, Volume 32, Issue 5, pp 379-389
Date: 20 Nov 2012

Prevalence, Incidence and Nature of Prescribing Errors in Hospital Inpatients

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Abstract

Prescribing errors affect patient safety throughout hospital practice. Previous reviews of studies have often targeted specific populations or settings, or did not adopt a systematic approach to reviewing the literature. Therefore, we set out to systematically review the prevalence, incidence and nature of prescribing errors in hospital inpatients. MEDLINE, EMBASE, CINAHL and International Pharmaceutical Abstracts (all from 1985 to October 2007) were searched for studies of prescriptions for adult or child hospital inpatients giving enough data to calculate an error rate. Electronic prescriptions and errors for single diseases, routes of administration or types of prescribing error were excluded, as were non-English language publications. Median error rate (interquartile range [IQR]) was 7% (2–14%) of medication orders, 52 (8–227) errors per 100 admissions and 24 (6–212) errors per 1000 patient days. Most studies (84%) were conducted in single hospitals and originated from the US or UK (72%). Most errors were intercepted and reported before they caused harm, although two studies reported adverse drug events. Errors were most common with antimicrobials and more common in adults (median 18% of orders [ten studies, IQR 7–25%]) than children (median 4% [six studies, IQR 2–17%]). Incorrect dosage was the most common error.

Overall, it is clear that prescribing errors are a common occurrence, affecting 7% of medication orders, 2% of patient days and 50% of hospital admissions. However, the reported rates of prescribing errors varied greatly and this could be partly explained by variations in the definition of a prescribing error, the methods used to collect error data and the setting of the study. Furthermore, a lack of standardization between severity scales prevented any comparison of error severity across studies. Future research should address the wide disparity of data-collection methods and definitions that bedevils comparison of error rates or meta-analysis of different studies.