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

5 октября 2026 г. обновлено: 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.

Обзор исследования

Статус

Еще не набирают

Условия

Вмешательство/лечение

Подробное описание

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.

Тип исследования

Наблюдательный

Регистрация (Оцененный)

100

Контакты и местонахождение

В этом разделе приведены контактные данные лиц, проводящих исследование, и информация о том, где проводится это исследование.

Контакты исследования

  • Имя: Sonu Subudhi, MBBS, PhD
  • Номер телефона: 617-726-8051
  • Электронная почта: ssubudhi@mgh.harvard.edu

Места учебы

Критерии участия

Исследователи ищут людей, которые соответствуют определенному описанию, называемому критериям приемлемости. Некоторыми примерами этих критериев являются общее состояние здоровья человека или предшествующее лечение.

Критерии приемлемости

Возраст, подходящий для обучения

18 лет и старше (Взрослый, Пожилой взрослый)

Принимает здоровых добровольцев

Нет

Полы, имеющие право на обучение

Женский

Метод выборки

Невероятностная выборка

Исследуемая популяция

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.

Описание

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

Учебный план

В этом разделе представлена ​​подробная информация о плане исследования, в том числе о том, как планируется исследование и что оно измеряет.

Как устроено исследование?

Детали дизайна

  • Наблюдательные модели: COHORT
  • Временные перспективы: PROSPECTIVE

Когорты и вмешательства

Группа / когорта
Вмешательство/лечение
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.
Другой: AI-Based Structured History-Taking Chatbot

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.

Что измеряет исследование?

Первичные показатели результатов

Мера результата
Мера Описание
Временное ограничение
Proportion of AI history summaries rated useful by the evaluating physician
Временное ограничение: 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)

Вторичные показатели результатов

Мера результата
Мера Описание
Временное ограничение
Completeness of the AI-generated history
Временное ограничение: 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
Временное ограничение: 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
Временное ограничение: 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
Временное ограничение: 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
Временное ограничение: 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)
Временное ограничение: 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
Временное ограничение: 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
Временное ограничение: 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
Временное ограничение: 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)

Соавторы и исследователи

Здесь вы найдете людей и организации, участвующие в этом исследовании.

Спонсор

Massachusetts General Hospital

Соавторы

University of Leipzig

Публикации и полезные ссылки

Лицо, ответственное за внесение сведений об исследовании, добровольно предоставляет эти публикации. Это может быть что угодно, связанное с исследованием.

Общие публикации

Даты записи исследования

Эти даты отслеживают ход отправки отчетов об исследованиях и сводных результатов на сайт ClinicalTrials.gov. Записи исследований и сообщаемые результаты проверяются Национальной медицинской библиотекой (NLM), чтобы убедиться, что они соответствуют определенным стандартам контроля качества, прежде чем публиковать их на общедоступном веб-сайте.

Изучение основных дат

Начало исследования (Оцененный)

2 октября 2026 г.

Первичное завершение (Оцененный)

28 февраля 2027 г.

Завершение исследования (Оцененный)

1 октября 2027 г.

Даты регистрации исследования

Первый отправленный

30 сентября 2026 г.

Впервые представлено, что соответствует критериям контроля качества

30 сентября 2026 г.

Первый опубликованный (Действительный)

6 октября 2026 г.

Обновления учебных записей

Последнее опубликованное обновление (Действительный)

7 октября 2026 г.

Последнее отправленное обновление, отвечающее критериям контроля качества

5 октября 2026 г.

Последняя проверка

1 сентября 2026 г.

Дополнительная информация

Термины, связанные с этим исследованием

Ключевые слова

Другие идентификационные номера исследования

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

Планирование данных отдельных участников (IPD)

Планируете делиться данными об отдельных участниках (IPD)?

НЕТ

Описание плана 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.

Информация о лекарствах и устройствах, исследовательские документы

Изучает лекарственный продукт, регулируемый FDA США.

Нет

Изучает продукт устройства, регулируемый Управлением по санитарному надзору за качеством пищевых продуктов и медикаментов США.

Нет

Эта информация была получена непосредственно с веб-сайта clinicaltrials.gov без каких-либо изменений. Если у вас есть запросы на изменение, удаление или обновление сведений об исследовании, обращайтесь по адресу register@clinicaltrials.gov. Как только изменение будет реализовано на clinicaltrials.gov, оно будет автоматически обновлено и на нашем веб-сайте. .

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