial function. Treatment attribute utility. Conjoint analysis attribute levels were set in accordance to the results of a meta-analysis. Forty-five case series were disaggregated to formulate microsurgery facial nerve and hearing preservation outcomes expectations models. Attribute utilities were computed and mapped to the realistic treatment choices of translabyrinthine craniotomy, middle fossa craniotomy, and gamma knife radiosurgery. Among the treatment attributes of likelihoods of causing deafness, temporary facial weakness for 2 months, and incurable cancer within 20 years, and recovery time, permanent deafness was less important to tumor surgeons, and temporary facial weakness was more important to tumor surgeons and observation patients (Wilcoxon rank-sum, p < 0.001). Inverse mapping of preference profiles to realistic treatment choices showed all study cohorts were inclined to choose gamma knife radiosurgery. Mapping clinical outcomes expectations to treatment decisions for a synthetic clinical scenario revealed inhomogeneous drivers of choice selection among study cohorts. Medical decision engines that analyze personal preferences of outcomes expectations for VS and many other diseases may be developed to promote shared decision making among health care stakeholders and transparency in the informed consent process.
Hydra: A web-based system for cardiovascular analysis, diagnosis and treatment.
Novo, J; Hermida, A; Ortega, M; Barreira, N; Penedo, M G; López, J E; Calvo, C
2017-02-01
Cardiovascular (CV) risk stratification is a highly complex process involving an extensive set of clinical trials to support the clinical decision-making process. There are many clinical conditions (e.g. diabetes, obesity, stress, etc.) that can lead to the early diagnosis or establishment of cardiovascular disease. In order to determine all these clinical conditions, a complete set of clinical patient analyses is typically performed, including a physical examination, blood analysis, electrocardiogram, blood pressure (BP) analysis, etc. This article presents a web-based system, called Hydra, which integrates a full and detailed set of services and functionalities for clinical decision support in order to help and improve the work of clinicians in cardiovascular patient diagnosis, risk assessment, treatment and monitoring over time. Hydra integrates a number of different services: a service for inputting all the information gathered by specialists (physical examination, habits, BP, blood analysis, electrocardiogram, etc.); a tool to automatically determine the CV risk stratification, including well-known standard risk stratification tables; and, finally, various tools to incorporate, analyze and graphically present the records of the ambulatory BP monitoring that provides BP analysis over a given period of time (24 or 48 hours). In addition, the platform presents a set of reports derived from all the information gathered from the patient in order to support physicians in their clinical decisions. Hydra was tested and validated in a real domain. In particular, internal medicine specialists at the Hypertension Unit of the Santiago de Compostela University Hospital (CHUS) validated the platform and used it in different clinical studies to demonstrate its utility. It was observed that the platform increased productivity and accuracy in the assessment of patient data yielding a cost reduction in clinical practice. This paper proposes a complete platform that includes different services for cardiovascular clinical decision support. It was also run as a web-based application to facilitate its use by clinicians, who can access the platform from any remote computer with Internet access. Hydra also includes different automated methods to facilitate the physicians' work and avoid potential errors in the analysis of patient data. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Islam, Roosan; Weir, Charlene R; Jones, Makoto; Del Fiol, Guilherme; Samore, Matthew H
2015-11-30
Clinical experts' cognitive mechanisms for managing complexity have implications for the design of future innovative healthcare systems. The purpose of the study is to examine the constituents of decision complexity and explore the cognitive strategies clinicians use to control and adapt to their information environment. We used Cognitive Task Analysis (CTA) methods to interview 10 Infectious Disease (ID) experts at the University of Utah and Salt Lake City Veterans Administration Medical Center. Participants were asked to recall a complex, critical and vivid antibiotic-prescribing incident using the Critical Decision Method (CDM), a type of Cognitive Task Analysis (CTA). Using the four iterations of the Critical Decision Method, questions were posed to fully explore the incident, focusing in depth on the clinical components underlying the complexity. Probes were included to assess cognitive and decision strategies used by participants. The following three themes emerged as the constituents of decision complexity experienced by the Infectious Diseases experts: 1) the overall clinical picture does not match the pattern, 2) a lack of comprehension of the situation and 3) dealing with social and emotional pressures such as fear and anxiety. All these factors contribute to decision complexity. These factors almost always occurred together, creating unexpected events and uncertainty in clinical reasoning. Five themes emerged in the analyses of how experts deal with the complexity. Expert clinicians frequently used 1) watchful waiting instead of over- prescribing antibiotics, engaged in 2) theory of mind to project and simulate other practitioners' perspectives, reduced very complex cases into simple 3) heuristics, employed 4) anticipatory thinking to plan and re-plan events and consulted with peers to share knowledge, solicit opinions and 5) seek help on patient cases. The cognitive strategies to deal with decision complexity found in this study have important implications for design future decision support systems for the management of complex patients.
Zarinabad, Niloufar; Meeus, Emma M; Manias, Karen; Foster, Katharine
2018-01-01
Background Advances in magnetic resonance imaging and the introduction of clinical decision support systems has underlined the need for an analysis tool to extract and analyze relevant information from magnetic resonance imaging data to aid decision making, prevent errors, and enhance health care. Objective The aim of this study was to design and develop a modular medical image region of interest analysis tool and repository (MIROR) for automatic processing, classification, evaluation, and representation of advanced magnetic resonance imaging data. Methods The clinical decision support system was developed and evaluated for diffusion-weighted imaging of body tumors in children (cohort of 48 children, with 37 malignant and 11 benign tumors). Mevislab software and Python have been used for the development of MIROR. Regions of interests were drawn around benign and malignant body tumors on different diffusion parametric maps, and extracted information was used to discriminate the malignant tumors from benign tumors. Results Using MIROR, the various histogram parameters derived for each tumor case when compared with the information in the repository provided additional information for tumor characterization and facilitated the discrimination between benign and malignant tumors. Clinical decision support system cross-validation showed high sensitivity and specificity in discriminating between these tumor groups using histogram parameters. Conclusions MIROR, as a diagnostic tool and repository, allowed the interpretation and analysis of magnetic resonance imaging images to be more accessible and comprehensive for clinicians. It aims to increase clinicians’ skillset by introducing newer techniques and up-to-date findings to their repertoire and make information from previous cases available to aid decision making. The modular-based format of the tool allows integration of analyses that are not readily available clinically and streamlines the future developments. PMID:29720361
Clinical intuition in the nursing process and decision-making-A mixed-studies review.
Melin-Johansson, Christina; Palmqvist, Rebecca; Rönnberg, Linda
2017-12-01
To review what is characteristic of registered nurses' intuition in clinical settings, in relationships and in the nursing process. Intuition is a controversial concept and nurses believe that there are difficulties in how they should explain their nursing actions or decisions based on intuition. Much of the evidence from the body of research indicates that nurses value their intuition in a variety of clinical settings. More information on how nurses integrate intuition as a core element in daily clinical work would contribute to an improved understanding on how they go about this. Intuition deserves a place in evidence-based activities, where intuition is an important component associated with the nursing process. An integrative review strengthened with a mixed-studies review. Literature searches were conducted in the databases CINAHL, PubMed and PsycINFO, and literature published 1985-2016 were included. The findings in the studies were analysed with content analysis, and the synthesis process entailed a reasoning between the authors. After a quality assessment, 16 studies were included. The analysis and synthesis resulted in three categories. The characteristics of intuition in the nurse's daily clinical activities include application, assertiveness and experiences; in the relationships with patients' intuition include unique connections, mental and bodily responses, and personal qualities; and in the nursing process include support and guidance, component and clues in decision-making, and validating decisions. Intuition is more than simply a "gut feeling," and it is a process based on knowledge and care experience and has a place beside research-based evidence. Nurses integrate both analysis and synthesis of intuition alongside objective data when making decisions. They should rely on their intuition and use this knowledge in clinical practice as a support in decision-making, which increases the quality and safety of patient care. We find that intuition plays a key role in more or less all of the steps in the nursing process as a base for decision-making that supports safe patient care, and is a validated component of nursing clinical care expertise. © 2017 John Wiley & Sons Ltd.
Hajjaj, F M; Salek, M S; Basra, M K A; Finlay, A Y
2010-01-01
Clinical decision making is a complex process and might be influenced by a wide range of clinical and non-clinical factors. Little is known about this process in dermatology. The aim of this study was to explore the different types of management decisions made in dermatology and to identify factors influencing those decisions from observation of consultations and interviews with the patients. 61 patient consultations were observed by a physician with experience in dermatology. The patients were interviewed immediately after each consultation. Consultations and interviews were audio recorded, transcribed and their content analysed using thematic content analysis. The most common management decisions made during the consultations included: follow-up, carrying out laboratory investigation, starting new topical treatment, renewal of systemic treatment, renewal of topical treatment, discharging patients and starting new systemic treatment. Common influences on those decisions included: clinical factors such as ineffectiveness of previous therapy, adherence to prescribing guidelines, side-effects of medications, previous experience with the treatment, deterioration or improvement in the skin condition, and chronicity of skin condition. Non-clinical factors included: patient's quality of life, patient's friends or relatives, patient's time commitment, travel or transportation difficulties, treatment-related costs, availability of consultant, and availability of treatment. The study has shown that patients are aware that management decisions in dermatology are influenced by a wide range of clinical and non-clinical factors. Education programmes should be developed to improve the quality of decision making. Copyright © 2010 S. Karger AG, Basel.
The value of decision tree analysis in planning anaesthetic care in obstetrics.
Bamber, J H; Evans, S A
2016-08-01
The use of decision tree analysis is discussed in the context of the anaesthetic and obstetric management of a young pregnant woman with joint hypermobility syndrome with a history of insensitivity to local anaesthesia and a previous difficult intubation due to a tongue tumour. The multidisciplinary clinical decision process resulted in the woman being delivered without complication by elective caesarean section under general anaesthesia after an awake fibreoptic intubation. The decision process used is reviewed and compared retrospectively to a decision tree analytical approach. The benefits and limitations of using decision tree analysis are reviewed and its application in obstetric anaesthesia is discussed. Copyright © 2016 Elsevier Ltd. All rights reserved.
A qualitative analysis of how advanced practice nurses use clinical decision support systems.
Weber, Scott
2007-12-01
The purpose of this study was to generate a grounded theory that will reflect the experiences of advanced practice nurses (APNs) working as critical care nurse practitioners (NPs) and clinical nurse specialists (CNS) with computer-based decision-making systems. A study design using grounded theory qualitative research methods and convenience sampling was employed in this study. Twenty-three APNs (13 CNS and 10 NPs) were recruited from 16 critical care units located in six large urban medical centers in the U.S. Midwest. Single-structured in-depth interviews with open-ended audio-taped questions were conducted with each APN. Through this process, APNs defined what they consider to be relevant themes and patterns of clinical decision system use in their critical care practices, and they identified the interrelatedness of the conceptual categories that emerged from the results. Data were analyzed using the constant comparative analysis method of qualitative research. APN participants were predominantly female, white/non-Hispanic, had a history of access to the clinical decision system used in their critical care settings for an average of 14 months, and had attended a formal training program to learn how to use clinical decision systems. "Forecasting decision outcomes," which was defined as the voluntary process employed to forecast the outcomes of patient care decisions in critical care prior to actual decision making, was the core variable describing system use that emerged from the responses. This variable consisted of four user constructs or components: (a) users' perceptions of their initial system learning experience, (b) users' sense of how well they understand how system technology works, (c) users' understanding of how system inferences are created or derived, and (d) users' relative trust of system-derived data. Each of these categories was further described through the grounded theory research process, and the relationships between the categories were identified. The findings of this study suggest that the main reason critical care APNs choose to integrate clinical decision systems into their practices is to provide an objective, scientifically derived, technology-based backup for human forecasting of the outcomes of patient care decisions prior to their actual decision making. Implications for nursing, health care, and technology research are presented.
Development and initial evaluation of a treatment decision dashboard.
Dolan, James G; Veazie, Peter J; Russ, Ann J
2013-04-21
For many healthcare decisions, multiple alternatives are available with different combinations of advantages and disadvantages across several important dimensions. The complexity of current healthcare decisions thus presents a significant barrier to informed decision making, a key element of patient-centered care.Interactive decision dashboards were developed to facilitate decision making in Management, a field marked by similarly complicated choices. These dashboards utilize data visualization techniques to reduce the cognitive effort needed to evaluate decision alternatives and a non-linear flow of information that enables users to review information in a self-directed fashion. Theoretically, both of these features should facilitate informed decision making by increasing user engagement with and understanding of the decision at hand. We sought to determine if the interactive decision dashboard format can be successfully adapted to create a clinically realistic prototype patient decision aid suitable for further evaluation and refinement. We created a computerized, interactive clinical decision dashboard and performed a pilot test of its clinical feasibility and acceptability using a multi-method analysis. The dashboard summarized information about the effectiveness, risks of side effects and drug-drug interactions, out-of-pocket costs, and ease of use of nine analgesic treatment options for knee osteoarthritis. Outcome evaluations included observations of how study participants utilized the dashboard, questionnaires to assess usability, acceptability, and decisional conflict, and an open-ended qualitative analysis. The study sample consisted of 25 volunteers - 7 men and 18 women - with an average age of 51 years. The mean time spent interacting with the dashboard was 4.6 minutes. Mean evaluation scores on scales ranging from 1 (low) to 7 (high) were: mechanical ease of use 6.1, cognitive ease of use 6.2, emotional difficulty 2.7, decision-aiding effectiveness 5.9, clarification of values 6.5, reduction in decisional uncertainty 6.1, and provision of decision-related information 6.0. Qualitative findings were similarly positive. Interactive decision dashboards can be adapted for clinical use and have the potential to foster informed decision making. Additional research is warranted to more rigorously test the effectiveness and efficiency of patient decision dashboards for supporting informed decision making and other aspects of patient-centered care, including shared decision making.
Van Dessel, E; Fierens, K; Pattyn, P; Van Nieuwenhove, Y; Berrevoet, F; Troisi, R; Ceelen, W
2009-01-01
Approximately 5%-20% of colorectal cancer (CRC) patients present with synchronous potentially resectable liver metastatic disease. Preclinical and clinical studies suggest a benefit of the 'liver first' approach, i.e. resection of the liver metastasis followed by resection of the primary tumour. A formal decision analysis may support a rational choice between several therapy options. Survival and morbidity data were retrieved from relevant clinical studies identified by a Web of Science search. Data were entered into decision analysis software (TreeAge Pro 2009, Williamstown, MA, USA). Transition probabilities including the risk of death from complications or disease progression associated with individual therapy options were entered into the model. Sensitivity analysis was performed to evaluate the model's validity under a variety of assumptions. The result of the decision analysis confirms the superiority of the 'liver first' approach. Sensitivity analysis demonstrated that this assumption is valid on condition that the mortality associated with the hepatectomy first is < 4.5%, and that the mortality of colectomy performed after hepatectomy is < 3.2%. The results of this decision analysis suggest that, in patients with synchronous resectable colorectal liver metastases, the 'liver first' approach is to be preferred. Randomized trials will be needed to confirm the results of this simulation based outcome.
Nurses' Clinical Decision Making on Adopting a Wound Clinical Decision Support System.
Khong, Peck Chui Betty; Hoi, Shu Yin; Holroyd, Eleanor; Wang, Wenru
2015-07-01
Healthcare information technology systems are considered the ideal tool to inculcate evidence-based nursing practices. The wound clinical decision support system was built locally to support nurses to manage pressure ulcer wounds in their daily practice. However, its adoption rate is not optimal. The study's objective was to discover the concepts that informed the RNs' decisions to adopt the wound clinical decision support system as an evidence-based technology in their nursing practice. This was an exploratory, descriptive, and qualitative design using face-to-face interviews, individual interviews, and active participatory observation. A purposive, theoretical sample of 14 RNs was recruited from one of the largest public tertiary hospitals in Singapore after obtaining ethics approval. After consenting, the nurses were interviewed and observed separately. Recruitment stopped when data saturation was reached. All transcribed interview data underwent a concurrent thematic analysis, whereas observational data were content analyzed independently and subsequently triangulated with the interview data. Eight emerging themes were identified, namely, use of the wound clinical decision support system, beliefs in the wound clinical decision support system, influences of the workplace culture, extent of the benefits, professional control over nursing practices, use of knowledge, gut feelings, and emotions (fear, doubt, and frustration). These themes represented the nurses' mental outlook as they made decisions on adopting the wound clinical decision support system in light of the complexities of their roles and workloads. This research has provided insight on the nurses' thoughts regarding their decision to interact with the computer environment in a Singapore context. It captured the nurses' complex thoughts when deciding whether to adopt or reject information technology as they practice in a clinical setting.
Dolan, James G
2010-01-01
Current models of healthcare quality recommend that patient management decisions be evidence-based and patient-centered. Evidence-based decisions require a thorough understanding of current information regarding the natural history of disease and the anticipated outcomes of different management options. Patient-centered decisions incorporate patient preferences, values, and unique personal circumstances into the decision making process and actively involve both patients along with health care providers as much as possible. Fundamentally, therefore, evidence-based, patient-centered decisions are multi-dimensional and typically involve multiple decision makers.Advances in the decision sciences have led to the development of a number of multiple criteria decision making methods. These multi-criteria methods are designed to help people make better choices when faced with complex decisions involving several dimensions. They are especially helpful when there is a need to combine "hard data" with subjective preferences, to make trade-offs between desired outcomes, and to involve multiple decision makers. Evidence-based, patient-centered clinical decision making has all of these characteristics. This close match suggests that clinical decision support systems based on multi-criteria decision making techniques have the potential to enable patients and providers to carry out the tasks required to implement evidence-based, patient-centered care effectively and efficiently in clinical settings.The goal of this paper is to give readers a general introduction to the range of multi-criteria methods available and show how they could be used to support clinical decision-making. Methods discussed include the balance sheet, the even swap method, ordinal ranking methods, direct weighting methods, multi-attribute decision analysis, and the analytic hierarchy process (AHP).
Dolan, James G.
2010-01-01
Current models of healthcare quality recommend that patient management decisions be evidence-based and patient-centered. Evidence-based decisions require a thorough understanding of current information regarding the natural history of disease and the anticipated outcomes of different management options. Patient-centered decisions incorporate patient preferences, values, and unique personal circumstances into the decision making process and actively involve both patients along with health care providers as much as possible. Fundamentally, therefore, evidence-based, patient-centered decisions are multi-dimensional and typically involve multiple decision makers. Advances in the decision sciences have led to the development of a number of multiple criteria decision making methods. These multi-criteria methods are designed to help people make better choices when faced with complex decisions involving several dimensions. They are especially helpful when there is a need to combine “hard data” with subjective preferences, to make trade-offs between desired outcomes, and to involve multiple decision makers. Evidence-based, patient-centered clinical decision making has all of these characteristics. This close match suggests that clinical decision support systems based on multi-criteria decision making techniques have the potential to enable patients and providers to carry out the tasks required to implement evidence-based, patient-centered care effectively and efficiently in clinical settings. The goal of this paper is to give readers a general introduction to the range of multi-criteria methods available and show how they could be used to support clinical decision-making. Methods discussed include the balance sheet, the even swap method, ordinal ranking methods, direct weighting methods, multi-attribute decision analysis, and the analytic hierarchy process (AHP) PMID:21394218
Proposed Clinical Decision Rules to Diagnose Acute Rhinosinusitis Among Adults in Primary Care.
Ebell, Mark H; Hansen, Jens Georg
2017-07-01
To reduce inappropriate antibiotic prescribing, we sought to develop a clinical decision rule for the diagnosis of acute rhinosinusitis and acute bacterial rhinosinusitis. Multivariate analysis and classification and regression tree (CART) analysis were used to develop clinical decision rules for the diagnosis of acute rhinosinusitis, defined using 3 different reference standards (purulent antral puncture fluid or abnormal finding on a computed tomographic (CT) scan; for acute bacterial rhinosinusitis, we used a positive bacterial culture of antral fluid). Signs, symptoms, C-reactive protein (CRP), and reference standard tests were prospectively recorded in 175 Danish patients aged 18 to 65 years seeking care for suspected acute rhinosinusitis. For each reference standard, we developed 2 clinical decision rules: a point score based on a logistic regression model and an algorithm based on a CART model. We identified low-, moderate-, and high-risk groups for acute rhinosinusitis or acute bacterial rhinosinusitis for each clinical decision rule. The point scores each had between 5 and 6 predictors, and an area under the receiver operating characteristic curve (AUROCC) between 0.721 and 0.767. For positive bacterial culture as the reference standard, low-, moderate-, and high-risk groups had a 16%, 49%, and 73% likelihood of acute bacterial rhinosinusitis, respectively. CART models had an AUROCC ranging from 0.783 to 0.827. For positive bacterial culture as the reference standard, low-, moderate-, and high-risk groups had a likelihood of acute bacterial rhinosinusitis of 6%, 31%, and 59% respectively. We have developed a series of clinical decision rules integrating signs, symptoms, and CRP to diagnose acute rhinosinusitis and acute bacterial rhinosinusitis with good accuracy. They now require prospective validation and an assessment of their effect on clinical and process outcomes. © 2017 Annals of Family Medicine, Inc.
A Mixed Methodological Analysis of the Role of Culture in the Clinical Decision-Making Process
ERIC Educational Resources Information Center
Hays, Danica G.; Prosek, Elizabeth A.; McLeod, Amy L.
2010-01-01
Even though literature indicates that particular cultural groups receive more severe diagnoses at disproportionate rates, there has been minimal research that addresses how culture interfaces specifically with clinical decision making. This mixed methodological study of 41 counselors indicated that cultural characteristics of both counselors and…
Hagbaghery, Mohsen Adib; Salsali, Mahvash; Ahmadi, Fazlolah
2004-01-01
Background Nurses' practice takes place in a context of ongoing advances in research and technology. The dynamic and uncertain nature of health care environment requires nurses to be competent decision-makers in order to respond to clients' needs. Recently, the public and the government have criticized Iranian nurses because of poor quality of patient care. However nurses' views and experiences on factors that affect their clinical function and clinical decision-making have rarely been studied. Methods Grounded theory methodology was used to analyze the participants' lived experiences and their viewpoints regarding the factors affecting their clinical function and clinical decision-making. Semi-structured interviews and participant observation methods were used to gather the data. Thirty-eight participants were interviewed and twelve sessions of observation were carried out. Constant comparative analysis method was used to analyze the data. Results Five main themes emerged from the data. From the participants' points of view, "feeling competent", "being self-confident", "organizational structure", "nursing education", and "being supported" were considered as important factors in effective clinical decision-making. Conclusion As participants in this research implied, being competent and self-confident are the most important personal factors influencing nurses clinical decision-making. Also external factors such as organizational structure, access to supportive resources and nursing education have strengthening or inhibiting effects on the nurses' decisions. Individual nurses, professional associations, schools of nursing, nurse educators, organizations that employ nurses and government all have responsibility for developing and finding strategies that facilitate nurses' effective clinical decision-making. They are responsible for identifying barriers and enhancing factors within the organizational structure that facilitate nurses' clinical decision-making. PMID:15068484
Nilsson, Tomas; Lindström, Veronica
2016-07-01
The purpose of this study was to explore the PECN students' clinical decision-making during a seven-week clinical rotation in the ambulance services. Developing expertise in prehospital emergency care practices requires both theoretical and empirical learning. A prehospital emergency care nurse (PECN) is a Registered Nurse (RN) with one year of additional training in emergency care. There has been little investigation of how PECN students describe their decision-making during a clinical rotation. A qualitative study design was used, and 12 logbooks written by the Swedish PECN students were analysed using content analysis. The students wrote about 997 patient encounters - ambulance assignments during their clinical rotation. Four themes emerged as crucial for the students' decision-making: knowing the patient, the context-situation awareness in the ambulance service, collaboration, and evaluation. Based on the themes, students made decisions on how to respond to patients' illnesses. The PECN students used several variables in their decision-making. The decision- making was an on-going process during the whole ambulance assignment. The university has the responsibility to guide the students during their transition from an RN to a PECN. The findings of the study can support the educators and clinical supervisors in developing the programme of study for becoming a PECN. Copyright © 2015 Elsevier Ltd. All rights reserved.
Lessard, Chantale; Contandriopoulos, André-Pierre; Beaulieu, Marie-Dominique
2009-01-01
Background A considerable amount of resource allocation decisions take place daily at the point of the clinical encounter; especially in primary care, where 80 percent of health problems are managed. Ignoring economic evaluation evidence in individual clinical decision-making may have a broad impact on the efficiency of health services. To date, almost all studies on the use of economic evaluation in decision-making used a quantitative approach, and few investigated decision-making at the clinical level. An important question is whether economic evaluations affect clinical practice. The project is an intervention research study designed to understand the role of economic evaluation in the decision-making process of family physicians (FPs). The contributions of the project will be from the perspective of Pierre Bourdieu's sociological theory. Methods/design A qualitative research strategy is proposed. We will conduct an embedded multiple-case study design. Ten case studies will be performed. The FPs will be the unit of analysis. The sampling strategies will be directed towards theoretical generalization. The 10 selected cases will be intended to reflect a diversity of FPs. There will be two embedded units of analysis: FPs (micro-level of analysis) and field of family medicine (macro-level of analysis). The division of the determinants of practice/behaviour into two groups, corresponding to the macro-structural level and the micro-individual level, is the basis for Bourdieu's mode of analysis. The sources of data collection for the micro-level analysis will be 10 life history interviews with FPs, documents and observational evidence. The sources of data collection for the macro-level analysis will be documents and 9 open-ended, focused interviews with key informants from medical associations and academic institutions. The analytic induction approach to data analysis will be used. A list of codes will be generated based on both the original framework and new themes introduced by the participants. We will conduct within-case and cross-case analyses of the data. Discussion The question of the role of economic evaluation in FPs' decision-making is of great interest to scientists, health care practitioners, managers and policy-makers, as well as to consultants, industry, and society. It is believed that the proposed research approach will make an original contribution to the development of knowledge, both empirical and theoretical. PMID:19210787
Grove, Amy; Clarke, Aileen; Currie, Graeme
2018-05-31
The uptake and use of clinical guidelines is often insufficient to change clinical behaviour and reduce variation in practice. As a consequence of diverse organisational contexts, the simple provision of guidelines cannot ensure fidelity or guarantee their use when making decisions. Implementation research in surgery has focused on understanding what evidence exists for clinical practice decisions but limits understanding to the technical, educational and accessibility issues. This research aims to identify where, when and how evidence and knowledge are used in orthopaedic decision-making and how variation in these factors contributes to different approaches to implementation of clinical guidance in practice. We used in-depth case studies to examine guideline implementation in real-life surgical practice. We conducted comparative case studies in three English National Health Service hospitals over a 12-month period. Each in-depth case study consisted of a mix of qualitative methods including interviews, observations and document analysis. Data included field notes from observations of day-to-day practice, 64 interviews with NHS surgeons and staff and the collection of 121 supplementary documents. Case studies identified 17 sources of knowledge and evidence which influenced clinical decisions in elective orthopaedic surgery. A comparative analysis across cases revealed that each hospital had distinct approaches to decision-making. Decision-making is described as occurring as a result of how 17 types of knowledge and evidence were privileged and of how they interacted and changed in context. Guideline implementation was contingent and mediated through four distinct contextual levels. Implementation could be assessed for individual surgeons, groups of surgeons or the organisation as a whole, but it could also differ between these levels. Differences in how evidence and knowledge were used contributed to variations in practice from guidelines. A range of complex and competing sources of evidence and knowledge exists which influence the working practices of healthcare professionals. The dynamic selection, combination and use of each type of knowledge and evidence influence the implementation and use of clinical guidance in practice. Clinical guidelines are a fundamental part of practice, but represent only one type of evidence influencing clinical decisions. In the orthopaedic speciality, other distinct sources of evidence and knowledge are selected and used which impact on how guidelines are implemented. New approaches to guideline implementation need to appreciate and incorporate this diverse range of knowledge and evidence which influences clinical decisions and to take account of the changing contexts in which decisions are made.
Kovshoff, Hanna; Williams, Sarah; Vrijens, May; Danckaerts, Marina; Thompson, Margaret; Yardley, Lucy; Hodgkins, Paul; Sonuga-Barke, Edmund J S
2012-02-01
Clinical decision making is influenced by a range of factors and constitutes an inherently complex task. Here we present results from the decisions regarding ADHD management (DRAMa) study in which we undertook a thematic analysis of clinicians' experiences and attitudes to assessment, diagnosis and treatment of ADHD. Fifty prescribing child psychiatrists and paediatricians from Belgium and the UK took part in semi-structured interviews about their decisions regarding the assessment, diagnosis and treatment of ADHD. Interviews were transcribed and processed using thematic analysis and the principles of grounded theory. Clinicians described the assessment and diagnostic process as inherently complicated and requiring time and experience to piece together the accounts of children made by multiple sources and through the use of varying information gathering techniques. Treatment decisions were viewed as a shared process between families, children, and the clinician. Published guidelines were viewed as vague, and few clinicians spoke about the use of symptom thresholds or specific impairment criteria. Furthermore, systematic or operationalised criteria to assess treatment outcomes were rarely used. Decision making in ADHD is regarded as a complicated, time consuming process which requires extensive use of clinical impression, and involves a partnership with parents. Clinicians want to separate biological from environmental causal factors to understand the level of impairment and the subsequent need for a diagnosis of ADHD. Clinical guidelines would benefit from revisions to take into account the real-world complexities of clinical decision making for ADHD.
Demeter, Sandor J
2016-12-21
Health care providers (HCP) and clinical scientists (CS) are generally most comfortable using evidence-based rational decision-making models. They become very frustrated when policymakers make decisions that, on the surface, seem irrational and unreasonable. However, such decisions usually make sense when analysed properly. The goal of this paper to provide a basic theoretical understanding of major policy models, to illustrate which models are most prevalent in publicly funded health care systems, and to propose a policy analysis framework to better understand the elements that drive policy decision-making. The proposed policy framework will also assist HCP and CS achieve greater success with their own proposals.
Kassakian, Steven Z; Yackel, Thomas R; Deloughery, Thomas; Dorr, David A
2016-06-01
Red blood cell transfusion is the most common procedure in hospitalized patients in the US. Growing evidence suggests that a sizeable percentage of these transfusions are inappropriate, putting patients at significant risk and increasing costs to the health care system. We performed a retrospective quasi-experimental study from November 2008 until November 2014 in a 576-bed tertiary care hospital. The intervention consisted of an interruptive clinical decision support alert shown to a provider when a red blood cell transfusion was ordered in a patient whose most recent hematocrit was ≥21%. We used interrupted time series analysis to determine whether our primary outcome of interest, rate of red blood cell transfusion in patients with hematocrit ≥21% per 100 patient (pt) days, was reduced by the implementation of the clinical decision support tool. The rate of platelet transfusions was used as a nonequivalent dependent control variable. A total of 143,000 hospital admissions were included in our analysis. Red blood cell transfusions decreased from 9.4 to 7.8 per 100 pt days after the clinical decision support intervention was implemented. Interrupted time series analysis showed that significant decline of 0.05 (95% confidence interval [CI], 0.03-0.07; P < .001) units of red blood cells transfused per 100 pt days per month was already underway in the preintervention period. This trend accelerated to 0.1 (95% CI, 0.09-0.12; P < .001) units of red blood cells transfused per 100 pt days per month following the implementation of the clinical decision support tool. There was no statistical change in the rate of platelet transfusion resulting from the intervention. The implementation of an evidence-based clinical decision support tool was associated with a significant decline in the overuse of red blood cell transfusion. We believe this intervention could be easily replicated in other hospitals using commercial electronic health records and a similar reduction in overuse of red blood cell transfusions achieved. Copyright © 2016 Elsevier Inc. All rights reserved.
Watt, Stuart; Jiao, Wei; Brown, Andrew M K; Petrocelli, Teresa; Tran, Ben; Zhang, Tong; McPherson, John D; Kamel-Reid, Suzanne; Bedard, Philippe L; Onetto, Nicole; Hudson, Thomas J; Dancey, Janet; Siu, Lillian L; Stein, Lincoln; Ferretti, Vincent
2013-09-01
Using sequencing information to guide clinical decision-making requires coordination of a diverse set of people and activities. In clinical genomics, the process typically includes sample acquisition, template preparation, genome data generation, analysis to identify and confirm variant alleles, interpretation of clinical significance, and reporting to clinicians. We describe a software application developed within a clinical genomics study, to support this entire process. The software application tracks patients, samples, genomic results, decisions and reports across the cohort, monitors progress and sends reminders, and works alongside an electronic data capture system for the trial's clinical and genomic data. It incorporates systems to read, store, analyze and consolidate sequencing results from multiple technologies, and provides a curated knowledge base of tumor mutation frequency (from the COSMIC database) annotated with clinical significance and drug sensitivity to generate reports for clinicians. By supporting the entire process, the application provides deep support for clinical decision making, enabling the generation of relevant guidance in reports for verification by an expert panel prior to forwarding to the treating physician. Copyright © 2013 Elsevier Inc. All rights reserved.
Medical Problem-Solving: A Critique of the Literature.
ERIC Educational Resources Information Center
McGuire, Christine H.
1985-01-01
Prescriptive, decision-analysis of medical problem-solving has been based on decision theory that involves calculation and manipulation of complex probability and utility values to arrive at optimal decisions that will maximize patient benefits. The studies offer a methodology for improving clinical judgment. (Author/MLW)
Sheehan, Barbara; Kaufman, David; Stetson, Peter; Currie, Leanne M.
2009-01-01
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
Boland, Laura; Taljaard, Monica; Dervin, Geoffrey; Trenaman, Logan; Tugwell, Peter; Pomey, Marie-Pascale; Stacey, Dawn
2017-12-01
Decision aids help patients make total joint arthroplasty decisions, but presurgical evaluation might influence the effects of a decision aid. We compared the effects of a decision aid among patients considering total knee arthroplasty at 2 surgical screening clinics with different evaluation processes. We performed a subgroup analysis of a randomized controlled trial. Patients were recruited from 2 surgical screening clinics: an academic clinic providing 20-minute physician consultations and a community clinic providing 45-minute physiotherapist/nurse consultations with education. We compared the effects of decision quality, decisional conflict and surgery rate using Cochran-Mantel-Haenszel χ 2 tests and the Breslow-Day test. We evaluated 242 patients: 123 from the academic clinic (61 who used the decision aid and 62 controls) and 119 from the community clinic (59 who used the decision aid and 60 controls). Results suggested a between-site difference in the effect of the decision aid on the patients' decision quality ( p = 0.09): at the academic site, patients who used the decision were more likely to make better-quality decisions than controls (54% v. 35%, p = 0.044), but not at the community site (47% v. 51%, p = 0.71). Fewer patients who used decision aids at the academic site than at the community site experienced decisional conflict ( p = 0.007) (33% v. 52%, p = 0.05 at the academic site and 40% v. 24%, p = 0.08 at the community site). The effect of the decision aid on surgery rates did not differ between sites ( p = 0.65). The decision aid had a greater effect at the academic site than at the community site, which provided longer consultations with more verbal education. Hence, decision aids might be of greater value when more extensive total knee arthroplasty presurgical assessment and counselling are either impractical or unavailable.
Boland, Laura; Taljaard, Monica; Dervin, Geoffrey; Trenaman, Logan; Tugwell, Peter; Pomey, Marie-Pascale; Stacey, Dawn
2018-02-01
Decision aids help patients make total joint arthroplasty decisions, but presurgical evaluation might influence the effects of a decision aid. We compared the effects of a decision aid among patients considering total knee arthroplasty at 2 surgical screening clinics with different evaluation processes. We performed a subgroup analysis of a randomized controlled trial. Patients were recruited from 2 surgical screening clinics: an academic clinic providing 20-minute physician consultations and a community clinic providing 45-minute physiotherapist/nurse consultations with education. We compared the effects of decision quality, decisional conflict and surgery rate using Cochran-Mantel-Haenszel χ 2 tests and the Breslow-Day test. We evaluated 242 patients: 123 from the academic clinic (61 who used the decision aid and 62 controls) and 119 from the community clinic (59 who used the decision aid and 60 controls). Results suggested a between-site difference in the effect of the decision aid on the patients' decision quality ( p = 0.09): at the academic site, patients who used the decision aid were more likely to make better-quality decisions than controls (54% v. 35%, p = 0.044), but not at the community site (47% v. 51%, p = 0.71). Fewer patients who used decision aids at the academic site than at the community site experienced decisional conflict ( p = 0.007) (33% v. 52%, p = 0.05 at the academic site and 40% v. 24%, p = 0.08 at the community site). The effect of the decision aid on surgery rates did not differ between sites ( p = 0.65). The decision aid had a greater effect at the academic site than at the community site, which provided longer consultations with more verbal education. Hence, decision aids might be of greater value when more extensive total knee arthroplasty presurgical assessment and counselling are either impractical or unavailable.
Phan, Thanh G; Chen, Jian; Singhal, Shaloo; Ma, Henry; Clissold, Benjamin B; Ly, John; Beare, Richard
2018-01-01
Prognostication following hypoxic ischemic encephalopathy (brain injury) is important for clinical management. The aim of this exploratory study is to use a decision tree model to find clinical and MRI associates of severe disability and death in this condition. We evaluate clinical model and then the added value of MRI data. The inclusion criteria were as follows: age ≥17 years, cardio-respiratory arrest, and coma on admission (2003-2011). Decision tree analysis was used to find clinical [Glasgow Coma Score (GCS), features about cardiac arrest, therapeutic hypothermia, age, and sex] and MRI (infarct volume) associates of severe disability and death. We used the area under the ROC (auROC) to determine accuracy of model. There were 41 (63.7% males) patients having MRI imaging with the average age 51.5 ± 18.9 years old. The decision trees showed that infarct volume and age were important factors for discrimination between mild to moderate disability and severe disability and death at day 0 and day 2. The auROC for this model was 0.94 (95% CI 0.82-1.00). At day 7, GCS value was the only predictor; the auROC was 0.96 (95% CI 0.86-1.00). Our findings provide proof of concept for further exploration of the role of MR imaging and decision tree analysis in the early prognostication of hypoxic ischemic brain injury.
[Structural elements of critical thinking of nurses in emergency care].
Crossetti, Maria da Graça Oliveira; Bittencourt, Greicy Kelly Gouveia Dias; Lima, Ana Amélia Antunes; de Góes, Marta Georgina Oliveira; Saurin, Gislaine
2014-09-01
The objective of this study was to analyze the structural elements of critical thinking (CT) of nurses in the clinical decision-making process. This exploratory, qualitative study was conducted with 20 emergency care nurses in three hospitals in southern Brazil. Data were collected from April to June 2009, and a validated clinical case was applied from which nurses listed health problems, prescribed care and listed the structural elements of CT. Content analysis resulted in categories used to determine priority structural elements of CT, namely theoretical foundations and practical relationship to clinical decision making; technical and scientific knowledge and clinical experience, thought processes and clinical decision making: clinical reasoning and basis for clinical judgments of nurses: patient assessment and ethics. It was concluded that thinking critically is a skill that enables implementation of a secure and effective nursing care process.
Reflections in the clinical practice.
Borrell-Carrió, F; Hernández-Clemente, J C
2014-03-01
The purpose of this article is to analyze some models of expert decision and their impact on the clinical practice. We have analyzed decision-making considering the cognitive aspects (explanatory models, perceptual skills, analysis of the variability of a phenomenon, creating habits and inertia of reasoning and declarative models based on criteria). We have added the importance of emotions in decision making within highly complex situations, such as those occurring within the clinical practice. The quality of the reflective act depends, among other factors, on the ability of metacognition (thinking about what we think). Finally, we propose an educational strategy based on having a task supervisor and rectification scenarios to improve the quality of medical decision making. Copyright © 2013 Elsevier España, S.L. All rights reserved.
Decision analysis in formulary decision making.
Schechter, C B
1993-06-01
Although decision making about what drugs to include in an institutional formulary appears to lend itself readily to quantitative techniques such as decision analysis and cost-benefit analysis, a review of the literature reveals that very little has been published in this area. Several of the published decision analyses use non-standard techniques that are, at best, of unproved validity, and may seriously distort the underlying issues through covert under-counting or double-counting of various drug attributes. Well executed decision analyses have contributed to establishing that drug acquisition costs are not an adequate measure of the total economic impact of formulary decisions and that costs of labour and materials associated with drug administration must be calculated on an institution-specific basis to reflect unique staffing patterns, bulk purchasing practices, and the availability of surplus capacity within the institution which might be mobilised at little marginal cost. Clinical studies of newly introduced drugs frequently fail to answer the questions that weigh most heavily on the structuring of a formal assessment of a proposed formulary acquisition. Studies comparing a full spectrum of therapeutically equivalent drugs are rarely done, and individual studies of particular pairs of drugs can rarely be used together because of differences in methodology or patient populations studied. Gathering of institution-specific economic and clinical data is a daunting, labour-intensive task. In many institutions, incentive and reward structures discourage behaviour that takes the broad institutional perspective that is intrinsic to a good decision analysis.(ABSTRACT TRUNCATED AT 250 WORDS)
Hess, Erik P; Wells, George A; Jaffe, Allan; Stiell, Ian G
2008-01-01
Background Chest pain is the second most common chief complaint in North American emergency departments. Data from the U.S. suggest that 2.1% of patients with acute myocardial infarction and 2.3% of patients with unstable angina are misdiagnosed, with slightly higher rates reported in a recent Canadian study (4.6% and 6.4%, respectively). Information obtained from the history, 12-lead ECG, and a single set of cardiac enzymes is unable to identify patients who are safe for early discharge with sufficient sensitivity. The 2007 ACC/AHA guidelines for UA/NSTEMI do not identify patients at low risk for adverse cardiac events who can be safely discharged without provocative testing. As a result large numbers of low risk patients are triaged to chest pain observation units and undergo provocative testing, at significant cost to the healthcare system. Clinical decision rules use clinical findings (history, physical exam, test results) to suggest a diagnostic or therapeutic course of action. Currently no methodologically robust clinical decision rule identifies patients safe for early discharge. Methods/design The goal of this study is to derive a clinical decision rule which will allow emergency physicians to accurately identify patients with chest pain who are safe for early discharge. The study will utilize a prospective cohort design. Standardized clinical variables will be collected on all patients at least 25 years of age complaining of chest pain prior to provocative testing. Variables strongly associated with the composite outcome acute myocardial infarction, revascularization, or death will be further analyzed with multivariable analysis to derive the clinical rule. Specific aims are to: i) apply standardized clinical assessments to patients with chest pain, incorporating results of early cardiac testing; ii) determine the inter-observer reliability of the clinical information; iii) determine the statistical association between the clinical findings and the composite outcome; and iv) use multivariable analysis to derive a highly sensitive clinical decision rule to guide triage decisions. Discussion The study will derive a highly sensitive clinical decision rule to identify low risk patients safe for early discharge. This will improve patient care, lower healthcare costs, and enhance flow in our busy and overcrowded emergency departments. PMID:18254973
Berg, Karianne; Rise, Marit By; Balandin, Susan; Armstrong, Elizabeth; Askim, Torunn
2016-01-01
Although client participation has been part of legislation and clinical guidelines for several years, the evidence of these recommendations being implemented into clinical practice is scarce, especially for people with communication disorders. The aim of this study was to investigate how speech pathologists experienced client participation during the process of goal-setting and clinical decision making for people with aphasia. Twenty speech pathologists participated in four focus group interviews. A qualitative analysis using Systematic Text Condensation was undertaken. Analysis revealed three different approaches to client participation: (1) client-oriented, (2) next of kin-oriented and (3) professional-oriented participation. Participants perceived client-oriented participation as the gold standard. The three approaches were described as overlapping, with each having individual characteristics incorporating different facilitators and barriers. There is a need for greater emphasis on how to involve people with severe aphasia in goal setting and treatment planning, and frameworks made to enhance collaboration could preferably be used. Participants reported use of next of kin as proxies in goal-setting and clinical decision making for people with moderate-to-severe aphasia, indicating the need for awareness towards maintaining the clients' autonomy and addressing the goals of next of kin. Speech pathologists, and most likely other professionals, should place greater emphasis on client participation to ensure active involvement of people with severe aphasia. To achieve this, existing tools and techniques made to enhance collaborative goal setting and clinical decision making have to be better incorporated into clinical rehabilitation practice. To ensure the autonomy of the person with aphasia, as well as to respect next of kin's own goals, professionals need to make ethical considerations when next of kin are used as proxies in collaborative goal setting and clinical decision making.
Trachtenberg, Felicia L; Pober, David M; Welch, Lisa C; McKinlay, John B
Variation in physician decisions may reflect personal styles of decision-making, as opposed to singular clinical actions and these styles may be applied differently depending on patient complexity. The objective of this study is to examine clusters of physician decision-making for type 2 diabetes, overall and in the presence of a mental health co-morbidity. This randomized balanced factorial experiment presented video vignettes of a "patient" with diagnosed, but uncontrolled type 2 diabetes. "Patients" were systematically varied by age, sex, race and co-morbidity (depression, schizophrenia with normal or bizarre affect, eczema as control). Two hundred and fifty-six primary care physicians, balanced by gender and experience level, completed a structured interview about clinical management. Cluster analysis identified 3 styles of diabetes management. "Minimalists" (n=84) performed fewer exams or tests compared to "middle of the road" physicians (n=84). "Interventionists" (n=88) suggested more medications and referrals. A second cluster analysis, without control for co-morbidities, identified an additional cluster of "information seekers" (n=15) who requested more additional information and referrals. Physicians ranking schizophrenia higher than diabetes on their problem list were more likely "minimalists" and none were "interventionists" or "information seekers". Variations in clinical management encompass multiple clinical actions and physicians subtly shift these decision-making styles depending on patient co-morbidities. Physicians' practice styles may help explain persistent differences in patient care. Training and continuing education efforts to encourage physicians to implement evidence-based clinical practice should account for general styles of decision-making and for how physicians process complicating comorbidities.
Development of an evidence-based decision pathway for vestibular schwannoma treatment options.
Linkov, Faina; Valappil, Benita; McAfee, Jacob; Goughnour, Sharon L; Hildrew, Douglas M; McCall, Andrew A; Linkov, Igor; Hirsch, Barry; Snyderman, Carl
To integrate multiple sources of clinical information with patient feedback to build evidence-based decision support model to facilitate treatment selection for patients suffering from vestibular schwannomas (VS). This was a mixed methods study utilizing focus group and survey methodology to solicit feedback on factors important for making treatment decisions among patients. Two 90-minute focus groups were conducted by an experienced facilitator. Previously diagnosed VS patients were recruited by clinical investigators at the University of Pittsburgh Medical Center (UPMC). Classical content analysis was used for focus group data analysis. Providers were recruited from practices within the UPMC system and were surveyed using Delphi methods. This information can provide a basis for multi-criteria decision analysis (MCDA) framework to develop a treatment decision support system for patients with VS. Eight themes were derived from these data (focus group + surveys): doctor/health care system, side effects, effectiveness of treatment, anxiety, mortality, family/other people, quality of life, and post-operative symptoms. These data, as well as feedback from physicians were utilized in building a multi-criteria decision model. The study illustrated steps involved in the development of a decision support model that integrates evidence-based data and patient values to select treatment alternatives. Studies focusing on the actual development of the decision support technology for this group of patients are needed, as decisions are highly multifactorial. Such tools have the potential to improve decision making for complex medical problems with alternate treatment pathways. Copyright © 2016 Elsevier Inc. All rights reserved.
Bayesian imperfect information analysis for clinical recurrent data
Chang, Chih-Kuang; Chang, Chi-Chang
2015-01-01
In medical research, clinical practice must often be undertaken with imperfect information from limited resources. This study applied Bayesian imperfect information-value analysis to realistic situations to produce likelihood functions and posterior distributions, to a clinical decision-making problem for recurrent events. In this study, three kinds of failure models are considered, and our methods illustrated with an analysis of imperfect information from a trial of immunotherapy in the treatment of chronic granulomatous disease. In addition, we present evidence toward a better understanding of the differing behaviors along with concomitant variables. Based on the results of simulations, the imperfect information value of the concomitant variables was evaluated and different realistic situations were compared to see which could yield more accurate results for medical decision-making. PMID:25565853
Broekhuizen, Henk; IJzerman, Maarten J; Hauber, A Brett; Groothuis-Oudshoorn, Catharina G M
2017-03-01
The need for patient engagement has been recognized by regulatory agencies, but there is no consensus about how to operationalize this. One approach is the formal elicitation and use of patient preferences for weighing clinical outcomes. The aim of this study was to demonstrate how patient preferences can be used to weigh clinical outcomes when both preferences and clinical outcomes are uncertain by applying a probabilistic value-based multi-criteria decision analysis (MCDA) method. Probability distributions were used to model random variation and parameter uncertainty in preferences, and parameter uncertainty in clinical outcomes. The posterior value distributions and rank probabilities for each treatment were obtained using Monte-Carlo simulations. The probability of achieving the first rank is the probability that a treatment represents the highest value to patients. We illustrated our methodology for a simplified case on six HIV treatments. Preferences were modeled with normal distributions and clinical outcomes were modeled with beta distributions. The treatment value distributions showed the rank order of treatments according to patients and illustrate the remaining decision uncertainty. This study demonstrated how patient preference data can be used to weigh clinical evidence using MCDA. The model takes into account uncertainty in preferences and clinical outcomes. The model can support decision makers during the aggregation step of the MCDA process and provides a first step toward preference-based personalized medicine, yet requires further testing regarding its appropriate use in real-world settings.
Huber, Timothy C; Krishnaraj, Arun; Monaghan, Dayna; Gaskin, Cree M
2018-05-18
Due to mandates from recent legislation, clinical decision support (CDS) software is being adopted by radiology practices across the country. This software provides imaging study decision support for referring providers at the point of order entry. CDS systems produce a large volume of data, providing opportunities for research and quality improvement. In order to better visualize and analyze trends in this data, an interactive data visualization dashboard was created using a commercially available data visualization platform. Following the integration of a commercially available clinical decision support product into the electronic health record, a dashboard was created using a commercially available data visualization platform (Tableau, Seattle, WA). Data generated by the CDS were exported from the data warehouse, where they were stored, into the platform. This allowed for real-time visualization of the data generated by the decision support software. The creation of the dashboard allowed the output from the CDS platform to be more easily analyzed and facilitated hypothesis generation. Integrating data visualization tools into clinical decision support tools allows for easier data analysis and can streamline research and quality improvement efforts.
Development and initial evaluation of a treatment decision dashboard
2013-01-01
Background For many healthcare decisions, multiple alternatives are available with different combinations of advantages and disadvantages across several important dimensions. The complexity of current healthcare decisions thus presents a significant barrier to informed decision making, a key element of patient-centered care. Interactive decision dashboards were developed to facilitate decision making in Management, a field marked by similarly complicated choices. These dashboards utilize data visualization techniques to reduce the cognitive effort needed to evaluate decision alternatives and a non-linear flow of information that enables users to review information in a self-directed fashion. Theoretically, both of these features should facilitate informed decision making by increasing user engagement with and understanding of the decision at hand. We sought to determine if the interactive decision dashboard format can be successfully adapted to create a clinically realistic prototype patient decision aid suitable for further evaluation and refinement. Methods We created a computerized, interactive clinical decision dashboard and performed a pilot test of its clinical feasibility and acceptability using a multi-method analysis. The dashboard summarized information about the effectiveness, risks of side effects and drug-drug interactions, out-of-pocket costs, and ease of use of nine analgesic treatment options for knee osteoarthritis. Outcome evaluations included observations of how study participants utilized the dashboard, questionnaires to assess usability, acceptability, and decisional conflict, and an open-ended qualitative analysis. Results The study sample consisted of 25 volunteers - 7 men and 18 women - with an average age of 51 years. The mean time spent interacting with the dashboard was 4.6 minutes. Mean evaluation scores on scales ranging from 1 (low) to 7 (high) were: mechanical ease of use 6.1, cognitive ease of use 6.2, emotional difficulty 2.7, decision-aiding effectiveness 5.9, clarification of values 6.5, reduction in decisional uncertainty 6.1, and provision of decision-related information 6.0. Qualitative findings were similarly positive. Conclusions Interactive decision dashboards can be adapted for clinical use and have the potential to foster informed decision making. Additional research is warranted to more rigorously test the effectiveness and efficiency of patient decision dashboards for supporting informed decision making and other aspects of patient-centered care, including shared decision making. PMID:23601912
ERIC Educational Resources Information Center
Fluke, John D.; Chabot, Martin; Fallon, Barbara; MacLaurin, Bruce; Blackstock, Cindy
2010-01-01
Objective: This paper examined the relative influence of clinical and organizational characteristics on the decision to place a child in out-of-home care at the conclusion of a child maltreatment investigation. It tested the hypothesis that extraneous factors, specifically, organizational characteristics, impact the decision to place a child in…
Use of handheld computers in clinical practice: a systematic review.
Mickan, Sharon; Atherton, Helen; Roberts, Nia Wyn; Heneghan, Carl; Tilson, Julie K
2014-07-06
Many healthcare professionals use smartphones and tablets to inform patient care. Contemporary research suggests that handheld computers may support aspects of clinical diagnosis and management. This systematic review was designed to synthesise high quality evidence to answer the question; Does healthcare professionals' use of handheld computers improve their access to information and support clinical decision making at the point of care? A detailed search was conducted using Cochrane, MEDLINE, EMBASE, PsycINFO, Science and Social Science Citation Indices since 2001. Interventions promoting healthcare professionals seeking information or making clinical decisions using handheld computers were included. Classroom learning and the use of laptop computers were excluded. Two authors independently selected studies, assessed quality using the Cochrane Risk of Bias tool and extracted data. High levels of data heterogeneity negated statistical synthesis. Instead, evidence for effectiveness was summarised narratively, according to each study's aim for assessing the impact of handheld computer use. We included seven randomised trials investigating medical or nursing staffs' use of Personal Digital Assistants. Effectiveness was demonstrated across three distinct functions that emerged from the data: accessing information for clinical knowledge, adherence to guidelines and diagnostic decision making. When healthcare professionals used handheld computers to access clinical information, their knowledge improved significantly more than peers who used paper resources. When clinical guideline recommendations were presented on handheld computers, clinicians made significantly safer prescribing decisions and adhered more closely to recommendations than peers using paper resources. Finally, healthcare professionals made significantly more appropriate diagnostic decisions using clinical decision making tools on handheld computers compared to colleagues who did not have access to these tools. For these clinical decisions, the numbers need to test/screen were all less than 11. Healthcare professionals' use of handheld computers may improve their information seeking, adherence to guidelines and clinical decision making. Handheld computers can provide real time access to and analysis of clinical information. The integration of clinical decision support systems within handheld computers offers clinicians the highest level of synthesised evidence at the point of care. Future research is needed to replicate these early results and to identify beneficial clinical outcomes.
Use of handheld computers in clinical practice: a systematic review
2014-01-01
Background Many healthcare professionals use smartphones and tablets to inform patient care. Contemporary research suggests that handheld computers may support aspects of clinical diagnosis and management. This systematic review was designed to synthesise high quality evidence to answer the question; Does healthcare professionals’ use of handheld computers improve their access to information and support clinical decision making at the point of care? Methods A detailed search was conducted using Cochrane, MEDLINE, EMBASE, PsycINFO, Science and Social Science Citation Indices since 2001. Interventions promoting healthcare professionals seeking information or making clinical decisions using handheld computers were included. Classroom learning and the use of laptop computers were excluded. Two authors independently selected studies, assessed quality using the Cochrane Risk of Bias tool and extracted data. High levels of data heterogeneity negated statistical synthesis. Instead, evidence for effectiveness was summarised narratively, according to each study’s aim for assessing the impact of handheld computer use. Results We included seven randomised trials investigating medical or nursing staffs’ use of Personal Digital Assistants. Effectiveness was demonstrated across three distinct functions that emerged from the data: accessing information for clinical knowledge, adherence to guidelines and diagnostic decision making. When healthcare professionals used handheld computers to access clinical information, their knowledge improved significantly more than peers who used paper resources. When clinical guideline recommendations were presented on handheld computers, clinicians made significantly safer prescribing decisions and adhered more closely to recommendations than peers using paper resources. Finally, healthcare professionals made significantly more appropriate diagnostic decisions using clinical decision making tools on handheld computers compared to colleagues who did not have access to these tools. For these clinical decisions, the numbers need to test/screen were all less than 11. Conclusion Healthcare professionals’ use of handheld computers may improve their information seeking, adherence to guidelines and clinical decision making. Handheld computers can provide real time access to and analysis of clinical information. The integration of clinical decision support systems within handheld computers offers clinicians the highest level of synthesised evidence at the point of care. Future research is needed to replicate these early results and to identify beneficial clinical outcomes. PMID:24998515
A decision-support system for the analysis of clinical practice patterns.
Balas, E A; Li, Z R; Mitchell, J A; Spencer, D C; Brent, E; Ewigman, B G
1994-01-01
Several studies documented substantial variation in medical practice patterns, but physicians often do not have adequate information on the cumulative clinical and financial effects of their decisions. The purpose of developing an expert system for the analysis of clinical practice patterns was to assist providers in analyzing and improving the process and outcome of patient care. The developed QFES (Quality Feedback Expert System) helps users in the definition and evaluation of measurable quality improvement objectives. Based on objectives and actual clinical data, several measures can be calculated (utilization of procedures, annualized cost effect of using a particular procedure, and expected utilization based on peer-comparison and case-mix adjustment). The quality management rules help to detect important discrepancies among members of the selected provider group and compare performance with objectives. The system incorporates a variety of data and knowledge bases: (i) clinical data on actual practice patterns, (ii) frames of quality parameters derived from clinical practice guidelines, and (iii) rules of quality management for data analysis. An analysis of practice patterns of 12 family physicians in the management of urinary tract infections illustrates the use of the system.
Zarinabad, Niloufar; Meeus, Emma M; Manias, Karen; Foster, Katharine; Peet, Andrew
2018-05-02
Advances in magnetic resonance imaging and the introduction of clinical decision support systems has underlined the need for an analysis tool to extract and analyze relevant information from magnetic resonance imaging data to aid decision making, prevent errors, and enhance health care. The aim of this study was to design and develop a modular medical image region of interest analysis tool and repository (MIROR) for automatic processing, classification, evaluation, and representation of advanced magnetic resonance imaging data. The clinical decision support system was developed and evaluated for diffusion-weighted imaging of body tumors in children (cohort of 48 children, with 37 malignant and 11 benign tumors). Mevislab software and Python have been used for the development of MIROR. Regions of interests were drawn around benign and malignant body tumors on different diffusion parametric maps, and extracted information was used to discriminate the malignant tumors from benign tumors. Using MIROR, the various histogram parameters derived for each tumor case when compared with the information in the repository provided additional information for tumor characterization and facilitated the discrimination between benign and malignant tumors. Clinical decision support system cross-validation showed high sensitivity and specificity in discriminating between these tumor groups using histogram parameters. MIROR, as a diagnostic tool and repository, allowed the interpretation and analysis of magnetic resonance imaging images to be more accessible and comprehensive for clinicians. It aims to increase clinicians' skillset by introducing newer techniques and up-to-date findings to their repertoire and make information from previous cases available to aid decision making. The modular-based format of the tool allows integration of analyses that are not readily available clinically and streamlines the future developments. ©Niloufar Zarinabad, Emma M Meeus, Karen Manias, Katharine Foster, Andrew Peet. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 02.05.2018.
Clinical decision-making by midwives: managing case complexity.
Cioffi, J; Markham, R
1997-02-01
In making clinical judgements, it is argued that midwives use 'shortcuts' or heuristics based on estimated probabilities to simplify the decision-making task. Midwives (n = 30) were given simulated patient assessment situations of high and low complexity and were required to think aloud. Analysis of verbal protocols showed that subjective probability judgements (heuristics) were used more frequently in the high than low complexity case and predominated in the last quarter of the assessment period for the high complexity case. 'Representativeness' was identified more frequently in the high than in the low case, but was the dominant heuristic in both. Reports completed after each simulation suggest that heuristics based on memory for particular conditions affect decisions. It is concluded that midwives use heuristics, derived mainly from their clinical experiences, in an attempt to save cognitive effort and to facilitate reasonably accurate decisions in the decision-making process.
Postnatal Psychosocial Assessment and Clinical Decision-Making, a Descriptive Study.
Sims, Deborah; Fowler, Cathrine
2018-05-18
The aim of this study is to describe experienced child and family health nurses' clinical decision-making during a postnatal psychosocial assessment. Maternal emotional wellbeing in the postnatal year optimises parenting and promotes infant development. Psychosocial assessment potentially enables early intervention and reduces the risk of a mental disorder occurring during this time of change. Assessment accuracy, and the interventions used are determined by the standard of nursing decision-making. A qualitative methodology was employed to explore decision-making behaviour when conducting a postnatal psychosocial assessment. This study was conducted in an Australian early parenting organisation. Twelve experienced child and family health nurses were interviewed. A detailed description of a postnatal psychosocial assessment process was obtained using a critical incident technique. Template analysis was used to determine the information domains the nurses accessed, and content analysis was used to determine the nurses' thinking strategies, to make clinical decisions from this assessment. The nurses described 24 domains of information and used 17 thinking strategies, in a variety of combinations. The four information domains most commonly used were parenting, assessment tools, women-determined issues and sleep. The seven thinking strategies most commonly used were searching for information, forming relationships between the information, recognising a pattern, drawing a conclusion, setting priorities, providing explanations for the information and judging the value of the information. The variety and complexity of the clinical decision-making involved in postnatal psychosocial assessment confirms that the nurses use information appropriately and within their scope of nursing practice. The standard of clinical decision-making determines the results of the assessment and the optimal access to care. Knowledge of the information domains and the decision-making strategies that experienced nurses use for psychosocial assessment potentially improves practice by providing a framework for education and mentoring. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.
Clinical and Business Intelligence: Why It's Important to Your Pharmacy.
Pinto, Brian; Fox, Brent I
2016-07-01
According to the Healthcare Information Management and Systems Society, "Clinical & Business Intelligence (C&BI) is the use and analysis of data captured in the healthcare setting to directly inform decision-making" (http://www.himss.org/library/clinical-business-intelligence). Some say that it is the right information given to the right person at the right time in the right way. No matter how you define it, the fact remains that timely access, synthesis, and visualization of clinical data have become key to how health professionals make patient care decisions and improve care delivery.
Chahine, Saad; Cristancho, Sayra; Padgett, Jessica; Lingard, Lorelei
2017-06-01
In the competency-based medical education (CBME) approach, clinical competency committees are responsible for making decisions about trainees' competence. However, we currently lack a theoretical model for group decision-making to inform this emerging assessment phenomenon. This paper proposes an organizing framework to study and guide the decision-making processes of clinical competency committees.This is an explanatory, non-exhaustive review, tailored to identify relevant theoretical and evidence-based papers related to small group decision-making. The search was conducted using Google Scholar, Web of Science, MEDLINE, ERIC, and PsycINFO for relevant literature. Using a thematic analysis, two researchers (SC & JP) met four times between April-June 2016 to consolidate the literature included in this review.Three theoretical orientations towards group decision-making emerged from the review: schema, constructivist, and social influence. Schema orientations focus on how groups use algorithms for decision-making. Constructivist orientations focus on how groups construct their shared understanding. Social influence orientations focus on how individual members influence the group's perspective on a decision. Moderators of decision-making relevant to all orientations include: guidelines, stressors, authority, and leadership.Clinical competency committees are the mechanisms by which groups of clinicians will be in charge of interpreting multiple assessment data points and coming to a shared decision about trainee competence. The way in which these committees make decisions can have huge implications for trainee progression and, ultimately, patient care. Therefore, there is a pressing need to build the science of how such group decision-making works in practice. This synthesis suggests a preliminary organizing framework that can be used in the implementation and study of clinical competency committees.
Ludin, Salizar Mohamed
2018-02-01
A critical thinker may not necessarily be a good decision-maker, but critical care nurses are expected to utilise outstanding critical thinking skills in making complex clinical judgements. Studies have shown that critical care nurses' decisions focus mainly on doing rather than reflecting. To date, the link between critical care nurses' critical thinking and decision-making has not been examined closely in Malaysia. To understand whether critical care nurses' critical thinking disposition affects their clinical decision-making skills. This was a cross-sectional study in which Malay and English translations of the Short Form-Critical Thinking Disposition Inventory-Chinese Version (SF-CTDI-CV) and the Clinical Decision-making Nursing Scale (CDMNS) were used to collect data from 113 nurses working in seven critical care units of a tertiary hospital on the east coast of Malaysia. Participants were recruited through purposive sampling in October 2015. Critical care nurses perceived both their critical thinking disposition and decision-making skills to be high, with a total score of 71.5 and a mean of 48.55 for the SF-CTDI-CV, and a total score of 161 and a mean of 119.77 for the CDMNS. One-way ANOVA test results showed that while age, gender, ethnicity, education level and working experience factors significantly impacted critical thinking (p<0.05), only age and working experience significantly impacted clinical decision-making (p<0.05). Pearson's correlation analysis showed a strong and positive relationship between critical care nurses' critical thinking and clinical decision-making (r=0.637, p=0.001). While this small-scale study has shown a relationship exists between critical care nurses' critical thinking disposition and clinical decision-making in one hospital, further investigation using the same measurement tools is needed into this relationship in diverse clinical contexts and with greater numbers of participants. Critical care nurses' perceived high level of critical thinking and decision-making also needs further investigation. Copyright © 2017 Elsevier Ltd. All rights reserved.
Role of pharmacoeconomic analysis in R&D decision making: when, where, how?
Miller, Paul
2005-01-01
Pharmacoeconomics is vitally important to drug manufacturers in terms of communicating to external decision-makers (payers, prescribers, patients) the value of their products, achieving regulatory and reimbursement approval and contributing to commercial success. Since development of new drugs is long, costly and risky, and decisions must be made how to allocate considerable research and development (R&D) resources, pharmacoeconomics also has an essential role informing internal decision-making (within a company) during drug development. The use of pharmacoeconomics in early development phases is likely to enhance the efficiency of R&D resource use and also provide a solid foundation for communicating product value to external decision-makers further downstream, increasing the likelihood of regulatory (reimbursement) approval and commercial success. This paper puts the case for use of pharmacoeconomic analyses earlier in the development process and outlines five techniques (clinical trial simulation [CTS], option pricing [OP], investment appraisal [IA], threshold analysis [TA] and value of information [VOI] analysis) that can provide useful input into the design of clinical development programmes, portfolio management and optimal pricing strategy. CTS can estimate efficacy and tolerability profiles before clinical data are available. OP can show the value of different clinical programme designs, sequencing of studies and stop decisions. IA can compare expected net present value (NPV) of different product profiles or study designs. TA can be used to understand development drug profile requirements given partial data. VOI can assist risk management by quantifying uncertainty and assessing the economic viability of gathering further information on the development drug. No amount of pharmacoeconomic data can make a bad drug good; what it can do is enhance the drug developers understanding of the characteristics of that drug. Decision-making, in light of this information, is likely to be better than that without it, whether it leads to faster termination of uneconomic projects or the allocation of more appropriate resources to attractive projects.
Bucknall, Tracey K; Forbes, Helen; Phillips, Nicole M; Hewitt, Nicky A; Cooper, Simon; Bogossian, Fiona
2016-10-01
The aim of this study was to examine the decision-making of nursing students during team based simulations on patient deterioration to determine the sources of information, the types of decisions made and the influences underpinning their decisions. Missed, misinterpreted or mismanaged physiological signs of deterioration in hospitalized patients lead to costly serious adverse events. Not surprisingly, an increased focus on clinical education and graduate nurse work readiness has resulted. A descriptive exploratory design. Clinical simulation laboratories in three Australian universities were used to run team based simulations with a patient actor. A convenience sample of 97 final-year nursing students completed simulations, with three students forming a team. Four teams from each university were randomly selected for detailed analysis. Cued recall during video review of team based simulation exercises to elicit descriptions of individual and team based decision-making and reflections on performance were audio-recorded post simulation (2012) and transcribed. Students recalled 11 types of decisions, including: information seeking; patient assessment; diagnostic; intervention/treatment; evaluation; escalation; prediction; planning; collaboration; communication and reflective. Patient distress, uncertainty and a lack of knowledge were frequently recalled influences on decisions. Incomplete information, premature diagnosis and a failure to consider alternatives when caring for patients is likely to lead to poor quality decisions. All health professionals have a responsibility in recognizing and responding to clinical deterioration within their scope of practice. A typology of nursing students' decision-making in teams, in this context, highlights the importance of individual knowledge, leadership and communication. © 2016 John Wiley & Sons Ltd.
Welch, Lisa C; Lutfey, Karen E; Gerstenberger, Eric; Grace, Matthew
2012-09-01
Nonmedical factors and diagnostic certainty contribute to variation in clinical decision making, but the process by which this occurs remains unclear. We examine how physicians' interpretations of patient sex-gender affect diagnostic certainty and, in turn, decision making for coronary heart disease. Data are from a factorial experiment of 256 physicians who viewed 1 of 16 video vignettes with different patient-actors presenting the same symptoms of coronary heart disease. Physician participants completed a structured interview and provided a narrative about their decision-making processes. Quantitative analysis showed that diagnostic uncertainty reduces the likelihood that physicians will order tests and medications appropriate for an urgent cardiac condition in particular. Qualitative analysis revealed that a subset of physicians applied knowledge that women have "atypical symptoms" as a generalization, which engendered uncertainty for some. Findings are discussed in relation to social-psychological processes that underlie clinical decision making and the social framing of medical knowledge.
Patel, Vaishali N; Riley, Anne W
2007-10-01
A multiple case study was conducted to examine how staff in child out-of-home care programs used data from an Outcomes Management System (OMS) and other sources to inform decision-making. Data collection consisted of thirty-seven semi-structured interviews with clinicians, managers, and directors from two treatment foster care programs and two residential treatment centers, and individuals involved with developing the OMS; and observations of clinical and quality management meetings. Case study and grounded theory methodology guided analyses. The application of qualitative data analysis software is described. Results show that although staff rarely used data from the OMS, they did rely on other sources of systematically collected information to inform clinical, quality management, and program decisions. Analyses of how staff used these data suggest that improving the utility of OMS will involve encouraging staff to participate in data-based decision-making, and designing and implementing OMS in a manner that reflects how decision-making processes operate.
Welch, Lisa C.; Lutfey, Karen E.; Gerstenberger, Eric; Grace, Matthew
2013-01-01
Nonmedical factors and diagnostic certainty contribute to variation in clinical decision making, but the process by which this occurs remains unclear. We examine how physicians’ interpretations of patient sex/gender affect diagnostic certainty and, in turn, decision making for coronary heart disease (CHD). Data are from a factorial experiment of 256 physicians who viewed one of 16 video vignettes with different patient-actors presenting the same CHD symptoms. Physician participants completed a structured interview and provided a narrative about their decision-making processes. Quantitative analysis showed that diagnostic uncertainty reduces the likelihood that physicians will order tests and medications appropriate for an urgent cardiac condition in particular. Qualitative analysis revealed that a subset of physicians applied knowledge that women have “atypical symptoms” as a generalization, which engendered uncertainty for some. Findings are discussed in relation to social-psychological processes that underlie clinical decision making and the social framing of medical knowledge. PMID:22933590
Barken, Tina Lien; Thygesen, Elin; Söderhamn, Ulrika
2017-12-28
Telemedicine is changing traditional nursing care, and entails nurses performing advanced and complex care within a new clinical environment, and monitoring patients at a distance. Telemedicine practice requires complex disease management, advocating that the nurses' reasoning and decision-making processes are supported. Computerised decision support systems are being used increasingly to assist reasoning and decision-making in different situations. However, little research has focused on the clinical reasoning of nurses using a computerised decision support system in a telemedicine setting. Therefore, the objective of the study is to explore the process of telemedicine nurses' clinical reasoning when using a computerised decision support system for the management of patients with chronic obstructive pulmonary disease. The factors influencing the reasoning and decision-making processes were investigated. In this ethnographic study, a combination of data collection methods, including participatory observations, the think-aloud technique, and a focus group interview was employed. Collected data were analysed using qualitative content analysis. When telemedicine nurses used a computerised decision support system for the management of patients with complex, unstable chronic obstructive pulmonary disease, two categories emerged: "the process of telemedicine nurses' reasoning to assess health change" and "the influence of the telemedicine setting on nurses' reasoning and decision-making processes". An overall theme, termed "advancing beyond the system", represented the connection between the reasoning processes and the telemedicine work and setting, where being familiar with the patient functioned as a foundation for the nurses' clinical reasoning process. In the telemedicine setting, when supported by a computerised decision support system, nurses' reasoning was enabled by the continuous flow of digital clinical data, regular video-mediated contact and shared decision-making with the patient. These factors fostered an in-depth knowledge of the patients and acted as a foundation for the nurses' reasoning process. Nurses' reasoning frequently advanced beyond the computerised decision support system recommendations. Future studies are warranted to develop more accurate algorithms, increase system maturity, and improve the integration of the digital clinical information with clinical experiences, to support telemedicine nurses' reasoning process.
