The Causes of Errors in Clinical Reasoning: Cognitive Biases, Knowledge Deficits, and Dual Process Thinking
TL;DR: The authors review the medical literature to answer two substantial questions that arise from this work: to what extent do diagnostic errors originate in Type 1 (intuitive) processes versus in Type 2 (analytical) processes?
Abstract: Contemporary theories of clinical reasoning espouse a dual processing model, which consists of a rapid, intuitive component (Type 1) and a slower, logical and analytical component (Type 2) Although the general consensus is that this dual processing model is a valid representation of clinical reasoning, the causes of diagnostic errors remain unclear Cognitive theories about human memory propose that such errors may arise from both Type 1 and Type 2 reasoning Errors in Type 1 reasoning may be a consequence of the associative nature of memory, which can lead to cognitive biases However, the literature indicates that, with increasing expertise (and knowledge), the likelihood of errors decreases Errors in Type 2 reasoning may result from the limited capacity of working memory, which constrains computational processes In this article, the authors review the medical literature to answer two substantial questions that arise from this work: (1) To what extent do diagnostic errors originate in Type 1 (intuitive) processes versus in Type 2 (analytical) processes? (2) To what extent are errors a consequence of cognitive biases versus a consequence of knowledge deficits?The literature suggests that both Type 1 and Type 2 processes contribute to errors Although it is possible to experimentally induce cognitive biases, particularly availability bias, the extent to which these biases actually contribute to diagnostic errors is not well established Educational strategies directed at the recognition of biases are ineffective in reducing errors; conversely, strategies focused on the reorganization of knowledge to reduce errors have small but consistent benefits
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TL;DR: The authors argue that explicit instruction in metacognition in medical education, including awareness of cognitive biases, has the potential to reduce diagnostic errors and thus improve patient safety.
Abstract: Diagnostic errors contribute to as many as 70% of medical errors. Prevention of diagnostic errors is more complex than building safety checks into health care systems; it requires an understanding of critical thinking, of clinical reasoning, and of the cognitive processes through which diagnoses are made. When a diagnostic error is recognized, it is imperative to identify where and how the mistake in clinical reasoning occurred. Cognitive biases may contribute to errors in clinical reasoning. By understanding how physicians make clinical decisions, and examining how errors due to cognitive biases occur, cognitive bias awareness training and debiasing strategies may be developed to decrease diagnostic errors and patient harm. Studies of the impact of teaching critical thinking skills have mixed results but are limited by methodological problems.This Perspective explores the role of clinical reasoning and cognitive bias in diagnostic error, as well as the effect of instruction in metacognitive skills on improvement of diagnostic accuracy for both learners and practitioners. Recent literature questioning whether teaching critical thinking skills increases diagnostic accuracy is critically examined, as are studies suggesting that metacognitive practices result in better patient care and outcomes. Instruction in metacognition, reflective practice, and cognitive bias awareness may help learners move toward adaptive expertise and help clinicians improve diagnostic accuracy. The authors argue that explicit instruction in metacognition in medical education, including awareness of cognitive biases, has the potential to reduce diagnostic errors and thus improve patient safety.
112 citations
TL;DR: It is hypothesized that as an unintended consequence of unlearning strategies clinicians may experience “reactance,” ie, feel their professional prerogative is being violated and, consequently, increase their commitment to the ineffective practice.
Abstract: Rationale and objectives One way to understand medical overuse at the clinician level is in terms of clinical decision-making processes that are normally adaptive but become maladaptive. In psychology, dual process models of cognition propose 2 decision-making processes. Reflective cognition is a conscious process of evaluating options based on some combination of utility, risk, capabilities, and/or social influences. Automatic cognition is a largely unconscious process occurring in response to environmental or emotive cues based on previously learned, ingrained heuristics. De-implementation strategies directed at clinicians may be conceptualized as corresponding to cognition: (1) a process of unlearning based on reflective cognition and (2) a process of substitution based on automatic cognition. Results We define unlearning as a process in which clinicians consciously change their knowledge, beliefs, and intentions about an ineffective practice and alter their behaviour accordingly. Unlearning has been described as "the questioning of established knowledge, habits, beliefs and assumptions as a prerequisite to identifying inappropriate or obsolete knowledge underpinning and/or embedded in existing practices and routines." We hypothesize that as an unintended consequence of unlearning strategies clinicians may experience "reactance," ie, feel their professional prerogative is being violated and, consequently, increase their commitment to the ineffective practice. We define substitution as replacing the ineffective practice with one or more alternatives. A substitute is a specific alternative action or decision that either precludes the ineffective practice or makes it less likely to occur. Both approaches may work independently, eg, a substitute could displace an ineffective practice without changing clinicians' knowledge, and unlearning could occur even if no alternative exists. For some clinical practice, unlearning and substitution strategies may be most effectively used together. Conclusions By taking into account the dual process model of cognition, we may be able to design de-implementation strategies matched to clinicians' decision-making processes and avoid unintended consequence.
