Jupiter Medical Center in North Palm Beach, Florida, went live with its Epic electronic health record on September 1, 2024. Since then, the hospital’s chief information officer, Kevin Olson, has been working to optimize the EHR to best meet the hospital’s needs.
He’s not done yet – nor will he ever be.
“EHR optimization should be seen as an ongoing initiative rather than a one-time project,” Olson explained. “Many health systems implement an EHR and optimize it at a specified time period, assuming the work is complete. However, workflows, clinician needs and patient expectations continually evolve. And the EHR should evolve with them.”
Optimization best practices
Olson offers five best practices to gain the most value from EHR optimization projects:
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Engage clinical and operational stakeholders early and often. Collaboration between IT and clinical leadership is key.
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Ensure each EHR optimization initiative aligns with the organization’s broader institutional goals (for example, improve patient outcomes, reduce administrative burden or strengthen financial sustainability).
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Use a regular and phased approach with measurable milestones and consistent feedback to ensure EHR optimizations provide real value rather than becoming a purely technical exercise.
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Approach all optimization projects with future interoperability requirements and data governance in mind. A well-optimized EHR should function smoothly within its own environment while integrating with external data sources for population health initiatives, telehealth or patient engagement platforms.
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Take a long-term approach to EHR management, balancing operational needs with nascent technology solutions and positioning the organization for sustained success.
“Physician alignment determines the success of any EHR optimization project,” Olson said. “If physicians find the changes to be inefficient or out of sync with workflows, frustration leads to burnout and workarounds that compromise data integrity and patient safety.
“Alignment begins with direct physician involvement,” he continued. “This ensures they have a voice in process and system improvements and any new changes reflect their needs. When they see meaningful enhancements based on their input, adoption increases.”
One effective strategy involves clinical champions – physicians who bridge the gap between IT and their peers, translating technical updates into practical terms, which helps foster trust and encourage adoption, he added.
Supporting caregivers with training
“Training also plays a critical role,” he noted. “Too often, new optimizations launch with minimal education, leaving physicians to navigate changes alone. Personalized training tailored to different specialties verifies they fully use system capabilities.
“Optimization efforts must also ease administrative burdens,” he continued. “AI-assisted documentation, well-structured order sets and enhanced decision support tools free up more time for patient care. The more the EHR supports physicians rather than complicating their work, the more likely they are to embrace change.”
Nursing and other provider efficiencies also are critical for an EHR optimization project.
“The entire organization wins when nurses and other clinicians experience new technology capabilities that enhance their ability to deliver care,” Olson said. “And since these frontline providers rely on the EHR throughout their shifts, efficiency remains a key priority.
“Optimizing nursing workflows within the EHR should include simplified charting, stronger care team communication and decision support tools that assist rather than overwhelm,” he continued. “Real-time feedback from these clinicians helps identify friction points.”
It’s not the technology
The industry has seen that post-optimization inefficiencies often stem from how the EHR changes are configured rather than the technology itself, Olson said. He offers two examples of value-added optimization:
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Automating routine tasks like vital sign documentation, medication administration tracking and shift handoff notes
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Integrating bedside tools such as digital whiteboards and mobile documentation options
“Finally, education and usability testing must be priorities before any changes go live,” he recommended. “Nurses often receive last-minute system updates with little preparation, which can cause frustration and lower adoption. Involve them early and offer training tailored to their roles to deliver real benefits rather than introduce new challenges.”
AI can play a role in EHR optimizations.
“AI can complement EHR optimizations,” Olson said. “Education and understanding of the use of AI is a key first step to ensure clinicians understand how workflows associated with the technology assist them. By providing background in industry experiences, connecting them to peers, creating an understanding of inherent risk, and explaining the targeted outcomes, we must ensure they have a voice in the implementation and change methodology.
“One of the most immediate applications is embedding AI-assisted clinical documentation into an EHR upgrade,” he continued. “These technologies generate summaries, suggest relevant codes and transcribe patient encounters in real time. This not only saves clinicians time but also improves accuracy and completeness, which is essential for both patient care and revenue cycle management. AI-assisted clinical documentation continues to improve.”
Beyond documentation, AI-driven decision support strengthens the EHR by delivering real-time, evidence-based recommendations tailored to individual patients, he added.
Don’t disrupt workflows
“However, balance is crucial – too many alerts or unnecessary recommendations disrupt workflows rather than enhance them,” he explained. “AI interventions should be meaningful, intuitive and embedded into existing processes rather than functioning as a separate layer of complexity.
“From an operational standpoint, AI optimizes resource allocation by being able to predict patient volumes, flag staffing shortages and identify trends in patient outcomes,” he continued. “The most effective AI implementations align with broader healthcare goals, such as clinician satisfaction, patient outcomes and financial performance. However, AI relies on data quality, so strong data governance and interoperability remain essential.”
On that note, C-suite executives and other IT leaders must deal with the issue of governance during an EHR optimization project.
“Strong governance ensures EHR optimization efforts remain strategic, sustainable and aligned with organizational priorities,” said Olson. “Without clear oversight, projects can fragment, with different departments focused on conflicting changes that reduce efficiency rather than improve it. An effective governance model unites IT, clinical leadership and operational stakeholders under a structured framework for decision making, prioritization and accountability.
“I suggest a multidisciplinary governance committee to oversee optimization efforts – this includes representatives from physicians, nurses, senior leadership, IT compliance, cyber and revenue cycle teams,” he continued. “This group evaluates proposed changes to confirm they align with patient outcomes and satisfaction, physician satisfaction and overarching organization imperatives.”
A data-driven approach, based on key performance indicators, helps organizations assess the impact of optimizations and adjust strategies when needed, he advised.
The ongoing process of governance
“Finally, governance – like EHR optimization – is an ongoing process,” Olson concluded. “Regular review cycles, clinician feedback mechanisms and iterative improvements ensure the EHR remains a dynamic tool that supports healthcare delivery. A culture of collaboration, transparency and accountability helps executives lead EHR optimization efforts that deliver lasting benefits without unintended disruptions.”
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