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

NCT06691724 | Completed

• 2 other identifiers: PaNaMa-12075MEC-2024-0286
• Study Type: observational
• Target: 800
• Locations: 1 country
• Sites: 1

Brief 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

Keywords

general practice; workload; large language model; artificial intelligence; documentation; electronic health record; transcription

Outcome Measures

Primary Outcomes (1)

• Time spent on documentation

  This outcome refers to the time spent on documentation for a clinical consultation. The investigators will measure time outcomes through continuous observation. An external observer will monitor the time spent on various tasks during a consultation, including taking the medical history, conducting the physical examination, explaining the diagnosis or treatment plan, consulting a colleague, clinical documentation, and administrative duties like prescribing or referring.

  Measured during the consultation (baseline and intervention)

Secondary Outcomes (8)

• Total consultation time

  Measured during the consultation (baseline and intervention)

• GP experience with the tool

  Measured within one week after the two-day intervention period

• Patient experience with the consultation

  Measured within 1 week after the consultation

• Patient experience with the tool

  Measured within 1 week after the consultation

• Usage rates

  Measured directly after the consultation

Study Arms (12)

GP 01

General practitioner working with/without the tool

Other: LLM-based transcription and reporting tool

GP 02

General practitioner working with/without the tool

Other: LLM-based transcription and reporting tool

GP 03

General practitioner working with/without the tool

Other: LLM-based transcription and reporting tool

GP 04

General practitioner working with/without the tool

Other: LLM-based transcription and reporting tool

GP 05

General practitioner working with/without the tool

Other: LLM-based transcription and reporting tool

GP 06

General practitioner working with/without the tool

Other: LLM-based transcription and reporting tool

GP 07

General practitioner working with/without the tool

Other: LLM-based transcription and reporting tool

GP 08

General practitioner working with/without the tool

Other: LLM-based transcription and reporting tool

GP 09

General practitioner working with/without the tool

Other: LLM-based transcription and reporting tool

GP 10

General practitioner working with/without the tool

Other: LLM-based transcription and reporting tool

GP 11

General practitioner working with/without the tool

Other: LLM-based transcription and reporting tool

GP 12

General practitioner working with/without the tool

Other: LLM-based transcription and reporting tool

Interventions

LLM-based transcription and reporting tool OTHER

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

Also known as: Juvoly QuickConsult

GP 01; GP 02; GP 03; GP 04; GP 05; GP 06; GP 07; GP 08; GP 09; GP 10; GP 11; GP 12

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

* General practitioners (in training) in the Southwest of the Netherlands * Patients seeing general practitioners (in training) in the Southwest of the Netherlands

You may qualify if:

• Planning to implement the AI-based transcription and reporting tool
• Give informed consent for observation and/or interview and/or questionnaire

You may not qualify if:

• \- Insufficient knowledge of the Dutch language to be interviewed
• Patients:
• Give informed consent for questionnaire and/or interview
• For questionnaire: had a consultation with the GP
• For interview: had a consultation with the GP in which the tool was used
• \- Insufficient knowledge of the Dutch language to be interviewed

Sponsors & Collaborators

• Erasmus Medical Center: lead

Study Sites (1)

Erasmus MC

Rotterdam, South Holland, 3015GD, Netherlands

Location

Study Design

• Study Type: observational
• Observational Model: OTHER
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: RCA van Linschoten, MD, Principal investigator

Study Record Dates

• First Submitted: October 25, 2024
• First Posted: November 15, 2024
• Study Start: December 9, 2024
• Primary Completion: July 2, 2025
• Study Completion: July 2, 2025
• Last Updated: December 11, 2025

Record last verified: 2025-12

Data Sharing

• IPD Sharing: Will share
• Shared Documents: STUDY PROTOCOL, SAP, ICF, ANALYTIC CODE
• Time Frame: Unlimited through a data repository.
• Access Criteria: Participants will be asked whether their data may be used in future research projects. Metadata of the project will be shared on a data repository. External investigators can apply for use of the data through this data repository. Only data of participants that allow for re-use of their data will be eligible for sharing.

Locations

NL (1)