Clinical Decision SupportNCT07708155
Generative AI-Assisted Clinical Decision Support for Medical Intensive Care Unit Physicians
A study testing Generative AI-Assisted Clinical Decision Support and Usual Clinical Information Resources in people with Clinical Decision Support and Clinical Decision-making, run by Seoul National University Hospital at 1 site in South Korea.
Trial 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. Read more about this study
- Who is it for?
- Ages 19 years and olderHealthy volunteers can take part
- Conditions the study is for
- Clinical Decision Support, Clinical Decision-making
- What is being tested?
- Generative AI-Assisted Clinical Decision Support and Usual Clinical Information Resources
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 15 participants
- Where
- 1 siteSouth Korea
- Study dates
- 1 Dec 2025to 31 May 2026
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 19 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Who may be able to join
- 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.
Who cannot join
- Did not provide written informed consent.
- Withdrew consent from study participation.
Trial locations and contacts
1 site in 1 country.
About this study
Official title: 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.
Read the detailed description
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.
- Being tested
- Generative AI-Assisted Clinical Decision Support, Usual Clinical Information Resources
- Keywords
- ChatGPT, Generative Artificial Intelligence, Large Language Model, Clinical Decision Support, Physician Decision-Making, Medical Intensive Care Unit, Critical Care, Usability, Cluster-Randomized Crossover Study, Acceptability
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Generative AI-Assisted Clinical Decision SupportOther
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.
Usual Clinical Information ResourcesOther
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.
| Study group | Role | What they receive |
|---|---|---|
| ChatGPT-Assisted Condition First, Then Control Condition | Experimental | 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. Receives: Other: Generative AI-Assisted Clinical Decision Support; Other: Usual Clinical Information Resources |
| Control Condition First, Then ChatGPT-Assisted Condition | Experimental | 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. Receives: Other: Generative AI-Assisted Clinical Decision Support; Other: Usual Clinical Information Resources |
What is being measured
The primary outcome is the main question the study is designed to answer.
Daily Physician Satisfaction Score
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.
Measured: At the end of each working day during the one-month medical intensive care unit rotation
Daily Clinical Decision-Making Score
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.
Measured: At the end of each working day during the one-month medical intensive care unit rotation
Perceived Quality Score for ChatGPT
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.
Measured: At the end of the one-month medical intensive care unit rotation, after completion of both crossover periods
Generative AI Usability Score
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.
Measured: At the end of the one-month medical intensive care unit rotation, after completion of both crossover periods
Satisfaction Score for Generative AI Use
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.
Measured: At the end of the one-month medical intensive care unit rotation, after completion of both crossover periods
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted16 Jul 2026
- Study start1 Dec 2025
- Primary completion31 May 2026
- Study completion31 May 2026
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Clinical Decision SupportStudies of the same condition, open and under way.
- More trials run by Seoul National University HospitalThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Health services research
- Allocation
- Randomised
- Intervention model
- Crossover
- Model description
- The unit of randomization was the physician cluster within each one-month medical intensive care unit rotation. At the beginning of each one-month medical intensive care unit rotation, participating physicians were divided into two clusters. The physician clusters were randomized to one of two intervention sequences: the ChatGPT-assisted condition followed by the control condition, or the control condition followed by the ChatGPT-assisted condition. Each period lasted approximately two weeks, after which the clusters crossed over to the alternate condition. Thus, all participating physicians experienced both study conditions during the same monthly rotation.
- Masking
- None (open label)
- Enrolment
- 15 participants (actual)
Sponsor and investigators
- Lead sponsor
- Seoul National University Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Minju Han, M.D., Principal investigator, Seoul National University Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07708155
- Sponsor's protocol ID
- 2510-145-1689
- Status last verified
- Jul 2026
- First submitted
- 12 Jul 2026
- Last updated
- 21 Jul 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: 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.
Study at a glance
From the registry record, last updated by the sponsor on 21 Jul 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Evaluation of the Feasibility and Effectiveness of Generative AI-Assisted Multidisciplinary Decision Support in Medical Intensive Care: A Pilot Randomized Controlled Trial
- ClinicalTrials.gov ID
- NCT07708155
- Acronym / sponsor ID
- 2510-145-1689
- Keywords
- ChatGPT, Generative Artificial Intelligence, Large Language Model, Clinical Decision Support, Physician Decision-Making, Medical Intensive Care Unit, Critical Care, Usability
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 15 participants (actual)
- Lead sponsor
- Seoul National University HospitalUniversity, hospital or other
- Study start
- 1 Dec 2025 (actual)
- Primary completion
- 31 May 2026 (actual)
- Study completion
- 31 May 2026 (actual)
- First posted
- 16 Jul 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed description
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.
Study design
- Primary purpose
- Health services research
- Allocation
- Randomised
- Intervention model
- Crossover
- Masking
- None (open label)
- Number of arms
- 2
- Model description
- The unit of randomization was the physician cluster within each one-month medical intensive care unit rotation. At the beginning of each one-month medical intensive care unit rotation, participating physicians were divided into two clusters. The physician clusters were randomized to one of two intervention sequences: the ChatGPT-assisted condition followed by the control condition, or the control condition followed by the ChatGPT-assisted condition. Each period lasted approximately two weeks, after which the clusters crossed over to the alternate condition. Thus, all participating physicians experienced both study conditions during the same monthly rotation.
| Arm | Type | Receives |
|---|---|---|
| ChatGPT-Assisted Condition First, Then Control Condition | Experimental | Other: Generative AI-Assisted Clinical Decision Support, Other: Usual Clinical Information ResourcesPhysician 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. |
| Control Condition First, Then ChatGPT-Assisted Condition | Experimental | Other: Generative AI-Assisted Clinical Decision Support, Other: Usual Clinical Information ResourcesPhysician 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. |
Who may qualify
- Ages
- 19 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (4 listed)
- 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.
Key exclusion criteria (2 listed)
- Did not provide written informed consent.
- Withdrew consent from study participation.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Generative AI-Assisted Clinical Decision SupportDuring 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 | ChatGPT-Assisted Condition First, Then Control Condition, Control Condition First, Then ChatGPT-Assisted Condition |
| Usual Clinical Information ResourcesDuring 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. | Other | ChatGPT-Assisted Condition First, Then Control Condition, Control Condition First, Then ChatGPT-Assisted Condition |
Primary outcome
Daily Physician Satisfaction Score
Time frame: At the end of each working day during the one-month medical intensive care unit rotation
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.
Daily Clinical Decision-Making Score
Time frame: At the end of each working day during the one-month medical intensive care unit rotation
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.
Perceived Quality Score for ChatGPT
Time frame: At the end of the one-month medical intensive care unit rotation, after completion of both crossover periods
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.
Generative AI Usability Score
Time frame: At the end of the one-month medical intensive care unit rotation, after completion of both crossover periods
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.
Satisfaction Score for Generative AI Use
Time frame: At the end of the one-month medical intensive care unit rotation, after completion of both crossover periods
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.
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 21 Jul 2026.
- Individual participant dataSharing planned: No. 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.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Minju Han, M.D. principal investigator
Seoul National University Hospital
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Generative AI-Assisted Clinical Decision Support and Usual Clinical Information Resources in people with Clinical Decision Support and Clinical Decision-making, run by Seoul National University Hospital at 1 site in South Korea.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 2 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 21 Jul 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in South Korea. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Daily Physician Satisfaction Score (time frame: At the end of each working day during the one-month medical intensive care unit rotation). The study lists 5 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 21 Jul 2026.