This research will use artificial intelligence and machine learning to create prediction tools integrated into visualization dashboards to guide critical care pharmacists in preventing adverse drug events.
This research will study the effectiveness of a virtual in-home program designed to reduce hospital readmissions among COPD patients post-hospitalization.
This research aims to determine the effectiveness of a program designed to reduce medication-related issues among patients during the hospital-to-skilled nursing facility transition.
This research developed strategies to optimize CancelRx implementation and measured its impact on dispensing errors and patient outcomes.
This study tested the feasibility, acceptability, and usability of a novel telemedicine application that incorporates a virtual pharmacist into the delivery of patient-centered palliative care.
This research explores the effectiveness of an e-prescribing tool to electronically communicate medication discontinuation orders between electronic health records and pharmacies.
The research examined the usability of medication assistive technologies and how these usability issues can impact patient safety and provider burden.
This research developed algorithms for eight key drug-drug interactions (DDI) to inform the building of contextualized DDI alerts; developed and tested three DDI-clinical decision support (CDS) apps; and disseminated the information and algorithms via the DDI-CDS.org website, webinars, and publications.
This study evaluated the effectiveness of displaying patient photos and alerts in the electronic health record for preventing wrong-patient order errors, finding rigorous evidence that these interventions significantly decrease such errors.
This study showed the feasibility and value of creating a methodology and process for a health information technology black box to inform electronic health record design and usability.
