Consensus Recommendations for Systematic Evaluation of Drug–Drug Interaction Evidence for Clinical Decision Support

Drug safety(2015)

引用 99|浏览19
暂无评分
摘要
Background Healthcare organizations, compendia, and drug knowledgebase vendors use varying methods to evaluate and synthesize evidence on drug–drug interactions (DDIs). This situation has a negative effect on electronic prescribing and medication information systems that warn clinicians of potentially harmful medication combinations. Objective The aim of this study was to provide recommendations for systematic evaluation of evidence for DDIs from the scientific literature, drug product labeling, and regulatory documents. Methods A conference series was conducted to develop a structured process to improve the quality of DDI alerting systems. Three expert workgroups were assembled to address the goals of the conference. The Evidence Workgroup consisted of 18 individuals with expertise in pharmacology, drug information, biomedical informatics, and clinical decision support. Workgroup members met via webinar 12 times from January 2013 to February 2014. Two in-person meetings were conducted in May and September 2013 to reach consensus on recommendations. Results We developed expert consensus answers to the following three key questions. (i) What is the best approach to evaluate DDI evidence? (ii) What evidence is required for a DDI to be applicable to an entire class of drugs? (iii) How should a structured evaluation process be vetted and validated? Conclusion Evidence-based decision support for DDIs requires consistent application of transparent and systematic methods to evaluate the evidence. Drug compendia and clinical decision support systems in which these recommendations are implemented should be able to provide higher-quality information about DDIs.
更多
查看译文
关键词
Clinical Decision Support, Clinical Decision Support System, Narrow Therapeutic Index Drug, Computerize Clinical Decision Support System, Drug Interaction Probability Scale
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要