MicrosoftLive source
Doctolib transforms consultations with Azure OpenAI Service
Use case typeClinical documentationUpdated Jun 13, 2026
Doctolib utilized Azure OpenAI Service to create an AI-powered medical assistant, enabling real-time transcription of consultations. This supports healthcare practitioners by reducing documentation workload and improving the patient experience.
- Organization
- Doctolib
- Industry
- Healthcare
- Location
- France
- Published
- April 2025
Reported outcomes
−50%
timeTime & speed
Strategic outcomes
Speed & agilityReduced documentation workload during consultationsCustomer experience & trustImproved consultation quality and patient engagementEmployee experienceEnhanced satisfaction among healthcare staffNew product / capabilityEnabled automated consultation note summarization
Catalog median for time & speed deployments: −60% across 727 reported metrics. Compare benchmarks →
Primary read
Use case focus
Showing 3 of 4
- 1Real-time medical consultation transcription
- 2Automated generation of structured consultation summaries
- 3AI-powered assistant for clinical note-taking
- Practitioners spend significant time on manual documentation during patient consultations
- Administrative workload leads to burnout among healthcare professionals
- Real-time note-taking increases risk of errors and documentation gaps
- Patients experience less engagement due to divided practitioner attention
- Deployed Azure OpenAI-based medical assistant for real-time transcription
- Enabled automated summarization and organization of consultation notes
- Integrated AI assistant seamlessly within practitioners' workflow
Technologies
- Reduced administrative documentation time by up to 50% for practitioners
- Improved consultation quality and patient engagement
- Enhanced satisfaction among healthcare staff
- Streamlined and accurate medical records creation
Sources & evidence1
Live sourceStill referenced
The case's original source is still reachable.
- Cited source last checked Jun 12, 2026 — ok (0/1 broken).
Measures whether this deployment's public evidence persists — not whether the system is still in production.
Groundedness: Unavailable
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