Dual process models of clinical reasoning: The central role of knowledge in diagnostic expertise

Dual process models of clinical reasoning: The central role of knowledge in diagnostic expertise

Abstract

Rationale: Research on diagnostic reasoning has been conducted for fifty years or more. There is growing consensus that there are two distinct processes involved in human diagnostic reasoning: System One, a rapid retrieval of possible diagnostic hypotheses, largely automatic and based to a large part on experiential knowledge, and System Two, a slower, analytical, conscious application of formal knowledge to arrive at a diagnostic conclusion. However, within this broad framework, controversy and disagreement abound. In particular, many authors have suggested that the root cause of diagnostic errors is cognitive biases originating in System One and propose that educating learners about the types of cognitive biases and their impact on diagnosis would have a major influence on error reduction.

Aims and Objectives: In the present paper, we take issue with these claims. Method: We reviewed the literature to examine the extent to which this theoretical model is supported by the evidence.

Results: We show that evidence derived from fundamental research in human cognition and studies in clinical medicine challenges the basic assumptions of this theory-that errors arise in System One processing as a consequence of cognitive biases, and are corrected by slow, deliberative analytical processing. We claim that, to the contrary, errors derive from both System One and System Two reasoning, that they arise from lack of access to the appropriate knowledge, not from errors of processing, and that the two processes are not essential to the process of diagnostic reasoning.

Conclusions: The two processing modes are better understood as a consequence of the nature of the knowledge retrieved, not as independent processes.

One INTRODUCTION

In the past few years, there has been increasing attention to the prevalence of diagnostic errors and its impact on health outcomes. A number of tools to mitigate diagnostic errors have been proposed, ranging from checklists to electronic diagnostic support systems. Empirical studies, typically in controlled settings, have demonstrated consistent, albeit moderate, success in reducing diagnostic error using these approaches. However there are limitations to implementation in clinical practice. Clinicians are reluctant to accept and apply diagnostic supports. Additionally, Sibbald and colleagues demonstrated that the benefit of an electronic diagnostic support system varies with the clinician's experience and whether it is accessed early or late in the diagnostic process.

Recent contributions of Sibbald and colleagues on the potential error reduction benefits of checklists and electronic diagnostic support tools, while few in comparison to the nearly five decade long research programme on diagnostic reasoning, have the potential to lead to meaningful improvements. Unfortunately, efforts to implement error reduction strategies have not been sufficiently aligned with our understanding of clinical and diagnostic reasoning processes. This misalignment between empirically tested error reduction strategies and theories of the diagnostic reasoning process has significantly slowed progress in reducing diagnostic errors. Error reduction strategies must integrate with naturalistic clinical reasoning to be effective and sustainable.

In this paper we briefly review the conclusions of research aimed at delineating diagnostic reasoning processes. We examine three common assertions about the relationship between reasoning processes and error. We critique the influential role of dual process theory on clinical reasoning research and the key assumption that the most effective error reduction strategies lie in the delineation of reasoning itself. Finally we propose a way forward that builds on evidence and theory.