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Search found 4 items
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 evaluated the impact of an electronic health record on the quality of diabetes care as measured by compliance with recommended processes of care and patient outcome measures.
The findings of this study demonstrated that electronic health record-based trigger methods can enable more meaningful measurement and surveillance of diagnostic errors in primary care.
Evaluated the effects of a Web portal-based patient empowerment program and EMR system on quality of care, patient safety, and utilization for patients with diabetes and physicians in primary care practices.