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

NCT06263855 · Status: WITHDRAWN · Phase: NA · Type: INTERVENTIONAL

Last updated 2026-01-30

No results posted yet for this study

Summary

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.

Conditions

  • Large Language Model

Interventions

OTHER

CURE

A large language model (LLM) to help clinicians prepare discharge summaries for hospitalized patients.

Sponsors & Collaborators

Principal Investigators

  • Xiaoxi Yao · Mayo Clinic

Study Design

Allocation
RANDOMIZED
Purpose
HEALTH_SERVICES_RESEARCH
Masking
NONE
Model
PARALLEL

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2026-01-01
Primary Completion
2026-07-01
Completion
2026-10-01

Countries

  • United States

Study Locations

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Entities

Companies

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06263855 on ClinicalTrials.gov