Effect of Large Language Model in Assisting Discharge Summary Notes Writing for Hospitalized Patients

Withdrawn before enrolling · Not applicable

Conditions studied: Large Language Model

In brief

This pilot study aims to assess the feasibility of carrying out a full-scale pragmatic, cluster-randomized controlled trial which will investigate whether discharge summary writing assisted by a large language model (LLM), called CURE (Checker for Unvalidated Response Errors), improves care delivery without adversely impacting patient outcomes.

Key facts

Study ID

NCT06263855

Run by

Mayo Clinic

People needed

0

Starts

2026-01-01

Expected to finish

2026-10-01

Last updated by the study team

2026-01-30

Who can join

Age: 18 and older. Sex: any. Healthy volunteers: not accepted.

You may qualify if…

• Adult patients admitted to one of three participating cardiology services at Mayo Clinic in Rochester, MN

You may not qualify if…

• Minor patients (<18)
• Patients admitted to a hospital service where CURE is not implemented
• CLINICIANS
• Inclusion Criteria:
• Clinicians who provide care to randomized patients included in this pilot
• Exclusion Criteria:
• Clinicians who do not provide care to randomized patients included in this pilot

Where it is running

• Mayo Clinic — Rochester, Minnesota, United States

Full record on ClinicalTrials.gov

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