AI Scribes Lag Clinicians on Note Quality - Summary - MDSpire

AI Scribes Lag Clinicians on Note Quality

A VHA study across 11 vendors finds AI-generated primary care notes score lower than clinician-written notes, with the largest deficits in thoroughness, organization, and usefulness

  • By

  • Kerri Miller

  • April 17, 2026

  • 6 min

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Objective:

To evaluate the quality of notes generated by AI scribe tools compared to those written by clinicians specifically in primary care scenarios.

Approach:
    Key Findings:
    • Human-generated notes scored higher than AI-generated notes across all five cases, with statistically significant differences noted in three scenarios.
    • The largest gap emerged in the acute low back pain scenario, where human notes averaged 43.8 points compared with 20.3 points for AI-generated notes.
    • AI-generated notes scored lower in all 10 quality domains, with the largest deficits in thoroughness, organization, and usefulness.
    Interpretation:

    The study indicates that while AI scribes may improve efficiency, they currently produce documentation of lower quality compared to human clinicians, which has significant implications for patient care.

    Limitations:
    • Simulated cases may not reflect real-world clinical complexity.
    • Human notes were not produced in typical clinical workflows.
    • Rater blinding may have been imperfect, and the PDQI-9 may not fully capture AI-specific errors.
    • Vendors were not permitted to generate multiple iterations of notes, which could influence AI performance.
    Conclusion:

    AI scribes should be used to generate draft documentation that requires thorough clinician review and editing, rather than replacing clinician-authored notes.

    Sources:

Original Source(s)

AI Scribes Lag Clinicians on Note Quality

  • by Kerri Miller

  • April 17, 2026

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