Algorithms in medical decision-making and in everyday life: what’s the difference?

David Chartash; Michael A. Bruno

doi:10.1515/dx-2024-0010

Article

Algorithms in medical decision-making and in everyday life: what’s the difference?

David Chartash and Michael A. Bruno

Published/Copyright: February 23, 2024

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From the journal Diagnosis Volume 11 Issue 3

Abstract

Algorithms are a ubiquitous part of modern life. Despite being a component of medicine since early efforts to deploy computers in medicine, clinicians’ resistance to using decision support and use algorithms to address cognitive biases has been limited. This resistance is not just limited to the use of algorithmic clinical decision support, but also evidence and stochastic reasoning and the implications of the forcing function of the electronic medical record. Physician resistance to algorithmic support in clinical decision making is in stark contrast to their general acceptance of algorithmic support in other aspects of life.

Keywords: artificial intelligence; clinical informatics; evidence-based medicine; cognitive science

Corresponding author: David Chartash, Section for Biomedical Informatics and Data Science, Yale University School of Medicine, New Haven, USA; and School of Medicine, University College Dublin–National University of Ireland, Dublin, Republic of Ireland, E-mail: david.chartash@yale.edu

Research ethics: Not applicable.
Informed consent: Not applicable.
Research funding: Not applicable.
Author contributions: DC and MB both provided substantial contributions to the conception and design of the paper, drafted the work, approved the final version to be published and agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.
Competing interests: The authors state no conflict of interest.
Data availability: Not applicable.

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Received: 2024-01-15

Accepted: 2024-02-06

Published Online: 2024-02-23

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https://doi.org/10.1515/dx-2024-0010

Keywords for this article

artificial intelligence; clinical informatics; evidence-based medicine; cognitive science