Generative AI-Assisted Clinical Decision Support for Medical Intensive Care Unit Physicians
2026년 7월 19일 업데이트: Seoul National University Hospital
Evaluation of the Feasibility and Effectiveness of Generative AI-Assisted Multidisciplinary Decision Support in Medical Intensive Care: A Pilot Randomized Controlled Trial
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.
연구 개요
상태
완전한
상세 설명
This was a single-center, open-label, pilot cluster-randomized crossover study involving physicians working in a medical intensive care unit. Each participating physician was observed during a scheduled one-month rotation in the medical intensive care unit. At the beginning of each monthly rotation, participating physicians were divided into two clusters. The clusters were randomized to begin with either the ChatGPT-assisted condition or the control condition. After approximately two weeks, each cluster crossed over to the alternate condition for the remainder of the one-month rotation. This design allowed participating physicians to experience both study conditions within the same rotation.
During the AI-assisted condition, physicians were encouraged to use ChatGPT (OpenAI) as a reference tool to support clinical information review and decision-making. Only non-identifiable clinical information was permitted to be entered into ChatGPT. Patient names, medical record numbers, contact information, and other information that could directly identify an individual patient were not entered. Physicians summarized clinically relevant information in their own words and considered the responses generated by ChatGPT when planning patient management. The Situation-Background-Assessment-Recommendation framework was recommended as an optional structure for organizing clinical information, but its use was not mandatory. Physicians were otherwise free to formulate their queries and interact with ChatGPT according to their clinical needs. A suggested prompt encouraged ChatGPT to present multiple management options, together with their rationale, potential benefits and risks, relevant supporting evidence, and areas of uncertainty. ChatGPT did not make or implement clinical decisions.
During the control condition, physicians used usual information resources, including discussions with other clinicians, multidisciplinary rounds, consultations, textbooks, clinical practice guidelines, PubMed, and other established clinical reference services, without using ChatGPT or other generative AI tools for study-related clinical decision support.
All diagnostic and treatment decisions were made independently by the treating physicians. Repeated questionnaires assessed satisfaction, decision-making experience, confidence, perceived efficiency, workload, educational value, and other aspects of clinical decision support. At study completion, participants also evaluated usability, satisfaction, perceived learning, reliance on ChatGPT, intention for future use, and the extent to which ChatGPT-generated suggestions were reflected in their clinical plans.
연구 유형
중재적
등록 (실제)
15
단계
- 해당 없음
연락처 및 위치
이 섹션에서는 연구를 수행하는 사람들의 연락처 정보와 이 연구가 수행되는 장소에 대한 정보를 제공합니다.
연구 장소
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Seoul
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Seoul, Seoul, 대한민국, 03080
- Seoul National University Hospital
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참여기준
연구원은 적격성 기준이라는 특정 설명에 맞는 사람을 찾습니다. 이러한 기준의 몇 가지 예는 개인의 일반적인 건강 상태 또는 이전 치료입니다.
자격 기준
공부할 수 있는 나이
- 성인
- 고령자
건강한 자원 봉사자를 받아들입니다
예
설명
Inclusion Criteria:
- Age 19 years or older.
- Physicians, including residents, fellows, and attending physicians, working in the medical intensive care unit at Seoul National University Hospital.
- Scheduled to work as a primary treating physician for at least 5 days during a planned observation period.
- Able and willing to provide written informed consent.
Exclusion Criteria:
- Did not provide written informed consent.
- Withdrew consent from study participation.
공부 계획
이 섹션에서는 연구 설계 방법과 연구가 측정하는 내용을 포함하여 연구 계획에 대한 세부 정보를 제공합니다.
연구는 어떻게 설계됩니까?
디자인 세부사항
- 주 목적: 건강 서비스 연구
- 할당: 무작위
- 중재 모델: 크로스오버 할당
- 마스킹: 없음(오픈 라벨)
무기와 개입
참가자 그룹 / 팔 |
개입 / 치료 |
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실험적: ChatGPT-Assisted Condition First, Then Control Condition
Physician clusters used ChatGPT-assisted clinical decision support during the first approximately two weeks of their one-month medical intensive care unit rotation.
They then crossed over to the control condition and used usual clinical information resources without generative AI for the remainder of the rotation.
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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.
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.
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실험적: Control Condition First, Then ChatGPT-Assisted Condition
Physician clusters used usual clinical information resources without generative AI during the first approximately two weeks of their one-month medical intensive care unit rotation.
They then crossed over to the ChatGPT-assisted clinical decision-support condition for the remainder of the rotation.
