United StatesHealthcare and life sciences2024 – ongoingIntermountain Health
Azure-based AI platform for clinical notes and patient messages
Utah health system estimates 4,300 hours saved in a year with Azure OpenAI tools
Problem
Intermountain wanted to scale AI for patient care and caregiver support on a reliable cloud base.
Approach
It moved its AI work to Azure with Databricks, Azure OpenAI Service and API Management. Automated deployment checks require models to reach at least 80% accuracy. Uses include note summaries, draft replies to patient emails and flagging high-risk patients.
Results
Takeaway
Microsoft estimates that Intermountain saved 4,300 hours of work in the previous year. Models that once took months to deploy now take weeks or days.
Categories
- Size
- Large enterprise
- Industry
- Healthcare and life sciences
- Business function
- IT and R&DInternal work and knowledge management
- Innovation type
- Process innovation
- AI technology
- Generative AIPredictive analytics and ML
- Adoption
- Built in-house
- Evidence
- Vendor's case study
Sources
Source summaries
Microsoft describes how Intermountain built and deployed AI models on Azure across its six-state health system. It reports an estimated 4,300 hours saved and faster model deployment.
Full details are in the original sources.
