A Large Language Model in Outpatient Care
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- The protocol lists: Large Language Model Based Tool, Workflow Support for Large Language Model Tool Integration.
- Who it may be relevant to
- Registry conditions: Outpatient Care. Basic parameters: from 18 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- Center list to be confirmed — check the primary protocol.
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
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Official title
A Prospective Randomized Controlled Trial of a Large Language Model in Outpatient Care
Overview
The goal of this clinical trial is to learn how the use of a large language model (LLM) based tool affects outpatient clinical care in adult patients attending general hospital outpatient clinics. The main questions it aims to answer are: Does the use of an LLM-based tool affect the efficiency of outpatient visits? Does the use of an LLM-based tool affect the experience of doctors and patients during outpatient care? Researchers will compare outpatient visits supported by an LLM-based tool to standard outpatient visits without such a tool, to see whether and how the tool influences the care process and the experiences of doctors and patients. Participants will: Take part in outpatient visits that may or may not involve an LLM-based tool, depending on their assigned group Complete a short questionnaire about their visit experience after the consultation
Interventions
- Other Large Language Model Based Tool
A large language model based tool is introduced into the outpatient consultation workflow to support the consultation and documentation process. - Other Workflow Support for Large Language Model Tool Integration
Additional workflow support is provided to integrate the output of the large language model based tool into the consultation process, approximating a more integrated deployment of the tool.
Primary outcome measures
- Duration of the Outpatient Consultation [Time frame: During the outpatient visit]
- Doctor-Reported Efficiency of the Consultation [Time frame: Immediately after the consultation]
- Doctor-Reported Satisfaction With the Consultation Process [Time frame: Immediately after the consultation]
Secondary outcome measures (9)
- Doctor-Reported Efficiency of Obtaining Patient Information [Time frame: Immediately after the consultation]
- Doctor-Reported Cognitive Effort in Clinical Decision-Making [Time frame: Immediately after the consultation]
- Doctor-Reported Burden of Clinical Documentation [Time frame: Immediately after the consultation]
- Doctor's Intention to Continue Using the Tool [Time frame: Within 1 week after the participating doctor completes all enrolled consultations]
- Patient Trust in the Physician [Time frame: Immediately after the consultation]
- Patient Satisfaction With the Visit [Time frame: Immediately after the consultation]
- Patient-Perceived Physician Attentiveness [Time frame: Immediately after the consultation]
- Patient Satisfaction With the AI Pre-Consultation (Arm 2 and Arm 3 ) [Time frame: Immediately after the consultation]
- Patient's Intention to Use AI Pre-Consultation in the Future (Arm 2 and Arm 3) [Time frame: Immediately after the consultation]
Eligibility criteria
Inclusion criteria
Doctors:
- Licensed physicians providing outpatient consultations at a participating study hospital
- Expected to complete a sufficient number of outpatient clinic sessions during the study period
- Provides written informed consent
Patients:
- Age 18 years or older
- Attending an outpatient consultation with a participating doctor
- Able to interact with the tool using an internet-connected device such as a smartphone
- Provides written informed consent
Exclusion criteria
Patients:
- Psychiatric conditions, unstable vital signs, or other medical situations considered unsuitable for AI-based interaction
- Declines to provide informed consent
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: No
Study design
- Allocation
- Randomized
- Model
- Crossover
- Masking
- Single blind
- Primary purpose
- Health services research
Study locations
Center list to be confirmed — check the primary protocol.
Identifiers
NCT: NCT07641478 · THU-01-2026-0055