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A characterization and disproportionality analysis of medication error related adverse events reported to the FAERS database

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DataCite Commons2020-08-28 更新2024-07-27 收录
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https://tandf.figshare.com/articles/A_characterization_and_disproportionality_analysis_of_medication_error_related_adverse_events_reported_to_the_FAERS_database/7387148
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<b>Objectives</b>: To characterize adverse reactions associated with medication errors (ME) reported in US Food and Drug Administration Adverse Event Reporting System (US-FAERS), and to identify the potential signals of disproportionate reporting (SDR) for different drugs. <b>Methods</b>: ME associated Individual Case Study Report (ICSRs) were identified. ICSRs were categorized by patient age groups, affected stages of medication process and Anatomical Therapeutic Chemical classification system. Disproportionality analyses were performed for different age groups. <b>Results</b>: 46,8677 ICSRs were retrieved. An increasing trend in reporting of cases of ME was observed during the studied period. Immunosuppressants and psycholeptic drugs were most frequently involved. Administration errors were reported most frequently, followed by prescribing and dispensing errors. In neonates, SDR following wrong drug administration, wrong dose, and accidental overdose were associated with methylergonovine, zidovudine, and acetaminophen. In elderlies, SDR were found for dose omission and underdose error associated with etanercept and evolocumab. <b>Conclusion</b>: While a detailed root-cause analysis for ME characteristic can rarely be performed on such a dataset, data mining for signals in spontaneous reporting database may assist in identifying potential ME in a more standardized and objective manner. Continued use of spontaneous reporting system for identifying MEs is encouraged to prevent unnecessary patient harm.
提供机构:
Taylor & Francis
创建时间:
2018-11-27
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