Browsing by Author "Djulbegovic, B."

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    Evaluation of physicians’ cognitive styles
    (Sage, 2014) Djulbegovic, B.; Beckstead, J.; Elqayam, Shira; Reljic, T.; Hozo, I.; Kumar, A.; Cannon-Bowers, J.; Taylor, S.; Tsalatsanis, A.; Turner, B.; Paidas, C.
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    How do physicians decide to treat: an empirical evaluation of the threshold model
    (BioMed Central, 2014) Djulbegovic, B.; Elqayam, Shira; Rejic, T.; Hozo, I.; Tsalatsanis, A.; Kumar, A.; Beckstead, J.; Chen, R.; Taylor, S.; Cannon-Bowers, J.
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    Many faces of rationality: Implications of the great rationality debate for clinical decision-making
    (Wiley, 2017-09-27) Djulbegovic, B.; Elqayam, Shira
    Given that more than 30% of healthcare costs are wasted on inappropriate care, suboptimal care is increasingly connected to the quality of medical decisions. It has been argued that personal decisions are the leading cause of death, and 80% of healthcare expenditures result from physicians' decisions. Therefore, improving healthcare necessitates improving medical decisions, ie, making decisions (more) rational. Drawing on writings fromThe Great Rationality Debate from the fields of philosophy, economics, and psychology, we identify core ingredients of rationality commonly encountered across various theoretical models. Rationality is typically classified under umbrella of normative (addressing the question how people “should” or “ought to” make their decisions) and descriptive theories of decision‐ making (which portray how people actually make their decisions). Normative theories of rational thought of relevance to medicine include epistemic theories that direct practice of evidencebasedmedicine and expected utility theory, which provides the basis for widely used clinical decision analyses. Descriptive theories of rationality of direct relevance to medical decision‐making include bounded rationality, argumentative theory of reasoning, adaptive rationality, dual processing model of rationality, regret‐based rationality, pragmatic/substantive rationality, and meta‐rationality. For the first time, we provide a review of wide range of theories and models of rationality. We showed that what is “rational” behaviour under one rationality theory may be irrational under the other theory. We also showed that context is of paramount importance to rationality and that no one model of rationality can possibly fit all contexts. We suggest that in context‐poor situations, such as policy decision‐making, normative theories based on expected utility informed by best research evidence may provide the optimal approach to medical decision‐making, whereas in the context‐rich circumstances other types of rationality, informed by human cognitive architecture and driven by intuition and emotions such as the aim to minimize regret, may provide better solution to the problem at hand. The choice of theory under which we operate is important as it determines both policy and our individual decision‐making.
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    Rational decision-making in medicine: implications for overuse and underuse
    (Wiley, 2017-12-01) Djulbegovic, B.; Elqayam, Shira; Dale, W.
    In spite of substantial spending and resource utilization, today's health care remains characterized by poor outcomes, largely due to overuse (over-testing/treatment) or underuse (under-testing/treatment) of services. To a significant extent, this is a consequence of low-quality decision-making that appears to violate various rationality criteria. Such sub-optimal decision-making is considered a leading cause of death and is responsible for more than 80% of health expenses. In this paper, we address the issue of overuse or underuse of healthcare interventions from the perspective of rational choice theory. We show that what is considered rational under one decision theory may not be considered rational under a different theory. We posit that the questions and concerns regarding both underuse and overuse have to be addressed within a specific theoretical framework. The applicable rationality criterion, and thus the “appropriateness” of health care delivery choices, depends on theory selection that is appropriate to specific clinical situations. We provide a number of illustrations showing how the choice of theoretical framework influences both our policy and individual decision-making. We also highlight the practical implications of our analysis for the current efforts to measure the quality of care and link such measurements to the financing of healthcare services.
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    Structured decision-making drives guidelines panels’ recommendations ‘for’ but not ‘against’ health interventions
    (Elsevier, 2019-02-16) Djulbegovic, B.; Reljic, T.; Elqayam, Shira; Cuker, A.; Hozo, I.; Zhou, Q.; Li, S.-A.; Alexander, P.; Nieuwlaat, R.; Wiercioch, W.; Schünemann, H.; Guyatt, G.
