Search found 24 items
This project will develop and evaluate the impact of the Prevent Diabetes Mellitus Clinical Decision Support on clinical outcomes, healthcare process measures, and associated costs.
This research will explore whether providing clinicians with contextual information at the point of care through the use of clinical decision support can reduce contextual errors, improve patient healthcare outcomes, and reduce misuse and overuse of medical services.
The project will develop and test a large set of alerts at two large health systems to demonstrate that alerts can help prevent wrong-drug and wrong-patient errors and improve the completeness of the problem list.
This research prospectively evaluated a machine learning algorithm that identifies candidates for neurologic surgery to control epilepsy.
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 developed, implemented, and evaluated a program that includes clinical decision support to improve diagnosis of hypertension in children.
This study assessed the usability and impact of inpatient portals on patient experience, engagement, and perceptions of care.
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 established the Center for Pediatric Practice-Based Research and Learning to develop evidence-based practices and improve child health outcomes.
This project developed an emergency care data registry for pediatric patients using electronic health records and assessed change in benchmarks for quality care measures.