Caruba Thibaut, Boussadi Abdelali, Lenain Emilie, Korb-Savoldelli Virginie, Gillaizeau Florence, Durieux Pierre, Sabatier Brigitte
Service de Pharmacie, Hôpital Européen Georges Pompidou, Assistance Publique - Hôpitaux de Paris, Paris, France.
Département de Santé Publique et Informatique Médicale, Hôpital Européen Georges Pompidou, Assistance Publique - Hôpitaux de Paris, Paris, France.
J Eval Clin Pract. 2015 Aug;21(4):673-80. doi: 10.1111/jep.12363. Epub 2015 Apr 22.
RATIONALE, AIMS AND OBJECTIVES: To evaluate the performance of several pharmacists in the same department who analysed the same prescriptions in a simulation study.
One hundred prescriptions were retrospectively extracted from the prospective database of our hospital. Five clinical pharmacists working in the same department were asked to analyse individually the order lines of each prescription as if it were part of their routine daily practice. Afterward, an independent committee of five other clinical pharmacists reviewed the same 100 prescriptions. We calculated the sensitivity and the specificity of error detection in a line order by using the results of the committee as the gold standard.
A total of 908 order lines were analysed (mean 9 ± 3 order lines per prescription). Fifty-one medication errors were identified by the committee (5.6%), including 23 related to laboratory test results: renal failure, or therapeutic concentrations being too low or too high. The sensitivity of the five pharmacists ranged between 19.6% and 56.9% and the specificity between 92.8% and 98.7%. The rates of agreement between each pharmacist and the committee, assessed using kappa coefficient, were between 0.20 and 0.39. The main factors affecting sensitivity and/or specificity in univariate analysis were the number of drugs per prescription, type of drug prescribed (ATC classification) and the glomerular filtration rate.
Discrepancies between the performances of pharmacists exist, as there are between other health care professionals. Pharmacist training, standardization of the pharmaceutical analysis of drug prescription, and implementation of a clinical decision support system allowing biological values to be linked to drug prescriptions could improve individual performance.
原理、目的和目标:在一项模拟研究中评估同一科室的几位药剂师分析相同处方的表现。
从我院前瞻性数据库中回顾性提取100份处方。要求同一科室的五名临床药剂师分别分析每份处方的医嘱项目,就如同这是他们日常工作的一部分。之后,由另外五名临床药剂师组成的独立委员会对相同的100份处方进行审查。我们以委员会的结果作为金标准,计算医嘱项目中错误检测的敏感性和特异性。
共分析了908个医嘱项目(每份处方平均9±3个医嘱项目)。委员会识别出51个用药错误(5.6%),其中23个与实验室检查结果有关:肾衰竭,或治疗浓度过低或过高。五名药剂师的敏感性在19.6%至56.9%之间,特异性在92.8%至98.7%之间。使用kappa系数评估,每位药剂师与委员会之间的一致率在0.20至0.39之间。单因素分析中影响敏感性和/或特异性的主要因素是每份处方的药物数量、所开药物的类型(ATC分类)和肾小球滤过率。
药剂师的表现之间存在差异,其他医疗保健专业人员之间也存在差异。药剂师培训、药物处方药学分析的标准化以及实施允许将生物学值与药物处方相联系的临床决策支持系统可以提高个人表现。