    Background: The determinants of guideline panels’ recommendations remain uncertain. Objective: To investigate factors considered by members of 8 panels convened by the American Society of Hematology (ASH) to develop guidelines using GRADE system. Study Design and Setting: web-based survey of the participants in the ASH guidelines panels. Analysis: two level hierarchical, random-effect, multivariable regression analysis to explore the relation between GRADE and non-GRADE factors and strength of recommendations (SOR). Results: In the primary analysis, certainty in evidence [OR=1.83; (95CI% 1.45 to 2.31)], balance of benefits and harms [OR=1.49 (95CI% 1.30 to 1.69)] and variability in patients’ values and preferences [OR=1.47 (95CI% 1.15 to 1.88)] proved the strongest predictors of SOR. In a secondary analysis, certainty of evidence was associated with a strong recommendation [OR=3.60 (95% CI 2.16 to 6.00)] when panel members recommended “for” interventions but not when they made recommendations “against” [OR=0.98 (95%CI: 0.57 to 1.8)] consistent with “yes” bias. Agreement between individual members and the group in rating SOR varied (kappa ranged from -0.01 to 0.64). Conclusion: GRADE’s conceptual framework proved, in general, highly associated with SOR. Failure of certainty of evidence to be associated with SOR against an intervention, suggest the need for improvements in the process.
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    Thinking styles and regret in physicians
    (PLOS, 2015) Djulbegovic, Mia; Beckstead, J.; Elqayam, Shira; Reljic, T.; Kumar, A.; Paidas, C.; Djulbegovic, B.
    Background Decision-making relies on both analytical and emotional thinking. Cognitive reasoning styles (e.g. maximizing and satisficing tendencies) heavily influence analytical processes, while affective processes are often dependent on regret. The relationship between regret and cognitive reasoning styles has not been well studied in physicians, and is the focus of this paper. Methods A regret questionnaire and 6 scales measuring individual differences in cognitive styles (maximizing-satisficing tendencies; analytical vs. intuitive reasoning; need for cognition; intolerance toward ambiguity; objectivism; and cognitive reflection) were administered through a web-based survey to physicians of the University of South Florida. Bonferroni’s adjustment was applied to the overall correlation analysis. The correlation analysis was also performed without Bonferroni’s correction, given the strong theoretical rationale indicating the need for a separate hypothesis. We also conducted a multivariate regression analysis to identify the unique influence of predictors on regret. Results 165 trainees and 56 attending physicians (age range 25 to 69) participated in the survey. After bivariate analysis we found that maximizing tendency positively correlated with regret with respect to both decision difficulty (r=0.673; p<0.001) and alternate search strategy (r=0.239; p=0.002). When Bonferroni’s correction was not applied, we also found a negative relationship between satisficing tendency and regret (r=-0.156; p=0.021). In trainees, but not faculty, regret negatively correlated with rational-analytical thinking (r=-0.422; p<0.001), need for cognition (r=-0.340; p<0.001), and objectivism (r=-0.309; p=0.003) and positively correlated with ambiguity intolerance (r=0.285; p=0.012). However, after conducting a multivariate regression analysis, we found that regret was positively associated with maximizing only with respect to decision difficulty (r=0.791; p<0.001), while it was negatively associated with satisficing (r=-0.257; p=0.020) and objectivism (r=-0.267; p=0.034). We found no statistically significant relationship between regret and overall accuracy on conditional inferential tasks. Conclusion Regret in physicians is strongly associated with their tendency to maximize; i.e. the tendency to consider more choices among abundant options leads to more regret. However, physicians who exhibit satisficing tendency – the inclination to accept a “good enough” solution – feel less regret. Our observation that objectivism is a negative predictor of regret indicates that the tendency to seek and use empirical data in decision-making leads to less regret. Therefore, promotion of evidence-based reasoning may lead to lower regret.