69 citations
Cites background from "The Causes of Errors in Clinical Re..."
...If physicians are enjoined to spend extra time on reaching a diagnosis in complex cases, diagnostic accuracy improves for experienced physicians but declines for inexperienced physicians.(22) Finally, reflective cognition cannot be used endlessly; an individual's ability to exert self‐control and engage in reflective cognition (eg, problem solving, self‐regulating behaviour,...
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...They found that after reflecting on an initial decision during an opportunity to revisit and amend their diagnosis, physicians are likely to make the diagnosis less accurate.(22) This may be because expert clinicians develop higher‐order concepts to represent clinical information and related diagnostic choices—a type of automatic cognition....
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TL;DR: This article focuses on the initial step of hypothesis generation and review how expert clinicians use experiential knowledge to intuitively recognize a medical diagnosis.
56 citations
TL;DR: Core principles of patient safety in the context of ILS are discussed, including the systems view of error, culture of safety, and contributing factors such as cognitive bias, as well as the topics of medical error disclosure and second victim syndrome.
Abstract: Incident learning is a key component for maintaining safety and quality in healthcare. Its use is well established and supported by professional society recommendations, regulations and accreditation, and objective evidence. There is an active interest in incident learning systems (ILS) in radiation oncology, with over 40 publications since 2010. This article is intended as a comprehensive topic review of ILS in radiation oncology, including history and summary of existing literature, nomenclature and categorization schemas, operational aspects of ILS at the institutional level including event handling and root cause analysis, and national and international ILS for shared learning. Core principles of patient safety in the context of ILS are discussed, including the systems view of error, culture of safety, and contributing factors such as cognitive bias. Finally, the topics of medical error disclosure and second victim syndrome are discussed. In spite of the rapid progress and understanding of ILS, challenges remain in applying ILS to the radiation oncology context. This comprehensive review may serve as a springboard for further work.
52 citations
TL;DR: There is a paucity of data to support an educational gold standard for teaching critical thinking, but it is believed that five strategies, routed in cognitive theory and personal teaching experiences, provide an effective framework to teach critical thinking in the intensive care unit.
Abstract: Critical thinking, the capacity to be deliberate about thinking, is increasingly the focus of undergraduate medical education, but is not commonly addressed in graduate medical education. Without critical thinking, physicians, and particularly residents, are prone to cognitive errors, which can lead to diagnostic errors, especially in a high-stakes environment such as the intensive care unit. Although challenging, critical thinking skills can be taught. At this time, there is a paucity of data to support an educational gold standard for teaching critical thinking, but we believe that five strategies, routed in cognitive theory and our personal teaching experiences, provide an effective framework to teach critical thinking in the intensive care unit. The five strategies are: make the thinking process explicit by helping learners understand that the brain uses two cognitive processes: type 1, an intuitive pattern-recognizing process, and type 2, an analytic process; discuss cognitive biases, such as premature closure, and teach residents to minimize biases by expressing uncertainty and keeping differentials broad; model and teach inductive reasoning by utilizing concept and mechanism maps and explicitly teach how this reasoning differs from the more commonly used hypothetico-deductive reasoning; use questions to stimulate critical thinking: "how" or "why" questions can be used to coach trainees and to uncover their thought processes; and assess and provide feedback on learner's critical thinking. We believe these five strategies provide practical approaches for teaching critical thinking in the intensive care unit.
50 citations
References
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TL;DR: Tested the 2-process theory of detection, search, and attention presented by the current authors (1977) in a series of experiments and demonstrated the qualitative difference between 2 modes of information processing: automatic detection and controlled search.
Abstract: Tested the 2-process theory of detection, search, and attention presented by the current authors (1977) in a series of experiments. The studies (a) demonstrate the qualitative difference between 2 modes of information processing: automatic detection and controlled search; (b) trace the course of the
7,032 citations
TL;DR: This article reviews a diverse set of proposals for dual processing in higher cognition within largely disconnected literatures in cognitive and social psychology and suggests that while some dual-process theories are concerned with parallel competing processes involving explicit and implicit knowledge systems, others are concerns with the influence of preconscious processes that contextualize and shape deliberative reasoning and decision-making.
