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This research will implement in pharmacies a patient-reported outcomes collection tool, PatientToc™, to collect data around medication adherence that can be used by pharmacists to improve adherence.
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 project will expand, implement, and evaluate the use of a cancer screening platform, the Oncology Symptom Screening Initiative (OSSI), to improve psychosocial screening of cancer patients.
This project will integrate the Computerized Adaptive Test for Mental Health into an electronic health record and evaluate the effectiveness of collecting depression symptoms with a patient portal.
This project will examine health information exchange (HIE) usage patterns, the barriers and facilitators of HIE use, and the impact of HIE use by emergency department clinicians.
This project will evaluate a computerized provider order entry (CPOE)-based function—medication voiding—that can be used to prospectively identify and document medication ordering errors.
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.
This project will enhance novel algorithms for matching patient health information across data sources, implement them, and evaluate their accuracy.
The goal of this project is to design and test an information technology called Power to the People to support self-care management among older patients with chronic heart failure.
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.