How Stanford Health Care turned generative AI into enterprise infrastructure

At Stanford Health Care, clinicians were already experimenting with AI. But like most organizations, those tools lived outside the EHR—creating friction, introducing compliance risk, and limiting real clinical impact.

Stanford didn’t double down on pilots. It rebuilt the foundation. Download the full case study here.

From disconnected tools to embedded infrastructure

Instead of layering AI on top of workflows, Stanford developed ChatEHR—a real-time, in-Epic platform designed to operate inside clinical workflows. The platform allows clinicians to ask plain-language questions directly within the chart, retrieve and synthesize patient data in seconds, and automate routine workflows without leaving Epic.

ChatEHR delivered measurable impact across the organization:

• 40–70% reduction in time spent on targeted workflows
• >95% faster data retrieval (from ~2 minutes to ~4 seconds)
• 4+ clinician hours saved daily from a single automation
• 450+ active users across clinical and operational teams

These gains came from embedding AI where work actually happens—not asking clinicians to adapt to new tools.

Why Stanford succeeded where others stall

Most organizations struggle to move beyond AI experimentation. Stanford avoided that trap by treating AI as infrastructure, not a feature.

Key differentiators:

• Workflow-first design grounded in real clinician behavior
• Platform architecture that supports repeatable, scalable use cases
• Continuous evaluation, powered by MedHELM, to ensure safety and accuracy over time
• Governance built in, not added later

What you’ll learn in the full case study

Download the full case study to see:

• How Stanford designed and deployed ChatEHR inside Epic
• The architecture behind scalable, multi-model AI platforms
• How MedHELM enables continuous evaluation and governance
• The phased rollout strategy that drove adoption across 1,400+ users
• Where Stanford is expanding next—and what it means for health systems

Download the full case study here. 

The Digital Health Most Wired® (DHMW) program is an industry-recognized benchmarking initiative that measures how effectively health systems and hospitals use digital health and information technology to drive better patient outcomes, improve clinical and operational performance, and advance innovation at scale. 

Each year, participating organizations complete a comprehensive survey that evaluates digital health capabilities across multiple domains, including infrastructure, interoperability, analytics, patient engagement, governance, cybersecurity, and emerging technologies such as AI and automation. Survey responses are validated through structured documentation and peer review to ensure accuracy and rigor. 

Organizations are scored and recognized across progressive performance levels, with Level 10 representing the highest achievement—demonstrating not only advanced technology adoption, but measurable outcomes, enterprise governance, and sustainable digital transformation. DHMW serves as both a benchmarking tool and a strategic framework, helping healthcare leaders assess digital maturity, identify opportunities for improvement, and share proven practices across the industry.