Djulbegovic, Benjamin; Hozo, Iztok; Dale, William
2018-02-27
Contemporary delivery of health care is inappropriate in many ways, largely due to suboptimal Q5 decision-making. A typical approach to improve practitioners' decision-making is to develop evidence-based clinical practice guidelines (CPG) by guidelines panels, who are instructed to use their judgments to derive practice recommendations. However, mechanisms for the formulation of guideline judgments remains a "black-box" operation-a process with defined inputs and outputs but without sufficient knowledge of its internal workings. Increased explicitness and transparency in the process can be achieved by implementing CPG as clinical pathways (CPs) (also known as clinical algorithms or flow-charts). However, clinical recommendations thus derived are typically ad hoc and developed by experts in a theory-free environment. As any recommendation can be right (true positive or negative), or wrong (false positive or negative), the lack of theoretical structure precludes the quantitative assessment of the management strategies recommended by CPGs/CPs. To realize the full potential of CPGs/CPs, they need to be placed on more solid theoretical grounds. We believe this potential can be best realized by converting CPGs/CPs within the heuristic theory of decision-making, often implemented as fast-and-frugal (FFT) decision trees. This is possible because FFT heuristic strategy of decision-making can be linked to signal detection theory, evidence accumulation theory, and a threshold model of decision-making, which, in turn, allows quantitative analysis of the accuracy of clinical management strategies. Fast-and-frugal provides a simple and transparent, yet solid and robust, methodological framework connecting decision science to clinical care, a sorely needed missing link between CPGs/CPs and patient outcomes. We therefore advocate that all guidelines panels express their recommendations as CPs, which in turn should be converted into FFTs to guide clinical care. © 2018 John Wiley & Sons, Ltd.
ERIC Educational Resources Information Center
Carney, Timothy Jay
2012-01-01
A study design has been developed that employs a dual modeling approach to identify factors associated with facility-level cancer screening improvement and how this is mediated by the use of clinical decision support. This dual modeling approach combines principles of (1) Health Informatics, (2) Cancer Prevention and Control, (3) Health Services…
Benefit-Risk Analysis for Decision-Making: An Approach.
Raju, G K; Gurumurthi, K; Domike, R
2016-12-01
The analysis of benefit and risk is an important aspect of decision-making throughout the drug lifecycle. In this work, the use of a benefit-risk analysis approach to support decision-making was explored. The proposed approach builds on the qualitative US Food and Drug Administration (FDA) approach to include a more explicit analysis based on international standards and guidance that enables aggregation and comparison of benefit and risk on a common basis and a lifecycle focus. The approach is demonstrated on six decisions over the lifecycle (e.g., accelerated approval, withdrawal, and traditional approval) using two case studies: natalizumab for multiple sclerosis (MS) and bedaquiline for multidrug-resistant tuberculosis (MDR-TB). © 2016 American Society for Clinical Pharmacology and Therapeutics.
Personalized health care and health information technology policy: an exploratory analysis.
Wald, Jonathan S; Shapiro, Michael
2013-01-01
Personalized healthcare (PHC) is envisioned to enhance clinical practice decision-making using new genome-driven knowledge that tailors diagnosis, treatment, and prevention to the individual patient. In 2012, we conducted a focused environmental scan and informal interviews with fifteen experts to anticipate how PHC might impact health Information Technology (IT) policy in the United States. Findings indicatedthat PHC has a variable impact on current clinical practice, creates complex questions for providers, patients, and policy-makers, and will require a robust health IT infrastructure with advanced data architecture, clinical decision support, provider workflow tools, and re-use of clinical data for research. A number of health IT challenge areas were identified, along with five policy areas including: interoperable clinical decision support, standards for patient values and preferences, patient engagement, data transparency, and robust privacy and security.
Vickers, Andrew J; Cronin, Angel M; Elkin, Elena B; Gonen, Mithat
2008-01-01
Background Decision curve analysis is a novel method for evaluating diagnostic tests, prediction models and molecular markers. It combines the mathematical simplicity of accuracy measures, such as sensitivity and specificity, with the clinical applicability of decision analytic approaches. Most critically, decision curve analysis can be applied directly to a data set, and does not require the sort of external data on costs, benefits and preferences typically required by traditional decision analytic techniques. Methods In this paper we present several extensions to decision curve analysis including correction for overfit, confidence intervals, application to censored data (including competing risk) and calculation of decision curves directly from predicted probabilities. All of these extensions are based on straightforward methods that have previously been described in the literature for application to analogous statistical techniques. Results Simulation studies showed that repeated 10-fold crossvalidation provided the best method for correcting a decision curve for overfit. The method for applying decision curves to censored data had little bias and coverage was excellent; for competing risk, decision curves were appropriately affected by the incidence of the competing risk and the association between the competing risk and the predictor of interest. Calculation of decision curves directly from predicted probabilities led to a smoothing of the decision curve. Conclusion Decision curve analysis can be easily extended to many of the applications common to performance measures for prediction models. Software to implement decision curve analysis is provided. PMID:19036144
Vickers, Andrew J; Cronin, Angel M; Elkin, Elena B; Gonen, Mithat
2008-11-26
Decision curve analysis is a novel method for evaluating diagnostic tests, prediction models and molecular markers. It combines the mathematical simplicity of accuracy measures, such as sensitivity and specificity, with the clinical applicability of decision analytic approaches. Most critically, decision curve analysis can be applied directly to a data set, and does not require the sort of external data on costs, benefits and preferences typically required by traditional decision analytic techniques. In this paper we present several extensions to decision curve analysis including correction for overfit, confidence intervals, application to censored data (including competing risk) and calculation of decision curves directly from predicted probabilities. All of these extensions are based on straightforward methods that have previously been described in the literature for application to analogous statistical techniques. Simulation studies showed that repeated 10-fold crossvalidation provided the best method for correcting a decision curve for overfit. The method for applying decision curves to censored data had little bias and coverage was excellent; for competing risk, decision curves were appropriately affected by the incidence of the competing risk and the association between the competing risk and the predictor of interest. Calculation of decision curves directly from predicted probabilities led to a smoothing of the decision curve. Decision curve analysis can be easily extended to many of the applications common to performance measures for prediction models. Software to implement decision curve analysis is provided.
Patient participation in palliative care decisions: An ethnographic discourse analysis
Bélanger, Emmanuelle; Rodríguez, Charo; Groleau, Danielle; Légaré, France; MacDonald, Mary Ellen; Marchand, Robert
2016-01-01
The participation of patients in making decisions about their care is especially important towards the end of life because palliative care decisions involve extensive uncertainty and are heavily influenced by personal values. Yet, there is a scarcity of studies directly observing clinical interactions between palliative patients and their health care providers. In this study, we aimed to understand how patient participation in palliative care decisions is constructed through discourse in a community hospital-based palliative care team. This qualitative study combined ethnographic observations of a palliative care team with discourse analysis. Eighteen palliative care patients with cancer diagnoses, six family physicians, and two nurses were involved in the study. Multiple interactions were observed between each patient and health care providers over the course of 1 year, for a total of 101 consultations, 24 of which were audio-recorded. The analysis consisted in looking for the interpretive repertoires (i.e., familiar lines of argument used to justify actions) that were used to justify patient participation in decision-making during clinical interactions, as well as exploring their implications for decision roles and end-of-life care. Patients and their health care providers seldom addressed their decision-making roles explicitly. Rather, they constructed patient participation in palliative care decisions in a covert manner. Four interpretive repertoires were used to justify patient participation: (1) exposing uncertainty, (2) co-constructing patient preferences, (3) affirming patient autonomy, and finally (4) upholding the authority of health care providers. The results demonstrate how patients and health care providers used these arguments to negotiate their respective roles in decision-making. In conclusion, patients and health care providers used a variety of interpretive repertoires to covertly negotiate their roles in decision-making, and to legitimize decisions that shaped patients’ dying trajectories. Discourse analysis encourages awareness of the role of language in either promoting or hindering patient participation in decision-making. PMID:27882864
Patient participation in palliative care decisions: An ethnographic discourse analysis.
Bélanger, Emmanuelle; Rodríguez, Charo; Groleau, Danielle; Légaré, France; MacDonald, Mary Ellen; Marchand, Robert
2016-01-01
The participation of patients in making decisions about their care is especially important towards the end of life because palliative care decisions involve extensive uncertainty and are heavily influenced by personal values. Yet, there is a scarcity of studies directly observing clinical interactions between palliative patients and their health care providers. In this study, we aimed to understand how patient participation in palliative care decisions is constructed through discourse in a community hospital-based palliative care team. This qualitative study combined ethnographic observations of a palliative care team with discourse analysis. Eighteen palliative care patients with cancer diagnoses, six family physicians, and two nurses were involved in the study. Multiple interactions were observed between each patient and health care providers over the course of 1 year, for a total of 101 consultations, 24 of which were audio-recorded. The analysis consisted in looking for the interpretive repertoires (i.e., familiar lines of argument used to justify actions) that were used to justify patient participation in decision-making during clinical interactions, as well as exploring their implications for decision roles and end-of-life care. Patients and their health care providers seldom addressed their decision-making roles explicitly. Rather, they constructed patient participation in palliative care decisions in a covert manner. Four interpretive repertoires were used to justify patient participation: (1) exposing uncertainty, (2) co-constructing patient preferences, (3) affirming patient autonomy, and finally (4) upholding the authority of health care providers. The results demonstrate how patients and health care providers used these arguments to negotiate their respective roles in decision-making. In conclusion, patients and health care providers used a variety of interpretive repertoires to covertly negotiate their roles in decision-making, and to legitimize decisions that shaped patients' dying trajectories. Discourse analysis encourages awareness of the role of language in either promoting or hindering patient participation in decision-making.
Clinical reasoning: concept analysis.
Simmons, Barbara
2010-05-01
This paper is a report of a concept analysis of clinical reasoning in nursing. Clinical reasoning is an ambiguous term that is often used synonymously with decision-making and clinical judgment. Clinical reasoning has not been clearly defined in the literature. Healthcare settings are increasingly filled with uncertainty, risk and complexity due to increased patient acuity, multiple comorbidities, and enhanced use of technology, all of which require clinical reasoning. Data sources. Literature for this concept analysis was retrieved from several databases, including CINAHL, PubMed, PsycINFO, ERIC and OvidMEDLINE, for the years 1980 to 2008. Rodgers's evolutionary method of concept analysis was used because of its applicability to concepts that are still evolving. Multiple terms have been used synonymously to describe the thinking skills that nurses use. Research in the past 20 years has elucidated differences among these terms and identified the cognitive processes that precede judgment and decision-making. Our concept analysis defines one of these terms, 'clinical reasoning,' as a complex process that uses cognition, metacognition, and discipline-specific knowledge to gather and analyse patient information, evaluate its significance, and weigh alternative actions. This concept analysis provides a middle-range descriptive theory of clinical reasoning in nursing that helps clarify meaning and gives direction for future research. Appropriate instruments to operationalize the concept need to be developed. Research is needed to identify additional variables that have an impact on clinical reasoning and what are the consequences of clinical reasoning in specific situations.
Forzley, Brian; Er, Lee; Chiu, Helen Hl; Djurdjev, Ognjenka; Martinusen, Dan; Carson, Rachel C; Hargrove, Gaylene; Levin, Adeera; Karim, Mohamud
2018-02-01
End-stage kidney disease is associated with poor prognosis. Health care professionals must be prepared to address end-of-life issues and identify those at high risk for dying. A 6-month mortality prediction model for patients on dialysis derived in the United States is used but has not been externally validated. We aimed to assess the external validity and clinical utility in an independent cohort in Canada. We examined the performance of the published 6-month mortality prediction model, using discrimination, calibration, and decision curve analyses. Data were derived from a cohort of 374 prevalent dialysis patients in two regions of British Columbia, Canada, which included serum albumin, age, peripheral vascular disease, dementia, and answers to the "the surprise question" ("Would I be surprised if this patient died within the next year?"). The observed mortality in the validation cohort was 11.5% at 6 months. The prediction model had reasonable discrimination (c-stat = 0.70) but poor calibration (calibration-in-the-large = -0.53 (95% confidence interval: -0.88, -0.18); calibration slope = 0.57 (95% confidence interval: 0.31, 0.83)) in our data. Decision curve analysis showed the model only has added value in guiding clinical decision in a small range of threshold probabilities: 8%-20%. Despite reasonable discrimination, the prediction model has poor calibration in this external study cohort; thus, it may have limited clinical utility in settings outside of where it was derived. Decision curve analysis clarifies limitations in clinical utility not apparent by receiver operating characteristic curve analysis. This study highlights the importance of external validation of prediction models prior to routine use in clinical practice.
Calder, Lisa A; Forster, Alan J; Stiell, Ian G; Carr, Laura K; Brehaut, Jamie C; Perry, Jeffrey J; Vaillancourt, Christian; Croskerry, Patrick
2012-10-01
Dual-process psychological theories argue that clinical decision making is achieved through a combination of experiential (fast and intuitive) and rational (slower and systematic) cognitive processes. To determine whether emergency physicians perceived their clinical decisions in general to be more experiential or rational and how this compared with other physicians. A validated psychometric tool, the Rational Experiential Inventory (REI-40), was sent through postal mail to all emergency physicians registered with the College of Physicians and Surgeons of Ontario, according to their website in November 2009. Forty statements were ranked on a Likert scale from 1 (Definitely False) to 5 (Definitely True). An initial survey was sent out, followed by reminder cards and a second survey to non-respondents. Analysis included descriptive statistics, Student t tests, analysis of variance and comparison of mean scores with those of cardiologists from New Zealand. The response rate in this study was 46.9% (434/925). The respondents' median age was 41-50 years; they were mostly men (72.6%) and most had more than 10 years of clinical experience (66.8%). The mean REI-40 rational scores were higher than the experiential scores (3.93/5 (SD 0.35) vs 3.33/5 (SD 0.49), p<0.0001), similar to the mean scores of cardiologists from New Zealand (mean rational 3.93/5, mean experiential 3.05/5). The mean experiential scores were significantly higher for female respondents than for male respondents (3.40/5 (SD 0.49) vs 3.30/5 (SD 0.48), p=0.003). Overall, emergency physicians favoured rational decision making rather than experiential decision making; however, female emergency physicians had higher experiential scores than male emergency physicians. This has important implications for future knowledge translation and decision support efforts among emergency physicians.
Sheehan, Barbara; Nigrovic, Lise E; Dayan, Peter S; Kuppermann, Nathan; Ballard, Dustin W; Alessandrini, Evaline; Bajaj, Lalit; Goldberg, Howard; Hoffman, Jeffrey; Offerman, Steven R; Mark, Dustin G; Swietlik, Marguerite; Tham, Eric; Tzimenatos, Leah; Vinson, David R; Jones, Grant S; Bakken, Suzanne
2013-10-01
Integration of clinical decision support services (CDSS) into electronic health records (EHRs) may be integral to widespread dissemination and use of clinical prediction rules in the emergency department (ED). However, the best way to design such services to maximize their usefulness in such a complex setting is poorly understood. We conducted a multi-site cross-sectional qualitative study whose aim was to describe the sociotechnical environment in the ED to inform the design of a CDSS intervention to implement the Pediatric Emergency Care Applied Research Network (PECARN) clinical prediction rules for children with minor blunt head trauma. Informed by a sociotechnical model consisting of eight dimensions, we conducted focus groups, individual interviews and workflow observations in 11 EDs, of which 5 were located in academic medical centers and 6 were in community hospitals. A total of 126 ED clinicians, information technology specialists, and administrators participated. We clustered data into 19 categories of sociotechnical factors through a process of thematic analysis and subsequently organized the categories into a sociotechnical matrix consisting of three high-level sociotechnical dimensions (workflow and communication, organizational factors, human factors) and three themes (interdisciplinary assessment processes, clinical practices related to prediction rules, EHR as a decision support tool). Design challenges that emerged from the analysis included the need to use structured data fields to support data capture and re-use while maintaining efficient care processes, supporting interdisciplinary communication, and facilitating family-clinician interaction for decision-making. Copyright © 2013 Elsevier Inc. All rights reserved.
Bozzaro, Claudia; Schildmann, Jan
2018-04-21
Palliative sedation is an increasingly used and, simultaneously, challenging practice at the end of life. Many controversies associated with this therapy are rooted in implicit differences regarding the understanding of "suffering" as prerequisite for palliative sedation. The aim of this paper is to inform the current debates by a conceptual analysis of two different philosophical accounts of suffering, (1) the subjective and holistic concept and (2) the objective and gradual concept and by a clinical-ethical analysis of the implications of each account for decisions about palliative sedation. We will show that while the subjective and holistic account of suffering fits well with the holistic approach of palliative care, there are considerable challenges to justify limits to requests for palliative sedation. By contrast, the objective and gradual account fits well with the need for an objective basis for clinical decisions in the context of palliative sedation, but runs the risk of falling short when considering the individual and subjective experience of suffering at the end of life. We will conclude with a plea for the necessity of further combined conceptual and empirical research to develop a sound and feasible understanding of suffering which can contribute to consistent decision-making about palliative sedation. Copyright © 2018. Published by Elsevier Inc.
Chow, S-J; Sciberras, E; Gillam, L H; Green, J; Efron, D
2014-05-01
Attention-deficit/hyperactivity disorder (ADHD) is now the most common reason for a child to present to a paediatrician in Australia. Stimulant medications are commonly prescribed for children with ADHD, to reduce symptoms and improve function. In this study we investigated the factors that influence paediatricians' decisions about prescribing stimulant medications. In-depth, semi-structured interviews were conducted with paediatricians (n = 13) who were purposively recruited so as to sample a broad demographic of paediatricians working in diverse clinical settings. Paediatricians were recruited from public outpatient and private paediatrician clinics in Victoria, Australia. The interviews were audio-recorded and transcribed verbatim for thematic analysis. Paediatricians also completed a questionnaire describing their demographic and practice characteristics. Our findings showed that the decision to prescribe is a dynamic process involving two key domains: (1) weighing up clinical factors; and (2) interacting with parents and the patient along the journey to prescribing. Five themes relating to this process emerged from data analysis: comprehensive assessments that include history, examination and information from others; influencing factors such as functional impairment and social inclusion; previous success; facilitating parental understanding including addressing myths and parental confusion; and decision-making model. Paediatricians' decisions to prescribe stimulant medications are influenced by multiple factors that operate concurrently and interdependently. Paediatricians do not make decisions about prescribing in isolation; rather, they actively involve parents, teachers and patients, to arrive at a collective, well-informed decision. © 2013 John Wiley & Sons Ltd.
DECISION-COMPONENTS OF NICE'S TECHNOLOGY APPRAISALS ASSESSMENT FRAMEWORK.
de Folter, Joost; Trusheim, Mark; Jonsson, Pall; Garner, Sarah
2018-01-01
Value assessment frameworks have gained prominence recently in the context of U.S. healthcare. Such frameworks set out a series of factors that are considered in funding decisions. The UK's National Institute of Health and Care Excellence (NICE) is an established health technology assessment (HTA) agency. We present a novel application of text analysis that characterizes NICE's Technology Appraisals in the context of the newer assessment frameworks and present the results in a visual way. A total of 243 documents of NICE's medicines guidance from 2007 to 2016 were analyzed. Text analysis was used to identify a hierarchical set of decision factors considered in the assessments. The frequency of decision factors stated in the documents was determined and their association with terms related to uncertainty. The results were incorporated into visual representations of hierarchical factors. We identified 125 decision factors, and hierarchically grouped these into eight domains: Clinical Effectiveness, Cost Effectiveness, Condition, Current Practice, Clinical Need, New Treatment, Studies, and Other Factors. Textual analysis showed all domains appeared consistently in the guidance documents. Many factors were commonly associated with terms relating to uncertainty. A series of visual representations was created. This study reveals the complexity and consistency of NICE's decision-making processes and demonstrates that cost effectiveness is not the only decision-criteria. The study highlights the importance of processes and methodology that can take both quantitative and qualitative information into account. Visualizations can help effectively communicate this complex information during the decision-making process and subsequently to stakeholders.
Cook, S A; Rosser, R; Meah, S; James, M I; Salmon, P
2003-07-01
Because of increasing demand for publicly funded elective cosmetic surgery, clinical decision guidelines have been developed to select those patients who should receive it. The aims of this study were to identify: the main characteristics of such guidelines; whether and how they influence clinical decision making; and ways in which they should be improved. UK health authorities were asked for their current guidelines for elective cosmetic surgery and, in a single plastic surgery unit, we examined the impact of its guidelines by observing consultations and interviewing surgeons and managers. Of 115 authorities approached, 32 reported using guidelines and provided sufficient information for analysis. Guidelines mostly concerned arbitrary sets of cosmetic procedures and lacked reference to an evidence base. They allowed surgery for specified anatomical, functional or symptomatic reasons, but these indications varied between guidelines. Most guidelines also permitted surgery 'exceptionally' for psychological reasons. The guidelines that were studied in detail did not appreciably influence surgeons' decisions, which reflected criteria that were not cited in the guidelines, including cost of the procedure and whether patients sought restoration or improvement of their appearance. Decision guidelines in this area have several limitations. Future guidelines should: include all cosmetic procedures; be informed by a broad range of evidence; and, arguably, include several nonclinical criteria that currently inform surgeons' decision-making.
Dying cancer patients talk about physician and patient roles in DNR decision making.
Eliott, Jaklin A; Olver, Ian
2011-06-01
Within medical and bioethical discourse, there are many models depicting the relationships between, and roles of, physician and patient in medical decision making. Contestation similarly exists over the roles of physician and patient with regard to the decision not to provide cardiopulmonary resuscitation (CPR) following cardiac arrest [the do-not-resuscitate or do-not-resuscitate (DNR) decision], but there is little analysis of patient perspectives. Analyse what patients with cancer within weeks before dying say about the decision to forego CPR and the roles of patient and physician in this decision. Discursive analysis of qualitative data gathered during semi-structured interviews with 28 adult cancer patients close to death and attending palliative or oncology clinics of an Australian teaching hospital. Participants' descriptions of appropriate patient or physician roles in decisions about CPR appeared related to how they conceptualized the decision: as a personal or a medical issue, with patient and doctor respectively identified as appropriate decision makers; or alternatively, both medical and personal, with various roles assigned embodying different versions of a shared decision-making process. Participants' endorsement of physicians as decision makers rested upon physicians' enactment of the rational, knowledgeable and compassionate expert, which legitimized entrusting them to make the DNR decision. Where this was called into question, physicians were positioned as inappropriate decision makers. When patients' and physicians' understandings of the best decision, or of the preferred role of either party, diverge, conflict may ensue. In order to elicit and negotiate with patient preferences, flexibility is required during clinical interactions about decision making. © 2010 Blackwell Publishing Ltd.
Suebnukarn, Siriwan; Chanakarn, Piyawadee; Phisutphatthana, Sirada; Pongpatarat, Kanchala; Wongwaithongdee, Udom; Oupadissakoon, Chanekrid
2015-12-01
An understanding of the processes of clinical decision-making is essential for the development of health information technology. In this study we have analysed the acquisition of information during decision-making in oral surgery, and analysed cognitive tasks using a "think-aloud" protocol. We studied the techniques of processing information that were used by novices and experts as they completed 4 oral surgical cases modelled from data obtained from electronic hospital records. We studied 2 phases of an oral surgeon's preoperative practice including the "diagnosis and planning of treatment" and "preparing for a procedure". A framework analysis approach was used to analyse the qualitative data, and a descriptive statistical analysis was made of the quantitative data. The results showed that novice surgeons used hypotheticodeductive reasoning, whereas experts recognised patterns to diagnose and manage patients. Novices provided less detail when they prepared for a procedure. Concepts regarding "signs", "importance", "decisions", and "process" occurred most often during acquisition of information by both novices and experts. Based on these results, we formulated recommendations for the design of clinical information technology that would help to improve the acquisition of clinical information required by oral surgeons at all levels of expertise in their clinical decision-making. Copyright © 2015 The British Association of Oral and Maxillofacial Surgeons. Published by Elsevier Ltd. All rights reserved.
Intuition: A Concept Analysis.
Chilcote, Deborah R
2017-01-01
The purpose of this article is to conceptually examine intuition; identify the importance of intuition in nursing education, clinical practice, and patient care; encourage acceptance of the use of intuition; and add to the body of nursing knowledge. Nurses often report using intuition when making clinical decisions. Intuition is a rapid, unconscious process based in global knowledge that views the patient holistically while synthesizing information to improve patient outcomes. However, with the advent of evidence-based practice (EBP), the use of intuition has become undervalued in nursing. Walker and Avant's framework was used to analyze intuition. A literature search from 1987 to 2014 was conducted using the following keywords: intuition, intuition and nursing, clinical decision making, clinical decision making and intuition, patient outcomes, EBP, and analytical thinking. The use of intuition is reported by nurses, but is not legitimized within the nursing profession. Defining attributes of intuition are an unconscious, holistic knowledge gathered without using an analytical process and knowledge derived through synthesis, not analysis. Consequences include verification of intuition through an analytical process and translating that knowledge into a course of action. This article supports the use of intuition in nursing by offering clarity to the concept, adds to the nursing knowledge base, encourages a holistic view of the patient during clinical decision making, and encourages nurse educators to promote the use of intuition. © 2016 Wiley Periodicals, Inc.
Spaulding, William; Deogun, Jitender
2011-09-01
Personalization of treatment is a current strategic goal for improving health care. Integrated treatment approaches such as psychiatric rehabilitation benefit from personalization because they involve matching diverse arrays of treatment options to individually unique profiles of need. The need for personalization is evident in the heterogeneity of people with severe mental illness and in the findings of experimental psychopathology. One pathway to personalization lies in analysis of the judgments and decision making of human experts and other participants as they respond to complex circumstances in pursuit of treatment and rehabilitation goals. Such analysis is aided by computer simulation of human decision making, which in turn informs development of computerized clinical decision support systems. This inspires a research program involving concurrent development of databases, domain ontology, and problem-solving algorithms, toward the goal of personalizing psychiatric rehabilitation through human collaboration with intelligent cyber systems. The immediate hurdle is to demonstrate that clinical decisions beyond diagnosis really do affect outcome. This can be done by supporting the hypothesis that a human treatment team with access to a reasonably comprehensive clinical database that tracks patient status and treatment response over time achieves better outcome than a treatment team without such access, in a controlled experimental trial. Provided the hypothesis can be supported, the near future will see prototype systems that can construct an integrated assessment, formulation, and rehabilitation plan from clinical assessment data and contextual information. This will lead to advanced systems that collaborate with human decision makers to personalize psychiatric rehabilitation and optimize outcome.
Palmer-Wackerly, Angela L; Krieger, Janice L; Rhodes, Nancy D
2017-01-01
Cancer patients rely on multiple sources of support when making treatment decisions; however, most research studies examine the influence of health care provider support while the influence of family member support is understudied. The current study fills this gap by examining the influence of health care providers and partners on decision-making satisfaction. In a cross-sectional study via an online Qualtrics panel, we surveyed cancer patients who reported that they had a spouse or romantic partner when making cancer treatment decisions (n = 479). Decisional support was measured using 5-point, single-item scales for emotional support, informational support, informational-advice support, and appraisal support. Decision-making satisfaction was measured using Holmes-Rovner and colleagues' (1996) Satisfaction With Decision Scale. We conducted a mediated regression analysis to examine treatment decision-making satisfaction for all participants and a moderated mediation analysis to examine treatment satisfaction among those patients offered a clinical trial. Results indicated that partner support significantly and partially mediated the relationship between health care provider support and patients' decision-making satisfaction but that results did not vary by enrollment in a clinical trial. This study shows how and why decisional support from partners affects communication between health care providers and cancer patients.
Abuzour, Aseel S; Lewis, Penny J; Tully, Mary P
2018-03-01
In the United Kingdom, pharmacist and nurse independent prescribers are responsible for both the clinical assessment of and prescribing for patients. Prescribing is a complex skill that entails the application of knowledge, skills, and clinical reasoning to arrive at a clinically appropriate decision. Decision-making is influenced and informed by many factors. This study, the first of its kind, explores what factors influence pharmacist and nurse independent prescribers during the process of clinical reasoning. A think-aloud methodology immediately followed by a semi-structured interview was conducted with 11 active nurse and 10 pharmacist independent prescribers working in secondary care. Each participant was presented with validated clinical vignettes for the think-aloud stage. Participants chose the clinical therapeutic areas for the vignettes, based on their self-perceived competencies. Data were audio-recorded, transcribed verbatim, and a constant-comparative approach was used for analysis. Influences on clinical reasoning were broadly categorised into themes: social interaction, intrinsic, and contextual factors. These themes showed that intrinsic, sociocultural, and contextual aspects heavily influenced the clinical reasoning processes of prescribers. For example, prescribers were aware of treatment pathways, but chose to refer patient cases to avoid making the final prescribing decision. Exploration of this behaviour in the interviews revealed that previous experience and attitudes such as confidence and cautiousness associated with responsibility were strong influencers within the decision-making process. In addition, strengthening the professional identity of prescribers could be achieved through collaborative work with interprofessional healthcare teams to orient their professional practice from within the profession. Findings from this study can be used to inform the education, training, and practice of independent prescribers to improve healthcare services by improving their professional and interprofessional development.
Dying cancer patients talk about physician and patient roles in DNR decision making
Eliott, Jaklin A.; Olver, Ian
2011-01-01
Abstract Background Within medical and bioethical discourse, there are many models depicting the relationships between, and roles of, physician and patient in medical decision making. Contestation similarly exists over the roles of physician and patient with regard to the decision not to provide cardiopulmonary resuscitation (CPR) following cardiac arrest [the do‐not‐resuscitate or do‐not‐resuscitate (DNR) decision], but there is little analysis of patient perspectives. Objective Analyse what patients with cancer within weeks before dying say about the decision to forego CPR and the roles of patient and physician in this decision. Design and participants Discursive analysis of qualitative data gathered during semi‐structured interviews with 28 adult cancer patients close to death and attending palliative or oncology clinics of an Australian teaching hospital. Results Participants’ descriptions of appropriate patient or physician roles in decisions about CPR appeared related to how they conceptualized the decision: as a personal or a medical issue, with patient and doctor respectively identified as appropriate decision makers; or alternatively, both medical and personal, with various roles assigned embodying different versions of a shared decision‐making process. Participants’ endorsement of physicians as decision makers rested upon physicians’ enactment of the rational, knowledgeable and compassionate expert, which legitimized entrusting them to make the DNR decision. Where this was called into question, physicians were positioned as inappropriate decision makers. Conclusion When patients’ and physicians’ understandings of the best decision, or of the preferred role of either party, diverge, conflict may ensue. In order to elicit and negotiate with patient preferences, flexibility is required during clinical interactions about decision making. PMID:20860782
Epidemiology and Clinical Research Design, Part 2: Principles.
Manja, Veena; Lakshminrusimha, Satyan
This is the third article covering core knowledge in scholarly activities for neonatal physicians. In this article, we discuss various principles of epidemiology and clinical research design. A basic knowledge of these principles is necessary for conducting clinical research and for proper interpretation of studies. This article reviews bias and confounding, causation, incidence and prevalence, decision analysis, cost-effectiveness, sensitivity analysis, and measurement.
de Greef-van der Sandt, I; Newgreen, D; Schaddelee, M; Dorrepaal, C; Martina, R; Ridder, A; van Maanen, R
2016-04-01
A multicriteria decision analysis (MCDA) approach was developed and used to estimate the benefit-risk of solifenacin and mirabegron and their combination in the treatment of overactive bladder (OAB). The objectives were 1) to develop an MCDA tool to compare drug effects in OAB quantitatively, 2) to establish transparency in the evaluation of the benefit-risk profile of various dose combinations, and 3) to quantify the added value of combination use compared to monotherapies. The MCDA model was developed using efficacy, safety, and tolerability attributes and the results of a phase II factorial design combination study were evaluated. Combinations of solifenacin 5 mg and mirabegron 25 mg and mirabegron 50 (5+25 and 5+50) scored the highest clinical utility and supported combination therapy development of solifenacin and mirabegron for phase III clinical development at these dose regimens. This case study underlines the benefit of using a quantitative approach in clinical drug development programs. © 2015 The American Society for Clinical Pharmacology and Therapeutics.
Willis, Sarah R; Ahmed, Hashim U; Moore, Caroline M; Donaldson, Ian; Emberton, Mark; Miners, Alec H; van der Meulen, Jan
2014-01-01
Objective To compare the diagnostic outcomes of the current approach of transrectal ultrasound (TRUS)-guided biopsy in men with suspected prostate cancer to an alternative approach using multiparametric MRI (mpMRI), followed by MRI-targeted biopsy if positive. Design Clinical decision analysis was used to synthesise data from recently emerging evidence in a format that is relevant for clinical decision making. Population A hypothetical cohort of 1000 men with suspected prostate cancer. Interventions mpMRI and, if positive, MRI-targeted biopsy compared with TRUS-guided biopsy in all men. Outcome measures We report the number of men expected to undergo a biopsy as well as the numbers of correctly identified patients with or without prostate cancer. A probabilistic sensitivity analysis was carried out using Monte Carlo simulation to explore the impact of statistical uncertainty in the diagnostic parameters. Results In 1000 men, mpMRI followed by MRI-targeted biopsy ‘clinically dominates’ TRUS-guided biopsy as it results in fewer expected biopsies (600 vs 1000), more men being correctly identified as having clinically significant cancer (320 vs 250), and fewer men being falsely identified (20 vs 50). The mpMRI-based strategy dominated TRUS-guided biopsy in 86% of the simulations in the probabilistic sensitivity analysis. Conclusions Our analysis suggests that mpMRI followed by MRI-targeted biopsy is likely to result in fewer and better biopsies than TRUS-guided biopsy. Future research in prostate cancer should focus on providing precise estimates of key diagnostic parameters. PMID:24934207
González-Ferrer, A; Peleg, M; Marcos, M; Maldonado, J A
2016-07-01
Delivering patient-specific decision-support based on computer-interpretable guidelines (CIGs) requires mapping CIG clinical statements (data items, clinical recommendations) into patients' data. This is most effectively done via intermediate data schemas, which enable querying the data according to the semantics of a shared standard intermediate schema. This study aims to evaluate the use of HL7 virtual medical record (vMR) and openEHR archetypes as intermediate schemas for capturing clinical statements from CIGs that are mappable to electronic health records (EHRs) containing patient data and patient-specific recommendations. Using qualitative research methods, we analyzed the encoding of ten representative clinical statements taken from two CIGs used in real decision-support systems into two health information models (openEHR archetypes and HL7 vMR instances) by four experienced informaticians. Discussion among the modelers about each case study example greatly increased our understanding of the capabilities of these standards, which we share in this educational paper. Differing in content and structure, the openEHR archetypes were found to contain a greater level of representational detail and structure while the vMR representations took fewer steps to complete. The use of openEHR in the encoding of CIG clinical statements could potentially facilitate applications other than decision-support, including intelligent data analysis and integration of additional properties of data items from existing EHRs. On the other hand, due to their smaller size and fewer details, the use of vMR potentially supports quicker mapping of EHR data into clinical statements.
ERIC Educational Resources Information Center
Snowden, Jessica A.; Leon, Scott C.; Bryant, Fred B.; Lyons, John S.
2007-01-01
This study explored clinical and nonclinical predictors of inpatient hospital admission decisions across a sample of children in foster care over 4 years (N = 13,245). Forty-eight percent of participants were female and the mean age was 13.4 (SD = 3.5 years). Optimal data analysis (Yarnold & Soltysik, 2005) was used to construct a nonlinear…
Smith, Michael W; Brown, Charnetta; Virani, Salim S; Weir, Charlene R; Petersen, Laura A; Kelly, Natalie; Akeroyd, Julia; Garvin, Jennifer H
2018-04-01
The recognition of and response to undertreatment of heart failure (HF) patients can be complicated. A clinical reminder can facilitate use of guideline-concordant β-blocker titration for HF patients with depressed ejection fraction. However, the design must consider the cognitive demands on the providers and the context of the work. This study's purpose is to develop requirements for a clinical decision support tool (a clinical reminder) by analyzing the cognitive demands of the task along with the factors in the Cabana framework of physician adherence to guidelines, the health information technology (HIT) sociotechnical framework, and the Promoting Action on Research Implementation in Health Services (PARIHS) framework of health services implementation. It utilizes a tool that extracts information from medical records (including ejection fraction in free text reports) to identify qualifying patients at risk of undertreatment. We conducted interviews with 17 primary care providers, 5 PharmDs, and 5 Registered Nurses across three Veterans Health Administration outpatient clinics. The interviews were based on cognitive task analysis (CTA) methods and enhanced through the inclusion of the Cabana, HIT sociotechnical, and PARIHS frameworks. The analysis of the interview data led to the development of requirements and a prototype design for a clinical reminder. We conducted a small pilot usability assessment of the clinical reminder using realistic clinical scenarios. We identified organizational challenges (such as time pressures and underuse of pharmacists), knowledge issues regarding the guideline, and information needs regarding patient history and treatment status. We based the design of the clinical reminder on how to best address these challenges. The usability assessment indicated the tool could help the decision and titration processes. Through the use of CTA methods enhanced with adherence, sociotechnical, and implementation frameworks, we designed a decision support tool that considers important challenges in the decision and execution of β-blocker titration for qualifying HF patients at risk of undertreatment. Schattauer GmbH Stuttgart.
Montgomery, Alan A; Emmett, Clare L; Fahey, Tom; Jones, Claire; Ricketts, Ian; Patel, Roshni R; Peters, Tim J; Murphy, Deirdre J
2007-06-23
To determine the effects of two computer based decision aids on decisional conflict and mode of delivery among pregnant women with a previous caesarean section. Randomised trial, conducted from May 2004 to August 2006. Four maternity units in south west England, and Scotland. 742 pregnant women with one previous lower segment caesarean section and delivery expected at >or=37 weeks. Non-English speakers were excluded. Usual care: standard care given by obstetric and midwifery staff. Information programme: women navigated through descriptions and probabilities of clinical outcomes for mother and baby associated with planned vaginal birth, elective caesarean section, and emergency caesarean section. Decision analysis: mode of delivery was recommended based on utility assessments performed by the woman combined with probabilities of clinical outcomes within a concealed decision tree. Both interventions were delivered via a laptop computer after brief instructions from a researcher. Total score on decisional conflict scale, and mode of delivery. Women in the information programme (adjusted difference -6.2, 95% confidence interval -8.7 to -3.7) and the decision analysis (-4.0, -6.5 to -1.5) groups had reduced decisional conflict compared with women in the usual care group. The rate of vaginal birth was higher for women in the decision analysis group compared with the usual care group (37% v 30%, adjusted odds ratio 1.42, 0.94 to 2.14), but the rates were similar in the information programme and usual care groups. Decision aids can help women who have had a previous caesarean section to decide on mode of delivery in a subsequent pregnancy. The decision analysis approach might substantially affect national rates of caesarean section. Trial Registration Current Controlled Trials ISRCTN84367722.
Web-based health services and clinical decision support.
Jegelevicius, Darius; Marozas, Vaidotas; Lukosevicius, Arunas; Patasius, Martynas
2004-01-01
The purpose of this study was the development of a Web-based e-health service for comprehensive assistance and clinical decision support. The service structure consists of a Web server, a PHP-based Web interface linked to a clinical SQL database, Java applets for interactive manipulation and visualization of signals and a Matlab server linked with signal and data processing algorithms implemented by Matlab programs. The service ensures diagnostic signal- and image analysis-sbased clinical decision support. By using the discussed methodology, a pilot service for pathology specialists for automatic calculation of the proliferation index has been developed. Physicians use a simple Web interface for uploading the pictures under investigation to the server; subsequently a Java applet interface is used for outlining the region of interest and, after processing on the server, the requested proliferation index value is calculated. There is also an "expert corner", where experts can submit their index estimates and comments on particular images, which is especially important for system developers. These expert evaluations are used for optimization and verification of automatic analysis algorithms. Decision support trials have been conducted for ECG and ophthalmology ultrasonic investigations of intraocular tumor differentiation. Data mining algorithms have been applied and decision support trees constructed. These services are under implementation by a Web-based system too. The study has shown that the Web-based structure ensures more effective, flexible and accessible services compared with standalone programs and is very convenient for biomedical engineers and physicians, especially in the development phase.
Kawamoto, Kensaku; Lobach, David F
2003-01-01
Computerized physician order entry (CPOE) systems represent an important tool for providing clinical decision support. In undertaking this systematic review, our objective was to identify the features of CPOE-based clinical decision support systems (CDSSs) most effective at modifying clinician behavior. For this review, two independent reviewers systematically identified randomized controlled trials that evaluated the effectiveness of CPOE-based CDSSs in changing clinician behavior. Furthermore, each included study was assessed for the presence of 14 CDSS features. We screened 10,023 citations and included 11 studies. Of the 10 studies comparing a CPOE-based CDSS intervention against a non-CDSS control group, 7 reported a significant desired change in professional practice. Moreover, meta-regression analysis revealed that automatic provision of the decision support was strongly associated with improved professional practice (adjusted odds ratio, 23.72; 95% confidence interval, 1.75-infiniti). Thus, we conclude that automatic provision of decision support is a critical feature of successful CPOE-based CDSS interventions.
Decision or no decision: how do patient-physician interactions end and what matters?
Tai-Seale, Ming; Bramson, Rachel; Bao, Xiaoming
2007-03-01
A clearly stated clinical decision can induce a cognitive closure in patients and is an important investment in the end of patient-physician communications. Little is known about how often explicit decisions are made in primary care visits. To use an innovative videotape analysis approach to assess physicians' propensity to state decisions explicitly, and to examine the factors influencing decision patterns. We coded topics discussed in 395 videotapes of primary care visits, noting the number of instances and the length of discussions on each topic, and how discussions ended. A regression analysis tested the relationship between explicit decisions and visit factors such as the nature of topics under discussion, instances of discussion, the amount of time the patient spoke, and competing demands from other topics. About 77% of topics ended with explicit decisions. Patients spoke for an average of 58 seconds total per topic. Patients spoke more during topics that ended with an explicit decision, (67 seconds), compared with 36 seconds otherwise. The number of instances of a topic was associated with higher odds of having an explicit decision (OR = 1.73, p < 0.01). Increases in the number of topics discussed in visits (OR = 0.95, p < .05), and topics on lifestyle and habits (OR = 0.60, p < .01) were associated with lower odds of explicit decisions. Although discussions often ended with explicit decisions, there were variations related to the content and dynamics of interactions. We recommend strengthening patients' voice and developing clinical tools, e.g., an "exit prescription," to improving decision making.
Liu, Ximeng; Lu, Rongxing; Ma, Jianfeng; Chen, Le; Qin, Baodong
2016-03-01
Clinical decision support system, which uses advanced data mining techniques to help clinician make proper decisions, has received considerable attention recently. The advantages of clinical decision support system include not only improving diagnosis accuracy but also reducing diagnosis time. Specifically, with large amounts of clinical data generated everyday, naïve Bayesian classification can be utilized to excavate valuable information to improve a clinical decision support system. Although the clinical decision support system is quite promising, the flourish of the system still faces many challenges including information security and privacy concerns. In this paper, we propose a new privacy-preserving patient-centric clinical decision support system, which helps clinician complementary to diagnose the risk of patients' disease in a privacy-preserving way. In the proposed system, the past patients' historical data are stored in cloud and can be used to train the naïve Bayesian classifier without leaking any individual patient medical data, and then the trained classifier can be applied to compute the disease risk for new coming patients and also allow these patients to retrieve the top- k disease names according to their own preferences. Specifically, to protect the privacy of past patients' historical data, a new cryptographic tool called additive homomorphic proxy aggregation scheme is designed. Moreover, to leverage the leakage of naïve Bayesian classifier, we introduce a privacy-preserving top- k disease names retrieval protocol in our system. Detailed privacy analysis ensures that patient's information is private and will not be leaked out during the disease diagnosis phase. In addition, performance evaluation via extensive simulations also demonstrates that our system can efficiently calculate patient's disease risk with high accuracy in a privacy-preserving way.
Clinical decision-making: predictors of patient participation in nursing care.
Florin, Jan; Ehrenberg, Anna; Ehnfors, Margareta
2008-11-01
To investigate predictors of patients' preferences for participation in clinical decision-making in inpatient nursing care. Patient participation in decision-making in nursing care is regarded as a prerequisite for good clinical practice regarding the person's autonomy and integrity. A cross-sectional survey of 428 persons, newly discharged from inpatient care. The survey was conducted using the Control Preference Scale. Multiple logistic regression analysis was used for testing the association of patient characteristics with preferences for participation. Patients, in general, preferred adopting a passive role. However, predictors for adopting an active participatory role were the patient's gender (odds ratio = 1.8), education (odds ratio = 2.2), living condition (odds ratio = 1.8) and occupational status (odds ratio = 2.0). A probability of 53% was estimated, which female senior citizens with at least a high school degree and who lived alone would prefer an active role in clinical decision-making. At the same time, a working cohabiting male with less than a high school degree had a probability of 8% for active participation in clinical decision making in nursing care. Patient preferences for participation differed considerably and are best elicited by assessment of the individual patient. Relevance to clinical practice. The nurses have a professional responsibility to act in such a way that patients can participate and make decisions according to their own values from an informed position. Access to knowledge of patients'basic assumptions and preferences for participation is of great value for nurses in the care process. There is a need for nurses to use structured methods and tools for eliciting individual patient preferences regarding participation in clinical decision-making.
Decision analysis. Clinical art or Clinical Science
1977-05-01
having helped some clients. Over the past half century, psychotherapy has faced a series of crises concerned with its transformation from an art to a...clinical science . These include validation of the effectiveness of various forms of therapy, validating elements of treatment programs and
An Investigation into the Clinical Reasoning Development of Veterinary Students.
Vinten, Claire E K; Cobb, Kate A; Freeman, Sarah L; Mossop, Liz H
Clinical reasoning is a fundamental skill for veterinary clinicians and a competency required of graduates by the Royal College of Veterinary Surgeons. However, it is unknown how veterinary students develop reasoning skills and where strengths and shortcomings of curricula lie. This research aimed to use the University of Nottingham School of Veterinary Medicine and Science (SVMS) as a case study to investigate the development of clinical reasoning among veterinary students. The analysis was framed in consideration of the taught, learned, and declared curricula. Sixteen staff and sixteen students from the SVMS participated separately in a total of four focus groups. In addition, five interviews were conducted with recent SVMS graduates. Audio transcriptions were used to conduct a thematic analysis. A content analysis was performed on all curriculum documentation. It was found that SVMS graduates feel they have a good level of reasoning ability, but they still experience a deficit in their reasoning capabilities when starting their first job. Overarching themes arising from the data suggest that a lack of responsibility for clinical decisions during the program and the embedded nature of the clinical reasoning skill within the curriculum could be restricting development. In addition, SVMS students would benefit from clinical reasoning training where factors influencing "real life" decisions (e.g., finances) are explored in more depth. Integrating these factors into the curriculum could lead to improved decision-making ability among SVMS graduates and better prepare students for the stressful transition to practice. These findings are likely to have implications for other veterinary curricula.
Systematic Analysis of the Decision Rules of Traditional Chinese Medicine
Bin-Rong, Ma; Xi-Yuan, Jiang; Su-Ming, Liso; Huai-ning, Zhu; Xiu-ru, Lin
1981-01-01
Chinese traditional medicine has evolved over many centuries, and has accumulated a body of observed relationships between symptoms, signs and prognoses, and the efficacy of alternative treatments and prescriptions. With the assistance of a computer-based clinical data base for recording the diagnostic and therapeutic practice of skilled practitioners of Chinese traditional medicine, a systematic program is being conducted to identify and define the clinical decision-making rules that underlie current practice.
Hoomans, Ties; Abrams, Keith R; Ament, Andre J H A; Evers, Silvia M A A; Severens, Johan L
2009-10-01
Decision making about resource allocation for guideline implementation to change clinical practice is inevitably undertaken in a context of uncertainty surrounding the cost-effectiveness of both clinical guidelines and implementation strategies. Adopting a total net benefit approach, a model was recently developed to overcome problems with the use of combined ratio statistics when analyzing decision uncertainty. To demonstrate the stochastic application of the model for informing decision making about the adoption of an audit and feedback strategy for implementing a guideline recommending intensive blood glucose control in type 2 diabetes in primary care in the Netherlands. An integrated Bayesian approach to decision modeling and evidence synthesis is adopted, using Markov Chain Monte Carlo simulation in WinBUGs. Data on model parameters is gathered from various sources, with effectiveness of implementation being estimated using pooled, random-effects meta-analysis. Decision uncertainty is illustrated using cost-effectiveness acceptability curves and frontier. Decisions about whether to adopt intensified glycemic control and whether to adopt audit and feedback alter for the maximum values that decision makers are willing to pay for health gain. Through simultaneously incorporating uncertain economic evidence on both guidance and implementation strategy, the cost-effectiveness acceptability curves and cost-effectiveness acceptability frontier show an increase in decision uncertainty concerning guideline implementation. The stochastic application in diabetes care demonstrates that the model provides a simple and useful tool for quantifying and exploring the (combined) uncertainty associated with decision making about adopting guidelines and implementation strategies and, therefore, for informing decisions about efficient resource allocation to change clinical practice.
A Benefit-Risk Analysis Approach to Capture Regulatory Decision-Making: Non-Small Cell Lung Cancer.
Raju, G K; Gurumurthi, K; Domike, R; Kazandjian, D; Blumenthal, G; Pazdur, R; Woodcock, J
2016-12-01
Drug regulators around the world make decisions about drug approvability based on qualitative benefit-risk analyses. There is much interest in quantifying regulatory approaches to benefit and risk. In this work the use of a quantitative benefit-risk analysis was applied to regulatory decision-making about new drugs to treat advanced non-small cell lung cancer (NSCLC). Benefits and risks associated with 20 US Food and Drug Administration (FDA) decisions associated with a set of candidate treatments submitted between 2003 and 2015 were analyzed. For benefit analysis, the median overall survival (OS) was used where available. When not available, OS was estimated based on overall response rate (ORR) or progression-free survival (PFS). Risks were analyzed based on magnitude (or severity) of harm and likelihood of occurrence. Additionally, a sensitivity analysis was explored to demonstrate analysis of systematic uncertainty. FDA approval decision outcomes considered were found to be consistent with the benefit-risk logic. © 2016 American Society for Clinical Pharmacology and Therapeutics.
Epidemiology and Clinical Research Design, Part 2: Principles
Manja, Veena; Lakshminrusimha, Satyan
2015-01-01
This is the third article covering core knowledge in scholarly activities for neonatal physicians. In this article, we discuss various principles of epidemiology and clinical research design. A basic knowledge of these principles is necessary for conducting clinical research and for proper interpretation of studies. This article reviews bias and confounding, causation, incidence and prevalence, decision analysis, cost-effectiveness, sensitivity analysis, and measurement. PMID:26236171
Mobile clinical decision support systems and applications: a literature and commercial review.
Martínez-Pérez, Borja; de la Torre-Díez, Isabel; López-Coronado, Miguel; Sainz-de-Abajo, Beatriz; Robles, Montserrat; García-Gómez, Juan Miguel
2014-01-01
The latest advances in eHealth and mHealth have propitiated the rapidly creation and expansion of mobile applications for health care. One of these types of applications are the clinical decision support systems, which nowadays are being implemented in mobile apps to facilitate the access to health care professionals in their daily clinical decisions. The aim of this paper is twofold. Firstly, to make a review of the current systems available in the literature and in commercial stores. Secondly, to analyze a sample of applications in order to obtain some conclusions and recommendations. Two reviews have been done: a literature review on Scopus, IEEE Xplore, Web of Knowledge and PubMed and a commercial review on Google play and the App Store. Five applications from each review have been selected to develop an in-depth analysis and to obtain more information about the mobile clinical decision support systems. Ninety-two relevant papers and 192 commercial apps were found. Forty-four papers were focused only on mobile clinical decision support systems. One hundred seventy-one apps were available on Google play and 21 on the App Store. The apps are designed for general medicine and 37 different specialties, with some features common in all of them despite of the different medical fields objective. The number of mobile clinical decision support applications and their inclusion in clinical practices has risen in the last years. However, developers must be careful with their interface or the easiness of use, which can impoverish the experience of the users.
Financial Concerns About Participation in Clinical Trials Among Patients With Cancer.
Wong, Yu-Ning; Schluchter, Mark D; Albrecht, Terrance L; Benson, Al Bowen; Buzaglo, Joanne; Collins, Michael; Flamm, Anne Lederman; Fleisher, Linda; Katz, Michael; Kinzy, Tyler G; Liu, Tasnuva M; Manne, Sharon; Margevicius, Seunghee; Miller, Dawn M; Miller, Suzanne M; Poole, David; Raivitch, Stephanie; Roach, Nancy; Ross, Eric; Meropol, Neal J
2016-02-10
The decision to enroll in a clinical trial is complex given the uncertain risks and benefits of new approaches. Many patients also have financial concerns. We sought to characterize the association between financial concerns and the quality of decision making about clinical trials. We conducted a secondary data analysis of a randomized trial of a Web-based educational tool (Preparatory Education About Clinical Trials) designed to improve the preparation of patients with cancer for making decisions about clinical trial enrollment. Patients completed a baseline questionnaire that included three questions related to financial concerns (five-point Likert scales): "How much of a burden on you is the cost of your medical care?," "I'm afraid that my health insurance won't pay for a clinical trial," and "I'm worried that I wouldn't be able to afford the costs of treatment on a clinical trial." Results were summed, with higher scores indicating greater concerns. We used multiple linear regressions to measure the association between concerns and self-reported measures of self-efficacy, preparation for decision making, distress, and decisional conflict in separate models, controlling for sociodemographic characteristics. One thousand two hundred eleven patients completed at least one financial concern question. Of these, 27% were 65 years or older, 58% were female, and 24% had a high school education or less. Greater financial concern was associated with lower self-efficacy and preparation for decision making, as well as with greater decisional conflict and distress, even after adjustment for age, race, sex, education, employment, and hospital location (P < .001 for all models). Financial concerns are associated with several psychological constructs that may negatively influence decision quality regarding clinical trials. Greater attention to patients' financial needs and concerns may reduce distress and improve patient decision making. © 2015 by American Society of Clinical Oncology.
Richardson, Karen J; Sengstack, Patricia; Doucette, Jeffrey N; Hammond, William E; Schertz, Matthew; Thompson, Julie; Johnson, Constance
2016-02-01
The primary aim of this performance improvement project was to determine whether the electronic health record implementation of stroke-specific nursing documentation flowsheet templates and clinical decision support alerts improved the nursing documentation of eligible stroke patients in seven stroke-certified emergency departments. Two system enhancements were introduced into the electronic record in an effort to improve nursing documentation: disease-specific documentation flowsheets and clinical decision support alerts. Using a pre-post design, project measures included six stroke management goals as defined by the National Institute of Neurological Disorders and Stroke and three clinical decision support measures based on entry of orders used to trigger documentation reminders for nursing: (1) the National Institutes of Health's Stroke Scale, (2) neurological checks, and (3) dysphagia screening. Data were reviewed 6 months prior (n = 2293) and 6 months following the intervention (n = 2588). Fisher exact test was used for statistical analysis. Statistical significance was found for documentation of five of the six stroke management goals, although effect sizes were small. Customizing flowsheets to meet the needs of nursing workflow showed improvement in the completion of documentation. The effects of the decision support alerts on the completeness of nursing documentation were not statistically significant (likely due to lack of order entry). For example, an order for the National Institutes of Health Stroke Scale was entered only 10.7% of the time, which meant no alert would fire for nursing in the postintervention group. Future work should focus on decision support alerts that trigger reminders for clinicians to place relevant orders for this population.
Aziz, Muhammad Tahir; Ur-Rehman, Tofeeq; Qureshi, Sadia; Bukhari, Nadeem Irfan
Medication errors in chemotherapy are frequent and lead to patient morbidity and mortality, as well as increased rates of re-admission and length of stay, and considerable extra costs. Objective: This study investigated the proposition that computerised chemotherapy ordering reduces the incidence and severity of chemotherapy protocol errors. A computerised physician order entry of chemotherapy order (C-CO) with clinical decision support system was developed in-house, including standardised chemotherapy protocol definitions, automation of pharmacy distribution, clinical checks, labeling and invoicing. A prospective study was then conducted in a C-CO versus paper based chemotherapy order (P-CO) in a 30-bed chemotherapy bay of a tertiary hospital. Both C-CO and P-CO orders, including pharmacoeconomic analysis and the severity of medication errors, were checked and validated by a clinical pharmacist. A group analysis and field trial were also conducted to assess clarity, feasibility and decision making. The C-CO was very usable in terms of its clarity and feasibility. The incidence of medication errors was significantly lower in the C-CO compared with the P-CO (10/3765 [0.26%] versus 134/5514 [2.4%]). There was also a reduction in dispensing time of chemotherapy protocols in the C-CO. The chemotherapy computerisation with clinical decision support system resulted in a significant decrease in the occurrence and severity of medication errors, improvements in chemotherapy dispensing and administration times, and reduction of chemotherapy cost.
Churilov, Leonid; Liu, Daniel; Ma, Henry; Christensen, Soren; Nagakane, Yoshinari; Campbell, Bruce; Parsons, Mark W; Levi, Christopher R; Davis, Stephen M; Donnan, Geoffrey A
2013-04-01
The appropriateness of a software platform for rapid MRI assessment of the amount of salvageable brain tissue after stroke is critical for both the validity of the Extending the Time for Thrombolysis in Emergency Neurological Deficits (EXTEND) Clinical Trial of stroke thrombolysis beyond 4.5 hours and for stroke patient care outcomes. The objective of this research is to develop and implement a methodology for selecting the acute stroke imaging software platform most appropriate for the setting of a multi-centre clinical trial. A multi-disciplinary decision making panel formulated the set of preferentially independent evaluation attributes. Alternative Multi-Attribute Value Measurement methods were used to identify the best imaging software platform followed by sensitivity analysis to ensure the validity and robustness of the proposed solution. Four alternative imaging software platforms were identified. RApid processing of PerfusIon and Diffusion (RAPID) software was selected as the most appropriate for the needs of the EXTEND trial. A theoretically grounded generic multi-attribute selection methodology for imaging software was developed and implemented. The developed methodology assured both a high quality decision outcome and a rational and transparent decision process. This development contributes to stroke literature in the area of comprehensive evaluation of MRI clinical software. At the time of evaluation, RAPID software presented the most appropriate imaging software platform for use in the EXTEND clinical trial. The proposed multi-attribute imaging software evaluation methodology is based on sound theoretical foundations of multiple criteria decision analysis and can be successfully used for choosing the most appropriate imaging software while ensuring both robust decision process and outcomes. © 2012 The Authors. International Journal of Stroke © 2012 World Stroke Organization.
Lessons of War: Turning Data Into Decisions.
Forsberg, Jonathan A; Potter, Benjamin K; Wagner, Matthew B; Vickers, Andrew; Dente, Christopher J; Kirk, Allan D; Elster, Eric A
2015-09-01
Recent conflicts in Afghanistan and Iraq produced a substantial number of critically wounded service-members. We collected biomarker and clinical information from 73 patients who sustained 116 life-threatening combat wounds, and sought to determine if the data could be used to predict the likelihood of wound failure. From each patient, we collected clinical information, serum, wound effluent, and tissue prior to and at each surgical débridement. Inflammatory cytokines were quantified in both the serum and effluent, as were gene expression targets. The primary outcome was successful wound healing. Computer intensive methods were used to derive prognostic models that were internally validated using target shuffling and cross-validation methods. A second cohort of eighteen critically injured civilian patients was evaluated to determine if similar inflammatory responses were observed. The best-performing models enhanced clinical observation with biomarker data from the serum and wound effluent, an indicator that systemic inflammatory conditions contribute to local wound failure. A Random Forest model containing ten variables demonstrated the highest accuracy (AUC 0.79). Decision Curve Analysis indicated that the use of this model would improve clinical outcomes and reduce unnecessary surgical procedures. Civilian trauma patients demonstrated similar inflammatory responses and an equivalent wound failure rate, indicating that the model may be generalizable to civilian settings. Using advanced analytics, we successfully codified clinical and biomarker data from combat patients into a potentially generalizable decision support tool. Analysis of inflammatory data from critically ill patients with acute injury may inform decision-making to improve clinical outcomes and reduce healthcare costs. United States Department of Defense Health Programs.
Al-Attar, Ghada S T; Bishai, David; El-Gibaly, Omaima
2017-03-01
Cost effectiveness studies of family planning (FP) services are very valuable in providing evidence-based data for decision makers in Egypt. Cost data came from record reviews for all 15 mobile clinics and a matched set of 15 static clinics and interviews with staff members of the selected clinics at Assiut Governorate. Effectiveness measures included couple years of protection (CYPs) and FP visits. Incremental cost-effectiveness ratios (ICER) and sensitivity analyses were calculated. Mobile clinics cost more per facility, produced more CYPs but had fewer FP visits. Sensitivity analysis was done using: total costs, CYP and FP visits of mobile and static clinics and showed that variations in CYP of mobile and static clinics altered the ICER for CYP from $2 -$6. Mobile clinics with their high emphasis on IUDs offer a reasonable cost effectiveness of $4.46 per additional CYP compared to static clinics. The ability of mobile clinics to reach more vulnerable women and to offer more long acting methods might affect a policy decision between these options. Static clinics should consider whether emphasizing IUDs may make their services more cost-effective.
Li, Shuqing; Sun, Ying; Soergel, Dagobert
2017-12-23
We present a novel approach to recommending articles from the medical literature that support clinical diagnostic decision-making, giving detailed descriptions of the associated ideas and principles. The specific goal is to retrieve biomedical articles that help answer questions of a specified type about a particular case. Based on the filtered keywords, MeSH(Medical Subject Headings) lexicon and the automatically extracted acronyms, the relationship between keywords and articles was built. The paper gives a detailed description of the process of by which keywords were measured and relevant articles identified based on link analysis in a weighted keywords network. Some important challenges identified in this study include the extraction of diagnosis-related keywords and a collection of valid sentences based on the keyword co-occurrence analysis and existing descriptions of symptoms. All data were taken from medical articles provided in the TREC (Text Retrieval Conference) clinical decision support track 2015. Ten standard topics and one demonstration topic were tested. In each case, a maximum of five articles with the highest relevance were returned. The total user satisfaction of 3.98 was 33% higher than average. The results also suggested that the smaller the number of results, the higher the average satisfaction. However, a few shortcomings were also revealed since medical literature recommendation for clinical diagnostic decision support is so complex a topic that it cannot be fully addressed through the semantic information carried solely by keywords in existing descriptions of symptoms. Nevertheless, the fact that these articles are actually relevant will no doubt inspire future research.
Xiao, Wen-Jun; Ye, Ding-Wei; Yao, Xu-Dong; Zhang, Shi-Lin; Dai, Bo
2013-01-01
To compare Partin tables (PTs) 1997, 2001, and 2007 for their clinical applicability in a Chinese cohort based upon a decision curve analysis (DCA). Clinical and pathologic data of 264 consecutive Chinese patients with clinically localized prostate cancer were used. These patients underwent open radical prostatectomy between 2005 and 2011. DCA quantified the net benefit of different PT versions relating to specific threshold probabilities of established capsular penetration (ECP), seminal vesicle involvement (SVI), and lymph node involvement (LNI). Overall, ECP, SVI, and LNI were recorded in 23.1, 10.2, and 6.1%, respectively. When the threshold probability was below the prevalence for LNI and ECP predictions, the DCA favored the 2007 version versus the 1997 version for SVI. DCA indicates that for low threshold probability, decision models are useful to discriminate the performance differences of three PT versions, although net benefit differences were not apparent. For high threshold probability, there may not be an important benefit from the use of PTs and the current analysis cannot translate into meaningful net gains differences. Copyright © 2013 S. Karger AG, Basel.
2011-01-01
Background A real-time clinical decision support system (RTCDSS) with interactive diagrams enables clinicians to instantly and efficiently track patients' clinical records (PCRs) and improve their quality of clinical care. We propose a RTCDSS to process online clinical informatics from multiple databases for clinical decision making in the treatment of prostate cancer based on Web Model-View-Controller (MVC) architecture, by which the system can easily be adapted to different diseases and applications. Methods We designed a framework upon the Web MVC-based architecture in which the reusable and extractable models can be conveniently adapted to other hospital information systems and which allows for efficient database integration. Then, we determined the clinical variables of the prostate cancer treatment based on participating clinicians' opinions and developed a computational model to determine the pretreatment parameters. Furthermore, the components of the RTCDSS integrated PCRs and decision factors for real-time analysis to provide evidence-based diagrams upon the clinician-oriented interface for visualization of treatment guidance and health risk assessment. Results The resulting system can improve quality of clinical treatment by allowing clinicians to concurrently analyze and evaluate the clinical markers of prostate cancer patients with instantaneous clinical data and evidence-based diagrams which can automatically identify pretreatment parameters. Moreover, the proposed RTCDSS can aid interactions between patients and clinicians. Conclusions Our proposed framework supports online clinical informatics, evaluates treatment risks, offers interactive guidance, and provides real-time reference for decision making in the treatment of prostate cancer. The developed clinician-oriented interface can assist clinicians in conveniently presenting evidence-based information to patients and can be readily adapted to an existing hospital information system and be easily applied in other chronic diseases. PMID:21385459
Lin, Hsueh-Chun; Wu, Hsi-Chin; Chang, Chih-Hung; Li, Tsai-Chung; Liang, Wen-Miin; Wang, Jong-Yi Wang
2011-03-08
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. 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. 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. 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 applied in other chronic diseases.
Guest, James; Harrop, James S; Aarabi, Bizhan; Grossman, Robert G; Fawcett, James W; Fehlings, Michael G; Tator, Charles H
2012-09-01
The North American Clinical Trials Network (NACTN) includes 9 clinical centers funded by the US Department of Defense and the Christopher Reeve Paralysis Foundation. Its purpose is to accelerate clinical testing of promising therapeutics in spinal cord injury (SCI) through the development of a robust interactive infrastructure. This structure includes key committees that serve to provide longitudinal guidance to the Network. These committees include the Executive, Data Management, and Neurological Outcome Assessments Committees, and the Therapeutic Selection Committee (TSC), which is the subject of this manuscript. The NACTN brings unique elements to the SCI field. The Network's stability is not restricted to a single clinical trial. Network members have diverse expertise and include experts in clinical care, clinical trial design and methodology, pharmacology, preclinical and clinical research, and advanced rehabilitation techniques. Frequent systematic communication is assigned a high value, as is democratic process, fairness and efficiency of decision making, and resource allocation. This article focuses on how decision making occurs within the TSC to rank alternative therapeutics according to 2 main variables: quality of the preclinical data set, and fit with the Network's aims and capabilities. This selection process is important because if the Network's resources are committed to a therapeutic, alternatives cannot be pursued. A proposed methodology includes a multicriteria decision analysis that uses a Multi-Attribute Global Inference of Quality matrix to quantify the process. To rank therapeutics, the TSC uses a series of consensus steps designed to reduce individual and group bias and limit subjectivity. Given the difficulties encountered by industry in completing clinical trials in SCI, stable collaborative not-for-profit consortia, such as the NACTN, may be essential to clinical progress in SCI. The evolution of the NACTN also offers substantial opportunity to refine decision making and group dynamics. Making the best possible decisions concerning therapeutics selection for trial testing is a cornerstone of the Network's function.
Holdar, Ulrika; Wallin, Lars; Heiwe, Susanne
2013-12-01
Despite the current movement for health-care to become more informed by evidence, knowledge on effective implementation of evidence-based practice is scarce. To improve research application among physiotherapists, the process of implementation and clinical reasoning needs to be scrutinized. The aim of this study was to identify various experiences of factors that influence the physiotherapist's clinical reasoning in specialist care. A phenomenographic approach was chosen. Eleven physiotherapists at two acute care hospitals in nn. Data was obtained by observations and interviews. Phenomenographic data analysis identified various experiences of clinical decision-making. The Ethical Review Board of the nn approved the study. The observations and the interviews enabled identification of various experiences that influenced clinical decision-making. The physiotherapists' clinical reasoning was perceived to be constrained by contextual factors. The physiotherapists collected current information on the patient by using written and verbal information exchange and used this to generate an inner picture of the patient. By creating hypotheses that were accepted or rejected, they made decisions in advance of their interventions. The decisions were influenced by the individual characteristics of the physiotherapist, his/her knowledge and patient perceptions. Clinical reasoning is a complex and constantly evolving process. Contextual factors such as economy and politics are not easily changed, but factors such as the patient and the physiotherapist as a person are more tangible. Copyright © 2013 John Wiley & Sons, Ltd.
Peters, Amanda; Vanstone, Meredith; Monteiro, Sandra; Norman, Geoff; Sherbino, Jonathan; Sibbald, Matthew
2017-05-01
According to the dual process model of reasoning, physicians make diagnostic decisions using two mental systems: System 1, which is rapid, unconscious, and intuitive, and System 2, which is slow, rational, and analytical. Currently, little is known about physicians' use of System 1 or intuitive reasoning in practice. In a qualitative study of clinical reasoning, physicians were asked to tell stories about times when they used intuitive reasoning while working up an acutely unwell patient, and we combine socio-narratology and rhetorical theory to analyze physicians' stories. Our analysis reveals that in describing their work, physicians draw on two competing narrative structures: one that is aligned with an evidence-based medicine approach valuing System 2 and one that is aligned with cooperative decision making involving others in the clinical environment valuing System 1. Our findings support an understanding of clinical reasoning as distributed, contextual, and influenced by professional culture.
The use of economic evaluations in NHS decision-making: a review and empirical investigation.
Williams, I; McIver, S; Moore, D; Bryan, S
2008-04-01
To determine the extent to which health economic information is used in health policy decision-making in the UK, and to consider factors associated with the utilisation of such research findings. Major electronic databases were searched up to 2004. A systematic review of existing reviews on the use of economic evaluations in policy decision-making, of health and non-health literature on the use of economic analyses in policy making and of studies identifying actual or perceived barriers to the use of economic evaluations was undertaken. Five UK case studies of committees from four local and one national organisation [the Technology Appraisal Committee of the National Institute for Health and Clinical Excellence (NICE)] were conducted. Local case studies were augmented by documentary analysis of new technology request forms and by workshop discussions with members of local decision-making committees. The systematic review demonstrated few previous systematic reviews of evidence in the area. At the local level in the NHS, it was an exception for economic evaluation to inform technology coverage decisions. Local decision-making focused primarily on evidence of clinical benefit and cost implications. And whilst information on implementation was frequently requested, cost-effectiveness information was rarely accessed. A number of features of the decision-making environment appeared to militate against emphasis on cost-effectiveness analysis. Constraints on the capacity to generate, access and interpret information, led to a minor role for cost-effectiveness analysis in the local decision-making process. At the national policy level in the UK, economic analysis was found to be highly integrated into NICE's technology appraisal programme. Attitudes to economic evaluation varied between committee members with some significant disagreement and extraneous factors diluted the health economics analysis available to the committee. There was strong evidence of an ordinal approach to consideration of clinical effectiveness and cost-effectiveness information. Some interviewees considered the key role of a cost-effectiveness analysis to be the provision of a framework for decision-making. Interviewees indicated that NICE makes use of some form of cost-effectiveness threshold but expressed concern about its basis and its use in decision-making. Frustrations with the appraisal process were expressed in terms of the scope of the policy question being addressed. Committee members raised concerns about lack of understanding of the economic analysis but felt that a single measure of benefit, e.g. the quality-adjusted life-year, was useful in allowing comparison of disparate health interventions and in providing a benchmark for later decisions. The importance of ensuring that committee members understood the limitations of the analysis was highlighted for model-based analyses. This study suggests that research is needed into structures, processes and mechanisms by which technology coverage decisions can and should be made in healthcare. Further development of 'resource centres' may be useful to provide independent published analyses in order to support local decision-makers. Improved methods of economic analyses and of their presentation, which take account of the concerns of their users, are needed. Finally, the findings point to the need for further assessment of the feasibility and value of a formal process of clarification of the objectives that we seek from investments in healthcare.
