Grant: Doctoral Award - Frederick Banting and Charles Best Canada Graduate Scholarships

This study aims to identify potentially modifiable patient and system-level factors associated with recurrent adverse drug events in emergency department patients, and to develop an automated tool to identify high-risk patients. To do this, high-quality, prospective emergency department data will be linked with administrative health data to investigate the rate of unintended re-exposure to previously harmful medications. Identifying potentially modifiable factors associated with adverse drug events will provide guidance in the development of effective, evidence-based strategies for adverse drug event prevention. We will use these factors to develop a clinical decision rule that health care personnel can use to identify patients at high-risk for these events. These high-risk patients can then be fast-tracked for medication review by clinical pharmacists, thereby targeting limited pharmacist resources towards those who will benefit most. Ultimately, we aim to automate this clinical decision rule using electronic health records. This will allow for instant and accurate identification of emergency department patients requiring clinical pharmacist consultation as they present to hospital. This computerized tool will help emergency departments meet the new Accreditation Canada requirements for adverse drug event identification. It will reduce workload for health care personnel (e.g., triage nurses currently applying the tool), increase efficiency within the health care system, and improve patient safety.