PT - JOURNAL ARTICLE AU - T Morimoto AU - T K Gandhi AU - A C Seger AU - T C Hsieh AU - D W Bates TI - Adverse drug events and medication errors: detection and classification methods AID - 10.1136/qshc.2004.010611 DP - 2004 Aug 01 TA - Quality and Safety in Health Care PG - 306--314 VI - 13 IP - 4 4099 - http://qualitysafety.bmj.com/content/13/4/306.short 4100 - http://qualitysafety.bmj.com/content/13/4/306.full SO - Qual Saf Health Care2004 Aug 01; 13 AB - Investigating the incidence, type, and preventability of adverse drug events (ADEs) and medication errors is crucial to improving the quality of health care delivery. ADEs, potential ADEs, and medication errors can be collected by extraction from practice data, solicitation of incidents from health professionals, and patient surveys. Practice data include charts, laboratory, prescription data, and administrative databases, and can be reviewed manually or screened by computer systems to identify signals. Research nurses, pharmacists, or research assistants review these signals, and those that are likely to represent an ADE or medication error are presented to reviewers who independently categorize them into ADEs, potential ADEs, medication errors, or exclusions. These incidents are also classified according to preventability, ameliorability, disability, severity, stage, and responsible person. These classifications, as well as the initial selection of incidents, have been evaluated for agreement between reviewers and the level of agreement found ranged from satisfactory to excellent (Îș  =  0.32–0.98). The method of ADE and medication error detection and classification described is feasible and has good reliability. It can be used in various clinical settings to measure and improve medication safety.