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AI Tool to Reduce Clinician Documentation Burden

NCT07498582 · Status: ENROLLING_BY_INVITATION · Phase: NA · Type: INTERVENTIONAL · Enrollment: 150

Last updated 2026-03-27

No results posted yet for this study

Summary

This study looks at whether a clinician-facing artificial intelligence (AI) tool can help outpatient doctors spend less time reviewing medical records and documenting care. The tool creates brief summaries of existing medical record information to support routine clinical work. This study examines how use of this tool affects clinicians' workload, time spent in the electronic health record, and overall experience with documentation. The goal is to better understand whether AI documentation support tools can improve efficiency and reduce burden for clinicians in outpatient specialty practice.

Eligible UNC outpatient specialists may be invited to complete surveys and, if they qualify, are randomly assigned either to receive access to the tool (Evidently) at the beginning of the study period or to continue their usual workflow for eight weeks before receiving access. The study does not recruit patients and does not change medical care for patients.

Conditions

  • Burnout, Healthcare Workers
  • Clinical Workflow Optimization
  • Health Information Technology
  • Electronic Health Records

Interventions

BEHAVIORAL

AI Clinical Summarization Tool (Evidently)

Clinicians randomized to the intervention arm will receive access to the AI clinical summarization tool following randomization and completion of baseline study procedures. Clinicians randomized to the control arm will continue usual chart review and documentation practices for the duration of the study. Participation in the study and use of the AI clinical summarization tool are voluntary. Clinicians assigned to the intervention arm are not required to use the tool as part of routine care. Use of the AI clinical summarization tool will be characterized using system-generated utilization metrics provided by the vendor. These metrics may include measures such as the number of sessions (i.e., the number of times the tool is invoked), the number of patients for whom the tool is used, and, where available, the number of customized summaries generated. All utilization measures will be aggregated at the clinician level over the study period.

Sponsors & Collaborators

  • University of North Carolina, Chapel Hill

    lead OTHER

Principal Investigators

  • Spencer Dorn, MD, MPH, MHA · University of North Carolina, Chapel Hill

Study Design

Allocation
RANDOMIZED
Purpose
HEALTH_SERVICES_RESEARCH
Masking
NONE
Model
PARALLEL

Eligibility

Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2026-03-30
Primary Completion
2026-06-30
Completion
2026-06-30

Countries

  • United States

Study Locations

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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 NCT07498582 on ClinicalTrials.gov