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. 2023 Jun 20;30(7):1237-1245.
doi: 10.1093/jamia/ocad072.

Using AI-generated suggestions from ChatGPT to optimize clinical decision support

Siru Liu  1 , Aileen P Wright  1   2 , Barron L Patterson  3 , Jonathan P Wanderer  1   4 , Robert W Turer  5   6 , Scott D Nelson  1 , Allison B McCoy  1 , Dean F Sittig  7 , Adam Wright  1
Affiliations

Using AI-generated suggestions from ChatGPT to optimize clinical decision support

Siru Liu et al. J Am Med Inform Assoc. .

Abstract

Objective: To determine if ChatGPT can generate useful suggestions for improving clinical decision support (CDS) logic and to assess noninferiority compared to human-generated suggestions.

Methods: We supplied summaries of CDS logic to ChatGPT, an artificial intelligence (AI) tool for question answering that uses a large language model, and asked it to generate suggestions. We asked human clinician reviewers to review the AI-generated suggestions as well as human-generated suggestions for improving the same CDS alerts, and rate the suggestions for their usefulness, acceptance, relevance, understanding, workflow, bias, inversion, and redundancy.

Results: Five clinicians analyzed 36 AI-generated suggestions and 29 human-generated suggestions for 7 alerts. Of the 20 suggestions that scored highest in the survey, 9 were generated by ChatGPT. The suggestions generated by AI were found to offer unique perspectives and were evaluated as highly understandable and relevant, with moderate usefulness, low acceptance, bias, inversion, redundancy.

Conclusion: AI-generated suggestions could be an important complementary part of optimizing CDS alerts, can identify potential improvements to alert logic and support their implementation, and may even be able to assist experts in formulating their own suggestions for CDS improvement. ChatGPT shows great potential for using large language models and reinforcement learning from human feedback to improve CDS alert logic and potentially other medical areas involving complex, clinical logic, a key step in the development of an advanced learning health system.

Keywords: artificial intelligence; clinical decision support; large language model.

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Conflict of interest statement

The authors do not have conflicts of interest related to this study.

Figures

Figure 1.
Figure 1.
An example of using ChatGPT to generate suggestions to improve an alert.
Figure 2.
Figure 2.
Stacked bar charts of the scores of each item (understanding, relevance, usefulness, acceptance, workflow, bias, inversion, redundancy) for AI-generated suggestions (A) and human-generated suggestions (B).
Figure 3.
Figure 3.
A prototype of potential implementation in EHR system—AI decision support editors.
See this image and copyright information in PMC

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