Search

The article discusses the use of cognitive debiasing in the medical profession. Particular focus is given to the prevention of errors in diagnosis and other forms of clinical decision making. Details on the cognitive biases known as search satisficing and confirmation bias are presented. Dual-process theory, which describes a two-tiered mental system for decision-making, is also discussed.

A letter to the editor is presented in response to the article "The Vanishing Lung" by N.N. Shah, R. Bhargava and Z. Ahmed published in a previous issue.

Abstract: Introduction: Although patient safety has improved steadily, harm remains a substantial global challenge. Additionally, safety needs to be ensured not only in hospitals but also across the continuum of care. Better understanding of the complex cognitive factors influencing health care–related decisions and organizational cultures could lead to more rational approaches, and thereby to further improvement. Hypothesis: A model integrating the concepts underlying Reason's Swiss cheese theory and the cognitive‐affective biases plus cascade could advance the understanding of cognitive‐affective processes that underlie decisions and organizational cultures across the continuum of care. Methods: Thematic analysis, qualitative information from several sources being used to support argumentation. Discussion: Complex covert cognitive phenomena underlie decisions influencing health care. In the integrated model, the Swiss cheese slices represent dynamic cognitive‐affective (mental) gates: Reason's successive layers of defence. Like firewalls and antivirus programs, cognitive‐affective gates normally allow the passage of rational decisions but block or counter unsounds ones. Gates can be breached (ie, holes created) at one or more levels of organizations, teams, and individuals, by (1) any element of cognitive‐affective biases plus (conflicts of interest and cognitive biases being the best studied) and (2) other potential error‐provoking factors. Conversely, flawed decisions can be blocked and consequences minimized; for example, by addressing cognitive biases plus and error‐provoking factors, and being constantly mindful. Informed shared decision making is a neglected but critical layer of defence (cognitive‐affective gate). The integrated model can be custom tailored to specific situations, and the underlying principles applied to all methods for improving safety. The model may also provide a framework for developing and evaluating strategies to optimize organizational cultures and decisions. Limitations: The concept is abstract, the model is virtual, and the best supportive evidence is qualitative and indirect. Conclusions: The proposed model may help enhance rational decision making across the continuum of care, thereby improving patient safety globally. [ABSTRACT FROM AUTHOR]

Diagnostic errors comprise the leading threat to patient safety in healthcare today. Learning how to extract the lessons from cases where diagnosis succeeds or fails is a promising approach to improve diagnostic safety going forward. We present up-to-date and authoritative guidance on how the existing approaches to conducting root cause analyses (RCA's) can be modified to study cases involving diagnosis. There are several diffierences: In cases involving diagnosis, the investigation should begin immediately after the incident, and clinicians involved in the case should be members of the RCA team. The review must include consideration of how the clinical reasoning process went astray (or succeeded), and use a human-factors perspective to consider the system-related contextual factors in the diagnostic process. We present detailed instructions for conducting RCA's of cases involving diagnosis, with advice on how to identify root causes and contributing factors and select appropriate interventions., (© 2024 the author(s), published by De Gruyter, Berlin/Boston.)

Cognitive bias may lead to medical error, and awareness of cognitive pitfalls is a potential first step to addressing the negative consequences of cognitive bias (see Part 1). For decision-making processes that occur under uncertainty, which encompass most physician decisions, a so-called "adaptive toolbox" is beneficial for good decisions. The adaptive toolbox is inclusive of broad strategies like cultural humility, emotional intelligence, and self-care that help combat implicit bias, negative consequences of affective bias, and optimize cognition. Additionally, the adaptive toolbox includes situational-specific tools such as heuristics, narratives, cognitive forcing functions, and fast and frugal trees. Such tools may mitigate against errors due to cultural, affective, and cognitive bias. Part 2 of this two-part series covers metacognition and cognitive bias in relation to broad and specific strategies aimed at better decision-making., (Copyright © 2024. Published by Elsevier Inc.)

Cognitive bias may lead to diagnostic error in the patient encounter. There are hundreds of different cognitive biases, but certain biases are more likely to affect patient diagnosis and management. As during morbidity and mortality rounds, retrospective evaluation of a given case, with comparison to an optimal diagnosis, can pinpoint errors in judgment and decision-making. The study of cognitive bias also illuminates how we might improve the diagnostic process. In Part 1 of this series, cognitive bias is defined and placed within the background of dual process theory, emotion, heuristics, and the more neutral term judgment and decision-making bias., (Copyright © 2024. Published by Elsevier Inc.)

