The goal of this study is to learn whether an artificial intelligence (AI) tool built into the electronic health record helps hospital physicians write discharge summaries. A discharge summary is the document that tells a patient's family doctor and other providers what happened during a hospital stay.
The main questions this study aims to answer are:
Does access to the AI tool reduce the time physicians spend writing discharge summaries? Does it change the quality of discharge summaries or how soon they are completed? How does it affect physician workload?
Physicians will be randomly assigned to either have access to the AI tool or complete discharge summaries as they usually do. Physicians with access can choose whether to use the tool, and they review and edit any AI-generated text before it becomes part of the discharge summary.
Healthcare provider at participating hospital on a hospitalist ward (teaching or non-teaching ward)
English speaking
Planned leave during study period
Parallel
Epic Discharge Summary Hospital Course Generator
Other interventionA generative AI (large language model) tool embedded in Epic that drafts a narrative of the patient's hospital course from existing chart data, including clinician notes, investigations, and medications and treatments. A draft is generated only when a clinician requests it, can be generated at any time during the hospitalization, and can be regenerated an unlimited number of times. Clinicians can choose a narrative (chronological) format, a problem-based format with a numbered entry for each clinical problem managed during the hospitalization, or an organ system-based format. The draft appears in a separate tab and is not automatically inserted into the discharge summary; clinicians may copy, edit, or disregard it.
Time-in-note (minutes per discharge summary)
Total active time (minutes) spent writing and editing the discharge summary by all clinicians contributing to the note (staff physician and, on teaching services, resident physicians), measured per discharge episode using Epic audit log "time in note" metadata. Includes teaching and non-teaching services.
Time from discharge to discharge summary signature (hours)
Time in hours between the patient's recorded hospital discharge and the final signature of the discharge summary, from Epic metadata. Summaries signed before discharge are recorded as negative values.
Expert-rated documentation quality
Blinded manual review of a random sample of 200 discharge summaries (100 per arm), each rated independently by a hospitalist and a primary care physician using the validated and standardized Provider Documentation Summarization Quality Instrument (PDSQI-9). Eight attributes (accurate, cited, comprehensible, organized, succinct, synthesized, thorough, useful) are each rated on a 5-point Likert scale (1 to 5) and summed to a total score ranging from 8 to 40; higher scores indicate better quality. The ninth attribute (free of stigmatizing language) is rated yes/no and reported separately. Reviewers will also verify accuracy against the medical record by chart review in Epic, recording omissions and factual errors in: administrative details (admission and discharge dates), diagnoses, medications and treatments, investigations, and subspecialty consultations.
Automated documentation quality (PDSQI-9, LLM-as-judge)
PDSQI-9 total score for all discharge summaries, assigned by a large language model using the published PDSQI-9 LLM-as-judge approach (Croxford et al., JAMIA 2025). Total score range 9 to 45; higher scores indicate better quality.
Physician task load (PTL-4)
Four NASA-TLX subscales (mental demand, physical demand, temporal demand, effort), each rated 0 to 100 while reflecting on a representative clinical workday in the past 1 to 2 weeks. Subscales are summed into a composite score of 0 to 400; higher scores indicate greater workload. Measured once per clinician.
Total attending time in the patient chart on the day of discharge (minutes)
Total minutes the staff physician spends with the patient's chart open on the calendar day of discharge (00:00 to 23:59), measured from Epic audit log metadata.
Discharge time of day
Clock time of the patient's recorded hospital discharge, from Epic metadata, analyzed as a continuous measure and as the proportion of patients discharged before 11:00.
Staff physician attestation lag (hours)
Time in hours between the resident's signature and the staff physician's attestation of the discharge summary. Teaching services only.
Physician wellbeing (Professional Fulfillment Index)
Stanford Professional Fulfillment Index subscale scores (professional fulfillment, work exhaustion, interpersonal disengagement), each scaled 0 to 100. Measured per clinician.
Click on the lead sponsor to view all of their trials.
Unity Health Toronto
Lead sponsor
University of California, San Diego
Collaborator
This trial is not recruiting at the moment. You can still explore other options:
