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.

Ethics committees require estimates of sample size for all trials, but statistical calculations are no more accurate than estimates from historical data. Geoffrey Norman and colleagues propose some “one size fits all” numbers for different study designs

Purpose Diagnostic errors are thought to arise from cognitive biases associated with System 1 reasoning, which is rapid and unconscious. The primary hypothesis of this study was that the instruction to be slow and thorough will have no advantage in diagnostic accuracy over the instruction to proceed rapidly. Method Participants were second-year residents who volunteered after they had taken the Medical Council of Canada (MCC) Qualifying Examination Part II. Participants were tested at three Canadian medical schools (McMaster, Ottawa, and McGill) in 2010 (n = 96) and 2011 (n = 108). The intervention consisted of 20 computer-based internal medicine cases, with instructions either (1) to be as quick as possible but not make mistakes (the Speed cohort, 2010), or (2) to be careful, thorough, and reflective (the Reflect cohort, 2011). The authors examined accuracy scores on the 20 cases, time taken to diagnose cases, and MCC examination performance. Results Overall accuracy in the Speed condition was 44.5%, and in the Reflect condition was 45.0%; this was not significant. The Speed cohort took an average of 69 seconds per case versus 89 seconds for the Reflect cohort (P < .001). In both cohorts, cases diagnosed incorrectly took an average of 17 seconds longer than cases diagnosed correctly. Diagnostic accuracy was moderately correlated with performance on both written and problem-solving components of the MCC licensure examination and inversely correlated with time. Conclusions The study demonstrates that simply encouraging slowing down and increasing attention to analytical thinking is insufficient to increase diagnostic accuracy.

Background Many authors have implicated cognitive biases as a primary cause of diagnostic error. If this is so, then physicians already familiar with common cognitive biases should consistently identify biases present in a clinical workup. The aim of this paper is to determine whether physicians agree on the presence or absence of particular biases in a clinical case workup and how case outcome knowledge affects bias identification. Methods We conducted a web survey of 37 physicians. Each participant read eight cases and listed which biases were present from a list provided. In half the cases the outcome implied a correct diagnosis; in the other half, it implied an incorrect diagnosis. We compared the number of biases identified when the outcome implied a correct or incorrect primary diagnosis. Additionally, the agreement among participants about presence or absence of specific biases was assessed. Results When the case outcome implied a correct diagnosis, an average of 1.75 cognitive biases were reported; when incorrect, 3.45 biases (F=71.3, p<0.00001). Individual biases were reported from 73% to 125% more often when an incorrect diagnosis was implied. There was no agreement on presence or absence of individual biases, with κ ranging from 0.000 to 0.044. Interpretation Individual physicians are unable to agree on the presence or absence of individual cognitive biases. Their judgements are heavily influenced by hindsight bias; when the outcome implies a diagnostic error, twice as many biases are identified. The results present challenges for current error reduction strategies based on identification of cognitive biases.

Recently, clinical diagnostic reasoning has been characterized by “dual processing” models, which postulate a fast, unconscious (System 1) component and a slow, logical, analytical (System 2) component. However, there are a number of variants of this basic model, which may lead to conflicting claims. This paper critically reviews current theories and evidence about the nature of clinical diagnostic reasoning. We begin by briefly discussing the history of research in clinical reasoning. We then focus more specifically on the evidence to support dual-processing models. We conclude by identifying knowledge gaps about clinical reasoning and provide suggestions for future research. In contrast to work on analytical and nonanalytical knowledge as a basis for reasoning, these theories focus on the thinking process, not the nature of the knowledge retrieved. Ironically, this appears to be a revival of an outdated concept. Rather than defining diagnostic performance by problem-solving skills, it is now being defined by processing strategy. The version of dual processing that has received most attention in the literature in medical diagnosis might be labeled a “default/interventionist” model,¹⁷ which suggests that a default system of cognitive processes (System 1) is responsible for cognitive biases that lead to diagnostic errors and that System 2 intervenes to correct these errors. Consequently, from this model, the best strategy for reducing errors is to make students aware of the biases and to encourage them to rely more on System 2. However, an accumulation of evidence suggests that (a) strategies directed at increasing analytical (System 2) processing, by slowing down, reducing distractions, paying conscious attention, and (b) strategies directed at making students aware of the effect of cognitive biases, have no impact on error rates. Conversely, strategies based on increasing application of relevant knowledge appear to have some success and are consistent with basic research on concept formation.