The historical tendency to view medicine as both an art and a science may have contributed to a disinclination among clinicians towards cognitive science. In particular, this has had an impact on the approach towards the diagnostic process which is a barometer of clinical decision-making behaviour and is increasingly seen as a yardstick of clinician calibration and performance. The process itself is more complicated and complex than was previously imagined, with multiple variables that are difficult to predict, are interactive, and show nonlinearity. They appear to characterise a complex adaptive system. Many aspects of the diagnostic process, including the psychophysics of signal detection and discrimination, ergonomics, probability theory, decision analysis, factor analysis, causal analysis and more recent developments in judgement and decision-making (JDM), especially including the domain of heuristics and cognitive and affective biases, appear fundamental to a good understanding of it. A preliminary analysis of factors such as manifestness of illness and others that may impede clinicians' awareness and understanding of these issues is proposed here. It seems essential that medical trainees be explicitly and systematically exposed to specific areas of cognitive science during the undergraduate curriculum, and learn to incorporate them into clinical reasoning and decision-making. Importantly, this understanding is needed for the development of cognitive bias mitigation and improved calibration of JDM in clinical practice., (© 2023. The Author(s).)

Medical error is now recognized as one of the leading causes of death in the United States. Of the medical errors, diagnostic failure appears to be the dominant contributor, failing in a significant number of cases, and associated with a high degree of morbidity and mortality. One of the significant contributors to diagnostic failure is the cognitive performance of the provider, how they think and decide about the process of diagnosis. This thinking deficit in clinical reasoning, referred to as a mindware gap, deserves the attention of medical educators. A variety of specific approaches are outlined here that have the potential to close the gap., (© 2021 Walter de Gruyter GmbH, Berlin/Boston.)

Diagnostic failure has emerged as one of the most significant threats to patient safety. It is important to understand the antecedents of such failures both for clinicians in practice as well is those in training. A consensus has developed in the literature that the majority of failures are due to individual or system factors or some combination of the two. A major source of variance in individual clinical performance is cognitive and affective biases; however, their role in clinical decision making has been difficult to assess partly because they are difficult to investigate experimentally. A significant drawback has been that experimental manipulations appear to confound the assessment of the context surrounding the diagnostic process itself. We conducted an exercise on selected actual cases of diagnostic errors to explore the effect of biases in the 'real world' emergency medicine (EM) context. Thirty anonymized EM cases were analysed in depth through a process of root cause analysis that included an assessment of error-producing conditions (EPCs), knowledge-based errors, and how clinicians were thinking and deciding during each case. A prominent feature of the exercise was the identification of the occurrence of and interaction between specific cognitive and affective biases, through a process called cognitive autopsy. The cases covered a broad range of diagnoses across a wide variety of disciplines. A total of 24 discrete cognitive and affective biases that contributed to misdiagnosis were identified and their incidence recorded. Five to six biases were detected per case, and observed on 168 occasions across the 30 cases. Thirteen EPCs were identified. Knowledge-based errors were rare, occurring in only five definite instances. The ordinal position in which biases appeared in the diagnostic process was recorded. This experiment provides a baseline for investigating and understanding the critical role that biases play in clinical decision making as well as providing a credible explanation for why diagnoses fail., Competing Interests: The authors have declared that no competing interests exist., (Copyright © 2021, Croskerry et al.)

Test ordering is an integral part of clinical decision making. Variation in test-ordering behavior appears to reflect uncertainty in the clinical reasoning and decision-making process. Among decision makers, novices function mostly in the analytic mode of reasoning, experiencing high levels of uncertainty and, therefore, account for the most variance. While less discriminate test ordering has both economical and clinical downsides, it nevertheless remains a rite of passage along the road toward expertise. In response to the article by Iwashyna and colleagues, the author of this commentary reflects on the implications of test-ordering behavior in the academic medicine setting. The process of ordering tests can serve purposes other than the obvious, not the least of which allows the decision maker additional time for reflection in the decision-making process, perhaps leading to a less mindless and more mindful approach. The author observes that test-ordering behavior of novitiates might be optimized through a variety of strategies that improve both active and passive learning in the clinical environment. In addition to specific education around costs, as well as Bayesian considerations, active learning importantly requires exposure to those processes that may subvert clinical reasoning, notably cognitive biases. Passive learning is enhanced in supportive environments. Throughout, those who supervise and teach should provide effective models.

Both systemic and individual factors contribute to missed or delayed diagnoses. Among the multiple factors that impact clinical performance of the individual, the caliber of cognition is perhaps the most relevant and deserves our attention and understanding. In the last few decades, cognitive psychologists have gained substantial insights into the processes that underlie cognition, and a new, universal model of reasoning and decision making has emerged, Dual Process Theory. The theory has immediate application to medical decision making and provides an overall schema for understanding the variety of theoretical approaches that have been taken in the past. The model has important practical applications for decision making across the multiple domains of healthcare, and may be used as a template for teaching decision theory, as well as a platform for future research. Importantly, specific operating characteristics of the model explain how diagnostic failure occurs.

This case describes a 45-year-old woman with significant respiratory distress secondary to a left-sided pleural effusion that mandated an urgent thoracentesis. An adverse event occurred when the physician performed the procedure on the incorrect side of the patient. Results of the incident investigation followed by a discussion of medical errors models, common errors types, human factors considerations, and conditions that contribute to error are presented. Pertinent case-specific and general concepts of a system approach to reduce this type of medical error are discussed, and educational recommendations are offered.