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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.
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.
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연구는 무엇을 측정합니까?
주요 결과 측정
결과 측정 |
측정값 설명 |
기간 |
|---|---|---|
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Daily Physician Satisfaction Score
기간: At the end of each working day during the one-month medical intensive care unit rotation
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The score of 10 questionnaire items assessing physicians' satisfaction with their daily clinical work, modified from Shore and Franks (1986) and Suchman et al. (1993).
Each item was rated on a 5-point Likert scale from -2 (strongly disagree) to +2 (strongly agree).
Negatively worded items were reverse-scored.
The mean score ranges from -2 to +2, with higher scores indicating greater satisfaction.
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At the end of each working day during the one-month medical intensive care unit rotation
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Daily Clinical Decision-Making Score
기간: At the end of each working day during the one-month medical intensive care unit rotation
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The score of 6 questionnaire items assessing satisfaction with the clinical decision-making process, perceived decision difficulty, clarity of the preferred treatment, availability of relevant information, and identification of factors affecting the decision.
Items were modified from Gedney (1994) and Dolan (1999) and rated on a 5-point Likert scale from -2 (strongly disagree) to +2 (strongly agree).
Negatively worded items were reverse-scored.
The mean score ranges from -2 to +2, with higher scores indicating a more favorable decision-making experience.
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At the end of each working day during the one-month medical intensive care unit rotation
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Perceived Quality Score for ChatGPT
기간: At the end of the one-month medical intensive care unit rotation, after completion of both crossover periods
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The score of 8 questionnaire items assessing the perceived information quality, system quality, and service quality of ChatGPT, modified from Pillong et al. (2025).
Each item was rated on a 5-point Likert scale from -2 (strongly disagree) to +2 (strongly agree).
The negatively worded response-time item was reverse-scored.
The mean score ranges from -2 to +2, with higher scores indicating better perceived quality.
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At the end of the one-month medical intensive care unit rotation, after completion of both crossover periods
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Generative AI Usability Score
기간: At the end of the one-month medical intensive care unit rotation, after completion of both crossover periods
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The score of 3 questionnaire items assessing ease of use, ease of learning, and clarity of interaction with Generative AI (ChatGPT), modified from Pillong et al. (2025).
Each item was rated on a 5-point Likert scale from -2 (strongly disagree) to +2 (strongly agree).
The mean score ranges from -2 to +2, with higher scores indicating greater usability.
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At the end of the one-month medical intensive care unit rotation, after completion of both crossover periods
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Satisfaction Score for Generative AI Use
기간: At the end of the one-month medical intensive care unit rotation, after completion of both crossover periods
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The score of 6 questionnaire items assessing the perceived usefulness, productivity, effectiveness, overall satisfaction, appropriateness, and intention to reuse Generative AI (ChatGPT), modified from Pillong et al. (2025).
Each item was rated on a 5-point Likert scale from -2 (strongly disagree) to +2 (strongly agree).
The mean score ranges from -2 to +2, with higher scores indicating greater satisfaction.
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At the end of the one-month medical intensive care unit rotation, after completion of both crossover periods
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기타 결과 측정
결과 측정 |
측정값 설명 |
기간 |
|---|---|---|
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Confidence
기간: At the end of the one-month medical intensive care unit rotation, after completion of both crossover periods
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A single questionnaire item assessing whether use of Generative AI (ChatGPT) increased the physician's confidence in clinical decision-making.
The item was rated on a 5-point Likert scale from -2 (strongly disagree) to +2 (strongly agree), with higher scores indicating a greater perceived increase in confidence.
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At the end of the one-month medical intensive care unit rotation, after completion of both crossover periods
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Perceived Acquisition of New Knowledge or Clinical Insight
기간: At the end of the one-month medical intensive care unit rotation, after completion of both crossover periods
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A single questionnaire item assessing whether the physician acquired new knowledge or clinical insight while using Generative AI (ChatGPT).
The item was rated on a 5-point Likert scale from -2 to +2, with higher scores indicating greater perceived learning.
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At the end of the one-month medical intensive care unit rotation, after completion of both crossover periods
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Application of Generative AI-Derived Knowledge to Other Clinical Situations
기간: At the end of the one-month medical intensive care unit rotation, after completion of both crossover periods
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A single questionnaire item assessing whether knowledge obtained through Generative AI (ChatGPT) was applied to the care of other patients.
The item was rated on a 5-point Likert scale from -2 to +2, with higher scores indicating greater transfer of learning.
