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Review
. 2023 Nov 10;4(11):100864.
doi: 10.1016/j.patter.2023.100864.

A normative framework for artificial intelligence as a sociotechnical system in healthcare

Melissa D McCradden  1   2   3 , Shalmali Joshi  4 , James A Anderson  1   5 , Alex John London  6
Affiliations
Review

A normative framework for artificial intelligence as a sociotechnical system in healthcare

Melissa D McCradden et al. Patterns (N Y). .

Abstract

Artificial intelligence (AI) tools are of great interest to healthcare organizations for their potential to improve patient care, yet their translation into clinical settings remains inconsistent. One of the reasons for this gap is that good technical performance does not inevitably result in patient benefit. We advocate for a conceptual shift wherein AI tools are seen as components of an intervention ensemble. The intervention ensemble describes the constellation of practices that, together, bring about benefit to patients or health systems. Shifting from a narrow focus on the tool itself toward the intervention ensemble prioritizes a "sociotechnical" vision for translation of AI that values all components of use that support beneficial patient outcomes. The intervention ensemble approach can be used for regulation, institutional oversight, and for AI adopters to responsibly and ethically appraise, evaluate, and use AI tools.

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Conflict of interest statement

M.D.M. receives research funding support from Canadian Institutes of Health Research (CIHR), the Edwin Leong Centre for Healthy Children, the Dalla Lana School of Public Health, and the SickKids Foundation.

Figures

Figure 1
Figure 1
The intervention ensemble of clinical machine learning systems
See this image and copyright information in PMC

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