Gebhardt, Brian J; Heron, Dwight E; Beriwal, Sushil
Clinical pathways are patient management plans that standardize evidence-based practices to ensure high-quality and cost-effective medical care. Implementation of a pathway is a collaborative process in our network, requiring the active involvement of physicians. This approach promotes acceptance of pathway recommendations, although a peer review process is necessary to ensure compliance and to capture and approve off-pathway selections. We investigated the peer review process and factors associated with time to completion of peer review. Our cancer center implemented radiation oncology pathways for every disease site throughout a large, integrated network. Recommendations are written based upon national guidelines, published literature, and institutional experience with evidence evaluated hierarchically in order of efficacy, toxicity, and then cost. Physicians enter decisions into an online, menu-driven decision support tool that integrates with medical records. Data were collected from the support tool and included the rate of on- and off-pathway selections, peer review decisions performed by disease site directors, and time to complete peer review. A total of 6965 treatment decisions were entered in 2015, and 605 (8.7%) were made off-pathway and were subject to peer review. The median time to peer review decision was 2 days (interquartile range, 0.2-6.8). Factors associated with time to peer review decision >48 hours on univariate analysis include disease site (P < .0001) with a trend toward significance (P = .066) for radiation therapy modality. There was no difference between recurrent and non-recurrent disease (P = .267). Multivariable analysis revealed disease site was associated with time to peer review (P < .001), with lymphoma and skin/sarcoma most strongly influencing decision time >48 hours. Clinical pathways are an integral tool for standardizing evidence-based care throughout our large, integrated network, with 91.3% of all treatment decisions being made as per pathway. The peer review process was feasible, with <1% selections ultimately rejected, suggesting that awareness of peer review of treatment decisions encourages compliance with clinical pathway recommendations. Copyright © 2017 American Society for Radiation Oncology. Published by Elsevier Inc. All rights reserved.
A social-technological epistemology of clinical decision-making as mediated by imaging.
van Baalen, Sophie; Carusi, Annamaria; Sabroe, Ian; Kiely, David G
2017-10-01
In recent years there has been growing attention to the epistemology of clinical decision-making, but most studies have taken the individual physicians as the central object of analysis. In this paper we argue that knowing in current medical practice has an inherently social character and that imaging plays a mediating role in these practices. We have analyzed clinical decision-making within a medical expert team involved in diagnosis and treatment of patients with pulmonary hypertension (PH), a rare disease requiring multidisciplinary team involvement in diagnosis and management. Within our field study, we conducted observations, interviews, video tasks, and a panel discussion. Decision-making in the PH clinic involves combining evidence from heterogeneous sources into a cohesive framing of a patient, in which interpretations of the different sources can be made consistent with each other. Because pieces of evidence are generated by people with different expertise and interpretation and adjustments take place in interaction between different experts, we argue that this process is socially distributed. Multidisciplinary team meetings are an important place where information is shared, discussed, interpreted, and adjusted, allowing for a collective way of seeing and a shared language to be developed. We demonstrate this with an example of image processing in the PH service, an instance in which knowledge is distributed over multiple people who play a crucial role in generating an evaluation of right heart function. Finally, we argue that images fulfill a mediating role in distributed knowing in 3 ways: first, as enablers or tools in acquiring information; second, as communication facilitators; and third, as pervasively framing the epistemic domain. With this study of clinical decision-making in diagnosis and treatment of PH, we have shown that clinical decision-making is highly social and mediated by technologies. The epistemology of clinical decision-making needs to take social and technological mediation into account. © 2016 The Authors Journal of Evaluation in Clinical Practice Published by John Wiley & Sons Ltd.
A preliminary study applying decision analysis to the treatment of caries in primary teeth.
Tamošiūnas, Vytautas; Kay, Elizabeth; Craven, Rebecca
2013-01-01
To determine an optimal treatment strategy for carious deciduous teeth. Manchester Dental Hospital. Decision analysis. The likelihoods of each of the sequelae of caries in deciduous teeth were determined from the literature. The utility of the outcomes from non-treatment and treatment was then measured in 100 parents of children with caries, using a visual analogue scale. Decision analysis was performed which weighted the value of each potential outcome by the probability of its occurrence. A decision tree "fold-back" and sensitivity analysis then determined which treatment strategies, under which circumstances, offered the maximum expected utilities. The decision to leave a carious deciduous tooth unrestored attracted a maximum utility of 76.65 and the overall expected utility for the decision "restore" was 73.27 The decision to restore or not restore carious deciduous teeth are therefore of almost equal value. The decision is however highly sensitive to the utility value assigned to the advent of pain by the patient. There is no clear advantage to be gained by restoring deciduous teeth if patients' evaluations of outcomes are taken into account. Avoidance of pain and avoidance of procedures which are viewed as unpleasant by parents should be key determinants of clinical decision making about carious deciduous teeth.
Cai, Wenli; Lee, June-Goo; Fikry, Karim; Yoshida, Hiroyuki; Novelline, Robert; de Moya, Marc
2012-07-01
It is commonly believed that the size of a pneumothorax is an important determinant of treatment decision, in particular regarding whether chest tube drainage (CTD) is required. However, the volumetric quantification of pneumothoraces has not routinely been performed in clinics. In this paper, we introduced an automated computer-aided volumetry (CAV) scheme for quantification of volume of pneumothoraces in chest multi-detect CT (MDCT) images. Moreover, we investigated the impact of accurate volume of pneumothoraces in the improvement of the performance in decision-making regarding CTD in the management of traumatic pneumothoraces. For this purpose, an occurrence frequency map was calculated for quantitative analysis of the importance of each clinical parameter in the decision-making regarding CTD by a computer simulation of decision-making using a genetic algorithm (GA) and a support vector machine (SVM). A total of 14 clinical parameters, including volume of pneumothorax calculated by our CAV scheme, was collected as parameters available for decision-making. The results showed that volume was the dominant parameter in decision-making regarding CTD, with an occurrence frequency value of 1.00. The results also indicated that the inclusion of volume provided the best performance that was statistically significant compared to the other tests in which volume was excluded from the clinical parameters. This study provides the scientific evidence for the application of CAV scheme in MDCT volumetric quantification of pneumothoraces in the management of clinically stable chest trauma patients with traumatic pneumothorax. Copyright © 2012 Elsevier Ltd. All rights reserved.
Capoccia, Massimo; Marconi, Silvia; Singh, Sanjeet Avtaar; Pisanelli, Domenico M; De Lazzari, Claudio
2018-05-02
Modelling and simulation may become clinically applicable tools for detailed evaluation of the cardiovascular system and clinical decision-making to guide therapeutic intervention. Models based on pressure-volume relationship and zero-dimensional representation of the cardiovascular system may be a suitable choice given their simplicity and versatility. This approach has great potential for application in heart failure where the impact of left ventricular assist devices has played a significant role as a bridge to transplant and more recently as a long-term solution for non eligible candidates. We sought to investigate the value of simulation in the context of three heart failure patients with a view to predict or guide further management. CARDIOSIM © was the software used for this purpose. The study was based on retrospective analysis of haemodynamic data previously discussed at a multidisciplinary meeting. The outcome of the simulations addressed the value of a more quantitative approach in the clinical decision process. Although previous experience, co-morbidities and the risk of potentially fatal complications play a role in clinical decision-making, patient-specific modelling may become a daily approach for selection and optimisation of device-based treatment for heart failure patients. Willingness to adopt this integrated approach may be the key to further progress.
Laboratory cost control and financial management software.
Mayer, M
1998-02-09
Economical constraints within the health care system advocate the introduction of tighter control of costs in clinical laboratories. Detailed cost information forms the basis for cost control and financial management. Based on the cost information, proper decisions regarding priorities, procedure choices, personnel policies and investments can be made. This presentation outlines some principles of cost analysis, describes common limitations of cost analysis, and exemplifies use of software to achieve optimized cost control. One commercially available cost analysis software, LabCost, is described in some detail. In addition to provision of cost information, LabCost also serves as a general management tool for resource handling, accounting, inventory management and billing. The application of LabCost in the selection process of a new high throughput analyzer for a large clinical chemistry service is taken as an example for decisions that can be assisted by cost evaluation. It is concluded that laboratory management that wisely utilizes cost analysis to support the decision-making process will undoubtedly have a clear advantage over those laboratories that fail to employ cost considerations to guide their actions.
Periodic benefit-risk assessment using Bayesian stochastic multi-criteria acceptability analysis
Li, Kan; Yuan, Shuai Sammy; Wang, William; Wan, Shuyan Sabrina; Ceesay, Paulette; Heyse, Joseph F.; Mt-Isa, Shahrul; Luo, Sheng
2018-01-01
Benefit-risk (BR) assessment is essential to ensure the best decisions are made for a medical product in the clinical development process, regulatory marketing authorization, post-market surveillance, and coverage and reimbursement decisions. One challenge of BR assessment in practice is that the benefit and risk profile may keep evolving while new evidence is accumulating. Regulators and the International Conference on Harmonization (ICH) recommend performing periodic benefit-risk evaluation report (PBRER) through the product's lifecycle. In this paper, we propose a general statistical framework for periodic benefit-risk assessment, in which Bayesian meta-analysis and stochastic multi-criteria acceptability analysis (SMAA) will be combined to synthesize the accumulating evidence. The proposed approach allows us to compare the acceptability of different drugs dynamically and effectively and accounts for the uncertainty of clinical measurements and imprecise or incomplete preference information of decision makers. We apply our approaches to two real examples in a post-hoc way for illustration purpose. The proposed method may easily be modified for other pre and post market settings, and thus be an important complement to the current structured benefit-risk assessment (sBRA) framework to improve the transparent and consistency of the decision-making process. PMID:29505866
Ramsey, Scott D; Willke, Richard J; Glick, Henry; Reed, Shelby D; Augustovski, Federico; Jonsson, Bengt; Briggs, Andrew; Sullivan, Sean D
2015-03-01
Clinical trials evaluating medicines, medical devices, and procedures now commonly assess the economic value of these interventions. The growing number of prospective clinical/economic trials reflects both widespread interest in economic information for new technologies and the regulatory and reimbursement requirements of many countries that now consider evidence of economic value along with clinical efficacy. As decision makers increasingly demand evidence of economic value for health care interventions, conducting high-quality economic analyses alongside clinical studies is desirable because they broaden the scope of information available on a particular intervention, and can efficiently provide timely information with high internal and, when designed and analyzed properly, reasonable external validity. In 2005, ISPOR published the Good Research Practices for Cost-Effectiveness Analysis Alongside Clinical Trials: The ISPOR RCT-CEA Task Force report. ISPOR initiated an update of the report in 2014 to include the methodological developments over the last 9 years. This report provides updated recommendations reflecting advances in several areas related to trial design, selecting data elements, database design and management, analysis, and reporting of results. Task force members note that trials should be designed to evaluate effectiveness (rather than efficacy) when possible, should include clinical outcome measures, and should obtain health resource use and health state utilities directly from study subjects. Collection of economic data should be fully integrated into the study. An incremental analysis should be conducted with an intention-to-treat approach, complemented by relevant subgroup analyses. Uncertainty should be characterized. Articles should adhere to established standards for reporting results of cost-effectiveness analyses. Economic studies alongside trials are complementary to other evaluations (e.g., modeling studies) as information for decision makers who consider evidence of economic value along with clinical efficacy when making resource allocation decisions. Copyright © 2015 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.
Yu, Yuncui; Jia, Lulu; Meng, Yao; Hu, Lihua; Liu, Yiwei; Nie, Xiaolu; Zhang, Meng; Zhang, Xuan; Han, Sheng; Peng, Xiaoxia; Wang, Xiaoling
2018-04-01
Establishing a comprehensive clinical evaluation system is critical in enacting national drug policy and promoting rational drug use. In China, the 'Clinical Comprehensive Evaluation System for Pediatric Drugs' (CCES-P) project, which aims to compare drugs based on clinical efficacy and cost effectiveness to help decision makers, was recently proposed; therefore, a systematic and objective method is required to guide the process. An evidence-based multi-criteria decision analysis model that involved an analytic hierarchy process (AHP) was developed, consisting of nine steps: (1) select the drugs to be reviewed; (2) establish the evaluation criterion system; (3) determine the criterion weight based on the AHP; (4) construct the evidence body for each drug under evaluation; (5) select comparative measures and calculate the original utility score; (6) place a common utility scale and calculate the standardized utility score; (7) calculate the comprehensive utility score; (8) rank the drugs; and (9) perform a sensitivity analysis. The model was applied to the evaluation of three different inhaled corticosteroids (ICSs) used for asthma management in children (a total of 16 drugs with different dosage forms and strengths or different manufacturers). By applying the drug analysis model, the 16 ICSs under review were successfully scored and evaluated. Budesonide suspension for inhalation (drug ID number: 7) ranked the highest, with comprehensive utility score of 80.23, followed by fluticasone propionate inhaled aerosol (drug ID number: 16), with a score of 79.59, and budesonide inhalation powder (drug ID number: 6), with a score of 78.98. In the sensitivity analysis, the ranking of the top five and lowest five drugs remains unchanged, suggesting this model is generally robust. An evidence-based drug evaluation model based on AHP was successfully developed. The model incorporates sufficient utility and flexibility for aiding the decision-making process, and can be a useful tool for the CCES-P.
Cai, Wenli; Lee, June-Goo; Fikry, Karim; Yoshida, Hiroyuki; Novelline, Robert; de Moya, Marc
2013-01-01
It is commonly believed that the size of a pneumothorax is an important determinant of treatment decision, in particular regarding whether chest tube drainage (CTD) is required. However, the volumetric quantification of pneumothoraces has not routinely been performed in clinics. In this paper, we introduced an automated computer-aided volumetry (CAV) scheme for quantification of volume of pneumothoraces in chest multi-detect CT (MDCT) images. Moreover, we investigated the impact of accurate volume of pneumothoraces in the improvement of the performance in decision-making regarding CTD in the management of traumatic pneumothoraces. For this purpose, an occurrence frequency map was calculated for quantitative analysis of the importance of each clinical parameter in the decision-making regarding CTD by a computer simulation of decision-making using a genetic algorithm (GA) and a support vector machine (SVM). A total of 14 clinical parameters, including volume of pneumothorax calculated by our CAV scheme, was collected as parameters available for decision-making. The results showed that volume was the dominant parameter in decision-making regarding CTD, with an occurrence frequency value of 1.00. The results also indicated that the inclusion of volume provided the best performance that was statistically significant compared to the other tests in which volume was excluded from the clinical parameters. This study provides the scientific evidence for the application of CAV scheme in MDCT volumetric quantification of pneumothoraces in the management of clinically stable chest trauma patients with traumatic pneumothorax. PMID:22560899
Giannunzio, Valeria; Degortes, Daniela; Tenconi, Elena; Collantoni, Enrico; Solmi, Marco; Santonastaso, Paolo; Favaro, Angela
2018-07-01
Patients with anorexia nervosa (AN) often report difficulties in decision making, which may interfere with treatment. The aim of this study was to investigate decision making in a large sample of adolescent and adult patients with AN, by using the Iowa gambling task. Participants were 611 female individuals (310 patients and 301 controls) who underwent neuropsychological and clinical assessment. Significantly poorer decision-making performance was observed in adult patients, whereas no difference emerged between affected and nonaffected adolescents. Both adolescent and adult patients were characterized by trends for higher levels of attention to losses in comparison with healthy controls. Although healthy adult women exhibited better decision-making performance than healthy adolescents, in AN, there was no improvement of decision making with age. A cluster analysis identified 2 different styles of decision making in both patients and controls: a conservative style and an impulsive style. Our study provides evidence of dysfunctional decision making in adult patients with AN and reveals an association between poor decision making and excessive punishment sensitivity in AN. The clinical and scientific implications of these findings merit further exploration. Copyright © 2018 John Wiley & Sons, Ltd and Eating Disorders Association.
Working with interpreters: The challenges of introducing Option Grid patient decision aids.
Wood, Fiona; Phillips, Katie; Edwards, Adrian; Elwyn, Glyn
2017-03-01
We aimed to observe how an Option Grid™ decision aid for clinical encounters might be used where an interpreter is present, and to assess the impact of its use on shared decision making. Data were available from three clinical consultations between patient, clinician (a physiotherapist), and interpreter about knee osteoarthritis. Clinicians were trained in the use of an Option Grid decision aid and the tool was used. Consultations were audio-recorded, transcribed, and translated by independent translators into English. Analysis revealed the difficulties with introducing a written decision aid into an interpreted consultation. The extra discussion needed between the clinician and interpreter around the principles and purpose of shared decision making and instructions regarding the Option Grid decision aid proved challenging and difficult to manage. Discussion of treatment options while using an Option Grid decision aid was predominantly done between clinician and interpreter. The patient appeared to have little involvement in discussion of treatment options. Patients were not active participants within the discussion. Further work needs to be done on how shared decision making can be achieved within interpreted consultations. Option Grid decision aids are not being used as intended in interpreted consultations. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Applied Swarm-based medicine: collecting decision trees for patterns of algorithms analysis.
Panje, Cédric M; Glatzer, Markus; von Rappard, Joscha; Rothermundt, Christian; Hundsberger, Thomas; Zumstein, Valentin; Plasswilm, Ludwig; Putora, Paul Martin
2017-08-16
The objective consensus methodology has recently been applied in consensus finding in several studies on medical decision-making among clinical experts or guidelines. The main advantages of this method are an automated analysis and comparison of treatment algorithms of the participating centers which can be performed anonymously. Based on the experience from completed consensus analyses, the main steps for the successful implementation of the objective consensus methodology were identified and discussed among the main investigators. The following steps for the successful collection and conversion of decision trees were identified and defined in detail: problem definition, population selection, draft input collection, tree conversion, criteria adaptation, problem re-evaluation, results distribution and refinement, tree finalisation, and analysis. This manuscript provides information on the main steps for successful collection of decision trees and summarizes important aspects at each point of the analysis.
Boland, Laura; McIsaac, Daniel I; Lawson, Margaret L
2016-04-01
To explore multiple stakeholders' perceived barriers to and facilitators of implementing shared decision making and decision support in a tertiary paediatric hospital. An interpretive descriptive qualitative study was conducted using focus groups and interviews to examine senior hospital administrators', clinicians', parents' and youths' perceived barriers to and facilitators of shared decision making and decision support implementation. Data were analyzed using inductive thematic analysis. Fifty-seven stakeholders participated. Six barrier and facilitator themes emerged. The main barrier was gaps in stakeholders' knowledge of shared decision making and decision support. Facilitators included compatibility between shared decision making and the hospital's culture and ideal practices, perceptions of positive patient and family outcomes associated with shared decision making, and positive attitudes regarding shared decision making and decision support. However, youth attitudes regarding the necessity and usefulness of a decision support program were a barrier. Two themes were both a barrier and a facilitator. First, stakeholder groups were uncertain which clinical situations are suitable for shared decision making (eg, new diagnoses, chronic illnesses, complex decisions or urgent decisions). Second, the clinical process may be hindered if shared decision making and decision support decrease efficiency and workflow; however, shared decision making may reduce repeat visits and save time over the long term. Specific knowledge translation strategies that improve shared decision making knowledge and match specific barriers identified by each stakeholder group may be required to promote successful shared decision making and decision support implementation in the authors' paediatric hospital.
Evaluating the decision accuracy and speed of clinical data visualizations.
Pieczkiewicz, David S; Finkelstein, Stanley M
2010-01-01
Clinicians face an increasing volume of biomedical data. Assessing the efficacy of systems that enable accurate and timely clinical decision making merits corresponding attention. This paper discusses the multiple-reader multiple-case (MRMC) experimental design and linear mixed models as means of assessing and comparing decision accuracy and latency (time) for decision tasks in which clinician readers must interpret visual displays of data. These tools can assess and compare decision accuracy and latency (time). These experimental and statistical techniques, used extensively in radiology imaging studies, offer a number of practical and analytic advantages over more traditional quantitative methods such as percent-correct measurements and ANOVAs, and are recommended for their statistical efficiency and generalizability. An example analysis using readily available, free, and commercial statistical software is provided as an appendix. While these techniques are not appropriate for all evaluation questions, they can provide a valuable addition to the evaluative toolkit of medical informatics research.
Evolutions in clinical reasoning assessment: The Evolving Script Concordance Test.
Cooke, Suzette; Lemay, Jean-François; Beran, Tanya
2017-08-01
Script concordance testing (SCT) is a method of assessment of clinical reasoning. We developed a new type of SCT case design, the evolving SCT (E-SCT), whereby the patient's clinical story is "evolving" and with thoughtful integration of new information at each stage, decisions related to clinical decision-making become increasingly clear. We aimed to: (1) determine whether an E-SCT could differentiate clinical reasoning ability among junior residents (JR), senior residents (SR), and pediatricians, (2) evaluate the reliability of an E-SCT, and (3) obtain qualitative feedback from participants to help inform the potential acceptability of the E-SCT. A 12-case E-SCT, embedded within a 24-case pediatric SCT (PaedSCT), was administered to 91 pediatric residents (JR: n = 50; SR: n = 41). A total of 21 pediatricians served on the panel of experts (POE). A one-way analysis of variance (ANOVA) was conducted across the levels of experience. Participants' feedback on the E-SCT was obtained with a post-test survey and analyzed using two methods: percentage preference and thematic analysis. Statistical differences existed across levels of training: F = 19.31 (df = 2); p < 0.001. The POE scored higher than SR (mean difference = 10.34; p < 0.001) and JR (mean difference = 16.00; p < 0.001). SR scored higher than JR (mean difference = 5.66; p < 0.001). Reliability (Cronbach's α) was 0.83. Participants found the E-SCT engaging, easy to follow and true to the daily clinical decision-making process. The E-SCT demonstrated very good reliability and was effective in distinguishing clinical reasoning ability across three levels of experience. Participants found the E-SCT engaging and representative of real-life clinical reasoning and decision-making processes. We suggest that further refinement and utilization of the evolving style case will enhance SCT as a robust, engaging, and relevant method for the assessment of clinical reasoning.
Designing Real-time Decision Support for Trauma Resuscitations
Yadav, Kabir; Chamberlain, James M.; Lewis, Vicki R.; Abts, Natalie; Chawla, Shawn; Hernandez, Angie; Johnson, Justin; Tuveson, Genevieve; Burd, Randall S.
2016-01-01
Background Use of electronic clinical decision support (eCDS) has been recommended to improve implementation of clinical decision rules. Many eCDS tools, however, are designed and implemented without taking into account the context in which clinical work is performed. Implementation of the pediatric traumatic brain injury (TBI) clinical decision rule at one Level I pediatric emergency department includes an electronic questionnaire triggered when ordering a head computed tomography using computerized physician order entry (CPOE). Providers use this CPOE tool in less than 20% of trauma resuscitation cases. A human factors engineering approach could identify the implementation barriers that are limiting the use of this tool. Objectives The objective was to design a pediatric TBI eCDS tool for trauma resuscitation using a human factors approach. The hypothesis was that clinical experts will rate a usability-enhanced eCDS tool better than the existing CPOE tool for user interface design and suitability for clinical use. Methods This mixed-methods study followed usability evaluation principles. Pediatric emergency physicians were surveyed to identify barriers to using the existing eCDS tool. Using standard trauma resuscitation protocols, a hierarchical task analysis of pediatric TBI evaluation was developed. Five clinical experts, all board-certified pediatric emergency medicine faculty members, then iteratively modified the hierarchical task analysis until reaching consensus. The software team developed a prototype eCDS display using the hierarchical task analysis. Three human factors engineers provided feedback on the prototype through a heuristic evaluation, and the software team refined the eCDS tool using a rapid prototyping process. The eCDS tool then underwent iterative usability evaluations by the five clinical experts using video review of 50 trauma resuscitation cases. A final eCDS tool was created based on their feedback, with content analysis of the evaluations performed to ensure all concerns were identified and addressed. Results Among 26 EPs (76% response rate), the main barriers to using the existing tool were that the information displayed is redundant and does not fit clinical workflow. After the prototype eCDS tool was developed based on the trauma resuscitation hierarchical task analysis, the human factors engineers rated it to be better than the CPOE tool for nine of 10 standard user interface design heuristics on a three-point scale. The eCDS tool was also rated better for clinical use on the same scale, in 84% of 50 expert–video pairs, and was rated equivalent in the remainder. Clinical experts also rated barriers to use of the eCDS tool as being low. Conclusions An eCDS tool for diagnostic imaging designed using human factors engineering methods has improved perceived usability among pediatric emergency physicians. PMID:26300010
A Computational Model of Reasoning from the Clinical Literature
Rennels, Glenn D.
1986-01-01
This paper explores the premise that a formalized representation of empirical studies can play a central role in computer-based decision support. The specific motivations underlying this research include the following propositions: 1. Reasoning from experimental evidence contained in the clinical literature is central to the decisions physicians make in patient care. 2. A computational model, based upon a declarative representation for published reports of clinical studies, can drive a computer program that selectively tailors knowledge of the clinical literature as it is applied to a particular case. 3. The development of such a computational model is an important first step toward filling a void in computer-based decision support systems. Furthermore, the model may help us better understand the general principles of reasoning from experimental evidence both in medicine and other domains. Roundsman is a developmental computer system which draws upon structured representations of the clinical literature in order to critique plans for the management of primary breast cancer. Roundsman is able to produce patient-specific analyses of breast cancer management options based on the 24 clinical studies currently encoded in its knowledge base. The Roundsman system is a first step in exploring how the computer can help to bring a critical analysis of the relevant literature to the physician, structured around a particular patient and treatment decision.
NASA Astrophysics Data System (ADS)
Augustine, Kurt E.; Camp, Jon J.; Holmes, David R.; Huddleston, Paul M.; Lu, Lichun; Yaszemski, Michael J.; Robb, Richard A.
2012-03-01
Failure of the spine's structural integrity from metastatic disease can lead to both pain and neurologic deficit. Fractures that require treatment occur in over 30% of bony metastases. Our objective is to use computed tomography (CT) in conjunction with analytic techniques that have been previously developed to predict fracture risk in cancer patients with metastatic disease to the spine. Current clinical practice for cancer patients with spine metastasis often requires an empirical decision regarding spinal reconstructive surgery. Early image-based software systems used for CT analysis are time consuming and poorly suited for clinical application. The Biomedical Image Resource (BIR) at Mayo Clinic, Rochester has developed an image analysis computer program that calculates from CT scans, the residual load-bearing capacity in a vertebra with metastatic cancer. The Spine Cancer Assessment (SCA) program is built on a platform designed for clinical practice, with a workflow format that allows for rapid selection of patient CT exams, followed by guided image analysis tasks, resulting in a fracture risk report. The analysis features allow the surgeon to quickly isolate a single vertebra and obtain an immediate pre-surgical multiple parallel section composite beam fracture risk analysis based on algorithms developed at Mayo Clinic. The analysis software is undergoing clinical validation studies. We expect this approach will facilitate patient management and utilization of reliable guidelines for selecting among various treatment option based on fracture risk.
Elwyn, Glyn; Frosch, Dominick; Volandes, Angelo E; Edwards, Adrian; Montori, Victor M
2010-01-01
This article provides an analysis of 'decision aids', interventions to support patients facing tough decisions. Interest has increased since the concept of shared decision making has become widely considered to be a means of achieving desirable clinical outcomes. We consider the aims of these interventions and examine assumptions about their use. We propose three categories, interventions that are used in face-to-face encounters, those designed for use outside clinical encounters and those which are mediated, using telephone or other communication media. We propose the following definition: decision support interventions help people think about choices they face; they describe where and why choice exists; they provide information about options, including, where reasonable, the option of taking no action. These interventions help people to deliberate, independently or in collaboration with others, about options, by considering relevantattributes; they support people to forecast how they might feel about short, intermediate and long-term outcomes which have relevant consequences, in ways which help the process of constructing preferences and eventual decision making, appropriate to their individual situation. Although quality standards have been published for these interventions, we are also cautious about premature closure and consider that the need for short versions for use inside clinical encounters and long versions for external use requires further research. More work is also needed on the use of narrative formats and the translation of theory into practical designs. The interest in decision support interventions for patients heralds a transformation in clinical practice although many important areas remain unresolved.
Using the weighted area under the net benefit curve for decision curve analysis.
Talluri, Rajesh; Shete, Sanjay
2016-07-18
Risk prediction models have been proposed for various diseases and are being improved as new predictors are identified. A major challenge is to determine whether the newly discovered predictors improve risk prediction. Decision curve analysis has been proposed as an alternative to the area under the curve and net reclassification index to evaluate the performance of prediction models in clinical scenarios. The decision curve computed using the net benefit can evaluate the predictive performance of risk models at a given or range of threshold probabilities. However, when the decision curves for 2 competing models cross in the range of interest, it is difficult to identify the best model as there is no readily available summary measure for evaluating the predictive performance. The key deterrent for using simple measures such as the area under the net benefit curve is the assumption that the threshold probabilities are uniformly distributed among patients. We propose a novel measure for performing decision curve analysis. The approach estimates the distribution of threshold probabilities without the need of additional data. Using the estimated distribution of threshold probabilities, the weighted area under the net benefit curve serves as the summary measure to compare risk prediction models in a range of interest. We compared 3 different approaches, the standard method, the area under the net benefit curve, and the weighted area under the net benefit curve. Type 1 error and power comparisons demonstrate that the weighted area under the net benefit curve has higher power compared to the other methods. Several simulation studies are presented to demonstrate the improvement in model comparison using the weighted area under the net benefit curve compared to the standard method. The proposed measure improves decision curve analysis by using the weighted area under the curve and thereby improves the power of the decision curve analysis to compare risk prediction models in a clinical scenario.
Ranzani, Otavio T; Prina, Elena; Menéndez, Rosario; Ceccato, Adrian; Cilloniz, Catia; Méndez, Raul; Gabarrus, Albert; Barbeta, Enric; Bassi, Gianluigi Li; Ferrer, Miquel; Torres, Antoni
2017-11-15
The Sepsis-3 Task Force updated the clinical criteria for sepsis, excluding the need for systemic inflammatory response syndrome (SIRS) criteria. The clinical implications of the proposed flowchart including the quick Sequential (Sepsis-related) Organ Failure Assessment (qSOFA) and SOFA scores are unknown. To perform a clinical decision-making analysis of Sepsis-3 in patients with community-acquired pneumonia. This was a cohort study including adult patients with community-acquired pneumonia from two Spanish university hospitals. SIRS, qSOFA, the Confusion, Respiratory Rate and Blood Pressure (CRB) score, modified SOFA (mSOFA), the Confusion, Urea, Respiratory Rate, Blood Pressure and Age (CURB-65) score, and Pneumonia Severity Index (PSI) were calculated with data from the emergency department. We used decision-curve analysis to evaluate the clinical usefulness of each score and the primary outcome was in-hospital mortality. Of 6,874 patients, 442 (6.4%) died in-hospital. SIRS presented the worst discrimination, followed by qSOFA, CRB, mSOFA, CURB-65, and PSI. Overall, overestimation of in-hospital mortality and miscalibration was more evident for qSOFA and mSOFA. SIRS had lower net benefit than qSOFA and CRB, significantly increasing the risk of over-treatment and being comparable with the "treat-all" strategy. PSI had higher net benefit than mSOFA and CURB-65 for mortality, whereas mSOFA seemed more applicable when considering mortality/intensive care unit admission. Sepsis-3 flowchart resulted in better identification of patients at high risk of mortality. qSOFA and CRB outperformed SIRS and presented better clinical usefulness as prompt tools for patients with community-acquired pneumonia in the emergency department. Among the tools for a comprehensive patient assessment, PSI had the best decision-aid tool profile.
Whalen, Kimberly; Bavuso, Karen; Bouyer-Ferullo, Sharon; Goldsmith, Denise; Fairbanks, Amanda; Gesner, Emily; Lagor, Charles; Collins, Sarah
2016-01-01
To understand requests for nursing Clinical Decision Support (CDS) interventions at a large integrated health system undergoing vendor-based EHR implementation. In addition, to establish a process to guide both short-term implementation and long-term strategic goals to meet nursing CDS needs. We conducted an environmental scan to understand current state of nursing CDS over three months. The environmental scan consisted of a literature review and an analysis of CDS requests received from across our health system. We identified existing high priority CDS and paper-based tools used in nursing practice at our health system that guide decision-making. A total of 46 nursing CDS requests were received. Fifty-six percent (n=26) were specific to a clinical specialty; 22 percent (n=10) were focused on facilitating clinical consults in the inpatient setting. "Risk Assessments/Risk Reduction/Promotion of Healthy Habits" (n=23) was the most requested High Priority Category received for nursing CDS. A continuum of types of nursing CDS needs emerged using the Data-Information-Knowledge-Wisdom Conceptual Framework: 1) facilitating data capture, 2) meeting information needs, 3) guiding knowledge-based decision making, and 4) exposing analytics for wisdom-based clinical interpretation by the nurse. Identifying and prioritizing paper-based tools that can be modified into electronic CDS is a challenge. CDS strategy is an evolving process that relies on close collaboration and engagement with clinical sites for short-term implementation and should be incorporated into a long-term strategic plan that can be optimized and achieved overtime. The Data-Information-Knowledge-Wisdom Conceptual Framework in conjunction with the High Priority Categories established may be a useful tool to guide a strategic approach for meeting short-term nursing CDS needs and aligning with the organizational strategic plan.
Diagnostic Performance of Electronic Syndromic Surveillance Systems in Acute Care
Kashiouris, M.; O’Horo, J.C.; Pickering, B.W.; Herasevich, V.
2013-01-01
Context Healthcare Electronic Syndromic Surveillance (ESS) is the systematic collection, analysis and interpretation of ongoing clinical data with subsequent dissemination of results, which aid clinical decision-making. Objective To evaluate, classify and analyze the diagnostic performance, strengths and limitations of existing acute care ESS systems. Data Sources All available to us studies in Ovid MEDLINE, Ovid EMBASE, CINAHL and Scopus databases, from as early as January 1972 through the first week of September 2012. Study Selection: Prospective and retrospective trials, examining the diagnostic performance of inpatient ESS and providing objective diagnostic data including sensitivity, specificity, positive and negative predictive values. Data Extraction Two independent reviewers extracted diagnostic performance data on ESS systems, including clinical area, number of decision points, sensitivity and specificity. Positive and negative likelihood ratios were calculated for each healthcare ESS system. A likelihood matrix summarizing the various ESS systems performance was created. Results The described search strategy yielded 1639 articles. Of these, 1497 were excluded on abstract information. After full text review, abstraction and arbitration with a third reviewer, 33 studies met inclusion criteria, reporting 102,611 ESS decision points. The yielded I2 was high (98.8%), precluding meta-analysis. Performance was variable, with sensitivities ranging from 21% –100% and specificities ranging from 5%-100%. Conclusions There is significant heterogeneity in the diagnostic performance of the available ESS implements in acute care, stemming from the wide spectrum of different clinical entities and ESS systems. Based on the results, we introduce a conceptual framework using a likelihood ratio matrix for evaluation and meaningful application of future, frontline clinical decision support systems. PMID:23874359
Bodin, Julie; Garlantézec, Ronan; Costet, Nathalie; Descatha, Alexis; Fouquet, Natacha; Caroly, Sandrine; Roquelaure, Yves
2017-03-01
The aim of this study was to identify forms of work organization in a French region and to study associations with the occurrence of symptomatic and clinically diagnosed shoulder disorders in workers. Workers were randomly included in this cross-sectional study from 2002 to 2005. Sixteen organizational variables were assessed by a self-administered questionnaire: i.e. shift work, job rotation, repetitiveness of tasks, paced work/automatic rate, work pace dependent on quantified targets, permanent controls or surveillance, colleagues' work and customer demand, and eight variables measuring decision latitude. Five forms of work organization were identified using hierarchical cluster analysis (HCA) of variables and HCA of workers: low decision latitude with pace constraints, medium decision latitude with pace constraints, low decision latitude with low pace constraints, high decision latitude with pace constraints and high decision latitude with low pace constraints. There were significant associations between forms of work organization and symptomatic and clinically-diagnosed shoulder disorders. Copyright © 2016 Elsevier Ltd. All rights reserved.
Liaw, Siaw-Teng; Deveny, Elizabeth; Morrison, Iain; Lewis, Bryn
2006-09-01
Using a factorial vignette survey and modeling methodology, we developed clinical and information models - incorporating evidence base, key concepts, relevant terms, decision-making and workflow needed to practice safely and effectively - to guide the development of an integrated rule-based knowledge module to support prescribing decisions in asthma. We identified workflows, decision-making factors, factor use, and clinician information requirements. The Unified Modeling Language (UML) and public domain software and knowledge engineering tools (e.g. Protégé) were used, with the Australian GP Data Model as the starting point for expressing information needs. A Web Services service-oriented architecture approach was adopted within which to express functional needs, and clinical processes and workflows were expressed in the Business Process Execution Language (BPEL). This formal analysis and modeling methodology to define and capture the process and logic of prescribing best practice in a reference implementation is fundamental to tackling deficiencies in prescribing decision support software.
The anatomy of clinical decision-making in multidisciplinary cancer meetings
Soukup, Tayana; Petrides, Konstantinos V.; Lamb, Benjamin W.; Sarkar, Somita; Arora, Sonal; Shah, Sujay; Darzi, Ara; Green, James S. A.; Sevdalis, Nick
2016-01-01
Abstract In the UK, treatment recommendations for patients with cancer are routinely made by multidisciplinary teams in weekly meetings. However, their performance is variable. The aim of this study was to explore the underlying structure of multidisciplinary decision-making process, and examine how it relates to team ability to reach a decision. This is a cross-sectional observational study consisting of 1045 patient reviews across 4 multidisciplinary cancer teams from teaching and community hospitals in London, UK, from 2010 to 2014. Meetings were chaired by surgeons. We used a validated observational instrument (Metric for the Observation of Decision-making in Cancer Multidisciplinary Meetings) consisting of 13 items to assess the decision-making process of each patient discussion. Rated on a 5-point scale, the items measured quality of presented patient information, and contributions to review by individual disciplines. A dichotomous outcome (yes/no) measured team ability to reach a decision. Ratings were submitted to Exploratory Factor Analysis and regression analysis. The exploratory factor analysis produced 4 factors, labeled “Holistic and Clinical inputs” (patient views, psychosocial aspects, patient history, comorbidities, oncologists’, nurses’, and surgeons’ inputs), “Radiology” (radiology results, radiologists’ inputs), “Pathology” (pathology results, pathologists’ inputs), and “Meeting Management” (meeting chairs’ and coordinators’ inputs). A negative cross-loading was observed from surgeons’ input on the fourth factor with a follow-up analysis showing negative correlation (r = −0.19, P < 0.001). In logistic regression, all 4 factors predicted team ability to reach a decision (P < 0.001). Hawthorne effect is the main limitation of the study. The decision-making process in cancer meetings is driven by 4 underlying factors representing the complete patient profile and contributions to case review by all core disciplines. Evidence of dual-task interference was observed in relation to the meeting chairs’ input and their corresponding surgical input into case reviews. PMID:27310981
A novel computer based expert decision making model for prostate cancer disease management.
Richman, Martin B; Forman, Ernest H; Bayazit, Yildirim; Einstein, Douglas B; Resnick, Martin I; Stovsky, Mark D
2005-12-01
We propose a strategic, computer based, prostate cancer decision making model based on the analytic hierarchy process. We developed a model that improves physician-patient joint decision making and enhances the treatment selection process by making this critical decision rational and evidence based. Two groups (patient and physician-expert) completed a clinical study comparing an initial disease management choice with the highest ranked option generated by the computer model. Participants made pairwise comparisons to derive priorities for the objectives and subobjectives related to the disease management decision. The weighted comparisons were then applied to treatment options to yield prioritized rank lists that reflect the likelihood that a given alternative will achieve the participant treatment goal. Aggregate data were evaluated by inconsistency ratio analysis and sensitivity analysis, which assessed the influence of individual objectives and subobjectives on the final rank list of treatment options. Inconsistency ratios less than 0.05 were reliably generated, indicating that judgments made within the model were mathematically rational. The aggregate prioritized list of treatment options was tabulated for the patient and physician groups with similar outcomes for the 2 groups. Analysis of the major defining objectives in the treatment selection decision demonstrated the same rank order for the patient and physician groups with cure, survival and quality of life being more important than controlling cancer, preventing major complications of treatment, preventing blood transfusion complications and limiting treatment cost. Analysis of subobjectives, including quality of life and sexual dysfunction, produced similar priority rankings for the patient and physician groups. Concordance between initial treatment choice and the highest weighted model option differed between the groups with the patient group having 59% concordance and the physician group having only 42% concordance. This study successfully validated the usefulness of a computer based prostate cancer management decision making model to produce individualized, rational, clinically appropriate disease management decisions without physician bias.
Rotge, J-Y; Poitou, C; Fossati, P; Aron-Wisnewsky, J; Oppert, J-M
2017-08-01
There is evidence that obesity is associated with impairments in executive functions, such as deficits in decision-making, planning or problem solving, which might interfere with weight loss in obese individuals. We performed a systematic review and meta-analysis of decision-making abilities, as measured with the Iowa gambling task (IGT), in obesity without eating disorders. A systematic search was conducted to identify studies comparing IGT performances between groups of obese patients without eating disorders and groups of healthy control groups. The standardized mean differences were calculated for the total IGT scores and for the course of IGT scores. Meta-regression analyses were performed to explore the influence of clinical variables on standardized mean differences. Total IGT scores were significantly lower in obese patients compared with normal-weight healthy controls. IGT performances did not differ between groups for the first trials of the task. Significant effect sizes for the last trials of the task were subjected to a high degree of heterogeneity. Risky decision-making is impaired in obesity. The clinical importance of non-food-related decision-making impairments remains to be assessed especially in terms of consequences in daily life or the achievement of weight loss. This meta-analysis has been registered in the Prospero database (CRD42016037533). © 2017 World Obesity Federation.
Jefford, Elaine; Jomeen, Julie; Martin, Colin R
2016-04-28
The ability to act on and justify clinical decisions as autonomous accountable midwifery practitioners, is encompassed within many international regulatory frameworks, yet decision-making within midwifery is poorly defined. Decision-making theories from medicine and nursing may have something to offer, but fail to take into consideration midwifery context and philosophy and the decisional autonomy of women. Using an underpinning qualitative methodology, a decision-making framework was developed, which identified Good Clinical Reasoning and Good Midwifery Practice as two conditions necessary to facilitate optimal midwifery decision-making during 2nd stage labour. This study aims to confirm the robustness of the framework and describe the development of Enhancing Decision-making Assessment in Midwifery (EDAM) as a measurement tool through testing of its factor structure, validity and reliability. A cross-sectional design for instrument development and a 2 (country; Australia/UK) x 2 (Decision-making; optimal/sub-optimal) between-subjects design for instrument evaluation using exploratory and confirmatory factor analysis, internal consistency and known-groups validity. Two 'expert' maternity panels, based in Australia and the UK, comprising of 42 participants assessed 16 midwifery real care episode vignettes using the empirically derived 26 item framework. Each item was answered on a 5 point likert scale based on the level of agreement to which the participant felt each item was present in each of the vignettes. Participants were then asked to rate the overall decision-making (optimal/sub-optimal). Post factor analysis the framework was reduced to a 19 item EDAM measure, and confirmed as two distinct scales of 'Clinical Reasoning' (CR) and 'Midwifery Practice' (MP). The CR scale comprised of two subscales; 'the clinical reasoning process' and 'integration and intervention'. The MP scale also comprised two subscales; women's relationship with the midwife' and 'general midwifery practice'. EDAM would generally appear to be a robust, valid and reliable psychometric instrument for measuring midwifery decision-making, which performs consistently across differing international contexts. The 'women's relationship with midwife' subscale marginally failed to meet the threshold for determining good instrument reliability, which may be due to its brevity. Further research using larger samples and in a wider international context to confirm the veracity of the instrument's measurement properties and its wider global utility, would be advantageous.
Bianchi, Lorenzo; Schiavina, Riccardo; Borghesi, Marco; Bianchi, Federico Mineo; Briganti, Alberto; Carini, Marco; Terrone, Carlo; Mottrie, Alex; Gacci, Mauro; Gontero, Paolo; Imbimbo, Ciro; Marchioro, Giansilvio; Milanese, Giulio; Mirone, Vincenzo; Montorsi, Francesco; Morgia, Giuseppe; Novara, Giacomo; Porreca, Angelo; Volpe, Alessandro; Brunocilla, Eugenio
2018-04-06
To assess the predictive accuracy and the clinical value of a recent nomogram predicting cancer-specific mortality-free survival after surgery in pN1 prostate cancer patients through an external validation. We evaluated 518 prostate cancer patients treated with radical prostatectomy and pelvic lymph node dissection with evidence of nodal metastases at final pathology, at 10 tertiary centers. External validation was carried out using regression coefficients of the previously published nomogram. The performance characteristics of the model were assessed by quantifying predictive accuracy, according to the area under the curve in the receiver operating characteristic curve and model calibration. Furthermore, we systematically analyzed the specificity, sensitivity, positive predictive value and negative predictive value for each nomogram-derived probability cut-off. Finally, we implemented decision curve analysis, in order to quantify the nomogram's clinical value in routine practice. External validation showed inferior predictive accuracy as referred to in the internal validation (65.8% vs 83.3%, respectively). The discrimination (area under the curve) of the multivariable model was 66.7% (95% CI 60.1-73.0%) by testing with receiver operating characteristic curve analysis. The calibration plot showed an overestimation throughout the range of predicted cancer-specific mortality-free survival rates probabilities. However, in decision curve analysis, the nomogram's use showed a net benefit when compared with the scenarios of treating all patients or none. In an external setting, the nomogram showed inferior predictive accuracy and suboptimal calibration characteristics as compared to that reported in the original population. However, decision curve analysis showed a clinical net benefit, suggesting a clinical implication to correctly manage pN1 prostate cancer patients after surgery. © 2018 The Japanese Urological Association.
Haider, Adil H; Schneider, Eric B; Sriram, N; Dossick, Deborah S; Scott, Valerie K; Swoboda, Sandra M; Losonczy, Lia; Haut, Elliott R; Efron, David T; Pronovost, Peter J; Freischlag, Julie A; Lipsett, Pamela A; Cornwell, Edward E; MacKenzie, Ellen J; Cooper, Lisa A
2014-09-01
Recent studies have found that unconscious biases may influence physicians' clinical decision making. The objective of our study was to determine, using clinical vignettes, if unconscious race and class biases exist specifically among trauma/acute care surgeons and, if so, whether those biases impact surgeons' clinical decision making. A prospective Web-based survey was administered to active members of the Eastern Association for the Surgery of Trauma. Participants completed nine clinical vignettes, each with three trauma/acute care surgery management questions. Race Implicit Association Test (IAT) and social class IAT assessments were completed by each participant. Multivariable, ordered logistic regression analysis was then used to determine whether implicit biases reflected on the IAT tests were associated with vignette responses. In total, 248 members of the Eastern Association for the Surgery of Trauma participated. Of these, 79% explicitly stated that they had no race preferences and 55% stated they had no social class preferences. However, 73.5% of the participants had IAT scores demonstrating an unconscious preference toward white persons; 90.7% demonstrated an implicit preference toward upper social class persons. Only 2 of 27 vignette-based clinical decisions were associated with patient race or social class on univariate analyses. Multivariable analyses revealed no relationship between IAT scores and vignette-based clinical assessments. Unconscious preferences for white and upper-class persons are prevalent among trauma and acute care surgeons. In this study, these biases were not statistically significantly associated with clinical decision making. Further study of the factors that may prevent implicit biases from influencing patient management is warranted. Epidemiologic study, level II.
Chodzaza, Elizabeth; Haycock-Stuart, Elaine; Holloway, Aisha; Mander, Rosemary
2018-03-01
to explore Malawian midwives decision making when caring for women during the first stage of labour in the hospital setting. this focused ethnographic study examined the decision making process of 9 nurse-midwives with varying years of clinical experience in the real world setting of an urban and semi urban hospital from October 2013 to May 2014.This was done using 27 participant observations and 27 post-observation in-depth interviews over a period of six months. Qualitative data analysis software, NVivo 10, was used to assist with data management for the analysis. All data was analysed using the principle of theme and category formation. analysis revealed a six-stage process of decision making that include a baseline for labour, deciding to admit a woman to labour ward, ascertaining the normal physiological progress of labour, supporting the normal physiological progress of labour, embracing uncertainty: the midwives' construction of unusual labour as normal, dealing with uncertainty and deciding to intervene in unusual labour. This six-stage process of decision making is conceptualised as the 'role of cue acquisition', illustrating the ways in which midwives utilise their assessment of labouring women to reason and make decisions on how to care for them in labour. Cue acquisition involved the midwives piecing together segments of information they obtained from the women to formulate an understanding of the woman's birthing progress and inform the midwives decision making process. This understanding of cue acquisition by midwives is significant for supporting safe care in the labour setting. When there was uncertainty in a woman's progress of labour, midwives used deductive reasoning, for example, by cross-checking and analysing the information obtained during the span of labour. Supporting normal labour physiological processes was identified as an underlying principle that shaped the midwives clinical judgement and decision making when they cared for women in labour. the significance of this study is in the new understanding and insight into the process of midwifery decision making. Whilst the approach to decision making by the midwives requires further testing and refinement in order to explore implications for practice, the findings here provide new conceptual and practical clarity of midwifery decision making. The work contributes to the identified lack of knowledge of how midwives working clinically, in the 'real world setting. These findings therefore, contribute to this body of knowledge with regards to our understanding of decision making of midwives. Copyright © 2017 Elsevier Ltd. All rights reserved.
Wilbanks, Bryan A; Geisz-Everson, Marjorie; Boust, Rebecca R
2016-09-01
Clinical documentation is a critical tool in supporting care provided to patients. Sound documentation provides a picture of clinical events that can be used to improve patient care. However, many other uses for clinical documentation are equally important. Such documentation informs clinical decision support tools, creates a legal record of patient care, assists in financial reimbursement of services, and serves as a repository for secondary data analysis. Conversely, poor documentation can impair patient safety and increase malpractice risk exposure by reflecting poor or inaccurate information that ultimately may guide patient care decisions.Through an examination of anesthesia-related closed claims, a descriptive qualitative study emerged, which explored the antecedents and consequences of documentation quality in the claims reviewed. A secondary data analysis utilized a database generated by the American Association of Nurse Anesthetists Foundation closed claim review team. Four major themes emerged from the analysis. Themes 1, 2, and 4 primarily describe how poor documentation quality can have negative consequences for clinicians. The third theme primarily describes how poor documentation quality that can negatively affect patient safety.
Applying Statistical Process Control to Clinical Data: An Illustration.
ERIC Educational Resources Information Center
Pfadt, Al; And Others
1992-01-01
Principles of statistical process control are applied to a clinical setting through the use of control charts to detect changes, as part of treatment planning and clinical decision-making processes. The logic of control chart analysis is derived from principles of statistical inference. Sample charts offer examples of evaluating baselines and…
Analysis of Search on Clinical Narrative within the EHR
ERIC Educational Resources Information Center
Natarajan, Karthik
2012-01-01
Electronic Health Records (EHRs) are used increasingly in the hospital and outpatient settings, and patients are amassing digitized clinical information. On one hand, aggregating all the patient's clinical information can greatly assist health care workers in making sound decisions. On the other hand, it can result in information overload,…
Brandling, J; Kirby, K; Black, S; Voss, S; Benger, J
2017-07-25
There are approximately 60,000 out-of-hospital cardiac arrests (OHCA) in the United Kingdom (UK) each year. Within the UK there are well-established clinical practice guidelines that define when resuscitation should be commenced in OHCA, and when resuscitation should cease. Background literature indicates that decision-making in the commencement and cessation of resuscitation efforts in OHCA is complex, and not comprehensively understood. No relevant research from the UK has been published to date and this research study seeks to explore the influences on UK Emergency Medical Service (EMS) provider decision-making when commencing and ceasing resuscitation attempts in OHCA. The aim of this research to explore the influences on UK Emergency Medical Services provider decision-making when commencing and ceasing resuscitation attempts in OHCA. Four focus groups were convened with 16 clinically active EMS providers. Four case vignettes were discussed to explore decision-making within the focus groups. Thematic analysis was used to analyse transcripts. This research found that there are three stages in the decision-making process when EMS providers consider whether to commence or cease resuscitation attempts in OHCA. These stages are: the call; arrival on scene; the protocol. Influential factors present at each of the three stages can lead to different decisions and variability in practice. These influences are: factual information available to the EMS provider; structural factors such as protocol, guidance and research; cultural beliefs and values; interpersonal factors; risk factors; personal values and beliefs. An improved understanding of the circumstantial, individual and interpersonal factors that mediate the decision-making process in clinical practice could inform the development of more effective clinical guidelines, education and clinical decision support in OHCA. These changes have the potential to lead to greater consistency. and EMS provider confidence, with the potential for improved patient outcome from OHCA.
Decision theory and the evaluation of risks and benefits of clinical trials.
Bernabe, Rosemarie D C; van Thiel, Ghislaine J M W; Raaijmakers, Jan A M; van Delden, Johannes J M
2012-12-01
Research ethics committees (RECs) are tasked to assess the risks and the benefits of a clinical trial. In previous studies, it was shown that RECs find this task difficult, if not impossible, to do. The current approaches to benefit-risk assessment (i.e. Component Analysis and the Net Risk Test) confound the various risk-benefit tasks, and as such, make balancing impossible. In this article, we show that decision theory, specifically through the expected utility theory and multiattribute utility theory, enable for an explicit and ethically weighted risk-benefit evaluation. This makes a balanced ethical justification possible, and thus a more rationally defensible decision making. Copyright © 2012 Elsevier Ltd. All rights reserved.
Enhanced Decision-Making: The Use of a Videotape Decision-Aid for Patients with Prostate Cancer.
ERIC Educational Resources Information Center
Schapira, Marilyn M.; Meade, Cathy; Nattinger, Ann B.
1997-01-01
The development of a videotape for patients considering treatment options for clinically localized prostate cancer is described. The effectiveness of videotape in improving short-term recall of treatment options and outcomes was assessed quantitatively; qualitative analysis was used to assess the likelihood of patient's active participation in the…
Goodacre, Steve; Horspool, Kimberley; Nelson-Piercy, Catherine; Knight, Marian; Shephard, Neil; Lecky, Fiona; Thomas, Steven; Hunt, Beverley; Fuller, Gordon
2017-12-01
To determine whether clinical features (in the form of a clinical decision rule) or d-dimer can be used to select pregnant or postpartum women with suspected PE for diagnostic imaging. Observational cohort study augmented with additional cases. Consultant-led maternity units participating in the UK Obstetric Surveillance System (UKOSS) and emergency departments and maternity units at eleven prospectively recruiting sites. 198 pregnant or postpartum women with diagnosed PE identified through UKOSS and 324 pregnant or postpartum women with suspected PE from prospectively recruiting sites. Data were collected relating to clinical features, elements of clinical decision rules, d-dimer measurements, diagnostic imaging, treatment for PE and adverse outcomes. Women were classified as having or not having PE on the basis of diagnostic imaging, treatment and subsequent adverse outcomes. Primary analysis was limited to women with conclusive diagnostic imaging. Secondary analyses included women with clinically diagnosed or ruled out PE. The primary analysis included 181 women with PE and 259 without. Most clinical features showed no association with PE. The only exceptions were number of previous pregnancies over 24 weeks (p=0.017), no varicose veins (p=0.045), no recent long haul travel (p=0.006), recent surgery including caesarean section (p=0.001), increased temperature (p=0.003), low oxygen saturation (p<0.001), PE-related chest x-ray abnormality (p=0.01) and other chest x-ray abnormality (p=0.001).Clinical decision rules had areas under the receiver-operator characteristic curve ranging from 0.577 to 0.732. No clinically useful threshold for decision-making was identified for any rule. The sensitivities and specificities of d-dimer were 88.4% and 8.8% using the standard laboratory threshold and 69.8% and 32.8% using a pregnancy-specific threshold. Clinical decision rules, d-dimer and chest x-ray should not be used to select pregnant or postpartum women with suspected PE for diagnostic imaging. © 2017, Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
NASA Astrophysics Data System (ADS)
Prince, John R.
1982-12-01
Sensitivity, specificity, and predictive accuracy have been shown to be useful measures of the clinical efficacy of diagnostic tests and can be used to predict the potential improvement in diagnostic certitude resulting from the introduction of a competing technology. This communication demonstrates how the informal use of clinical decision analysis may guide health planners in the allocation of resources, purchasing decisions, and implementation of high technology. For didactic purposes the focus is on a comparison between conventional planar radioscintigraphy (RS) and single photon transverse section emission conputed tomography (SPECT). For example, positive predictive accuracy (PPA) for brain RS in a specialist hospital with a 50% disease prevalance is about 95%. SPECT should increase this predicted accuracy to 96%. In a primary care hospital with only a 15% disease prevalance the PPA is only 77% and SPECT may increase this accuracy to about 79%. Similar calculations based on published data show that marginal improvements are expected with SPECT in the liver. It is concluded that: a) The decision to purchase a high technology imaging modality such as SPECT for clinical purposes should be analyzed on an individual organ system and institutional basis. High technology may be justified in specialist hospitals but not necessarily in primary care hospitals. This is more dependent on disease prevalance than procedure volume; b) It is questionable whether SPECT imaging will be competitive with standard RS procedures. Research should concentrate on the development of different medical applications.
Analyzing the effectiveness of teaching and factors in clinical decision-making.
Hsieh, Ming-Chen; Lee, Ming-Shinn; Chen, Tsung-Ying; Tsai, Tsuen-Chiuan; Pai, Yi-Fong; Sheu, Min-Muh
2017-01-01
The aim of this study is to prepare junior physicians, clinical education should focus on the teaching of clinical decision-making. This research is designed to explore teaching of clinical decision-making and to analyze the benefits of an "Analogy guide clinical decision-making" as a learning intervention for junior doctors. This study had a "quasi-experimental design" and was conducted in a medical center in eastern Taiwan. Participants and Program Description: Thirty junior doctors and three clinical teachers were involved in the study. The experimental group (15) received 1 h of instruction from the "Analogy guide for teaching clinical decision-making" every day for 3 months. Program Evaluation: A "Clinical decision-making self-evaluation form" was used as the assessment tool to evaluate participant learning efficiency before and after the teaching program. Semi-structured qualitative research interviews were also conducted. We found using the analogy guide for teaching clinical decision-making could help enhance junior doctors' self-confidence. Important factors influencing clinical decision-making included workload, decision-making, and past experience. Clinical teaching using the analogy guide for clinical decision-making may be a helpful tool for training and can contribute to a more comprehensive understanding of decision-making.
Van den Bergh, An; Van Hemelryck, Sandy; Bevernage, Jan; Van Peer, Achiel; Brewster, Marcus; Mackie, Claire; Mannaert, Erik
2018-06-11
The aim of the presented retrospective analysis was to verify whether a previously proposed Janssen Biopharmaceutical Classification System (BCS)-like decision tree, based on preclinical bioavailability data of a solution and suspension formulation, would facilitate informed decision making on the clinical formulation development strategy. In addition, the predictive value of (in vitro) selection criteria, such as solubility, human permeability, and/or a clinical dose number (Do), were evaluated, potentially reducing additional supporting formulation bioavailability studies in animals. The absolute ( F abs,sol ) and relative ( F rel, susp/sol ) bioavailability of an oral solution and suspension, respectively, in rat or dog and the anticipated BCS classification were analyzed for 89 Janssen compounds with 28 of these having F rel,susp/sol and F abs,sol in both rat and dog at doses around 10 and 5 mg/kg, respectively. The bioavailability outcomes in the dog aligned well with a BCS-like classification based upon the solubility of the active pharmaceutical ingredient (API) in biorelevant media, while the alignment was less clear for the bioavailability data in the rat. A retrospective analysis on the clinically tested formulations for a set of 12 Janssen compounds confirmed that the previously proposed animal bioavailability-based decision tree facilitated decisions on the oral formulation type, with the dog as the most discriminative species. Furthermore, the analysis showed that based on a Do for a standard human dose of 100 mg in aqueous and/or biorelevant media, a similar formulation type would have been selected compared to the one suggested by the animal data. However, the concept of a Do did not distinguish between solubility enhancing or enabling formulations and does not consider the API permeability, and hence, it produces the risk of slow and potentially incomplete oral absorption of an API with poor intestinal permeability. In cases where clinical dose estimations are available early in development, the preclinical bioavailability studies and dose number calculations, used to guide formulation selection, may be performed at more relevant doses instead of the proposed standard human dose. It should be noted, however, that unlike in late development, there is uncertainty on the clinical dose estimated in the early clinical phases because that dose is usually only based on in vitro and/or in vivo animal pharmacology models, or early clinical biomarker information. Therefore, formulation strategies may be adjusted based on emerging data supporting clinical doses. In summary, combined early information on in vitro-assessed API solubility and permeability, preclinical suspension/solution bioavailability data in relation to the intravenous clearance, and metabolic pathways of the API can strengthen formulation decisions. However, these data may not always fully distinguish between conventional (e.g., to be taken with food), enhancing, and enabling formulations. Therefore, to avoid overinvestment in complex and expensive enabling technologies, it is useful to evaluate a conventional and solubility (and/or permeability) enhancing formulation under fasted and fed conditions, as part of a first-in-human study or in a subsequent early human bioavailability study, for compounds with high Do, a low animal F rel,susp/sol , or low F abs,sol caused by precipitation of the solubilized API.
Interpretation of diagnostic data: 6. How to do it with more complex maths.
1983-11-15
We have now shown you how to use decision analysis in making those rare, tough diagnostic decisions that are not soluble through other, easier routes. In summary, to "use more complex maths" the following steps will be useful: Create a decision tree or map of all the pertinent courses of action and their consequences. Assign probabilities to the branches of each chance node. Assign utilities to each of the potential outcomes shown on the decision tree. Combine the probabilities and utilities for each node on the decision tree. Pick the decision that leads to the highest expected utility. Test your decision for its sensitivity to clinically sensible changes in probabilities and utilities. That concludes this series of clinical epidemiology rounds. You've come a long way from "doing it with pictures" and are now able to extract most of the diagnostic information that can be provided from signs, symptoms and laboratory investigations. We would appreciate learning whether you have found this series useful and how we can do a better job of presenting these and other elements of "the science of the art of medicine".
Bexkens, Anika; Jansen, Brenda R J; Van der Molen, Maurits W; Huizenga, Hilde M
2016-02-01
Adolescents with Behavior Disorders (BD), Mild-to-Borderline Intellectual Disability (MBID), and with both BD and MBID (BD + MBID) are known to take more risks than normal controls. To examine the processes underlying this increased risk-taking, the present study investigated cool decision-making strategies in 479 adolescents (12-18 years, 55.9 % male) from these four groups. Cool decision-making was assessed with the paper-and-pencil Gambling Machine Task. This task, in combination with advanced latent group analysis, allows for an assessment of decision strategies. Results indicated that adolescents with BD and controls were almost equivalent in their decision-making strategies, whereas adolescents with MBID and adolescents with BD + MBID were characterized by suboptimal decision-making strategies, with only minor differences between these two clinical groups. These findings may have important clinical implications, as they suggest that risk taking in adolescents with MBID and in adolescents with BD + MBID can be (partly) attributed to the strategies that these adolescents use to make their decisions. Interventions may therefore focus on an improvement of these strategies.
Decision curve analysis to compare 3 versions of Partin Tables to predict final pathologic stage.
Augustin, Herbert; Sun, Maxine; Isbarn, Hendrik; Pummer, Karl; Karakiewicz, Pierre
2012-01-01
To perform a decision curve analysis (DCA) to compare the Partin Tables 1997, 2001, and 2007 for their clinical applicability. Clinical and pathologic data of 687 consecutive patients treated with open radical prostatectomy for clinically localized prostate cancer between 2003 and 2008 at a single institution were used. DCA quantified the net benefit relating to specific threshold probabilities of extraprostatic extension (EPE), seminal vesicle involvement (SVI), and lymph node involvement (LNI). Overall, EPE, SVI, and LNI were recorded in 17.8, 6.0, and 1.2%, respectively. For EPE predictions, the DCA favored the 2007 version vs. 1997 for SVI vs. none of the versions for LNI. DCA indicate that for very low prevalence conditions such as LNI (1.2%), decision models are not useful. For low prevalence rates such as SVI, the use of different versions of the Partin Tables does not translate into meaningful net gains differences. Finally, for intermediate prevalence conditions such as EPE (18%), despite apparent performance differences, the net benefit differences were also marginal. In consequence, the current analysis could not confirm an important benefit from the use of the Partin Tables and it could not identify a clearly better version of any of the 3 available iterations. Copyright © 2012 Elsevier Inc. All rights reserved.
Carbogim, Fábio da Costa; de Oliveira, Larissa Bertacchini; Püschel, Vilanice Alves de Araújo
2016-01-01
ABSTRACT Objective: to analyze the concept of critical thinking (CT) in Rodger's evolutionary perspective. Method: documentary research undertaken in the Cinahl, Lilacs, Bdenf and Dedalus databases, using the keywords of 'critical thinking' and 'Nursing', without limitation based on year of publication. The data were analyzed in accordance with the stages of Rodger's conceptual model. The following were included: books and articles in full, published in Portuguese, English or Spanish, which addressed CT in the teaching and practice of Nursing; articles which did not address aspects related to the concept of CT were excluded. Results: the sample was made up of 42 works. As a substitute term, emphasis is placed on 'analytical thinking', and, as a related factor, decision-making. In order, the most frequent preceding and consequent attributes were: ability to analyze, training of the student nurse, and clinical decision-making. As the implications of CT, emphasis is placed on achieving effective results in care for the patient, family and community. Conclusion: CT is a cognitive skill which involves analysis, logical reasoning and clinical judgment, geared towards the resolution of problems, and standing out in the training and practice of the nurse with a view to accurate clinical decision-making and the achieving of effective results. PMID:27598376
Pattern Analysis and Decision Support for Cancer through Clinico-Genomic Profiles
NASA Astrophysics Data System (ADS)
Exarchos, Themis P.; Giannakeas, Nikolaos; Goletsis, Yorgos; Papaloukas, Costas; Fotiadis, Dimitrios I.
Advances in genome technology are playing a growing role in medicine and healthcare. With the development of new technologies and opportunities for large-scale analysis of the genome, genomic data have a clear impact on medicine. Cancer prognostics and therapeutics are among the first major test cases for genomic medicine, given that all types of cancer are related with genomic instability. In this paper we present a novel system for pattern analysis and decision support in cancer. The system integrates clinical data from electronic health records and genomic data. Pattern analysis and data mining methods are applied to these integrated data and the discovered knowledge is used for cancer decision support. Through this integration, conclusions can be drawn for early diagnosis, staging and cancer treatment.
LeBlanc, Annie; Ruud, Kari L; Branda, Megan E; Tiedje, Kristina; Boehmer, Kasey R; Pencille, Laurie J; Van Houten, Holly; Matthews, Marc; Shah, Nilay D; May, Carl R; Yawn, Barbara P; Montori, Victor M
2012-05-28
Shared decision making contributes to high quality healthcare by promoting a patient-centered approach. Patient involvement in selecting the components of a diabetes medication program that best match the patient's values and preferences may also enhance medication adherence and improve outcomes. Decision aids are tools designed to involve patients in shared decision making, but their adoption in practice has been limited. In this study, we propose to obtain a preliminary estimate of the impact of patient decision aids vs. usual care on measures of patient involvement in decision making, diabetes care processes, medication adherence, glycemic and cardiovascular risk factor control, and resource utilization. In addition, we propose to identify, describe, and explain factors that promote or inhibit the routine embedding of decision aids in practice. We will be conducting a mixed-methods study comprised of a cluster-randomized, practical, multicentered trial enrolling clinicians and their patients (n = 240) with type 2 diabetes from rural and suburban primary care practices (n = 8), with an embedded qualitative study to examine factors that influence the incorporation of decision aids into routine practice. The intervention will consist of the use of a decision aid (Statin Choice and Aspirin Choice, or Diabetes Medication Choice) during the clinical encounter. The qualitative study will include analysis of video recordings of clinical encounters and in-depth, semi-structured interviews with participating patients, clinicians, and clinic support staff, in both trial arms. Upon completion of this trial, we will have new knowledge about the effectiveness of diabetes decision aids in these practices. We will also better understand the factors that promote or inhibit the successful implementation and normalization of medication choice decision aids in the care of chronic patients in primary care practices. NCT00388050.
Berggren, Ingela; Severinsson, Elisabeth
2003-03-01
The aim of the study was to explore the decision-making style and ethical approach of nurse supervisors by focusing on their priorities and interventions in the supervision process. Clinical supervision promotes ethical awareness and behaviour in the nursing profession. A focus group comprised of four clinical nurse supervisors with considerable experience was studied using qualitative hermeneutic content analysis. The essence of the nurse supervisors' decision-making style is deliberations and priorities. The nurse supervisors' willingness, preparedness, knowledge and awareness constitute and form their way of creating a relationship. The nurse supervisors' ethical approach focused on patient situations and ethical principles. The core components of nursing supervision interventions, as demonstrated in supervision sessions, are: guilt, reconciliation, integrity, responsibility, conscience and challenge. The nurse supervisors' interventions involved sharing knowledge and values with the supervisees and recognizing them as nurses and human beings. Nurse supervisors frequently reflected upon the ethical principle of autonomy and the concept and substance of integrity. The nurse supervisors used an ethical approach that focused on caring situations in order to enhance the provision of patient care. They acted as role models, shared nursing knowledge and ethical codes, and focused on patient related situations. This type of decision-making can strengthen the supervisees' professional identity. The clinical nurse supervisors in the study were experienced and used evaluation decisions as their form of clinical decision-making activity. The findings underline the need for further research and greater knowledge in order to improve the understanding of the ethical approach to supervision.
Boland, Laura; McIsaac, Daniel I; Lawson, Margaret L
2016-01-01
OBJECTIVE: To explore multiple stakeholders’ perceived barriers to and facilitators of implementing shared decision making and decision support in a tertiary paediatric hospital. METHODS: An interpretive descriptive qualitative study was conducted using focus groups and interviews to examine senior hospital administrators’, clinicians’, parents’ and youths’ perceived barriers to and facilitators of shared decision making and decision support implementation. Data were analyzed using inductive thematic analysis. RESULTS: Fifty-seven stakeholders participated. Six barrier and facilitator themes emerged. The main barrier was gaps in stakeholders’ knowledge of shared decision making and decision support. Facilitators included compatibility between shared decision making and the hospital’s culture and ideal practices, perceptions of positive patient and family outcomes associated with shared decision making, and positive attitudes regarding shared decision making and decision support. However, youth attitudes regarding the necessity and usefulness of a decision support program were a barrier. Two themes were both a barrier and a facilitator. First, stakeholder groups were uncertain which clinical situations are suitable for shared decision making (eg, new diagnoses, chronic illnesses, complex decisions or urgent decisions). Second, the clinical process may be hindered if shared decision making and decision support decrease efficiency and workflow; however, shared decision making may reduce repeat visits and save time over the long term. CONCLUSIONS: Specific knowledge translation strategies that improve shared decision making knowledge and match specific barriers identified by each stakeholder group may be required to promote successful shared decision making and decision support implementation in the authors’ paediatric hospital. PMID:27398058
Camacho, Jhon; Medina Ch, Ana María; Landis-Lewis, Zach; Douglas, Gerald; Boyce, Richard
2018-04-13
The distribution of printed materials is the most frequently used strategy to disseminate and implement clinical practice guidelines, although several studies have shown that the effectiveness of this approach is modest at best. Nevertheless, there is insufficient evidence to support the use of other strategies. Recent research has shown that the use of computerized decision support presents a promising approach to address some aspects of this problem. The aim of this study is to provide qualitative evidence on the potential effect of mobile decision support systems to facilitate the implementation of evidence-based recommendations included in clinical practice guidelines. We will conduct a qualitative study with two arms to compare the experience of primary care physicians while they try to implement an evidence-based recommendation in their clinical practice. In the first arm, we will provide participants with a printout of the guideline article containing the recommendation, while in the second arm, we will provide participants with a mobile app developed after formalizing the recommendation text into a clinical algorithm. Data will be collected using semistructured and open interviews to explore aspects of behavioral change and technology acceptance involved in the implementation process. The analysis will be comprised of two phases. During the first phase, we will conduct a template analysis to identify barriers and facilitators in each scenario. Then, during the second phase, we will contrast the findings from each arm to propose hypotheses about the potential impact of the system. We have formalized the narrative in the recommendation into a clinical algorithm and have developed a mobile app. Data collection is expected to occur during 2018, with the first phase of analysis running in parallel. The second phase is scheduled to conclude in July 2019. Our study will further the understanding of the role of mobile decision support systems in the implementation of clinical practice guidelines. Furthermore, we will provide qualitative evidence to aid decisions made by low- and middle-income countries' ministries of health about investments in these technologies. ©Jhon Camacho, Ana María Medina Ch, Zach Landis-Lewis, Gerald Douglas, Richard Boyce. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 13.04.2018.
