ArticleMayo Clinic proceedings. Digital health2026
Large Language Model-Generated Electronic Consultations: A Blinded Comparative Study of OpenEvidence and Gastroenterologist Electronic Consultations.
Article in Mayo Clinic proceedings. Digital health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
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Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: To evaluate whether a context-specific large language model, OpenEvidence, can generate gastroenterology/hepatology eConsult responses for metabolic dysfunction-associated steatotic liver disease (MASLD), while characterizing the frequency and potential severity of errors. Patients and Methods: In this retrospective cohort study at a tertiary academic medical center, 125 specialist electronic consultations (eConsults) for MASLD (from January 2020 to December 2024) were paired with OpenEvidence-generated eConsults produced using OpenEvidence and standardized prompts. Five blinded physician reviewers evaluated all eConsults using a previously validated instrument. A board-certified gastroenterologist independently reviewed OpenEvidence-generated eConsults to identify errors and assess potential for harm. Results: OpenEvidence-generated eConsults received higher overall eConsult Specialist Quality of Response scores than specialist eConsults (mean difference, 6.4; 95% CI, 6.0-6.9; Conclusion: In this blind comparison of paired eConsults for MASLD, OpenEvidence-generated responses were rated higher in perceived quality and informational adequacy than specialist-authored responses, but occasionally clinically relevant errors occurred. These findings support further evaluation of OpenEvidence-assisted eConsult workflows for protocol-driven conditions.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.