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Ambient Scribe in General Practice: a Multi-perspective Before-after Longitudinal Mixed-methods Study

NCT06691724 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 800

Last updated 2025-12-11

No results posted yet for this study

Summary

General practitioners (GPs) in the Netherlands are under unsustainable pressure. Recent surveys show that 68% of general practitioners find the workload too high and 18% find their work extremely or very stressful. The pressure on GPs significantly harms patient care, as reduced physician well-being can negatively impact patient experiences, treatment adherence, patient-provider communication, healthcare costs, care quality, and patient safety.

A key contributor to the stress is the increasing time commitment associated with clinical documentation. The documentation process has evolved into a time-intensive task, which is a significant obstacle to efficient patient care. Large language models (LLMs) are promising artificial intelligence (AI) solutions to reduce the documentation in general practice. In this project, the investigators aim to study an AI-based transcription and reporting tool in general practice.

Conditions

  • Workload

Interventions

OTHER

LLM-based transcription and reporting tool

The LLM-based transcription and reporting tool works in three steps: 1. The conversation between patient and GP is transcribed to text with a speech-to-text LLM 2. The text is summarized according to the Subjective, Objective, Assessment, Plan (SOAP) rules 3. The SOAP summary is imported in the electronic health record of the GP

Sponsors & Collaborators

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2024-12-09
Primary Completion
2025-07-02
Completion
2025-07-02

Countries

  • Netherlands

Study Locations

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Entities

Companies

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06691724 on ClinicalTrials.gov