Across the United States, health systems that completed their Epic implementations years ago are now confronting a quieter but more persistent challenge: the system is live, but it is not performing the way it should. Workflows are slower than expected. Clinicians are working around the software rather than through it. Data that should flow between departments gets stuck at handoff points. Reporting takes longer than it should, and staff are spending time on documentation tasks that the system was supposed to simplify.
This is not an uncommon situation. Epic is a complex platform, and going live is only the beginning of a longer operational journey. The optimization phase—refining configuration, improving workflows, integrating connected systems, and training staff to use available tools correctly—is where much of the real value is either captured or lost. In 2025, with interoperability mandates tightening, staffing pressures ongoing, and patient volume demands increasing, health system leaders cannot afford to treat optimization as a background project. It requires structured attention, clear ownership, and a realistic assessment of where the system currently stands versus where it needs to be.
This checklist is built for operational and clinical informatics leaders who are either beginning an optimization effort or reassessing one already underway. It covers the primary readiness areas that determine whether an optimization initiative will deliver lasting improvements or stall under competing priorities.
Understanding What Epic Optimization Integration Actually Involves
Epic optimization integration refers to the ongoing process of refining how Epic functions within a health system’s broader clinical and operational environment. This includes adjusting build configurations, resolving workflow inefficiencies, connecting Epic more effectively with ancillary systems, and ensuring that data moves accurately between Epic and other platforms—such as laboratory systems, imaging platforms, patient communication tools, scheduling applications, and billing infrastructure. It is distinct from initial implementation in that it assumes the system is already live and that the work is now about performance, fit, and connectivity rather than setup.
For health systems evaluating where they stand, engaging with a structured program around epic optimization integration often reveals that problems assumed to be user-related are actually configuration issues, and that workarounds staff have developed over time are masking deeper system gaps. Identifying these gaps requires both technical knowledge of the Epic environment and operational understanding of how clinical workflows actually function day to day.
The distinction between optimization and re-implementation matters here. Optimization does not mean rebuilding from scratch. It means applying targeted improvements to what already exists—adjusting build, improving interface connections, updating preference lists, refining order sets, and closing gaps between how the system was configured and how the organization now operates.
Why Optimization Gaps Accumulate Over Time
Health systems that implemented Epic several years ago often did so under significant time pressure, with go-live deadlines that compressed the configuration and testing work. Decisions made during implementation—on order set design, workflow routing, interface setup, and reporting logic—were reasonable at the time but reflected the organization as it existed then, not as it operates now. Staff roles change. Service lines expand. Regulatory requirements shift. Merger and acquisition activity brings in new facilities with different workflows. All of these changes create drift between how the system is configured and how the organization actually functions.
In addition, Epic itself continues to evolve. Major version updates introduce new tools and functionality that existing customers often underuse because they were not implemented at go-live and no one has since been assigned to evaluate their applicability. Functionality that could meaningfully reduce clinical burden—such as advanced decision support tools, updated documentation templates, or improved patient matching logic—sits unused not because it lacks value, but because the optimization effort to activate and train on it has not been prioritized.
The Readiness Checklist: Governance and Ownership
Optimization initiatives fail most often not because of technical complexity, but because of unclear ownership and inconsistent governance. Before any configuration work begins, a health system needs to confirm that it has clear answers to a set of foundational governance questions. These questions are not bureaucratic formalities. They determine whether decisions get made, whether conflicts between departments get resolved, and whether changes actually reach the point of implementation.
Establishing Decision-Making Authority
Every optimization effort generates decisions that affect multiple stakeholders. A change to an order set affects physicians, pharmacists, and clinical documentation staff differently. A modification to a scheduling workflow affects front desk staff, clinical coordinators, and revenue cycle teams simultaneously. Without a defined governance body that has authority to make and finalize these decisions, optimization work stalls at the point of disagreement and never recovers momentum.
The governance structure does not need to be large, but it needs to include both clinical and operational representation, have an identified executive sponsor, meet on a regular cadence, and have a documented process for escalating unresolved issues. Health systems that treat governance as a formality tend to find their optimization projects stretched across years with minimal measurable progress.
Assigning Technical and Clinical Ownership
For each area of the Epic environment being optimized—whether that is inpatient clinical documentation, ambulatory scheduling, revenue cycle workflows, or interface management—there should be a named technical owner on the informatics or IT side and a named clinical or operational owner on the business side. These two individuals are jointly accountable for outcomes in their domain. When one exists without the other, the work tends to either lose clinical relevance or stall in technical review without forward movement.
