Real-Time Artificial Intelligence Diagnostic Copilot in Simulated Primary Care Consultations: Randomized Simulation Study.

JMIR Form ResSep 22, 2026 (epub)
Clinical ResearchFamily Medicine

Ivan Cusacovich, Manuel Pinilla, Ruben Garcia Castro

✦ AI-curated · Sources linked

In 30 seconds

This randomized simulation study evaluated the impact of a real-time, voice-based AI diagnostic assistant on physician diagnostic accuracy in primary care consultations. Involving 13 board-certified physicians managing 260 simulated cases, the AI-assisted condition achieved a Top-3 diagnostic accuracy of 74.6% compared to 62.3% in the unassisted condition, with an adjusted odds ratio of 2.68 (P = .01).

Key findings

  • AI-assisted diagnostic accuracy was 74.6% compared to 62.3% in the unassisted condition.
  • The adjusted odds ratio for improved accuracy with AI assistance was 2.68 (P = .01).
  • Mean consultation time increased by 10.7% with AI assistance.
  • Physicians rated the AI system highly for usefulness and satisfaction.

Why it matters

The study highlights the potential of AI diagnostic assistants to enhance diagnostic accuracy in primary care, addressing a significant source of diagnostic errors. Understanding their effectiveness and risks is crucial for future clinical implementation.

Source

Published in JMIR Form Res. This summary was written by xxcode from the publication's abstract and metadata. It is not peer reviewed and is not a substitute for the original article. For clinical decisions, review the original publication.

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AI-generated summaries may contain errors or omissions. Verify clinically important information with the original publication.

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