Clinical decision support systems (CDSSs) are thought to reduce adverse drug events (ADEs) by monitoring drug-drug interactions(DDIs). However, clinically improper or excessive alerts can result in high alert overrides. A tailored CDS service, which is appropriate for clinicians and their ordering situations, is required to increase alert acceptance. In this study, we conducted a 12-week pilot project adopting a tailed CDSS at an emergency department. The new CDSS was conducted via a stepwise integration of additional new rules. The alert status with changes in acceptance rate was analyzed. The most frequent DDI alerts were related to prescriptions of anti-inflammatory drugs. The percentages of alert overrides for each stage were 98.0%, 96.0%, 96.9%, and 98.1%, respectively. 91.5% of overridden alerts were related to discharge medications. To reduce the potential hazards of ADEs, the development of an effective customized DDI CDSS is required, via in-depth analysis on alert patterns and overridden reasons. © 2010 Springer-Verlag.
CITATION STYLE
Kam, H. J., Park, M. Y., Kim, W., Yoon, D. Y., Ahn, E. K., & Park, R. W. (2010). Knowledge integration and use-case analysis for a customized drug-drug interaction CDS service. In Communications in Computer and Information Science (Vol. 78 CCIS, pp. 46–51). https://doi.org/10.1007/978-3-642-16444-6_7
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