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A Novel Workflow for Artificial Intelligence-Enhanced Patient Messaging Services
Matthew R Allen1,2, Vijay M Tiyyala3, Karthik Ramesh1,4
1School of Medicine, University of California San Diego, La Jolla, California, United States.
Background:
Current artificial intelligence (AI) integration in patient messaging often relies on generating AI drafts for clinician review, yet this workflow has achieved limited effect.
Objective:
This study aimed to describe and evaluate a novel, clinician-first workflow for patient messaging where AI enhances a clinician-generated draft.
Methods:
Using 268 patient questions from public data, we compared physician-only responses, AI-only responses, and AI-enhanced responses.
Results:
Responses were ranked on overall preference and the CREATE TRUST framework. AI-enhanced responses were significantly preferred overall, ranking first in 38.8% of evaluations (average rank 1.69; p < 0.01), outperforming both AI-only (27.6%; 2.29) and physician-only (25.5%; 2.11) responses. AI-enhanced responses ranked highest for Understandable (44.5%) and Tailored (39.4%). AI-only responses ranked highest for Thorough (71.0%) and Empathic (69.8%), while physician-only responses ranked highest in Authentic (90.9%; all p < 0.01). Safety analysis identified consequential additions in 3.36% and omissions in 1.12% of AI-enhanced messages.
Conclusion:
A novel workflow-based on the Clinical Action Support framework-where AI enhances a clinician's draft may offer an improved approach to AI implementation in patient messaging services.
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