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Cognitive biases associated with medical decisions: a systematic review

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      Abstract

      Background

      Cognitive biases and personality traits (aversion to risk or ambiguity) may lead to diagnostic inaccuracies and medical errors resulting in mismanagement or inadequate utilization of resources. We conducted a systematic review with four objectives: 1) to identify the most common cognitive biases, 2) to evaluate the influence of cognitive biases on diagnostic accuracy or management errors, 3) to determine their impact on patient outcomes, and 4) to identify literature gaps.

      Methods

      We searched MEDLINE and the Cochrane Library databases for relevant articles on cognitive biases from 1980 to May 2015. We included studies conducted in physicians that evaluated at least one cognitive factor using case-vignettes or real scenarios and reported an associated outcome written in English. Data quality was assessed by the Newcastle-Ottawa scale. Among 114 publications, 20 studies comprising 6810 physicians met the inclusion criteria. Nineteen cognitive biases were identified.

      Results

      All studies found at least one cognitive bias or personality trait to affect physicians. Overconfidence, lower tolerance to risk, the anchoring effect, and information and availability biases were associated with diagnostic inaccuracies in 36.5 to 77 % of case-scenarios. Five out of seven (71.4 %) studies showed an association between cognitive biases and therapeutic or management errors. Of two (10 %) studies evaluating the impact of cognitive biases or personality traits on patient outcomes, only one showed that higher tolerance to ambiguity was associated with increased medical complications (9.7 % vs 6.5 %; p = .004). Most studies (60 %) targeted cognitive biases in diagnostic tasks, fewer focused on treatment or management (35 %) and on prognosis (10 %). Literature gaps include potentially relevant biases (e.g. aggregate bias, feedback sanction, hindsight bias) not investigated in the included studies. Moreover, only five (25 %) studies used clinical guidelines as the framework to determine diagnostic or treatment errors. Most studies ( n = 12, 60 %) were classified as low quality.

      Conclusions

      Overconfidence, the anchoring effect, information and availability bias, and tolerance to risk may be associated with diagnostic inaccuracies or suboptimal management. More comprehensive studies are needed to determine the prevalence of cognitive biases and personality traits and their potential impact on physicians’ decisions, medical errors, and patient outcomes.

      Electronic supplementary material

      The online version of this article (doi:10.1186/s12911-016-0377-1) contains supplementary material, which is available to authorized users.

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      Most cited references 65

      • Record: found
      • Abstract: found
      • Article: not found

      Judgment under Uncertainty: Heuristics and Biases.

       A Tversky,  D Kahneman (1974)
      This article described three heuristics that are employed in making judgements under uncertainty: (i) representativeness, which is usually employed when people are asked to judge the probability that an object or event A belongs to class or process B; (ii) availability of instances or scenarios, which is often employed when people are asked to assess the frequency of a class or the plausibility of a particular development; and (iii) adjustment from an anchor, which is usually employed in numerical prediction when a relevant value is available. These heuristics are highly economical and usually effective, but they lead to systematic and predictable errors. A better understanding of these heuristics and of the biases to which they lead could improve judgements and decisions in situations of uncertainty.
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        • Record: found
        • Abstract: found
        • Article: not found

        The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration.

        Systematic reviews and meta-analyses are essential to summarize evidence relating to efficacy and safety of health care interventions accurately and reliably. The clarity and transparency of these reports, however, is not optimal. Poor reporting of systematic reviews diminishes their value to clinicians, policy makers, and other users. Since the development of the QUOROM (QUality Of Reporting Of Meta-analysis) Statement-a reporting guideline published in 1999-there have been several conceptual, methodological, and practical advances regarding the conduct and reporting of systematic reviews and meta-analyses. Also, reviews of published systematic reviews have found that key information about these studies is often poorly reported. Realizing these issues, an international group that included experienced authors and methodologists developed PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) as an evolution of the original QUOROM guideline for systematic reviews and meta-analyses of evaluations of health care interventions. The PRISMA Statement consists of a 27-item checklist and a four-phase flow diagram. The checklist includes items deemed essential for transparent reporting of a systematic review. In this Explanation and Elaboration document, we explain the meaning and rationale for each checklist item. For each item, we include an example of good reporting and, where possible, references to relevant empirical studies and methodological literature. The PRISMA Statement, this document, and the associated Web site (www.prisma-statement.org) should be helpful resources to improve reporting of systematic reviews and meta-analyses.
          Bookmark
          • Record: found
          • Abstract: found
          • Article: not found

          Incidence of adverse drug events and potential adverse drug events. Implications for prevention. ADE Prevention Study Group.

          To assess incidence and preventability of adverse drug events (ADEs) and potential ADEs. To analyze preventable events to develop prevention strategies. Prospective cohort study. All 4031 adult admissions to a stratified random sample of 11 medical and surgical units in two tertiary care hospitals over a 6-month period. Units included two medical and three surgical intensive care units and four medical and two surgical general care units. Adverse drug events and potential ADEs. Incidents were detected by stimulated self-report by nurses and pharmacists and by daily review of all charts by nurse investigators. Incidents were subsequently classified by two independent reviewers as to whether they represented ADEs or potential ADEs and as to severity and preventability. Over 6 months, 247 ADEs and 194 potential ADEs were identified. Extrapolated event rates were 6.5 ADEs and 5.5 potential ADEs per 100 nonobstetrical admissions, for mean numbers per hospital per year of approximately 1900 ADEs and 1600 potential ADEs. Of all ADEs, 1% were fatal (none preventable), 12% life-threatening, 30% serious, and 57% significant. Twenty-eight percent were judged preventable. Of the life-threatening and serious ADEs, 42% were preventable, compared with 18% of significant ADEs. Errors resulting in preventable ADEs occurred most often at the stages of ordering (56%) and administration (34%); transcription (6%) and dispensing errors (4%) were less common. Errors were much more likely to be intercepted if the error occurred earlier in the process: 48% at the ordering stage vs 0% at the administration stage. Adverse drug events were common and often preventable; serious ADEs were more likely to be preventable. Most resulted from errors at the ordering stage, but many also occurred at the administration stage. Prevention strategies should target both stages of the drug delivery process.
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            Author and article information

            Affiliations
            [1 ]Department of Economics, University of Zurich, Zürich, Switzerland
            [2 ]Stroke Program, Department of Medicine, St Michael’s Hospital, University of Toronto, Toronto, M5C 1R6 Canada
            [3 ]Institute for Clinical Evaluative Sciences (ICES), Toronto, Canada
            [4 ]University of Zurich, 9 Blumplistrasse, Zurich, (8006) Switzerland
            Contributors
            gustavo.saposnik@econ.uzh.ch
            Journal
            BMC Med Inform Decis Mak
            BMC Med Inform Decis Mak
            BMC Medical Informatics and Decision Making
            BioMed Central (London )
            1472-6947
            3 November 2016
            3 November 2016
            2016
            : 16
            27809908 5093937 377 10.1186/s12911-016-0377-1
            © The Author(s). 2016

            Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

            Funding
            Funded by: Swiss National Science Foundation
            Award ID: CRSII3_141965
            Funded by: FundRef http://dx.doi.org/10.13039/100004411, Heart and Stroke Foundation of Canada;
            Award ID: NA
            Award Recipient :
            Categories
            Research Article
            Custom metadata
            © The Author(s) 2016

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