Not_yet_recruitingNANCT07602725

Patient Experience and Trust When Viewing Original Medical Notes Versus Large Language Model (LLM)-Generated Plain Language Summaries

Sponsor: University of Texas at Austin

Trial Details

Condition	Musculoskeletal Disease, Orthopedic Patients
Intervention	LLM-Generated Medical Note; Control (Original Medical Note)
Phase	NA
Status	Not_yet_recruiting
Participants	135
Est. Completion	1 Dec 2026
Last Updated	22 May 2026

Primary Outcome

Trust and Experience with the Clinician Scale (TRECS-7)

Eligibility Criteria

Inclusion Criteria

Inclusion Criteria: * Adult (18-89) * Seeking outpatient musculoskeletal specialty care * English language literacy * Return patient to the clinic Exclusion criteria: \- Any impairment precluding completion of a survey on a tablet

View Registry Entry

Related Analysis

Novel Trial Examines Patient Trust When Reading AI-Generated Plain Language Medical Notes vs Original Clinical Documentation

University of Texas researchers are investigating whether AI-generated plain language summaries of medical notes improve patient trust and understanding compared to original clinical documentation. The 135-participant study focuses on musculoskeletal specialty care patients.

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