Optimizing the Electronic Health Record for Cardiac Care

University Of Nebraska Medical Center, Omaha NE

Investigators

Linked publications & trials

Abstract

DESCRIPTION (provided by applicant): The electronic health record (EHR) promises to revolutionize the practice of medicine. Advocates tout its ability to reduce costs and improve health by standardized practice and reducing medical errors. However, physician adoption has been slow. The Institute of Medicine and the Leapfrog Group cite physician adoption as a significant barrier. There is growing evidence, however, that adoption has been delayed by the negative impact of EHRs on workflow, communications and patient care. We believe substantial improvement in the health care provider's perception of usability can be achieved by creating realistic clinical scenarios, incorporating best practices of Human-Computer Interactions (HCI) design and partnering providers and experts together to build usable, vendor-neutral EHR models. We have three specific aims: 1) Determine the usability of the electronic health record as measured by provider-defined usability (efficiency, effectiveness and satisfaction). We will use cardiovascular clinical scenarios and trained simulated patients (actors) to test existing installed electronic health records. 2) Using value-based software engineering principles and agile development methods link providers with clinical content and HCI experts to build and test wireframe models of desired EHR functionality. 3) Using information obtained through Specific Aims 1 and 2 synthesize the characteristics of users' preferences (clinical setting, clinical expertise and learning style, etc.) and demographics (age, gender, race/ethnicity, and comfort with technology) to propose a set of best practice designs to guide EHR developers. This grant can significantly impact future EHR systems by providing a framework and reliable methods to measure the usability of the EHR by nurses and physicians caring for the patient. Although using cardiovascular clinical scenarios we believe these results will be generalizable to other health care teams.