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Augmenting Clinical Workflow With a Structured Chatbot for Patient History Collection and Diagnostic Support (CHAT-HX)

5. Oktober 2026 aktualisiert von: Sonu Subudhi, Massachusetts General Hospital

Prospective Observational Evaluation of a Structured, Agentic AI Chatbot for Pre-Visit Patient History Collection and Diagnostic Support in Outpatient Clinical Workflows

Doctors spend much of each visit collecting the patient's medical history, and incomplete histories can delay diagnosis. This study tests an AI chatbot that interviews patients before their appointment and produces a structured summary of their history for the doctor. Adult patients at the first study site, a university gynecology outpatient clinic in Germany, answer the chatbot's questions on a tablet before the doctor visit. The doctor then takes the history and examines the patient as usual, without seeing the chatbot's output. Only after the doctor has finished planning care does the doctor review the chatbot's summary and rate its usefulness and accuracy. The chatbot does not change patient care. Patients also rate the ease of use and acceptability of the chatbot. The investigators will report how useful doctors find the summaries, how complete and correct the summaries are, and how patients experience the tool.

Studienübersicht

Status

Noch keine Rekrutierung

Bedingungen

Intervention / Behandlung

Detaillierte Beschreibung

This is a prospective, observational study of an AI-based, structured history-taking tool used before a clinical visit. The tool uses large language models and follows a fixed interview plan with defined topic blocks, such as chief complaint, current history, past conditions, medications, allergies, specialty-specific history, and social and family history. It produces a structured history summary, a list of possible diagnoses, and suggested workup steps. In earlier benchmarking on more than 670 simulated and clinical cases, the system captured most clinically relevant history items and flagged clinically important warning signs.

The study is designed so that the tool does not influence care. Participants give written informed consent, then complete the AI interview on a study tablet using a pseudonymous study ID. Participants enter no name, birth date, or address. Participants then complete a short questionnaire on usability and acceptance. The treating physician takes a full history, examines the patient, and documents a plan without access to the AI output. Only afterward does the physician receive the AI output and complete a structured evaluation of its completeness, correctness, plausibility, and usefulness. No follow-up contact occurs after the visit.

The study is not randomized and has no control arm. The physician's independently obtained history serves as the reference standard. The first site is the Department of Gynecology at Leipzig University Hospital, with about 100 patients and 8 to 15 physicians. Analysis is descriptive, with subgroup comparisons by reason for visit. Additional sites may be added later. The study is a collaboration between Leipzig University Hospital and Massachusetts General Hospital and Harvard Medical School.

Studientyp

Beobachtungs

Einschreibung (Geschätzt)

100

Kontakte und Standorte

Dieser Abschnitt enthält die Kontaktdaten derjenigen, die die Studie durchführen, und Informationen darüber, wo diese Studie durchgeführt wird.

Studienkontakt

Studienorte

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

18 Jahre und älter (Erwachsene, Älterer Erwachsener)

Akzeptiert gesunde Freiwillige

Nein

Studienberechtigte Geschlechter

Weiblich

Probenahmeverfahren

Nicht-Wahrscheinlichkeitsprobe

Studienpopulation

Adult women presenting for the first time, or with a new complaint, to the general gynecology outpatient clinic, the gynecology emergency clinic, or as referrals to the gynecology outpatient clinic at the first study site (Leipzig University Hospital, Germany). Patients are recruited consecutively in the clinic waiting area by trained study staff. Additional sites may be added later.

Beschreibung

Inclusion Criteria:

Women 18 years or older

First presentation or new complaint at the gynecology outpatient clinic (self-presentation, emergency, or referral)

Sufficient German language skills to complete a structured patient interview independently

Able to complete study participation without external support

Written informed consent

Exclusion Criteria:

Acute emergency requiring immediate treatment (for example, impaired consciousness, hemodynamic instability, or acute bleeding requiring immediate care)

Lack of legal or decisional capacity to consent

Insufficient language skills

Severe cognitive, visual, or motor impairment preventing tablet use

Previous participation in this study

Refusal or withdrawal of consent

Studienplan

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

Wie ist die Studie aufgebaut?

Designdetails

  • Beobachtungsmodelle: COHORT
  • Zeitperspektiven: PROSPECTIVE

Kohorten und Interventionen

Gruppe / Kohorte
Intervention / Behandlung
Adult Clinic Patients

Adult patients with a first presentation or new complaint at the participating outpatient clinic who consent to complete the AI-based pre-visit history interview and questionnaire. Their physician completes routine care blinded to the AI output, then evaluates the AI-generated summary.

A large language model-based agentic chatbot that conducts a structured, pre-visit history interview on a study tablet and generates a history summary, differential diagnosis list, and workup suggestions. The output is released to the treating physician only after the physician has completed an independent history, examination, and care plan, and does not influence patient care.

Was misst die Studie?