Decision analysis applied to the purchase of frozen premixed intravenous admixtures.
Witte, K W; Eck, T A; Vogel, D P
1985-04-01
A structured decision-analysis model was used to evaluate frozen premixed cefazolin admixtures. Decision analysis is a process of stating the desired outcome, establishing and weighting evaluation criteria, identifying options for reaching the outcome, evaluating and numerically ranking each option for each criterion, multiplying the ranking by the weight for each criterion, and calculating total points for each option. It was used to compare objectively frozen premixed cefazolin admixtures with batch reconstitution from vials and reconstitution of lyophilized, ready-to-mix containers. In this institution the model numerically demonstrated a distinct preference for the premixed frozen admixture over these other alternatives. A comparison of these results with the total cost impact of each option resulted in a decision to purchase the frozen premixed solution. The advantages of the frozen premixed solution that contributed most to this decision were decreased waste and personnel time. The latter was especially important since it allowed for the reallocation of personnel resources to other potentially cost-reducing clinical functions. Decision analysis proved to be an effective tool for formalizing the process of selecting among various alternatives to reach a desired outcome in this hospital pharmacy.
Periodic benefit-risk assessment using Bayesian stochastic multi-criteria acceptability analysis.
Li, Kan; Yuan, Shuai Sammy; Wang, William; Wan, Shuyan Sabrina; Ceesay, Paulette; Heyse, Joseph F; Mt-Isa, Shahrul; Luo, Sheng
2018-04-01
Benefit-risk (BR) assessment is essential to ensure the best decisions are made for a medical product in the clinical development process, regulatory marketing authorization, post-market surveillance, and coverage and reimbursement decisions. One challenge of BR assessment in practice is that the benefit and risk profile may keep evolving while new evidence is accumulating. Regulators and the International Conference on Harmonization (ICH) recommend performing periodic benefit-risk evaluation report (PBRER) through the product's lifecycle. In this paper, we propose a general statistical framework for periodic benefit-risk assessment, in which Bayesian meta-analysis and stochastic multi-criteria acceptability analysis (SMAA) will be combined to synthesize the accumulating evidence. The proposed approach allows us to compare the acceptability of different drugs dynamically and effectively and accounts for the uncertainty of clinical measurements and imprecise or incomplete preference information of decision makers. We apply our approaches to two real examples in a post-hoc way for illustration purpose. The proposed method may easily be modified for other pre and post market settings, and thus be an important complement to the current structured benefit-risk assessment (sBRA) framework to improve the transparent and consistency of the decision-making process. Copyright © 2018 Elsevier Inc. All rights reserved.
Garfield, S; Smith, F; Francis, S A; Chalmers, C
2007-06-01
The current study aimed to develop a model of patients' preferences for involvement in decision-making concerning the use of medicines for chronic conditions in the UK and test it in a large representative sample of patients with one of two clinical conditions. Following a structured literature review, an instrument was developed which measured the variables that had been identified as predictors of patients' preferences for involvement in decision making in previous research. Five hundred and sixteen patients with rheumatoid arthritis or type 2 diabetes were recruited from outpatient and primary care clinics and asked to complete the instrument. Multivariate analysis revealed that age, social class and clinical condition were associated with preferences for involvement in decision-making concerning the use of medicines for chronic illness but gender, ethnic group, concerns about medicines, beliefs about necessity of medicines, health status, quality of life and time since diagnosis were not. In total, the fitted model explained only 14% of the variance. This study has demonstrated that current research does not provide a basis for predicting patients' preferences for involvement in decision-making. Building concordant relationships may depend on practitioners developing strategies to establish individuals' preferences for involvement in decision-making as part of the ongoing prescriber-patient relationship.
Incorporating the patient experience into regulatory decision making in the USA, Europe, and Canada.
Kluetz, Paul G; O'Connor, Daniel J; Soltys, Katherine
2018-05-01
The clinical development of cancer therapeutics is a global undertaking, and incorporation of the patient experience into the clinical decision-making process is of increasing interest to the international regulatory and health policy community. Disease and treatment-related symptoms and their effect on patient function and health-related quality of life are important outcomes to consider. The identification of methods to scientifically assess, analyse, interpret, and present these clinical outcomes requires sustained international collaboration by multiple stakeholders including patients, clinicians, scientists, and policy makers. Several data sources can be considered to capture the patient experience, including patient-reported outcome (PRO) measures, performance measures, wearable devices, and biosensors, as well as the careful collection and analysis of clinical events and supportive care medications. In this Policy Review, we focus on PRO measures and present the perspectives of three international regulatory scientists to identify areas of common ground regarding opportunities to incorporate rigorous PRO data into the regulatory decision-making process. Copyright © 2018 Elsevier Ltd. All rights reserved.
[Development and clinical evaluation of an anesthesia information management system].
Feng, Jing-yi; Chen, Hua; Zhu, Sheng-mei
2010-09-21
To study the design, implementation and clinical evaluation of an anesthesia information management system. To record, process and store peri-operative patient data automatically, all kinds of bedside monitoring equipments are connected into the system based on information integrating technology; after a statistical analysis of those patient data by data mining technology, patient status can be evaluated automatically based on risk prediction standard and decision support system, and then anesthetist could perform reasonable and safe clinical processes; with clinical processes electronically recorded, standard record tables could be generated, and clinical workflow is optimized, as well. With the system, kinds of patient data could be collected, stored, analyzed and archived, kinds of anesthesia documents could be generated, and patient status could be evaluated to support clinic decision. The anesthesia information management system is useful for improving anesthesia quality, decreasing risk of patient and clinician, and aiding to provide clinical proof.
Williams, Robert L; Romney, Crystal; Kano, Miria; Wright, Randy; Skipper, Betty; Getrich, Christina M; Sussman, Andrew L; Zyzanski, Stephen J
2015-06-01
Research suggests stereotyping by clinicians as one contributor to racial and gender-based health disparities. It is necessary to understand the origins of such biases before interventions can be developed to eliminate them. As a first step toward this understanding, we tested for the presence of bias in senior medical students. The purpose of the study was to determine whether bias based on race, gender, or socioeconomic status influenced clinical decision-making among medical students. We surveyed seniors at 84 medical schools, who were required to choose between two clinically equivalent management options for a set of cardiac patient vignettes. We examined variations in student recommendations based on patient race, gender, and socioeconomic status. The study included senior medical students. We investigated the percentage of students selecting cardiac procedural options for vignette patients, analyzed by patient race, gender, and socioeconomic status. Among 4,603 returned surveys, we found no evidence in the overall sample supporting racial or gender bias in student clinical decision-making. Students were slightly more likely to recommend cardiac procedural options for black (43.9 %) vs. white (42 %, p = .03) patients; there was no difference by patient gender. Patient socioeconomic status was the strongest predictor of student recommendations, with patients described as having the highest socioeconomic status most likely to receive procedural care recommendations (50.3 % vs. 43.2 % for those in the lowest socioeconomic status group, p < .001). Analysis by subgroup, however, showed significant regional geographic variation in the influence of patient race and gender on decision-making. Multilevel analysis showed that white female patients were least likely to receive procedural recommendations. In the sample as a whole, we found no evidence of racial or gender bias in student clinical decision-making. However, we did find evidence of bias with regard to the influence of patient socioeconomic status, geographic variations, and the influence of interactions between patient race and gender on student recommendations.
The relationship between patient data and pooled clinical management decisions.
Ludbrook, G I; O'Loughlin, E J; Corcoran, T B; Grant, C
2013-01-01
A strong relationship between patient data and preoperative clinical decisions could potentially be used to support clinical decisions in preoperative management. The aim of this exploratory study was to determine the relationship between key patient data and pooled clinical opinions on management. In a previous study, panels of anaesthetists compared the quality of computer-assisted patient health assessments with outpatient consultations and made decisions on the need for preoperative tests, no preoperative outpatient assessment, possible postoperative intensive care unit/high dependency unit requirements and aspiration prophylaxis. In the current study, the relationship between patient data and these decisions was examined using binomial logistic regression analysis. Backward stepwise regression was used to identify independent predictors of each decision (at P >0.15), which were then incorporated into a predictive model. The number of factors related to each decision varied: blood picture (four factors), biochemistry (six factors), coagulation studies (three factors), electrocardiography (eight factors), chest X-ray (seven factors), preoperative outpatient assessment (17 factors), intensive care unit requirement (eight factors) and aspiration prophylaxis (one factor). The factor types also varied, but included surgical complexity, age, gender, number of medications or comorbidities, body mass index, hypertension, central nervous system condition, heart disease, sleep apnoea, smoking, persistent pain and stroke. Models based on these relationships usually demonstrated good sensitivity and specificity, with receiver operating characteristics in the following areas under curve: blood picture (0.75), biochemistry (0.86), coagulation studies (0.71), electrocardiography (0.90), chest X-ray (0.85), outpatient assessment (0.85), postoperative intensive care unit requirement (0.88) and aspiration prophylaxis (0.85). These initial results suggest modelling of patient data may have utility supporting clinicians' preoperative decisions.
Colorectal cancer patients' attitudes towards involvement in decision making.
Beaver, Kinta; Campbell, Malcolm; Craven, Olive; Jones, David; Luker, Karen A; Susnerwala, Shabbir S
2009-03-01
To design and administer an attitude rating scale, exploring colorectal cancer patients' views of involvement in decision making. To examine the impact of socio-demographic and/or treatment-related factors on decision making. To conduct principal components analysis to determine if the scale could be simplified into a number of factors for future clinical utility. An attitude rating scale was constructed based on previous qualitative work and administered to colorectal cancer patients using a cross-sectional survey approach. 375 questionnaires were returned (81.7% response). For patients it was important to be informed and involved in the decision-making process. Information was not always used to make decisions as patients placed their trust in medical expertise. Women had more positive opinions on decision making and were more likely to want to make decisions. Written information was understood to a greater degree than verbal information. The scale could be simplified to a number of factors, indicating clinical utility. Few studies have explored the attitudes of colorectal cancer patients towards involvement in decision making. This study presents new insights into how patients view the concept of participation; important when considering current policy imperatives in the UK of involving service users in all aspects of care and treatment.
Fallon, Barbara; Chabot, Martin; Fluke, John; Blackstock, Cindy; Sinha, Vandna; Allan, Kate; MacLaurin, Bruce
2015-11-01
A series of papers using data from the Canadian Incidence Study of Reported Child Abuse and Neglect (CIS) explored the influence of clinical and organizational characteristics on the decision to place Aboriginal children in out-of-home placements at the conclusion of child maltreatment investigations. The purpose of this paper is to further explore a consistent finding of the previous analyses: the proportion of investigations involving Aboriginal children at a child welfare agency is associated with placement for all children in that agency. CIS-2008 data were used in the analysis, which allowed for inclusion of previously unavailable organizational and contextual variables. Multi-level statistical models were developed to analyze the influence of clinical and organizational variables on the placement decision. Final models revealed that the proportion of investigations conducted by the child welfare agency involving Aboriginal children was again a key agency-level predictor of the placement decision for any child served by the agency. Specifically, the higher the proportion of investigations of Aboriginal children, the more likely placement was to occur for any child. Further, this analysis demonstrated that structure of governance, an organizational-level variable not available in previous cycles of the CIS, is an important agency-level predictor of out-of-home placement. Further analysis is needed to fully understand individual and organizational level variables that may influence decisions regarding placement of Aboriginal children. Copyright © 2015 Elsevier Ltd. All rights reserved.
Hostiuc, Sorin; Rusu, Mugurel Constantin; Negoi, Ionut; Drima, Eduard
2018-01-05
The process of assessing the decision-making capacity of potential subjects before their inclusion in clinical trials is a legal requirement and a moral obligation, as it is essential for respecting their autonomy. This issue is especially important in psychiatry patients (such as those diagnosed with schizophrenia). The primary purpose of this article was to evaluate the degree of impairment in each dimension of decision-making capacity in schizophrenia patients compared to non-mentally-ill controls, as quantified by the (MacCAT-CR) instrument. Secondary objectives were (1) to see whether enhanced consent forms are associated with a significant increase in decision-making capacity in schizophrenia patients, and (2) if decision-making capacity in schizophrenia subjects is dependent on the age, gender, or the inpatient status of the subjects. We systematically reviewed the results obtained from three databases: ISI Web of Science, Pubmed, Scopus. Each database was scrutinised using the following keywords: "MacCAT-CR + schizophrenia", "decision-making capacity + schizophrenia", and "informed consent + schizophrenia." We included 13 studies in the analysis. The effect size between the schizophrenia and the control group was significant, with a difference in means of -4.43 (-5.76; -3.1, p < 0.001) for understanding, -1.17 (-1.49, -0.84, p < 0.001) for appreciation, -1.29 (-1.79, -0.79, p < 0.001) for reasoning, and -0.05 (-0.9, -0.01, p = 0.022) for expressing a choice. Even if schizophrenia patients have a significantly decreased decision-making capacity compared to non-mentally-ill controls, they should be considered as competent unless very severe changes are identifiable during clinical examination. Enhanced informed consent forms decrease the differences between schizophrenia patients and non-mentally-ill controls (except for the reasoning dimension) and should be used whenever the investigators want to include more ill patients in their clinical trials. Increased age, men gender and an increased percentage of inpatients might increase the differential of decision-making incompetence compared to non-mentally-ill subjects in various dimensions of the decision-making competence as analysed by the MacCAT-CR scale, but the small number of subjects did not allow us (except for one instance) to reach statistical significance.
Richter Sundberg, Linda; Garvare, Rickard; Nyström, Monica Elisabeth
2017-05-11
The judgment and decision making process during guideline development is central for producing high-quality clinical practice guidelines, but the topic is relatively underexplored in the guideline research literature. We have studied the development process of national guidelines with a disease-prevention scope produced by the National board of Health and Welfare (NBHW) in Sweden. The NBHW formal guideline development model states that guideline recommendations should be based on five decision-criteria: research evidence; curative/preventive effect size, severity of the condition; cost-effectiveness; and ethical considerations. A group of health profession representatives (i.e. a prioritization group) was assigned the task of ranking condition-intervention pairs for guideline recommendations, taking into consideration the multiple decision criteria. The aim of this study was to investigate the decision making process during the two-year development of national guidelines for methods of preventing disease. A qualitative inductive longitudinal case study approach was used to investigate the decision making process. Questionnaires, non-participant observations of nine two-day group meetings, and documents provided data for the analysis. Conventional and summative qualitative content analysis was used to analyse data. The guideline development model was modified ad-hoc as the group encountered three main types of dilemmas: high quality evidence vs. low adoptability of recommendation; insufficient evidence vs. high urgency to act; and incoherence in assessment and prioritization within and between four different lifestyle areas. The formal guideline development model guided the decision-criteria used, but three new or revised criteria were added by the group: 'clinical knowledge and experience', 'potential guideline consequences' and 'needs of vulnerable groups'. The frequency of the use of various criteria in discussions varied over time. Gender, professional status, and interpersonal skills were perceived to affect individuals' relative influence on group discussions. The study shows that guideline development groups make compromises between rigour and pragmatism. The formal guideline development model incorporated multiple aspects, but offered few details on how the different criteria should be handled. The guideline development model devoted little attention to the role of the decision-model and group-related factors. Guideline development models could benefit from clarifying the role of the group-related factors and non-research evidence, such as clinical experience and ethical considerations, in decision-processes during guideline development.
Palazzo, Salvatore; Filice, Aldo; Mastroianni, Candida; Biamonte, Rosalbino; Conforti, Serafino; Liguori, Virginia; Turano, Salvatore; De Simone, Rosanna; Rovito, Antonio; Manfredi, Caterina; Minardi, Stefano; Vilardo, Emmanuelle; Loizzo, Monica; Oriolo, Carmela
2016-04-01
Clinical decision making in oncology is based so far on the evidence of efficacy from high-quality clinical research. Data collection and analysis from experimental studies provide valuable insight into response rates and progression-free or overall survival. Data processing generates valuable information for medical professionals involved in cancer patient care, enabling them to make objective and unbiased choices. The increased attention of many scientific associations toward a more rational resource consumption in clinical decision making is mirrored in the Choosing Wisely campaign against the overuse or misuse of exams and procedures of little or no benefit for the patient. This cultural movement has been actively promoting care solutions based on the concept of "value". As a result, the value-based decision-making process for cancer care should not be dissociated from economic sustainability and from ethics of the affordability, also given the growing average cost of the most recent cancer drugs. In support of this orientation, the National Comprehensive Cancer Network (NCCN) has developed innovative and "complex" guidelines based on values, defined as "evidence blocks", with the aim of assisting the medical community in making overall sustainable choices.
A clinical decision rule to prioritize polysomnography in patients with suspected sleep apnea.
Rodsutti, Julvit; Hensley, Michael; Thakkinstian, Ammarin; D'Este, Catherine; Attia, John
2004-06-15
To derive and validate a clinical decision rule that can help to prioritize patients who are on waiting lists for polysomnography, Prospective data collection on consecutive patients referred to a sleep center. The Newcastle Sleep Disorders Centre, University of Newcastle, NSW, Australia. Consecutive adult patients who had been scheduled for initial diagnostic polysomnography. Eight hundred and thirty-seven patients were used for derivation of the decision rule. An apnea-hypopnoea index of at least 5 was used as the cutoff point to diagnose sleep apnea. Fifteen clinical features were included in the analyses using logistic regression to construct a model from the derivation data set. Only 5 variables--age, sex, body mass index, snoring, and stopping breathing during sleep--were significantly associated with sleep apnea. A scoring scheme based on regression coefficients was developed, and the total score was trichotomized into low-, moderate-, and high-risk groups with prevalence of sleep apnea of 8%, 51%, and 82%, respectively. Color-coded tables were developed for ease of use. The clinical decision rule was validated on a separate set of 243 patients. Receiver operating characteristic analysis confirmed that the decision rule performed well, with the area under the curve being similar for both the derivation and validation sets: 0.81 and 0.79, P =.612. We conclude that this decision rule was able to accurately classify the risk of sleep apnea and will be useful for prioritizing patients with suspected sleep apnea who are on waiting lists for polysomnography.
Prognostic Factors and Decision Tree for Long-term Survival in Metastatic Uveal Melanoma.
Lorenzo, Daniel; Ochoa, María; Piulats, Josep Maria; Gutiérrez, Cristina; Arias, Luis; Català, Jaum; Grau, María; Peñafiel, Judith; Cobos, Estefanía; Garcia-Bru, Pere; Rubio, Marcos Javier; Padrón-Pérez, Noel; Dias, Bruno; Pera, Joan; Caminal, Josep Maria
2017-12-04
The purpose of this study was to demonstrate the existence of a bimodal survival pattern in metastatic uveal melanoma. Secondary aims were to identify the characteristics and prognostic factors associated with long-term survival and to develop a clinical decision tree. The medical records of 99 metastatic uveal melanoma patients were retrospectively reviewed. Patients were classified as either short (≤ 12 months) or long-term survivors (> 12 months) based on a graphical interpretation of the survival curve after diagnosis of the first metastatic lesion. Ophthalmic and oncological characteristics were assessed in both groups. Of the 99 patients, 62 (62.6%) were classified as short-term survivors, and 37 (37.4%) as long-term survivors. The multivariate analysis identified the following predictors of long-term survival: age ≤ 65 years (p=0.012) and unaltered serum lactate dehydrogenase levels (p=0.018); additionally, the size (smaller vs. larger) of the largest liver metastasis showed a trend towards significance (p=0.063). Based on the variables significantly associated with long-term survival, we developed a decision tree to facilitate clinical decision-making. The findings of this study demonstrate the existence of a bimodal survival pattern in patients with metastatic uveal melanoma. The presence of certain clinical characteristics at diagnosis of distant disease is associated with long-term survival. A decision tree was developed to facilitate clinical decision-making and to counsel patients about the expected course of disease.
Shared clinical decision making
AlHaqwi, Ali I.; AlDrees, Turki M.; AlRumayyan, Ahmad; AlFarhan, Ali I.; Alotaibi, Sultan S.; AlKhashan, Hesham I.; Badri, Motasim
2015-01-01
Objectives: To determine preferences of patients regarding their involvement in the clinical decision making process and the related factors in Saudi Arabia. Methods: This cross-sectional study was conducted in a major family practice center in King Abdulaziz Medical City, Riyadh, Saudi Arabia, between March and May 2012. Multivariate multinomial regression models were fitted to identify factors associated with patients preferences. Results: The study included 236 participants. The most preferred decision-making style was shared decision-making (57%), followed by paternalistic (28%), and informed consumerism (14%). The preference for shared clinical decision making was significantly higher among male patients and those with higher level of education, whereas paternalism was significantly higher among older patients and those with chronic health conditions, and consumerism was significantly higher in younger age groups. In multivariate multinomial regression analysis, compared with the shared group, the consumerism group were more likely to be female [adjusted odds ratio (AOR) =2.87, 95% confidence interval [CI] 1.31-6.27, p=0.008] and non-dyslipidemic (AOR=2.90, 95% CI: 1.03-8.09, p=0.04), and the paternalism group were more likely to be older (AOR=1.03, 95% CI: 1.01-1.05, p=0.04), and female (AOR=2.47, 95% CI: 1.32-4.06, p=0.008). Conclusion: Preferences of patients for involvement in the clinical decision-making varied considerably. In our setting, underlying factors that influence these preferences identified in this study should be considered and tailored individually to achieve optimal treatment outcomes. PMID:26620990
Bruen, Catherine; Kreiter, Clarence; Wade, Vincent; Pawlikowska, Teresa
2017-01-01
Experience with simulated patients supports undergraduate learning of medical consultation skills. Adaptive simulations are being introduced into this environment. The authors investigate whether it can underpin valid and reliable assessment by conducting a generalizability analysis using IT data analytics from the interaction of medical students (in psychiatry) with adaptive simulations to explore the feasibility of adaptive simulations for supporting automated learning and assessment. The generalizability (G) study was focused on two clinically relevant variables: clinical decision points and communication skills. While the G study on the communication skills score yielded low levels of true score variance, the results produced by the decision points, indicating clinical decision-making and confirming user knowledge of the process of the Calgary-Cambridge model of consultation, produced reliability levels similar to what might be expected with rater-based scoring. The findings indicate that adaptive simulations have potential as a teaching and assessment tool for medical consultations.
Brien, Sarah; Dibb, Bridget; Burch, Alex
2011-01-01
While intuition plays a role in clinical decision making within conventional medicine, little is understood about its use in complementary and alternative medicine (CAM). The aim of this qualitative study was to investigate intuition from the perspective of homeopathic practitioners; its' manifestation, how it was recognized, its origins and when it was used within daily clinical practice. Semi-structured interviews were carried out with clinically experienced non-National Health Service (NHS) UK homeopathic practitioners. Interpretative phenomenological analysis was used to analyze the data. Homeopaths reported many similarities with conventional medical practitioner regarding the nature, perceived origin and manifestation of their intuitions in clinical practice. Intuition was used in two key aspects of the consultation: (i) to enhance the practitioner-patient relationship, these were generally trusted; and (ii) intuitions relating to the prescribing decision. Homeopaths were cautious about these latter intuitions, testing any intuitive thoughts through deductive reasoning before accepting them. Their reluctance is not surprising given the consequences for patient care, but we propose this also reflects homeopaths' sensitivity to the academic and medical mistrust of both homeopathy and intuition. This study is the first to explore the use of intuition in decision making in any form of complementary medicine. The similarities with conventional practitioners may provide confidence in validating intuition as a legitimate part of the decision making process for these specific practitioners. Further work is needed to elucidate if these findings reflect intuitive use in clinical practice of other CAM practitioners in both private and NHS (i.e., time limited) settings. PMID:19773389
Using multicriteria decision analysis during drug development to predict reimbursement decisions.
Williams, Paul; Mauskopf, Josephine; Lebiecki, Jake; Kilburg, Anne
2014-01-01
Pharmaceutical companies design clinical development programs to generate the data that they believe will support reimbursement for the experimental compound. The objective of the study was to present a process for using multicriteria decision analysis (MCDA) by a pharmaceutical company to estimate the probability of a positive recommendation for reimbursement for a new drug given drug and environmental attributes. The MCDA process included 1) selection of decisions makers who were representative of those making reimbursement decisions in a specific country; 2) two pre-workshop questionnaires to identify the most important attributes and their relative importance for a positive recommendation for a new drug; 3) a 1-day workshop during which participants undertook three tasks: i) they agreed on a final list of decision attributes and their importance weights, ii) they developed level descriptions for these attributes and mapped each attribute level to a value function, and iii) they developed profiles for hypothetical products 'just likely to be reimbursed'; and 4) use of the data from the workshop to develop a prediction algorithm based on a logistic regression analysis. The MCDA process is illustrated using case studies for three countries, the United Kingdom, Germany, and Spain. The extent to which the prediction algorithms for each country captured the decision processes for the workshop participants in our case studies was tested using a post-meeting questionnaire that asked the participants to make recommendations for a set of hypothetical products. The data collected in the case study workshops resulted in a prediction algorithm: 1) for the United Kingdom, the probability of a positive recommendation for different ranges of cost-effectiveness ratios; 2) for Spain, the probability of a positive recommendation at the national and regional levels; and 3) for Germany, the probability of a determination of clinical benefit. The results from the post-meeting questionnaire revealed a high predictive value for the algorithm developed using MCDA. Prediction algorithms developed using MCDA could be used by pharmaceutical companies when designing their clinical development programs to estimate the likelihood of a favourable reimbursement recommendation for different product profiles and for different positions in the treatment pathway.
Using multicriteria decision analysis during drug development to predict reimbursement decisions
Williams, Paul; Mauskopf, Josephine; Lebiecki, Jake; Kilburg, Anne
2014-01-01
Background Pharmaceutical companies design clinical development programs to generate the data that they believe will support reimbursement for the experimental compound. Objective The objective of the study was to present a process for using multicriteria decision analysis (MCDA) by a pharmaceutical company to estimate the probability of a positive recommendation for reimbursement for a new drug given drug and environmental attributes. Methods The MCDA process included 1) selection of decisions makers who were representative of those making reimbursement decisions in a specific country; 2) two pre-workshop questionnaires to identify the most important attributes and their relative importance for a positive recommendation for a new drug; 3) a 1-day workshop during which participants undertook three tasks: i) they agreed on a final list of decision attributes and their importance weights, ii) they developed level descriptions for these attributes and mapped each attribute level to a value function, and iii) they developed profiles for hypothetical products ‘just likely to be reimbursed’; and 4) use of the data from the workshop to develop a prediction algorithm based on a logistic regression analysis. The MCDA process is illustrated using case studies for three countries, the United Kingdom, Germany, and Spain. The extent to which the prediction algorithms for each country captured the decision processes for the workshop participants in our case studies was tested using a post-meeting questionnaire that asked the participants to make recommendations for a set of hypothetical products. Results The data collected in the case study workshops resulted in a prediction algorithm: 1) for the United Kingdom, the probability of a positive recommendation for different ranges of cost-effectiveness ratios; 2) for Spain, the probability of a positive recommendation at the national and regional levels; and 3) for Germany, the probability of a determination of clinical benefit. The results from the post-meeting questionnaire revealed a high predictive value for the algorithm developed using MCDA. Conclusions Prediction algorithms developed using MCDA could be used by pharmaceutical companies when designing their clinical development programs to estimate the likelihood of a favourable reimbursement recommendation for different product profiles and for different positions in the treatment pathway.
[A study on participation in clinical decision making by home healthcare nurses].
Kim, Se Young
2010-12-01
This study was done to identify participation by home healthcare nurses in clinical decision making and factors influencing clinical decision making. A descriptive survey was used to collect data from 68 home healthcare nurses in 22 hospital-based home healthcare services in Korea. To investigate participation, the researcher developed 3 scenarios through interviews with 5 home healthcare nurses. A self-report questionnaire composed of tools for characteristics, factors of clinical decision making, and participation was used. Participation was relatively high, but significantly lower in the design phase (F=3.51, p=.032). Competency in clinical decision making (r=.45, p<.001), perception of the decision maker role (r=.47, p<.001), and perception of the utility of clinical practice guidelines (r=.25, p=.043) were significantly correlated with participation. Competency in clinical decision making (Odds ratio [OR]=41.79, p=.007) and perception of the decision maker role (OR=15.09, p=.007) were significant factors predicting participation in clinical decision making by home healthcare nurses. In order to encourage participation in clinical decision making, education programs should be provided to home healthcare nurses. Official clinical practice guidelines should be used to support home healthcare nurses' participation in clinical decision making in cases where they can identify and solve the patient health problems.
Return to Play after Cervical Spine Injuries: A Consensus of Opinion
France, John C.; Karsy, Michael; Harrop, James S.; Dailey, Andrew T.
2016-01-01
Study Design Survey. Objective Sports-related spinal cord injury (SCI) represents a growing proportion of total SCIs but lacks evidence or guidelines to guide clinical decision-making on return to play (RTP). Our objective is to offer the treating physician a consensus analysis of expert opinion regarding RTP that can be incorporated with the unique factors of a case for clinical decision-making. Methods Ten common clinical scenarios involving neurapraxia and stenosis, atlantoaxial injury, subaxial injury, and general cervical spine injury were presented to 25 spine surgeons from level 1 trauma centers for whom spine trauma is a significant component of their practice. We evaluated responses to questions about patient RTP, level of contact, imaging required for a clinical decision, and time to return for each scenario. The chi-square test was used for statistical analysis, with p < 0.05 considered significant. Results Evaluation of the surgeons' responses to these cases showed significant consensus regarding return to high-contact sports in cases of cervical cord neurapraxia without symptoms or stenosis, surgically repaired herniated disks, and nonoperatively healed C1 ring or C2 hangman's fractures. Greater variability was found in recommendations for patients showing persistent clinical symptomatology. Conclusion This survey suggests a consensus among surgeons for allowing patients with relatively normal imaging and resolution of symptoms to return to high-contact activities; however, patients with cervical stenosis or clinical symptoms continue to be a challenge for management. This survey may serve as a basis for future clinical trials and consensus guidelines. PMID:27853664
Clinical decision-making: the case against the new casuistry.
Ananth, Mahesh
2017-01-01
Albert Jonsen and Stephen Toulmin have argued that the best way to resolve the complex issues in medical settings is to focus on the actual details of cases and then determine what to do in the given cases. This approach to medical decision-making, labeled "casuistry," has met with much criticism. In response, Carson Strong has attempted to save much of Jonsen and Toulmin's version of casuistry. This analysis reveals that Strong's recent salvage efforts fail to deflect the major criticisms. The upshot of this analysis is that Jonsen and Toulmin's version of casuistry is not an appropriate framework from which to resolve complex issues in clinical settings. Copyright © 2017 by the National Legal Center for the Medically Dependent and Disabled, Inc.
Thompson, Carl; Stapley, Sally
2011-07-01
Despite the growing popularity of decision making in nursing curricula, the effectiveness of educational interventions to improve nursing judgement and decision making is unknown. We sought to synthesise and summarise the comparative evidence for educational interventions to improve nursing judgements and clinical decisions. A systematic review. Electronic databases: Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, CINAHL and PsycINFO, Social Sciences Citation Index, OpenSIGLE conference proceedings and hand searching nursing journals. Studies published since 1960, reporting any educational intervention that aimed to improve nurses' clinical judgements or decision making were included. Studies were assessed for relevance and quality. Data extracted included study design; educational setting; the nature of participants; whether the study was concerned with the clinical application of skills or the application of theory; the type of decision targeted by the intervention (e.g. diagnostic reasoning) and whether the evaluation of the intervention focused on efficacy or effectiveness. A narrative approach to study synthesis was used due to heterogeneity in interventions, study samples, outcomes and settings and incomplete reporting of effect sizes. From 5262 initial citations 24 studies were included in the review. A variety of educational approaches were reported. Study quality and content reporting was generally poor. Pedagogical theories were widely used but use of decision theory (with the exception of subjective expected utility theory implicit in decision analysis) was rare. The effectiveness and efficacy of interventions was mixed. Educational interventions to improve nurses' judgements and decisions are complex and the evidence from comparative studies does little to reduce the uncertainty about 'what works'. Nurse educators need to pay attention to decision, as well as pedagogical, theory in the design of interventions. Study design and reporting requires improvement to maximise the information contained in reports of educational interventions. Copyright © 2011 Elsevier Ltd. All rights reserved.
Hoffner, Brianna; Bauer-Wu, Susan; Hitchcock-Bryan, Suzanne; Powell, Mark; Wolanski, Andrew; Joffe, Steven
2011-01-01
PURPOSE This randomized study was designed to assess the utility of an educational video in preparing cancer patients for decisions about clinical trial participation. The study assessed the effect of the video on patients’ understanding and perceptions of clinical trials, its impact on decision making and patient-provider communication, and patients’ satisfaction with the video. METHODS Ninety adults considering cancer clinical trials were randomized to receive (n=45) or not receive (n=45) the video. Using the validated Quality of Informed Consent (QuIC), respondents’ knowledge about clinical trial participation was assessed. All subjects completed additional questions about satisfaction with the video, decision making, and patient-provider communication. Data were analyzed using the Wilcoxon rank-sum test, regression model and descriptive statistics. RESULTS Although intent-to-treat analysis found no significant group differences in objective understanding between those randomized to view or not view the video, the majority of participants reported favorable experiences with regard to watching the video: 85% found the video was an important source of information about clinical trials; 81% felt better prepared to discuss the trial with their physician; 89% of those who watched the video with family indicated that it helped family better understand clinical trials; and 73% indicated it helped family accept their decision about participation. CONCLUSIONS Although the video did not measurably improve patients’ knowledge about clinical trials, it was an important source of information, helped educate families, and enhanced patient communication with their oncology providers. PMID:22009665
Kondo, M; Nagao, Y; Mahbub, M H; Tanabe, T; Tanizawa, Y
2018-04-29
To identify factors predicting early postpartum glucose intolerance in Japanese women with gestational diabetes mellitus, using decision-curve analysis. A retrospective cohort study was performed. The participants were 123 Japanese women with gestational diabetes who underwent 75-g oral glucose tolerance tests at 8-12 weeks after delivery. They were divided into a glucose intolerance and a normal glucose tolerance group based on postpartum oral glucose tolerance test results. Analysis of the pregnancy oral glucose tolerance test results showed predictive factors for postpartum glucose intolerance. We also evaluated the clinical usefulness of the prediction model based on decision-curve analysis. Of 123 women, 78 (63.4%) had normoglycaemia and 45 (36.6%) had glucose intolerance. Multivariable logistic regression analysis showed insulinogenic index/fasting immunoreactive insulin and summation of glucose levels, assessed during pregnancy oral glucose tolerance tests (total glucose), to be independent risk factors for postpartum glucose intolerance. Evaluating the regression models, the best discrimination (area under the curve 0.725) was obtained using the basic model (i.e. age, family history of diabetes, BMI ≥25 kg/m 2 and use of insulin during pregnancy) plus insulinogenic index/fasting immunoreactive insulin <1.1. Decision-curve analysis showed that combining insulinogenic index/fasting immunoreactive insulin <1.1 with basic clinical information resulted in superior net benefits for prediction of postpartum glucose intolerance. Insulinogenic index/fasting immunoreactive insulin calculated using oral glucose tolerance test results during pregnancy is potentially useful for predicting early postpartum glucose intolerance in Japanese women with gestational diabetes. © 2018 Diabetes UK.
Waks, Zeev; Goldbraich, Esther; Farkash, Ariel; Torresani, Michele; Bertulli, Rossella; Restifo, Nicola; Locatelli, Paolo; Casali, Paolo; Carmeli, Boaz
2013-01-01
Clinical decision support systems (CDSSs) are gaining popularity as tools that assist physicians in optimizing medical care. These systems typically comply with evidence-based medicine and are designed with input from domain experts. Nonetheless, deviations from CDSS recommendations are abundant across a broad spectrum of disorders, raising the question as to why this phenomenon exists. Here, we analyze this gap in adherence to a clinical guidelines-based CDSS by examining the physician treatment decisions for 1329 adult soft tissue sarcoma patients in northern Italy using patient-specific parameters. Dubbing this analysis "CareGap", we find that deviations correlate strongly with certain disease features such as local versus metastatic clinical presentation. We also notice that deviations from the guideline-based CDSS suggestions occur more frequently for patients with shorter survival time. Such observations can direct physicians' attention to distinct patient cohorts that are prone to higher deviation levels from clinical practice guidelines. This illustrates the value of CareGap analysis in assessing quality of care for subsets of patients within a larger pathology.
[Research applications in digital radiology. Big data and co].
Müller, H; Hanbury, A
2016-02-01
Medical imaging produces increasingly complex images (e.g. thinner slices and higher resolution) with more protocols, so that image reading has also become much more complex. More information needs to be processed and usually the number of radiologists available for these tasks has not increased to the same extent. The objective of this article is to present current research results from projects on the use of image data for clinical decision support. An infrastructure that can allow large volumes of data to be accessed is presented. In this way the best performing tools can be identified without the medical data having to leave secure servers. The text presents the results of the VISCERAL and Khresmoi EU-funded projects, which allow the analysis of previous cases from institutional archives to support decision-making and for process automation. The results also represent a secure evaluation environment for medical image analysis. This allows the use of data extracted from past cases to solve information needs occurring when diagnosing new cases. The presented research prototypes allow direct extraction of knowledge from the visual data of the images and to use this for decision support or process automation. Real clinical use has not been tested but several subjective user tests showed the effectiveness and efficiency of the process. The future in radiology will clearly depend on better use of the important knowledge in clinical image archives to automate processes and aid decision-making via big data analysis. This can help concentrate the work of radiologists towards the most important parts of diagnostics.
Formulary evaluation of third-generation cephalosporins using decision analysis.
Cano, S B; Fujita, N K
1988-03-01
A structured, objective approach to formulary review of third-generation cephalosporins using the decision-analysis model is described. The pharmacy and therapeutics (P&T) committee approved the evaluation criteria for this drug class and assigned priority weights (as percentages of 100) to those drug characteristics deemed most important. Clinical data (spectrum of activity, pharmacokinetics, adverse effects, and stability) and financial data (cost of acquisition and cost of therapy per day) were used to determine ranking scores for each drug. Total scores were determined by multiplying ranking scores by the assigned priority weights for the criteria. The two highest-scoring drugs were selected for inclusion in the formulary. By this decision-analysis process, the P&T committee recommended that all current third-generation cephalosporins (cefotaxime, cefoperazone, and moxalactam) be removed from the institutions's formulary and be replaced with ceftazidime and ceftriaxone. P&T committees at other institutions may structure their criteria differently, and different recommendations may result. Using decision analysis for formulary review may promote rational drug therapy and achieve cost savings.
Heuristics in Managing Complex Clinical Decision Tasks in Experts’ Decision Making
Islam, Roosan; Weir, Charlene; Del Fiol, Guilherme
2016-01-01
Background Clinical decision support is a tool to help experts make optimal and efficient decisions. However, little is known about the high level of abstractions in the thinking process for the experts. Objective The objective of the study is to understand how clinicians manage complexity while dealing with complex clinical decision tasks. Method After approval from the Institutional Review Board (IRB), three clinical experts were interviewed the transcripts from these interviews were analyzed. Results We found five broad categories of strategies by experts for managing complex clinical decision tasks: decision conflict, mental projection, decision trade-offs, managing uncertainty and generating rule of thumb. Conclusion Complexity is created by decision conflicts, mental projection, limited options and treatment uncertainty. Experts cope with complexity in a variety of ways, including using efficient and fast decision strategies to simplify complex decision tasks, mentally simulating outcomes and focusing on only the most relevant information. Application Understanding complex decision making processes can help design allocation based on the complexity of task for clinical decision support design. PMID:27275019
Heuristics in Managing Complex Clinical Decision Tasks in Experts' Decision Making.
Islam, Roosan; Weir, Charlene; Del Fiol, Guilherme
2014-09-01
Clinical decision support is a tool to help experts make optimal and efficient decisions. However, little is known about the high level of abstractions in the thinking process for the experts. The objective of the study is to understand how clinicians manage complexity while dealing with complex clinical decision tasks. After approval from the Institutional Review Board (IRB), three clinical experts were interviewed the transcripts from these interviews were analyzed. We found five broad categories of strategies by experts for managing complex clinical decision tasks: decision conflict, mental projection, decision trade-offs, managing uncertainty and generating rule of thumb. Complexity is created by decision conflicts, mental projection, limited options and treatment uncertainty. Experts cope with complexity in a variety of ways, including using efficient and fast decision strategies to simplify complex decision tasks, mentally simulating outcomes and focusing on only the most relevant information. Understanding complex decision making processes can help design allocation based on the complexity of task for clinical decision support design.
Clinical assessment of decision-making capacity in acquired brain injury with personality change.
Owen, Gareth S; Freyenhagen, Fabian; Martin, Wayne; David, Anthony S
2017-01-01
Assessment of decision-making capacity (DMC) can be difficult in acquired brain injury (ABI) particularly with the syndrome of organic personality disorder (OPD) (the "frontal lobe syndrome"). Clinical neuroscience may help but there are challenges translating its constructs to the decision-making abilities considered relevant by law and ethics. An in-depth interview study of DMC in OPD was undertaken. Six patients were purposefully sampled and rich interview data were acquired for scrutiny using interpretative phenomenological analysis. Interview data revealed that awareness of deficit and thinking about psychological states can be present. However, the awareness of deficit may not be "online" and effectively integrated into decision-making. Without this online awareness of deficit the ability to appreciate or use and weigh information in the process of deciding some matters appeared absent. We argue that the decision-making abilities discussed are: (1) necessary for DMC, (2) threatened by ABI , and (3) assessable at interview. Some advice for practically incorporating these abilities within assessments of DMC in patients with OPD is outlined.
A study on specialist or special disease clinics based on big data.
Fang, Zhuyuan; Fan, Xiaowei; Chen, Gong
2014-09-01
Correlation analysis and processing of massive medical information can be implemented through big data technology to find the relevance of different factors in the life cycle of a disease and to provide the basis for scientific research and clinical practice. This paper explores the concept of constructing a big medical data platform and introduces the clinical model construction. Medical data can be collected and consolidated by distributed computing technology. Through analysis technology, such as artificial neural network and grey model, a medical model can be built. Big data analysis, such as Hadoop, can be used to construct early prediction and intervention models as well as clinical decision-making model for specialist and special disease clinics. It establishes a new model for common clinical research for specialist and special disease clinics.
van Trijffel, Emiel; Plochg, Thomas; van Hartingsveld, Frank; Lucas, Cees; Oostendorp, Rob A B
2010-06-01
Passive intervertebral motion (PIVM) assessment is a characterizing skill of manual physical therapists (MPTs) and is important for judgments about impairments in spinal joint function. It is unknown as to why and how MPTs use this mobility testing of spinal motion segments within their clinical reasoning and decision-making. This qualitative study aimed to explore and understand the role and position of PIVM assessment within the manual diagnostic process. Eight semistructured individual interviews with expert MPTs and three subsequent group interviews using manual physical therapy consultation platforms were conducted. Line-by-line coding was performed on the transcribed data, and final main themes were identified from subcategories. Three researchers were involved in the analysis process. Four themes emerged from the data: contextuality, consistency, impairment orientedness, and subjectivity. These themes were interrelated and linked to concepts of professionalism and clinical reasoning. MPTs used PIVM assessment within a multidimensional, biopsychosocial framework incorporating clinical data relating to mechanical dysfunction as well as to personal factors while applying various clinical reasoning strategies. Interpretation of PIVM assessment and subsequent decisions on manipulative treatment were strongly rooted within practitioners' practical knowledge. This study has identified the specific role and position of PIVM assessment as related to other clinical findings within clinical reasoning and decision-making in manual physical therapy in The Netherlands. We recommend future research in manual diagnostics to account for the multivariable character of physical examination of the spine.
van Trijffel, Emiel; Plochg, Thomas; van Hartingsveld, Frank; Lucas, Cees; Oostendorp, Rob A B
2010-01-01
Passive intervertebral motion (PIVM) assessment is a characterizing skill of manual physical therapists (MPTs) and is important for judgments about impairments in spinal joint function. It is unknown as to why and how MPTs use this mobility testing of spinal motion segments within their clinical reasoning and decision-making. This qualitative study aimed to explore and understand the role and position of PIVM assessment within the manual diagnostic process. Eight semistructured individual interviews with expert MPTs and three subsequent group interviews using manual physical therapy consultation platforms were conducted. Line-by-line coding was performed on the transcribed data, and final main themes were identified from subcategories. Three researchers were involved in the analysis process. Four themes emerged from the data: contextuality, consistency, impairment orientedness, and subjectivity. These themes were interrelated and linked to concepts of professionalism and clinical reasoning. MPTs used PIVM assessment within a multidimensional, biopsychosocial framework incorporating clinical data relating to mechanical dysfunction as well as to personal factors while applying various clinical reasoning strategies. Interpretation of PIVM assessment and subsequent decisions on manipulative treatment were strongly rooted within practitioners’ practical knowledge. This study has identified the specific role and position of PIVM assessment as related to other clinical findings within clinical reasoning and decision-making in manual physical therapy in The Netherlands. We recommend future research in manual diagnostics to account for the multivariable character of physical examination of the spine. PMID:21655394
A review of clinical decision making: models and current research.
Banning, Maggi
2008-01-01
The aim of this paper was to review the current literature clinical decision-making models and the educational application of models to clinical practice. This was achieved by exploring the function and related research of the three available models of clinical decision making: information-processing model, the intuitive-humanist model and the clinical decision-making model. Clinical decision making is a unique process that involves the interplay between knowledge of pre-existing pathological conditions, explicit patient information, nursing care and experiential learning. Historically, two models of clinical decision making are recognized from the literature; the information-processing model and the intuitive-humanist model. The usefulness and application of both models has been examined in relation the provision of nursing care and care related outcomes. More recently a third model of clinical decision making has been proposed. This new multidimensional model contains elements of the information-processing model but also examines patient specific elements that are necessary for cue and pattern recognition. Literature review. Evaluation of the literature generated from MEDLINE, CINAHL, OVID, PUBMED and EBESCO systems and the Internet from 1980 to November 2005. The characteristics of the three models of decision making were identified and the related research discussed. Three approaches to clinical decision making were identified, each having its own attributes and uses. The most recent addition to the clinical decision making is a theoretical, multidimensional model which was developed through an evaluation of current literature and the assessment of a limited number of research studies that focused on the clinical decision-making skills of inexperienced nurses in pseudoclinical settings. The components of this model and the relative merits to clinical practice are discussed. It is proposed that clinical decision making improves as the nurse gains experience of nursing patients within a specific speciality and with experience, nurses gain a sense of saliency in relation to decision making. Experienced nurses may use all three forms of clinical decision making both independently and concurrently to solve nursing-related problems. It is suggested that O'Neill's clinical decision-making model could be tested by educators and experienced nurses to assess the efficacy of this hybrid approach to decision making.
Søreide, Kjetil; Kørner, Hartwig; Søreide, Jon Arne
2011-01-01
In surgical research, the ability to correctly classify one type of condition or specific outcome from another is of great importance for variables influencing clinical decision making. Receiver-operating characteristic (ROC) curve analysis is a useful tool in assessing the diagnostic accuracy of any variable with a continuous spectrum of results. In order to rule a disease state in or out with a given test, the test results are usually binary, with arbitrarily chosen cut-offs for defining disease versus health, or for grading of disease severity. In the postgenomic era, the translation from bench-to-bedside of biomarkers in various tissues and body fluids requires appropriate tools for analysis. In contrast to predetermining a cut-off value to define disease, the advantages of applying ROC analysis include the ability to test diagnostic accuracy across the entire range of variable scores and test outcomes. In addition, ROC analysis can easily examine visual and statistical comparisons across tests or scores. ROC is also favored because it is thought to be independent from the prevalence of the condition under investigation. ROC analysis is used in various surgical settings and across disciplines, including cancer research, biomarker assessment, imaging evaluation, and assessment of risk scores.With appropriate use, ROC curves may help identify the most appropriate cutoff value for clinical and surgical decision making and avoid confounding effects seen with subjective ratings. ROC curve results should always be put in perspective, because a good classifier does not guarantee the expected clinical outcome. In this review, we discuss the fundamental roles, suggested presentation, potential biases, and interpretation of ROC analysis in surgical research.
Make versus buy: a financial perspective.
Kisner, Harold J
2003-01-01
Clinical laboratories are often faced with the decision to either perform a service in-house using their own assets or outsource the service to another vendor. This decision affects many aspects of the laboratory's business, from the macroeconomic perspective of outsourcing the laboratory service to a laboratory vendor, to the microeconomics of determining whether to refer a test out to their reference laboratory or perform the test in-house. The basis for decision making includes many variables, but a detailed financial analysis is usually the basis for the decision, especially when the decision only affects the laboratory and not the rest of the institution. Other factors often come into play, and depending on the magnitude, the "make versus buy" decision could be based more on strategic or political factors than economics. Even when noneconomic factors are involved, an effort usually is made to quantify those factors so that the make versus buy decision is reduced to financial terms. The previous article in this issue, "Effectively Managing Your Reference Laboratory Relationship" by Ronald L. Weiss, M.D., focused on the "buy" decision relating to managing the reference laboratory relationship. Although that article took a more clinical perspective through the eyes of the reference laboratory, this article looks at the make versus buy decision from a financial perspective through the eyes of the buying party.
A business planning model to identify new safety net clinic locations.
Langabeer, James; Helton, Jeffrey; DelliFraine, Jami; Dotson, Ebbin; Watts, Carolyn; Love, Karen
2014-01-01
Community health clinics serving the poor and underserved are geographically expanding due to changes in U.S. health care policy. This paper describes the experience of a collaborative alliance of health care providers in a large metropolitan area who develop a conceptual and mathematical decision model to guide decisions on expanding its network of community health clinics. Community stakeholders participated in a collaborative process that defined constructs they deemed important in guiding decisions on the location of community health clinics. This collaboration also defined key variables within each construct. Scores for variables within each construct were then totaled and weighted into a community-specific optimal space planning equation. This analysis relied entirely on secondary data available from published sources. The model built from this collaboration revolved around the constructs of demand, sustainability, and competition. It used publicly available data defining variables within each construct to arrive at an optimal location that maximized demand and sustainability and minimized competition. This is a model that safety net clinic planners and community stakeholders can use to analyze demographic and utilization data to optimize capacity expansion to serve uninsured and Medicaid populations. Communities can use this innovative model to develop a locally relevant clinic location-planning framework.
[Clinical judgment is a schema. Conceptual proposals and training perspectives.
Nagels, Marc
2017-06-01
Clinical judgment is a critical concept for the development of nursing and nursing education. Its theoretical origins are multiple and its definition is not yet consensus. The analysis of the scientific and professional literature shows heterogeneous and dispersed points of views, notably on the role of intuition, on its cognitive and metacognitive dimensions, and on its proximity to other concepts. Between professional stakes and epistemological constructions, clinical judgment is still an emerging concept.To overcome the obstacle and contribute to the theoretical effort, we will argue that clinical judgment must be analyzed as a schema. It presents all the characteristics : diagnosis and information necessary for reasoning, rational decision-making process, metacognitive control and evaluation of decision-making. Perspectives then open to better understand the nursing activity.In conclusion, recommendations for developing clinical judgment in training will be presented.
Alammari, M R; Smith, P W; de Josselin de Jong, E; Higham, S M
2013-02-01
This study reports the development and assessment of a novel method using quantitative light-induced fluorescence (QLF), to determine whether QLF parameters ΔF and ΔQ were appropriate for aiding diagnosis and clinical decision making of early occlusal mineral loss by comparing QLF analysis with actual restorative management. Following ethical approval, 46 subjects attending a dental teaching hospital were enrolled. White light digital (WL) and QLF images/analyses of 46 unrestored posterior teeth with suspected occlusal caries were made after a clinical decision had already been taken to explore fissures operatively. WL and QLF imaging/analysis were repeated after initial cavity preparation. The type of restorative treatment was determined by the supervising clinician independent of any imaging performed. Actual restorative management carried out was recorded as fissure sealant/preventive resin restoration (F/P) or class I occlusal restoration (Rest.) thus reflecting the extent of intervention (=gold standard). All QLF images were analysed independently. The results showed statistically significant differences between the two treatment groups ΔF (p=0.002) (mean 22.60 - F/P and 28.80 - Rest.) and ΔQ (p=0.012) (mean 230.49 - F/P and 348.30 - Rest.). ΔF and ΔQ values may be useful in aiding clinical diagnosis and decision making in relation to the management of early mineral loss and restorative intervention of occlusal caries. QLF has the potential to be a valuable tool for caries diagnosis in clinical practice. Copyright © 2012 Elsevier Ltd. All rights reserved.
Croft, Hayley; Gilligan, Conor; Rasiah, Rohan; Levett-Jones, Tracy; Schneider, Jennifer
2017-01-01
Medication review and supply by pharmacists involves both cognitive and technical skills related to the safety and appropriateness of prescribed medicines. The cognitive ability of pharmacists to recall, synthesise and memorise information is a critical aspect of safe and optimal medicines use, yet few studies have investigated the clinical reasoning and decision-making processes pharmacists use when supplying prescribed medicines. The objective of this study was to examine the patterns and processes of pharmacists’ clinical reasoning and to identify the information sources used, when making decisions about the safety and appropriateness of prescribed medicines. Ten community pharmacists participated in a simulation in which they were required to review a prescription and make decisions about the safety and appropriateness of supplying the prescribed medicines to the patient, whilst at the same time thinking aloud about the tasks required. Following the simulation each pharmacist was asked a series of questions to prompt retrospective thinking aloud using video-stimulated recall. The simulated consultation and retrospective interview were recorded and transcribed for thematic analysis. All of the pharmacists made a safe and appropriate supply of two prescribed medicines to the simulated patient. Qualitative analysis identified seven core thinking processes used during the supply process: considering prescription in context, retrieving information, identifying medication-related issues, processing information, collaborative planning, decision making and reflection; and align closely with other health professionals. The insights from this study have implications for enhancing awareness of decision making processes in pharmacy practice and informing teaching and assessment approaches in medication supply. PMID:29301223
Croft, Hayley; Gilligan, Conor; Rasiah, Rohan; Levett-Jones, Tracy; Schneider, Jennifer
2017-12-31
Medication review and supply by pharmacists involves both cognitive and technical skills related to the safety and appropriateness of prescribed medicines. The cognitive ability of pharmacists to recall, synthesise and memorise information is a critical aspect of safe and optimal medicines use, yet few studies have investigated the clinical reasoning and decision-making processes pharmacists use when supplying prescribed medicines. The objective of this study was to examine the patterns and processes of pharmacists' clinical reasoning and to identify the information sources used, when making decisions about the safety and appropriateness of prescribed medicines. Ten community pharmacists participated in a simulation in which they were required to review a prescription and make decisions about the safety and appropriateness of supplying the prescribed medicines to the patient, whilst at the same time thinking aloud about the tasks required. Following the simulation each pharmacist was asked a series of questions to prompt retrospective thinking aloud using video-stimulated recall. The simulated consultation and retrospective interview were recorded and transcribed for thematic analysis. All of the pharmacists made a safe and appropriate supply of two prescribed medicines to the simulated patient. Qualitative analysis identified seven core thinking processes used during the supply process: considering prescription in context, retrieving information, identifying medication-related issues, processing information, collaborative planning, decision making and reflection; and align closely with other health professionals. The insights from this study have implications for enhancing awareness of decision making processes in pharmacy practice and informing teaching and assessment approaches in medication supply.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Shakespeare, Thomas P.; Back, Michael F.; Lu, Jiade J.
2006-03-01
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/qualitymore » 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.« less
Haider, Adil H; Schneider, Eric B; Sriram, N; Dossick, Deborah S; Scott, Valerie K; Swoboda, Sandra M; Losonczy, Lia; Haut, Elliott R; Efron, David T; Pronovost, Peter J; Lipsett, Pamela A; Cornwell, Edward E; MacKenzie, Ellen J; Cooper, Lisa A; Freischlag, Julie A
2015-05-01
Significant health inequities persist among minority and socially disadvantaged patients. Better understanding of how unconscious biases affect clinical decision making may help to illuminate clinicians' roles in propagating disparities. To determine whether clinicians' unconscious race and/or social class biases correlate with patient management decisions. We conducted a web-based survey among 230 physicians from surgery and related specialties at an academic, level I trauma center from December 1, 2011, through January 31, 2012. We administered clinical vignettes, each with 3 management questions. Eight vignettes assessed the relationship between unconscious bias and clinical decision making. We performed ordered logistic regression analysis on the Implicit Association Test (IAT) scores and used multivariable analysis to determine whether implicit bias was associated with the vignette responses. Differential response times (D scores) on the IAT as a surrogate for unconscious bias. Patient management vignettes varied by patient race or social class. Resulting D scores were calculated for each management decision. In total, 215 clinicians were included and consisted of 74 attending surgeons, 32 fellows, 86 residents, 19 interns, and 4 physicians with an undetermined level of education. Specialties included surgery (32.1%), anesthesia (18.1%), emergency medicine (18.1%), orthopedics (7.9%), otolaryngology (7.0%), neurosurgery (7.0%), critical care (6.0%), and urology (2.8%); 1.9% did not report a departmental affiliation. Implicit race and social class biases were present in most respondents. Among all clinicians, mean IAT D scores for race and social class were 0.42 (95% CI, 0.37-0.48) and 0.71 (95% CI, 0.65-0.78), respectively. Race and class scores were similar across departments (general surgery, orthopedics, urology, etc), race, or age. Women demonstrated less bias concerning race (mean IAT D score, 0.39 [95% CI, 0.29-0.49]) and social class (mean IAT D score, 0.66 [95% CI, 0.57-0.75]) relative to men (mean IAT D scores, 0.44 [95% CI, 0.37-0.52] and 0.82 [95% CI, 0.75-0.89], respectively). In univariate analyses, we found an association between race/social class bias and 3 of 27 possible patient-care decisions. Multivariable analyses revealed no association between the IAT D scores and vignette-based clinical assessments. Unconscious social class and race biases were not significantly associated with clinical decision making among acute care surgical clinicians. Further studies involving real physician-patient interactions may be warranted.
Bayesian Decision Support for Adaptive Lung Treatments
NASA Astrophysics Data System (ADS)
McShan, Daniel; Luo, Yi; Schipper, Matt; TenHaken, Randall
2014-03-01
Purpose: A Bayesian Decision Network will be demonstrated to provide clinical decision support for adaptive lung response-driven treatment management based on evidence that physiologic metrics may correlate better with individual patient response than traditional (population-based) dose and volume-based metrics. Further, there is evidence that information obtained during the course of radiation therapy may further improve response predictions. Methods: Clinical factors were gathered for 58 patients including planned mean lung dose, and the bio-markers IL-8 and TGF-β1 obtained prior to treatment and two weeks into treatment along with complication outcomes for these patients. A Bayesian Decision Network was constructed using Netica 5.0.2 from Norsys linking these clinical factors to obtain a prediction of radiation induced lung disese (RILD) complication. A decision node was added to the network to provide a plan adaption recommendation based on the trade-off between the RILD prediction and complexity of replanning. A utility node provides the weighting cost between the competing factors. Results: The decision node predictions were optimized against the data for the 58 cases. With this decision network solution, one can consider the decision result for a new patient with specific findings to obtain a recommendation to adaptively modify the originally planned treatment course. Conclusions: A Bayesian approach allows handling and propagating probabilistic data in a logical and principled manner. Decision networks provide the further ability to provide utility-based trade-offs, reflecting non-medical but practical cost/benefit analysis. The network demonstrated illustrates the basic concept, but many other factors may affect these decisions and work on building better models are being designed and tested. Acknowledgement: Supported by NIH-P01-CA59827
Zizzo, Natalie; Bell, Emily; Lafontaine, Anne-Louise; Racine, Eric
2017-08-01
Patient-centred care is a recommended model of care for Parkinson's disease (PD). It aims to provide care that is respectful and responsive to patient preferences, values and perspectives. Provision of patient-centred care should entail considering how patients want to be involved in their care. To understand the participation preferences of patients with PD from a patient-centred care clinic in health-care decision-making processes. Mixed-methods study with early-stage Parkinson's disease patients from a patient-centred care clinic. Study involved a modified Autonomy Preference Index survey (N=65) and qualitative, semi-structured in-depth interviews, analysed using thematic qualitative content analysis (N=20, purposefully selected from survey participants). Interviews examined (i) the patient preferences for involvement in health-care decision making; (ii) patient perspectives on the patient-physician relationship; and (iii) patient preferences for communication of information relevant to decision making. Preferences for participation in decision making varied between individuals and also within individuals depending on decision type, relational and contextual factors. Patients had high preferences for communication of information, but with acknowledged limits. The importance of communication in the patient-physician relationship was emphasized. Patient preferences for involvement in decision making are dynamic and support shared decision making. Relational autonomy corresponds to how patients envision their participation in decision making. Clinicians may need to assess patient preferences on an on-going basis. Our results highlight the complexities of decision-making processes. Improved understanding of individual preferences could enhance respect for persons and make for patient-centred care that is truly respectful of individual patients' wants, needs and values. © 2016 The Authors. Health Expectations Published by John Wiley & Sons Ltd.
He, Xin; Frey, Eric C
2006-08-01
Previously, we have developed a decision model for three-class receiver operating characteristic (ROC) analysis based on decision theory. The proposed decision model maximizes the expected decision utility under the assumption that incorrect decisions have equal utilities under the same hypothesis (equal error utility assumption). This assumption reduced the dimensionality of the "general" three-class ROC analysis and provided a practical figure-of-merit to evaluate the three-class task performance. However, it also limits the generality of the resulting model because the equal error utility assumption will not apply for all clinical three-class decision tasks. The goal of this study was to investigate the optimality of the proposed three-class decision model with respect to several other decision criteria. In particular, besides the maximum expected utility (MEU) criterion used in the previous study, we investigated the maximum-correctness (MC) (or minimum-error), maximum likelihood (ML), and Nyman-Pearson (N-P) criteria. We found that by making assumptions for both MEU and N-P criteria, all decision criteria lead to the previously-proposed three-class decision model. As a result, this model maximizes the expected utility under the equal error utility assumption, maximizes the probability of making correct decisions, satisfies the N-P criterion in the sense that it maximizes the sensitivity of one class given the sensitivities of the other two classes, and the resulting ROC surface contains the maximum likelihood decision operating point. While the proposed three-class ROC analysis model is not optimal in the general sense due to the use of the equal error utility assumption, the range of criteria for which it is optimal increases its applicability for evaluating and comparing a range of diagnostic systems.
Clinical evaluation of patients with patellofemoral disorders.
Post, W R
1999-01-01
Accurate clinical evaluation of patients with patellofemoral disorders is the cornerstone of effective treatment. This article defines how a careful history and physical examination can direct strategies for nonoperative and operative management. A critical analysis of traditional methods of evaluation and a streamlined rational approach to clinical evaluation is presented. Key questions and important physical findings that affect treatment decisions are emphasized.
Abidi, Samina
2017-10-26
Clinical management of comorbidities is a challenge, especially in a clinical decision support setting, as it requires the safe and efficient reconciliation of multiple disease-specific clinical procedures to formulate a comorbid therapeutic plan that is both effective and safe for the patient. In this paper we pursue the integration of multiple disease-specific Clinical Practice Guidelines (CPG) in order to manage co-morbidities within a computerized Clinical Decision Support System (CDSS). We present a CPG integration framework-termed as COMET (Comorbidity Ontological Modeling & ExecuTion) that manifests a knowledge management approach to model, computerize and integrate multiple CPG to yield a comorbid CPG knowledge model that upon execution can provide evidence-based recommendations for handling comorbid patients. COMET exploits semantic web technologies to achieve (a) CPG knowledge synthesis to translate a paper-based CPG to disease-specific clinical pathways (CP) that include specialized co-morbidity management procedures based on input from domain experts; (b) CPG knowledge modeling to computerize the disease-specific CP using a Comorbidity CPG ontology; (c) CPG knowledge integration by aligning multiple ontologically-modeled CP to develop a unified comorbid CPG knowledge model; and (e) CPG knowledge execution using reasoning engines to derive CPG-mediated recommendations for managing patients with comorbidities. We present a web-accessible COMET CDSS that provides family physicians with CPG-mediated comorbidity decision support to manage Atrial Fibrillation and Chronic Heart Failure. We present our qualitative and quantitative analysis of the knowledge content and usability of COMET CDSS.
Roehle, Robert; Wieske, Viktoria; Schuetz, Georg M; Gueret, Pascal; Andreini, Daniele; Meijboom, Willem Bob; Pontone, Gianluca; Garcia, Mario; Alkadhi, Hatem; Honoris, Lily; Hausleiter, Jörg; Bettencourt, Nuno; Zimmermann, Elke; Leschka, Sebastian; Gerber, Bernhard; Rochitte, Carlos; Schoepf, U Joseph; Shabestari, Abbas Arjmand; Nørgaard, Bjarne; Sato, Akira; Knuuti, Juhani; Meijs, Matthijs F L; Brodoefel, Harald; Jenkins, Shona M M; Øvrehus, Kristian Altern; Diederichsen, Axel Cosmus Pyndt; Hamdan, Ashraf; Halvorsen, Bjørn Arild; Mendoza Rodriguez, Vladimir; Wan, Yung Liang; Rixe, Johannes; Sheikh, Mehraj; Langer, Christoph; Ghostine, Said; Martuscelli, Eugenio; Niinuma, Hiroyuki; Scholte, Arthur; Nikolaou, Konstantin; Ulimoen, Geir; Zhang, Zhaoqi; Mickley, Hans; Nieman, Koen; Kaufmann, Philipp A; Buechel, Ronny Ralf; Herzog, Bernhard A; Clouse, Melvin; Halon, David A; Leipsic, Jonathan; Bush, David; Jakamy, Reda; Sun, Kai; Yang, Lin; Johnson, Thorsten; Laissy, Jean-Pierre; Marcus, Roy; Muraglia, Simone; Tardif, Jean-Claude; Chow, Benjamin; Paul, Narinder; Maintz, David; Hoe, John; de Roos, Albert; Haase, Robert; Laule, Michael; Schlattmann, Peter; Dewey, Marc
2018-03-19
To analyse the implementation, applicability and accuracy of the pretest probability calculation provided by NICE clinical guideline 95 for decision making about imaging in patients with chest pain of recent onset. The definitions for pretest probability calculation in the original Duke clinical score and the NICE guideline were compared. We also calculated the agreement and disagreement in pretest probability and the resulting imaging and management groups based on individual patient data from the Collaborative Meta-Analysis of Cardiac CT (CoMe-CCT). 4,673 individual patient data from the CoMe-CCT Consortium were analysed. Major differences in definitions in the Duke clinical score and NICE guideline were found for the predictors age and number of risk factors. Pretest probability calculation using guideline criteria was only possible for 30.8 % (1,439/4,673) of patients despite availability of all required data due to ambiguity in guideline definitions for risk factors and age groups. Agreement regarding patient management groups was found in only 70 % (366/523) of patients in whom pretest probability calculation was possible according to both models. Our results suggest that pretest probability calculation for clinical decision making about cardiac imaging as implemented in the NICE clinical guideline for patients has relevant limitations. • Duke clinical score is not implemented correctly in NICE guideline 95. • Pretest probability assessment in NICE guideline 95 is impossible for most patients. • Improved clinical decision making requires accurate pretest probability calculation. • These refinements are essential for appropriate use of cardiac CT.
Designing Colorectal Cancer Screening Decision Support: A Cognitive Engineering Enterprise.
Militello, Laura G; Saleem, Jason J; Borders, Morgan R; Sushereba, Christen E; Haverkamp, Donald; Wolf, Steven P; Doebbeling, Bradley N
2016-03-01
Adoption of clinical decision support has been limited. Important barriers include an emphasis on algorithmic approaches to decision support that do not align well with clinical work flow and human decision strategies, and the expense and challenge of developing, implementing, and refining decision support features in existing electronic health records (EHRs). We applied decision-centered design to create a modular software application to support physicians in managing and tracking colorectal cancer screening. Using decision-centered design facilitates a thorough understanding of cognitive support requirements from an end user perspective as a foundation for design. In this project, we used an iterative design process, including ethnographic observation and cognitive task analysis, to move from an initial design concept to a working modular software application called the Screening & Surveillance App. The beta version is tailored to work with the Veterans Health Administration's EHR Computerized Patient Record System (CPRS). Primary care providers using the beta version Screening & Surveillance App more accurately answered questions about patients and found relevant information more quickly compared to those using CPRS alone. Primary care providers also reported reduced mental effort and rated the Screening & Surveillance App positively for usability.
Designing Colorectal Cancer Screening Decision Support: A Cognitive Engineering Enterprise
Militello, Laura G.; Saleem, Jason J.; Borders, Morgan R.; Sushereba, Christen E.; Haverkamp, Donald; Wolf, Steven P.; Doebbeling, Bradley N.
2016-01-01
Adoption of clinical decision support has been limited. Important barriers include an emphasis on algorithmic approaches to decision support that do not align well with clinical work flow and human decision strategies, and the expense and challenge of developing, implementing, and refining decision support features in existing electronic health records (EHRs). We applied decision-centered design to create a modular software application to support physicians in managing and tracking colorectal cancer screening. Using decision-centered design facilitates a thorough understanding of cognitive support requirements from an end user perspective as a foundation for design. In this project, we used an iterative design process, including ethnographic observation and cognitive task analysis, to move from an initial design concept to a working modular software application called the Screening & Surveillance App. The beta version is tailored to work with the Veterans Health Administration’s EHR Computerized Patient Record System (CPRS). Primary care providers using the beta version Screening & Surveillance App more accurately answered questions about patients and found relevant information more quickly compared to those using CPRS alone. Primary care providers also reported reduced mental effort and rated the Screening & Surveillance App positively for usability. PMID:26973441
Unconscious emotional reasoning and the therapeutic misconception.
Charuvastra, A; Marder, S R
2008-03-01
The "therapeutic misconception" describes a process whereby research volunteers misinterpret the intentions of researchers and the nature of clinical research. This misinterpretation leads research volunteers to falsely attribute a therapeutic potential to clinical research, and compromises informed decision making, therefore compromising the ethical integrity of a clinical experiment. We review recent evidence from the neurobiology of social cognition to provide a novel framework for thinking about the therapeutic misconception. We argue that the neurobiology of social cognition should be considered in any ethical analysis of how people make decisions about participating in clinical trials. The neurobiology of social cognition also suggests how the complicated dynamics of the doctor-patient relationship may unavoidably interfere with the process of obtaining informed consent. Following this argument we suggest new ways to prevent or at least mitigate the therapeutic misconception.
Laskaris, James; Regan, Katie
2013-12-01
Changes in the economic and legislative environment have complicated the capital acquisition landscape. Hospitals and health systems should: Question the assumptions that underlie their break-even analysis. Revamp the break-even calculator. Engage in discussions about the clinical aspects of equipment and technology acquisition decisions.
