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This project will apply machine learning against a large data set to develop a model to both understand and predict surgical cancellations on individual pediatric patients at two pediatric surgical sites.
This project assessed quality measurement performance and electronic health record (EHR) implementation and found that EHR reminders were associated with improved performance.
This project synthesized what was learned from the Practice Partner Research Network - Translating Research into Practice (PPRNet-TRIP) project regarding how to use health information technology to improve quality in primary care practices.
The project successfully developed a set of medication safety measures relevant for primary care and incorporated these measures in quarterly performance reports sent to participating practices.
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.