Duke University Health System uses computerized adverse drug event surveillance as an integral part of medication safety at 2 community hospitals and an academic medical center. This information must be swiftly communicated to organizational patient safety stakeholders to find opportunities to improve patient care; however, this process is encumbered by highly manual methods of preparing the data.
Following the examples of other industries, we deployed a business intelligence tool to provide dynamic safety reports on adverse drug events. Once data were migrated into the health system data warehouse, we developed census-adjusted reports with user-driven prompts. Drill down functionality enables navigation from aggregate trends to event details by clicking report graphics. Reports can be accessed by patient safety leadership either through an existing safety reporting portal or the health system performance improvement Web site.
Elaborate prompt screens allow many varieties of reports to be created quickly by patient safety personnel without consultation with the research analyst. The reduction in research analyst workload because of business intelligence implementation made this individual available to additional patient safety projects thereby leveraging their talents more effectively.
Dedicated liaisons are essential to ensure clear communication between clinical and technical staff throughout the development life cycle. Design and development of the business intelligence model for adverse drug event data must reflect the eccentricities of the operational system, especially as new areas of emphasis evolve. Future usability studies examining the data presentation and access model are needed.
From the *Duke University Health System; †Duke University School of Medicine; and ‡Department of Pediatrics, Duke University School of Medicine, Durham, NC.
Correspondence: Jeffrey Ferranti MD, MS, Duke Health Technology Solutions, 2424 Erwin Rd, DUMC 2718, Durham, North Carolina 27705 (e-mail: email@example.com).
This study was supported by grant no. 5UC1HS014882-03 from the Agency for Healthcare Research and Quality, National Institute of Health.
The authors do not have any competing or conflicting financial interests.