Ramnarayan, Padmanabhan; Kapoor, Ritika R; Coren, Michael; Nanduri, Vasantha; Tomlinson, Amanda L; Taylor, Paul M; Wyatt, Jeremy C; Britto, Joseph F
2003-01-01
Few previous studies evaluating the benefits of diagnostic decision support systems have simultaneously measured changes in diagnostic quality and clinical management prompted by use of the system. This report describes a reliable and valid scoring technique to measure the quality of clinical decision plans in an acute medical setting, where diagnostic decision support tools might prove most useful. Sets of differential diagnoses and clinical management plans generated by 71 clinicians for six simulated cases, before and after decision support from a Web-based pediatric differential diagnostic tool (ISABEL), were used. A composite quality score was calculated separately for each diagnostic and management plan by considering the appropriateness value of each component diagnostic or management suggestion, a weighted sum of individual suggestion ratings, relevance of the entire plan, and its comprehensiveness. The reliability and validity (face, concurrent, construct, and content) of these two final scores were examined. Two hundred fifty-two diagnostic and 350 management suggestions were included in the interrater reliability analysis. There was good agreement between raters (intraclass correlation coefficient, 0.79 for diagnoses, and 0.72 for management). No counterintuitive scores were demonstrated on visual inspection of the sets. Content validity was verified by a consultation process with pediatricians. Both scores discriminated adequately between the plans of consultants and medical students and correlated well with clinicians' subjective opinions of overall plan quality (Spearman rho 0.65, p < 0.01). The diagnostic and management scores for each episode showed moderate correlation (r = 0.51). The scores described can be used as key outcome measures in a larger study to fully assess the value of diagnostic decision aids, such as the ISABEL system.
Supply chain optimization for pediatric perioperative departments.
Davis, Janice L; Doyle, Robert
2011-09-01
Economic challenges compel pediatric perioperative departments to reduce nonlabor supply costs while maintaining the quality of patient care. Optimization of the supply chain introduces a framework for decision making that drives fiscally responsible decisions. The cost-effective supply chain is driven by implementing a value analysis process for product selection, being mindful of product sourcing decisions to reduce supply expense, creating logistical efficiency that will eliminate redundant processes, and managing inventory to ensure product availability. The value analysis approach is an analytical methodology for product selection that involves product evaluation and recommendation based on consideration of clinical benefit, overall financial impact, and revenue implications. Copyright © 2011 AORN, Inc. Published by Elsevier Inc. All rights reserved.
Difficult end-of-life treatment decisions: do other factors trump advance directives?
Hardin, Steven B; Yusufaly, Yasmin A
2004-07-26
Advance directives are widely promoted as a means to plan for patients' decisional incapacity, yet there is little evidence of their effectiveness. We devised a study to assess physicians' compliance with hypothetical advance directives and further examine their clinical reasoning. The study consisted of an analysis of a mailed written survey containing 6 hypothetical cases of seriously ill patients. Each case contained an explicit advance directive with potential conflict between the directive and (1) prognosis, (2) wishes of family or friends, or (3) quality of life. Data were collected on the clinical treatment decisions made by physicians and the reasons for those decisions. Study participants were all internal medicine faculty and resident physicians from a single academic institution. A total of 47% analyzable surveys (117/250) were returned. Decisions by faculty and residents were not consistent with the advance directive in 65% of cases. This inconsistency was similar for faculty and residents (68% and 61%, respectively; P>.05). When physicians made decisions inconsistent with the advance directive, they were more likely to list reasons other than the directive for their decisions (89%; P<.001). Internists frequently made treatment decisions that were not consistent with an explicit advance directive. In difficult clinical situations, internists appear to consider other factors such as prognosis, perceived quality of life, and the wishes of family or friends as more determinative than the directive. Future work needs to explore the generalizability of these findings and examine how strictly patients desire their advance directives to be followed.
Bavuso, Karen; Bouyer-Ferullo, Sharon; Goldsmith, Denise; Fairbanks, Amanda; Gesner, Emily; Lagor, Charles; Collins, Sarah
2016-01-01
Summary Objectives To understand requests for nursing Clinical Decision Support (CDS) interventions at a large integrated health system undergoing vendor-based EHR implementation. In addition, to establish a process to guide both short-term implementation and long-term strategic goals to meet nursing CDS needs. Materials and Methods We conducted an environmental scan to understand current state of nursing CDS over three months. The environmental scan consisted of a literature review and an analysis of CDS requests received from across our health system. We identified existing high priority CDS and paper-based tools used in nursing practice at our health system that guide decision-making. Results A total of 46 nursing CDS requests were received. Fifty-six percent (n=26) were specific to a clinical specialty; 22 percent (n=10) were focused on facilitating clinical consults in the inpatient setting. “Risk Assessments/Risk Reduction/Promotion of Healthy Habits” (n=23) was the most requested High Priority Category received for nursing CDS. A continuum of types of nursing CDS needs emerged using the Data-Information-Knowledge-Wisdom Conceptual Framework: 1) facilitating data capture, 2) meeting information needs, 3) guiding knowledge-based decision making, and 4) exposing analytics for wisdom-based clinical interpretation by the nurse. Conclusion Identifying and prioritizing paper-based tools that can be modified into electronic CDS is a challenge. CDS strategy is an evolving process that relies on close collaboration and engagement with clinical sites for short-term implementation and should be incorporated into a long-term strategic plan that can be optimized and achieved overtime. The Data-Information-Knowledge-Wisdom Conceptual Framework in conjunction with the High Priority Categories established may be a useful tool to guide a strategic approach for meeting short-term nursing CDS needs and aligning with the organizational strategic plan. PMID:27437036
Fraser, Alec; Baeza, Juan I; Boaz, Annette
2017-06-09
Health service reconfigurations are of international interest but remain poorly understood. This article focuses on the use of evidence by senior managerial decision-makers involved in the reconfiguration of stroke services in London 2008-2012. Recent work comparing stroke service reconfiguration in London and Manchester emphasises the ability of senior managerial decision-makers in London to 'hold the line' in the crucial early phases of the stroke reconfiguration programme. In this article, we explore in detail how these decision-makers 'held the line' and ask what the broader power implications of doing so are for the interaction between evidence, health policy and system redesign. The research combined semi-structured interviews (n = 20) and documentary analysis of historically relevant policy papers and contemporary stroke reconfiguration documentation published by NHS London and other interested parties (n = 125). We applied a critical interpretive and reflexive approach to the analysis of the data. We identified two forms of power which senior managerial decision-makers drew upon in order to 'hold the line'. Firstly, discursive power, which through an emphasis on evidence, better patient outcomes, professional support and clinical credibility alongside a tightly managed consultation process, helped to set an agenda that was broadly receptive to the overall decision to change stroke services in the capital in a radical way. Secondly, once the essential parameters of the decision to change services had been agreed, senior managerial decision-makers 'held the line' through hierarchical New Public Management style power to minimise the traditional pressures to de-radicalise the reconfiguration through 'top down' decision-making. We problematise the concept of 'holding the line' and explore the power implications of such managerial approaches in the early phases of health service reconfiguration. We highlight the importance of evidence for senior managerial decision-makers in agenda setting and the limitations of clinical research findings in guiding politically sensitive policy decisions which impact upon regional healthcare systems.
Clinical decisions for anterior restorations: the concept of restorative volume.
Cardoso, Jorge André; Almeida, Paulo Júlio; Fischer, Alex; Phaxay, Somano Luang
2012-12-01
The choice of the most appropriate restoration for anterior teeth is often a difficult decision. Numerous clinical and technical factors play an important role in selecting the treatment option that best suits the patient and the restorative team. Experienced clinicians have developed decision processes that are often more complex than may seem. Less experienced professionals may find difficulties making treatment decisions because of the widely varied restorative materials available and often numerous similar products offered by different manufacturers. The authors reviewed available evidence and integrated their clinical experience to select relevant factors that could provide a logical and practical guideline for restorative decisions in anterior teeth. The presented concept of restorative volume is based on structural, optical, and periodontal factors. Each of these factors will influence the short- and long-term behavior of restorations in terms of esthetics, biology, and function. Despite the marked evolution of esthetic restorative techniques and materials, significant limitations still exist, which should be addressed by researchers. The presented guidelines must be regarded as a mere orientation for risk analysis. A comprehensive individual approach should always be the core of restorative esthetic treatments. The complex decision process for anterior esthetic restorations can be clarified by a systematized examination of structural, optical, and periodontal factors. The basis for the proposed thought process is the concept of restorative volume that is a contemporary interpretation of restoration categories and their application. © 2012 Wiley Periodicals, Inc.
Moro, Marilyn; Goparaju, Balaji; Castillo, Jelina; Alameddine, Yvonne; Bianchi, Matt T
2016-01-01
Introduction Periodic limb movements of sleep (PLMS) may increase cardiovascular and cerebrovascular morbidity. However, most people with PLMS are either asymptomatic or have nonspecific symptoms. Therefore, predicting elevated PLMS in the absence of restless legs syndrome remains an important clinical challenge. Methods We undertook a retrospective analysis of demographic data, subjective symptoms, and objective polysomnography (PSG) findings in a clinical cohort with or without obstructive sleep apnea (OSA) from our laboratory (n=443 with OSA, n=209 without OSA). Correlation analysis and regression modeling were performed to determine predictors of periodic limb movement index (PLMI). Markov decision analysis with TreeAge software compared strategies to detect PLMS: in-laboratory PSG, at-home testing, and a clinical prediction tool based on the regression analysis. Results Elevated PLMI values (>15 per hour) were observed in >25% of patients. PLMI values in No-OSA patients correlated with age, sex, self-reported nocturnal leg jerks, restless legs syndrome symptoms, and hypertension. In OSA patients, PLMI correlated only with age and self-reported psychiatric medications. Regression models indicated only a modest predictive value of demographics, symptoms, and clinical history. Decision modeling suggests that at-home testing is favored as the pretest probability of PLMS increases, given plausible assumptions regarding PLMS morbidity, costs, and assumed benefits of pharmacological therapy. Conclusion Although elevated PLMI values were commonly observed, routinely acquired clinical information had only weak predictive utility. As the clinical importance of elevated PLMI continues to evolve, it is likely that objective measures such as PSG or at-home PLMS monitors will prove increasingly important for clinical and research endeavors. PMID:27540316
Selecting automation for the clinical chemistry laboratory.
Melanson, Stacy E F; Lindeman, Neal I; Jarolim, Petr
2007-07-01
Laboratory automation proposes to improve the quality and efficiency of laboratory operations, and may provide a solution to the quality demands and staff shortages faced by today's clinical laboratories. Several vendors offer automation systems in the United States, with both subtle and obvious differences. Arriving at a decision to automate, and the ensuing evaluation of available products, can be time-consuming and challenging. Although considerable discussion concerning the decision to automate has been published, relatively little attention has been paid to the process of evaluating and selecting automation systems. To outline a process for evaluating and selecting automation systems as a reference for laboratories contemplating laboratory automation. Our Clinical Chemistry Laboratory staff recently evaluated all major laboratory automation systems in the United States, with their respective chemistry and immunochemistry analyzers. Our experience is described and organized according to the selection process, the important considerations in clinical chemistry automation, decisions and implementation, and we give conclusions pertaining to this experience. Including the formation of a committee, workflow analysis, submitting a request for proposal, site visits, and making a final decision, the process of selecting chemistry automation took approximately 14 months. We outline important considerations in automation design, preanalytical processing, analyzer selection, postanalytical storage, and data management. Selecting clinical chemistry laboratory automation is a complex, time-consuming process. Laboratories considering laboratory automation may benefit from the concise overview and narrative and tabular suggestions provided.
Chew, Keng Sheng; Kueh, Yee Cheng; Abdul Aziz, Adlihafizi
2017-03-21
Despite their importance on diagnostic accuracy, there is a paucity of literature on questionnaire tools to assess clinicians' awareness toward cognitive errors. A validation study was conducted to develop a questionnaire tool to evaluate the Clinician's Awareness Towards Cognitive Errors (CATChES) in clinical decision making. This questionnaire is divided into two parts. Part A is to evaluate the clinicians' awareness towards cognitive errors in clinical decision making while Part B is to evaluate their perception towards specific cognitive errors. Content validation for both parts was first determined followed by construct validation for Part A. Construct validation for Part B was not determined as the responses were set in a dichotomous format. For content validation, all items in both Part A and Part B were rated as "excellent" in terms of their relevance in clinical settings. For construct validation using exploratory factor analysis (EFA) for Part A, a two-factor model with total variance extraction of 60% was determined. Two items were deleted. Then, the EFA was repeated showing that all factor loadings are above the cut-off value of >0.5. The Cronbach's alpha for both factors are above 0.6. The CATChES questionnaire tool is a valid questionnaire tool aimed to evaluate the awareness among clinicians toward cognitive errors in clinical decision making.
Rousson, Valentin; Zumbrunn, Thomas
2011-06-22
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. 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. 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. We present several interrelated extensions to decision curve analysis that will both facilitate its interpretation and broaden its potential area of application.
2011-01-01
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
Nagashima, Hisashi; Wada, Yoshitaka; Hongo, Kazuhiro
2017-08-15
Following the modern raising of public awareness, the numbers of malpractice litigation are increasing in the health care delivery system in Japan despite the extensive efforts of physicians. Authors reviewed the issues of litigation and the reasons for court decision from the healthcare-related negligence lawsuits in the past 15 years in Japan and investigated the cautionary points for reducing potential litigation. Healthcare-related negligence lawsuits between January 2001 and December 2015 were retrieved and sorted in each clinical field from the database in Courts in Japan and investigated on the proportional factors of the claims and court decisions in the neurosurgical field. During the period, 446 of healthcare-related court decisions including 41 against neurosurgeons (9.2%) were retrieved. Three of 41 decisions retrieved were decisions to retries for lower court decisions. In 38 claims against the neurosurgeons, 26 identified the negligence and 12 dismissed. In 26 decisions in favor of the plaintiffs, identified negligence in diagnosis in 4, clinical judgment in 3, technical skills in 5, clinical management in 7 and process of informed consent in 7. Five out of 18 decisions after 2006 were identified as negligence in an informed consent process, and additional one, who was mainly identified in inadequate technical skills also identified existing an inadequate informed consent process as a fundamental cause of litigation. Neurosurgeons are a higher risk group for malpractice litigation in Japan and adequate informed consent is important to reduce the risk of litigation.
Gender Differences in Bladder Cancer Treatment Decision Making.
Pozzar, Rachel A; Berry, Donna L
2017-03-01
To explore gender differences in bladder cancer treatment decision making. . Secondary qualitative analysis of interview transcripts. . One multidisciplinary genitourinary oncology clinic (Dana-Farber Cancer Institute) and two urology clinics (Brigham and Women's Hospital and Beth Israel Deaconess Medical Center) in Boston, MA. . As part of the original study, 45 men and 15 women with bladder cancer participated in individual interviews. Participants were primarily Caucasian, and most had at least some college education. . Word frequency reports were used to identify thematic differences between the men's and women's statements. Line-by-line coding of constructs prevalent among women was then performed on all participants in NVivo 9. Coding results were compared between genders using matrix coding queries. . The role of family in the decision-making process was found to be a dominant theme for women but not for men. Women primarily described family members as facilitators of bladder cancer treatment-related decisions, but men were more likely to describe family in a nonsupportive role. . The results suggest that influences on the decision-making process are different for men and women with bladder cancer. Family may play a particularly important role for women faced with bladder cancer treatment-related decisions. . Clinical nurses who care for individuals with bladder cancer should routinely assess patients' support systems and desired level of family participation in decision making. For some people with bladder cancer, family may serve as a stressor. Nurses should support the decision-making processes of all patients and be familiar with resources that can provide support to patients who do not receive it from family.
Hozo, Iztok; Schell, Michael J; Djulbegovic, Benjamin
2008-07-01
The absolute truth in research is unobtainable, as no evidence or research hypothesis is ever 100% conclusive. Therefore, all data and inferences can in principle be considered as "inconclusive." Scientific inference and decision-making need to take into account errors, which are unavoidable in the research enterprise. The errors can occur at the level of conclusions that aim to discern the truthfulness of research hypothesis based on the accuracy of research evidence and hypothesis, and decisions, the goal of which is to enable optimal decision-making under present and specific circumstances. To optimize the chance of both correct conclusions and correct decisions, the synthesis of all major statistical approaches to clinical research is needed. The integration of these approaches (frequentist, Bayesian, and decision-analytic) can be accomplished through formal risk:benefit (R:B) analysis. This chapter illustrates the rational choice of a research hypothesis using R:B analysis based on decision-theoretic expected utility theory framework and the concept of "acceptable regret" to calculate the threshold probability of the "truth" above which the benefit of accepting a research hypothesis outweighs its risks.
Robinson, M; Palmer, S; Sculpher, M; Philips, Z; Ginnelly, L; Bowens, A; Golder, S; Alfakih, K; Bakhai, A; Packham, C; Cooper, N; Abrams, K; Eastwood, A; Pearman, A; Flather, M; Gray, D; Hall, A
2005-07-01
To identify and prioritise key areas of clinical uncertainty regarding the medical management of non-ST elevation acute coronary syndrome (ACS) in current UK practice. Electronic databases. Consultations with clinical advisors. Postal survey of cardiologists. Potential areas of important uncertainty were identified and 'decision problems' prioritised. A systematic literature review was carried out using standard methods. The constructed decision model consisted of a short-term phase that applied the results of the systematic review and a long-term phase that included relevant information from a UK observational study to extrapolate estimated costs and effects. Sensitivity analyses were undertaken to examine the dependence of the results on baseline parameters, using alternative data sources. Expected value of information analysis was undertaken to estimate the expected value of perfect information associated with the decision problem. This provided an upper bound on the monetary value associated with additional research in the area. Seven current areas of clinical uncertainty (decision problems) in the drug treatment of unstable angina patients were identified. The agents concerned were clopidogrel, low molecular weight heparin, hirudin and intravenous glycoprotein antagonists (GPAs). Twelve published clinical guidelines for unstable angina or non-ST elevation ACS were identified, but few contained recommendations about the specified decision problems. The postal survey of clinicians showed that the greatest disagreement existed for the use of small molecule GPAs, and the greatest uncertainty existed for decisions relating to the use of abciximab (a large molecule GPA). Overall, decision problems concerning the GPA class of drugs were considered to be the highest priority for further study. Selected papers describing the clinical efficacy of treatment were divided into three groups, each representing an alternative strategy. The strategy involving the use of GPAs as part of the initial medical management of all non-ST elevation ACS was the optimal choice, with an incremental cost-effectiveness ratio (ICER) of 5738 pounds per quality-adjusted life-year (QALY) compared with no use of GPAs. Stochastic analysis showed that if the health service is willing to pay 10,000 pounds per additional QALY, the probability of this strategy being cost-effective was around 82%, increasing to 95% at a threshold of 50,000 pounds per QALY. A sensitivity analysis including an additional strategy of using GPAs as part of initial medical management only in patients at particular high risk (as defined by age, ST depression or diabetes) showed that this additional strategy was yet more cost-effective, with an ICER of 3996 pounds per QALY compared with no treatment with GPA. Value of information analysis suggested that there was considerable merit in additional research to reduce the level of uncertainty in the optimal decision. At a threshold of 10,000 pounds per QALY, the maximum potential value of such research in the base case was calculated as 12.7 million pounds per annum for the UK as a whole. Taking account of the greater uncertainty in the sensitivity analyses including clopidogrel, this figure was increased to approximately 50 million pounds. This study suggests the use of GPAs in all non-ST elevation ACS patients as part of their initial medical management. Sensitivity analysis showed that virtually all of the benefit could be realised by treating only high-risk patients. Further clarification of the optimum role of GPAs in the UK NHS depends on the availability of further high-quality observational and trial data. Value of information analysis derived from the model suggests that a relatively large investment in such research may be worthwhile. Further research should focus on the identification of the characteristics of patients who benefit most from GPAs as part of medical management, the comparison of GPAs with clopidogrel as an adjunct to standard care, follow-up cohort studies of the costs and outcomes of high-risk non-ST elevation ACS over several years, and exploring how clinicians' decisions combine a normative evidence-based decision model with their own personal behavioural perspective.
Objective consensus from decision trees.
Putora, Paul Martin; Panje, Cedric M; Papachristofilou, Alexandros; Dal Pra, Alan; Hundsberger, Thomas; Plasswilm, Ludwig
2014-12-05
Consensus-based approaches provide an alternative to evidence-based decision making, especially in situations where high-level evidence is limited. Our aim was to demonstrate a novel source of information, objective consensus based on recommendations in decision tree format from multiple sources. Based on nine sample recommendations in decision tree format a representative analysis was performed. The most common (mode) recommendations for each eventuality (each permutation of parameters) were determined. The same procedure was applied to real clinical recommendations for primary radiotherapy for prostate cancer. Data was collected from 16 radiation oncology centres, converted into decision tree format and analyzed in order to determine the objective consensus. Based on information from multiple sources in decision tree format, treatment recommendations can be assessed for every parameter combination. An objective consensus can be determined by means of mode recommendations without compromise or confrontation among the parties. In the clinical example involving prostate cancer therapy, three parameters were used with two cut-off values each (Gleason score, PSA, T-stage) resulting in a total of 27 possible combinations per decision tree. Despite significant variations among the recommendations, a mode recommendation could be found for specific combinations of parameters. Recommendations represented as decision trees can serve as a basis for objective consensus among multiple parties.
Guidi, G; Pettenati, M C; Miniati, R; Iadanza, E
2012-01-01
In this paper we describe an Heart Failure analysis Dashboard that, combined with a handy device for the automatic acquisition of a set of patient's clinical parameters, allows to support telemonitoring functions. The Dashboard's intelligent core is a Computer Decision Support System designed to assist the clinical decision of non-specialist caring personnel, and it is based on three functional parts: Diagnosis, Prognosis, and Follow-up management. Four Artificial Intelligence-based techniques are compared for providing diagnosis function: a Neural Network, a Support Vector Machine, a Classification Tree and a Fuzzy Expert System whose rules are produced by a Genetic Algorithm. State of the art algorithms are used to support a score-based prognosis function. The patient's Follow-up is used to refine the diagnosis.
Stein, Sherman C; Fabbri, Andrea; Servadei, Franco; Glick, Henry A
2009-02-01
A number of clinical decision aids have been introduced to limit unnecessary computed tomographic scans in patients with mild traumatic brain injury. These aids differ in the risk factors they use to recommend a scan. We compare the instruments according to their sensitivity and specificity and recommend ones based on incremental benefit of correctly classifying patients as having surgical, nonsurgical, or no intracranial lesions. We performed a secondary analysis of prospectively collected database from 7,955 patients aged 10 years or older with mild traumatic brain injury to compare sensitivity and specificity of 6 common clinical decision strategies: the Canadian CT Head Rule, the Neurotraumatology Committee of the World Federation of Neurosurgical Societies, the New Orleans, the National Emergency X-Radiography Utilization Study II (NEXUS-II), the National Institute of Clinical Excellence guideline, and the Scandinavian Neurotrauma Committee guideline. Excluded from the database were patients for whom the history of trauma was unclear, the initial Glasgow Coma Scale score was less than 14, the injury was penetrating, vital signs were unstable, or who refused diagnostic tests. Patients revisiting the emergency department within 7 days were counted only once. The percentage of scans that would have been required by applying each of the 6 aids were Canadian CT head rule (high risk only) 53%, Canadian (medium & high risk) 56%, the Neurotraumatology Committee of the World Federation of Neurosurgical Societies 56%, New Orleans 69%, NEXUS-II 56%, National Institute of Clinical Excellence 71%, and the Scandinavian 50%. The 6 decision aids' sensitivities for surgical hematomas could not be distinguished statistically (P>.05). Sensitivity was 100% (95% confidence interval [CI] 96% to 100%) for NEXUS-II, 98.1% (95% CI 93% to 100%) for National Institute of Clinical Excellence, and 99.1% (95% CI 94% to 100%) for the other 4 clinical decision instruments. Sensitivity for any intracranial lesion ranged from 95.7% (95% CI 93% to 97%) (Scandinavian) to 100% (95% CI 98% to 100%) (National Institute of Clinical Excellence). In contrast, specificities varied between 30.9% (95% CI 30% to 32%) (National Institute of Clinical Excellence) and 52.9% (95% CI 52% to 54) (Scandinavian). NEXUS-II and the Scandinavian clinical decision aids displayed the best combination of sensitivity and specificity in this patient population. However, we cannot demonstrate that the higher sensitivity of NEXUS-II for surgical hematomas is statistically significant. Therefore, choosing which of the 2 clinical decision instruments to use must be based on decisionmakers' attitudes toward risk.
Registered nurses' decision-making regarding documentation in patients' progress notes.
Tower, Marion; Chaboyer, Wendy; Green, Quentine; Dyer, Kirsten; Wallis, Marianne
2012-10-01
To examine registered nurses' decision-making when documenting care in patients' progress notes. What constitutes effective nursing documentation is supported by available guidelines. However, ineffective documentation continues to be cited as a major cause of adverse events for patients. Decision-making in clinical practice is a complex process. To make an effective decision, the decision-maker must be situationally aware. The concept of situation awareness and its implications for making safe decisions has been examined extensively in air safety and more recently is being applied to health. The study was situated in a naturalistic paradigm. Purposive sampling was used to recruit 17 registered nurses who used think-aloud research methods when making decisions about documenting information in patients' progress notes. Follow-up interviews were conducted to validate interpretations. Data were analysed systematically for evidence of cues that demonstrated situation awareness as nurses made decisions about documentation. Three distinct decision-making scenarios were illuminated from the analysis: the newly admitted patient, the patient whose condition was as expected and the discharging patient. Nurses used mental models for decision-making in documenting in progress notes, and the cues nurses used to direct their assessment of patients' needs demonstrated situation awareness at different levels. Nurses demonstrate situation awareness at different levels in their decision-making processes. While situation awareness is important, it is also important to use an appropriate decision-making framework. Cognitive continuum theory is suggested as a decision-making model that could support situation awareness when nurses made decisions about documenting patient care. Because nurses are key decision-makers, it is imperative that effective decisions are made that translate into safe clinical care. Including situation awareness training, combined with employing cognitive continuum theory as a decision-making framework, provides a powerful means of guiding nurses' decision-making. © 2012 Blackwell Publishing Ltd.
Goenka, Anu; Jeena, Prakash M; Mlisana, Koleka; Solomon, Tom; Spicer, Kevin; Stephenson, Rebecca; Verma, Arpana; Dhada, Barnesh; Griffiths, Michael J
2018-03-01
Early diagnosis of tuberculous meningitis (TBM) is crucial to achieve optimum outcomes. There is no effective rapid diagnostic test for use in children. We aimed to develop a clinical decision tool to facilitate the early diagnosis of childhood TBM. Retrospective case-control study was performed across 7 hospitals in KwaZulu-Natal, South Africa (2010-2014). We identified the variables most predictive of microbiologically confirmed TBM in children (3 months to 15 years) by univariate analysis. These variables were modelled into a clinical decision tool and performance tested on an independent sample group. Of 865 children with suspected TBM, 3% (25) were identified with microbiologically confirmed TBM. Clinical information was retrieved for 22 microbiologically confirmed cases of TBM and compared with 66 controls matched for age, ethnicity, sex and geographical origin. The 9 most predictive variables among the confirmed cases were used to develop a clinical decision tool (CHILD TB LP): altered Consciousness; caregiver HIV infected; Illness length >7 days; Lethargy; focal neurologic Deficit; failure to Thrive; Blood/serum sodium <132 mmol/L; CSF >10 Lymphocytes ×10/L; CSF Protein >0.65 g/L. This tool successfully classified an independent sample of 7 cases and 21 controls with a sensitivity of 100% and specificity of 90%. The CHILD TB LP decision tool accurately classified microbiologically confirmed TBM. We propose that CHILD TB LP is prospectively evaluated as a novel rapid diagnostic tool for use in the initial evaluation of children with suspected neurologic infection presenting to hospitals in similar settings.
Santos, Adriano A; Moura, J Antão B; de Araújo, Joseana Macêdo Fechine Régis
2015-01-01
Mitigating uncertainty and risks faced by specialist physicians in analysis of rare clinical cases is something desired by anyone who needs health services. The number of clinical cases never seen by these experts, with little documentation, may introduce errors in decision-making. Such errors negatively affect well-being of patients, increase procedure costs, rework, health insurance premiums, and impair the reputation of specialists and medical systems involved. In this context, IT and Clinical Decision Support Systems (CDSS) play a fundamental role, supporting decision-making process, making it more efficient and effective, reducing a number of avoidable medical errors and enhancing quality of treatment given to patients. An investigation has been initiated to look into characteristics and solution requirements of this problem, model it, propose a general solution in terms of a conceptual risk-based, automated framework to support rare-case medical diagnostics and validate it by means of case studies. A preliminary validation study of the proposed framework has been carried out by interviews conducted with experts who are practicing professionals, academics, and researchers in health care. This paper summarizes the investigation and its positive results. These results motivate continuation of research towards development of the conceptual framework and of a software tool that implements the proposed model.
Jackman, David M; Zhang, Yichen; Dalby, Carole; Nguyen, Tom; Nagle, Julia; Lydon, Christine A; Rabin, Michael S; McNiff, Kristen K; Fraile, Belen; Jacobson, Joseph O
2017-04-01
Increasing costs and medical complexity are significant challenges in modern oncology. We explored the use of clinical pathways to support clinical decision making and manage resources prospectively across our network. We created customized lung cancer pathways and partnered with a commercial vendor to provide a Web-based platform for real-time decision support and post-treatment data aggregation. Dana-Farber Cancer Institute (DFCI) Pathways for non-small cell lung cancer (NSCLC) were introduced in January 2014. We identified all DFCI patients who were diagnosed and treated for stage IV NSCLC in 2012 (before pathways) and 2014 (after pathways). Costs of care were determined for 1 year from the time of diagnosis. Pre- and postpathway cohorts included 160 and 210 patients with stage IV NSCLC, respectively. The prepathway group had more women but was otherwise similarly matched for demographic and tumor characteristics. The total 12-month cost of care (adjusted for age, sex, race, distance to DFCI, clinical trial enrollment, and EGFR and ALK status) demonstrated a $15,013 savings after the implementation of pathways ($67,050 before pathways v $52,037 after pathways). Antineoplastics were the largest source of cost savings. Clinical outcomes were not compromised, with similar median overall survival times (10.7 months before v 11.2 months after pathways; P = .08). After introduction of a clinical pathway in metastatic NSCLC, cost of care decreased significantly, with no compromise in survival. In an era where comparative outcomes analysis and value assessment are increasingly important, the implementation of clinical pathways may provide a means to coalesce and disseminate institutional expertise and track and learn from care decisions.
Mühlbacher, Axel C; Kaczynski, Anika
2016-02-01
Healthcare decision making is usually characterized by a low degree of transparency. The demand for transparent decision processes can be fulfilled only when assessment, appraisal and decisions about health technologies are performed under a systematic construct of benefit assessment. The benefit of an intervention is often multidimensional and, thus, must be represented by several decision criteria. Complex decision problems require an assessment and appraisal of various criteria; therefore, a decision process that systematically identifies the best available alternative and enables an optimal and transparent decision is needed. For that reason, decision criteria must be weighted and goal achievement must be scored for all alternatives. Methods of multi-criteria decision analysis (MCDA) are available to analyse and appraise multiple clinical endpoints and structure complex decision problems in healthcare decision making. By means of MCDA, value judgments, priorities and preferences of patients, insurees and experts can be integrated systematically and transparently into the decision-making process. This article describes the MCDA framework and identifies potential areas where MCDA can be of use (e.g. approval, guidelines and reimbursement/pricing of health technologies). A literature search was performed to identify current research in healthcare. The results showed that healthcare decision making is addressing the problem of multiple decision criteria and is focusing on the future development and use of techniques to weight and score different decision criteria. This article emphasizes the use and future benefit of MCDA.
How do community pharmacists make decisions? Results of an exploratory qualitative study in Ontario.
Gregory, Paul A M; Whyte, Brenna; Austin, Zubin
2016-03-01
As the complexity of pharmacy practice increases, pharmacists are required to make more decisions under ambiguous or information-deficient conditions. There is scant literature examining how pharmacists make decisions and what factors or values influence their choices. The objective of this exploratory research was to characterize decision-making patterns in the clinical setting of community pharmacists in Ontario. The think-aloud decision-making method was used for this study. Community pharmacists with 3 or more years' experience were presented with 2 clinical case studies dealing with challenging situations and were asked to verbally reason through their decision-making process while being probed by an interviewer for clarification, justification and further explication. Verbatim transcripts were analyzed using a protocol analysis method. A total of 12 pharmacists participated in this study. Participants experienced cognitive dissonance in attempting to reconcile their desire for a clear and confrontation-free conclusion to the case discussion and the reality of the challenge presented within each case. Strategies for resolving this cognitive dissonance included strong emphasis on the educational (rather than decision-making) role of the pharmacist, the value of strong interpersonal relationships as a way to avoid conflict and achieve desired outcomes, the desire to seek external advice or defer to others' authority to avoid making a decision and the use of strict interpretations of rules to avoid ambiguity and contextual interpretation. This research was neither representative nor generalizable but was indicative of patterns of decisional avoidance and fear of assuming responsibility for outcomes that warrant further investigation. The think-aloud method functioned effectively in this context and provided insights into pharmacists' decision-making patterns in the clinical setting. Can Pharm J (Ott) 2016;149:90-98.
Michel, Christiane; Scosyrev, Emil; Petrin, Michael; Schmouder, Robert
2017-05-01
Clinical trials usually do not have the power to detect rare adverse drug reactions. Spontaneous adverse reaction reports as for example available in post-marketing safety databases such as the FDA Adverse Event Reporting System (FAERS) are therefore a valuable source of information to detect new safety signals early. To screen such large data-volumes for safety signals, data-mining algorithms based on the concept of disproportionality have been developed. Because disproportionality analysis is based on spontaneous reports submitted for a large number of drugs and adverse event types, one might consider using these data to compare safety profiles across drugs. In fact, recent publications have promoted this practice, claiming to provide guidance on treatment decisions to healthcare decision makers. In this article we investigate the validity of this approach. We argue that disproportionality cannot be used for comparative drug safety analysis beyond basic hypothesis generation because measures of disproportionality are: (1) missing the incidence denominators, (2) subject to severe reporting bias, and (3) not adjusted for confounding. Hypotheses generated by disproportionality analyses must be investigated by more robust methods before they can be allowed to influence clinical decisions.
Challenges of assessing critical thinking and clinical judgment in nurse practitioner students.
Gorton, Karen L; Hayes, Janice
2014-03-01
The purpose of this study was to determine whether there was a relationship between critical thinking skills and clinical judgment in nurse practitioner students. The study used a convenience, nonprobability sampling technique, engaging participants from across the United States. Correlational analysis demonstrated no statistically significant relationship between critical thinking skills and examination-style questions, critical thinking skills and scores on the evaluation and reevaluation of consequences subscale of the Clinical Decision Making in Nursing Scale, and critical thinking skills and the preceptor evaluation tool. The study found no statistically significant relationships between critical thinking skills and clinical judgment. Educators and practitioners could consider further research in these areas to gain insight into how critical thinking is and could be measured, to gain insight into the clinical decision making skills of nurse practitioner students, and to gain insight into the development and measurement of critical thinking skills in advanced practice educational programs. Copyright 2014, SLACK Incorporated.
Faiola, Anthony; Srinivas, Preethi; Duke, Jon
2015-01-01
Advances in intensive care unit bedside displays/interfaces and electronic medical record (EMR) technology have not adequately addressed the topic of visual clarity of patient data/information to further reduce cognitive load during clinical decision-making. We responded to these challenges with a human-centered approach to designing and testing a decision-support tool: MIVA 2.0 (Medical Information Visualization Assistant, v.2). Envisioned as an EMR visualization dashboard to support rapid analysis of real-time clinical data-trends, our primary goal originated from a clinical requirement to reduce cognitive overload. In the study, a convenience sample of 12 participants were recruited, in which quantitative and qualitative measures were used to compare MIVA 2.0 with ICU paper medical-charts, using time-on-task, post-test questionnaires, and interviews. Findings demonstrated a significant difference in speed and accuracy with the use of MIVA 2.0. Qualitative outcomes concurred, with participants acknowledging the potential impact of MIVA 2.0 for reducing cognitive load and enabling more accurate and quicker decision-making.
Network meta-analysis: an introduction for pharmacists.
Xu, Yina; Amiche, Mohamed Amine; Tadrous, Mina
2018-05-21
Network meta-analysis is a new tool used to summarize and compare studies for multiple interventions, irrespective of whether these interventions have been directly evaluated against each other. Network meta-analysis is quickly becoming the standard in conducting therapeutic reviews and clinical guideline development. However, little guidance is available to help pharmacists review network meta-analysis studies in their practice. Major institutions such as the Cochrane Collaboration, Agency for Healthcare Research and Quality, Canadian Agency for Drugs and Technologies in Health, and National Institute for Health and Care Excellence Decision Support Unit have endorsed utilizing network meta-analysis to establish therapeutic evidence and inform decision making. Our objective is to introduce this novel technique to pharmacy practitioners, and highlight key assumptions behind network meta-analysis studies.
Hostettler, Isabel Charlotte; Muroi, Carl; Richter, Johannes Konstantin; Schmid, Josef; Neidert, Marian Christoph; Seule, Martin; Boss, Oliver; Pangalu, Athina; Germans, Menno Robbert; Keller, Emanuela
2018-01-19
OBJECTIVE The aim of this study was to create prediction models for outcome parameters by decision tree analysis based on clinical and laboratory data in patients with aneurysmal subarachnoid hemorrhage (aSAH). METHODS The database consisted of clinical and laboratory parameters of 548 patients with aSAH who were admitted to the Neurocritical Care Unit, University Hospital Zurich. To examine the model performance, the cohort was randomly divided into a derivation cohort (60% [n = 329]; training data set) and a validation cohort (40% [n = 219]; test data set). The classification and regression tree prediction algorithm was applied to predict death, functional outcome, and ventriculoperitoneal (VP) shunt dependency. Chi-square automatic interaction detection was applied to predict delayed cerebral infarction on days 1, 3, and 7. RESULTS The overall mortality was 18.4%. The accuracy of the decision tree models was good for survival on day 1 and favorable functional outcome at all time points, with a difference between the training and test data sets of < 5%. Prediction accuracy for survival on day 1 was 75.2%. The most important differentiating factor was the interleukin-6 (IL-6) level on day 1. Favorable functional outcome, defined as Glasgow Outcome Scale scores of 4 and 5, was observed in 68.6% of patients. Favorable functional outcome at all time points had a prediction accuracy of 71.1% in the training data set, with procalcitonin on day 1 being the most important differentiating factor at all time points. A total of 148 patients (27%) developed VP shunt dependency. The most important differentiating factor was hyperglycemia on admission. CONCLUSIONS The multiple variable analysis capability of decision trees enables exploration of dependent variables in the context of multiple changing influences over the course of an illness. The decision tree currently generated increases awareness of the early systemic stress response, which is seemingly pertinent for prognostication.
Bryan, Stirling; Williams, Iestyn; McIver, Shirley
2007-02-01
Resource scarcity is the raison d'être for the discipline of economics. Thus, the primary purpose of economic analysis is to help decision-makers when addressing problems arising due to the scarcity problem. The research reported here was concerned with how cost-effectiveness information is used by the National Institute for Health & Clinical Excellence (NICE) in national technology coverage decisions in the UK, and how its impact might be increased. The research followed a qualitative case study methodology with semi-structured interviews, supported by observation and analysis of secondary sources. Our research highlights that the technology appraisal function of NICE represents an important progression for the UK health economics community: new cost-effectiveness work is commissioned for each technology and that work directly informs national health policy. However, accountability in policy decisions necessitates that the information upon which decisions are based (including cost-effectiveness analysis, CEA) is accessible. This was found to be a serious problem and represents one of the main ongoing challenges. Other issues highlighted include perceived weaknesses in analysis methods and the poor alignment between the health maximisation objectives assumed in economic analyses and the range of other objectives facing decision-makers in reality. Copyright (c) 2006 John Wiley & Sons, Ltd.
Wu, Dehua
2016-01-01
The spatial position and distribution of human body meridian are expressed limitedly in the decision support system (DSS) of acupuncture and moxibustion at present, which leads to the failure to give the effective quantitative analysis on the spatial range and the difficulty for the decision-maker to provide a realistic spatial decision environment. Focusing on the limit spatial expression in DSS of acupuncture and moxibustion, it was proposed that on the basis of the geographic information system, in association of DSS technology, the design idea was developed on the human body meridian spatial DSS. With the 4-layer service-oriented architecture adopted, the data center integrated development platform was taken as the system development environment. The hierarchical organization was done for the spatial data of human body meridian via the directory tree. The structured query language (SQL) server was used to achieve the unified management of spatial data and attribute data. The technologies of architecture, configuration and plug-in development model were integrated to achieve the data inquiry, buffer analysis and program evaluation of the human body meridian spatial DSS. The research results show that the human body meridian spatial DSS could reflect realistically the spatial characteristics of the spatial position and distribution of human body meridian and met the constantly changeable demand of users. It has the powerful spatial analysis function and assists with the scientific decision in clinical treatment and teaching of acupuncture and moxibustion. It is the new attempt to the informatization research of human body meridian.
Personalized Clinical Diagnosis in Data Bases for Treatment Support in Phthisiology.
Lugovkina, T K; Skornyakov, S N; Golubev, D N; Egorov, E A; Medvinsky, I D
2016-01-01
The decision-making is a key event in the clinical practice. The program products with clinical decision support models in electronic data-base as well as with fixed decision moments of the real clinical practice and treatment results are very actual instruments for improving phthisiological practice and may be useful in the severe cases caused by the resistant strains of Mycobacterium tuberculosis. The methodology for gathering and structuring of useful information (critical clinical signals for decisions) is described. Additional coding of clinical diagnosis characteristics was implemented for numeric reflection of the personal situations. The created methodology for systematization and coding Clinical Events allowed to improve the clinical decision models for better clinical results.
Should I Pack My Umbrella? Clinical versus Statistical Prediction of Mental Health Decisions
ERIC Educational Resources Information Center
Aegisdottir, Stefania; Spengler, Paul M.; White, Michael J.
2006-01-01
In this rejoinder, the authors respond to the insightful commentary of Strohmer and Arm, Chwalisz, and Hilton, Harris, and Rice about the meta-analysis on statistical versus clinical prediction techniques for mental health judgments. The authors address issues including the availability of statistical prediction techniques for real-life psychology…
Personalized Surgical Risk Assessment Using Population-Based Data Analysis
ERIC Educational Resources Information Center
AbuSalah, Ahmad Mohammad
2013-01-01
The volume of information generated by healthcare providers is growing at a relatively high speed. This tremendous growth has created a gap between knowledge and clinical practice that experts say could be narrowed with the proper use of healthcare data to guide clinical decisions and tools that support rapid information availability at the…
Han, Kyung-Ja; Kim, Hesook Suzie; Kim, Mae-Ja; Hong, Kyung-Ja; Park, Sungae; Yun, Soon-Nyoung; Song, Misoon; Jung, Yoenyi; Kim, Haewon; Kim, Dong-Oak Debbie; Choi, Heejung; Kim, Kyungae
2007-06-01
The purpose of the paper is to discover the patterns and processes of decision-making in clinical nursing practice. A set of think-aloud data from five critical care nurses during 40 to 50 minutes of caregiving in intensive care units were obtained and analyzed by applying the procedures recommended by Ericsson and Simon for protocol analysis. Four thinking processes before acting were identified to constitute various sorts of thoughts in which the nurses were engaged during patient care: reviewing, validation, consideration, rationalization, and action. In addition, three patterns of sequential streaming of thinking (short, intermediate, long) were identified to reveal various ways the nurses dealt with clinical situations involving nursing tasks and responsibilities. This study specifies the initial categories of thoughts for each of the processes and various patterns with which these processes are sequentially combined, providing insights into the ways nurses think about problems and address their concerns. The findings suggest that the thinking in clinical practice involves more than focused decision-making and reasoning, and needs to be examined from a broader perspective.
Searching for Clinically Relevant Biomarkers in Geriatric Oncology.
Katsila, Theodora; Patrinos, George P; Kardamakis, Dimitrios
2018-01-01
Ageing, which is associated with a progressive decline and functional deterioration in multiple organ systems, is highly heterogeneous, both inter- and intraindividually. For this, tailored-made theranostics and optimum patient stratification become fundamental, when decision-making in elderly patients is considered. In particular, when cancer incidence and cancer-related mortality and morbidity are taken into account, elderly patient care is a public health concern. In this review, we focus on oncogeriatrics and highlight current opportunities and challenges with an emphasis on the unmet need of clinically relevant biomarkers in elderly cancer patients. We performed a literature search on PubMed and Scopus databases for articles published in English between 2000 and 2017 coupled to text mining and analysis. Considering the top insights, we derived from our literature analysis that information knowledge needs to turn into knowledge growth in oncogeriatrics towards clinically relevant biomarkers, cost-effective practices, updated educational schemes for health professionals (in particular, geriatricians and oncologists), and awareness of ethical issues. We conclude with an interdisciplinary call to omics, geriatricians, oncologists, informatics, and policy-makers communities that Big Data should be translated into decision-making in the clinic.
NewYork-Presbyterian Hospital: translating innovation into practice.
Johnson, Trudy; Currie, Gail; Keill, Patricia; Corwin, Steven J; Pardes, Herbert; Cooper, Mary Reich
2005-10-01
NewYork-Presbyterian (NYP) Hospital, a 2,242-bed not-for-profit academic medical center, was formed by a merger of The New York Hospital and The Presbyterian Hospital in the City of New York. It is also the flagship for the NewYork-Presbyterian Healthcare System, with 37 acute care facilities and 18 others. The hospital embeds safety in the culture through strategic initiatives and enhances service and efficiency using Six Sigma and other techniques to drive adoption of improvements. Goals are selected in alignment with the annual strategic initiatives, which are chosen on the basis of satisfaction surveys, patient and family complaints, community advisory groups, and performance measures, among other sources. A new business intelligence system enables online, dynamic analysis of performance results, replacing static paper reports. Advanced features in the clinical information systems include computerized physician order entry; interactive clinical alerts for decision support; a real-time infection control tracking system; and a clinical data warehouse supporting data mining and analysis for quality improvement, decision making, and education. To achieve clinical, service, and operational excellence, NYP focuses on all Institute of Medicine quality aims.
Assembling Amperometric Biosensors for Clinical Diagnostics
Belluzo, María Soledad; Ribone, María Élida; Lagier, Claudia Marina
2008-01-01
Clinical diagnosis and disease prevention routinely require the assessment of species determined by chemical analysis. Biosensor technology offers several benefits over conventional diagnostic analysis. They include simplicity of use, specificity for the target analyte, speed to arise to a result, capability for continuous monitoring and multiplexing, together with the potentiality of coupling to low-cost, portable instrumentation. This work focuses on the basic lines of decisions when designing electron-transfer-based biosensors for clinical analysis, with emphasis on the strategies currently used to improve the device performance, the present status of amperometric electrodes for biomedicine, and the trends and challenges envisaged for the near future. PMID:27879771
Rothermundt, Christian; Bailey, Alexandra; Cerbone, Linda; Eisen, Tim; Escudier, Bernard; Gillessen, Silke; Grünwald, Viktor; Larkin, James; McDermott, David; Oldenburg, Jan; Porta, Camillo; Rini, Brian; Schmidinger, Manuela; Sternberg, Cora; Putora, Paul M
2015-09-01
With the advent of targeted therapies, many treatment options in the first-line setting of metastatic clear cell renal cell carcinoma (mccRCC) have emerged. Guidelines and randomized trial reports usually do not elucidate the decision criteria for the different treatment options. In order to extract the decision criteria for the optimal therapy for patients, we performed an analysis of treatment algorithms from experts in the field. Treatment algorithms for the treatment of mccRCC from experts of 11 institutions were obtained, and decision trees were deduced. Treatment options were identified and a list of unified decision criteria determined. The final decision trees were analyzed with a methodology based on diagnostic nodes, which allows for an automated cross-comparison of decision trees. The most common treatment recommendations were determined, and areas of discordance were identified. The analysis revealed heterogeneity in most clinical scenarios. The recommendations selected for first-line treatment of mccRCC included sunitinib, pazopanib, temsirolimus, interferon-α combined with bevacizumab, high-dose interleukin-2, sorafenib, axitinib, everolimus, and best supportive care. The criteria relevant for treatment decisions were performance status, Memorial Sloan Kettering Cancer Center risk group, only or mainly lung metastases, cardiac insufficiency, hepatic insufficiency, age, and "zugzwang" (composite of multiple, related criteria). In the present study, we used diagnostic nodes to compare treatment algorithms in the first-line treatment of mccRCC. The results illustrate the heterogeneity of the decision criteria and treatment strategies for mccRCC and how available data are interpreted and implemented differently among experts. The data provided in the present report should not be considered to serve as treatment recommendations for the management of treatment-naïve patients with multiple metastases from metastatic clear cell renal cell carcinoma outside a clinical trial; however, the data highlight the different treatment options and the criteria used to select them. The diversity in decision making and how results from phase III trials can be interpreted and implemented differently in daily practice are demonstrated. ©AlphaMed Press.
Syed, Ayeshah; Mohd Don, Zuraidah; Ng, Chirk Jenn; Lee, Yew Kong; Khoo, Ee Ming; Lee, Ping Yein; Lim Abdullah, Khatijah; Zainal, Azlin
2017-01-01
Objective To investigate whether the use of apatient decision aid (PDA) for insulin initiation fulfils its purpose of facilitating patient-centred decision-making through identifying how doctors and patients interact when using the PDA during primary care consultations. Design Conversation analysis of seven single cases of audio-recorded/video-recorded consultations between doctors and patients with type 2 diabetes, using a PDA on starting insulin. Setting Primary care in three healthcare settings: (1) one private clinic; (2) two public community clinics and (3) one primary care clinic in a public university hospital, in Negeri Sembilan and the Klang Valley in Malaysia. Participants Clinicians and seven patients with type 2 diabetes to whom insulin had been recommended. Purposive sampling was used to select a sample high in variance across healthcare settings, participant demographics and perspectives on insulin. Primary outcome measures Interaction between doctors and patients in a clinical consultation involving the use of a PDA about starting insulin. Results Doctors brought the PDA into the conversation mainly by asking information-focused ‘yes/no’ questions, and used the PDA for information exchange only if patients said they had not read it. While their contributions were limited by doctors’ questions, some patients disclosed issues or concerns. Although doctors’ PDA-related questions acted as a presequence to deliberation on starting insulin, their interactional practices raised questions on whether patients were informed and their preferences prioritised. Conclusions Interactional practices can hinder effective PDA implementation, with habits from ordinary conversation potentially influencing doctors’ practices and complicating their implementation of patient-centred decision-making. Effective interaction should therefore be emphasised in the design and delivery of PDAs and in training clinicians to use them. PMID:28490553
Wen, Shihua; Zhang, Lanju; Yang, Bo
2014-07-01
The Problem formulation, Objectives, Alternatives, Consequences, Trade-offs, Uncertainties, Risk attitude, and Linked decisions (PrOACT-URL) framework and multiple criteria decision analysis (MCDA) have been recommended by the European Medicines Agency for structured benefit-risk assessment of medicinal products undergoing regulatory review. The objective of this article was to provide solutions to incorporate the uncertainty from clinical data into the MCDA model when evaluating the overall benefit-risk profiles among different treatment options. Two statistical approaches, the δ-method approach and the Monte-Carlo approach, were proposed to construct the confidence interval of the overall benefit-risk score from the MCDA model as well as other probabilistic measures for comparing the benefit-risk profiles between treatment options. Both approaches can incorporate the correlation structure between clinical parameters (criteria) in the MCDA model and are straightforward to implement. The two proposed approaches were applied to a case study to evaluate the benefit-risk profile of an add-on therapy for rheumatoid arthritis (drug X) relative to placebo. It demonstrated a straightforward way to quantify the impact of the uncertainty from clinical data to the benefit-risk assessment and enabled statistical inference on evaluating the overall benefit-risk profiles among different treatment options. The δ-method approach provides a closed form to quantify the variability of the overall benefit-risk score in the MCDA model, whereas the Monte-Carlo approach is more computationally intensive but can yield its true sampling distribution for statistical inference. The obtained confidence intervals and other probabilistic measures from the two approaches enhance the benefit-risk decision making of medicinal products. Copyright © 2014 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.
Clinical trials finance and operations.
O'Brien, Jennifer A
2007-01-01
The National Coverage Decision of 2000 was designed to enhance the participation in clinical trials for both patients and physicians by mandating the governmental coverage for services in a clinical trial that are considered "routine" regardless of the trial. Participation in clinical trials can be a practice builder as well as a contribution to the betterment of medical science. Without proper coverage analysis, study budgeting, accurate time estimates, and effective negotiation prior to signing the contract, participation in clinical trials can cost a practice rather than benefit it.
Becerra-Perez, Maria-Margarita; Menear, Matthew; Turcotte, Stephane; Labrecque, Michel; Légaré, France
2016-11-10
We sought to estimate the extent of decision regret among primary care patients and identify risk factors associated with regret. Secondary analysis of an observational descriptive study conducted in two Canadian provinces. Unique patient-physician dyads were recruited from 17 primary care clinics and data on patient, physician and consultation characteristics were collected before, during and immediately after consultations, as well as two weeks post-consultation, when patients completed the Decision Regret Scale (DRS). We examined the DRS score distribution and performed ordinal logistic regression analysis to identify predictors of regret. Among 258 unique patient-physicians dyads, mean ± standard deviation of decision regret scores was 11.7 ± 15.1 out of 100. Overall, 43 % of patients reported no regret, 45 % reported mild regret and 12 % reported moderate to strong regret. In multivariate analyses, higher decision regret was strongly associated with increased decisional conflict and less significantly associated with patient age and education, as well with male (vs. female) physicians and residents (vs. teachers). After consulting family physicians, most primary care patients experience little decision regret, but some experience more regret if there is decisional conflict. Strategies for reducing decisional conflict in primary care, such as shared decision-making with decision aids, seem warranted.
Problems and Processes in Medical Encounters: The CASES method of dialogue analysis
Laws, M. Barton; Taubin, Tatiana; Bezreh, Tanya; Lee, Yoojin; Beach, Mary Catherine; Wilson, Ira B.
2013-01-01
Objective To develop methods to reliably capture structural and dynamic temporal features of clinical interactions. Methods Observational study of 50 audio-recorded routine outpatient visits to HIV specialty clinics, using innovative analytic methods. The Comprehensive Analysis of the Structure of Encounters System (CASES) uses transcripts coded for speech acts, then imposes larger-scale structural elements: threads – the problems or issues addressed; and processes within threads –basic tasks of clinical care labeled Presentation, Information, Resolution (decision making) and Engagement (interpersonal exchange). Threads are also coded for the nature of resolution. Results 61% of utterances are in presentation processes. Provider verbal dominance is greatest in information and resolution processes, which also contain a high proportion of provider directives. About half of threads result in no action or decision. Information flows predominantly from patient to provider in presentation processes, and from provider to patient in information processes. Engagement is rare. Conclusions In this data, resolution is provider centered; more time for patient participation in resolution, or interpersonal engagement, would have to come from presentation. Practice Implications Awareness of the use of time in clinical encounters, and the interaction processes associated with various tasks, may help make clinical communication more efficient and effective. PMID:23391684
Problems and processes in medical encounters: the cases method of dialogue analysis.
Laws, M Barton; Taubin, Tatiana; Bezreh, Tanya; Lee, Yoojin; Beach, Mary Catherine; Wilson, Ira B
2013-05-01
To develop methods to reliably capture structural and dynamic temporal features of clinical interactions. Observational study of 50 audio-recorded routine outpatient visits to HIV specialty clinics, using innovative analytic methods. The comprehensive analysis of the structure of encounters system (CASES) uses transcripts coded for speech acts, then imposes larger-scale structural elements: threads--the problems or issues addressed; and processes within threads--basic tasks of clinical care labeled presentation, information, resolution (decision making) and Engagement (interpersonal exchange). Threads are also coded for the nature of resolution. 61% of utterances are in presentation processes. Provider verbal dominance is greatest in information and resolution processes, which also contain a high proportion of provider directives. About half of threads result in no action or decision. Information flows predominantly from patient to provider in presentation processes, and from provider to patient in information processes. Engagement is rare. In this data, resolution is provider centered; more time for patient participation in resolution, or interpersonal engagement, would have to come from presentation. Awareness of the use of time in clinical encounters, and the interaction processes associated with various tasks, may help make clinical communication more efficient and effective. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.
Makhni, Eric C; Lamba, Nayan; Swart, Eric; Steinhaus, Michael E; Ahmad, Christopher S; Romeo, Anthony A; Verma, Nikhil N
2016-09-01
To compare the cost-effectiveness of arthroscopic revision instability repair and Latarjet procedure in treating patients with recurrent instability after initial arthroscopic instability repair. An expected-value decision analysis of revision arthroscopic instability repair compared with Latarjet procedure for recurrent instability followed by failed repair attempt was modeled. Inputs regarding procedure cost, clinical outcomes, and health utilities were derived from the literature. Compared with revision arthroscopic repair, Latarjet was less expensive ($13,672 v $15,287) with improved clinical outcomes (43.78 v 36.76 quality-adjusted life-years). Both arthroscopic repair and Latarjet were cost-effective compared with nonoperative treatment (incremental cost-effectiveness ratios of 3,082 and 1,141, respectively). Results from sensitivity analyses indicate that under scenarios of high rates of stability postoperatively, along with improved clinical outcome scores, revision arthroscopic repair becomes increasingly cost-effective. Latarjet procedure for failed instability repair is a cost-effective treatment option, with lower costs and improved clinical outcomes compared with revision arthroscopic instability repair. However, surgeons must still incorporate clinical judgment into treatment algorithm formation. Level IV, expected value decision analysis. Copyright © 2016. Published by Elsevier Inc.
Kohli, R; Tan, J K; Piontek, F A; Ziege, D E; Groot, H
1999-08-01
Changes in health care delivery, reimbursement schemes, and organizational structure have required health organizations to manage the costs of providing patient care while maintaining high levels of clinical and patient satisfaction outcomes. Today, cost information, clinical outcomes, and patient satisfaction results must become more fully integrated if strategic competitiveness and benefits are to be realized in health management decision making, especially in multi-entity organizational settings. Unfortunately, traditional administrative and financial systems are not well equipped to cater to such information needs. This article presents a framework for the acquisition, generation, analysis, and reporting of cost information with clinical outcomes and patient satisfaction in the context of evolving health management and decision-support system technology. More specifically, the article focuses on an enhanced costing methodology for determining and producing improved, integrated cost-outcomes information. Implementation issues and areas for future research in cost-information management and decision-support domains are also discussed.
Kunkler, I H; Prescott, R J; Lee, R J; Brebner, J A; Cairns, J A; Fielding, R G; Bowman, A; Neades, G; Walls, A D F; Chetty, U; Dixon, J M; Smith, M E; Gardner, T W; Macnab, M; Swann, S; Maclean, J R
2007-11-01
The TELEMAM trial aimed to assess the clinical effectiveness and costs of telemedicine in conducting breast cancer multi-disciplinary meetings (MDTs). Over 12 months 473 MDT patient discussions in two district general hospitals (DGHs) were cluster randomised (2:1) to the intervention of telemedicine linkage to breast specialists in a cancer centre or to the control group of 'in-person' meetings. Primary endpoints were clinical effectiveness and costs. Economic analysis was based on a cost-minimisation approach. Levels of agreement of MDT members on a scale from 1 to 5 were high and similar in both the telemedicine and standard meetings for decision sharing (4.04 versus 4.17), consensus (4.06 versus 4.20) and confidence in the decision (4.16 versus 4.07). The threshold at which the telemedicine meetings became cheaper than standard MDTs was approximately 40 meetings per year. Telemedicine delivered breast cancer multi-disciplinary meetings have similar clinical effectiveness to standard 'in-person' meetings.
Martins Pereira, Sandra; Fradique, Emília; Hernández-Marrero, Pablo
2018-05-01
End-of-life decisions (ELDs) are embedded in clinical, sociocultural, political, economic, and ethical concerns. In 2014, the Council of Europe (CoE) through its Committee on Bioethics launched the "Guide on the decision-making process regarding medical treatment in end-of-life situations," aiming at improving decision-making processes and empowering professionals in making ELDs. To analyze if end-of-life decision making in palliative care (PC) is consistent with this Guide and to identify if disputed/controversial issues are part of current ELDs. Qualitative secondary analysis. Four qualitative datasets, including 44 interviews and 9 team observation field notes from previous studies with PC teams/professionals in Portugal. An analysis grid based on the abovementioned guide was created considering three dimensions: ethical and legal frameworks, decision-making process, and disputed/controversial issues. The majority of the professionals considered the ethical principle of autonomy paramount in end-of-life decision making. Justice and beneficence/nonmaleficence were also valued. Although not mentioned in the Guide, the professionals also considered other ethical principles when making ELDs, namely, responsibility, integrity, and dignity. Most of the interviewees and field notes referred to the collective interprofessional dimension of the decision-making process. Palliative sedation and the wish to hasten death were the most mentioned disputed/controversial issues. The nature, limitations, and benefits of qualitative secondary analysis are discussed. End-of-life decision-making processes made by Portuguese PC teams seem to be consistent with the guidelines of the CoE. Further research is needed about disputed/controversial issues and the actual use, effectiveness, and impact of ethical guidelines for end-of-life decision making on professionals' empowerment and for all parties involved.
Melnick, Edward R.; Lopez, Kevin; Hess, Erik P.; Abujarad, Fuad; Brandt, Cynthia A.; Shiffman, Richard N.; Post, Lori A.
2015-01-01
Context: Current information-rich electronic health record (EHR) interfaces require large, high-resolution screens running on desktop computers. This interface compromises the provider’s already limited time at the bedside by physically separating the patient from the doctor. The case study presented here describes a patient-centered clinical decision support (CDS) design process that aims to bring the physician back to the bedside by integrating a patient decision aid with CDS for shared use by the patient and provider on a touchscreen tablet computer for deciding whether or not to obtain a CT scan for minor head injury in the emergency department, a clinical scenario that could benefit from CDS but has failed previous implementation attempts. Case Description: This case study follows the user-centered design (UCD) approach to build a bedside aid that is useful and usable, and that promotes shared decision-making between patients and their providers using a tablet computer at the bedside. The patient-centered decision support design process focuses on the prototype build using agile software development, but also describes the following: (1) the requirement gathering phase including triangulated qualitative research (focus groups and cognitive task analysis) to understand current challenges, (2) features for patient education, the physician, and shared decision-making, (3) system architecture and technical requirements, and (4) future plans for formative usability testing and field testing. Lessons Learned: We share specific lessons learned and general recommendations from critical insights gained in the patient-centered decision support design process about early stakeholder engagement, EHR integration, external expert feedback, challenges to two users on a single device, project management, and accessibility. Conclusions: Successful implementation of this tool will require seamless integration into the provider’s workflow. This protocol can create an effective interface for shared decision-making and safe resource reduction at the bedside in the austere and dynamic clinical environment of the ED and is generalizable for these purposes in other clinical environments as well. PMID:26290885
Melnick, Edward R; Lopez, Kevin; Hess, Erik P; Abujarad, Fuad; Brandt, Cynthia A; Shiffman, Richard N; Post, Lori A
2015-01-01
Current information-rich electronic health record (EHR) interfaces require large, high-resolution screens running on desktop computers. This interface compromises the provider's already limited time at the bedside by physically separating the patient from the doctor. The case study presented here describes a patient-centered clinical decision support (CDS) design process that aims to bring the physician back to the bedside by integrating a patient decision aid with CDS for shared use by the patient and provider on a touchscreen tablet computer for deciding whether or not to obtain a CT scan for minor head injury in the emergency department, a clinical scenario that could benefit from CDS but has failed previous implementation attempts. This case study follows the user-centered design (UCD) approach to build a bedside aid that is useful and usable, and that promotes shared decision-making between patients and their providers using a tablet computer at the bedside. The patient-centered decision support design process focuses on the prototype build using agile software development, but also describes the following: (1) the requirement gathering phase including triangulated qualitative research (focus groups and cognitive task analysis) to understand current challenges, (2) features for patient education, the physician, and shared decision-making, (3) system architecture and technical requirements, and (4) future plans for formative usability testing and field testing. We share specific lessons learned and general recommendations from critical insights gained in the patient-centered decision support design process about early stakeholder engagement, EHR integration, external expert feedback, challenges to two users on a single device, project management, and accessibility. Successful implementation of this tool will require seamless integration into the provider's workflow. This protocol can create an effective interface for shared decision-making and safe resource reduction at the bedside in the austere and dynamic clinical environment of the ED and is generalizable for these purposes in other clinical environments as well.
Krieger, Janice L; Krok-Schoen, Jessica L; Dailey, Phokeng M; Palmer-Wackerly, Angela L; Schoenberg, Nancy; Paskett, Electra D; Dignan, Mark
2017-07-01
Distributed cognition occurs when cognitive and affective schemas are shared between two or more people during interpersonal discussion. Although extant research focuses on distributed cognition in decision making between health care providers and patients, studies show that caregivers are also highly influential in the treatment decisions of patients. However, there are little empirical data describing how and when families exert influence. The current article addresses this gap by examining decisional support in the context of cancer randomized clinical trial (RCT) decision making. Data are drawn from in-depth interviews with rural, Appalachian cancer patients ( N = 46). Analysis of transcript data yielded empirical support for four distinct models of health decision making. The implications of these findings for developing interventions to improve the quality of treatment decision making and overall well-being are discussed.
Postlethwaite, R J; Reynolds, J M; Wood, A J; Evans, J H; Lewis, M A; Eminson, D M
1995-07-01
Issues raised by the recruitment of children to trials of growth hormone treatment for short stature in chronic renal failure are reported. Information needs of parents and children are discussed, the latter should take account of the children's developmental level and anticipated involvement in decision making. When the incidence of certain side effects is low and probably unquantifiable there are particular problems; failure to include these in information sheets may compromise informed consent but inclusion will, at least for some families, make an already difficult decision even more complicated. A process of recruitment is described which attempts to protect against bias and which balances the requirement to impart neutral information with appropriate clinical involvement in the decision to enter the study. Other functions of the recruitment process are identified. Analysis of understanding and decision making demonstrates that good understanding is neither necessary nor sufficient for ease of decision making. The recruitment process was time consuming and needs planning and funding in future studies. Many of these issues are of general importance for trials of treatment in children.
A review of costing methodologies in critical care studies.
Pines, Jesse M; Fager, Samuel S; Milzman, David P
2002-09-01
Clinical decision making in critical care has traditionally been based on clinical outcome measures such as mortality and morbidity. Over the past few decades, however, increasing competition in the health care marketplace has made it necessary to consider costs when making clinical and managerial decisions in critical care. Sophisticated costing methodologies have been developed to aid this decision-making process. We performed a narrative review of published costing studies in critical care during the past 6 years. A total of 282 articles were found, of which 68 met our search criteria. They involved a mean of 508 patients (range, 20-13,907). A total of 92.6% of the studies (63 of 68) used traditional cost analysis, whereas the remaining 7.4% (5 of 68) used cost-effectiveness analysis. None (0 of 68) used cost-benefit analysis or cost-utility analysis. A total of 36.7% (25 of 68) used hospital charges as a surrogate for actual costs. Of the 43 articles that actually counted costs, 37.2% (16 of 43) counted physician costs, 27.9% (12 of 43) counted facility costs, 34.9% (15 of 43) counted nursing costs, 9.3% (4 of 43) counted societal costs, and 90.7% (39 of 43) counted laboratory, equipment, and pharmacy costs. Our conclusion is that despite considerable progress in costing methodologies, critical care studies have not adequately implemented these techniques. Given the importance of financial implications in medicine, it would be prudent for critical care studies to use these more advanced techniques. Copyright 2002, Elsevier Science (USA). All rights reserved.
Saposnik, Gustavo; Johnston, S Claiborne
2016-04-01
Acute stroke care represents a challenge for decision makers. Decisions based on erroneous assessments may generate false expectations of patients and their family members, and potentially inappropriate medical advice. Game theory is the analysis of interactions between individuals to study how conflict and cooperation affect our decisions. We reviewed principles of game theory that could be applied to medical decisions under uncertainty. Medical decisions in acute stroke care are usually made under constrains: short period of time, with imperfect clinical information, limit understanding about patients and families' values and beliefs. Game theory brings some strategies to help us manage complex medical situations under uncertainty. For example, it offers a different perspective by encouraging the consideration of different alternatives through the understanding of patients' preferences and the careful evaluation of cognitive distortions when applying 'real-world' data. The stag-hunt game teaches us the importance of trust to strength cooperation for a successful patient-physician interaction that is beyond a good or poor clinical outcome. The application of game theory to stroke care may improve our understanding of complex medical situations and help clinicians make practical decisions under uncertainty. © 2016 World Stroke Organization.
Observational Research Opportunities and Limitations
Boyko, Edward J.
2013-01-01
Medical research continues to progress in its ability to identify treatments and characteristics associated with benefits and adverse outcomes. The principle engine for the evaluation of treatment efficacy is the randomized controlled trial (RCT). Due to the cost and other considerations, RCTs cannot address all clinically important decisions. Observational research often is used to address issues not addressed or not addressable by RCTs. This article provides an overview of the benefits and limitations of observational research to serve as a guide to the interpretation of this category of research designs in diabetes investigations. The potential for bias is higher in observational research but there are design and analysis features that can address these concerns although not completely eliminate them. Pharmacoepidemiologic research may provide important information regarding relative safety and effectiveness of diabetes pharmaceuticals. Such research must effectively address the important issue of confounding by indication in order to produce clinically meaningful results. Other methods such as instrumental variable analysis are being employed to enable stronger causal inference but these methods also require fulfillment of several key assumptions that may or may not be realistic. Nearly all clinical decisions involve probabilistic reasoning and confronting uncertainly, so a realistic goal for observational research may not be the high standard set by RCTs but instead the level of certainty needed to influence a diagnostic or treatment decision. PMID:24055326
Observational research--opportunities and limitations.
Boyko, Edward J
2013-01-01
Medical research continues to progress in its ability to identify treatments and characteristics associated with benefits and adverse outcomes. The principal engine for the evaluation of treatment efficacy is the randomized controlled trial (RCT). Due to the cost and other considerations, RCTs cannot address all clinically important decisions. Observational research often is used to address issues not addressed or not addressable by RCTs. This article provides an overview of the benefits and limitations of observational research to serve as a guide to the interpretation of this category of research designs in diabetes investigations. The potential for bias is higher in observational research but there are design and analysis features that can address these concerns although not completely eliminate them. Pharmacoepidemiologic research may provide important information regarding relative safety and effectiveness of diabetes pharmaceuticals. Such research must effectively address the important issue of confounding by indication in order to produce clinically meaningful results. Other methods such as instrumental variable analysis are being employed to enable stronger causal inference but these methods also require fulfillment of several key assumptions that may or may not be realistic. Nearly all clinical decisions involve probabilistic reasoning and confronting uncertainly, so a realistic goal for observational research may not be the high standard set by RCTs but instead the level of certainty needed to influence a diagnostic or treatment decision. © 2013.
Future of electronic health records: implications for decision support.
Rothman, Brian; Leonard, Joan C; Vigoda, Michael M
2012-01-01
The potential benefits of the electronic health record over traditional paper are many, including cost containment, reductions in errors, and improved compliance by utilizing real-time data. The highest functional level of the electronic health record (EHR) is clinical decision support (CDS) and process automation, which are expected to enhance patient health and healthcare. The authors provide an overview of the progress in using patient data more efficiently and effectively through clinical decision support to improve health care delivery, how decision support impacts anesthesia practice, and how some are leading the way using these systems to solve need-specific issues. Clinical decision support uses passive or active decision support to modify clinician behavior through recommendations of specific actions. Recommendations may reduce medication errors, which would result in considerable savings by avoiding adverse drug events. In selected studies, clinical decision support has been shown to decrease the time to follow-up actions, and prediction has proved useful in forecasting patient outcomes, avoiding costs, and correctly prompting treatment plan modifications by clinicians before engaging in decision-making. Clinical documentation accuracy and completeness is improved by an electronic health record and greater relevance of care data is delivered. Clinical decision support may increase clinician adherence to clinical guidelines, but educational workshops may be equally effective. Unintentional consequences of clinical decision support, such as alert desensitization, can decrease the effectiveness of a system. Current anesthesia clinical decision support use includes antibiotic administration timing, improved documentation, more timely billing, and postoperative nausea and vomiting prophylaxis. Electronic health record implementation offers data-mining opportunities to improve operational, financial, and clinical processes. Using electronic health record data in real-time for decision support and process automation has the potential to both reduce costs and improve the quality of patient care. © 2012 Mount Sinai School of Medicine.
