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 study will develop, evaluate, and disseminate a multicomponent intervention including a mobile health application and digital navigator training to support safe care transitions for patients with multiple chronic conditions.
This research will use digital health tools leveraging patient-reported outcomes and data from electronic health records to engage individuals with multiple chronic conditions to improve understanding of individualized risk of adverse events during care transitions.
This research will examine the factors affecting cancer patients’ use of an electronic patient safety event reporting system to communicate adverse medication-related events to their care team.
This research will evaluate a novel, technology-enabled intervention that will determine the impact of bedside shift reporting and hourly rounding on nurse-sensitive patient outcomes.
This research developed a publicly available cost-effectiveness model for programs combining pharmacogenomics testing with clinical decision support alerts, so that decision makers may more robustly evaluate whether or not to implement such a program.
This research will evaluate the safety, usability, and impact of an e-prescribing standard on adverse drug events related to erroneously dispensed medications.
This research developed DDInteract, a patient-facing shared decision making (SDM) tool that uses interactive decision dashboards to graphically communicate risks and decision options, supporting SDM for patients and providers regarding drug-drug interactions.
This research explores the effectiveness of an e-prescribing tool to electronically communicate medication discontinuation orders between electronic health records and pharmacies.
This project proposes a novel proactive system to reduce alert burden and thereby increase attention to situations in which patient safety is at risk.