The Readiness Checklist: Workflow Assessment Before Configuration Changes
One of the most consistent mistakes in optimization work is moving directly to configuration changes without first conducting a structured workflow assessment. Configuration changes that are made without a clear understanding of the current workflow often solve a surface problem while creating new ones downstream. Clinicians find that a change intended to reduce their documentation burden has altered a data element that reporting depends on, or that a revised order set has removed a medication option that a specific patient population requires.
Mapping Current-State Workflows Before Proposing Changes
Current-state mapping does not require elaborate process documentation. It requires honest conversations with the staff who use the system daily, observation of how workflows actually run as opposed to how they were designed to run, and a record of where the system creates friction. The U.S. Department of Health and Human Services has noted in its health IT guidance that workflow integration failures remain among the most common contributors to implementation dissatisfaction, even in systems that have been live for multiple years.
Common friction points to document during current-state assessment include:
• Steps in the clinical workflow where staff consistently leave Epic to consult a separate system, spreadsheet, or paper document
• Order sets or documentation templates that clinicians routinely bypass in favor of free-text entries
• Handoff points between departments where information loss or duplication occurs regularly
• Reporting requests that cannot be fulfilled using existing Epic data structures without manual extraction
• Patient-facing communication workflows that rely on manual intervention where automation is technically available
The Readiness Checklist: Interface and Integration Stability
Epic does not operate in isolation. In most health systems, it is connected to a range of external systems—laboratory information systems, radiology platforms, scheduling tools, patient portals, billing clearinghouses, and increasingly, third-party analytics and population health applications. The stability and accuracy of these connections determines whether clinicians and administrators can trust the data they see in Epic, and whether the system can serve as a reliable operational record rather than just a documentation platform.
Auditing Existing Interfaces for Accuracy and Timeliness
Interfaces that were built at go-live and never formally reassessed are a common source of data quality problems. A laboratory interface that was mapped correctly three years ago may have encountered changes on either side—a system upgrade at the lab, a reconfiguration of Epic result routing, or a change in ordering nomenclature—that introduced silent errors into result delivery. These errors often go undetected because results still appear in Epic; it is only when a clinician notices an unexpected pattern, or when an audit is conducted, that the discrepancy surfaces.
An interface audit as part of an epic optimization integration effort should examine message volume trends, error logs, acknowledgment failures, and any fields that are inconsistently populated. It should also include a review of interfaces that were planned at go-live but never fully activated, which is more common than most health systems expect.
Planning for New Integration Requirements
Beyond existing interfaces, health systems need to assess what new integration needs have emerged since go-live. This includes connections to telehealth platforms, remote patient monitoring tools, care management applications, and any newly acquired facilities or practices that need to be brought into the Epic environment. Each of these represents a discrete integration project with its own testing, validation, and training requirements.
The Readiness Checklist: Staff Competency and Adoption
Technical configuration improvements deliver limited value if staff do not know how to use the updated system effectively. Optimization efforts that focus exclusively on build changes without accompanying training and communication rarely achieve sustained workflow improvement. Staff who were trained at go-live several years ago may have developed habits that made sense under the original configuration but are counterproductive under the revised one. New staff hired after go-live may have received minimal formal training and rely heavily on informal guidance from peers whose practices are inconsistent.
Identifying Competency Gaps Through Usage Data
Epic’s reporting tools provide visibility into how the system is actually being used—which features are being accessed, which order sets are being completed versus abandoned, which documentation tools are being bypassed. This usage data is a practical diagnostic tool for identifying where staff competency gaps are largest and where targeted training would have the most impact. It also helps distinguish between adoption problems, where staff know how to use a feature but choose not to, and knowledge gaps, where they genuinely do not know the functionality exists or how to use it correctly.
Closing Considerations for Health System Leaders
Epic optimization integration in 2025 is not a one-time project with a defined endpoint. It is an ongoing operational responsibility that reflects how seriously a health system takes the performance of its core clinical and administrative infrastructure. The checklist areas covered here—governance and ownership, workflow assessment, interface stability, and staff competency—are not exhaustive, but they represent the foundational readiness conditions without which more advanced optimization work is unlikely to produce durable results.
Health systems that approach this work with clarity about what they currently have, where the gaps are, and who is responsible for closing them are in a substantially stronger position than those that treat optimization as a vendor relationship issue or an IT department backlog item. The platform is capable. The question is whether the organization around it is structured to realize that capability consistently and at scale.
Leaders who are beginning this process should resist the pressure to move quickly into configuration changes before the foundational work is done. Taking time to assess governance structures, map current workflows honestly, audit interface accuracy, and evaluate staff adoption patterns is not a delay in the optimization effort—it is the optimization effort, done in the order that actually works.
