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A Novel Workflow for Artificial Intelligence-Enhanced Patient Messaging Services.

Matthew R Allen1,2, Vijay M Tiyyala3, Karthik Ramesh1,4

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A new clinician-first artificial intelligence (AI) workflow significantly improved patient message responses. This AI-enhanced approach, where AI assists clinician drafts, was preferred over AI-only or physician-only messages.

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Area of Science:

  • Medical Informatics
  • Artificial Intelligence in Healthcare

Background:

  • Current artificial intelligence (AI) integration in patient messaging typically involves AI generating drafts for clinician review, a workflow with limited demonstrated effectiveness.
  • The existing paradigm has not optimized AI's potential for enhancing clinical communication.

Purpose of the Study:

  • To describe and evaluate a novel clinician-first workflow for patient messaging.
  • To assess the efficacy of AI enhancing a clinician-generated draft compared to AI-only and physician-only responses.

Main Methods:

  • A comparative study using 268 patient questions sourced from public data.
  • Evaluation of physician-only, AI-only, and AI-enhanced responses using overall preference rankings and the CREATE TRUST framework.
  • Safety analysis of AI-enhanced messages for consequential additions and omissions.

Main Results:

  • AI-enhanced responses were significantly preferred overall (ranking first in 38.8% of evaluations, average rank 1.69; p < 0.01), outperforming AI-only (27.6%; 2.29) and physician-only (25.5%; 2.11) responses.
  • AI-enhanced responses excelled in Understandable (44.5%) and Tailored (39.4%) aspects.
  • AI-only responses led in Thoroughness (71.0%) and Empathy (69.8%), while physician-only responses were highest in Authenticity (90.9%).
  • Safety analysis revealed consequential additions in 3.36% and omissions in 1.12% of AI-enhanced messages.

Conclusions:

  • A novel workflow, grounded in the Clinical Action Support framework, where AI enhances clinician drafts, presents a promising approach for AI implementation in patient messaging.
  • This clinician-first strategy may overcome limitations of previous AI integration models.
  • Further research into safety and optimization of AI-assisted clinical communication is warranted.