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

5 de octubre de 2026 actualizado por: 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.

Descripción general del estudio

Descripción detallada

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.

Tipo de estudio

De observación

Inscripción (Estimado)

100

Contactos y Ubicaciones

Esta sección proporciona los datos de contacto de quienes realizan el estudio e información sobre dónde se lleva a cabo este estudio.

Estudio Contacto

Ubicaciones de estudio

Criterios de participación

Los investigadores buscan personas que se ajusten a una determinada descripción, denominada criterio de elegibilidad. Algunos ejemplos de estos criterios son el estado de salud general de una persona o tratamientos previos.

Criterio de elegibilidad

Edades elegibles para estudiar

18 años y mayores (Adulto, Adulto Mayor)

Acepta Voluntarios Saludables

No

Géneros elegibles para el estudio

Femenino

Método de muestreo

Muestra no probabilística

Población de estudio

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.

Descripción

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

Plan de estudios

Esta sección proporciona detalles del plan de estudio, incluido cómo está diseñado el estudio y qué mide el estudio.

¿Cómo está diseñado el estudio?

Detalles de diseño

  • Modelos observacionales: COHORT
  • Perspectivas temporales: PROSPECTIVE

Cohortes e Intervenciones

Grupo / Cohorte
Intervención / Tratamiento
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.

¿Qué mide el estudio?

Medidas de resultado primarias

Medida de resultado
Medida Descripción
Periodo de tiempo
Proportion of AI history summaries rated useful by the evaluating physician
Periodo de tiempo: 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)

Medidas de resultado secundarias

Medida de resultado
Medida Descripción
Periodo de tiempo
Completeness of the AI-generated history
Periodo de tiempo: 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
Periodo de tiempo: 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
Periodo de tiempo: 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
Periodo de tiempo: 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
Periodo de tiempo: 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)
Periodo de tiempo: 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
Periodo de tiempo: 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
Periodo de tiempo: 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
Periodo de tiempo: 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)

Colaboradores e Investigadores

Aquí es donde encontrará personas y organizaciones involucradas en este estudio.

Publicaciones y enlaces útiles

La persona responsable de ingresar información sobre el estudio proporciona voluntariamente estas publicaciones. Estos pueden ser sobre cualquier cosa relacionada con el estudio.

Fechas de registro del estudio

Estas fechas rastrean el progreso del registro del estudio y los envíos de resultados resumidos a ClinicalTrials.gov. Los registros del estudio y los resultados informados son revisados ​​por la Biblioteca Nacional de Medicina (NLM) para asegurarse de que cumplan con los estándares de control de calidad específicos antes de publicarlos en el sitio web público.

Fechas importantes del estudio

Inicio del estudio (Estimado)

2 de octubre de 2026

Finalización primaria (Estimado)

28 de febrero de 2027

Finalización del estudio (Estimado)

1 de octubre de 2027

Fechas de registro del estudio

Enviado por primera vez

30 de septiembre de 2026

Primero enviado que cumplió con los criterios de control de calidad

30 de septiembre de 2026

Publicado por primera vez (Actual)

6 de octubre de 2026

Actualizaciones de registros de estudio

Última actualización publicada (Actual)

7 de octubre de 2026

Última actualización enviada que cumplió con los criterios de control de calidad

5 de octubre de 2026

Última verificación

1 de septiembre de 2026

Más información

Términos relacionados con este estudio

Otros números de identificación del estudio

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

Plan de datos de participantes individuales (IPD)

¿Planea compartir datos de participantes individuales (IPD)?

NO

Descripción del plan IPD

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.

Información sobre medicamentos y dispositivos, documentos del estudio

Estudia un producto farmacéutico regulado por la FDA de EE. UU.

No

Estudia un producto de dispositivo regulado por la FDA de EE. UU.

No

Esta información se obtuvo directamente del sitio web clinicaltrials.gov sin cambios. Si tiene alguna solicitud para cambiar, eliminar o actualizar los detalles de su estudio, comuníquese con register@clinicaltrials.gov. Tan pronto como se implemente un cambio en clinicaltrials.gov, también se actualizará automáticamente en nuestro sitio web. .

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