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SOO-HEE HWANG, B.S.PHARM,. is Researcher, Center for Interoperable Electronic Health Record, Seoul, Korea. SUKHYANG LEE, PHARM.D., is Associate Professor, Clinical Pharmacy, Graduate School of Clinical Pharmacy, Sookmyung Women’s University, Seoul, Korea. HYUN-KYUNG KOO, M.S., is Researcher, Center for Interoperable Electronic Health Record. YOON KIM, M.S., PH.D., is Associate Professor, Department of Health Policy and Management; and Director, Institute of Health Policy and Management, Seoul National University College of Medicine, Seoul; and Director, Center for Interoperable Electronic Health Record.

Address correspondence to Dr. Kim at the Department of Health Policy and Management, Seoul National University College of Medicine, 28 Yeongeon-Dong, Jongno-Gu, Seoul, 110-799, Republic of Korea (yoonkim{at}snu.ac.kr).

Purpose. The performance of a computer-based adverse-drug-event (ADE) monitor is evaluated, and the characteristics of ADEs detected and undetected by the monitor are compared. Methods. A retrospective analysis was conducted to identify ADEs using pre-defined ADE alerts that were recognized by a computer-based ADE monitor in a 1300-bed, tertiary care, teaching hospital in Seoul, Korea. A subsequent chart review was conducted by a pharmacist to confirm the ADEs and identify ADEs unrecognized by the monitor. The performance of the monitor was evaluated for its sensitivity and positive predictive value in detecting an ADE. The differences in characteristics of ADEs were compared between computer-recognized ADEs and computer-unrecognized ADEs for severity, causality, preventability, associated clinical manifestations, and types of ADEs. Results. During a one-month period, a total of 598 patients from two intensive care units and five general wards were monitored to identify ADEs. The computer-based ADE monitor identified 148 ADEs, and the chart review identified 39 computer-unrecognized ADEs. The sensitivity of the computer-based ADE monitor was 79% (148 of 187). The computer-recognized ADEs were more severe than computer-unrecognized ADEs, but there were no statistically significant differences in the causality, preventability, and types of ADEs. The positive predictive value of the computer monitor was 21% (148 of 718). Conclusion. The computer-based ADE monitor successfully identified most of the ADEs and almost all of the severe ADEs that occurred in the hospitalized patients. However, the accuracy of the computer-based ADE monitor needs to be improved. Index terms: Computers; Errors, medication; Hospitals; Quality assurance