Rittman, Timothy; Nombela, Cristina; Fois, Alessandro; Coyle-Gilchrist, Ian; Barker, Roger A.; Hughes, Laura E.; Rowe, James B.
2016-01-01
Abstract Progressive supranuclear palsy and Parkinson’s disease have distinct underlying neuropathology, but both diseases affect cognitive function in addition to causing a movement disorder. They impair response inhibition and may lead to impulsivity, which can occur even in the presence of profound akinesia and rigidity. The current study examined the mechanisms of cognitive impairments underlying disinhibition, using horizontal saccadic latencies that obviate the impact of limb slowness on executing response decisions. Nineteen patients with clinically diagnosed progressive supranuclear palsy (Richardson’s syndrome), 24 patients with clinically diagnosed Parkinson’s disease and 26 healthy control subjects completed a saccadic Go/No-Go task with a head-mounted infrared saccadometer. Participants were cued on each trial to make a pro-saccade to a horizontal target or withhold their responses. Both patient groups had impaired behavioural performance, with more commission errors than controls. Mean saccadic latencies were similar between all three groups. We analysed behavioural responses as a binary decision between Go and No-Go choices. By using Bayesian parameter estimation, we fitted a hierarchical drift–diffusion model to individual participants’ single trial data. The model decomposes saccadic latencies into parameters for the decision process: decision boundary, drift rate of accumulation, decision bias, and non-decision time. In a leave-one-out three-way classification analysis, the model parameters provided better discrimination between patients and controls than raw behavioural measures. Furthermore, the model revealed disease-specific deficits in the Go/No-Go decision process. Both patient groups had slower drift rate of accumulation, and shorter non-decision time than controls. But patients with progressive supranuclear palsy were strongly biased towards a pro-saccade decision boundary compared to Parkinson’s patients and controls. This indicates a prepotency of responding in combination with a reduction in further accumulation of evidence, which provides a parsimonious explanation for the apparently paradoxical combination of disinhibition and severe akinesia. The combination of the well-tolerated oculomotor paradigm and the sensitivity of the model-based analysis provides a valuable approach for interrogating decision-making processes in neurodegenerative disorders. The mechanistic differences underlying participants’ poor performance were not observable from classical analysis of behavioural data, but were clearly revealed by modelling. These differences provide a rational basis on which to develop and assess new therapeutic strategies for cognition and behaviour in these disorders. PMID:26582559
Zhang, Jiaxiang; Rittman, Timothy; Nombela, Cristina; Fois, Alessandro; Coyle-Gilchrist, Ian; Barker, Roger A; Hughes, Laura E; Rowe, James B
2016-01-01
Progressive supranuclear palsy and Parkinson's disease have distinct underlying neuropathology, but both diseases affect cognitive function in addition to causing a movement disorder. They impair response inhibition and may lead to impulsivity, which can occur even in the presence of profound akinesia and rigidity. The current study examined the mechanisms of cognitive impairments underlying disinhibition, using horizontal saccadic latencies that obviate the impact of limb slowness on executing response decisions. Nineteen patients with clinically diagnosed progressive supranuclear palsy (Richardson's syndrome), 24 patients with clinically diagnosed Parkinson's disease and 26 healthy control subjects completed a saccadic Go/No-Go task with a head-mounted infrared saccadometer. Participants were cued on each trial to make a pro-saccade to a horizontal target or withhold their responses. Both patient groups had impaired behavioural performance, with more commission errors than controls. Mean saccadic latencies were similar between all three groups. We analysed behavioural responses as a binary decision between Go and No-Go choices. By using Bayesian parameter estimation, we fitted a hierarchical drift-diffusion model to individual participants' single trial data. The model decomposes saccadic latencies into parameters for the decision process: decision boundary, drift rate of accumulation, decision bias, and non-decision time. In a leave-one-out three-way classification analysis, the model parameters provided better discrimination between patients and controls than raw behavioural measures. Furthermore, the model revealed disease-specific deficits in the Go/No-Go decision process. Both patient groups had slower drift rate of accumulation, and shorter non-decision time than controls. But patients with progressive supranuclear palsy were strongly biased towards a pro-saccade decision boundary compared to Parkinson's patients and controls. This indicates a prepotency of responding in combination with a reduction in further accumulation of evidence, which provides a parsimonious explanation for the apparently paradoxical combination of disinhibition and severe akinesia. The combination of the well-tolerated oculomotor paradigm and the sensitivity of the model-based analysis provides a valuable approach for interrogating decision-making processes in neurodegenerative disorders. The mechanistic differences underlying participants' poor performance were not observable from classical analysis of behavioural data, but were clearly revealed by modelling. These differences provide a rational basis on which to develop and assess new therapeutic strategies for cognition and behaviour in these disorders. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain.
Jefford, Elaine; Fahy, Kathleen; Sundin, Deborah
2011-06-01
What are the strengths and limitations of existing Decision-Making Theories as a basis for guiding best practice clinical decision-making within a framework of midwifery philosophy? Each theory is compared in relation with how well they provide a teachable framework for midwifery clinical reasoning that is consistent with midwifery philosophy. Hypothetico-Deductive Theory, from which medical clinical reasoning is based; intuitive decision-making; Dual Processing Theory; The International Confederation of Midwives Clinical Decision-Making Framework; Australian Nursing and Midwifery Council Midwifery Practice Decisions Flowchart and Midwifery Practice. Best practice midwifery clinical Decision-Making Theory needs to give guidance about: (i) effective use of cognitive reasoning processes; (ii) how to include contextual and emotional factors; (iii) how to include the interests of the baby as an integral part of the woman; (iv) decision-making in partnership with woman; and (v) how to recognize/respond to clinical situations outside the midwife's legal/personal scope of practice. No existing Decision-Making Theory meets the needs of midwifery. Medical clinical reasoning has a good contribution to make in terms of cognitive reasoning processes. Two limitations of medical clinical reasoning are its reductionistic focus and privileging of reason to the exclusion of emotional and contextual factors. Hypothetico-deductive clinical reasoning is a necessary but insufficient condition for best practice clinical decision-making in midwifery. © 2011 Blackwell Publishing Asia Pty Ltd.
"In the physio we trust": A qualitative study on patients' preferences for physiotherapy.
Bernhardsson, Susanne; Larsson, Maria E H; Johansson, Kajsa; Öberg, Birgitta
2017-07-01
Patients' preferences should be integrated in evidence-based practice. This study aimed to explore patients' preferences for physiotherapy treatment and participation in decision making. A qualitative study set in an urban physiotherapy clinic in Gothenburg, Sweden. Individual, semi-structured interviews were conducted with 20 individuals who sought physiotherapy for musculoskeletal disorders. The interviews were recorded, transcribed, and analyzed with qualitative content analysis. An overarching theme, embracing six categories, was conceptualized: Trust in the physiotherapist fosters active engagement in therapy. The participants preferred active treatment strategies such as exercise and advice for self-management, allowing them to actively engage in their therapy. Some preferred passive treatments. Key influencers on treatment preferences were previous experiences and media. All participants wanted to be involved in the clinical decision making, but to varying extents. Some expressed a preference for an active role and wanting to share decisions while others were content with a passive role. Expectations for a professional management were reflected in trust and confidence in physiotherapists' skills and competence, expectations for good outcomes, and believing that treatment methods should be evidence-based. Trust in the physiotherapist's competence, as well as a desire to participate in clinical decision making, fosters active engagement in physiotherapy.
Factors and outcomes of decision making for cancer clinical trial participation.
Biedrzycki, Barbara A
2011-09-01
To describe factors and outcomes related to the decision-making process regarding participation in a cancer clinical trial. Cross-sectional, descriptive. Urban, academic, National Cancer Institute-designated comprehensive cancer center in the mid-Atlantic United States. 197 patients with advanced gastrointestinal cancer. Mailed survey using one investigator-developed instrument, eight instruments used in published research, and a medical record review. disease context, sociodemographics, hope, quality of life, trust in healthcare system, trust in health professional, preference for research decision control, understanding risks, and information. decision to accept or decline research participation and satisfaction with this decision. All of the factors within the Research Decision Making Model together predicted cancer clinical trial participation and satisfaction with this decision. The most frequently preferred decision-making style for research participation was shared (collaborative) (83%). Multiple factors affect decision making for cancer clinical trial participation and satisfaction with this decision. Shared decision making previously was an unrecognized factor and requires further investigation. Enhancing the process of research decision making may facilitate an increase in cancer clinical trial enrollment rates. Oncology nurses have unique opportunities as educators and researchers to support shared decision making by those who prefer this method for deciding whether to accept or decline cancer clinical trial participation.
Zuchowski, Jessica L; Hamilton, Alison B; Pyne, Jeffrey M; Clark, Jack A; Naik, Aanand D; Smith, Donna L; Kanwal, Fasiha
2015-10-01
In this era of a constantly changing landscape of antiviral treatment options for chronic viral hepatitis C (CHC), shared clinical decision-making addresses the need to engage patients in complex treatment decisions. However, little is known about the decision attributes that CHC patients consider when making treatment decisions. We identify key patient-centered decision attributes, and explore relationships among these attributes, to help inform the development of a future CHC shared decision-making aid. Semi-structured qualitative interviews with CHC patients at four Veterans Health Administration (VHA) hospitals, in three comparison groups: contemplating CHC treatment at the time of data collection (Group 1), recently declined CHC treatment (Group 2), or recently started CHC treatment (Group 3). Participant descriptions of decision attributes were analyzed for the entire sample as well as by patient group and by gender. Twenty-nine Veteran patients participated (21 males, eight females): 12 were contemplating treatment, nine had recently declined treatment, and eight had recently started treatment. Patients on average described eight (range 5-13) decision attributes. The attributes most frequently reported overall were: physical side effects (83%); treatment efficacy (79%), new treatment drugs in development (55%); psychological side effects (55%); and condition of the liver (52%), with some variation based on group and gender. Personal life circumstance attributes (such as availability of family support and the burden of financial responsibilities) influencing treatment decisions were also noted by all participants. Multiple decision attributes were interrelated in highly complex ways. Participants considered numerous attributes in their CHC treatment decisions. A better understanding of these attributes that influence patient decision-making is crucial in order to inform patient-centered clinical approaches to care (such as shared decision-making augmented with relevant decision-making aids) that respond to patients' needs, preferences, and circumstances.
Lipstein, Ellen A; Britto, Maria T
2015-08-01
In the context of pediatric chronic conditions, patients and families are called upon repeatedly to make treatment decisions. However, little is known about how their decision making evolves over time. The objective was to understand parents' processes for treatment decision making in pediatric chronic conditions. We conducted a qualitative, prospective longitudinal study using recorded clinic visits and individual interviews. After consent was obtained from health care providers, parents, and patients, clinic visits during which treatment decisions were expected to be discussed were video-recorded. Parents then participated in sequential telephone interviews about their decision-making experience. Data were coded by 2 people and analyzed using framework analysis with sequential, time-ordered matrices. 21 families, including 29 parents, participated in video-recording and interviews. We found 3 dominant patterns of decision evolution. Each consisted of a series of decision events, including conversations, disease flares, and researching of treatment options. Within all 3 patterns there were both constant and evolving elements of decision making, such as role perceptions and treatment expectations, respectively. After parents made a treatment decision, they immediately turned to the next decision related to the chronic condition, creating an iterative cycle. In this study, decision making was an iterative process occurring in 3 distinct patterns. Understanding these patterns and the varying elements of parents' decision processes is an essential step toward developing interventions that are appropriate to the setting and that capitalize on the skills families may develop as they gain experience with a chronic condition. Future research should also consider the role of children and adolescents in this decision process. © The Author(s) 2015.
The stakeholder approach: a new perspective on developing and marketing clinical trials.
Droms, Courtney M; Ferguson, Michael; Giuliano, Karen
2014-01-01
The use of evidence-based medical practice has become the standard for health care decision-making. Thus, it has become increasingly important for medical device manufactures to provide evidence for the efficacy of their products. As new products, services, and solutions are developed, it is important to perform a stakeholder analysis to assess clinical evidence needs. As evidenced by the variety of stakeholders in clinical trials, we expect that each has different interests in how clinical trials are developed, conducted, and promoted to the general public. This analysis of the stakeholders' concerns provides recommendations for marketing professionals on meeting the needs of these stakeholders.
Clinical decision-making and secondary findings in systems medicine.
Fischer, T; Brothers, K B; Erdmann, P; Langanke, M
2016-05-21
Systems medicine is the name for an assemblage of scientific strategies and practices that include bioinformatics approaches to human biology (especially systems biology); "big data" statistical analysis; and medical informatics tools. Whereas personalized and precision medicine involve similar analytical methods applied to genomic and medical record data, systems medicine draws on these as well as other sources of data. Given this distinction, the clinical translation of systems medicine poses a number of important ethical and epistemological challenges for researchers working to generate systems medicine knowledge and clinicians working to apply it. This article focuses on three key challenges: First, we will discuss the conflicts in decision-making that can arise when healthcare providers committed to principles of experimental medicine or evidence-based medicine encounter individualized recommendations derived from computer algorithms. We will explore in particular whether controlled experiments, such as comparative effectiveness trials, should mediate the translation of systems medicine, or if instead individualized findings generated through "big data" approaches can be applied directly in clinical decision-making. Second, we will examine the case of the Riyadh Intensive Care Program Mortality Prediction Algorithm, pejoratively referred to as the "death computer," to demonstrate the ethical challenges that can arise when big-data-driven scoring systems are applied in clinical contexts. We argue that the uncritical use of predictive clinical algorithms, including those envisioned for systems medicine, challenge basic understandings of the doctor-patient relationship. Third, we will build on the recent discourse on secondary findings in genomics and imaging to draw attention to the important implications of secondary findings derived from the joint analysis of data from diverse sources, including data recorded by patients in an attempt to realize their "quantified self." This paper examines possible ethical challenges that are likely to be raised as systems medicine to be translated into clinical medicine. These include the epistemological challenges for clinical decision-making, the use of scoring systems optimized by big data techniques and the risk that incidental and secondary findings will significantly increase. While some ethical implications remain still hypothetical we should use the opportunity to prospectively identify challenges to avoid making foreseeable mistakes when systems medicine inevitably arrives in routine care.
Colorectal cancer patients’ attitudes towards involvement in decision making
Beaver, Kinta; Campbell, Malcolm; Craven, Olive; Jones, David; Luker, Karen A.; Susnerwala, Shabbir S.
2009-01-01
Abstract Objectives To design and administer an attitude rating scale, exploring colorectal cancer patients’ views of involvement in decision making. To examine the impact of socio‐demographic and/or treatment‐related factors on decision making. To conduct principal components analysis to determine if the scale could be simplified into a number of factors for future clinical utility. Methods An attitude rating scale was constructed based on previous qualitative work and administered to colorectal cancer patients using a cross‐sectional survey approach. Results 375 questionnaires were returned (81.7% response). For patients it was important to be informed and involved in the decision‐making process. Information was not always used to make decisions as patients placed their trust in medical expertise. Women had more positive opinions on decision making and were more likely to want to make decisions. Written information was understood to a greater degree than verbal information. The scale could be simplified to a number of factors, indicating clinical utility. Conclusion Few studies have explored the attitudes of colorectal cancer patients towards involvement in decision making. This study presents new insights into how patients view the concept of participation; important when considering current policy imperatives in the UK of involving service users in all aspects of care and treatment. PMID:19250150
Creating and sharing clinical decision support content with Web 2.0: Issues and examples.
Wright, Adam; Bates, David W; Middleton, Blackford; Hongsermeier, Tonya; Kashyap, Vipul; Thomas, Sean M; Sittig, Dean F
2009-04-01
Clinical decision support is a powerful tool for improving healthcare quality and patient safety. However, developing a comprehensive package of decision support interventions is costly and difficult. If used well, Web 2.0 methods may make it easier and less costly to develop decision support. Web 2.0 is characterized by online communities, open sharing, interactivity and collaboration. Although most previous attempts at sharing clinical decision support content have worked outside of the Web 2.0 framework, several initiatives are beginning to use Web 2.0 to share and collaborate on decision support content. We present case studies of three efforts: the Clinfowiki, a world-accessible wiki for developing decision support content; Partners Healthcare eRooms, web-based tools for developing decision support within a single organization; and Epic Systems Corporation's Community Library, a repository for sharing decision support content for customers of a single clinical system vendor. We evaluate the potential of Web 2.0 technologies to enable collaborative development and sharing of clinical decision support systems through the lens of three case studies; analyzing technical, legal and organizational issues for developers, consumers and organizers of clinical decision support content in Web 2.0. We believe the case for Web 2.0 as a tool for collaborating on clinical decision support content appears strong, particularly for collaborative content development within an organization.
Health professionals' decision-making in wound management: a grounded theory.
Gillespie, Brigid M; Chaboyer, Wendy; St John, Winsome; Morley, Nicola; Nieuwenhoven, Paul
2015-06-01
To develop a conceptual understanding of the decision-making processes used by healthcare professionals in wound care practice. With the global move towards using an evidence-base in standardizing wound care practices and the need to reduce hospital wound care costs, it is important to understand health professionals' decision-making in this important yet under-researched area. A grounded theory approach was used to explore clinical decision-making of healthcare professionals in wound care practice. Interviews were conducted with 20 multi-disciplinary participants from nursing, surgery, infection control and wound care who worked at a metropolitan hospital in Australia. Data were collected during 2012-2013. Constant comparative analysis underpinned by Strauss and Corbin's framework was used to identify clinical decision-making processes. The core category was 'balancing practice-based knowledge with evidence-based knowledge'. Participants' clinical practice and actions embedded the following processes: 'utilizing the best available information', 'using a consistent approach in wound assessment' and 'using a multidisciplinary approach'. The substantive theory explains how practice and evidence knowledge was balanced and the variation in use of intuitive practice-based knowledge versus evidence-based knowledge. Participants considered patients' needs and preferences, costs, outcomes, technologies, others' expertise and established practices. Participants' decision-making tended to be more heavily weighted towards intuitive practice-based processes. These findings offer a better understanding of the processes used by health professionals' in their decision-making in wound care. Such an understanding may inform the development of evidence-based interventions that lead to better patient outcomes. © 2014 John Wiley & Sons Ltd.
Application and Exploration of Big Data Mining in Clinical Medicine.
Zhang, Yue; Guo, Shu-Li; Han, Li-Na; Li, Tie-Ling
2016-03-20
To review theories and technologies of big data mining and their application in clinical medicine. Literatures published in English or Chinese regarding theories and technologies of big data mining and the concrete applications of data mining technology in clinical medicine were obtained from PubMed and Chinese Hospital Knowledge Database from 1975 to 2015. Original articles regarding big data mining theory/technology and big data mining's application in the medical field were selected. This review characterized the basic theories and technologies of big data mining including fuzzy theory, rough set theory, cloud theory, Dempster-Shafer theory, artificial neural network, genetic algorithm, inductive learning theory, Bayesian network, decision tree, pattern recognition, high-performance computing, and statistical analysis. The application of big data mining in clinical medicine was analyzed in the fields of disease risk assessment, clinical decision support, prediction of disease development, guidance of rational use of drugs, medical management, and evidence-based medicine. Big data mining has the potential to play an important role in clinical medicine.
Stakeholder perspectives on decision-analytic modeling frameworks to assess genetic services policy.
Guzauskas, Gregory F; Garrison, Louis P; Stock, Jacquie; Au, Sylvia; Doyle, Debra Lochner; Veenstra, David L
2013-01-01
Genetic services policymakers and insurers often make coverage decisions in the absence of complete evidence of clinical utility and under budget constraints. We evaluated genetic services stakeholder opinions on the potential usefulness of decision-analytic modeling to inform coverage decisions, and asked them to identify genetic tests for decision-analytic modeling studies. We presented an overview of decision-analytic modeling to members of the Western States Genetic Services Collaborative Reimbursement Work Group and state Medicaid representatives and conducted directed content analysis and an anonymous survey to gauge their attitudes toward decision-analytic modeling. Participants also identified and prioritized genetic services for prospective decision-analytic evaluation. Participants expressed dissatisfaction with current processes for evaluating insurance coverage of genetic services. Some participants expressed uncertainty about their comprehension of decision-analytic modeling techniques. All stakeholders reported openness to using decision-analytic modeling for genetic services assessments. Participants were most interested in application of decision-analytic concepts to multiple-disorder testing platforms, such as next-generation sequencing and chromosomal microarray. Decision-analytic modeling approaches may provide a useful decision tool to genetic services stakeholders and Medicaid decision-makers.
Nicod, Elena
2017-07-01
Health technology assessment (HTA) coverage recommendations differ across countries for the same drugs. Unlike previous studies, this study adopts a mixed methods research design to investigate, in a systematic manner, these differences. HTA recommendations for ten orphan drugs appraised in England (NICE), Scotland (SMC), Sweden (TLV) and France (HAS) (N = 35) were compared using a validated methodological framework that breaks down these complex decision processes into stages facilitating their understanding, analysis and comparison, namely: (1) the clinical/cost-effectiveness evidence, (2) its interpretation (e.g. part of the deliberative process) and (3) influence on the final decision. This allowed qualitative and quantitative identification of the criteria driving recommendations and highlighted cross-country differences. Six out of ten drugs received diverging HTA recommendations. Reasons for cross-country differences included heterogeneity in the evidence appraised, in the interpretation of the same evidence, and in the different ways of dealing with the same uncertainty. These may have been influenced by agency-specific evidentiary, risk and value preferences, or stakeholder input. "Other considerations" (e.g. severity, orphan status) and other decision modulators (e.g. patient access schemes, lower discount rates, restrictions, re-assessments) also rendered uncertainty and cost-effectiveness estimates more acceptable. The different HTA approaches (clinical versus cost-effectiveness) and ways identified of dealing with orphan drug particularities also had implications on the final decisions. This research contributes to better understanding the drivers of these complex decisions and why countries make different decisions. It also contributed to identifying those factors beyond the standard clinical and cost-effectiveness tools used in HTA, and their role in shaping these decisions.
Next generation terminology infrastructure to support interprofessional care planning.
Collins, Sarah; Klinkenberg-Ramirez, Stephanie; Tsivkin, Kira; Mar, Perry L; Iskhakova, Dina; Nandigam, Hari; Samal, Lipika; Rocha, Roberto A
2017-11-01
Develop a prototype of an interprofessional terminology and information model infrastructure that can enable care planning applications to facilitate patient-centered care, learn care plan linkages and associations, provide decision support, and enable automated, prospective analytics. The study steps included a 3 step approach: (1) Process model and clinical scenario development, and (2) Requirements analysis, and (3) Development and validation of information and terminology models. Components of the terminology model include: Health Concerns, Goals, Decisions, Interventions, Assessments, and Evaluations. A terminology infrastructure should: (A) Include discrete care plan concepts; (B) Include sets of profession-specific concerns, decisions, and interventions; (C) Communicate rationales, anticipatory guidance, and guidelines that inform decisions among the care team; (D) Define semantic linkages across clinical events and professions; (E) Define sets of shared patient goals and sub-goals, including patient stated goals; (F) Capture evaluation toward achievement of goals. These requirements were mapped to AHRQ Care Coordination Measures Framework. This study used a constrained set of clinician-validated clinical scenarios. Terminology models for goals and decisions are unavailable in SNOMED CT, limiting the ability to evaluate these aspects of the proposed infrastructure. Defining and linking subsets of care planning concepts appears to be feasible, but also essential to model interprofessional care planning for common co-occurring conditions and chronic diseases. We recommend the creation of goal dynamics and decision concepts in SNOMED CT to further enable the necessary models. Systems with flexible terminology management infrastructure may enable intelligent decision support to identify conflicting and aligned concerns, goals, decisions, and interventions in shared care plans, ultimately decreasing documentation effort and cognitive burden for clinicians and patients. Copyright © 2017 Elsevier Inc. All rights reserved.
Dunger, Christine; Schnell, Martin W; Bausewein, Claudia
2017-02-22
Decision-making (DM) in healthcare can be understood as an interactive process addressing decision makers' reasoning as well as their visible behaviour after the decision is made. Other key elements of DM are ethical aspects and the role as well as the treatment options of the examined professions. Nurses' DM to choose interventions in situations of severe breathlessness is such interactions. They are also ethically relevant regarding the vulnerability of affected patients and possible restrictions or treatment options. The study aims to explore which factors influence nurses' DM to use nursing interventions in situations where patients suffer from severe breathlessness. Qualitative study including nurses in German hospital wards and hospices. A triangulation of different methods of data collection-participant observation and qualitative expert interviews-and analysis merge in a reflexive grounded theory approach which integrates Goffman's framework analysis. It allows an analysis of nurses' self-statements about DM, their behaviour in relevant clinical situations and its influences. Data collection and analysis will be examined simultaneously. Informed consent will be gained from all participants and the institutional stakeholders. Ongoing consent has to be ensured since observations will take place in healthcare institutions and many patients will be highly vulnerable. The study has been evaluated and approved by the Witten/Herdecke University Ethics Committee, Witten, Germany. Results of the study will be published at congresses and in journal papers. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.
Schuster, Steven R; Pockaj, Barbara A; Bothe, Mary R; David, Paru S; Northfelt, Donald W
2012-09-10
Breast cancer is the most common malignancy among women in the United States with the second highest incidence of cancer-related death following lung cancer. The decision-making process regarding adjuvant therapy is a time intensive dialogue between the patient and her oncologist. There are multiple tools that help individualize the treatment options for a patient. Population-based analysis with Adjuvant! Online and genomic profiling with Oncotype DX are two commonly used tools in patients with early stage, node-negative breast cancer. This case report illustrates a situation in which the population-based prognostic and predictive information differed dramatically from that obtained from genomic profiling and affected the patient's decision. In light of this case, we discuss the benefits and limitations of these tools.
Characterizing Decision-Analysis Performances of Risk Prediction Models Using ADAPT Curves.
Lee, Wen-Chung; Wu, Yun-Chun
2016-01-01
The area under the receiver operating characteristic curve is a widely used index to characterize the performance of diagnostic tests and prediction models. However, the index does not explicitly acknowledge the utilities of risk predictions. Moreover, for most clinical settings, what counts is whether a prediction model can guide therapeutic decisions in a way that improves patient outcomes, rather than to simply update probabilities.Based on decision theory, the authors propose an alternative index, the "average deviation about the probability threshold" (ADAPT).An ADAPT curve (a plot of ADAPT value against the probability threshold) neatly characterizes the decision-analysis performances of a risk prediction model.Several prediction models can be compared for their ADAPT values at a chosen probability threshold, for a range of plausible threshold values, or for the whole ADAPT curves. This should greatly facilitate the selection of diagnostic tests and prediction models.
SteelFisher, Gillian K.; Martin, Lauren A.; Dowal, Sarah L.; Inouye, Sharon K.
2013-01-01
OBJECTIVES To explore strategies used by clinical programs to justify operations to decision-makers using the example of the Hospital Elder Life Program (HELP), an evidence-based, cost-effective program to improve care for hospitalized older adults. DESIGN Qualitative study design utilizing 62 in-depth, semi-structured interviews conducted with HELP staff members and hospital administrators between September 2008 and August 2009. SETTING 19 HELP sites in hospitals across the U.S. and Canada that had been recruiting patients for at least 6 months. PARTICIPANTS and MEASUREMENTS HELP staff and hospital administrator experiences sustaining the program in the face of actual or perceived financial threats, with a focus on factors they believe are effective in justifying the program to decision-makers in the hospital or health system. RESULTS Using the constant comparative method, a standard qualitative analysis technique, three major themes were identified across interviews. Each focuses on a strategy for successfully justifying the program and securing funds for continued operations: 1) interact meaningfully with decision-makers, including formal presentations that showcase operational successes, and also informal means that highlight the benefits of HELP to the hospital or health system; 2) document day-to-day, operational successes in metrics that resonate with decision-maker priorities; and 3) garner support from influential hospital staff that feed into administrative decision-making, particularly nurses and physicians. CONCLUSION As clinical programs face financially challenging times, it is important to find effective ways to justify their operations to decision-makers. Strategies described here may help clinically-effective and cost-effective programs sustain themselves, and thus may help improve care in their institutions. PMID:22091501
Perspective: Uses and misuses of thresholds in diagnostic decision making.
Warner, Jeremy L; Najarian, Robert M; Tierney, Lawrence M
2010-03-01
The concept of thresholds plays a vital role in decisions involving the initiation, continuation, and completion of diagnostic testing. Much research has focused on the development of explicit thresholds, in the form of practice guidelines and decision analyses. However, these tools are used infrequently; most medical decisions are made at the bedside, using implicit thresholds. Study of these thresholds can lead to a deeper understanding of clinical decision making. The authors examine some factors constituting individual clinicians' implicit thresholds. They propose a model for static thresholds using the concept of situational gravity to explain why some thresholds are high, and some low. Next, they consider the hypothetical effects of incorrect placement of thresholds (miscalibration) and changes to thresholds during diagnosis (manipulation). They demonstrate these concepts using common clinical scenarios. Through analysis of miscalibration of thresholds, the authors demonstrate some common maladaptive clinical behaviors, which are nevertheless internally consistent. They then explain how manipulation of thresholds gives rise to common cognitive heuristics including premature closure and anchoring. They also discuss the case where no threshold has been exceeded despite exhaustive collection of data, which commonly leads to application of the availability or representativeness heuristics. Awareness of implicit thresholds allows for a more effective understanding of the processes of medical decision making and, possibly, to the avoidance of detrimental heuristics and their associated medical errors. Research toward accurately defining these thresholds for individual physicians and toward determining their dynamic properties during the diagnostic process may yield valuable insights.
Maxson, Pamela M; Dozois, Eric J; Holubar, Stefan D; Wrobleski, Diane M; Dube, Joyce A Overman; Klipfel, Janee M; Arnold, Jacqueline J
2011-01-01
To determine whether interdisciplinary simulation team training can positively affect registered nurse and/or physician perceptions of collaboration in clinical decision making. 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. 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). Team training using high-fidelity simulation scenarios promoted collaboration between nurses and physicians and enhanced the patient care decision-making process.
Integrating complex business processes for knowledge-driven clinical decision support systems.
Kamaleswaran, Rishikesan; McGregor, Carolyn
2012-01-01
This paper presents in detail the component of the Complex Business Process for Stream Processing framework that is responsible for integrating complex business processes to enable knowledge-driven Clinical Decision Support System (CDSS) recommendations. CDSSs aid the clinician in supporting the care of patients by providing accurate data analysis and evidence-based recommendations. However, the incorporation of a dynamic knowledge-management system that supports the definition and enactment of complex business processes and real-time data streams has not been researched. In this paper we discuss the process web service as an innovative method of providing contextual information to a real-time data stream processing CDSS.
[Factors influencing nurses' clinical decision making--focusing on critical thinking disposition].
Park, Seungmi; Kwon, In Gak
2007-10-01
The purpose of this study was to investigate the factors influencing nurses' clinical decision making focusing on critical thinking disposition. The subjects of this study consisted of 505 nurses working at one of the general hospitals located in Seoul. Data was collected by a self-administered questionnaire between December 2006 and January 2007. Data was analyzed by one way ANOVA, Pearson correlation coefficients, and stepwise multiple regression using SPSS Win 14.0. The mean scores of critical thinking disposition and clinical decision making were 99.10 and 134.32 respectively. Clinical decision making scores were significantly higher in groups under continuing education, with a master or higher degree, with clinical experience more than 5 years, or with experts. Critical thinking disposition and its subscales have a significant correlation with clinical decision making. Intellectual eagerness/curiosity, prudence, clinical experience, intellectual honesty, self-confidence, and healthy skepticism were important factors influencing clinical decision making(adjusted R(2)=33%). Results of this study suggest that various strategies such as retaining experienced nurses, encouraging them to continue with education and enhancing critical thinking disposition are warranted for development of clinical decision making.
Optimal management of adults with pharyngitis – a multi-criteria decision analysis
Singh, Sonal; Dolan, James G; Centor, Robert M
2006-01-01
Background Current practice guidelines offer different management recommendations for adults presenting with a sore throat. The key issue is the extent to which the clinical likelihood of a Group A streptococcal infection should affect patient management decisions. To help resolve this issue, we conducted a multi-criteria decision analysis using the Analytic Hierarchy Process. Methods We defined optimal patient management using four criteria: 1) reduce symptom duration; 2) prevent infectious complications, local and systemic; 3) minimize antibiotic side effects, minor and anaphylaxis; and 4) achieve prudent use of antibiotics, avoiding both over-use and under-use. In our baseline analysis we assumed that all criteria and sub-criteria were equally important except minimizing anaphylactic side effects, which was judged very strongly more important than minimizing minor side effects. Management strategies included: a) No test, No treatment; b) Perform a rapid strep test and treat if positive; c) Perform a throat culture and treat if positive; d) Perform a rapid strep test and treat if positive; if negative obtain a throat culture and treat if positive; and e) treat without further tests. We defined four scenarios based on the likelihood of group A streptococcal infection using the Centor score, a well-validated clinical index. Published data were used to estimate the likelihoods of clinical outcomes and the test operating characteristics of the rapid strep test and throat culture for identifying group A streptococcal infections. Results Using the baseline assumptions, no testing and no treatment is preferred for patients with Centor scores of 1; two strategies – culture and treat if positive and rapid strep with culture of negative results – are equally preferable for patients with Centor scores of 2; and rapid strep with culture of negative results is the best management strategy for patients with Centor scores 3 or 4. These results are sensitive to the priorities assigned to the decision criteria, especially avoiding over-use versus under-use of antibiotics, and the population prevalence of Group A streptococcal pharyngitis. Conclusion The optimal clinical management of adults with sore throat depends on both the clinical probability of a group A streptococcal infection and clinical judgments that incorporate individual patient and practice circumstances. PMID:16533386
Kastner, Monika; Straus, Sharon E
2008-12-01
Studies indicate a gap between evidence and clinical practice in osteoporosis management. Tools that facilitate clinical decision making at the point of care are promising strategies for closing these practice gaps. To systematically review the literature to identify and describe the effectiveness of tools that support clinical decision making in osteoporosis disease management. Medline, EMBASE, CINAHL, and EBM Reviews (CDSR, DARE, CCTR, and ACP J Club), and contact with experts in the field. Randomized controlled trials (RCTs) in any language from 1966 to July 2006 investigating disease management interventions in patients at risk for osteoporosis. Outcomes included fractures and bone mineral density (BMD) testing. Two investigators independently assessed articles for relevance and study quality, and extracted data using standardized forms. Of 1,246 citations that were screened for relevance, 13 RCTs met the inclusion criteria. Reported study quality was generally poor. Meta-analysis was not done because of methodological and clinical heterogeneity; 77% of studies included a reminder or education as a component of their intervention. Three studies of reminders plus education targeted to physicians and patients showed increased BMD testing (RR range 1.43 to 8.67) and osteoporosis medication use (RR range 1.60 to 8.67). A physician reminder plus a patient risk assessment strategy found reduced fractures [RR 0.58, 95% confidence interval (CI) 0.37 to 0.90] and increased osteoporosis therapy (RR 2.44, CI 1.43 to 4.17). Multi-component tools that are targeted to physicians and patients may be effective for supporting clinical decision making in osteoporosis disease management.
Probabilistic Gait Classification in Children with Cerebral Palsy: A Bayesian Approach
ERIC Educational Resources Information Center
Van Gestel, Leen; De Laet, Tinne; Di Lello, Enrico; Bruyninckx, Herman; Molenaers, Guy; Van Campenhout, Anja; Aertbelien, Erwin; Schwartz, Mike; Wambacq, Hans; De Cock, Paul; Desloovere, Kaat
2011-01-01
Three-dimensional gait analysis (3DGA) generates a wealth of highly variable data. Gait classifications help to reduce, simplify and interpret this vast amount of 3DGA data and thereby assist and facilitate clinical decision making in the treatment of CP. CP gait is often a mix of several clinically accepted distinct gait patterns. Therefore,…
Time Keeps on Ticking: The Experience of Clinical Judgment
ERIC Educational Resources Information Center
Spengler, Paul M.; White, Michael J.; Aegisdottir, Stefania; Maugherman, Alan S.
2009-01-01
The reactions by Ridley and Shaw-Ridley (EJ832451) and Lichtenberg (EJ832452) to the authors' meta-analysis on the effects of experience on judgment accuracy add positively to what is hoped will become an ever more focused discourse on this most basic question: How can mental health clinical decision making be improved? In this rejoinder, the…
Types of vicarious learning experienced by pre-dialysis patients.
McCarthy, Kate; Sturt, Jackie; Adams, Ann
2015-01-01
Haemodialysis and peritoneal dialysis renal replacement treatment options are in clinical equipoise, although the cost of haemodialysis to the National Health Service is £16,411/patient/year greater than peritoneal dialysis. Treatment decision-making takes place during the pre-dialysis year when estimated glomerular filtration rate drops to between 15 and 30 mL/min/1.73 m(2). Renal disease can be familial, and the majority of patients have considerable health service experience when they approach these treatment decisions. Factors affecting patient treatment decisions are currently unknown. The objective of this article is to explore data from a wider study in specific relation to the types of vicarious learning experiences reported by pre-dialysis patients. A qualitative study utilised unstructured interviews and grounded theory analysis during the participant's pre-dialysis year. The interview cohort comprised 20 pre-dialysis participants between 24 and 80 years of age. Grounded theory design entailed thematic sampling and analysis, scrutinised by secondary coding and checked with participants. Participants were recruited from routine renal clinics at two local hospitals when their estimated glomerular filtration rate was between 15 and 30 mL/min/1.73 m(2). Vicarious learning that contributed to treatment decision-making fell into three main categories: planned vicarious leaning, unplanned vicarious learning and historical vicarious experiences. Exploration and acknowledgement of service users' prior vicarious learning, by healthcare professionals, is important in understanding its potential influences on individuals' treatment decision-making. This will enable healthcare professionals to challenge heuristic decisions based on limited information and to encourage analytic thought processes.
Korduner, E-K; Collin Bagewitz, I; Vult von Steyern, P; Wolf, E
2016-12-01
The aim of this investigation was to study the clinical prosthodontic decision-making process relating to dentitions with compromised molars among Swedish general dental practitioners (GDPs). Eleven Swedish GDPs were purposively selected, and all agreed to participate. Then, in-depth, semi-structured interviews were conducted and covered treatment considerations concerning two authentic patient cases, initially with complete dental arches, and later, a final treatment based on a shortened dental arch (SDA) was discussed. The cases involved patients with compromised teeth situated mainly in the molar regions. One patient suffered from extensive caries and the other from severe periodontal disease. Qualitative content analysis was used to analyse the data. In the systematic analysis, two main categories were identified: holistic and functional approach. Among the interviewed GDPs, focus was put on patients' needs, background history and motivation for treatment as well as the preservation of molar support. Within the limitations of this study, the following can be concluded: keeping a dental arch with molars seems to be important to Swedish general dental practitioners. The SDA concept does not seem to have a substantial impact on the prosthodontic decision-making relating to dentitions with compromised molars. The dentist's experiences, as well as colleagues' or consulting specialist advice together with aetiological factors and the patient's individual situation, influence the decision-making more than the SDA concept. The conflicting results in the prosthetic decision-making process concerning the relevance of age and the need for molar support need further investigation, for example based on decisions made in the dentist's own clinical practice. © 2016 John Wiley & Sons Ltd.
Baker, Elizabeth A; Ledford, Cynthia H; Fogg, Louis; Way, David P; Park, Yoon Soo
2015-01-01
Construct: Clinical skills are used in the care of patients, including reporting, diagnostic reasoning, and decision-making skills. Written comprehensive new patient admission notes (H&Ps) are a ubiquitous part of student education but are underutilized in the assessment of clinical skills. The interpretive summary, differential diagnosis, explanation of reasoning, and alternatives (IDEA) assessment tool was developed to assess students' clinical skills using written comprehensive new patient admission notes. The validity evidence for assessment of clinical skills using clinical documentation following authentic patient encounters has not been well documented. Diagnostic justification tools and postencounter notes are described in the literature (1,2) but are based on standardized patient encounters. To our knowledge, the IDEA assessment tool is the first published tool that uses medical students' H&Ps to rate students' clinical skills. The IDEA assessment tool is a 15-item instrument that asks evaluators to rate students' reporting, diagnostic reasoning, and decision-making skills based on medical students' new patient admission notes. This study presents validity evidence in support of the IDEA assessment tool using Messick's unified framework, including content (theoretical framework), response process (interrater reliability), internal structure (factor analysis and internal-consistency reliability), and relationship to other variables. Validity evidence is based on results from four studies conducted between 2010 and 2013. First, the factor analysis (2010, n = 216) yielded a three-factor solution, measuring patient story, IDEA, and completeness, with reliabilities of .79, .88, and .79, respectively. Second, an initial interrater reliability study (2010) involving two raters demonstrated fair to moderate consensus (κ = .21-.56, ρ =.42-.79). Third, a second interrater reliability study (2011) with 22 trained raters also demonstrated fair to moderate agreement (intraclass correlations [ICCs] = .29-.67). There was moderate reliability for all three skill domains, including reporting skills (ICC = .53), diagnostic reasoning skills (ICC = .64), and decision-making skills (ICC = .63). Fourth, there was a significant correlation between IDEA rating scores (2010-2013) and final Internal Medicine clerkship grades (r = .24), 95% confidence interval (CI) [.15, .33]. The IDEA assessment tool is a novel tool with validity evidence to support its use in the assessment of students' reporting, diagnostic reasoning, and decision-making skills. The moderate reliability achieved supports formative or lower stakes summative uses rather than high-stakes summative judgments.
Miniati, Roberto; Dori, Fabrizio; Cecconi, Giulio; Gusinu, Roberto; Niccolini, Fabrizio; Gentili, Guido Biffi
2013-01-01
A fundamental element of the social and safety function of a health structure is the need to guarantee continuity of clinical activity through the continuity of technology. This paper aims to design a Decision Support System (DSS) for medical technology evaluations based on the use of Key Performance Indicators (KPI) in order to provide a multi-disciplinary valuation of a technology in a health structure. The methodology used in planning the DSS followed the following key steps: the definition of relevant KPIs, the development of a database to calculate the KPIs, the calculation of the defined KPIs and the resulting study report. Finally, the clinical and economic validation of the system was conducted though a case study of Business Continuity applied in the operating department of the Florence University Hospital AOU Careggi in Italy. A web-based support system was designed for HTA in health structures. The case study enabled Business Continuity Management (BCM) to be implemented in a hospital department in relation to aspects of a single technology and the specific clinical process. Finally, an economic analysis of the procedure was carried out. The system is useful for decision makers in that it precisely defines which equipment to include in the BCM procedure, using a scale analysis of the specific clinical process in which the equipment is used. In addition, the economic analysis shows how the cost of the procedure is completely covered by the indirect costs which would result from the expenses incurred from a broken device, hence showing the complete auto-sustainability of the methodology.
Crawford, E D; Batuello, J T; Snow, P; Gamito, E J; McLeod, D G; Partin, A W; Stone, N; Montie, J; Stock, R; Lynch, J; Brandt, J
2000-05-01
The current study assesses artificial intelligence methods to identify prostate carcinoma patients at low risk for lymph node spread. If patients can be assigned accurately to a low risk group, unnecessary lymph node dissections can be avoided, thereby reducing morbidity and costs. A rule-derivation technology for simple decision-tree analysis was trained and validated using patient data from a large database (4,133 patients) to derive low risk cutoff values for Gleason sum and prostate specific antigen (PSA) level. An empiric analysis was used to derive a low risk cutoff value for clinical TNM stage. These cutoff values then were applied to 2 additional, smaller databases (227 and 330 patients, respectively) from separate institutions. The decision-tree protocol derived cutoff values of < or = 6 for Gleason sum and < or = 10.6 ng/mL for PSA. The empiric analysis yielded a clinical TNM stage low risk cutoff value of < or = T2a. When these cutoff values were applied to the larger database, 44% of patients were classified as being at low risk for lymph node metastases (0.8% false-negative rate). When the same cutoff values were applied to the smaller databases, between 11 and 43% of patients were classified as low risk with a false-negative rate of between 0.0 and 0.7%. The results of the current study indicate that a population of prostate carcinoma patients at low risk for lymph node metastases can be identified accurately using a simple decision algorithm that considers preoperative PSA, Gleason sum, and clinical TNM stage. The risk of lymph node metastases in these patients is < or = 1%; therefore, pelvic lymph node dissection may be avoided safely. The implications of these findings in surgical and nonsurgical treatment are significant.
Tappenden, Paul; Chilcott, Jim; Brennan, Alan; Squires, Hazel; Glynne-Jones, Rob; Tappenden, Janine
2013-06-01
To assess the feasibility and value of simulating whole disease and treatment pathways within a single model to provide a common economic basis for informing resource allocation decisions. A patient-level simulation model was developed with the intention of being capable of evaluating multiple topics within National Institute for Health and Clinical Excellence's colorectal cancer clinical guideline. The model simulates disease and treatment pathways from preclinical disease through to detection, diagnosis, adjuvant/neoadjuvant treatments, follow-up, curative/palliative treatments for metastases, supportive care, and eventual death. The model parameters were informed by meta-analyses, randomized trials, observational studies, health utility studies, audit data, costing sources, and expert opinion. Unobservable natural history parameters were calibrated against external data using Bayesian Markov chain Monte Carlo methods. Economic analysis was undertaken using conventional cost-utility decision rules within each guideline topic and constrained maximization rules across multiple topics. Under usual processes for guideline development, piecewise economic modeling would have been used to evaluate between one and three topics. The Whole Disease Model was capable of evaluating 11 of 15 guideline topics, ranging from alternative diagnostic technologies through to treatments for metastatic disease. The constrained maximization analysis identified a configuration of colorectal services that is expected to maximize quality-adjusted life-year gains without exceeding current expenditure levels. This study indicates that Whole Disease Model development is feasible and can allow for the economic analysis of most interventions across a disease service within a consistent conceptual and mathematical infrastructure. This disease-level modeling approach may be of particular value in providing an economic basis to support other clinical guidelines. Copyright © 2013 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.
Hallgren, Kevin A; Bauer, Amy M; Atkins, David C
2017-06-01
Clinical decision making encompasses a broad set of processes that contribute to the effectiveness of depression treatments. There is emerging interest in using digital technologies to support effective and efficient clinical decision making. In this paper, we provide "snapshots" of research and current directions on ways that digital technologies can support clinical decision making in depression treatment. Practical facets of clinical decision making are reviewed, then research, design, and implementation opportunities where technology can potentially enhance clinical decision making are outlined. Discussions of these opportunities are organized around three established movements designed to enhance clinical decision making for depression treatment, including measurement-based care, integrated care, and personalized medicine. Research, design, and implementation efforts may support clinical decision making for depression by (1) improving tools to incorporate depression symptom data into existing electronic health record systems, (2) enhancing measurement of treatment fidelity and treatment processes, (3) harnessing smartphone and biosensor data to inform clinical decision making, (4) enhancing tools that support communication and care coordination between patients and providers and within provider teams, and (5) leveraging treatment and outcome data from electronic health record systems to support personalized depression treatment. The current climate of rapid changes in both healthcare and digital technologies facilitates an urgent need for research, design, and implementation of digital technologies that explicitly support clinical decision making. Ensuring that such tools are efficient, effective, and usable in frontline treatment settings will be essential for their success and will require engagement of stakeholders from multiple domains. © 2017 Wiley Periodicals, Inc.
The emerging potential for network analysis to inform precision cancer medicine.
Ozturk, Kivilcim; Dow, Michelle; Carlin, Daniel E; Bejar, Rafael; Carter, Hannah
2018-06-14
Precision cancer medicine promises to tailor clinical decisions to patients using genomic information. Indeed, successes of drugs targeting genetic alterations in tumors, such as imatinib that targets BCR-ABL in chronic myelogenous leukemia, have demonstrated the power of this approach. However biological systems are complex, and patients may differ not only by the specific genetic alterations in their tumor, but by more subtle interactions among such alterations. Systems biology and more specifically, network analysis, provides a framework for advancing precision medicine beyond clinical actionability of individual mutations. Here we discuss applications of network analysis to study tumor biology, early methods for N-of-1 tumor genome analysis and the path for such tools to the clinic. Copyright © 2018. Published by Elsevier Ltd.
Kessler, Maya Elizabeth; Cook, David A; Kor, Daryl Jon; McKie, Paul M; Pencille, Laurie J; Scheitel, Marianne R; Chaudhry, Rajeev
2017-01-01
Introduction Clinical practice guidelines facilitate optimal clinical practice. Point of care access, interpretation and application of such guidelines, however, is inconsistent. Informatics-based tools may help clinicians apply guidelines more consistently. We have developed a novel clinical decision support tool that presents guideline-relevant information and actionable items to clinicians at the point of care. We aim to test whether this tool improves the management of hyperlipidaemia, atrial fibrillation and heart failure by primary care clinicians. Methods/analysis Clinician care teams were cluster randomised to receive access to the clinical decision support tool or passive access to institutional guidelines on 16 May 2016. The trial began on 1 June 2016 when access to the tool was granted to the intervention clinicians. The trial will be run for 6 months to ensure a sufficient number of patient encounters to achieve 80% power to detect a twofold increase in the primary outcome at the 0.05 level of significance. The primary outcome measure will be the percentage of guideline-based recommendations acted on by clinicians for hyperlipidaemia, atrial fibrillation and heart failure. We hypothesise care teams with access to the clinical decision support tool will act on recommendations at a higher rate than care teams in the standard of care arm. Ethics and dissemination The Mayo Clinic Institutional Review Board approved all study procedures. Informed consent was obtained from clinicians. A waiver of informed consent and of Health Insurance Portability and Accountability Act (HIPAA) authorisation for patients managed by clinicians in the study was granted. In addition to publication, results will be disseminated via meetings and newsletters. Trial registration number NCT02742545. PMID:29208620
Assessing decision quality in patient-centred care requires a preference-sensitive measure
Kaltoft, Mette; Cunich, Michelle; Salkeld, Glenn; Dowie, Jack
2014-01-01
A theory-based instrument for measuring the quality of decisions made using any form of decision technology, including both decision-aided and unaided clinical consultations is required to enable person- and patient-centred care and to respond positively to individual heterogeneity in the value aspects of decision making. Current instruments using the term ‘decision quality’ have adopted a decision- and thus condition-specific approach. We argue that patient-centred care requires decision quality to be regarded as both preference-sensitive across multiple relevant criteria and generic across all conditions and decisions. MyDecisionQuality is grounded in prescriptive multi criteria decision analysis and employs a simple expected value algorithm to calculate a score for the quality of a decision that combines, in the clinical case, the patient’s individual preferences for eight quality criteria (expressed as importance weights) and their ratings of the decision just taken on each of these criteria (expressed as performance rates). It thus provides an index of decision quality that encompasses both these aspects. It also provides patients with help in prioritizing quality criteria for future decision making by calculating, for each criterion, the Incremental Value of Perfect Rating, that is, the increase in their decision quality score that would result if their performance rating on the criterion had been 100%, weightings unchanged. MyDecisionQuality, which is a web-based generic and preference-sensitive instrument, can constitute a key patient-reported measure of the quality of the decision-making process. It can provide the basis for future decision improvement, especially when the clinician (or other stakeholders) completes the equivalent instrument and the extent and nature of concordance and discordance can be established. Apart from its role in decision preparation and evaluation, it can also provide real time and relevant documentation for the patient’s record. PMID:24335587
Surgical decision making in a teaching hospital: a linguistic analysis.
Bezemer, Jeff; Murtagh, Ged; Cope, Alexandra; Kneebone, Roger
2016-10-01
The aim of the study was to gain insight in the involvement of non-operating surgeons in intraoperative surgical decision making at a teaching hospital. The decision to proceed to clip and cut the cystic duct during laparoscopic cholecystectomy was investigated through direct observation of team work. Eleven laparoscopic cholecystectomies performed by consultant surgeons and specialty trainees at a London teaching hospital were audio and video recorded. Talk among the surgical team was transcribed and subjected to linguistic analysis, in conjunction with observational analysis of the video material, sequentially marking the unfolding operation. Two components of decision making were identified, participation and rationalization. Participation refers to the degree to which agreement was sought within the surgical team prior to clipping the cystic duct. Rationalization refers to the degree to which the evidential grounds for clipping and cutting were verbalized. The decision to clip and cut the cystic duct was jointly made by members of the surgical team, rather than a solitary surgeon in the majority of cases, involving verbal explication of clinical reasoning and verbal agreement. The extent of joint decision making appears to have been mitigated by two factors: trainee's level of training and duration of the case. © 2014 Royal Australasian College of Surgeons.
Stokes, Tim; Tumilty, Emma; Doolan-Noble, Fiona; Gauld, Robin
2017-04-05
Multimorbidity is a major issue for primary care. We aimed to explore primary care professionals' accounts of managing multimorbidity and its impact on clinical decision making and regional health care delivery. Qualitative interviews with 12 General Practitioners and 4 Primary Care Nurses in New Zealand's Otago region. Thematic analysis was conducted using the constant comparative method. Primary care professionals encountered challenges in providing care to patients with multimorbidity with respect to both clinical decision making and health care delivery. Clinical decision making occurred in time-limited consultations where the challenges of complexity and inadequacy of single disease guidelines were managed through the use of "satisficing" (care deemed satisfactory and sufficient for a given patient) and sequential consultations utilising relational continuity of care. The New Zealand primary care co-payment funding model was seen as a barrier to the delivery of care as it discourages sequential consultations, a problem only partially addressed through the use of the additional capitation based funding stream of Care Plus. Fragmentation of care also occurred within general practice and across the primary/secondary care interface. These findings highlight specific New Zealand barriers to the delivery of primary care to patients living with multimorbidity. There is a need to develop, implement and nationally evaluate a revised version of Care Plus that takes account of these barriers.
[Generalization of the results of clinical studies through the analysis of subgroups].
Costa, João; Fareleira, Filipa; Ascensão, Raquel; Vaz Carneiro, António
2012-01-01
Subgroup analysis in clinical trials are usually performed to define the potential heterogeneity of treatment effect in relation with the baseline risk, physiopathology, practical application of therapy or the under-utilization in clinical practice of effective interventions due to uncertainties of its benefit/risk ratio. When appropriately planned, subgroup analysis are a valid methodology the define benefits in subgroups of patients, thus providing good quality evidence to support clinical decision making. However, in order to be correct, subgroup analysis should be defined a priori, done in small numbers, should be fully reported and, most important, must endure statistical tests for interaction. In this paper we present an example of the treatment of post-menopausal osteoporosis, in which the benefits of an intervention (the higher the fracture risk is, the better the benefit is) with a specific agent (bazedoxifene) was only disclosed after a post-hoc analysis of the initial global trial sample.
In the teeth of the evidence: the curious case of evidence-based medicine.
Davidoff, F
1999-03-01
For a very long time, evidence from research has contributed to clinical decision making. Over the past 50 years, however, the nature of clinical research evidence has drastically changed compared with previous eras: its standards are higher, the tools for assembling and analyzing it are more powerful, and the context in which it is used is less authoritarian. The consequence has been a shift in both the concept and the practice of clinical decision making known as evidence-based medicine. Evidence-based decisions, by definition, use the strongest available evidence, are often more quantitatively informed than decisions made in the traditional fashion; and sometimes run counter to expert opinion. The techniques of evidence-based medicine are also helpful in resolving conflicting opinions. Evidence-based medicine did not simply appear in vacuo; its roots extend back at least as far as the great French Encyclopedia of the 18th century, and the subsequent work of Pierre Louis in Paris in the early 19th century. The power of the evidence-based approach has been enhanced in recent years by the development of the techniques of systematic review and meta-analysis. While this approach has its critics, we would all want the best available evidence used in making decisions about our care if we got sick. It is only fair that the patients under our care receive nothing less.
Weber, Scott; Crago, Elizabeth A; Sherwood, Paula R; Smith, Tara
2009-11-01
The aim of this study was to explore the experiences of nurses and physicians who use a clinical decision support system (CDSS) in the critical care area, focusing on clinicians' motives and values related to decisions to either use or not use this optional technology. Information technology (IT) has been demonstrated to positively impact quality of patient care. Decision-support technology serves as an adjunct to, not as a replacement for, actual clinical decision making. Nurse administrators play an imperative role in the planning and implementation of IT projects and can benefit from understanding clinicians' affective considerations and approaches to the technology. This qualitative study used grounded theory methods. A total of 33 clinicians participated in in-depth structured interviews probing their professional concerns with how the technology is used. Data were analyzed using the constant comparative method. Medical staff were frustrated by perceived lack of planning input before system implementation. Both nurse and physician cohort groups were dissatisfied with preimplementation education. Barriers to system use were identified in significant detail by the participants. Both nurses and physicians should be involved in preimplementation planning and ongoing evaluation of CDSSs. There is a need for a systematic review or Cochrane meta-analysis describing the affective aspects of successful implementations of decisional technology in critical care, specifically from the perspective of nursing administrators.
Gurney, J C; Ansari, E; Harle, D; O'Kane, N; Sagar, R V; Dunne, M C M
2018-02-09
To determine the accuracy of a Bayesian learning scheme (Bayes') applied to the prediction of clinical decisions made by specialist optometrists in relation to the referral refinement of chronic open angle glaucoma. This cross-sectional observational study involved collection of data from the worst affected or right eyes of a consecutive sample of cases (n = 1,006) referred into the West Kent Clinical Commissioning Group Community Ophthalmology Team (COT) by high street optometrists. Multilevel classification of each case was based on race, sex, age, family history of chronic open angle glaucoma, reason for referral, Goldmann Applanation Tonometry (intraocular pressure and interocular asymmetry), optic nerve head assessment (vertical size, cup disc ratio and interocular asymmetry), central corneal thickness and visual field analysis (Hodapp-Parrish-Anderson classification). Randomised stratified tenfold cross-validation was applied to determine the accuracy of Bayes' by comparing its output to the clinical decisions of three COT specialist optometrists; namely, the decision to discharge, follow-up or refer each case. Outcomes of cross-validation, expressed as means and standard deviations, showed that the accuracy of Bayes' was high (95%, 2.0%) but that it falsely discharged (3.4%, 1.6%) or referred (3.1%, 1.5%) some cases. The results indicate that Bayes' has the potential to augment the decisions of specialist optometrists.
Pelaccia, Thierry; Tardif, Jacques; Triby, Emmanuel; Charlin, Bernard
2011-03-14
Clinical reasoning plays a major role in the ability of doctors to make diagnoses and decisions. It is considered as the physician's most critical competence, and has been widely studied by physicians, educationalists, psychologists and sociologists. Since the 1970s, many theories about clinical reasoning in medicine have been put forward. This paper aims at exploring a comprehensive approach: the "dual-process theory", a model developed by cognitive psychologists over the last few years. After 40 years of sometimes contradictory studies on clinical reasoning, the dual-process theory gives us many answers on how doctors think while making diagnoses and decisions. It highlights the importance of physicians' intuition and the high level of interaction between analytical and non-analytical processes. However, it has not received much attention in the medical education literature. The implications of dual-process models of reasoning in terms of medical education will be discussed.
Etchells, Edward; Ferrari, Michel; Kiss, Alex; Martyn, Nikki; Zinman, Deborah; Levinson, Wendy
2011-06-01
Prior studies show significant gaps in the informed decision-making process, a central goal of surgical care. These studies have been limited by their focus on low-risk decisions, single visits rather than entire consultations, or both. Our objectives were, first, to rate informed decision-making for major elective vascular surgery based on audiotapes of actual physician-patient conversations and, second, to compare ratings of informed decision-making for first visits to ratings for multiple visits by the same patient over time. We prospectively enrolled patients for whom vascular surgical treatment was a potential option at a tertiary care outpatient vascular surgery clinic. We audio-taped all surgeon-patient conversations, including multiple visits when necessary, until a decision was made. Using an existing method, we evaluated the transcripts for elements of decision-making, including basic elements (e.g., an explanation of the clinical condition), intermediate elements (e.g., risks and benefits) and complex elements (e.g., uncertainty around the decision). We analyzed 145 surgeon-patient consultations. Overall, 45% of consultations contained complex elements, whereas 23% did not contain the basic elements of decision-making. For the 67 consultations that involved multiple visits, ratings were significantly higher when evaluating all visits (50% complex elements) compared with evaluating only the first visit (33% complex elements, p < 0.001.) We found that 45% of consultations contained complex elements, which is higher than prior studies with similar methods. Analyzing decision-making over multiple visits yielded different results than analyzing decision-making for single visits.
A stochastic multicriteria model for evidence-based decision making in drug benefit-risk analysis.
Tervonen, Tommi; van Valkenhoef, Gert; Buskens, Erik; Hillege, Hans L; Postmus, Douwe
2011-05-30
Drug benefit-risk (BR) analysis is based on firm clinical evidence regarding various safety and efficacy outcomes. In this paper, we propose a new and more formal approach for constructing a supporting multi-criteria model that fully takes into account the evidence on efficacy and adverse drug reactions. Our approach is based on the stochastic multi-criteria acceptability analysis methodology, which allows us to compute the typical value judgments that support a decision, to quantify decision uncertainty, and to compute a comprehensive BR profile. We construct a multi-criteria model for the therapeutic group of second-generation antidepressants. We assess fluoxetine and venlafaxine together with placebo according to incidence of treatment response and three common adverse drug reactions by using data from a published study. Our model shows that there are clear trade-offs among the treatment alternatives. Copyright © 2011 John Wiley & Sons, Ltd.
Hierarchical Bayes approach for subgroup analysis.
Hsu, Yu-Yi; Zalkikar, Jyoti; Tiwari, Ram C
2017-01-01
In clinical data analysis, both treatment effect estimation and consistency assessment are important for a better understanding of the drug efficacy for the benefit of subjects in individual subgroups. The linear mixed-effects model has been used for subgroup analysis to describe treatment differences among subgroups with great flexibility. The hierarchical Bayes approach has been applied to linear mixed-effects model to derive the posterior distributions of overall and subgroup treatment effects. In this article, we discuss the prior selection for variance components in hierarchical Bayes, estimation and decision making of the overall treatment effect, as well as consistency assessment of the treatment effects across the subgroups based on the posterior predictive p-value. Decision procedures are suggested using either the posterior probability or the Bayes factor. These decision procedures and their properties are illustrated using a simulated example with normally distributed response and repeated measurements.
Enhancing clinical decision making: development of a contiguous definition and conceptual framework.
Tiffen, Jennifer; Corbridge, Susan J; Slimmer, Lynda
2014-01-01
Clinical decision making is a term frequently used to describe the fundamental role of the nurse practitioner; however, other terms have been used interchangeably. The purpose of this article is to begin the process of developing a definition and framework of clinical decision making. The developed definition was "Clinical decision making is a contextual, continuous, and evolving process, where data are gathered, interpreted, and evaluated in order to select an evidence-based choice of action." A contiguous framework for clinical decision making specific for nurse practitioners is also proposed. Having a clear and unique understanding of clinical decision making will allow for consistent use of the term, which is relevant given the changing educational requirements for nurse practitioners and broadening scope of practice. Copyright © 2014 Elsevier Inc. All rights reserved.
Forsberg, Elenita; Ziegert, Kristina; Hult, Håkan; Fors, Uno
2014-04-01
In health-care education, it is important to assess the competencies that are essential for the professional role. To develop clinical reasoning skills is crucial for nursing practice and therefore an important learning outcome in nursing education programmes. Virtual patients (VPs) are interactive computer simulations of real-life clinical scenarios and have been suggested for use not only for learning, but also for assessment of clinical reasoning. The aim of this study was to investigate how experienced paediatric nurses reason regarding complex VP cases and how they make clinical decisions. The study was also aimed to give information about possible issues that should be assessed in clinical reasoning exams for post-graduate students in diploma specialist paediatric nursing education. The information from this study is believed to be of high value when developing scoring and grading models for a VP-based examination for the specialist diploma in paediatric nursing education. Using the think-aloud method, data were collected from 30 RNs working in Swedish paediatric departments, and child or school health-care centres. Content analysis was used to analyse the data. The results indicate that experienced nurses try to consolidate their hypotheses by seeing a pattern and judging the value of signs, symptoms, physical examinations, laboratory tests and radiology. They show high specific competence but earlier experience of similar cases was also of importance for the decision making. The nurses thought it was an innovative assessment focusing on clinical reasoning and clinical decision making. They thought it was an enjoyable way to be assessed and that all three main issues could be assessed using VPs. In conclusion, VPs seem to be a possible model for assessing the clinical reasoning process and clinical decision making, but how to score and grade such exams needs further research. © 2013.
Savitz, Adam; Melkote, Rama; Riley, Ralph; Pobre, Maria A; McQuarrie, Kelly; Williamson, David; Banderas, Benjamin
2018-05-19
The cause of treatment failure of antipsychotic medications is often difficult to determine in patients with schizophrenia. Evaluation of antipsychotic blood levels (ABLs) may aid clinicians in determining the cause of antipsychotic failure. The Clinical Assessment of the Schizophrenia Patient (CASP) was developed to evaluate clinical decision making during outpatient visits. The CASP assesses changes in medications, psychosocial treatments, and acute interventions along with factors influencing clinical decision making. Nine vignettes representative of clinical situations in patients with schizophrenia were created in two versions (one with ABLs, one without ABLs). The CASP was used to evaluate clinical decisions using the vignettes. Thirty-four clinicians participated in the study. In 8 out of 9 vignettes, most clinicians (at least 89.7%) made a different clinical decision with ABLs compared to without ABLs. In assessing the usefulness of ABLs, a majority (60.7%-85.7%, depending on the vignette) of clinicians responded that ABLs changed their clinical decision for 8 vignettes. Most clinicians (79%-93%) responded that they were more confident in their decisions with ABL information. This study demonstrated that ABLs have the potential to influence clinical decision making in the treatment of patients with schizophrenia. Copyright © 2018. Published by Elsevier B.V.
Electronic decision support for diagnostic imaging in a primary care setting
Reed, Martin H
2011-01-01
Methods Clinical guideline adherence for diagnostic imaging (DI) and acceptance of electronic decision support in a rural community family practice clinic was assessed over 36 weeks. Physicians wrote 904 DI orders, 58% of which were addressed by the Canadian Association of Radiologists guidelines. Results Of those orders with guidelines, 76% were ordered correctly; 24% were inappropriate or unnecessary resulting in a prompt from clinical decision support. Physicians followed suggestions from decision support to improve their DI order on 25% of the initially inappropriate orders. The use of decision support was not mandatory, and there were significant variations in use rate. Initially, 40% reported decision support disruptive in their work flow, which dropped to 16% as physicians gained experience with the software. Conclusions Physicians supported the concept of clinical decision support but were reluctant to change clinical habits to incorporate decision support into routine work flow. PMID:21486884
[Application of evidence based medicine to the individual patient: the role of decision analysis].
Housset, B; Junod, A F
2003-11-01
The objective of evidence based medicine (EBM) is to contribute to medical decision making by providing the best possible information in terms of validity and relevance. This allows evaluation in a specific manner of the benefits and risks of a decision. The limitations and hazards of this approach are discussed in relation to a clinical case where the diagnosis of pulmonary embolism was under consideration. The individual details and the limited availability of some technical procedures illustrate the need to adapt the data of EBM to the circumstances. The choice between two diagnostic tests (d-dimers and ultrasound of the legs) and their optimal timing is analysed with integration of the consequences for the patient of the treatments proposed. This allows discussion of the concept of utility and the use of sensitivity analysis. If EBM is the cornerstone of rational and explicit practise it should also allow for the constraints of real life. Decision analysis, which depends on the same critical demands as EBM but can also take account of the individual features of each patient and test the robustness of a decision, gives a unique opportunity reconcile rigorous reasoning with individualisation of management.
Satomi, Junichiro; Ghaibeh, A Ammar; Moriguchi, Hiroki; Nagahiro, Shinji
2015-07-01
The severity of clinical signs and symptoms of cranial dural arteriovenous fistulas (DAVFs) are well correlated with their pattern of venous drainage. Although the presence of cortical venous drainage can be considered a potential predictor of aggressive DAVF behaviors, such as intracranial hemorrhage or progressive neurological deficits due to venous congestion, accurate statistical analyses are currently not available. Using a decision tree data mining method, the authors aimed at clarifying the predictability of the future development of aggressive behaviors of DAVF and at identifying the main causative factors. Of 266 DAVF patients, 89 were eligible for analysis. Under observational management, 51 patients presented with intracranial hemorrhage/infarction during the follow-up period. The authors created a decision tree able to assess the risk for the development of aggressive DAVF behavior. Evaluated by 10-fold cross-validation, the decision tree's accuracy, sensitivity, and specificity were 85.28%, 88.33%, and 80.83%, respectively. The tree shows that the main factor in symptomatic patients was the presence of cortical venous drainage. In its absence, the lesion location determined the risk of a DAVF developing aggressive behavior. Decision tree analysis accurately predicts the future development of aggressive DAVF behavior.
Cost-effectiveness of Skin Cancer Referral and Consultation Using Teledermoscopy in Australia.
Snoswell, Centaine L; Caffery, Liam J; Whitty, Jennifer A; Soyer, H Peter; Gordon, Louisa G
2018-06-01
International literature has shown that teledermoscopy referral may be a viable method for skin cancer referral; however, no economic investigations have occurred in Australia. To assess the cost-effectiveness of teledermoscopy as a referral mechanism for skin cancer diagnosis and management in Australia. Cost-effectiveness analysis using a decision-analytic model of Australian primary care, informed by publicly available data. We compared the costs of teledermoscopy referral (electronic referral containing digital dermoscopic images) vs usual care (a written referral letter) for specialist dermatologist review of a suspected skin cancer. Cost and time in days to clinical resolution, where clinical resolution was defined as diagnosis by a dermatologist or excision by a general practitioner. Probabilistic sensitivity analysis was performed to examine the uncertainty of the main results. Findings from the decision-analytic model showed that the mean time to clinical resolution was 9 days (range, 1-50 days) with teledermoscopy referral compared with 35 days (range, 0-138 days) with usual care alone (difference, 26 days; 95% credible interval [CrI], 13-38 days). The estimated mean cost difference between teledermoscopy referral (A$318.39) vs usual care (A$263.75) was A$54.64 (95% CrI, A$22.69-A$97.35) per person. The incremental cost per day saved to clinical resolution was A$2.10 (95% CrI, A$0.87-A$5.29). Using teledermoscopy for skin cancer referral and triage in Australia would cost A$54.64 extra per case on average but would result in clinical resolution 26 days sooner than usual care. Implementation recommendations depend on the preferences of the Australian health system decision makers for either lower cost or expedited clinical resolution. Further research around the clinical significance of expedited clinical resolution and its importance for patients could inform implementation recommendations for the Australian setting.
Factors affecting Korean nursing student empowerment in clinical practice.
