Toward an operational definition of Artificial Intelligence for health care informatics: a Delphi survey

The proliferation of Artificial Intelligence (AI) technologies, fueled by advancements in computational power and generative models, is rapidly reshaping healthcare delivery and research. However, the absence of a standardized definition of AI impedes regulatory development, confounds public discourse, and hinders clinical adoption. This study provides clarity for AI developers and users in terminology surrounding the topic, which will ultimately assist in mitigating risks to patients and the public. Utilizing a multiphase Delphi method involving international informatics experts, we synthesized existing definitions and facilitated consensus on an operational definition of AI tailored to healthcare contexts. Our findings aim to establish a foundational framework to guide ethical governance, promote funding alignment, and optimize AI integration in clinical settings.

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Publication Details

Journal
Health Affairs Scholar
Published
2025-12-20
DOI
https://doi.org/10.1093/haschl/qxaf243
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

Toward an operational definition of Artificial Intelligence for health care informatics: a Delphi survey

Carolyn Sun, Shannon L. Harris, Shakib Hossain
Health Affairs Scholar
Artificial Intelligence in Healthcare and Education
article

Toward an operational definition of Artificial Intelligence for health care informatics: a Delphi survey

Carolyn Sun, Shannon L. Harris, Shakib Hossain
article en

Abstract

The proliferation of Artificial Intelligence (AI) technologies, fueled by advancements in computational power and generative models, is rapidly reshaping healthcare delivery and research. However, the absence of a standardized definition of AI impedes regulatory development, confounds public discourse, and hinders clinical adoption. This study provides clarity for AI developers and users in terminology surrounding the topic, which will ultimately assist in mitigating risks to patients and the public. Utilizing a multiphase Delphi method involving international informatics experts, we synthesized existing definitions and facilitated consensus on an operational definition of AI tailored to healthcare contexts. Our findings aim to establish a foundational framework to guide ethical governance, promote funding alignment, and optimize AI integration in clinical settings.

Health Affairs ScholarVol. 4(1)
Virginia Commonwealth University (US), Columbia University Irving Medical Center (US), Hunter College (US)
Partnerships for the goals
Openalex Percentile: Top 40%
Artificial Intelligence in Healthcare and Education
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