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Large language model-based scribing tools for ophthalmology: performance and safety evaluation using simulated

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Summary

Heidi AI led in performance among six LLM scribing tools for ophthalmology notes, but all tools had errors, necessitating human oversight for patient safety.

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Area of Science:

  • Ophthalmology
  • Medical Informatics
  • Artificial Intelligence

Background:

  • Six large language model (LLM)-based scribing tools were evaluated for their ability to generate ophthalmological clinical notes.
  • The study focused on performance and safety in simulated physician-patient encounters.

Purpose of the Study:

  • To compare the performance and safety of six LLM-based scribing tools in generating ophthalmological clinical notes.
  • To identify the best-performing tool and assess the types and frequency of errors made by these AI scribes.

Main Methods:

  • A cross-sectional comparative study used seven ophthalmic encounters transcribed by six scribing tools.
  • Note quality was assessed by consultant ophthalmologists using the Physician Documentation Quality Instrument (PDQI-9) and text-generation metrics (ROUGE-L, BERTScore, BARTScore, AlignScore).
  • Safety analysis identified documentation errors, including omissions, incorrect information, and extraneous content.

Main Results:

  • Heidi AI achieved the highest overall documentation quality (PDQI-9: 38.524) and led in accuracy, usefulness, organization, comprehensiveness, and succinctness.
  • Heidi AI also led in ROUGE-L (0.326), BERTScore (0.727), and AlignScore (0.704).
  • All tools exhibited errors, primarily omissions of critical clinical details, but also incorrect or extraneous information.

Conclusions:

  • Heidi AI demonstrated the highest performance among the evaluated LLM scribing tools for ophthalmology documentation.
  • Despite promising performance, all tools exhibited errors, particularly omissions of critical details, posing potential risks to patient care.
  • Human oversight and rigorous verification are essential before clinical integration of these AI scribing tools.