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At the end of the one-month medical intensive care unit rotation, after completion of both crossover periods
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Intention to Continue Using Generative AI (ChatGPT) in Future Clinical Practice
기간: At the end of the one-month medical intensive care unit rotation, after completion of both crossover periods
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A single questionnaire item assessing the physician's intention to continue using Generative AI (ChatGPT) in future clinical practice.
The item was rated on a 5-point Likert scale from -2 to +2, with higher scores indicating stronger intention for continued use.
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At the end of the one-month medical intensive care unit rotation, after completion of both crossover periods
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Perceived Reliance on Generative AI (ChatGPT)
기간: At the end of the one-month medical intensive care unit rotation, after completion of both crossover periods
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A single questionnaire item assessing whether the physician perceived increased reliance on Generative AI (ChatGPT) during clinical care.
The item was rated on a 5-point Likert scale from -2 to +2, with higher scores indicating greater perceived reliance.
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At the end of the one-month medical intensive care unit rotation, after completion of both crossover periods
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Perceived Reduction in Clinical Workload
기간: At the end of the one-month medical intensive care unit rotation, after completion of both crossover periods
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A single questionnaire item assessing whether use of Generative AI (ChatGPT) reduced the physician's perceived clinical workload.
The item was rated on a 5-point Likert scale from -2 to +2, with higher scores indicating greater perceived workload reduction.
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At the end of the one-month medical intensive care unit rotation, after completion of both crossover periods
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Clinical Specialty Area in Which Generative AI (ChatGPT) Was Most Helpful
기간: At the end of the one-month medical intensive care unit rotation, after completion of both crossover periods
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The clinical specialty area in which the physician perceived the greatest practical benefit from Generative AI (ChatGPT), selected from predefined categories or reported as free text, including cardiology, infectious diseases, pulmonology, and nephrology.
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At the end of the one-month medical intensive care unit rotation, after completion of both crossover periods
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Percentage of Generative AI (ChatGPT) Suggestions Reflected in Clinical Plans
기간: At the end of the one-month medical intensive care unit rotation, after completion of both crossover periods
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The physician-reported percentage of Generative AI (ChatGPT)-generated suggestions that were reflected in actual clinical management plans.
Scores range from 0% to 100%, with higher percentages indicating greater incorporation of ChatGPT suggestions.
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At the end of the one-month medical intensive care unit rotation, after completion of both crossover periods
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공동 작업자 및 조사자
여기에서 이 연구와 관련된 사람과 조직을 찾을 수 있습니다.
수사관
- 수석 연구원: Minju Han, M.D., Seoul National University Hospital
연구 기록 날짜
이 날짜는 ClinicalTrials.gov에 대한 연구 기록 및 요약 결과 제출의 진행 상황을 추적합니다. 연구 기록 및 보고된 결과는 공개 웹사이트에 게시되기 전에 특정 품질 관리 기준을 충족하는지 확인하기 위해 국립 의학 도서관(NLM)에서 검토합니다.
연구 주요 날짜
연구 시작 (실제)
2025년 12월 1일
기본 완료 (실제)
2026년 5월 31일
연구 완료 (실제)
2026년 5월 31일
연구 등록 날짜
최초 제출
2026년 7월 12일
QC 기준을 충족하는 최초 제출
2026년 7월 12일
처음 게시됨 (실제)
2026년 7월 16일
연구 기록 업데이트
마지막 업데이트 게시됨 (실제)
2026년 7월 21일
QC 기준을 충족하는 마지막 업데이트 제출
2026년 7월 19일
마지막으로 확인됨
2026년 7월 1일
추가 정보
이 연구와 관련된 용어
키워드
기타 연구 ID 번호
- 2510-145-1689
개별 참가자 데이터(IPD) 계획
개별 참가자 데이터(IPD)를 공유할 계획입니까?
아니요
IPD 계획 설명
Individual participant data will not be shared because of the small sample size, the limited number of physicians working in the study setting, and the potential risk of re-identification even after removal of direct identifiers.
External sharing of individual-level data was not included in the participant consent or institutional review board-approved data management plan.
약물 및 장치 정보, 연구 문서
미국 FDA 규제 의약품 연구
아니
미국 FDA 규제 기기 제품 연구
아니
이 정보는 변경 없이 clinicaltrials.gov 웹사이트에서 직접 가져온 것입니다. 귀하의 연구 세부 정보를 변경, 제거 또는 업데이트하도록 요청하는 경우 register@clinicaltrials.gov. 문의하십시오. 변경 사항이 clinicaltrials.gov에 구현되는 즉시 저희 웹사이트에도 자동으로 업데이트됩니다. .