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This project compared high and low intensity support for implementation of clinical decision support (CDS) and found that the low intensity support may be sufficient to help community health centers improve their use of CDS over a relatively short time period.
This project refined a set of asthma care quality measures and developed and validated the use of an automated method using natural language processing to utilize the measures.
The goal of this project was to promote increased adherence to evidence-based pharmacotherapy guidelines through both traditional clinic-based and newer models of care.
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.
Implemented and evaluated a community-wide EHR for health care providers in pediatric primary care, school health, specialty care, and emergency medicine who provide care for inner city children with asthma.