Tackling the Documentation Burden
AI can synthesize outside records, draft visit notes, and translate retina jargon, but the physician remains responsible for every word.
Bradley S. Gundlach, MD; Haley S. Garrison, MD, MS; and Prashant D. Tailor, MD
Retina Today 
KEY TAKEAWAYS AI can assist with documentation before, during, and after a retina visit, but efficiency gains vary by product, clinician, and workflow. Protected health information should be processed only through approved systems with appropriate contracts, security review, patient disclosure, and clinician oversight. Clinicians should use AI to organize and draft and require verification of high-consequence details. Retina practice is a documentation stress test. A single encounter may require synthesis of outside anti-VEGF history, prior surgery, systemic medications, examination findings, multimodal imaging, and injection details followed by initiating a plan that patients and referring clinicians can understand. In one academic study, ophthalmologists spent a mean of 10.8 minutes in the electronic health record (EHR) per encounter, totaling 3.7 hours during a full clinic day.1 Large language models (LLMs), which can organize information quickly, may be able to reduce some of this burden; however, they can also omit crucial facts, reverse laterality, and add unsupported details. BEFORE THE VISIT New retina consultations often arrive with fragmented or lengthy notes, imaging reports, operative records, and injection histories. AI can extract a timeline and populate a problem-oriented draft, so the physician has a structured summary. For example, Mayo Clinic’s RecordTime, a tool that organizes and summarizes outside records, anecdotally saved one physician 5 to 30 minutes of preparation per patient,2 although peer-reviewed performance data have not yet been published. In our study, a locally hosted LLM generated pre-charting drafts for 48 external retina, uveitis, and ocular oncology referrals.3 AI drafts were rated more complete and organized, whereas physician drafts were clearer and more clinically relevant; overall preference did not significantly favor either source. Physicians spent a median of 5.12 minutes manually summarizing and pre-charting each referral, although the study did not directly compare this time with physician review and editing of AI drafts.
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