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 will further scale clinical decision support aimed at preventing the prescription of inappropriate medications to older adults upon discharge from the emergency department.
This research will examine the evidence around the value of order sets, while uncovering clinician perceptions that hinder their efficient use.
This project will use mobile health technology to collect patient-reported outcomes after dental procedures to optimize the quality of acute post-operative dental pain management.
The research team developed and evaluated a natural language processing allergy module that was used to study different types of allergies in an electronic health record.
This project will formulate evidence-based recommendations for clinical decision support used by community pharmacist delivering medication therapy management. The goal is to reduce medication-related problems and improve health outcomes for chronically ill patients.
This project will implement and evaluate a “smart” pillbox given to patients in order to understand its ability to minimize discrepancies in prescribed regimens and to improve patients’ medication adherence after hospital discharge.
This project evaluated the Pharmaceutical Safety Tracking (PhaST) system, which monitors medication safety in children and adolescents who are taking antidepressants.
This project investigated the feasibility and impact of novel approaches to clinician decision support in multidisciplinary ambulatory care, emphasizing high-risk transitions of care.
This project demonstrated the ability of an interoperable health information exchange and an electronic health record to provide useful quality and safety measures for the vulnerable populations served by two community health center clinics.