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Augmenting Clinical Workflow With a Structured Chatbot for Patient History Collection and Diagnostic Support
Sponsor: Massachusetts General Hospital
Summary
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.
Official title: Prospective Observational Evaluation of a Structured, Agentic AI Chatbot for Pre-Visit Patient History Collection and Diagnostic Support in Outpatient Clinical Workflows
Key Details
Gender
FEMALE
Age Range
18 Years - Any
Study Type
OBSERVATIONAL
Enrollment
100
Start Date
2026-10-02
Completion Date
2027-10-01
Last Updated
2026-10-07
Healthy Volunteers
No
Conditions
Interventions
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.
Locations (1)
Universität Leipzig
Leipzig, Germany