In a wide-ranging interview, John Lee, MD, Emergency Physician, Edward Hospital Naperville; Informaticist, & Epic Consultant, outlined a disciplined approach to getting more value from Epic while preparing for an AI-enabled future. He emphasized that health systems are still leaving significant capability untapped, urged CIOs to define firm boundaries for customization, and described how consolidating instances after mergers unlocks operational and analytics gains that are otherwise difficult to realize.

Epic Usage and the Case for Foundation

Asked how deeply health systems use Epic, Lee estimated that adoption remains limited: “Most Epic organizations are probably using somewhere less than 25% of the utility of Epic.” He tied the gap to a mix of over-customization, restrictive analytics policies and uneven data governance. Foundation—Epic’s design specification for standard build—serves as a guardrail, he said, because it preserves the underlying configuration and data structures that fuel analytics, benchmarking and new features that increasingly arrive “turnkey” only when the foundation pattern is respected. He expects the platform’s AI roadmap and Cosmos data to magnify this effect by embedding model-driven insights directly into clinical workflows; to benefit, organizations must keep their builds aligned with the structures those tools assume.

He has seen how replicating legacy workflows can make early adoption feel easier yet degrade performance later. In one example from the emergency department, duplicating a proprietary chief-complaint list made it harder to use Epic’s standard protocols and comparative analytics. The remedy, he said, is not scorched-earth standardization but a smart configuration strategy: use synonyms and behind-the-scenes mapping so clinicians can search familiar terms while the system stores and reports on foundation-aligned data. That approach lowers friction for users but protects cross-system comparability and decision support.

Mergers, Consolidation, and Data Leverage

Amid ongoing consolidation, Lee said the economics of platform value become unavoidable. “If you are trying to operate across three instances of Epic, you have basically negated a huge chunk of the value of Epic.” He described the short-term pain of rebuilding as the price of long-term integration: moving from multiple instances to one reduces transactional friction, simplifies configuration, and turns analytics into a single source of insight that can drive shared protocols and operational playbooks across the enterprise.



He noted that even “clean” foundation builds at two separate organizations tend to drift over time, complicating efforts to harmonize order sets, clinical pathways and quality measures. Foundation, moreover, is a design pattern, not a prebuilt product; teams still have to build, but the specification yields normalized data and configurations that travel well. Consolidation also streamlines the data layer: rather than reconciling separate warehouses (such as parallel Kaboodle environments) and mapping metrics post hoc, a single instance supports one model of truth for outcomes tracking and compliance monitoring.

Customization Boundaries and Governance

For customization decisions, Lee argued that leaders need a consistent rationale for when to deviate from foundation, grounded in clinical and operational benefit and mindful of technical cost. “You have to know where to fight that fight and where to try to preserve as much of the Epic foundation as possible.” He encouraged CIOs and CMIOs to pair that principle with stronger operational and clinical data governance so that configuration choices serve enterprise goals, not just local convenience.

He pointed to staffing as a leverage point: physician builders and clinically fluent analysts reduce rework by translating intent into architecture and avoiding cycles of unclear tickets and misaligned des...