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The project is adapting and scaling a technology-enabled practice model for asthma in a primary care setting, then evaluating its impact on patient-reported quality of life and utilization.
This project will determine the impact of using telemedicine to serve children with special healthcare needs living in rural and underserved communities.
This research prospectively evaluated a machine learning algorithm that identifies candidates for neurologic surgery to control epilepsy.
Created an information management environment that integrated patient care data, standardized practice variation and use of best practices, and supported the delivery of a seamless continuum of patient care throughout the health system through CPOE.
Evaluated the effects of staggered installation of an Epic health IT system that includes an EMR with provider order entry and clinical decision support in primary care settings on quality, safety, and resource use within a large integrated delivery system on cohort of 780,000 members with chronic illnesses.