Enhancing Interdisciplinary Understanding of Ophthalmology Notes Through a Local Large Language Model

John J Chen

Status: Completed

Conditions: Interdisciplinary Communication; Communication; Artificial Intelligence Technology; Artificial Intelligence (AI)

Treatments: Other: Large Language Model-generated Plain Language Summary of Ophthalmology notes

Study type: Interventional

Funder types: Other

Identifiers

NCT06624605

24-000550

Details and patient eligibility

About

This prospective, randomized controlled trial evaluated the efficacy of adding Large Language model (LLM)-generated Plain Language Summaries (PLSs) to Standard Ophthalmology Notes (SONs) in enhancing comprehension among non-ophthalmology providers. The study utilized surveys to assess non-ophthalmology providers' comprehension and satisfaction with the notes and ophthalmologists' evaluation of PLS accuracy, safety, and time burden. An objective semantic and linguistic analysis of the PLSs was also conducted.

Enrollment: 851 patients

Sex: All

Ages: 18+ years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• Evaluation by an Ophthalmologist in the Mayo Clinic Department of Ophthalmology in Rochester, MN in either the inpatient or outpatient setting between Feb 1, 2024 - May 31, 2024.

Exclusion criteria

• No in-network non-Ophthalmologist care providers in the medical record
• Procedure-only visits containing only a procedure note

Trial design

Primary purpose: Health Services Research

Allocation: Randomized

Interventional model: Parallel Assignment

Masking: None (Open label)

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851 participants in 2 patient groups

Control

No Intervention group

Description:

Participants receive standard ophthalmology notes without any additions.

Intervention

Experimental group

Description:

Participants receive standard ophthalmology notes with an appended LLM-generated plain language summary, reviewed and edited by the ophthalmologist. The plain language summary is clearly marked as generated as part of a Quality Improvement initiative.

Treatment:

Other: Large Language Model-generated Plain Language Summary of Ophthalmology notes