Academic Medical Center
This project will study the usability of electronic health records (EHRs) by cardiac care physicians and nurses to develop a set of best practices in EHR design to inform vendors of the wants and needs of clinical providers.
This study examined clinical decision task complexity to guide the design of innovative clinical decision support to for high-level reasoning in complex decision tasks.
This project studied the influence of social networks on technology implementation and found that clinicians’ networks influence beliefs and use of the electronic medical records.
This project developed a decision making tool for patients with asymptomatic carotid stenosis and concluded that it was feasible to implement in clinical practice.
This project assessed and made recommendations about draft Stage 3 Meaningful Use objectives in the areas of care coordination and patient and family engagement.
This project evaluated select Stage 3 Meaningful Use criteria in the Patient and Family Engagement, Care Coordination, and Interoperability domains and developed recommendations to improve them and increase their value to hospitals and practices implementing them.
This project informed Stage 3 Meaningful Use requirements by evaluating metrics related to identification of delirium in real time and improving accuracy of the problem list, thus potentially improving care for patients with delirium.
Women have unique information needs during their pregnancies, ranging from medical questions about pregnancy to logistical concerns about hospital policies. This project is designed to understand these needs, the contexts in which they occur, and the resources used.
This project developed, implemented, and assessed a patient data collection and clinician feedback system for depression care management in primary care practices, and found improvements in patient medication filling and adherence.
This project applied a human factors-based framework to understand factors associated with missed test results and found that health information technology is a key barrier to test followup.