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AI Tool to Reduce Clinician Documentation Burden
Sponsor: University of North Carolina, Chapel Hill
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.
Official title: Evidently Workflow Study: Randomized Evaluation of a Clinician-Facing AI Documentation Support Tool in Outpatient Specialty Practice
Key Details
Gender
All
Age Range
Any - Any
Study Type
INTERVENTIONAL
Enrollment
150
Start Date
2026-03-30
Completion Date
2026-06
Last Updated
2026-03-27
Healthy Volunteers
Yes
Conditions
Interventions
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.
Locations (1)
UNC Health
Chapel Hill, North Carolina, United States