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Please use this identifier to cite or link to this item: https://hdl.handle.net/11055/1109
Title: Cognitive biases in diagnosis and decision making during anaesthesia and intensive care
Authors: Webster CS
Taylor S
Weller JM 
Keywords: bias reduction
diagnosis
dual process theory
Issue Date: 1-Nov-2021
Source: 21(11):420-425
Abstract: Diagnosing the patient's condition is perhaps the single most important task performed by clinicians, as an incorrect diagnosis may lead to an incorrect management plan. In high-intensity domains such as anaesthesia and intensive care, diagnosis is often performed under time pressure and in rapidly evolving and uncertain situations, putting clinicians at particular risk of error. In this context, cognitive bias is typically defined as flaws or distortions in judgment and decision making that can lead to poor outcomes. More than 100 different identifiable biases have been reported in healthcare. 1 The overall rate of incorrect diagnosis in healthcare has been estimated to be between 10% and 15%, with autopsy studies suggesting higher rates. 1 , 2 Human error is known to be a major contributor to preventable harm to patients, associated with substantial injury, death and large financial costs. 3 Therefore, reducing or eliminating cognitive biases would potentially reduce harm. However, reducing cognitive bias is easier to propose than to achieve. In a forthcoming paper we will consider the effects of interpersonal bias on the interactions between members of clinical teams, between clinicians and their patients, and the consequences for healthcare outcomes. In this article, we consider the underlying causes of cognitive biases, why they are so difficult to eliminate, several common manifestations of bias, and the evidence for the effectiveness of strategies to reduce cognitive biases and their consequences.
Description: LEARNING OBJECTIVES By reading this article, you should be able to: • Discuss the widely accepted dual process theory of cognition and its relevance to bias and diagnosis. • Illustrate the evidence base for strategies to reduce bias during diagnosis. • Apply evidence to the development of more effective bias reduction strategies.
URI: http://hdl.handle.net/11055/1109
ISSN: 2058-5349
Appears in Collections:Scholarly and Clinical

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