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A Large Language Model in Outpatient Care

7. Juni 2026 aktualisiert von: Tien Yin Wong, Tsinghua University

A Prospective Randomized Controlled Trial of a Large Language Model in Outpatient Care

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

Studienübersicht

Status

Noch keine Rekrutierung

Bedingungen

Intervention / Behandlung

Studientyp

Interventionell

Einschreibung (Geschätzt)

3500

Phase

  • Unzutreffend

Teilnahmekriterien

Forscher suchen nach Personen, die einer bestimmten Beschreibung entsprechen, die als Auswahlkriterien bezeichnet werden. Einige Beispiele für diese Kriterien sind der allgemeine Gesundheitszustand einer Person oder frühere Behandlungen.

Zulassungskriterien

Studienberechtigtes Alter

  • Erwachsene
  • Älterer Erwachsener

Akzeptiert gesunde Freiwillige

Nein

Beschreibung

Inclusion Criteria:

Doctors:

  1. Licensed physicians providing outpatient consultations at a participating study hospital
  2. Expected to complete a sufficient number of outpatient clinic sessions during the study period
  3. Provides written informed consent

Patients:

  1. Age 18 years or older
  2. Attending an outpatient consultation with a participating doctor
  3. Able to interact with the tool using an internet-connected device such as a smartphone
  4. Provides written informed consent

Exclusion Criteria:

Patients:

  1. Psychiatric conditions, unstable vital signs, or other medical situations considered unsuitable for AI-based interaction
  2. Declines to provide informed consent

Studienplan

Dieser Abschnitt enthält Einzelheiten zum Studienplan, einschließlich des Studiendesigns und der Messung der Studieninhalte.

Wie ist die Studie aufgebaut?

Designdetails

  • Hauptzweck: Versorgungsforschung
  • Zuteilung: Zufällig
  • Interventionsmodell: Crossover-Aufgabe
  • Maskierung: Single

Waffen und Interventionen

Teilnehmergruppe / Arm
Intervention / Behandlung
Kein Eingriff: Standard Outpatient Care (No AI)
Neither doctors nor patients use a large language model based tool. Outpatient consultations and documentation are conducted following routine clinical practice.
Experimental: Outpatient Care With a Large Language Model Tool
Before the consultation, patients complete an AI-based pre-consultation interaction. During the visit, a large language model based tool is available to support the outpatient consultation process. Doctors may refer to the tool during the visit.
Sonstiges: 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.
Experimental: Outpatient Care With a Large Language Model Tool and Workflow Support
Before the consultation, patients complete an AI-based pre-consultation interaction. During the visit, a large language model based tool is used together with additional workflow support to integrate the tool's output into the outpatient consultation process.
Sonstiges: 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.

Was misst die Studie?

Primäre Ergebnismessungen

Ergebnis Maßnahme
Maßnahmenbeschreibung
Zeitfenster
Duration of the Outpatient Consultation
Zeitfenster: During the outpatient visit
Time of the outpatient consultation, measured in milliseconds
During the outpatient visit
Doctor-Reported Efficiency of the Consultation
Zeitfenster: Immediately after the consultation
Doctor's self-rated efficiency of the consultation, measured on a 5-point Likert scale (1 = very low to 5 = very high), with higher scores indicating higher perceived efficiency.
Immediately after the consultation
Doctor-Reported Satisfaction With the Consultation Process
Zeitfenster: Immediately after the consultation
Doctor's satisfaction with the consultation process, measured on a 5-point Likert scale (1 = very low to 5 = very high), with higher scores indicating higher satisfaction.
Immediately after the consultation

