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A Structured Framework for Electronic Health Record Optimization: The EASY Program
Obeid M Shafi1,2, Daniel Liu1,2, James S Magee3
1University of Arkansas for Medical Sciences, Little Rock, Arkansas, United States.
None:
Despite widespread adoption, electronic health records (EHRs) continue to present persistent challenges related to usability, workflow inefficiencies, and clinician burden. Structured EHR optimization programs that address these issues in a scalable and replicable manner remain limited in the literature.This study aimed to describe the development, implementation, and outcomes of the EASY (Eliminate, Automate, Standardize, and Simplify, Y'all) EHR Optimization program-designed to enhance EHR usability, provider satisfaction, and workflow efficiency through a multidisciplinary, data-informed approach.EASY employs a structured three-phase model (people, process, technology), integrating user-centered design principles and institutional tools such as clinician observations, GROSS (Getting Rid of Stupid Stuff) surveys, Epic EHR analytics (Signal and Tune-Up reports), and SOAARR (Subjective, Objective, Artifacts, Assessment, Recommendations, Results) documentation. The program evolved to adopt a sprint-based implementation cycle (4-6 weeks) to maintain engagement, reduce scope creep, and support iterative improvements.EASY yielded both user-reported and analytic benefits. Providers described improved satisfaction, greater alignment with clinical workflows, and enhanced transparency through structured communication. Signal data demonstrated measurable improvements in documentation efficiency, ordering practices, and reduced time spent in specific EHR functions. Targeted usability enhancements, ranging from quick wins to complex builds, were data-informed and guided by clinician feedback. The EASY program reflects best practices in EHR optimization, aligning with literature that emphasizes provider engagement, data-informed design and decision-making, and multidisciplinary collaboration. Its modular design and analytic rigor support adaptability across varied clinical settings, though implementation success is contingent on sustained provider involvement and informatics infrastructure.EASY offers a practical, scalable model for structured EHR optimization. It provides a replicable framework and actionable strategies for informatics teams seeking to improve EHR usability, reduce burden, and foster provider-centered innovation.
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