Comparison of three commercial knowledge bases for detection of drug-drug interactions in clinical decision support
| Autor: | Jean Cunningham, Olivier Bodenreider, Stefanie Higby-Baker, Kin Wah Fung, Joan Kapusnik-Uner |
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| Rok vydání: | 2017 |
| Předmět: |
Drug
Computer science Health information technology Knowledge Bases media_common.quotation_subject Clinical Decision-Making Health Informatics Research and Applications computer.software_genre 030226 pharmacology & pharmacy Clinical decision support system Medical Order Entry Systems Ranking (information retrieval) 03 medical and health sciences 0302 clinical medicine Computerized physician order entry Humans Drug Interactions Relevance (information retrieval) 030212 general & internal medicine Medical prescription media_common Information retrieval Decision Support Systems Clinical Drug Therapy Computer-Assisted Data mining RxNorm computer |
| Zdroj: | Journal of the American Medical Informatics Association. 24:806-812 |
| ISSN: | 1527-974X 1067-5027 |
| DOI: | 10.1093/jamia/ocx010 |
| Popis: | Objective: To compare 3 commercial knowledge bases (KBs) used for detection and avoidance of potential drug-drug interactions (DDIs) in clinical practice.Methods: Drugs in the DDI tables from First DataBank (FDB), Micromedex, and Multum were mapped to RxNorm. The KBs were compared at the clinical drug, ingredient, and DDI rule levels. The KBs were evaluated against a reference list of highly significant DDIs from the Office of the National Coordinator for Health Information Technology (ONC). The KBs and the ONC list were applied to a prescription data set to simulate their use in clinical decision support.Results: The KBs contained 1.6 million (FDB), 4.5 million (Micromedex), and 4.8 million (Multum) clinical drug pairs. Altogether, there were 8.6 million unique pairs, of which 79% were found only in 1 KB and 5% in all 3 KBs. However, there was generally more agreement than disagreement in the severity rankings, especially in the contraindicated category. The KBs covered 99.8–99.9% of the alerts of the ONC list and would have generated 25 (FDB), 145 (Micromedex), and 84 (Multum) alerts per 1000 prescriptions.Conclusion: The commercial KBs differ considerably in size and quantity of alerts generated. There is less variability in severity ranking of DDIs than suggested by previous studies. All KBs provide very good coverage of the ONC list. More work is needed to standardize the editorial policies and evidence for inclusion of DDIs to reduce variation among knowledge sources and improve relevance. Some DDIs considered contraindicated in all 3 KBs might be possible candidates to add to the ONC list. |
| Databáze: | OpenAIRE |
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