Abstract: This article reviews a diverse set of proposals for dual processing in higher cognition within largely disconnected literatures in cognitive and social psychology. All these theories have in common the distinction between cognitive processes that are fast, automatic, and unconscious and those that are slow, deliberative, and conscious. A number of authors have recently suggested that there may be two architecturally (and evolutionarily) distinct cognitive systems underlying these dual-process accounts. However, it emerges that (a) there are multiple kinds of implicit processes described by different theorists and (b) not all of the proposed attributes of the two kinds of processing can be sensibly mapped on to two systems as currently conceived. It is suggested that while some dual-process theories are concerned with parallel competing processes involving explicit and implicit knowledge systems, others are concerned with the influence of preconscious processes that contextualize and shape deliberative reasoning and decision-making.
3,859 citations
TL;DR: The distinction between rule-based and associative systems of reasoning has been discussed extensively in cognitive psychology as discussed by the authors, where the distinction is based on the properties that are normally assigned to rules.
Abstract: Distinctions have been proposed between systems of reasoning for centuries. This article distills properties shared by many of these distinctions and characterizes the resulting systems in light of recent findings and theoretical developments. One system is associative because its computations reflect similarity structure and relations of temporal contiguity. The other is "rule based" because it operates on symbolic structures that have logical content and variables and because its computations have the properties that are normally assigned to rules. The systems serve complementary functions and can simultaneously generate different solutions to a reasoning problem. The rule-based system can suppress the associative system but not completely inhibit it. The article reviews evidence in favor of the distinction and its characterization. One of the oldest conundrums in psychology is whether people are best conceived as parallel processors of information who operate along diffuse associative links or as analysts who operate by deliberate and sequential manipulation of internal representations. Are inferences drawn through a network of learned associative pathways or through application of a kind of"psychologic" that manipulates symbolic tokens in a rule-governed way? The debate has raged (again) in cognitive psychology for almost a decade now. It has pitted those who prefer models of mental phenomena to be built out of networks of associative devices that pass activation around in parallel and distributed form (the way brains probably function) against those who prefer models built out of formal languages in which symbols are composed into sentences that are processed sequentially (the way computers function). An obvious solution to the conundrum is to conceive of the
3,488 citations
TL;DR: In this article, the authors present a theory in which automatization is construed as the acquisition of a domainspeciSc knowledge base, formed of separate representations, instances, of each exposure to the task.
Abstract: This article presents a theory in which automatization is construed as the acquisition of a domainspeciSc knowledge base, formed of separate representations, instances, of each exposure to the task. Processing is considered automatic if it relies on retrieval of stored instances, which will occur only after practice in a consistent environment. Practice is important because it increases the amount retrieved and the speed of retrieval; consistency is important because it ensures that the retrieved instances will be useful. The theory accounts quantitatively for the power-function speed-up and predicts a power-function reduction in the standard deviation that is constrained to have the same exponent as the power function for the speed-up. The theory accounts for qualitative properties as well, explaining how some may disappear and others appear with practice. More generally, it provides an alternative to the modal view of automaticity, arguing that novice performance is limited by a lack of knowledge rather than a scarcity of resources. The focus on learning avoids many problems with the modal view that stem from its focus on resource limitations.
3,222 citations
01 Jul 2002
TL;DR: The program of research now known as the heuristics and biases approach began with a survey of 84 participants at the 1969 meetings of the Mathematical Psychology Society and the American Psychological Association (Tversky & Kahneman, 1971) as discussed by the authors.
Abstract: The program of research now known as the heuristics and biases approach began with a survey of 84 participants at the 1969 meetings of the Mathematical Psychology Society and the American Psychological Association (Tversky & Kahneman, 1971). The respondents, including several authors of statistics texts, were asked realistic questions about the robustness of statistical estimates and the replicability of research results. The article commented tongue-in-heek on the prevalence of a belief that the law of large numbers applies to small numbers as well: Respondents placed too much confidence in the results of small samples, and their statistical judgments showed little sensitivity to sample size. The mathematical psychologists who participated in the survey not only should have known better – they did know better. Although their intuitive guesses were off the mark, most of them could have computed the correct answers on the back of an envelope. These sophisticated individuals apparently had access to two distinct approaches for answering statistical questions: one that is spontaneous, intuitive, effortless, and fast; and another that is deliberate, rule-governed, effortful, and slow. The persistence of large biases in the guesses of experts raised doubts about the educability of statistical intuitions. Moreover, it was known that the same biases affect choices in the real world, where researchers commonly select sample sizes that are too small to provide a fair test of their hypotheses (Cohen, 1969, 1992).
2,740 citations