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This project will examine the impact of implementing the e-Prescribing standard CancelRx on outpatient medication discrepancies and on clinic and pharmacy workflows.
The project will develop a patient portal intervention to increase patient activation and promote collaborative decision making for patients with depression.
This study will test the hypothesis that low-income, disadvantaged patients can provide high-quality patient-generated health data and patient-reported outcomes through commercial technologies, and that these data can be used to improve healthcare quality and delivery.
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 design natural language processing algorithms to extract data from free text notes on autism spectrum disorders in electronic health records, and demonstrate the feasibility and usefulness of this approach.
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 project will develop a method to use video captured electronic health record interactions to analyze the context around medication errors, identify design elements that contributed to the errors, and make design recommendations to mitigate those errors.
The goal of this project is to develop and evaluate an air traffic control-like command center for operating rooms.
This project will develop and evaluate an electronic health record-embedded clinical decision support tool that draws upon the strength of analytical and naturalistic decision-making to optimize the use of blood cultures in critically ill children.
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.