The information distortion bias: implications for medical decisions

Abstract

Context Every diagnosis involves an act of decision making, which requires proper evaluation of information. However, even seemingly objective information can require interpretation, often without our conscious awareness. In this cross‐cutting edge article we describe the phenomenon of leader‐driven information distortion (ID) and its implications for medical education. Information distortion Recent research indicates that one threat to good decisions is a biased interpretation of information to favour one alternative course of action over another. Once an alternative emerges as a leader during a decision there is a strong tendency to evaluate subsequent information as supporting that option. This can occur when deciding between two competing diagnoses. It is particularly a concern if diagnostic tests provide potentially ambiguous results. This leader‐driven ID is pre‐decisional in nature, in that it develops during a decision and involves the interpretation of information available prior to the final decision or diagnosis, with different interpretations possible depending on whichever alternative is the leader. Studies reveal that the distortion bias is pervasive in decisions, and that awareness of the act of distortion is low in decision makers. Application to medical education Empirical research has confirmed the presence of leader‐driven ID in hypothetical diagnoses made by physicians. ID creates two threats to medical decisions: First, it can make a diagnosis sticky in that it is resistant to being overturned by contradictory information. Second, it can promote unwarranted certainty in a diagnosis. The outcome may be premature closure, unnecessary testing or incorrect treatment, resulting in delayed or missed diagnoses. Methods This paper summarises research related to leader‐driven ID in medical and professional decisions and discusses various approaches directed towards reducing ID. A framework and language are provided for thinking about and discussing ID in medical decisions and medical education. Courses of action for mitigating the effects of ID are suggested.

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“…Another reason for the incorrect or poor knowledge of health workers on MiP delivery directives could be the inherent limitation of the ToT strategy. The ToT strategy is hinged on transferring information from one person to another, where there could be distortion of information (22), especially, if training manuals are not made available to the district level managers to use as reference materials for health workers. Health workforce factors related to lack of knowledge of policy directives resulting in missed opportunities to deliver IPTp-SP to pregnant women have been reported in a number of studies (23,24,25,26).…”

There is no shortcut to de‐biasing biases

“…This definition closely resembles what has been described in the literature as ‘confirmation bias’. However, Boyle and Purdon maintain that it is the emphasis on the disfavouring of the non‐leading alternative that distinguishes information distortion bias from simple confirmation bias . Although this is an interesting idea meriting further scrutiny, this commentary focuses on Boyle and Purdon's proposal to de‐bias information distortion bias …”

“…In their article ‘The Information Distortion Bias: Implications for Medical Decisions’, Boyle and Purdon introduce ‘information distortion bias’ as a new addition to the continually growing list of biases threatening diagnostic accuracy . Information distortion bias proposes that whenever a leading diagnosis emerges, subsequent information will be interpreted as supporting that diagnosis or disfavouring a non‐leading diagnosis.…”

“…As a first approach to de‐biasing, Boyle and Purdon suggest training to create awareness . We are sceptical of this idea because there is currently no convincing evidence that de‐biasing strategies, such as metacognitive awareness, cognitive forcing strategies and teaching interventions directed at cognitive de‐biasing, are effective.…”

“…A more interesting suggestion by Boyle and Purdon, which connects well with the current technology zeitgeist, concerns the use of artificial intelligence (AI) to de‐bias information distortion and improve medical decision making . There is some research suggesting that technology can be useful as a decision support system in authentic clinical settings .…”