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This research will create patient-centered, interoperable, shareable clinical decision support tools that will support providers and patients in making patient-centered decisions about management of hypertension.
This research prospectively evaluated a machine learning algorithm that identifies candidates for neurologic surgery to control epilepsy.
This project evaluated the impact of an integrated care coordination information system (ICCIS) on the outcomes and satisfaction of patients with chronic and complex illnesses.
This project investigated the feasibility and impact of novel approaches to clinician decision support in multidisciplinary ambulatory care, emphasizing high-risk transitions of 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.