Abstract
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.
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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: Kim, Th., Stoica, A., Chang, RS. (eds) Security-Enriched Urban Computing and Smart Grid. SUComS 2010. Communications in Computer and Information Science, vol 78. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16444-6_7
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DOI: https://doi.org/10.1007/978-3-642-16444-6_7
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