Primäre Ergebnismessungen

Ergebnis Maßnahme
Maßnahmenbeschreibung
Zeitfenster
Proportion of AI history summaries rated useful by the evaluating physician
Zeitfenster: Same day as the enrollment visit, after routine care is complete (up to approximately 1 day)

After completing routine care, the treating physician rates the usefulness of the AI-generated history summary on a 5-point Likert scale (1 = not useful at all, 5 = very useful). The outcome is the proportion of summaries rated 4 or higher, reported with a 95% Wilson confidence interval.

Same day as the enrollment visit, after routine care is complete (up to approximately 1 day)

Sekundäre Ergebnismessungen

Ergebnis Maßnahme
Maßnahmenbeschreibung
Zeitfenster
Completeness of the AI-generated history
Zeitfenster: Same day as the enrollment visit, after routine care is complete (up to approximately 1 day)

Percentage of items from a standardized history grid that the AI captured correctly, reported overall and by history domain.

Same day as the enrollment visit, after routine care is complete (up to approximately 1 day)
Correctness of the AI-generated history
Zeitfenster: Same day as the enrollment visit, after routine care is complete (up to approximately 1 day)

Proportion of factually incorrect or missing clinically relevant items in the AI history, per physician review.

Same day as the enrollment visit, after routine care is complete (up to approximately 1 day)
Plausibility of AI differential diagnoses
Zeitfenster: Same day as the enrollment visit, after routine care is complete (up to approximately 1 day)

Physician rating of plausibility on a 1-5 Likert scale, and concordance of the AI differential with the physician's working diagnosis.

Same day as the enrollment visit, after routine care is complete (up to approximately 1 day)
Plausibility of AI workup recommendations
Zeitfenster: Same day as the enrollment visit, after routine care is complete (up to approximately 1 day)

Physician rating of the AI's suggested diagnostic workup on a 1-5 Likert scale.

Same day as the enrollment visit, after routine care is complete (up to approximately 1 day)
Identification of clinically relevant red flags
Zeitfenster: Same day as the enrollment visit, after routine care is complete (up to approximately 1 day)

Proportion of clinically relevant red flags correctly recognized by the AI versus not recognized, per physician review.

Same day as the enrollment visit, after routine care is complete (up to approximately 1 day)
Patient usability (System Usability Scale)
Zeitfenster: Same day as the enrollment visit, immediately after the AI interview or after the physician consultation (up to approximately 1 day)

Patient-completed System Usability Scale, score 0-100, higher scores indicating better usability.

Same day as the enrollment visit, immediately after the AI interview or after the physician consultation (up to approximately 1 day)
Patient acceptance and willingness to use the tool again
Zeitfenster: Same day as the enrollment visit, immediately after the AI interview or after the physician consultation (up to approximately 1 day)

Patient-reported acceptance, comprehensibility, empathy, comfort, trust, and willingness to use again, each on a 1-5 Likert scale.

Same day as the enrollment visit, immediately after the AI interview or after the physician consultation (up to approximately 1 day)
Duration of the AI interaction
Zeitfenster: During the AI interview at the enrollment visit (approximately 15 minutes)

Time in minutes for the patient to complete the AI interview, recorded automatically by the system.

During the AI interview at the enrollment visit (approximately 15 minutes)
Physician-estimated time savings
Zeitfenster: Same day as the enrollment visit, after routine care is complete (up to approximately 1 day)

Physician's estimate, in minutes, of the time the AI history would save in clinical workflow.

Same day as the enrollment visit, after routine care is complete (up to approximately 1 day)

Mitarbeiter und Ermittler

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

Sponsor

Mitarbeiter

Publikationen und hilfreiche Links

Die Bereitstellung dieser Publikationen erfolgt freiwillig durch die für die Eingabe von Informationen über die Studie verantwortliche Person. Diese können sich auf alles beziehen, was mit dem Studium zu tun hat.

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)

2. Oktober 2026

Primärer Abschluss (Geschätzt)

28. Februar 2027

Studienabschluss (Geschätzt)

1. Oktober 2027

Studienanmeldedaten

Zuerst eingereicht

30. September 2026

Zuerst eingereicht, das die QC-Kriterien erfüllt hat

30. September 2026

Zuerst gepostet (Tatsächlich)

6. Oktober 2026

Studienaufzeichnungsaktualisierungen

Letztes Update gepostet (Tatsächlich)

7. Oktober 2026

Letztes eingereichtes Update, das die QC-Kriterien erfüllt

5. Oktober 2026

Zuletzt verifiziert

1. September 2026

Mehr Informationen

Begriffe im Zusammenhang mit dieser Studie

Andere Studien-ID-Nummern

  • 2026P001764
  • 201/26-ek (Andere Kennung: Ethics Committee, Medical Faculty, Leipzig University)

Plan für individuelle Teilnehmerdaten (IPD)

Planen Sie, individuelle Teilnehmerdaten (IPD) zu teilen?

NEIN

Beschreibung des IPD-Plans

Individual participant data will not be shared with outside researchers. Participants consented under a German ethics-approved form that permits only fully anonymized, aggregated data to be shared with collaborating study partners for analysis and publication. Data are pseudonymized, are classified as health data under GDPR, and remain on servers of the clinical site. De-identified aggregate results will be reported in publications.

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 .