Ahn, Yang-Heui; Choi, Jihea
2015-12-01
Understanding the phenomenon of nursing student empowerment in clinical practice is important. Investigating the cognition of empowerment and identifying predictors are necessary to enhance nursing student empowerment in clinical practice. To identify empowerment predictors for Korean nursing students in clinical practice based on studies by Bradbury-Jones et al. and Spreitzer. A cross-sectional design was used for this study. This study was performed in three nursing colleges in Korea, all of which had similar baccalaureate nursing curricula. Three hundred seven junior or senior nursing students completed a survey designed to measure factors that were hypothesized to influence nursing student empowerment in clinical practice. Data were collected from November to December 2011. Study variables included self-esteem, clinical decision making, being valued as a learner, satisfaction regarding practice with a team member, perception on professor/instructor/clinical preceptor attitude, and total number of clinical practice fields. Data were analyzed using stepwise multiple regression analyses. All of the hypothesized study variables were significantly correlated to nursing student empowerment. Stepwise multiple regression analysis revealed that clinical decision making in nursing (t=7.59, p<0.001), being valued as a learner (t=6.24, p<0.001), self-esteem (t=3.62, p<0.001), and total number of clinical practice fields (t=2.06, p=0.040). The explanatory power of these predictors was 35% (F=40.71, p<0.001). Enhancing nursing student empowerment in clinical practice will be possible by using educational strategies to improve nursing student clinical decision making. Simultaneously, attitudes of nurse educators are also important to ensure that nursing students are treated as valued learners and to increase student self-esteem in clinical practice. Finally, diverse clinical practice field environments should be considered to enhance experience. Copyright © 2015 Elsevier Ltd. All rights reserved.
Louie, Michelle; Spencer, Jennifer; Wheeler, Stephanie; Ellis, Victoria; Toubia, Tarek; Schiff, Lauren D; Siedhoff, Matthew T; Moulder, Janelle K
2017-11-01
A better understanding of the relative risks and benefits of common treatment options for abnormal uterine bleeding (AUB) can help providers and patients to make balanced, evidence-based decisions. To provide comparative estimates of clinical outcomes after placement of levonorgestrel-releasing intrauterine system (LNG-IUS), ablation, or hysterectomy for AUB. A PubMED search was done using combinations of search terms related to abnormal uterine bleeding, LNG-IUS, hysterectomy, endometrial ablation, cost-benefit analysis, cost-effectiveness, and quality-adjusted life years. Full articles published in 2006-2016 available in English comparing at least two treatment modalities of interest among women of reproductive age with AUB were included. A decision tree was generated to compare clinical outcomes in a hypothetical cohort of 100 000 premenopausal women with nonmalignant AUB. We evaluated complications, mortality, and treatment outcomes over a 5-year period, calculated cumulative quality-adjusted life years (QALYs), and conducted probabilistic sensitivity analysis. Levonorgestrel-releasing intrauterine system had the highest number of QALYs (406 920), followed by hysterectomy (403 466), non-resectoscopic ablation (399 244), and resectoscopic ablation (395 827). Ablation had more treatment failures and complications than LNG-IUS and hysterectomy. Findings were robust in probabilistic sensitivity analysis. Levonorgestrel-releasing intrauterine system and hysterectomy outperformed endometrial ablation for treatment of AUB. © 2017 International Federation of Gynecology and Obstetrics.
Huser, Vojtech; Rasmussen, Luke V; Oberg, Ryan; Starren, Justin B
2011-04-10
Workflow engine technology represents a new class of software with the ability to graphically model step-based knowledge. We present application of this novel technology to the domain of clinical decision support. Successful implementation of decision support within an electronic health record (EHR) remains an unsolved research challenge. Previous research efforts were mostly based on healthcare-specific representation standards and execution engines and did not reach wide adoption. We focus on two challenges in decision support systems: the ability to test decision logic on retrospective data prior prospective deployment and the challenge of user-friendly representation of clinical logic. We present our implementation of a workflow engine technology that addresses the two above-described challenges in delivering clinical decision support. Our system is based on a cross-industry standard of XML (extensible markup language) process definition language (XPDL). The core components of the system are a workflow editor for modeling clinical scenarios and a workflow engine for execution of those scenarios. We demonstrate, with an open-source and publicly available workflow suite, that clinical decision support logic can be executed on retrospective data. The same flowchart-based representation can also function in a prospective mode where the system can be integrated with an EHR system and respond to real-time clinical events. We limit the scope of our implementation to decision support content generation (which can be EHR system vendor independent). We do not focus on supporting complex decision support content delivery mechanisms due to lack of standardization of EHR systems in this area. We present results of our evaluation of the flowchart-based graphical notation as well as architectural evaluation of our implementation using an established evaluation framework for clinical decision support architecture. We describe an implementation of a free workflow technology software suite (available at http://code.google.com/p/healthflow) and its application in the domain of clinical decision support. Our implementation seamlessly supports clinical logic testing on retrospective data and offers a user-friendly knowledge representation paradigm. With the presented software implementation, we demonstrate that workflow engine technology can provide a decision support platform which evaluates well against an established clinical decision support architecture evaluation framework. Due to cross-industry usage of workflow engine technology, we can expect significant future functionality enhancements that will further improve the technology's capacity to serve as a clinical decision support platform.
Helping parents cope with crying babies: decision-making and interaction at NHS Direct.
Smith, Suzanne
2010-02-01
This paper is a report of a study of how nurses at a national telephone triage centre in England (NHS Direct) make different use of the algorithms and organizational protocols to make decisions and give advice to parents with crying babies, how their clinical knowledge and experience influences these decisions, and the techniques used to enhance parental coping ability. Parents of persistently crying babies state that they need to be listened to, understood, believed and reassured to help them cope. Nurses at NHS Direct use their clinical judgement in decision-making, and see the software as a guide that can be both valuable and problematic. The study design was influenced by grounded theory and incorporated discourse and thematic analysis. It had two phases involving data collection and analysis over the period 2002-2006. A theoretical sample of 11 calls was analysed and later a focus group of six nurses at the same site. NHS Direct nurses used the 'crying baby' algorithm in various ways, influenced by their experience and confidence to use the algorithm to support their clinical knowledge. Its medical elements were regarded as safe but its non-medical elements, including questions about the likelihood of shaking a child, were treated differently. Nurses were reluctant to deviate from the algorithm when dealing with child-focused calls. However, this reluctance did not apply when they were prompted to ask the caller if they felt that they were reaching a point where they might shake their baby, or when prompted to give related advice.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Defreyne, Luc, E-mail: Luc.Defreyne@UGent.b; Schrijver, Ignace De; Decruyenaere, Johan
2008-09-15
The purpose of this study was to identify endoscopic and clinical parameters influencing the decision-making in salvage of endoscopically unmanageable, nonvariceal upper gastrointestinal hemorrhage (UGIH) and to report the outcome of selected therapy. We retrospectively retrieved all cases of surgery and arteriography for arrest of endoscopically unmanageable UGIH. Only patients with overt bleeding on endoscopy within the previous 24 h were included. Patients with preceding nonendoscopic hemostatic interventions, portal hypertension, malignancy, and transpapillar bleeding were excluded. Potential clinical and endoscopic predictors of allocation to either surgery or arteriography were tested using statistical models. Outcome and survival were regressed on themore » choice of rescue and clinical variables. Forty-six arteriographed and 51 operated patients met the inclusion criteria. Univariate analysis revealed a higher number of patients with a coagulation disorder in the catheterization group (41.4%, versus 20.4% in the laparotomy group; p = 0.044). With multivariate analysis, the identification of a bleeding peptic ulcer at endoscopy significantly steered decision-making toward surgical rescue (OR = 5.2; p = 0.021). Taking into account reinterventions, hemostasis was achieved in nearly 90% of cases in both groups. Overall therapy failure (no survivors), rebleeding within 3 days (OR = 3.7; p = 0.042), and corticosteroid use (OR = 5.2; p = 0.017) had a significant negative impact on survival. The odds of dying were not different for embolotherapy or surgery. In conclusion, decision-making was endoscopy-based, with bleeding peptic ulcer significantly directing the choice of rescue toward surgery. Unsuccessful hemostasis and corticosteroid use, but not the choice of rescue, negatively affected outcome.« less
Decision aid use during post-biopsy consultations for localized prostate cancer.
Holmes-Rovner, Margaret; Srikanth, Akshay; Henry, Stephen G; Langford, Aisha; Rovner, David R; Fagerlin, Angela
2018-02-01
Decision Aids (DAs) effectively translate medical evidence for patients but are not routinely used in clinical practice. Little is known about how DAs are used during patient-clinician encounters. To characterize the content and communicative function of high-quality DAs during diagnostic clinic visits for prostate cancer. 252 men newly diagnosed with localized prostate cancer who had received a DA, 45 treating physicians at 4 US Veterans Administration urology clinics. Qualitative analysis of transcribed audio recordings was used to inductively develop categories capturing content and function of all direct references to DAs (booklet talk). The presence or absence of any booklet talk per transcript was also calculated. Booklet talk occurred in 55% of transcripts. Content focused on surgical procedures (36%); treatment choice (22%); and clarifying risk classification (17%). The most common function of booklet talk was patient corroboration of physicians' explanations (42%), followed by either physician or patient acknowledgement that the patient had the booklet. Codes reflected the absence of DA use for shared decision-making. In regression analysis, predictors of booklet talk were fewer years of patient education (P = .027) and more time in the encounter (P = .027). Patient race, DA type, time reading the DA, physician informing quality and physician age did not predict booklet talk. Results show that good decision aids, systematically provided to patients, appeared to function not to open up deliberations about how to balance benefits and harms of competing treatments, but rather to allow patients to ask narrow technical questions about recommended treatments. © 2017 The Authors Health Expectations Published by John Wiley & Sons Ltd.
Deciding to Come Out to Parents: Toward a Model of Sexual Orientation Disclosure Decisions.
Grafsky, Erika L
2017-08-16
The purpose of this study was to conduct research to understand nonheterosexual youths' decision to disclose their sexual orientation information to their parents. The sample for this study includes 22 youth between the ages of 14 and 21. Constructivist grounded theory guided the qualitative methodology and data analysis. The findings from this study posit an emerging model of sexual orientation disclosure decisions comprised of four interrelated factors that influence the decision to disclose or not disclose, as well as a description of the mechanism through which disclosure either does or does not occur. Clinical implications and recommendations for further research are provided. © 2017 Family Process Institute.
Clinical decision making by nurses when faced with third-space fluid shift. How well do they fare?
Redden, M; Wotton, K
2001-01-01
Nurses' use of knowledge, the connection of this knowledge to treatment decisions and information actually used to reach such decisions, delineates nurses' level of expertise. Previous research has shown that nurses in their clinical decision-making use the hypothetico-deductive method and intuitive judgment or pattern recognition. This interpretive study explored experienced critical care nurses' (n = 5) and gastrointestinal surgical nurses' (n = 5) clinical decision-making processes through ascertaining their knowledge and understanding of third-space fluid shift in elderly patients undergoing major gastrointestinal surgery. Both groups of nurses, because of their experience with elderly patients undergoing gastrointestinal surgery, were assumed to be experts. Data collection techniques included semi-structured interviews and the use of think aloud protocol for clinical scenario analysis. The findings demonstrated that the gastrointestinal surgical nurses used the hypothetico-deductive method to recognize critical cues and the existence of a problem but could not name the problem. The critical care nurses, on the other hand, used a combination of the hypothetico-deductive method and pattern recognition as a basis for identification of critical cues. The critical care nurses also possessed in depth knowledge of third-space fluid shift and were able to use pivotal cues to identify the actual phenomenon. Ultimately, it would appear that the structure of critical care nurses' work, their increased educational qualifications and the culture of the critical care unit promote a more proactive approach to reasoning in the physiological domain. The findings have implications for the development of practice guidelines and curriculum development in both tertiary and continuing nurse education.
Clinical decision making and the expected value of information.
Willan, Andrew R
2007-01-01
The results of the HOPE study, a randomized clinical trial, provide strong evidence that 1) ramipril prevents the composite outcome of cardiovascular death, myocardial infarction or stroke in patients who are at high risk of a cardiovascular event and 2) ramipril is cost-effective at a threshold willingness-to-pay of $10,000 to prevent an event of the composite outcome. In this report the concept of the expected value of information is used to determine if the information provided by the HOPE study is sufficient for decision making in the US and Canada. and results Using the cost-effectiveness data from a clinical trial, or from a meta-analysis of several trials, one can determine, based on the number of future patients that would benefit from the health technology under investigation, the expected value of sample information (EVSI) of a future trial as a function of proposed sample size. If the EVSI exceeds the cost for any particular sample size then the current information is insufficient for decision making and a future trial is indicated. If, on the other hand, there is no sample size for which the EVSI exceeds the cost, then there is sufficient information for decision making and no future trial is required. Using the data from the HOPE study these concepts are applied for various assumptions regarding the fixed and variable cost of a future trial and the number of patients who would benefit from ramipril. Expected value of information methods provide a decision-analytic alternative to the standard likelihood methods for assessing the evidence provided by cost-effectiveness data from randomized clinical trials.
Models based on value and probability in health improve shared decision making.
Ortendahl, Monica
2008-10-01
Diagnostic reasoning and treatment decisions are a key competence of doctors. A model based on values and probability provides a conceptual framework for clinical judgments and decisions, and also facilitates the integration of clinical and biomedical knowledge into a diagnostic decision. Both value and probability are usually estimated values in clinical decision making. Therefore, model assumptions and parameter estimates should be continually assessed against data, and models should be revised accordingly. Introducing parameter estimates for both value and probability, which usually pertain in clinical work, gives the model labelled subjective expected utility. Estimated values and probabilities are involved sequentially for every step in the decision-making process. Introducing decision-analytic modelling gives a more complete picture of variables that influence the decisions carried out by the doctor and the patient. A model revised for perceived values and probabilities by both the doctor and the patient could be used as a tool for engaging in a mutual and shared decision-making process in clinical work.
Decision science and cervical cancer.
Cantor, Scott B; Fahs, Marianne C; Mandelblatt, Jeanne S; Myers, Evan R; Sanders, Gillian D
2003-11-01
Mathematical modeling is an effective tool for guiding cervical cancer screening, diagnosis, and treatment decisions for patients and policymakers. This article describes the use of mathematical modeling as outlined in five presentations from the Decision Science and Cervical Cancer session of the Second International Conference on Cervical Cancer held at The University of Texas M. D. Anderson Cancer Center, April 11-14, 2002. The authors provide an overview of mathematical modeling, especially decision analysis and cost-effectiveness analysis, and examples of how it can be used for clinical decision making regarding the prevention, diagnosis, and treatment of cervical cancer. Included are applications as well as theory regarding decision science and cervical cancer. Mathematical modeling can answer such questions as the optimal frequency for screening, the optimal age to stop screening, and the optimal way to diagnose cervical cancer. Results from one mathematical model demonstrated that a vaccine against high-risk strains of human papillomavirus was a cost-effective use of resources, and discussion of another model demonstrated the importance of collecting direct non-health care costs and time costs for cost-effectiveness analysis. Research presented indicated that care must be taken when applying the results of population-wide, cost-effectiveness analyses to reduce health disparities. Mathematical modeling can encompass a variety of theoretical and applied issues regarding decision science and cervical cancer. The ultimate objective of using decision-analytic and cost-effectiveness models is to identify ways to improve women's health at an economically reasonable cost. Copyright 2003 American Cancer Society.
DesAutels, Spencer J; Fox, Zachary E; Giuse, Dario A; Williams, Annette M; Kou, Qing-Hua; Weitkamp, Asli; Neal R, Patel; Bettinsoli Giuse, Nunzia
2016-01-01
Clinical decision support (CDS) knowledge, embedded over time in mature medical systems, presents an interesting and complex opportunity for information organization, maintenance, and reuse. To have a holistic view of all decision support requires an in-depth understanding of each clinical system as well as expert knowledge of the latest evidence. This approach to clinical decision support presents an opportunity to unify and externalize the knowledge within rules-based decision support. Driven by an institutional need to prioritize decision support content for migration to new clinical systems, the Center for Knowledge Management and Health Information Technology teams applied their unique expertise to extract content from individual systems, organize it through a single extensible schema, and present it for discovery and reuse through a newly created Clinical Support Knowledge Acquisition and Archival Tool (CS-KAAT). CS-KAAT can build and maintain the underlying knowledge infrastructure needed by clinical systems.
Non-clinical influences on clinical decision-making: a major challenge to evidence-based practice.
Hajjaj, F M; Salek, M S; Basra, M K A; Finlay, A Y
2010-05-01
This article reviews an aspect of daily clinical practice which is of critical importance in virtually every clinical consultation, but which is seldom formally considered. Non-clinical influences on clinical decision-making profoundly affect medical decisions. These influences include patient-related factors such as socioeconomic status, quality of life and patient's expectations and wishes, physician-related factors such as personal characteristics and interaction with their professional community, and features of clinical practice such as private versus public practice as well as local management policies. This review brings together the different strands of knowledge concerning non-clinical influences on clinical decision-making. This aspect of decision-making may be the biggest obstacle to the reality of practising evidence-based medicine. It needs to be understood in order to develop clinical strategies that will facilitate the practice of evidence-based medicine.
Alexander, L M
1998-01-01
The Joint National Committee's report on the Prevention, Detection, Evaluation, and Treatment of High Blood Pressure was released in November 1997. With its release, an increased emphasis on "treating the patient, not just the number" has taken place. The report provides a comprehensive review of recent clinical evidence that helps guide clinical decision making in the care of the hypertensive patient. A new disease classification system entitled "risk stratification" is introduced and takes into account comorbid conditions that are present for many hypertensive individuals. This risk stratification is then linked to treatment strategies and provides a concise decision analysis framework to aid in clinical decision making. Community-based prevention strategies are also highlighted and should raise the awareness of clinicians to adopt these recommendations and integrate them more aggressively into daily practice. Increased emphasis on patient compliance to improve overall hypertension control rates is also presented. Maximum efficacy through once-daily dosing and fixed-dose combinations are reviewed in the report. The JNC report is a comprehensive resource for clinicians in primary care practice. Its evidenced-based approach is a wonderful teaching tool for those clinicians who also serve as clinical educators in primary care.
Bau, Cho-Tsan; Huang, Chung-Yi
2014-01-01
Abstract Objective: To construct a clinical decision support system (CDSS) for undergoing surgery based on domain ontology and rules reasoning in the setting of hospitalized diabetic patients. Materials and Methods: The ontology was created with a modified ontology development method, including specification and conceptualization, formalization, implementation, and evaluation and maintenance. The Protégé–Web Ontology Language editor was used to implement the ontology. Embedded clinical knowledge was elicited to complement the domain ontology with formal concept analysis. The decision rules were translated into JENA format, which JENA can use to infer recommendations based on patient clinical situations. Results: The ontology includes 31 classes and 13 properties, plus 38 JENA rules that were built to generate recommendations. The evaluation studies confirmed the correctness of the ontology, acceptance of recommendations, satisfaction with the system, and usefulness of the ontology for glycemic management of diabetic patients undergoing surgery, especially for domain experts. Conclusions: The contribution of this research is to set up an evidence-based hybrid ontology and an evaluation method for CDSS. The system can help clinicians to achieve inpatient glycemic control in diabetic patients undergoing surgery while avoiding hypoglycemia. PMID:24730353
Bau, Cho-Tsan; Chen, Rung-Ching; Huang, Chung-Yi
2014-05-01
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. 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. 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. 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.
Loos, Sabine; Clarke, Eleanor; Jordan, Harriet; Puschner, Bernd; Fiorillo, Andrea; Luciano, Mario; Ivánka, Tibor; Magyar, Erzsébet; Krogsgaard-Bording, Malene; Østermark-Sørensen, Helle; Rössler, Wulf; Kawohl, Wolfram; Mayer, Benjamin; Slade, Mike
2017-01-23
Clinical decision-making is the vehicle of health care provision, and level of involvement predicts implementation and satisfaction. The aim of this study was to investigate the impact of decision-making experience on recovery. Data derived from an observational cohort study "Clinical decision making and outcome in routine care for people with severe mental illness" (CEDAR). Adults (aged 18-60) meeting standardised criteria for severe mental illness were recruited from caseloads of outpatient and community mental health services in six European countries. After consenting, they were assessed using standardised measures of decision-making, clinical outcome and stage of recovery at baseline and 1 year later. Latent class analysis was used to identify course of recovery, and proportional odds models to investigate predictors of recovery stage and change. Participants (n = 581) clustered into three stages of recovery at baseline: Moratorium (N = 115; 19.8%), Awareness/Preparation (N = 145; 25.0%) and Rebuilding/Growth (N = 321; 55.2%). Higher stage was cross-sectionally associated with being male, married, living alone or with parents, and having better patient-rated therapeutic alliance and fewer symptoms. The model accounted for 40% of the variance in stage of recovery. An increased chance of worse outcome (change over 1 year to lower stage of recovery) was found for patients with active involvement compared with either shared (OR = 1.84, 95% CI 1.15-2.94) or passive (OR = 1.71, 95% CI = 1.00-2.95) involvement. Overall, both process (therapeutic relationship) and outcome (symptomatology) are cross-sectionally associated with stage of recovery. Patient-rated decision-making involvement and change in stage of recovery are associated. Joint consideration of decision practise within the recovery process between patient and clinician is supposed to be a useful strategy to improve clinical practice (ISRCTN registry: ISRCTN75841675. Retrospectively registered 15 September 2010).
Thompson, Rachel; Manski, Ruth; Donnelly, Kyla Z; Stevens, Gabrielle; Agusti, Daniela; Banach, Michelle; Boardman, Maureen B; Brady, Pearl; Colón Bradt, Christina; Foster, Tina; Johnson, Deborah J; Li, Zhongze; Norsigian, Judy; Nothnagle, Melissa; Olson, Ardis L; Shepherd, Heather L; Stern, Lisa F; Tosteson, Tor D; Trevena, Lyndal; Upadhya, Krishna K; Elwyn, Glyn
2017-01-01
Introduction Despite the observed and theoretical advantages of shared decision-making in a range of clinical contexts, including contraceptive care, there remains a paucity of evidence on how to facilitate its adoption. This paper describes the protocol for a study to assess the comparative effectiveness of patient-targeted and provider-targeted interventions for facilitating shared decision-making about contraceptive methods. Methods and analysis We will conduct a 2×2 factorial cluster randomised controlled trial with four arms: (1) video+prompt card, (2) decision aids+training, (3) video+prompt card and decision aids+training and (4) usual care. The clusters will be clinics in USA that deliver contraceptive care. The participants will be people who have completed a healthcare visit at a participating clinic, were assigned female sex at birth, are aged 15–49 years, are able to read and write English or Spanish and have not previously participated in the study. The primary outcome will be shared decision-making about contraceptive methods. Secondary outcomes will be the occurrence of a conversation about contraception in the healthcare visit, satisfaction with the conversation about contraception, intended contraceptive method(s), intention to use a highly effective method, values concordance of the intended method(s), decision regret, contraceptive method(s) used, use of a highly effective method, use of the intended method(s), adherence, satisfaction with the method(s) used, unintended pregnancy and unwelcome pregnancy. We will collect study data via longitudinal patient surveys administered immediately after the healthcare visit, four weeks later and six months later. Ethics and dissemination We will disseminate results via presentations at scientific and professional conferences, papers published in peer-reviewed, open-access journals and scientific and lay reports. We will also make an anonymised copy of the final participant-level dataset available to others for research purposes. Trial registration number ClinicalTrials.gov Identifier: NCT02759939. PMID:29061624
Duijn, Chantal C M A; Welink, Lisanne S; Bok, Harold G J; Ten Cate, Olle T J
2018-06-01
Clinical training programs increasingly use entrustable professional activities (EPAs) as focus of assessment. However, questions remain about which information should ground decisions to trust learners. This qualitative study aimed to identify decision variables in the workplace that clinical teachers find relevant in the elaboration of the entrustment decision processes. The findings can substantiate entrustment decision-making in the clinical workplace. Focus groups were conducted with medical and veterinary clinical teachers, using the structured consensus method of the Nominal Group Technique to generate decision variables. A ranking was made based on a relevance score assigned by the clinical teachers to the different decision variables. Field notes, audio recordings and flip chart lists were analyzed and subsequently translated and, as a form of axial coding, merged into one list, combining the decision variables that were similar in their meaning. A list of 11 and 17 decision variables were acknowledged as relevant by the medical and veterinary teacher groups, respectively. The focus groups yielded 21 unique decision variables that were considered relevant to inform readiness to perform a clinical task on a designated level of supervision. The decision variables consisted of skills, generic qualities, characteristics, previous performance or other information. We were able to group the decision variables into five categories: ability, humility, integrity, reliability and adequate exposure. To entrust a learner to perform a task at a specific level of supervision, a supervisor needs information to support such a judgement. This trust cannot be credited on a single case at a single moment of assessment, but requires different variables and multiple sources of information. This study provides an overview of decision variables giving evidence to justify the multifactorial process of making an entrustment decision.
ERIC Educational Resources Information Center
Fallon, Barbara; Chabot, Martin; Fluke, John; Blackstock, Cindy; MacLaurin, Bruce; Tonmyr, Lil
2013-01-01
Objective: Fluke et al. (2010) analyzed Canadian Incidence Study on Reported Child Abuse and Neglect (CIS) data collected in 1998 to explore the influence of clinical and organizational characteristics on the decision to place Aboriginal children in an out-of-home placement at the conclusion of a child maltreatment investigation. This study…
Amland, Robert C; Lyons, Jason J; Greene, Tracy L; Haley, James M
2015-10-01
To examine the diagnostic accuracy of a two-stage clinical decision support system for early recognition and stratification of patients with sepsis. Observational cohort study employing a two-stage sepsis clinical decision support to recognise and stratify patients with sepsis. The stage one component was comprised of a cloud-based clinical decision support with 24/7 surveillance to detect patients at risk of sepsis. The cloud-based clinical decision support delivered notifications to the patients' designated nurse, who then electronically contacted a provider. The second stage component comprised a sepsis screening and stratification form integrated into the patient electronic health record, essentially an evidence-based decision aid, used by providers to assess patients at bedside. Urban, 284 acute bed community hospital in the USA; 16,000 hospitalisations annually. Data on 2620 adult patients were collected retrospectively in 2014 after the clinical decision support was implemented. 'Suspected infection' was the established gold standard to assess clinical decision support clinimetric performance. A sepsis alert activated on 417 (16%) of 2620 adult patients hospitalised. Applying 'suspected infection' as standard, the patient population characteristics showed 72% sensitivity and 73% positive predictive value. A postalert screening conducted by providers at bedside of 417 patients achieved 81% sensitivity and 94% positive predictive value. Providers documented against 89% patients with an alert activated by clinical decision support and completed 75% of bedside screening and stratification of patients with sepsis within one hour from notification. A clinical decision support binary alarm system with cross-checking functionality improves early recognition and facilitates stratification of patients with sepsis.
2012-01-01
Background A statistical analysis plan (SAP) is a critical link between how a clinical trial is conducted and the clinical study report. To secure objective study results, regulatory bodies expect that the SAP will meet requirements in pre-specifying inferential analyses and other important statistical techniques. To write a good SAP for model-based sensitivity and ancillary analyses involves non-trivial decisions on and justification of many aspects of the chosen setting. In particular, trials with longitudinal count data as primary endpoints pose challenges for model choice and model validation. In the random effects setting, frequentist strategies for model assessment and model diagnosis are complex and not easily implemented and have several limitations. Therefore, it is of interest to explore Bayesian alternatives which provide the needed decision support to finalize a SAP. Methods We focus on generalized linear mixed models (GLMMs) for the analysis of longitudinal count data. A series of distributions with over- and under-dispersion is considered. Additionally, the structure of the variance components is modified. We perform a simulation study to investigate the discriminatory power of Bayesian tools for model criticism in different scenarios derived from the model setting. We apply the findings to the data from an open clinical trial on vertigo attacks. These data are seen as pilot data for an ongoing phase III trial. To fit GLMMs we use a novel Bayesian computational approach based on integrated nested Laplace approximations (INLAs). The INLA methodology enables the direct computation of leave-one-out predictive distributions. These distributions are crucial for Bayesian model assessment. We evaluate competing GLMMs for longitudinal count data according to the deviance information criterion (DIC) or probability integral transform (PIT), and by using proper scoring rules (e.g. the logarithmic score). Results The instruments under study provide excellent tools for preparing decisions within the SAP in a transparent way when structuring the primary analysis, sensitivity or ancillary analyses, and specific analyses for secondary endpoints. The mean logarithmic score and DIC discriminate well between different model scenarios. It becomes obvious that the naive choice of a conventional random effects Poisson model is often inappropriate for real-life count data. The findings are used to specify an appropriate mixed model employed in the sensitivity analyses of an ongoing phase III trial. Conclusions The proposed Bayesian methods are not only appealing for inference but notably provide a sophisticated insight into different aspects of model performance, such as forecast verification or calibration checks, and can be applied within the model selection process. The mean of the logarithmic score is a robust tool for model ranking and is not sensitive to sample size. Therefore, these Bayesian model selection techniques offer helpful decision support for shaping sensitivity and ancillary analyses in a statistical analysis plan of a clinical trial with longitudinal count data as the primary endpoint. PMID:22962944
Adrion, Christine; Mansmann, Ulrich
2012-09-10
A statistical analysis plan (SAP) is a critical link between how a clinical trial is conducted and the clinical study report. To secure objective study results, regulatory bodies expect that the SAP will meet requirements in pre-specifying inferential analyses and other important statistical techniques. To write a good SAP for model-based sensitivity and ancillary analyses involves non-trivial decisions on and justification of many aspects of the chosen setting. In particular, trials with longitudinal count data as primary endpoints pose challenges for model choice and model validation. In the random effects setting, frequentist strategies for model assessment and model diagnosis are complex and not easily implemented and have several limitations. Therefore, it is of interest to explore Bayesian alternatives which provide the needed decision support to finalize a SAP. We focus on generalized linear mixed models (GLMMs) for the analysis of longitudinal count data. A series of distributions with over- and under-dispersion is considered. Additionally, the structure of the variance components is modified. We perform a simulation study to investigate the discriminatory power of Bayesian tools for model criticism in different scenarios derived from the model setting. We apply the findings to the data from an open clinical trial on vertigo attacks. These data are seen as pilot data for an ongoing phase III trial. To fit GLMMs we use a novel Bayesian computational approach based on integrated nested Laplace approximations (INLAs). The INLA methodology enables the direct computation of leave-one-out predictive distributions. These distributions are crucial for Bayesian model assessment. We evaluate competing GLMMs for longitudinal count data according to the deviance information criterion (DIC) or probability integral transform (PIT), and by using proper scoring rules (e.g. the logarithmic score). The instruments under study provide excellent tools for preparing decisions within the SAP in a transparent way when structuring the primary analysis, sensitivity or ancillary analyses, and specific analyses for secondary endpoints. The mean logarithmic score and DIC discriminate well between different model scenarios. It becomes obvious that the naive choice of a conventional random effects Poisson model is often inappropriate for real-life count data. The findings are used to specify an appropriate mixed model employed in the sensitivity analyses of an ongoing phase III trial. The proposed Bayesian methods are not only appealing for inference but notably provide a sophisticated insight into different aspects of model performance, such as forecast verification or calibration checks, and can be applied within the model selection process. The mean of the logarithmic score is a robust tool for model ranking and is not sensitive to sample size. Therefore, these Bayesian model selection techniques offer helpful decision support for shaping sensitivity and ancillary analyses in a statistical analysis plan of a clinical trial with longitudinal count data as the primary endpoint.
Stacey, Dawn; Vandemheen, Katherine L; Hennessey, Rosamund; Gooyers, Tracy; Gaudet, Ena; Mallick, Ranjeeta; Salgado, Josette; Freitag, Andreas; Berthiaume, Yves; Brown, Neil; Aaron, Shawn D
2015-02-07
The decision to have lung transplantation as treatment for end-stage lung disease from cystic fibrosis (CF) has benefits and serious risks. Although patient decision aids are effective interventions for helping patients reach a quality decision, little is known about implementing them in clinical practice. Our study evaluated a sustainable approach for implementing a patient decision aid for adults with CF considering referral for lung transplantation. A prospective pragmatic observational study was guided by the Knowledge-to-Action Framework. Healthcare professionals in all 23 Canadian CF clinics were eligible. We surveyed participants regarding perceived barriers and facilitators to patient decision aid use. Interventions tailored to address modifiable identified barriers included training, access to decision aids, and conference calls. The primary outcome was >80% use of the decision aid in year 2. Of 23 adult CF clinics, 18 participated (78.2%) and 13 had healthcare professionals attend training. Baseline barriers were healthcare professionals' inadequate knowledge for supporting patients making decisions (55%), clarifying patients' values for outcomes of options (58%), and helping patients handle conflicting views of others (71%). Other barriers were lack of time (52%) and needing to change how transplantation is discussed (42%). Baseline facilitators were healthcare professionals feeling comfortable discussing bad transplantation outcomes (74%), agreeing the decision aid would be easy to experiment with (71%) and use in the CF clinic (87%), and agreeing that using the decision aid would not require reorganization of the CF clinic (90%). After implementing the decision aid with interventions tailored to the barriers, decision aid use increased from 29% at baseline to 85% during year 1 and 92% in year 2 (p < 0.001). Compared to baseline, more healthcare professionals at the end of the study were confident in supporting decision-making (p = 0.03) but continued to feel inadequate ability with supporting patients to handle conflicting views (p = 0.01). Most Canadian CF clinics agreed to participate in the study. Interventions were used to target identified modifiable barriers to using the patient decision aid in routine CF clinical practice. CF clinics reported using it with almost all patients in the second year.
[Big data analysis and evidence-based medicine: controversy or cooperation].
Chen, Xinzu; Hu, Jiankun
2016-01-01
The development of evidence-based medicince should be an important milestone from the empirical medicine to the evidence-driving modern medicine. With the outbreak in biomedical data, the rising big data analysis can efficiently solve exploratory questions or decision-making issues in biomedicine and healthcare activities. The current problem in China is that big data analysis is still not well conducted and applied to deal with problems such as clinical decision-making, public health policy, and should not be a debate whether big data analysis can replace evidence-based medicine or not. Therefore, we should clearly understand, no matter whether evidence-based medicine or big data analysis, the most critical infrastructure must be the substantial work in the design, constructure and collection of original database in China.
A Toolbox to Improve Algorithms for Insulin-Dosing Decision Support
Donsa, K.; Plank, J.; Schaupp, L.; Mader, J. K.; Truskaller, T.; Tschapeller, B.; Höll, B.; Spat, S.; Pieber, T. R.
2014-01-01
Summary Background Standardized insulin order sets for subcutaneous basal-bolus insulin therapy are recommended by clinical guidelines for the inpatient management of diabetes. The algorithm based GlucoTab system electronically assists health care personnel by supporting clinical workflow and providing insulin-dose suggestions. Objective To develop a toolbox for improving clinical decision-support algorithms. Methods The toolbox has three main components. 1) Data preparation: Data from several heterogeneous sources is extracted, cleaned and stored in a uniform data format. 2) Simulation: The effects of algorithm modifications are estimated by simulating treatment workflows based on real data from clinical trials. 3) Analysis: Algorithm performance is measured, analyzed and simulated by using data from three clinical trials with a total of 166 patients. Results Use of the toolbox led to algorithm improvements as well as the detection of potential individualized subgroup-specific algorithms. Conclusion These results are a first step towards individualized algorithm modifications for specific patient subgroups. PMID:25024768
Marsidi, Nick; van den Bergh, Maurice W H M; Luijendijk, Roland W
2014-01-01
To provide the best marketing strategy for a private clinic, knowledge of patients' preferences is essential. In marketing, conjoint analysis has been frequently used to calculate which attributes of a product are most valuable to consumers. This study investigates the relative importance of attributes that influence the selection and decision-making process when choosing an aesthetic private clinic, using conjoint analysis. The following attributes were chosen by the senior author (R.W.L.) and a marketing and communications director after a preselection of 25 randomly selected people: relative cost of the procedure, travel time, experience of the plastic surgeon, size of the clinic, method of referral, and online presentation. The attributes were then divided into levels. Using a random factor conducted by SPSS, 18 different scenarios were created and rated online by 150 potential patients before their potential visit or consultation. The patients could rate these scenarios on a scale from 1 to 7 with respect to the likeliness of visiting the clinic. The most important attribute was experience of the surgeon (35.6 percent), followed by method of referral (21.5 percent), travel time (14.2 percent), cost of procedure (12.9 percent), online presentation (9.7 percent), and size of the clinic (6.1 percent). Six of 16 levels gave a negative influence on the decision making. The authors' study shows that the two most important attributes are the experience of the surgeon and the method of referral and that conjoint analysis is effective in determining patients' preferences. It also shows which levels positively or negatively contribute per attribute.
Influence of patients' socioeconomic status on clinical management decisions: a qualitative study.
Bernheim, Susannah M; Ross, Joseph S; Krumholz, Harlan M; Bradley, Elizabeth H
2008-01-01
Little is known about how patients' socioeconomic status (SES) influences physicians' clinical management decisions, although this information may have important implications for understanding inequities in health care quality. We investigated physician perspectives on how patients' SES influences care. The study consisted of in-depth semistructured interviews with primary care physicians in Connecticut. Investigators coded interviews line by line and refined the coding structure and interview guide based on successive interviews. Recurrent themes emerged through iterative analysis of codes and tagged quotations. We interviewed 18 physicians from varied practice settings, 6 female, 9 from minority racial backgrounds, and 3 of Hispanic ethnicity. Four themes emerged from our interviews: (1) physicians held conflicting views about the effect of patient SES on clinical management, (2) physicians believed that changes in clinical management based on the patient's SES were made in the patient's interest, (3) physicians varied in the degree to which they thought changes in clinical management influenced patient outcomes, and (4) physicians faced personal and financial strains when caring for patients of low SES. Physicians indicated that patient SES did affect their clinical management decisions. As a result, physicians commonly undertook changes to their management plan in an effort to enhance patient outcomes, but they experienced numerous strains when trying to balance what they believed was feasible for the patient with what they perceived as established standards of care.
ERIC Educational Resources Information Center
Kostagiolas, Petros; Martzoukou, Konstantina; Georgantzi, Georgia; Niakas, Dimitris
2013-01-01
Introduction: This study investigated the information seeking behaviour and needs of parents of paediatric patients and their motives for seeking Internet-based information. Method: A questionnaire survey of 121 parents was conducted in a paediatric clinic of a Greek university hospital. Analysis: The data were analysed using SPSS; descriptive…
Nagase, Satoshi; Iyoda, Tomokazu; Kanno, Hiroshi; Akase, Tomohide; Arakawa, Ichiro; Inoue, Tadao; Uetsuka, Yoshio
2016-10-01
Phase III clinical trials have comfirmed that the S-1 plus oxaliplatin(SOX)is inferior to the capecitabine plus oxaliplatin (COX)regimen in the treatment of metastatic colorectal cancer.On the basis of these findings, we compared, using a clinical decision analysis-based approach, the cost-effectiveness of the SOX and COX regimens.Herein, we simulated the expected effects and costs of the SOX and COX regimens using the markov model.Clinical data were obtained from Hong's 2012 report.The cost data comprised the costs for pharmacist labor, material, inspection, and treatment for adverse event, as well as the total cost of care at the advanced stage.The result showed that the expected cost of the SOX and COX regimen was 1,538,330 yen, and 1,429,596 yen, respectively, with an expected survival rate of 29.18 months, and 28.63 months, respectively.The incremental cost-effectiveness ratio of the SOX regimen was 197,698 yen/month; thus, the SOX regimen was found to be more cost-effective that the COX regimen.
Understanding cognitive processes behind acceptance or refusal of phase I trials.
Pravettoni, Gabriella; Mazzocco, Ketti; Gorini, Alessandra; Curigliano, Giuseppe
2016-04-01
Participation in phase I trials gives patients the chance to obtain control over their disease by trying an experimental therapy. The patients' vulnerability, the informed consent process aiming at understanding the purpose and potential benefits of the phase I trial, and the complexity of the studies may impact the patient's final decision. Emotionally difficult health conditions may induce patients to succumb to cognitive biases, allocating attention only on a part of the provided information. Filling the gap in patients' information process can foster the implementation of strategies to help physicians tailor clinical trials' communication providing personalized support and tailored medical information around patients' need, so avoiding cognitive biases in patients and improving informed shared decision quality. The aim of the present review article focuses on the analysis of cognitive and psychological factors that affect patients' decision to participate or not to early phase clinical trials. Copyright © 2016. Published by Elsevier Ireland Ltd.
Making the Right Treatment Decision Requires Consideration of Utility and Reconsideration of Value.
Rossi, Michael J; Lubowitz, James H; Brand, Jefferson C; Provencher, Matthew T
2017-02-01
To achieve a good clinical outcome, arthroscopic and related surgeons must choose the proper treatment, and the basis of this choice is accurate diagnosis. Generally, our clinical focus is on outcome, but outcome is achieved after the fact. While this seems obvious, arthroscopic and related surgeons-and our patients who participate in shared decision making-evaluate the utility, or usefulness, of potential treatments based on desired and expected benefits versus potential risks. Today, cost is frequently considered as a determinant of value in medicine and may be applied to the decision analysis, but if an individual patient perceives health to be priceless, cost becomes irrelevant. In the end, an individual patient's satisfaction is determined on a case-by-case basis. Proper choice of treatment cannot be formulaic. Copyright © 2016 Arthroscopy Association of North America. Published by Elsevier Inc. All rights reserved.
Do neonatologists limit parental decision-making authority? A Canadian perspective.
Albersheim, Susan G; Lavoie, Pascal M; Keidar, Yaron D
2010-12-01
According to the principles of family-centered care, fully informed parents and health care professionals are partners in the care of sick neonates. The aim of this study was to assess the attitudes of Canadian neonatologists towards the authority of parents to make life-and-death decisions for their babies. We interviewed 121 (74%) of the 164 practicing neonatologists in Canada (June 2004-March 2005), using scripted open-ended questions and common clinical scenarios. Data analysis employed interpretive description methodology. The main outcome measure was the intention of neonatologists to limit parental life-and-death decision-making authority, when they disagree with parental decisions. Neonatologists' self-rated respect for parental decision-making authority was 8/10. Most neonatologists thought that parents should be either primary decision-makers or part of the decision-making team. Fifty-six percent of neonatologists would limit parental decision-making authority if the parents' decision is not in the baby's "best interest". In response to common neonatal severe illness scenarios, up to 18% of neonatologists said they would limit parental decision-making, even if the chance of intact survival is very poor. For clinical scenarios with equally poor long-term outcomes, neonatologists were more likely to comply with parental wishes early in the life of a baby, particularly with documented brain injury. Canadian neonatologists espouse high regard for parental decision-making authority, but are prepared to limit parental authority if the parents' decision is not thought to be in the baby's best interest. Although neonatologists advise parents that treatment can be started at birth, and stopped later, this was only for early severe brain injury. Copyright © 2010 Elsevier Ltd. All rights reserved.
Sposato, Niklas S; Bjerså, Kristofer
2017-01-01
Assessment in manual therapy includes quantitative and qualitative procedures, and intervertebral motion palpation (IMP) is one of the core assessment methods in osteopathic practice. The aim of this study was to explore osteopathic practitioners' experiences of clinical decision-making and IMP as a diagnostic tool for planning and evaluation of osteopathic interventions. The study was conducted with semi-structured interviews that included eight informants. Content analysis was used as the analytical procedure. In total, three categories emerged from the analysis: strategic decision-making, diagnostic usability of IMP, and treatment applicability of IMP. The study indicated that IMP was considered relevant and was given particular importance in cases where IMP findings confirmed clinical information attained from other stages in the diagnostic process as a whole. However, IMP findings were experienced as less important if they were not correlated to other findings. Copyright © 2016 Elsevier Ltd. All rights reserved.
Adolescent decision making about participation in a hypothetical HIV vaccine trial.
Alexander, Andreia B; Ott, Mary A; Lally, Michelle A; Sniecinski, Kevin; Baker, Alyne; Zimet, Gregory D
2015-03-10
The purpose of this study was to examine the process of adolescent decision-making about participation in an HIV vaccine clinical trial, comparing it to adult models of informed consent with attention to developmental differences. As part of a larger study of preventive misconception in adolescent HIV vaccine trials, we interviewed 33 male and female 16-19-year-olds who have sex with men. Participants underwent a simulated HIV vaccine trial consent process, and then completed a semistructured interview about their decision making process when deciding whether or not to enroll in and HIV vaccine trial. An ethnographic content analysis approach was utilized. Twelve concepts related to adolescents' decision-making about participation in an HIV vaccine trial were identified and mapped onto Appelbaum and Grisso's four components of decision making capacity including understanding of vaccines and how they work, the purpose of the study, trial procedures, and perceived trial risks and benefits, an appreciation of their own situation, the discussion and weighing of risks and benefits, discussing the need to consult with others about participation, motivations for participation, and their choice to participate. The results of this study suggest that most adolescents at high risk for HIV demonstrate the key abilities needed to make meaningful decisions about HIV vaccine clinical trial participation. Published by Elsevier Ltd.
Xu, Richard H; Cheung, Annie W L; Wong, Eliza L Y
2017-08-01
To elucidate the association between health-related quality of life and shared decision-making among patients in Hong Kong after adjustment for potential confounding variables. A telephone survey was conducted with patients attending all public specialist outpatient clinics in Hong Kong between July and December 2014. The Specialist Outpatient Patient Experience Questionnaire and EQ-5D questionnaire were used to evaluate shared decision-making and quality of life, respectively. We performed a Tobit regression analysis to examine the associations between shared decision-making and quality of life after adjustment for known social, economic and health-related factors. Twenty-six of the Hospital Authority's specialist outpatient clinics. Patients aged 18 years or older who attended one of the Hospital Authority's specialist outpatient clinics between July and November 2014. Shared decision-making and quality of life score. Overall, 13 966 patients completed the study. The group reporting partial involvement in decision-making had slightly higher EQ-5D scores than the 'not involved' group and the 'fully involved' group. EQ-5D scores were higher among subjects who were younger, male, and had a higher level of education. Respondents living alone and living in institutions scored lower on the EQ-5D than patients living with families. Important differences in the relationship between the attitudes towards shared decision-making and quality of life were identified among patients. These associations should be taken into consideration when promoting patient-centred care and improving health professional-patient communication. © The Author 2017. Published by Oxford University Press in association with the International Society for Quality in Health Care. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com
Rigoard, P; Slavin, K
2015-03-01
In the context of failed back surgery syndrome (FBSS) treatment, the current practice in neurostimulation varies from center-to-center and most clinical decisions are based on an individual diagnosis. Neurostimulation evaluation tools and pain relief assessment are of major concern, as they now constitute one of the main biases of clinical trials. Moreover, the proliferation of technological devices, in a fertile and unsatisfied market, fosters and only furthers the confusion. There are three options available to apply scientific debates to our daily neurostimulation practice: intentional ignorance, standardized evidence-based practice or alternative data mining approach. In view of the impossibility of conducting multiple randomized clinical trials comparing various devices, one by one, the proposed concept would be to redefine the indications and the respective roles of the various spinal cord and peripheral nerve stimulation devices with large-scale computational modeling/data mining approach, by conducting a multicenter prospective database registry, supported by a clinician's global network called "PROBACK". We chose to specifically analyze 6 parameters: device coverage performance/coverage selectivity/persistence of the long-term electrical response (technical criteria) and comparative mapping of patient pain relief/persistence of the long-term clinical response/safety and complications occurrence (clinical criteria). Two types of analysis will be performed: immediate analysis (including cost analysis) and computational analysis, i.e. demonstration of the robustness of certain correlations of variables, in order to extract response predictors. By creating an international prospective database, the purpose of the PROBACK project was to set up a process of extraction and comparative analysis of data derived from the selection, implantation and follow-up of FBSS patients candidates for implanted neurostimulation. This evaluation strategy should help to change the opinions of each implanter and each health system towards a more rational decision-making approach subtended by mathematical reality. Copyright © 2014 Elsevier Masson SAS. All rights reserved.
A review of the literature: midwifery decision-making and birth.
Jefford, Elaine; Fahy, Kathleen; Sundin, Deborah
2010-12-01
Clinical decision-making was initially studied in medicine where hypothetico-deductive reasoning is the model for decision-making. The nursing perspective on clinical decision-making has largely been shaped by Patricia Benner's ground breaking work. Benner claimed expert nurses use humanistic-intuitive ways of making clinical decisions rather than the 'rational reasoning' as claimed by medicine. Clinical decision-making in midwifery is not the same as either nursing or medical decision-making because of the woman-midwife partnership where the woman is the ultimate decision-maker. CINHAL, Medline and Cochrane databases were systematically searched using key words derived from the guiding question. A review of the decision-making research literature in midwifery was undertaken where studies were published in English. The selection criteria for papers were: only research papers of direct relevance to the guiding research question were included in the review. Decision-making is under-researched in midwifery and more specifically birth, as only 4 research articles met the inclusion criteria in this review. Three of the studies involved qualified midwives, and one involved student midwives. Two studies were undertaken in England, one in Scotland and one in Sweden. The major findings synthesised from this review, are that; (1) midwifery decision-making during birth is socially negotiated involving hierarchies of surveillance and control; (2) the role of the woman in shared decision-making during birth has not been explored by midwifery research; (3) clinical decision-making encompasses clinical reasoning as essential but not sufficient for midwives to actually implement their preferred decision. We argue that existing research does not inform the discipline of the complexity of midwifery clinical decision-making during birth. A well-designed study would involve investigating the clinical reasoning skills of the midwife, her relationship with the woman, the context of the particular birthing unit and the employment status of the midwife. The role of the woman as decision-maker in her own care during birth also needs careful research attention. Copyright © 2010 Australian College of Midwives. All rights reserved.
Freidl, Marion; Pesola, Francesca; Konrad, Jana; Puschner, Bernd; Kovacs, Attila Istvan; De Rosa, Corrado; Fiorillo, Andrea; Krogsgaard Bording, Malene; Kawohl, Wolfram; Rössler, Wulf; Nagy, Marietta; Munk-Jørgensen, Povl; Slade, Mike
2016-06-01
Clinical decision making is an important aspect of mental health care. Predictors of how patients experience decision making and whether decisions are implemented are underresearched. This study investigated the relationship between decision topic and involvement in the decision, satisfaction with it, and its subsequent implementation from both staff and patient perspectives. As part of the Clinical Decision Making and Outcome in Routine Care for People With Severe Mental Illness study, patients (N=588) and their providers (N=213) were recruited from community-based mental health services in six European countries. Both completed bimonthly assessments for one year using the Clinical Decision Making in Routine Care Scale to assess the decision topic and implementation; both also completed the Clinical Decision Making Involvement and Satisfaction Scale. Three categories of decision topics were determined: treatment (most frequently cited), social, and financial. The topic identified as most important remained stable over the follow-up. Patients were more likely to rate their involvement as active rather than passive for social decisions (odds ratio [OR]=5.7, p<.001) and financial decisions (OR=9.5, p<.001). They were more likely to report higher levels of satisfaction rather than lower levels for social decisions (OR=1.5, p=.01) and financial decisions (OR=1.7, p=.01). Social decisions were more likely to be partly implemented (OR=3.0, p<.001) or fully implemented (OR=1.7, p=.03) than not implemented. Patients reported poorer involvement, satisfaction, and implementation in regard to treatment-related decisions, compared with social and financial decisions. Clinicians may need to employ different interactional styles for different types of decisions to maximize satisfaction and decision implementation.
Using statistical process control to make data-based clinical decisions.
Pfadt, A; Wheeler, D J
1995-01-01
Applied behavior analysis is based on an investigation of variability due to interrelationships among antecedents, behavior, and consequences. This permits testable hypotheses about the causes of behavior as well as for the course of treatment to be evaluated empirically. Such information provides corrective feedback for making data-based clinical decisions. This paper considers how a different approach to the analysis of variability based on the writings of Walter Shewart and W. Edwards Deming in the area of industrial quality control helps to achieve similar objectives. Statistical process control (SPC) was developed to implement a process of continual product improvement while achieving compliance with production standards and other requirements for promoting customer satisfaction. SPC involves the use of simple statistical tools, such as histograms and control charts, as well as problem-solving techniques, such as flow charts, cause-and-effect diagrams, and Pareto charts, to implement Deming's management philosophy. These data-analytic procedures can be incorporated into a human service organization to help to achieve its stated objectives in a manner that leads to continuous improvement in the functioning of the clients who are its customers. Examples are provided to illustrate how SPC procedures can be used to analyze behavioral data. Issues related to the application of these tools for making data-based clinical decisions and for creating an organizational climate that promotes their routine use in applied settings are also considered.
Kennedy, Joshua L; Robinson, Derek; Christophel, Jared; Borish, Larry; Payne, Spencer
2014-01-01
The purpose of the study was to determine the age at which initiation of specific subcutaneous immunotherapy (SCIT) becomes more cost-effective than continued lifetime intranasal steroid (NS) therapy in the treatment of allergic rhinitis, with the use of a decision analysis model. A Markov decision analysis model was created for this study. Economic analyses were performed to identify "break-even" points in the treatment of allergic rhinitis with the use of SCIT and NS. Efficacy rates for therapy and cost data were collected from the published literature. Models in which there was only incomplete improvement while receiving SCIT were also evaluated for economic break-even points. The primary perspective of the study was societal. Multiple break-even point curves were obtained corresponding to various clinical scenarios. For patients with seasonal allergic rhinitis requiring NS (i.e., fluticasone) 6 months per year, the age at which initiation of SCIT provides long-term direct cost advantage is less than 41 years. For patients with perennial rhinitis symptoms requiring year-round NS, the cut-off age for SCIT cost-effectiveness increases to 60 years. Hypothetical subjects who require continued NS treatment (50% reduction of previous dosage) while receiving SCIT also display break-even points, whereby it is economically advantageous to consider allergy referral and SCIT, dependent on the cost of the NS prescribed. The age at which SCIT provides economic advantages over NS in the treatment of allergic rhinitis depends on multiple clinical factors. Decision analysis models can assist the physician in accounting for these factors and customize patient counseling with regard to treatment options.
Nierenberg, Andrew A; Smoller, Jordan W; Eidelman, Polina; Wu, Yelena P; Tilley, Claire A
2008-01-01
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. (c) 2008 S. Karger AG, Basel.
Mandzuka, Mensur; Begic, Edin; Boskovic, Dusanka; Begic, Zijo; Masic, Izet
2017-06-01
This paper presents mobile application implementing a decision support system for acid-base disorder diagnosis and treatment recommendation. The application was developed using the official integrated development environment for the Android platform (to maximize availability and minimize investments in specialized hardware) called Android Studio. The application identifies disorder, based on the blood gas analysis, evaluates whether the disorder has been compensated, and based on additional input related to electrolyte imbalance, provides recommendations for treatment. The application is a tool in the hands of the user, which provides assistance during acid-base disorders treatment. The application will assist the physician in clinical practice and is focused on the treatment in intensive care.
Cook, Sharon A; Damato, Bertil; Marshall, Ernie; Salmon, Peter
2011-12-01
Influential views on how to protect patient autonomy in clinical care have been greatly shaped by rational and deliberative models of decision-making. Our aim was to understand how the general principle of respecting autonomy can be reconciled with the local reality of obtaining consent in a clinical situation that precludes extended deliberation. We interviewed 22 patients with intraocular melanoma who had been offered cytogenetic tumour typing to indicate whether the tumour was likely to shorten life considerably. They were interviewed before and/or up to 36 months after receiving cytogenetic results. Patients described their decision-making about the test and how they anticipated and used the results. Their accounts were analysed qualitatively, using inconsistencies at a descriptive level to guide interpretative analysis. Patients did not see a decision to be made. For those who accepted testing, their choice reflected trust of what the clinicians offered them. Patients anticipated that a good prognosis would be reassuring, but this response was not evident. Although they anticipated that a poor prognosis would enable end-of-life planning, adverse results were interpreted hopefully. In general, the meaning of the test for patients was not separable from ongoing care. Models of decision-making and associated consent procedures that emphasize patients' active consideration of isolated decision-making opportunities are invalid for clinical situations such as this. Hence, responsibility for ensuring that a procedure protects patients' interests rests with practitioners who offer it and cannot be delegated to patients. © 2010 Blackwell Publishing Ltd.
Maxson, Pamela M.; Dozois, Eric J.; Holubar, Stefan D.; Wrobleski, Diane M.; Dube, Joyce A. Overman; Klipfel, Janee M.; Arnold, Jacqueline J.
2011-01-01
OBJECTIVE: To determine whether interdisciplinary simulation team training can positively affect registered nurse and/or physician perceptions of collaboration in clinical decision making. PARTICIPANTS AND METHODS: Between March 1 and April 21, 2009, a convenience sample of volunteer nurses and physicians was recruited to undergo simulation training consisting of a team response to 3 clinical scenarios. Participants completed the Collaboration and Satisfaction About Care Decisions (CSACD) survey before training and at 2 weeks and 2 months after training. Differences in CSACD summary scores between the time points were assessed with paired t tests. RESULTS: Twenty-eight health care professionals (19 nurses, 9 physicians) underwent simulation training. Nurses were of similar age to physicians (27.3 vs 34.5 years; p=.82), were more likely to be women (95.0% vs 12.5%; p<.001), and were less likely to have undergone prior simulation training (0% vs 37.5%; p=.02). The pretest showed that physicians were more likely to perceive that open communication exists between nurses and physicians (p=.04) and that both medical and nursing concerns influence the decision-making process (p=.02). Pretest CSACD analysis revealed that most participants were dissatisfied with the decision-making process. The CSACD summary score showed significant improvement from baseline to 2 weeks (4.2 to 5.1; p<.002), a trend that persisted at 2 months (p<.002). CONCLUSION: Team training using high-fidelity simulation scenarios promoted collaboration between nurses and physicians and enhanced the patient care decision-making process. PMID:21193653
Application of HTA research on policy decision-making.
Youngkong, Sitaporn
2014-05-01
This article provides an overview of the potential uses of health technology assessment (HTA) in health technology or health intervention-related policy decision-making. It summarises the role of HTA in policy planning, health system investment, price negotiation, development of clinical practice guidelines, and communication with health professionals. While the multifaceted nature of HTA means that some aspects of the data can result in conflicting conclusions, the comprehensive approach of HTA is still recommended. To help minimise the potential conflicts within HTA data, a multicriteria decision analysis (MCDA) approach is recommended as a way to assess a number of decision criteria simultaneously. A combination of HTA with MCDA allows policy decision-making to be undertaken in an empirically rigorous and rational way. This combination can be used to support policy decision-makers in Thailand and help them prioritise topics for assessment and make informed health benefit package coverage decisions. This approach enhances the legitimacy of policy decisions by increasing the transparency, systematic nature, and inclusiveness of the process.
Kennedy, Tara J T; Regehr, Glenn; Baker, G Ross; Lingard, Lorelei
2009-02-09
To develop a conceptual framework of the influences on medical trainees' decisions regarding requests for clinical support from a supervisor. Phase 1: members of teaching teams in internal and emergency medicine were observed during regular clinical activities (216 hours) and subsequently completed brief interviews. Phase 2: 36 in depth interviews were conducted using videotaped vignettes to probe tacit influences on decisions to request support. Data collection and analysis used grounded theory methods. Three teaching hospitals in an urban setting in Canada. 124 members of teaching teams on general internal medicine wards and in the emergency department, comprising 31 attending physicians, 57 junior and senior residents, 28 medical students, and eight nurses. Purposeful sampling to saturation was conducted. Trainees' decisions about whether or not to seek clinical support were influenced by three issues: the clinical question (clinical importance, scope of practice), supervisor factors (availability, approachability), and trainee factors (skill, desire for independence, evaluation). Trainees perceived that requesting frequent/inappropriate support threatened their credibility and used rhetorical strategies to preserve credibility. These strategies included building a case for the importance of requests, saving requests for opportune moments, making a plan before requesting support, and targeting requests to specific team members. Trainees consider not only clinical implications but also professional credibility when requesting support from clinical supervisors. Exposing the complexity of this process provides the opportunity to make changes to training programmes to promote timely supervision and provides a framework for further exploration of the impact of clinical training on quality of care of patients.
Straus, Sharon E.
2008-01-01
BACKGROUND Studies indicate a gap between evidence and clinical practice in osteoporosis management. Tools that facilitate clinical decision making at the point of care are promising strategies for closing these practice gaps. OBJECTIVE To systematically review the literature to identify and describe the effectiveness of tools that support clinical decision making in osteoporosis disease management. DATA SOURCES Medline, EMBASE, CINAHL, and EBM Reviews (CDSR, DARE, CCTR, and ACP J Club), and contact with experts in the field. REVIEW METHODS Randomized controlled trials (RCTs) in any language from 1966 to July 2006 investigating disease management interventions in patients at risk for osteoporosis. Outcomes included fractures and bone mineral density (BMD) testing. Two investigators independently assessed articles for relevance and study quality, and extracted data using standardized forms. RESULTS Of 1,246 citations that were screened for relevance, 13 RCTs met the inclusion criteria. Reported study quality was generally poor. Meta-analysis was not done because of methodological and clinical heterogeneity; 77% of studies included a reminder or education as a component of their intervention. Three studies of reminders plus education targeted to physicians and patients showed increased BMD testing (RR range 1.43 to 8.67) and osteoporosis medication use (RR range 1.60 to 8.67). A physician reminder plus a patient risk assessment strategy found reduced fractures [RR 0.58, 95% confidence interval (CI) 0.37 to 0.90] and increased osteoporosis therapy (RR 2.44, CI 1.43 to 4.17). CONCLUSION Multi-component tools that are targeted to physicians and patients may be effective for supporting clinical decision making in osteoporosis disease management. Electronic supplementary material The online version of this article (doi:10.1007/s11606-008-0812-9) contains supplementary material, which is available to authorized users. PMID:18836782
Bautista-Molano, Wilson; Landewé, Robert B M; Serna, Cesar; Valle-Oñate, Rafael; van der Heijde, Désirée
2017-01-01
To evaluate the patients' characteristics associated with the clinical decision to request SI-MRI and/or HLA-B27 in patients with SpA in daily practice. Patients referred to a rheumatology outpatient-clinic in a national referral-centre were selected. Patients with a clinical diagnosis of SpA according to the rheumatologist were included. SI-MRI and HLA-B27 was available for patients in whom the rheumatologists had ordered these tests. Characteristics associated with ordering SI-MRI or HLA-B27 were identified with univariable analyses. Variables with p-value <0.05 and >80% completeness were selected for further analysis. A multivariable logistic regression analysis was used to evaluate the determinants related with the decision to perform SI-MRI and/or HLA-B27 and odds ratios with 95% confidence intervals were calculated. In total, 581 patients with SpA were included in the cohort, 72% were men, mean age 34.6±12.1 and disease duration 7.3±9.7 years. Of these patients, 24% (n=137) had SI-MRI and 77% (n=441) had HLA-B27 tests ordered. Independently predictive factors for ordering a SI-MRI were the presence of IBP (OR=1.81), enthesitis (OR=1.57) and the number of initial-symptoms at presentation (OR=1.27 per additional symptom present). Independently predictive factors of HLA-B27 testing were the number of initial-symptoms (OR=1.45 per symptom) and uveitis (OR=3.19). This study strongly suggests that rheumatologists use certain clinical clues to decide if they order expensive and scarce tests in the diagnostic work-up of SpA patients. These manifestations may increase the efficiency of these tests in clinical practice and suggest that clinical reasoning follows principles of Bayesian theory.
2011-01-01
Background Workflow engine technology represents a new class of software with the ability to graphically model step-based knowledge. We present application of this novel technology to the domain of clinical decision support. Successful implementation of decision support within an electronic health record (EHR) remains an unsolved research challenge. Previous research efforts were mostly based on healthcare-specific representation standards and execution engines and did not reach wide adoption. We focus on two challenges in decision support systems: the ability to test decision logic on retrospective data prior prospective deployment and the challenge of user-friendly representation of clinical logic. Results We present our implementation of a workflow engine technology that addresses the two above-described challenges in delivering clinical decision support. Our system is based on a cross-industry standard of XML (extensible markup language) process definition language (XPDL). The core components of the system are a workflow editor for modeling clinical scenarios and a workflow engine for execution of those scenarios. We demonstrate, with an open-source and publicly available workflow suite, that clinical decision support logic can be executed on retrospective data. The same flowchart-based representation can also function in a prospective mode where the system can be integrated with an EHR system and respond to real-time clinical events. We limit the scope of our implementation to decision support content generation (which can be EHR system vendor independent). We do not focus on supporting complex decision support content delivery mechanisms due to lack of standardization of EHR systems in this area. We present results of our evaluation of the flowchart-based graphical notation as well as architectural evaluation of our implementation using an established evaluation framework for clinical decision support architecture. Conclusions We describe an implementation of a free workflow technology software suite (available at http://code.google.com/p/healthflow) and its application in the domain of clinical decision support. Our implementation seamlessly supports clinical logic testing on retrospective data and offers a user-friendly knowledge representation paradigm. With the presented software implementation, we demonstrate that workflow engine technology can provide a decision support platform which evaluates well against an established clinical decision support architecture evaluation framework. Due to cross-industry usage of workflow engine technology, we can expect significant future functionality enhancements that will further improve the technology's capacity to serve as a clinical decision support platform. PMID:21477364
Saigal, Christopher S; Lambrechts, Sylvia I; Seenu Srinivasan, V; Dahan, Ely
2017-06-01
Many guidelines advocate the use of shared decision making for men with newly diagnosed prostate cancer. Decision aids can facilitate the process of shared decision making. Implicit in this approach is the idea that physicians understand which elements of treatment matter to patients. Little formal work exists to guide physicians or developers of decision aids in identifying these attributes. We use a mixed-methods technique adapted from marketing science, the 'Voice of the Patient', to describe and identify treatment elements of value for men with localized prostate cancer. We conducted semi-structured interviews with 30 men treated for prostate cancer in the urology clinic of the West Los Angeles Veteran Affairs Medical Center. We used a qualitative analysis to generate themes in patient narratives, and a quantitative approach, agglomerative hierarchical clustering, to identify attributes of treatment that were most relevant to patients making decisions about prostate cancer. We identified five 'traditional' prostate cancer treatment attributes: sexual dysfunction, bowel problems, urinary problems, lifespan, and others' opinions. We further identified two novel treatment attributes: a treatment's ability to validate a sense of proactivity and the need for an incision (separate from risks of surgery). Application of a successful marketing technique, the 'Voice of the Customer', in a clinical setting elicits non-obvious attributes that highlight unique patient decision-making concerns. Use of this method in the development of decision aids may result in more effective decision support.
Critical thinking: the development of an essential skill for nursing students.
Papathanasiou, Ioanna V; Kleisiaris, Christos F; Fradelos, Evangelos C; Kakou, Katerina; Kourkouta, Lambrini
2014-08-01
Critical thinking is defined as the mental process of actively and skillfully perception, analysis, synthesis and evaluation of collected information through observation, experience and communication that leads to a decision for action. In nursing education there is frequent reference to critical thinking and to the significance that it has in daily clinical nursing practice. Nursing clinical instructors know that students face difficulties in making decisions related to clinical practice. The main critical thinking skills in which nursing students should be exercised during their studies are critical analysis, introductory and concluding justification, valid conclusion, distinguish of facts and opinions, evaluation the credibility of information sources, clarification of concepts and recognition of conditions. Specific behaviors are essentials for enhancing critical thinking. Nursing students in order to learn and apply critical thinking should develop independence of thought, fairness, perspicacity in personal and social level, humility, spiritual courage, integrity, perseverance, self-confidence, interest for research and curiosity. Critical thinking is an essential process for the safe, efficient and skillful nursing practice. The nursing education programs should adopt attitudes that promote critical thinking and mobilize the skills of critical reasoning.
Critical Thinking: The Development of an Essential Skill for Nursing Students
Papathanasiou, Ioanna V.; Kleisiaris, Christos F.; Fradelos, Evangelos C.; Kakou, Katerina; Kourkouta, Lambrini
2014-01-01
Critical thinking is defined as the mental process of actively and skillfully perception, analysis, synthesis and evaluation of collected information through observation, experience and communication that leads to a decision for action. In nursing education there is frequent reference to critical thinking and to the significance that it has in daily clinical nursing practice. Nursing clinical instructors know that students face difficulties in making decisions related to clinical practice. The main critical thinking skills in which nursing students should be exercised during their studies are critical analysis, introductory and concluding justification, valid conclusion, distinguish of facts and opinions, evaluation the credibility of information sources, clarification of concepts and recognition of conditions. Specific behaviors are essentials for enhancing critical thinking. Nursing students in order to learn and apply critical thinking should develop independence of thought, fairness, perspicacity in personal and social level, humility, spiritual courage, integrity, perseverance, self-confidence, interest for research and curiosity. Critical thinking is an essential process for the safe, efficient and skillful nursing practice. The nursing education programs should adopt attitudes that promote critical thinking and mobilize the skills of critical reasoning. PMID:25395733
Exploring factors affecting registered nurses' pursuit of postgraduate education in Australia.
Ng, Linda; Eley, Robert; Tuckett, Anthony
2016-12-01
The aim of this study was to explore the factors influencing registered nurses' pursuit of postgraduate education in specialty nursing practice in Australia. Despite the increased requirement for postgraduate education for advanced practice, little has been reported on the contributory factors involved in the decision to undertake further education. The Nurses' Attitudes Towards Postgraduate Education instrument was administered to 1632 registered nurses from the Nurses and Midwives e-Cohort Study across Australia, with a response rate of 35.9% (n = 568). Data reduction techniques using principal component analysis with varimax rotation were used. The analysis identified a three-factor solution for 14 items, accounting for 52.5% of the variance of the scale: "facilitators," "professional recognition," and "inhibiting factors." Facilitators of postgraduate education accounted for 28.5% of the variance, including: (i) improves knowledge; (ii) increases nurses' confidence in clinical decision-making; (iii) enhances nurses' careers; (iv) improves critical thinking; (v) improves nurses' clinical skill; and (vi) increased job satisfaction. This new instrument has potential clinical and research applications to support registered nurses' pursuit of postgraduate education. © 2016 John Wiley & Sons Australia, Ltd.
MacGillivray, Brian H
2017-08-01
In many environmental and public health domains, heuristic methods of risk and decision analysis must be relied upon, either because problem structures are ambiguous, reliable data is lacking, or decisions are urgent. This introduces an additional source of uncertainty beyond model and measurement error - uncertainty stemming from relying on inexact inference rules. Here we identify and analyse heuristics used to prioritise risk objects, to discriminate between signal and noise, to weight evidence, to construct models, to extrapolate beyond datasets, and to make policy. Some of these heuristics are based on causal generalisations, yet can misfire when these relationships are presumed rather than tested (e.g. surrogates in clinical trials). Others are conventions designed to confer stability to decision analysis, yet which may introduce serious error when applied ritualistically (e.g. significance testing). Some heuristics can be traced back to formal justifications, but only subject to strong assumptions that are often violated in practical applications. Heuristic decision rules (e.g. feasibility rules) in principle act as surrogates for utility maximisation or distributional concerns, yet in practice may neglect costs and benefits, be based on arbitrary thresholds, and be prone to gaming. We highlight the problem of rule-entrenchment, where analytical choices that are in principle contestable are arbitrarily fixed in practice, masking uncertainty and potentially introducing bias. Strategies for making risk and decision analysis more rigorous include: formalising the assumptions and scope conditions under which heuristics should be applied; testing rather than presuming their underlying empirical or theoretical justifications; using sensitivity analysis, simulations, multiple bias analysis, and deductive systems of inference (e.g. directed acyclic graphs) to characterise rule uncertainty and refine heuristics; adopting "recovery schemes" to correct for known biases; and basing decision rules on clearly articulated values and evidence, rather than convention. Copyright © 2017. Published by Elsevier Ltd.
Nurses' pressure ulcer related judgements and decisions in clinical practice: a systematic review.
Samuriwo, Ray; Dowding, Dawn
2014-12-01
Pressure ulcers are considered to be an adverse outcome of care that should never occur in clinical practice. The formation of a pressure ulcer is also perceived to be an indicator of poor quality nursing care. Therefore, pressure ulcer prevention is a priority for nurses, healthcare professionals and healthcare organisations throughout the world. A key factor in pressure ulcer prevention and management is individual nurse decision making. To synthesise the literature on the judgement and decision making of nurses in relation to the assessment, prevention, grading and management of pressure ulcers in all care settings (hospital and community). A systematic search of published literature relating to judgement and decision making in nurses, with a focus on the prevention and management of pressure ulcers. A search of electronic databases from 1992 to present, together with hand searching of the reference lists of retrieved publications, to identify published papers that reported results of studies evaluating the decision making of nurses in relation to the prevention and management of pressure ulcers. Abstracts were independently reviewed by two authors and full text of potentially relevant articles retrieved. Each paper included in this systematic review was evaluated using recognised appraisal criteria relevant to the specific study design. Included papers provided empirical data on key aspects of nurses' pressure ulcer related judgements and decision making. Data were synthesised into themes using narrative analysis. Sixteen studies and one systematic review were included in the review, focusing on pressure ulcer risk assessment, pressure ulcer prevention, grading of pressure ulcers and treatment decisions. The results indicated that assessment tools were not routinely used to identify pressure ulcer risk, and that nurses rely on their own knowledge and experience rather than research evidence to decide what skin care to deliver. Emphasising pressure ulcer risk assessment and pressure ulcer grading in clinical practice is unlikely to deliver improved outcomes. Further research into nurses' pressure ulcer related judgements and decision making is needed and clinicians must focus on the consistent delivery of high quality care to prevent and mange pressure ulcers to all patients in clinical practice. Crown Copyright © 2014. Published by Elsevier Ltd. All rights reserved.
