Intermountain Health Improves Patient Care and Efficiency with Cloud AI Solutions
Intermountain Health, a large US healthcare system serving the western states, aimed to reduce caregiver burnout, streamline operations, and scale responsible AI deployment in healthcare. They built an AI-first infrastructure on Microsoft Azure, leveraging Azure OpenAI Service, Azure Databricks, Azure API Management, Microsoft 365, Microsoft Copilot, and GitHub Actions for continuous integration, alongside Arize AI for AI observability. Solutions deployed included clinical documentation summarization, patient email response automation, and high-risk patient identification for proactive outreach. Arize AI was integrated for robust AI observability, responsible AI deployment, and continuous performance monitoring, enhancing both reliability and transparency. AI models can now be developed and put into production in weeks rather than months, directly improving efficiency for both clinical and IT caregivers. Over 4,300 work hours saved in a year for clinical caregivers; automated monitoring and analysis help maintain responsible AI performance across 34 hospitals and 400 clinics. Plans involve expanding use of personalized AI agents and RAG frameworks for additional workflows and clinical processes.
- Organization
- Intermountain Health
- Industry
- Healthcare
- Location
- United States
Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
- Customer
- Intermountain Health
- Provider
- Microsoft
- Maturity
- Scaled Production
- Linked source
- microsoft.com
Long lead times for deploying new AI models at scale
Primary read
Use case focus
Showing 3 of 3
- 1Clinical Documentation Summarization via AI
- 2Automated Patient Email Response
- 3High-risk Patient Identification/Outreach
- Deployment of cloud-based AI infrastructure using Azure OpenAI Service, Databricks, and API Management.
- Automated documentation and email response workflows for clinicians.
- Continuous integration and delivery pipelines with GitHub Actions for Azure.
- AI observability via Arize AI to monitor, assess performance, and ensure responsible use.
- Saved 4,300+ work hours for clinical staff in one year.
- Reduced clinician documentation time, allowing more patient-facing care.
- AI deployments accelerated from months to weeks or days.
Architecture
Intermountain Health uses Azure cloud infrastructure for centralized AI model deployment, integrates workflow automation (documentation, email response, patient risk prediction) with services like Azure OpenAI, Databricks, API Management, and employs Arize AI for observability and responsible AI monitoring.
Sources & evidence1
- Customer explicitly identified
- Deployment status explicitly supported
- Primary source available
- Technical implementation details available
AI-generated summary. Verify important details with the linked sources before relying on this case.
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