Quantifying Electronic Medical Record Usability to Improve Clinical Workflow

Veterans Medical Research Fdn/San Diego, San Diego CA

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Linked publications & trials

Abstract

DESCRIPTION (provided by applicant): We propose to conduct a prospective clinical study to understand how clinical work is actually done in outpatient clinics that use EMRs, and to explore associations between EMR usage, workflow, physician-patient communication, cognitive load, and user satisfaction. The proposed study will use an observational prospective design consistent with the knowledge discovery goals of the project. The study will be conducted in the outpatient clinics at VA San Diego and at University of California San Diego (UCSD) Healthcare System. Within the outpatient arena, we will study 2 use case scenarios (primary care clinics and medical specialty clinics). We propose to recruit and study 32 providers and 192 patients (6 unique patient visits/provider) across 2 sites. A multifaceted and complementary data collection schema is proposed to study EMR usability, workflow, communication, and cognitive load. EMR user-interface activity, including mouse-click events and screen activity, will be logged via usability software. Videos will be temporally coded for communication and workflow behaviors. Surveys will be used to measure satisfaction and cognitive load. The analysis consists of development of a range of process-level quantitative measures and indicators of EMR usage, clinical workflow, and provider-patient communication. We will link data on EMR use and clinical work to develop composite models of EMR usability, clinical workflow, and provider's cognitive load and will explore associations between these indicators across study sites (UCSD and VA), provider types (Primary and Specialty), patient visits, and EMRs (CPRS and EPIC) while accounting for important covariates. The present study will provide a comprehensive assessment of usability, workflow, communication, and cognitive load. This critical knowledge can inform the development of the next generation of user-centered EMRs, hence improving clinical performance and effectiveness.