DesAutels, Spencer J.; Fox, Zachary E.; Giuse, Dario A.; Williams, Annette M.; Kou, Qing-hua; Weitkamp, Asli; Neal R, Patel; Bettinsoli Giuse, Nunzia
2016-01-01
Clinical decision support (CDS) knowledge, embedded over time in mature medical systems, presents an interesting and complex opportunity for information organization, maintenance, and reuse. To have a holistic view of all decision support requires an in-depth understanding of each clinical system as well as expert knowledge of the latest evidence. This approach to clinical decision support presents an opportunity to unify and externalize the knowledge within rules-based decision support. Driven by an institutional need to prioritize decision support content for migration to new clinical systems, the Center for Knowledge Management and Health Information Technology teams applied their unique expertise to extract content from individual systems, organize it through a single extensible schema, and present it for discovery and reuse through a newly created Clinical Support Knowledge Acquisition and Archival Tool (CS-KAAT). CS-KAAT can build and maintain the underlying knowledge infrastructure needed by clinical systems. PMID:28269846
de Bruin, Jeroen S; Adlassnig, Klaus-Peter; Leitich, Harald; Rappelsberger, Andrea
2018-01-01
Evidence-based clinical guidelines have a major positive effect on the physician's decision-making process. Computer-executable clinical guidelines allow for automated guideline marshalling during a clinical diagnostic process, thus improving the decision-making process. Implementation of a digital clinical guideline for the prevention of mother-to-child transmission of hepatitis B as a computerized workflow, thereby separating business logic from medical knowledge and decision-making. We used the Business Process Model and Notation language system Activiti for business logic and workflow modeling. Medical decision-making was performed by an Arden-Syntax-based medical rule engine, which is part of the ARDENSUITE software. We succeeded in creating an electronic clinical workflow for the prevention of mother-to-child transmission of hepatitis B, where institution-specific medical decision-making processes could be adapted without modifying the workflow business logic. Separation of business logic and medical decision-making results in more easily reusable electronic clinical workflows.
Applying a family systems lens to proxy decision making in clinical practice and research.
Rolland, John S; Emanuel, Linda L; Torke, Alexia M
2017-03-01
When patients are incapacitated and face serious illness, family members must make medical decisions for the patient. Medical decision sciences give only modest attention to the relationships among patients and their family members, including impact that these relationships have on the decision-making process. A review of the literature reveals little effort to systematically apply a theoretical framework to the role of family interactions in proxy decision making. A family systems perspective can provide a useful lens through which to understand the dynamics of proxy decision making. This article considers the mutual impact of family systems on the processes and outcomes of proxy decision making. The article first reviews medical decision science's evolution and focus on proxy decision making and then reviews a family systems approach, giving particular attention to Rolland's Family Systems Illness Model. A case illustrates how clinical practice and how research would benefit from bringing family systems thinking to proxy decisions. We recommend including a family systems approach in medical decision science research and clinical practices around proxy decisions making. We propose that clinical decisions could be less conflicted and less emotionally troubling for families and clinicians if family systems approaches were included. This perspective opens new directions for research and novel approaches to clinical care. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
Interactive decision support in hepatic surgery
Dugas, Martin; Schauer, Rolf; Volk, Andreas; Rau, Horst
2002-01-01
Background Hepatic surgery is characterized by complicated operations with a significant peri- and postoperative risk for the patient. We developed a web-based, high-granular research database for comprehensive documentation of all relevant variables to evaluate new surgical techniques. Methods To integrate this research system into the clinical setting, we designed an interactive decision support component. The objective is to provide relevant information for the surgeon and the patient to assess preoperatively the risk of a specific surgical procedure. Based on five established predictors of patient outcomes, the risk assessment tool searches for similar cases in the database and aggregates the information to estimate the risk for an individual patient. Results The physician can verify the analysis and exclude manually non-matching cases according to his expertise. The analysis is visualized by means of a Kaplan-Meier plot. To evaluate the decision support component we analyzed data on 165 patients diagnosed with hepatocellular carcinoma (period 1996–2000). The similarity search provides a two-peak distribution indicating there are groups of similar patients and singular cases which are quite different to the average. The results of the risk estimation are consistent with the observed survival data, but must be interpreted with caution because of the limited number of matching reference cases. Conclusion Critical issues for the decision support system are clinical integration, a transparent and reliable knowledge base and user feedback. PMID:12003639
Wright, Adam; Sittig, Dean F
2008-12-01
In this paper, we describe and evaluate a new distributed architecture for clinical decision support called SANDS (Service-oriented Architecture for NHIN Decision Support), which leverages current health information exchange efforts and is based on the principles of a service-oriented architecture. The architecture allows disparate clinical information systems and clinical decision support systems to be seamlessly integrated over a network according to a set of interfaces and protocols described in this paper. The architecture described is fully defined and developed, and six use cases have been developed and tested using a prototype electronic health record which links to one of the existing prototype National Health Information Networks (NHIN): drug interaction checking, syndromic surveillance, diagnostic decision support, inappropriate prescribing in older adults, information at the point of care and a simple personal health record. Some of these use cases utilize existing decision support systems, which are either commercially or freely available at present, and developed outside of the SANDS project, while other use cases are based on decision support systems developed specifically for the project. Open source code for many of these components is available, and an open source reference parser is also available for comparison and testing of other clinical information systems and clinical decision support systems that wish to implement the SANDS architecture. The SANDS architecture for decision support has several significant advantages over other architectures for clinical decision support. The most salient of these are:
Müller-Staub, Maria; de Graaf-Waar, Helen; Paans, Wolter
2016-11-01
Nurses are accountable to apply the nursing process, which is key for patient care: It is a problem-solving process providing the structure for care plans and documentation. The state-of-the art nursing process is based on classifications that contain standardized concepts, and therefore, it is named Advanced Nursing Process. It contains valid assessments, nursing diagnoses, interventions, and nursing-sensitive patient outcomes. Electronic decision support systems can assist nurses to apply the Advanced Nursing Process. However, nursing decision support systems are missing, and no "gold standard" is available. The study aim is to develop a valid Nursing Process-Clinical Decision Support System Standard to guide future developments of clinical decision support systems. In a multistep approach, a Nursing Process-Clinical Decision Support System Standard with 28 criteria was developed. After pilot testing (N = 29 nurses), the criteria were reduced to 25. The Nursing Process-Clinical Decision Support System Standard was then presented to eight internationally known experts, who performed qualitative interviews according to Mayring. Fourteen categories demonstrate expert consensus on the Nursing Process-Clinical Decision Support System Standard and its content validity. All experts agreed the Advanced Nursing Process should be the centerpiece for the Nursing Process-Clinical Decision Support System and should suggest research-based, predefined nursing diagnoses and correct linkages between diagnoses, evidence-based interventions, and patient outcomes.
Application and Exploration of Big Data Mining in Clinical Medicine
Zhang, Yue; Guo, Shu-Li; Han, Li-Na; Li, Tie-Ling
2016-01-01
Objective: To review theories and technologies of big data mining and their application in clinical medicine. Data Sources: Literatures published in English or Chinese regarding theories and technologies of big data mining and the concrete applications of data mining technology in clinical medicine were obtained from PubMed and Chinese Hospital Knowledge Database from 1975 to 2015. Study Selection: Original articles regarding big data mining theory/technology and big data mining's application in the medical field were selected. Results: This review characterized the basic theories and technologies of big data mining including fuzzy theory, rough set theory, cloud theory, Dempster–Shafer theory, artificial neural network, genetic algorithm, inductive learning theory, Bayesian network, decision tree, pattern recognition, high-performance computing, and statistical analysis. The application of big data mining in clinical medicine was analyzed in the fields of disease risk assessment, clinical decision support, prediction of disease development, guidance of rational use of drugs, medical management, and evidence-based medicine. Conclusion: Big data mining has the potential to play an important role in clinical medicine. PMID:26960378
Thompson-Leduc, Philippe; Turcotte, Stéphane; Labrecque, Michel; Légaré, France
2016-06-28
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. We performed a secondary analysis of existing data sets from studies conducted in Primary Care Practice-Based Research Networks in Québec and Ontario, Canada. 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. 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. 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. 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. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/
Sherman, Kerry A; Shaw, Laura-Kate; Jørgensen, Lone; Harcourt, Diana; Cameron, Linda; Boyages, John; Elder, Elisabeth; Kirk, Judy; Tucker, Katherine
2017-10-01
Women diagnosed with breast cancer or ductal carcinoma in situ and those with a genetic susceptibility to developing this disease face the challenging decision of whether or not to undergo breast reconstruction following mastectomy. As part of a large randomized controlled trial, this qualitative study examined women's experiences of using the Breast RECONstruction Decision Aid (BRECONDA) and health professionals' feedback regarding the impact of this resource on patients' knowledge and decision making about breast reconstruction. Semistructured interviews were conducted with women who accessed the BRECONDA intervention (N = 36) and with their healthcare providers (N = 6). All interviews were transcribed verbatim and subjected to thematic analysis by 3 independent coders. Participants reported an overall positive impression, with all interviewees endorsing this decision aid as a useful resource for women considering reconstructive surgery. Thematic analysis of patient interviews revealed 4 themes: overall impressions and aesthetics; personal relevance and utility; introducing BRECONDA; and advantages and suggested improvements. Analysis of health professionals' interviews also revealed 4 themes: need for BRECONDA, impact of BRECONDA, potential difficulties that may arise in using the decision aid, and recommending BRECONDA to patients. Patients indicated that they derived benefit from this resource at all stages of their decision-making process, with the greatest perceived benefit being for those early in their breast reconstruction journey. These findings support the use of BRECONDA as an adjunct to clinical consultation and other information sources. Copyright © 2016 John Wiley & Sons, Ltd.
ERIC Educational Resources Information Center
Thorne, John C.; Coggins, Truman E.; Olson, Heather Carmichael; Astley, Susan J.
2007-01-01
Purpose: To evaluate classification accuracy and clinical feasibility of a narrative analysis tool for identifying children with a fetal alcohol spectrum disorder (FASD). Method: Picture-elicited narratives generated by 16 age-matched pairs of school-aged children (FASD vs. typical development [TD]) were coded for semantic elaboration and…
[Screening for cancer - economic consideration and cost-effectiveness].
Kjellberg, Jakob
2014-06-09
Cost-effectiveness analysis has become an accepted method to evaluate medical technology and allocate scarce health-care resources. Published decision analyses show that screening for cancer in general is cost-effective. However, cost-effectiveness analyses are only as good as the clinical data and the results are sensitive to the chosen methods and perspective of the analysis.
Gilmour, Joan; Harrison, Christine; Vohra, Sunita
2011-11-01
Our goal for this supplemental issue of Pediatrics was to consider what practitioners, parents, patients, institutions, and policy-makers need to take into account to make good decisions about using complementary and alternative medicine (CAM) to treat children and to develop guidelines for appropriate use. We began by explaining underlying concepts and principles in ethical, legal, and clinical reasoning and then used case scenarios to explore how they apply and identify gaps that remain in practice and policy. In this concluding article, we review our major findings, summarize our recommendations, and suggest further research. We focus on several key areas: practitioner and patient/parent relationships; decision-making; dispute resolution; standards of practice; hospital/health facility policies; patient safety; education; and research. Ethical principles, standards, and rules applicable when making decisions about conventional care for children apply to decision-making about CAM as well. The same is true of legal reasoning. Although CAM use has seldom led to litigation, general legal principles relied on in cases involving conventional medical care provide the starting point for analysis. Similarly, with respect to clinical decision-making, clinicians are guided by clinical judgment and the best interests of their patient. Whether a therapy is CAM or conventional, clinicians must weigh the relative risks and benefits of therapeutic options and take into account their patient's values, beliefs, and preferences. Consequently, many of our observations apply to conventional and CAM care and to both adult and pediatric patients.
Elwyn, Glyn; Rasmussen, Julie; Kinsey, Katharine; Firth, Jill; Marrin, Katy; Edwards, Adrian; Wood, Fiona
2018-02-01
Tools used in clinical encounters to illustrate to patients the risks and benefits of treatment options have been shown to increase shared decision making. However, we do not have good information about how these tools are viewed by clinicians and how clinicians think patients would react to their use. Our aim was to examine clinicians' views about the possible and actual use of tools designed to support patients and clinicians to collaborate and deliberate about treatment options, namely, Option Grid decision aids. We conducted a thematic analysis of qualitative interviews embedded in the intervention phase of a trial of an Option Grid decision aid for osteoarthritis of the knee. Interviews were conducted with 6 participating clinicians before they used the tool and again after clinicians had used the tool with 6 patients. In the first interview, clinicians voiced concerns that the tool would lead to an increase in encounter duration, patient resistance regarding involvement in decision making, and potential information overload. At the second interview, after minimal training, the clinicians reported that the tool had changed their usual way of communicating, and it was generally acceptable and helpful to integrate it into practice. After experiencing the use of Option Grids, clinicians became more willing to use the tools in their clinical encounters with patients. How best to introduce Option Grids to clinicians and adopt their use into practice will need careful consideration of context, workflow, and clinical pathways. © 2016 John Wiley & Sons, Ltd.
Clinical microbiology informatics.
Rhoads, Daniel D; Sintchenko, Vitali; Rauch, Carol A; Pantanowitz, Liron
2014-10-01
The clinical microbiology laboratory has responsibilities ranging from characterizing the causative agent in a patient's infection to helping detect global disease outbreaks. All of these processes are increasingly becoming partnered more intimately with informatics. Effective application of informatics tools can increase the accuracy, timeliness, and completeness of microbiology testing while decreasing the laboratory workload, which can lead to optimized laboratory workflow and decreased costs. Informatics is poised to be increasingly relevant in clinical microbiology, with the advent of total laboratory automation, complex instrument interfaces, electronic health records, clinical decision support tools, and the clinical implementation of microbial genome sequencing. This review discusses the diverse informatics aspects that are relevant to the clinical microbiology laboratory, including the following: the microbiology laboratory information system, decision support tools, expert systems, instrument interfaces, total laboratory automation, telemicrobiology, automated image analysis, nucleic acid sequence databases, electronic reporting of infectious agents to public health agencies, and disease outbreak surveillance. The breadth and utility of informatics tools used in clinical microbiology have made them indispensable to contemporary clinical and laboratory practice. Continued advances in technology and development of these informatics tools will further improve patient and public health care in the future. Copyright © 2014, American Society for Microbiology. All Rights Reserved.
Clinical Microbiology Informatics
Sintchenko, Vitali; Rauch, Carol A.; Pantanowitz, Liron
2014-01-01
SUMMARY The clinical microbiology laboratory has responsibilities ranging from characterizing the causative agent in a patient's infection to helping detect global disease outbreaks. All of these processes are increasingly becoming partnered more intimately with informatics. Effective application of informatics tools can increase the accuracy, timeliness, and completeness of microbiology testing while decreasing the laboratory workload, which can lead to optimized laboratory workflow and decreased costs. Informatics is poised to be increasingly relevant in clinical microbiology, with the advent of total laboratory automation, complex instrument interfaces, electronic health records, clinical decision support tools, and the clinical implementation of microbial genome sequencing. This review discusses the diverse informatics aspects that are relevant to the clinical microbiology laboratory, including the following: the microbiology laboratory information system, decision support tools, expert systems, instrument interfaces, total laboratory automation, telemicrobiology, automated image analysis, nucleic acid sequence databases, electronic reporting of infectious agents to public health agencies, and disease outbreak surveillance. The breadth and utility of informatics tools used in clinical microbiology have made them indispensable to contemporary clinical and laboratory practice. Continued advances in technology and development of these informatics tools will further improve patient and public health care in the future. PMID:25278581
Automating Performance Measures and Clinical Practice Guidelines: Differences and Complementarities.
Tu, Samson W; Martins, Susana; Oshiro, Connie; Yuen, Kaeli; Wang, Dan; Robinson, Amy; Ashcraft, Michael; Heidenreich, Paul A; Goldstein, Mary K
2016-01-01
Through close analysis of two pairs of systems that implement the automated evaluation of performance measures (PMs) and guideline-based clinical decision support (CDS), we contrast differences in their knowledge encoding and necessary changes to a CDS system that provides management recommendations for patients failing performance measures. We trace the sources of differences to the implementation environments and goals of PMs and CDS.
Lobach, David F; Kawamoto, Kensaku; Anstrom, Kevin J; Russell, Michael L; Woods, Peter; Smith, Dwight
2007-01-01
Clinical decision support is recognized as one potential remedy for the growing crisis in healthcare quality in the United States and other industrialized nations. While decision support systems have been shown to improve care quality and reduce errors, these systems are not widely available. This lack of availability arises in part because most decision support systems are not portable or scalable. The Health Level 7 international standard development organization recently adopted a draft standard known as the Decision Support Service standard to facilitate the implementation of clinical decision support systems using software services. In this paper, we report the first implementation of a clinical decision support system using this new standard. This system provides point-of-care chronic disease management for diabetes and other conditions and is deployed throughout a large regional health system. We also report process measures and usability data concerning the system. Use of the Decision Support Service standard provides a portable and scalable approach to clinical decision support that could facilitate the more extensive use of decision support systems.
Martinho, Margarida Suzel Lopes; da Costa Santos, Cristina Maria Nogueira; Silva Carvalho, João Luís Mendonça; Bernardes, João Francisco Montenegro Andrade Lima
2018-02-01
Inter-observer agreement and reliability in hysteroscopic image assessment remain uncertain and the type of factors that may influence it has only been studied in relation to the experience of hysteroscopists. We aim to assess the effect of clinical information and previous exam execution on observer agreement and reliability in the analysis of hysteroscopic video-recordings. Ninety hysteroscopies were video-recorded and randomized into a group without (Group 1) and with clinical information (Group 2). The videos were independently analyzed by three hysteroscopists, regarding lesion location, dimension, and type, as well as decision to perform a biopsy. One of the hysteroscopists had executed all the exams before. Proportions of agreement (PA) and kappa statistics (κ) with 95% confidence intervals (95% CI) were used. In Group 2, there was a higher proportion of a normal diagnosis (p < 0.001) and a lower proportion of biopsies recommended (p = 0.027). Observer agreement and reliability were better in Group 2, with the PA and κ ranging, respectively, from 0.73 (95% CI 0.62, 0.83) and 0.44 (95% CI 0.26, 0.63), for image quality, to 0.94 (95% CI 0.88, 0.99) and 0.85 (95% CI 0.65, 0.95), for the decision to perform a biopsy. Execution of the exams before the analysis of the video-recordings did not significantly affect the results. With clinical information, agreement and reliability in the overall analysis of hysteroscopic video-recordings may reach almost perfect results and this was not significantly affected by the execution of the exams before the analysis. However, there is still uncertainty in the analysis of specific endometrial cavity abnormalities.
SANDS: an architecture for clinical decision support in a National Health Information Network.
Wright, Adam; Sittig, Dean F
2007-10-11
A new architecture for clinical decision support called SANDS (Service-oriented Architecture for NHIN Decision Support) is introduced and its performance evaluated. The architecture provides a method for performing clinical decision support across a network, as in a health information exchange. Using the prototype we demonstrated that, first, a number of useful types of decision support can be carried out using our architecture; and, second, that the architecture exhibits desirable reliability and performance characteristics.
Chakrabarty, Lipi; Joshi, Gopal Datt; Chakravarty, Arunava; Raman, Ganesh V; Krishnadas, S R; Sivaswamy, Jayanthi
2016-07-01
To describe and evaluate the performance of an automated CAD system for detection of glaucoma from color fundus photographs. Color fundus photographs of 2252 eyes from 1126 subjects were collected from 2 centers: Aravind Eye Hospital, Madurai and Coimbatore, India. The images of 1926 eyes (963 subjects) were used to train an automated image analysis-based system, which was developed to provide a decision on a given fundus image. A total of 163 subjects were clinically examined by 2 ophthalmologists independently and their diagnostic decisions were recorded. The consensus decision was defined to be the clinical reference (gold standard). Fundus images of eyes with disagreement in diagnosis were excluded from the study. The fundus images of the remaining 314 eyes (157 subjects) were presented to 4 graders and their diagnostic decisions on the same were collected. The performance of the system was evaluated on the 314 images, using the reference standard. The sensitivity and specificity of the system and 4 independent graders were determined against the clinical reference standard. The system achieved an area under receiver operating characteristic curve of 0.792 with a sensitivity of 0.716 and specificity of 0.717 at a selected threshold for the detection of glaucoma. The agreement with the clinical reference standard as determined by Cohen κ is 0.45 for the proposed system. This is comparable to that of the image-based decisions of 4 ophthalmologists. An automated system was presented for glaucoma detection from color fundus photographs. The overall evaluation results indicated that the presented system was comparable in performance to glaucoma classification by a manual grader solely based on fundus image examination.
NASA Astrophysics Data System (ADS)
Le, Anh H.; Deshpande, Ruchi; Liu, Brent J.
2010-03-01
The electronic patient record (ePR) has been developed for prostate cancer patients treated with proton therapy. The ePR has functionality to accept digital input from patient data, perform outcome analysis and patient and physician profiling, provide clinical decision support and suggest courses of treatment, and distribute information across different platforms and health information systems. In previous years, we have presented the infrastructure of a medical imaging informatics based ePR for PT with functionality to accept digital patient information and distribute this information across geographical location using Internet protocol. In this paper, we present the ePR decision support tools which utilize the imaging processing tools and data collected in the ePR. The two decision support tools including the treatment plan navigator and radiation toxicity tool are presented to evaluate prostate cancer treatment to improve proton therapy operation and improve treatment outcomes analysis.
[Parameter of evidence-based medicine in health care economics].
Wasem, J; Siebert, U
1999-08-01
In the view of scarcity of resources, economic evaluations in health care, in which not only effects but also costs related to a medical intervention are examined and a incremental cost-outcome-ratio is build, are an important supplement to the program of evidence based medicine. Outcomes of a medical intervention can be measured by clinical effectiveness, quality-adjusted life years, and monetary evaluation of benefits. As far as costs are concerned, direct medical costs, direct non-medical costs and indirect costs have to be considered in an economic evaluation. Data can be used from primary studies or secondary analysis; metaanalysis for synthesizing of data may be adequate. For calculation of incremental cost-benefit-ratios, models of decision analysis (decision tree models, Markov-models) often are necessary. Methodological and ethical limits for application of the results of economic evaluation in resource allocation decision in health care have to be regarded: Economic evaluations and the calculation of cost-outcome-rations should only support decision making but cannot replace it.
Patients' Values in Clinical Decision-Making.
Faggion, Clovis Mariano; Pachur, Thorsten; Giannakopoulos, Nikolaos Nikitas
2017-09-01
Shared decision-making involves the participation of patient and dental practitioner. Well-informed decision-making requires that both parties understand important concepts that may influence the decision. This fourth article in a series of 4 aims to discuss the importance of patients' values when a clinical decision is made. We report on how to incorporate important concepts for well-informed, shared decision-making. Here, we present patient values as an important issue, in addition to previously established topics such as the risk of bias of a study, cost-effectiveness of treatment approaches, and a comparison of therapeutic benefit with potential side effects. We provide 2 clinical examples and suggestions for a decision tree, based on the available evidence. The information reported in this article may improve the relationship between patient and dental practitioner, resulting in more well-informed clinical decisions. Copyright © 2017 Elsevier Inc. All rights reserved.
An exploration of clinical decision making in mental health triage.
Sands, Natisha
2009-08-01
Mental health (MH) triage is a specialist area of clinical nursing practice that involves complex decision making. The discussion in this article draws on the findings of a Ph.D. study that involved a statewide investigation of the scope of MH triage nursing practice in Victoria, Australia. Although the original Ph.D. study investigated a number of core practices in MH triage, the focus of the discussion in this article is specifically on the findings related to clinical decision making in MH triage, which have not previously been published. The study employed an exploratory descriptive research design that used mixed data collection methods including a survey questionnaire (n = 139) and semistructured interviews (n = 21). The study findings related to decision making revealed a lack of empirically tested evidence-based decision-making frameworks currently in use to support MH triage nursing practice. MH triage clinicians in Australia rely heavily on clinical experience to underpin decision making and have little of knowledge of theoretical models for practice, such as methodologies for rating urgency. A key recommendation arising from the study is the need to develop evidence-based decision-making frameworks such as clinical guidelines to inform and support MH triage clinical decision making.
Shariat, Shahrokh F; Savage, Caroline; Chromecki, Thomas F; Sun, Maxine; Scherr, Douglas S; Lee, Richard K; Lughezzani, Giovanni; Remzi, Mesut; Marberger, Michael J; Karakiewicz, Pierre I; Vickers, Andrew J
2011-07-01
Several studies have demonstrated that abnormal levels of nuclear matrix protein 22 (NMP22) are associated with bladder cancer and have led to the approval of NMP22 as a urinary biomarker by the US Food and Drug Administration. Nonetheless, the clinical significance of NMP22 remains unclear. The objective of this study was to use decision analysis to determine whether NMP22 improves medical decision-making. The current study included 2222 patients who had a history of nonmuscle-invasive bladder cancer and current negative cytology. The authors developed models to predict cancer recurrence or progression to muscle-invasive disease using voided NMP22 levels, cystoscopy, age, and sex. Clinical net benefit was calculated by summing the benefits (true-positives), subtracting the harms (false-positives), and weighting these values by the threshold probability at which a patient or clinician would opt for cytoscopy. After cystoscopy, 581 patients (26%) had cancer identified. The NMP22 level was associated significantly with bladder cancer recurrence and progression (P < .001 for both). The use of NMP22 in a model with age and sex was associated with better patient outcomes than performing cystoscopy on everyone and produced threshold probabilities > 8% for recurrence and > 3% for progression. Only offering cystoscopy to those who had a risk > 15% reduced the number of cystoscopies by 229 while missing only 25 cancer recurrences per 1000 men with negative cytology. The current study was limited by its multicenter design. For clinicians who would perform a cystoscopy at a threshold of 5% for recurrence or 1% for progression, NMP22 did not aid clinical decision-making. For less risk-averse clinicians who would only perform a cystoscopy at a threshold probability >thinsp;8% for recurrence or > 3% for progression, NMP22 helped to indicate which patients required cystoscopy and which could be spared this procedure. Copyright © 2011 American Cancer Society.
Probability or Reasoning: Current Thinking and Realistic Strategies for Improved Medical Decisions
2017-01-01
A prescriptive model approach in decision making could help achieve better diagnostic accuracy in clinical practice through methods that are less reliant on probabilistic assessments. Various prescriptive measures aimed at regulating factors that influence heuristics and clinical reasoning could support clinical decision-making process. Clinicians could avoid time-consuming decision-making methods that require probabilistic calculations. Intuitively, they could rely on heuristics to obtain an accurate diagnosis in a given clinical setting. An extensive literature review of cognitive psychology and medical decision-making theory was performed to illustrate how heuristics could be effectively utilized in daily practice. Since physicians often rely on heuristics in realistic situations, probabilistic estimation might not be a useful tool in everyday clinical practice. Improvements in the descriptive model of decision making (heuristics) may allow for greater diagnostic accuracy. PMID:29209469
Probability or Reasoning: Current Thinking and Realistic Strategies for Improved Medical Decisions.
Nantha, Yogarabindranath Swarna
2017-11-01
A prescriptive model approach in decision making could help achieve better diagnostic accuracy in clinical practice through methods that are less reliant on probabilistic assessments. Various prescriptive measures aimed at regulating factors that influence heuristics and clinical reasoning could support clinical decision-making process. Clinicians could avoid time-consuming decision-making methods that require probabilistic calculations. Intuitively, they could rely on heuristics to obtain an accurate diagnosis in a given clinical setting. An extensive literature review of cognitive psychology and medical decision-making theory was performed to illustrate how heuristics could be effectively utilized in daily practice. Since physicians often rely on heuristics in realistic situations, probabilistic estimation might not be a useful tool in everyday clinical practice. Improvements in the descriptive model of decision making (heuristics) may allow for greater diagnostic accuracy.
[Shared medical decision making in gynaecology].
This, P; Panel, P
2010-02-01
When two options or more can be chosen in medical care, the final decision implies two steps: facts analysis, and patient evaluation of preferences. Shared Medical Decision-Making is a rational conceptual frame that can be used in such cases. In this paper, we describe the concept, its practical modalities, and the questions raised by its use. In gynaecology, many medical situations involve "sensitive preferences choice": for example, contraceptive choice, menorrhagia treatment, and approach of menopause. Some tools from the "Shared Medical Decision Making" concept are useful to structure medical consultations, to convey information, and to reveal patients preferences. Decision aid are used in clinical research settings, but some of them may also be easily used in usual practice, and help physicians to improve both quality and traceability of the decisional process. Copyright 2009 Elsevier Masson SAS. All rights reserved.
Veinot, Tiffany C; Senteio, Charles R; Hanauer, David; Lowery, Julie C
2018-06-01
To describe a new, comprehensive process model of clinical information interaction in primary care (Clinical Information Interaction Model, or CIIM) based on a systematic synthesis of published research. We used the "best fit" framework synthesis approach. Searches were performed in PubMed, Embase, the Cumulative Index to Nursing and Allied Health Literature (CINAHL), PsycINFO, Library and Information Science Abstracts, Library, Information Science and Technology Abstracts, and Engineering Village. Two authors reviewed articles according to inclusion and exclusion criteria. Data abstraction and content analysis of 443 published papers were used to create a model in which every element was supported by empirical research. The CIIM documents how primary care clinicians interact with information as they make point-of-care clinical decisions. The model highlights 3 major process components: (1) context, (2) activity (usual and contingent), and (3) influence. Usual activities include information processing, source-user interaction, information evaluation, selection of information, information use, clinical reasoning, and clinical decisions. Clinician characteristics, patient behaviors, and other professionals influence the process. The CIIM depicts the complete process of information interaction, enabling a grasp of relationships previously difficult to discern. The CIIM suggests potentially helpful functionality for clinical decision support systems (CDSSs) to support primary care, including a greater focus on information processing and use. The CIIM also documents the role of influence in clinical information interaction; influencers may affect the success of CDSS implementations. The CIIM offers a new framework for achieving CDSS workflow integration and new directions for CDSS design that can support the work of diverse primary care clinicians.
Foody, JoAnne M; Mendys, Phillip M; Liu, Larry Z; Simpson, Ross J
2010-05-01
Contemporary clinical decision making is well supported by a wide variety of information sources, including clinical practice guidelines, position papers, and insights from randomized controlled trials (RCTs). Much of our fundamental understanding of cardiovascular risk factors is based on multiple observations from major epidemiologic studies, such as The Seven Country Studies and the US-based Framingham Heart Study. These studies provided the framework for the development of clinical practice guidelines, including the National Cholesterol Education Program Adult Treatment Panel series. The objective of this article is to highlight the value of observational studies as a complement to clinical trial data for clinical decision making in real-world practice. Although RCTs are still the benchmark for assessing clinical efficacy and safety of a specific therapeutic approach, they may be of limited utility to practitioners who must then adapt the lessons learned from the trial into the patient care environment. The use of well-structured observational studies can improve our understanding of the translation of clinical trials into clinical practice, as demonstrated here with the example of statins. Although such studies have their own limitations, improved techniques for design and analysis have reduced the impact of bias and confounders. The introduction of the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines has provided more uniformity for such studies. When used together with RCTs, observational studies can enhance our understanding of effectiveness and utility in real-world clinical practice. In the examples of statin observational studies, the results suggest that relative effectiveness of different statins and potential impact of switching statins should be carefully considered in treating individual patients by practicing physicians.
Using service data: tools for taking action.
1992-01-01
Program performance can be improved through use of a simple information system. The focus of the discussion is on analysis of service data, decision making, and program improvement. Clinic managers must collect and analyze their own data and not wait for supervisors from central or district offices to conduct thorough examination. Local decision making has the advantage of providing monitoring and modification of services in a timely way and in a way responsive to client needs. Information can be shared throughout all levels of local and central administration. The model for decision making is based on data collection, data analysis, decision making, action, evaluation, information dissemination, and feedback. Data need to be collected on types of clients (new acceptor or continuing user), type of contraceptive method and quantity dispensed, and how the client learned about the clinic. Supply data also needs to be collected on methods of contraceptives on hand, number dispensed by method to clients, and projected supplies; requests for additional supplies can thus be made in a timely and appropriate way. The basic clinic forms are the family planning (FP), client record, the client referral card, an appointment card, a complication card, a daily FP activity register, a FP activities worksheet, a monthly summary of FP activities, and a commodities request/receipt form. A suggestion sheet from users addresses issues about performance targets, continuing users, dropouts, staff motivation, and setting up a system. Suggestions are also provided on the importance of staff training in data collection and analysis and in creating awareness of the program's objectives. Discussion is directed to how to interpret new acceptor data and to look for patterns. A sample chart is provided of a summary of FP activities, possible interpretations, and possible actions to take. Analysis is given for new acceptor trends, contraceptive method mix, and sources of information. A short example illustrates how client card data and bar graphs of method mix by desire for no more children or for more children revealed that couples childbearing desires did not affect method choice.
Shared decision-making – transferring research into practice: the Analytic Hierarchy Process (AHP)
Dolan, James G.
2008-01-01
Objective To illustrate how the Analytic Hierarchy Process (AHP) can be used to promote shared decision-making and enhance clinician-patient communication. Methods Tutorial review. Results The AHP promotes shared decision making by creating a framework that is used to define the decision, summarize the information available, prioritize information needs, elicit preferences and values, and foster meaningful communication among decision stakeholders. Conclusions The AHP and related multi-criteria methods have the potential for improving the quality of clinical decisions and overcoming current barriers to implementing shared decision making in busy clinical settings. Further research is needed to determine the best way to implement these tools and to determine their effectiveness. Practice Implications Many clinical decisions involve preference-based trade-offs between competing risks and benefits. The AHP is a well-developed method that provides a practical approach for improving patient-provider communication, clinical decision-making, and the quality of patient care in these situations. PMID:18760559
Establishing Good Practices for Exposure–Response Analysis of Clinical Endpoints in Drug Development
Overgaard, RV; Ingwersen, SH; Tornøe, CW
2015-01-01
This tutorial aims at promoting good practices for exposure–response (E-R) analyses of clinical endpoints in drug development. The focus is on practical aspects of E-R analyses to assist modeling scientists with a process of performing such analyses in a consistent manner across individuals and projects and tailored to typical clinical drug development decisions. This includes general considerations for planning, conducting, and visualizing E-R analyses, and how these are linked to key questions. PMID:26535157
The effect of cone beam CT (CBCT) on therapeutic decision-making in endodontics.
Mota de Almeida, F J; Knutsson, K; Flygare, L
2014-01-01
The aim was to assess to what extent cone beam CT (CBCT) used in accordance with current European Commission guidelines in a normal clinical setting has an impact on therapeutic decisions in a population referred for endodontic problems. The study includes data of consecutively examined patients collected from October 2011 to December 2012. From 2 different endodontic specialist clinics, 57 patients were referred for a CBCT examination using criteria in accordance with current European guidelines. The CBCT examinations were performed using similar equipment and standardized among clinics. After a thorough clinical examination, but before CBCT, the examiner made a preliminary therapy plan which was recorded. After the CBCT examination, the same examiner made a new therapy plan. Therapy plans both before and after the CBCT examination were plotted for 53 patients and 81 teeth. As four patients had incomplete protocols, they were not included in the final analysis. 4% of the patients referred to endodontic clinics during the study period were examined with CBCT. The most frequent reason for referral to CBCT examination was to differentiate pathology from normal anatomy, this was the case in 24 patients (45% of the cases). The primary outcome was therapy plan changes that could be attributed to CBCT examination. There were changes in 28 patients (53%). CBCT has a significant impact on therapeutic decision efficacy in endodontics when used in concordance with the current European Commission guidelines.
The clinical utility index as a practical multiattribute approach to drug development decisions.
Poland, B; Hodge, F L; Khan, A; Clemen, R T; Wagner, J A; Dykstra, K; Krishna, R
2009-07-01
We identify some innovative approaches to predicting overall patient benefit from investigational drugs to support development decisions. We then illustrate calculation of a probabilistic clinical utility index (CUI), an implementation of multiattribute utility that focuses on clinical attributes. We recommend use of the CUI for the support of early drug development decisions because of its practicality, reasonable accuracy, and transparency to decision makers, at stages in which financial factors that may dominate later-phase decisions are less critical.
Patterns of out-of-home placement decision-making in child welfare.
Chor, Ka Ho Brian; McClelland, Gary M; Weiner, Dana A; Jordan, Neil; Lyons, John S
2013-10-01
Out-of-home placement decision-making in child welfare is founded on the best interest of the child in the least restrictive setting. After a child is removed from home, however, little is known about the mechanism of placement decision-making. This study aims to systematically examine the patterns of out-of-home placement decisions made in a state's child welfare system by comparing two models of placement decision-making: a multidisciplinary team decision-making model and a clinically based decision support algorithm. Based on records of 7816 placement decisions representing 6096 children over a 4-year period, hierarchical log-linear modeling characterized concordance or agreement, and discordance or disagreement when comparing the two models and accounting for age-appropriate placement options. Children aged below 16 had an overall concordance rate of 55.7%, most apparent in the least restrictive (20.4%) and the most restrictive placement (18.4%). Older youth showed greater discordant distributions (62.9%). Log-linear analysis confirmed the overall robustness of concordance (odd ratios [ORs] range: 2.9-442.0), though discordance was most evident from small deviations from the decision support algorithm, such as one-level under-placement in group home (OR=5.3) and one-level over-placement in residential treatment center (OR=4.8). Concordance should be further explored using child-level clinical and placement stability outcomes. Discordance might be explained by dynamic factors such as availability of placements, caregiver preferences, or policy changes and could be justified by positive child-level outcomes. Empirical placement decision-making is critical to a child's journey in child welfare and should be continuously improved to effect positive child welfare outcomes. Copyright © 2013 Elsevier Ltd. All rights reserved.
Chorpita, Bruce F; Bernstein, Adam; Daleiden, Eric L
2008-03-01
This paper illustrates the application of design principles for tools that structure clinical decision-making. If the effort to implement evidence-based practices in community services organizations is to be effective, attention must be paid to the decision-making context in which such treatments are delivered. Clinical research trials commonly occur in an environment characterized by structured decision making and expert supports. Technology has great potential to serve mental health organizations by supporting these potentially important contextual features of the research environment, through organization and reporting of clinical data into interpretable information to support decisions and anchor decision-making procedures. This article describes one example of a behavioral health reporting system designed to facilitate clinical and administrative use of evidence-based practices. The design processes underlying this system-mapping of decision points and distillation of performance information at the individual, caseload, and organizational levels-can be implemented to support clinical practice in a wide variety of settings.
A Domain Analysis Model for eIRB Systems: Addressing the Weak Link in Clinical Research Informatics
He, Shan; Narus, Scott P.; Facelli, Julio C.; Lau, Lee Min; Botkin, Jefferey R.; Hurdle, John F.
2014-01-01
Institutional Review Boards (IRBs) are a critical component of clinical research and can become a significant bottleneck due to the dramatic increase, in both volume and complexity of clinical research. Despite the interest in developing clinical research informatics (CRI) systems and supporting data standards to increase clinical research efficiency and interoperability, informatics research in the IRB domain has not attracted much attention in the scientific community. The lack of standardized and structured application forms across different IRBs causes inefficient and inconsistent proposal reviews and cumbersome workflows. These issues are even more prominent in multi-institutional clinical research that is rapidly becoming the norm. This paper proposes and evaluates a domain analysis model for electronic IRB (eIRB) systems, paving the way for streamlined clinical research workflow via integration with other CRI systems and improved IRB application throughput via computer-assisted decision support. PMID:24929181
Company stock prices before and after public announcements related to oncology drugs.
Rothenstein, Jeffrey M; Tomlinson, George; Tannock, Ian F; Detsky, Allan S
2011-10-19
Phase III clinical trials and Food and Drug Administration (FDA) regulatory decisions are critical for success of new drugs and can influence a company's market valuation. Knowledge of trial results before they are made public (ie, "inside information") can affect the price of a drug company's stock. We examined the stock prices of companies before and after public announcements regarding experimental anticancer drugs owned by the companies. We identified drugs that were undergoing evaluation in phase III trials or for regulatory approval by the US FDA from January 2000 to January 2009. Stock prices of companies that owned such drugs were analyzed for 120 trading days before and after the first public announcement of 1) results of clinical trials with positive and negative outcomes and 2) positive and negative regulatory decisions. All statistical tests were two-sided. We identified public announcements from 23 positive trials and 36 negative trials and from 41 positive and nine negative FDA regulatory decisions. The mean stock price for the 120 trading days before a phase III clinical trial announcement increased by 13.7% (95% confidence interval = -2.2% to 29.6%) for companies that reported positive trials and decreased by 0.7% (95% confidence interval = -13.8% to 12.3%) for companies that reported negative trials (P = .09). In a post hoc analysis comparing the stock price averaged over 60 trading days before and after day -60 relative to the clinical trial announcement, the mean stock price increased by 9.4% for companies that reported positive trials and decreased by 4.5% for companies that reported negative trials (P = .03). Changes in company stock prices before FDA regulatory decisions did not differ statistically between companies with positive decision and companies with negative decisions. Trends in company stock prices before the first public announcement differ for companies that report positive vs negative trials. This finding has important legal and ethical implications for investigators, drug companies, and the investment industry.
Clinical decision support tool for Co-management signalling.
Horta, Alexandra Bayão; Salgado, Cátia; Fernandes, Marta; Vieira, Susana; Sousa, João M; Papoila, Ana Luísa; Xavier, Miguel
2018-05-01
Co-management between internists and surgeons of selected patients is becoming one of the pillars of modern clinical management in large hospitals. Defining the patients to be co-managed is essential. The aim of this study is to create a decision tool using real-world patient data collected in the preoperative period, to support the decision on which patients should have the co-management service offered. Data was collected from the electronic clinical health records of patients who had an International Classification of Diseases, 9th edition (ICD-9) code of colorectal surgery during the period between January 2012 and October 2014 in a 200 bed private teaching hospital in Lisbon. ICD-9 codes of colorectal surgery [48.5 and 48.6 (anterior rectal resection and abdominoperineal resection), 45.7 (partial colectomy), 45.8 (Total Colectomy), and 45.9 (Bowel Anastomosis)] were used. Only patients above 18 years old were considered. Patients with more than one procedure were excluded from the study. From these data the authors investigated the construction of predictive models using logistic regression and Takagi-Sugeno fuzzy modelling. Data contains information obtained from the clinical records of a cohort of 344 adult patients. Data from 398 emergent and elective surgeries were collected, from which 54 were excluded because they were second procedures for the same patients. Four preoperative variables were identified as being the most predictive of co-management, in multivariable regression analysis. The final model performed well after being internally validated (0.81 AUC, 77% accuracy, 74% sensitivity, 78% specificity, 93% negative predictive value). The results indicate that the decision process can be more objective and potentially automated. The authors developed a prediction model based on preoperative characteristics, in order to support the decision for the co-management of surgical patients in the postoperative ward setting. The model is a simple bedside decision tool that uses only four numerical variables. Copyright © 2018 Elsevier B.V. All rights reserved.
Goddard, Katrina A.B.; Knaus, William A.; Whitlock, Evelyn; Lyman, Gary H.; Feigelson, Heather Spencer; Schully, Sheri D.; Ramsey, Scott; Tunis, Sean; Freedman, Andrew N.; Khoury, Muin J.; Veenstra, David L.
2013-01-01
Background The clinical utility is uncertain for many cancer genomic applications. Comparative effectiveness research (CER) can provide evidence to clarify this uncertainty. Objectives To identify approaches to help stakeholders make evidence-based decisions, and to describe potential challenges and opportunities using CER to produce evidence-based guidance. Methods We identified general CER approaches for genomic applications through literature review, the authors’ experiences, and lessons learned from a recent, seven-site CER initiative in cancer genomic medicine. Case studies illustrate the use of CER approaches. Results Evidence generation and synthesis approaches include comparative observational and randomized trials, patient reported outcomes, decision modeling, and economic analysis. We identified significant challenges to conducting CER in cancer genomics: the rapid pace of innovation, the lack of regulation, the limited evidence for clinical utility, and the beliefs that genomic tests could have personal utility without having clinical utility. Opportunities to capitalize on CER methods in cancer genomics include improvements in the conduct of evidence synthesis, stakeholder engagement, increasing the number of comparative studies, and developing approaches to inform clinical guidelines and research prioritization. Conclusions CER offers a variety of methodological approaches to address stakeholders’ needs. Innovative approaches are needed to ensure an effective translation of genomic discoveries. PMID:22516979
2012-01-01
Background Efficient rule authoring tools are critical to allow clinical Knowledge Engineers (KEs), Software Engineers (SEs), and Subject Matter Experts (SMEs) to convert medical knowledge into machine executable clinical decision support rules. The goal of this analysis was to identify the critical success factors and challenges of a fully functioning Rule Authoring Environment (RAE) in order to define requirements for a scalable, comprehensive tool to manage enterprise level rules. Methods The authors evaluated RAEs in active use across Partners Healthcare, including enterprise wide, ambulatory only, and system specific tools, with a focus on rule editors for reminder and medication rules. We conducted meetings with users of these RAEs to discuss their general experience and perceived advantages and limitations of these tools. Results While the overall rule authoring process is similar across the 10 separate RAEs, the system capabilities and architecture vary widely. Most current RAEs limit the ability of the clinical decision support (CDS) interventions to be standardized, sharable, interoperable, and extensible. No existing system meets all requirements defined by knowledge management users. Conclusions A successful, scalable, integrated rule authoring environment will need to support a number of key requirements and functions in the areas of knowledge representation, metadata, terminology, authoring collaboration, user interface, integration with electronic health record (EHR) systems, testing, and reporting. PMID:23145874
2014-01-01
Objective To offer a practical demonstration of receiver operating characteristic (ROC) analyses, diagnostic efficiency statistics, and their application to clinical decision making using a popular parent checklist to assess for potential mood disorder. Method Secondary analyses of data from 589 families seeking outpatient mental health services, completing the Child Behavior Checklist and semi-structured diagnostic interviews. Results Internalizing Problems raw scores discriminated mood disorders significantly better than did age- and gender-normed T scores, or an Affective Problems score. Internalizing scores <8 had a diagnostic likelihood ratio <0.3, and scores >30 had a diagnostic likelihood ratio of 7.4. Conclusions This study illustrates a series of steps in defining a clinical problem, operationalizing it, selecting a valid study design, and using ROC analyses to generate statistics that support clinical decisions. The ROC framework offers important advantages for clinical interpretation. Appendices include sample scripts using SPSS and R to check assumptions and conduct ROC analyses. PMID:23965298
Pelaccia, Thierry; Tardif, Jacques; Triby, Emmanuel; Charlin, Bernard
2011-01-01
Context Clinical reasoning plays a major role in the ability of doctors to make diagnoses and decisions. It is considered as the physician's most critical competence, and has been widely studied by physicians, educationalists, psychologists and sociologists. Since the 1970s, many theories about clinical reasoning in medicine have been put forward. Purpose This paper aims at exploring a comprehensive approach: the “dual-process theory”, a model developed by cognitive psychologists over the last few years. Discussion After 40 years of sometimes contradictory studies on clinical reasoning, the dual-process theory gives us many answers on how doctors think while making diagnoses and decisions. It highlights the importance of physicians’ intuition and the high level of interaction between analytical and non-analytical processes. However, it has not received much attention in the medical education literature. The implications of dual-process models of reasoning in terms of medical education will be discussed. PMID:21430797
Youngstrom, Eric A
2014-03-01
To offer a practical demonstration of receiver operating characteristic (ROC) analyses, diagnostic efficiency statistics, and their application to clinical decision making using a popular parent checklist to assess for potential mood disorder. Secondary analyses of data from 589 families seeking outpatient mental health services, completing the Child Behavior Checklist and semi-structured diagnostic interviews. Internalizing Problems raw scores discriminated mood disorders significantly better than did age- and gender-normed T scores, or an Affective Problems score. Internalizing scores <8 had a diagnostic likelihood ratio <0.3, and scores >30 had a diagnostic likelihood ratio of 7.4. This study illustrates a series of steps in defining a clinical problem, operationalizing it, selecting a valid study design, and using ROC analyses to generate statistics that support clinical decisions. The ROC framework offers important advantages for clinical interpretation. Appendices include sample scripts using SPSS and R to check assumptions and conduct ROC analyses.
Moore, Andrew; Crossley, Anne; Ng, Bernard; Phillips, Lawrence; Sancak, Özgür; Rainsford, K D
2017-10-01
To test the ability of a multicriteria decision analysis (MCDA) model to incorporate disparate data sources of varying quality along with clinical judgement in a benefit-risk assessment of six well-known pain-relief drugs. Six over-the-counter (OTC) analgesics were evaluated against three favourable effects and eight unfavourable effects by seven experts who specialise in the relief of pain, two in a 2-day facilitated workshop whose input data and judgements were later peer-reviewed by five additional experts. Ibuprofen salts and solubilised emerged with the best benefit-risk profile, followed by naproxen, ibuprofen acid, diclofenac, paracetamol and aspirin. Multicriteria decision analysis enabled participants to evaluate the OTC analgesics against a range of favourable and unfavourable effects in a group setting that enabled all issues to be openly aired and debated. The model was easily communicated and understood by the peer reviewers, so the model should be comprehensible to physicians, pharmacists and other health professionals. © 2017 Royal Pharmaceutical Society.
Wang, Elyn H; Gross, Cary P; Tilburt, Jon C; Yu, James B; Nguyen, Paul L; Smaldone, Marc C; Shah, Nilay D; Abouassally, Robert; Sun, Maxine; Kim, Simon P
2015-05-01
The current attitudes of prostate cancer specialists toward decision aids and their use in clinical practice to facilitate shared decision making are poorly understood. To assess attitudes toward decision aids and their dissemination in clinical practice. A survey was mailed to a national random sample of 1422 specialists (711 radiation oncologists and 711 urologists) in the United States from November 1, 2011, through April 30, 2012. Respondents were asked about familiarity, perceptions, and use of decision aids for clinically localized prostate cancer and trust in various professional societies in developing decision aids. The Pearson χ2 test was used to test for bivariate associations between physician characteristics and outcomes. Similar response rates were observed for radiation oncologists and urologists (44.0% vs 46.1%; P=.46). Although most respondents had some familiarity with decision aids, only 35.5% currently use a decision aid in clinic practice. The most commonly cited barriers to decision aid use included the perception that their ability to estimate the risk of recurrence was superior to that of decision aids (7.7% in those not using decision aids and 26.2% in those using decision aids; P<.001) and the concern that patients could not process information from a decision aid (7.6% in those not using decision aids and 23.7% in those using decision aids; P<.001). In assessing trust in decision aids established by various professional medical societies, specialists consistently reported trust in favor of their respective organizations, with 9.2% being very confident and 59.2% being moderately confident (P=.01). Use of decision aids among specialists treating patients with prostate cancer is relatively low. Efforts to address barriers to clinical implementation of decision aids may facilitate greater shared decision making for patients diagnosed as having prostate cancer.
Quantifying patient preferences for symptomatic breast clinic referral: a decision analysis study.
Quinlan, Aisling; O'Brien, Kirsty K; Galvin, Rose; Hardy, Colin; McDonnell, Ronan; Joyce, Doireann; McDowell, Ronald D; Aherne, Emma; Keogh, Claire; O'Sullivan, Katriona; Fahey, Tom
2018-05-31
Decision analysis study that incorporates patient preferences and probability estimates to investigate the impact of women's preferences for referral or an alternative strategy of watchful waiting if faced with symptoms that could be due to breast cancer. Community-based study. Asymptomatic women aged 30-60 years. Participants were presented with 11 health scenarios that represent the possible consequences of symptomatic breast problems. Participants were asked the risk of death that they were willing to take in order to avoid the health scenario using the standard gamble utility method. This process was repeated for all 11 health scenarios. Formal decision analysis for the preferred individual decision was then estimated for each participant. The preferred diagnostic strategy was either watchful waiting or referral to a breast clinic. Sensitivity analysis was used to examine how each varied according to changes in the probabilities of the health scenarios. A total of 35 participants completed the interviews, with a median age 41 years (IQR 35-47 years). The majority of the study sample was employed (n=32, 91.4%), with a third-level (university) education (n=32, 91.4%) and with knowledge of someone with breast cancer (n=30, 85.7%). When individual preferences were accounted for, 25 (71.4%) patients preferred watchful waiting to referral for triple assessment as their preferred initial diagnostic strategy. Sensitivity analysis shows that referral for triple assessment becomes the dominant strategy at the upper probability estimate (18%) of breast cancer in the community. Watchful waiting is an acceptable strategy for most women who present to their general practitioner (GP) with breast symptoms. These findings suggest that current referral guidelines should take more explicit account of women's preferences in relation to their GPs initial management strategy. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
In search of tools to aid logical thinking and communicating about medical decision making.
Hunink, M G
2001-01-01
To have real-time impact on medical decision making, decision analysts need a wide variety of tools to aid logical thinking and communication. Decision models provide a formal framework to integrate evidence and values, but they are commonly perceived as complex and difficult to understand by those unfamiliar with the methods, especially in the context of clinical decision making. The theory of constraints, introduced by Eliyahu Goldratt in the business world, provides a set of tools for logical thinking and communication that could potentially be useful in medical decision making. The author used the concept of a conflict resolution diagram to analyze the decision to perform carotid endarterectomy prior to coronary artery bypass grafting in a patient with both symptomatic coronary and asymptomatic carotid artery disease. The method enabled clinicians to visualize and analyze the issues, identify and discuss the underlying assumptions, search for the best available evidence, and use the evidence to make a well-founded decision. The method also facilitated communication among those involved in the care of the patient. Techniques from fields other than decision analysis can potentially expand the repertoire of tools available to support medical decision making and to facilitate communication in decision consults.
Mobile Clinical Decision Support System for Acid-base Balance Diagnosis and Treatment Recommendation
Mandzuka, Mensur; Begic, Edin; Boskovic, Dusanka; Begic, Zijo; Masic, Izet
2017-01-01
Introduction: This paper presents mobile application implementing a decision support system for acid-base disorder diagnosis and treatment recommendation. Material and methods: The application was developed using the official integrated development environment for the Android platform (to maximize availability and minimize investments in specialized hardware) called Android Studio. Results: The application identifies disorder, based on the blood gas analysis, evaluates whether the disorder has been compensated, and based on additional input related to electrolyte imbalance, provides recommendations for treatment. Conclusion: The application is a tool in the hands of the user, which provides assistance during acid-base disorders treatment. The application will assist the physician in clinical practice and is focused on the treatment in intensive care. PMID:28883678
Wisdom in clinical reasoning and medical practice.
Edmondson, Ricca; Pearce, Jane; Woerner, Markus H
2009-01-01
Exploring informal components of clinical reasoning, we argue that they need to be understood via the analysis of professional wisdom. Wise decisions are needed where action or insight is vital, but neither everyday nor expert knowledge provides solutions. Wisdom combines experiential, intellectual, ethical, emotional and practical capacities; we contend that it is also more strongly social than is usually appreciated. But many accounts of reasoning specifically rule out such features as irrational. Seeking to illuminate how wisdom operates, we therefore build on Aristotle's work on informal reasoning. His account of rhetorical communication shows how non-formal components can play active parts in reasoning, retaining, or even enhancing its reasonableness. We extend this account, applying it to forms of healthcare-related reasoning which are characterised by the need for wise decision-making. We then go on to explore some of what clinical wise reasoning may mean, concluding with a case taken from psychotherapeutic practice.
Benefit-risk Evaluation for Diagnostics: A Framework (BED-FRAME).
Evans, Scott R; Pennello, Gene; Pantoja-Galicia, Norberto; Jiang, Hongyu; Hujer, Andrea M; Hujer, Kristine M; Manca, Claudia; Hill, Carol; Jacobs, Michael R; Chen, Liang; Patel, Robin; Kreiswirth, Barry N; Bonomo, Robert A
2016-09-15
The medical community needs systematic and pragmatic approaches for evaluating the benefit-risk trade-offs of diagnostics that assist in medical decision making. Benefit-Risk Evaluation of Diagnostics: A Framework (BED-FRAME) is a strategy for pragmatic evaluation of diagnostics designed to supplement traditional approaches. BED-FRAME evaluates diagnostic yield and addresses 2 key issues: (1) that diagnostic yield depends on prevalence, and (2) that different diagnostic errors carry different clinical consequences. As such, evaluating and comparing diagnostics depends on prevalence and the relative importance of potential errors. BED-FRAME provides a tool for communicating the expected clinical impact of diagnostic application and the expected trade-offs of diagnostic alternatives. BED-FRAME is a useful fundamental supplement to the standard analysis of diagnostic studies that will aid in clinical decision making. © The Author 2016. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail journals.permissions@oup.com.
An evaluation of treatment decisions at a colorectal cancer multi-disciplinary team.
Wood, J J; Metcalfe, C; Paes, A; Sylvester, P; Durdey, P; Thomas, M G; Blazeby, J M
2008-10-01
It is mandatory for treatment decisions for patients with colorectal cancer to be made within the context of a multi-disciplinary team (MDT) meeting. It is currently uncertain, however, how to best evaluate the quality of MDT decision-making. This study examined MDT decision-making by studying whether MDT treatment decisions were implemented and investigated the reasons why some decisions changed after the meeting. Consecutive MDT treatment decisions were prospectively recorded. Implementation of decisions was studied by examining hospital records. Reasons for changes in MDT decisions were identified. In all, 201 consecutive treatment decisions were analysed, concerning 157 patients. Twenty decisions (10.0%, 95% confidence interval 6.3-15.2%) were not implemented. Looking at the reasons for nonimplementation, nine (40%) related to co-morbidity, seven (35%) to patient choice, two changed in light of new clinical information, one doctor changed a decision and for one changed decision, no reason was apparent. When decisions changed, the final treatment was always more conservative than was originally planned and decisions were more likely to change for colon rather than rectal cancer (P = 0.024). The vast majority of colorectal MDT decisions were implemented and when decisions changed, it mostly related to patient factors that had not been taken into account. Analysis of the implementation of team decisions is an informative process to monitor the quality of MDT decision-making.
Ranieri, Veronica F; Barratt, Helen; Rees, Geraint; Fulop, Naomi J
2018-01-23
To describe the influences on clinical academic physicians' postdoctoral career decision-making. Thirty-five doctoral trainee physicians from University College London took part in semi-structured interviews in 2015 and 2016. Participants were asked open-ended questions about their career to-date, their experiences undertaking a PhD, and their career plans post-PhD. The interviews were audio-recorded and transcribed. Thematic analysis was used to generate, review, and define themes from the transcripts. Emerging differences and similarities in participants' reasons for pursuing a PhD were then grouped to produce typologies to explore how their experiences influenced their career decision-making. Participants described four key reasons for undertaking a PhD, which formed the basis of the four typologies identified. These reasons included: to pursue a clinical academic career; to complete an extensive period of research to understand whether a clinical academic career was the desired path forward; to improve clinical career prospects; and to take a break from clinical training. These findings highlight the need to target efforts at retaining clinical academic physicians according to their reasons for pursuing a PhD and their subsequent experiences with the process. Those responsible for overseeing clinical training must be well-informed of the long-term benefits of training academically-qualified physicians. In light of current political uncertainty, universities, hospitals, and external agencies alike must increase their efforts to inspire and assuage early-career clinical academic physicians' fears regarding their academic future.This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Cook, David A; Sorensen, Kristi J; Wilkinson, John M; Berger, Richard A
2013-11-25
Answering clinical questions affects patient-care decisions and is important to continuous professional development. The process of point-of-care learning is incompletely understood. To understand what barriers and enabling factors influence physician point-of-care learning and what decisions physicians face during this process. Focus groups with grounded theory analysis. Focus group discussions were transcribed and then analyzed using a constant comparative approach to identify barriers, enabling factors, and key decisions related to physician information-seeking activities. Academic medical center and outlying community sites. Purposive sample of 50 primary care and subspecialist internal medicine and family medicine physicians, interviewed in 11 focus groups. Insufficient time was the main barrier to point-of-care learning. Other barriers included the patient comorbidities and contexts, the volume of available information, not knowing which resource to search, doubt that the search would yield an answer, difficulty remembering questions for later study, and inconvenient access to computers. Key decisions were whether to search (reasons to search included infrequently seen conditions, practice updates, complex questions, and patient education), when to search (before, during, or after the clinical encounter), where to search (with the patient present or in a separate room), what type of resource to use (colleague or computer), what specific resource to use (influenced first by efficiency and second by credibility), and when to stop. Participants noted that key features of efficiency (completeness, brevity, and searchability) are often in conflict. Physicians perceive that insufficient time is the greatest barrier to point-of-care learning, and efficiency is the most important determinant in selecting an information source. Designing knowledge resources and systems to target key decisions may improve learning and patient care.
Ayyappan, Sabarish; Gonzalez, Claudia; Yarlagadda, Roopa; Zakharia, Yousef; Woodlock, Timothy J.
2011-01-01
Background and objectives Lung cancer presentation and decision-making in the very elderly patient population, 80 years of age and older, was studied given the projected increase in cancer incidence in the very elderly and yet only limited management guidelines. Design and setting A 10-year experience at the Unity Health System of Rochester, NY, was reviewed using tumor registry data for the entire lung cancer population plus focused medical record review of very elderly patients. A questionnaire survey on the clinical approach to lung cancer in the elderly was distributed to medical staff involved in their care. Participants, measurements, and results Of 997 patients, approximately 100 cases each year, the very elderly comprised 18% of patients from year 1998 through 2002, and 23% from year 2003 through 2007. One-third of the very elderly were diagnosed with lung cancer on clinical grounds without tissue confirmation. The majority of this group had cardio-pulmonary symptoms and an advanced clinical stage. The very elderly had no tissue sampling as per their own decision in 12 of 44 of cases, per family decision in 28 of 44, and per physician and other input in 4 of 44. Physicians stated that patient wishes and health-related factors, more so than socio-economic factors, were primary concerns for management decision-making. Conclusions The number of very elderly lung cancer patients in this community setting has been significant and appears to be increasing. These patients were more likely to have an incomplete diagnostic work-up, with patient and family wishes being the major factor in medical decision-making. The physician approach to these patients emphasized patient autonomy and medical factors. PMID:23882335
Influence of clinician referral on Nebraska women's decision-to-abortion time.
French, Valerie; Anthony, Renaisa; Souder, Chelsea; Geistkemper, Christine; Drey, Eleanor; Steinauer, Jody
2016-03-01
To assess the association of clinician referral with decision-to-abortion time. We conducted a cross-sectional survey of women seeking abortion at all three Nebraska abortion clinics. We defined referral as direct (information for an abortion clinic), inappropriate (information for a clinic that does not provide abortions) or no referral. Women reported when they recognized their pregnancy, decided to seek abortion and contacted a clinician. The primary outcome - decision-to-abortion time - was time from certain decision to abortion. We used multivariate linear regression analysis, controlling for potential confounders. Participants (n=356) were a mean of 26.8±5.3years old, primarily white (62%), unmarried (88%) and urban (87%), with a mean gestational duration of 8(2/7)weeks (S.D.±20days). Forty-six percent (164) had contacted a clinician and 30% (104) had discussed abortion with one before their abortion. Of those, 30% received a direct referral, 6% received an inappropriate referral and 64% received no referral. Decision-to-abortion time did not vary by referral type [mean difference compared with direct referral: inappropriate referral, 1.1days, 95% confidence interval (CI) -13.4 to 15.6, p=.88; no referral, -0.4days, 95% CI -7.0 to 6.3]. The most common reasons cited for delay in obtaining an abortion were an inability to get an earlier appointment (105/263, 40%) and time needed to raise money to pay for the abortion (73/263, 28%). While neither occurrence of referral nor type was associated with decision-to-abortion times, women in Nebraska continue to face barriers to timely abortion care. Additional research is needed to explore whether quality clinician referral improves abortion access and whether increased resources should be dedicated to improving referral patterns. Copyright © 2016 Elsevier Inc. All rights reserved.
Dolan, James G; Veazie, Peter J
2015-12-01
Growing recognition of the importance of involving patients in preference-driven healthcare decisions has highlighted the need to develop practical strategies to implement patient-centered shared decision-making. The use of tabular balance sheets to support clinical decision-making is well established. More recent evidence suggests that graphic, interactive decision dashboards can help people derive deeper a understanding of information within a specific decision context. We therefore conducted a non-randomized trial comparing the effects of adding an interactive dashboard to a static tabular balance sheet on patient decision-making. The study population consisted of members of the ResearchMatch registry who volunteered to participate in a study of medical decision-making. Two separate surveys were conducted: one in the control group and one in the intervention group. All participants were instructed to imagine they were newly diagnosed with a chronic illness and were asked to choose between three hypothetical drug treatments, which varied with regard to effectiveness, side effects, and out-of-pocket cost. Both groups made an initial treatment choice after reviewing a balance sheet. After a brief "washout" period, members of the control group made a second treatment choice after reviewing the balance sheet again, while intervention group members made a second treatment choice after reviewing an interactive decision dashboard containing the same information. After both choices, participants rated their degree of confidence in their choice on a 1 to 10 scale. Members of the dashboard intervention group were more likely to change their choice of preferred drug (10.2 versus 7.5%; p = 0.054) and had a larger increase in decision confidence than the control group (0.67 versus 0.075; p < 0.03). There were no statistically significant between-group differences in decisional conflict or decision aid acceptability. These findings suggest that clinical decision dashboards may be an effective point-of-care decision-support tool. Further research to explore this possibility is warranted.
Simpao, Allan F; Tan, Jonathan M; Lingappan, Arul M; Gálvez, Jorge A; Morgan, Sherry E; Krall, Michael A
2017-10-01
Anesthesia information management systems (AIMS) are sophisticated hardware and software technology solutions that can provide electronic feedback to anesthesia providers. This feedback can be tailored to provide clinical decision support (CDS) to aid clinicians with patient care processes, documentation compliance, and resource utilization. We conducted a systematic review of peer-reviewed articles on near real-time and point-of-care CDS within AIMS using the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols. Studies were identified by searches of the electronic databases Medline and EMBASE. Two reviewers screened studies based on title, abstract, and full text. Studies that were similar in intervention and desired outcome were grouped into CDS categories. Three reviewers graded the evidence within each category. The final analysis included 25 articles on CDS as implemented within AIMS. CDS categories included perioperative antibiotic prophylaxis, post-operative nausea and vomiting prophylaxis, vital sign monitors and alarms, glucose management, blood pressure management, ventilator management, clinical documentation, and resource utilization. Of these categories, the reviewers graded perioperative antibiotic prophylaxis and clinical documentation as having strong evidence per the peer reviewed literature. There is strong evidence for the inclusion of near real-time and point-of-care CDS in AIMS to enhance compliance with perioperative antibiotic prophylaxis and clinical documentation. Additional research is needed in many other areas of AIMS-based CDS.
Principles and application of LIMS in mouse clinics.
Maier, Holger; Schütt, Christine; Steinkamp, Ralph; Hurt, Anja; Schneltzer, Elida; Gormanns, Philipp; Lengger, Christoph; Griffiths, Mark; Melvin, David; Agrawal, Neha; Alcantara, Rafael; Evans, Arthur; Gannon, David; Holroyd, Simon; Kipp, Christian; Raj, Navis Pretheeba; Richardson, David; LeBlanc, Sophie; Vasseur, Laurent; Masuya, Hiroshi; Kobayashi, Kimio; Suzuki, Tomohiro; Tanaka, Nobuhiko; Wakana, Shigeharu; Walling, Alison; Clary, David; Gallegos, Juan; Fuchs, Helmut; de Angelis, Martin Hrabě; Gailus-Durner, Valerie
2015-10-01
Large-scale systemic mouse phenotyping, as performed by mouse clinics for more than a decade, requires thousands of mice from a multitude of different mutant lines to be bred, individually tracked and subjected to phenotyping procedures according to a standardised schedule. All these efforts are typically organised in overlapping projects, running in parallel. In terms of logistics, data capture, data analysis, result visualisation and reporting, new challenges have emerged from such projects. These challenges could hardly be met with traditional methods such as pen & paper colony management, spreadsheet-based data management and manual data analysis. Hence, different Laboratory Information Management Systems (LIMS) have been developed in mouse clinics to facilitate or even enable mouse and data management in the described order of magnitude. This review shows that general principles of LIMS can be empirically deduced from LIMS used by different mouse clinics, although these have evolved differently. Supported by LIMS descriptions and lessons learned from seven mouse clinics, this review also shows that the unique LIMS environment in a particular facility strongly influences strategic LIMS decisions and LIMS development. As a major conclusion, this review states that there is no universal LIMS for the mouse research domain that fits all requirements. Still, empirically deduced general LIMS principles can serve as a master decision support template, which is provided as a hands-on tool for mouse research facilities looking for a LIMS.
The impact of simulation sequencing on perceived clinical decision making.
Woda, Aimee; Hansen, Jamie; Paquette, Mary; Topp, Robert
2017-09-01
An emerging nursing education trend is to utilize simulated learning experiences as a means to optimize competency and decision making skills. The purpose of this study was to examine differences in students' perception of clinical decision making and clinical decision making-related self-confidence and anxiety based on the sequence (order) in which they participated in a block of simulated versus hospital-based learning experiences. A quasi-experimental crossover design was used. Between and within group differences were found relative to self-confidence with the decision making process. When comparing groups, at baseline the simulation followed by hospital group had significantly higher self-confidence scores, however, at 14-weeks both groups were not significantly different. Significant within group differences were found in the simulation followed by hospital group only, demonstrating a significant decrease in clinical decision making related anxiety across the semester. Finally, there were no significant difference in; perceived clinical decision making within or between the groups at the two measurement points. Preliminary findings suggest that simulated learning experiences can be offered with alternating sequences without impacting the process, anxiety or confidence with clinical decision making. This study provides beginning evidence to guide curriculum development and allow flexibility based on student needs and available resources. Copyright © 2017. Published by Elsevier Ltd.
Abbasian Ardakani, Ali; Reiazi, Reza; Mohammadi, Afshin
2018-03-30
This study investigated the potential of a clinical decision support approach for the classification of metastatic and tumor-free cervical lymph nodes (LNs) in papillary thyroid carcinoma on the basis of radiologic and textural analysis through ultrasound (US) imaging. In this research, 170 metastatic and 170 tumor-free LNs were examined by the proposed clinical decision support method. To discover the difference between the groups, US imaging was used for the extraction of radiologic and textural features. The radiologic features in the B-mode scans included the echogenicity, margin, shape, and presence of microcalcification. To extract the textural features, a wavelet transform was applied. A support vector machine classifier was used to classify the LNs. In the training set data, a combination of radiologic and textural features represented the best performance with sensitivity, specificity, accuracy, and area under the curve (AUC) values of 97.14%, 98.57%, 97.86%, and 0.994, respectively, whereas the classification based on radiologic and textural features alone yielded lower performance, with AUCs of 0.964 and 0.922. On testing the data set, the proposed model could classify the tumor-free and metastatic LNs with an AUC of 0.952, which corresponded to sensitivity, specificity, and accuracy of 93.33%, 96.66%, and 95.00%. The clinical decision support method based on textural and radiologic features has the potential to characterize LNs via 2-dimensional US. Therefore, it can be used as a supplementary technique in daily clinical practice to improve radiologists' understanding of conventional US imaging for characterizing LNs. © 2018 by the American Institute of Ultrasound in Medicine.