Table of Contents
As health systems race to adopt new AI capabilities, Walnut Creek, California-based John Muir Health has built an EHR optimization strategy centered on avoiding unnecessary customization. The health system’s approach is to stay as close as possible to its EHR vendor’s standard configuration, a strategy Chief Medical Information Officer Priti Patel, MD, said has made it easier to adopt new functionality over time.
Why Standard Configuration Anchors This EHR Optimization Strategy
After more than a decade on its current EHR, John Muir Health has learned that customization creates long-term maintenance burdens and makes it harder to adopt future enhancements, according to Dr. Patel. The closer the organization stays to standard configuration, the easier it becomes to adopt the rapid pace of innovation coming from its EHR vendor — a principle that sits at the core of the health system’s EHR optimization strategy.
A Shared Effort Across Teams
Dr. Patel said EHR optimization at John Muir Health is a shared effort among clinical informatics, IT and operational leaders. The teams conduct an annual review of the vendor’s product roadmap to evaluate new features and determine which initiatives best align with the organization’s priorities, forming a structured backbone for the broader EHR optimization strategy.
How Requests Are Prioritized Under This EHR Optimization Strategy
Throughout the year, end users and business leaders can submit optimization requests, which are reviewed through governance committees before being prioritized by executive leadership. This structured intake process ensures the EHR optimization strategy reflects input from across the organization, rather than being driven solely by IT or executive priorities.
Balancing Priorities Against Resource Availability
The health system weighs requests against its strategic priorities while also considering the availability of specialized IT resources, as analyst capacity varies across different areas of the EHR. Dr. Patel gave an example: the organization may have limited resources available to support inpatient care-related initiatives while having greater capacity to support patient portal optimization. As a result, timing and sequencing under this EHR optimization strategy are influenced not only by strategic importance but also by the availability of the specific teams needed to execute the work.
How AI Fits Into John Muir Health’s EHR Optimization Strategy
That standardized approach has also positioned John Muir Health to take advantage of AI-driven documentation capabilities. Rather than continuing to invest primarily in templates and other documentation shortcuts, the organization has shifted more of its optimization efforts toward AI tools that reduce clinicians’ documentation workload, marking a notable evolution in its EHR optimization strategy.
A Fundamentally Different Kind of Tool
“AI is fundamentally different,” Dr. Patel said. Rather than making documentation tools more efficient, it provides substantive documentation support and helps reduce manual work, which she described as one of the most significant improvements in clinical documentation she has seen during her time working with EHRs.
The Biggest ROI Lever in This EHR Optimization Strategy
John Muir Health’s biggest optimization lever, and the one that has delivered the greatest return, has been its focus on EHR best-practice adoption programs. According to Dr. Patel, these programs have given the health system a framework for implementing best-practice functionality, strengthened the foundation of its EHR, and increased adoption of valuable capabilities — a central pillar of the overall EHR optimization strategy.
A Foundation, Not a Single Feature
“The biggest ROI has not come from any single feature,” Dr. Patel said. It has come from building a strong EHR foundation that allows the organization to continuously benefit from innovations like AI delivered through the platform.
What Other Health Systems Can Learn From This EHR Optimization Strategy
John Muir Health’s experience suggests that a disciplined EHR optimization strategy built around standard configuration, structured governance and best-practice adoption can position health systems to absorb new AI capabilities more smoothly than a heavily customized environment would allow. As AI-driven documentation tools continue to mature, this kind of foundational approach may become an increasingly important differentiator for health systems evaluating their own EHR roadmaps.