Sekundäre Ergebnismessungen

Ergebnis Maßnahme
Maßnahmenbeschreibung
Zeitfenster
Doctor-Reported Efficiency of Obtaining Patient Information
Zeitfenster: Immediately after the consultation
Doctor's self-rated efficiency in obtaining the patient's clinical information (such as symptoms, history, prior examinations) during the consultation, measured on a 5-point Likert scale (1 = very low to 5 = very high); higher scores indicate higher efficiency.
Immediately after the consultation
Doctor-Reported Cognitive Effort in Clinical Decision-Making
Zeitfenster: Immediately after the consultation
Doctor's self-rated cognitive effort invested in clinical decision-making during the consultation, measured on a 5-point Likert scale (1 = very low to 5 = very high); higher scores indicate greater effort.
Immediately after the consultation
Doctor-Reported Burden of Clinical Documentation
Zeitfenster: Immediately after the consultation
Doctor's self-rated burden of completing the outpatient medical record for the consultation, measured on a 5-point Likert scale (1 = very low to 5 = very high); higher scores indicate greater burden.
Immediately after the consultation
Doctor's Intention to Continue Using the Tool
Zeitfenster: Within 1 week after the participating doctor completes all enrolled consultations
Doctor's intention to continue using the large language model based tool in routine practice, measured on a 5-point Likert scale (1 = strongly unwilling to 5 = strongly willing); higher scores indicate stronger intention.
Within 1 week after the participating doctor completes all enrolled consultations
Patient Trust in the Physician
Zeitfenster: Immediately after the consultation
Patient's level of trust in the physician after the visit, measured on a 5-point Likert scale (1 = very low to 5 = very high); higher scores indicate greater trust.
Immediately after the consultation
Patient Satisfaction With the Visit
Zeitfenster: Immediately after the consultation
Patient's satisfaction with the visit, measured on a 5-point Likert scale (1 = very low to 5 = very high); higher scores indicate greater satisfaction.
Immediately after the consultation
Patient-Perceived Physician Attentiveness
Zeitfenster: Immediately after the consultation
Patient-perceived attentiveness of the physician during the visit, assessed by a multi-item measure and reported as a composite score on a 1-5 scale; higher scores indicate greater perceived attentiveness.
Immediately after the consultation
Patient Satisfaction With the AI Pre-Consultation (Arm 2 and Arm 3 )
Zeitfenster: Immediately after the consultation
Patient's satisfaction with the AI-based pre-consultation interaction, measured on a 5-point Likert scale (1 = very low to 5 = very high); higher scores indicate greater satisfaction. Assessed only in Arm 2 and Arm 3.
Immediately after the consultation
Patient's Intention to Use AI Pre-Consultation in the Future (Arm 2 and Arm 3)
Zeitfenster: Immediately after the consultation
Patient's intention to use AI-based pre-consultation again in the future, measured on a 5-point Likert scale (1 = strongly unwilling to 5 = strongly willing); higher scores indicate stronger intention. Assessed only in Arm 2 and Arm 3.
Immediately after the consultation

Mitarbeiter und Ermittler

Hier finden Sie Personen und Organisationen, die an dieser Studie beteiligt sind.

Sponsor

Tsinghua University

Studienaufzeichnungsdaten

Diese Daten verfolgen den Fortschritt der Übermittlung von Studienaufzeichnungen und zusammenfassenden Ergebnissen an ClinicalTrials.gov. Studienaufzeichnungen und gemeldete Ergebnisse werden von der National Library of Medicine (NLM) überprüft, um sicherzustellen, dass sie bestimmten Qualitätskontrollstandards entsprechen, bevor sie auf der öffentlichen Website veröffentlicht werden.

Haupttermine studieren

Studienbeginn (Geschätzt)

12. Juni 2026

Primärer Abschluss (Geschätzt)

4. September 2026

Studienabschluss (Geschätzt)

4. September 2026

Studienanmeldedaten

Zuerst eingereicht

29. Mai 2026

Zuerst eingereicht, das die QC-Kriterien erfüllt hat

7. Juni 2026

Zuerst gepostet (Tatsächlich)

11. Juni 2026

Studienaufzeichnungsaktualisierungen

Letztes Update gepostet (Tatsächlich)

11. Juni 2026

Letztes eingereichtes Update, das die QC-Kriterien erfüllt

7. Juni 2026

Zuletzt verifiziert

1. Juni 2026

Mehr Informationen

Begriffe im Zusammenhang mit dieser Studie

Andere Studien-ID-Nummern

  • THU-01-2026-0055

Arzneimittel- und Geräteinformationen, Studienunterlagen

Studiert ein von der US-amerikanischen FDA reguliertes Arzneimittelprodukt

Nein

Studiert ein von der US-amerikanischen FDA reguliertes Geräteprodukt

Nein

Diese Informationen wurden ohne Änderungen direkt von der Website clinicaltrials.gov abgerufen. Wenn Sie Ihre Studiendaten ändern, entfernen oder aktualisieren möchten, wenden Sie sich bitte an register@clinicaltrials.gov. Sobald eine Änderung auf clinicaltrials.gov implementiert wird, wird diese automatisch auch auf unserer Website aktualisiert .

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