Evaluation and overview of the National Electronic Injury Surveillance System-Cooperative Adverse Drug Event Surveillance Project (NEISS-CADES).

2007 
Background: Adverse drug events (ADEs) are an important cause of patient injury. Although most medications are prescribed and used in the outpatient setting, prevention efforts focus on the inpatient setting, partly because of limited data on outpatient events. We describe and evaluate a new system for surveillance of outpatient ADEs treated in hospital emergency departments (EDs). Methods: We used guidelines for evaluating public health surveillance systems, developed by the Centers for Disease Control and Prevention, to assess the performance of the National Electronic Injury Surveillance System-Cooperative Adverse Drug Event Surveillance project (NEISS-CADES) from January 1, 2004 through December 31, 2004. Results: NEISS-CADES is a nationally representative surveillance system that identifies ADEs using ED clinical records. Of 10,383 reports in 2004, 100% listed patient age, sex, and disposition; 98% listed the implicated drugs. A 6-hospital evaluation of data quality, completeness, and other system attributes showed that NEISS-CADES data accurately reflected clinical records with respect to patient age and sex (100%), primary diagnosis (93%), implicated drugs (93%), primary treatments (80%), and diagnostic testing (61%). Sensitivity of case identification was estimated to be at least 0.33; estimated positive predictive value was 0.92. Data collection does not require additional work by clinical staff and has been well accepted by participating institutions. Conclusions: NEISS-CADES provides detailed and timely information on outpatient ADEs treated in EDs and identifies specific drugs and circumstances associated with these injuries. Findings from NEISS-CADES can help design and prioritize patient safety interventions for outpatient ADEs.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    30
    References
    61
    Citations
    NaN
    KQI
    []