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Generative AI-Assisted Clinical Decision Support for Medical Intensive Care Unit Physicians

NCT07708155 · Status: COMPLETED · Phase: NA · Type: INTERVENTIONAL · Enrollment: 15

Last updated 2026-07-21

No results posted yet for this study

Summary

This pilot study evaluated the feasibility and usefulness of generative artificial intelligence (AI) as a clinical decision-support tool for physicians working in a medical intensive care unit. Participating physicians were assigned by work period to either use a generative AI system in addition to usual clinical information resources or to use usual resources without generative AI. The assigned condition was then switched so that participants experienced both approaches. During the AI-assisted periods, physicians used de-identified clinical information and considered the AI-generated responses as reference information. All final clinical decisions remained the responsibility of the treating physicians. The study assessed acceptability, usability, satisfaction, perceived decision support, workload, confidence, and learning experience through repeated questionnaires.

Conditions

  • Clinical Decision Support
  • Clinical Decision-making

Interventions

OTHER

Generative AI-Assisted Clinical Decision Support

During the assigned period, physicians were encouraged to use ChatGPT (OpenAI) as a generative AI-based reference tool to support clinical information review and decision-making.

OTHER

Usual Clinical Information Resources

During the control period, physicians used usual clinical information resources, including discussions with other clinicians, multidisciplinary rounds, specialty consultations, textbooks, clinical practice guidelines, PubMed, and established clinical reference services. No generative AI tool was used for clinical decision support during this period.

Sponsors & Collaborators

  • Seoul National University Hospital

    lead OTHER

Principal Investigators

  • Minju Han, M.D. · Seoul National University Hospital

Study Design

Allocation
RANDOMIZED
Purpose
HEALTH_SERVICES_RESEARCH
Masking
NONE
Model
CROSSOVER

Eligibility

Min Age
19 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2025-12-01
Primary Completion
2026-05-31
Completion
2026-05-31

Countries

  • South Korea

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 NCT07708155 on ClinicalTrials.gov