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Can Feedback From a Large Language Model Improve Health Care Quality?

NCT06823765 · Status: COMPLETED · Phase: NA · Type: INTERVENTIONAL · Enrollment: 491

Last updated 2026-02-03

No results posted yet for this study

Summary

The goal of this study is to learn if computer-assisted advice can help improve patient care in Nigerian health clinics. The main question it aims to answer is: does giving healthcare workers instant computer feedback help them make better decisions about patient care?

Researchers will compare patient care notes written by healthcare workers before and after they receive computer feedback to see if the feedback improves care quality. A doctor who doesn't know if feedback was given will review these notes.

Participants will:

* Be seen by a community healthcare worker who uses the computer feedback system
* Be treated by a fully trained medical doctor
* Get tested for malaria, anemia, or urinary tract infections if they have certain symptoms

Conditions

  • All Conditions

Interventions

OTHER

Large Language Model Clinical Decision Support

A Large Language Model (LLM) integrated into the clinic's Electronic Medical Record system provides real-time feedback on patient assessments. Community Health Extension Workers first create a standard SOAP note, submit it to the LLM, and receive detailed feedback and key recommendations. They can then update their assessment based on this feedback. All final treatment decisions are made by Medical Officers who independently evaluate patients.

Sponsors & Collaborators

  • EHA Clinics Nigeria

    collaborator UNKNOWN

  • World Bank

    collaborator OTHER

  • University of Pennsylvania

    collaborator OTHER

  • George Washington University

    collaborator OTHER

  • Yale University

    lead OTHER

Principal Investigators

  • Jason Abaluck · Yale University

Study Design

Allocation
NA
Purpose
HEALTH_SERVICES_RESEARCH
Masking
NONE
Model
SINGLE_GROUP

Eligibility

Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2025-01-30
Primary Completion
2025-10-17
Completion
2025-10-17

Countries

  • Nigeria

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 NCT06823765 on ClinicalTrials.gov