title: A simulation study of the interception of prescribing errors by clinical pharmacists in an acute hospital setting.
abstract: OBJECTIVE
  To evaluate the performance of several pharmacists in the same department who analysed the same prescriptions in a simulation study.
  
  
  METHODS
  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.
  
  
  RESULTS
  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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Service de Pharmacie, Hôpital Européen Georges Pompidou, Assistance Publique - Hôpitaux de Paris, Paris, France.
authors.forename: Thibaut
authors.initials: T
authors.lastname: Caruba
authors.affiliation: Département de Santé Publique et Informatique Médicale, Hôpital Européen Georges Pompidou, Assistance Publique - Hôpitaux de Paris, Paris, France.|INSERM UMR 1138, Equipe 22, Centre de Recherche des Cordeliers, Universités Paris 5 et 6, Paris, France.
authors.forename: Abdelali
authors.initials: A
authors.lastname: Boussadi
authors.affiliation: Unité d'Epidémiologie et de Recherche Clinique, Hôpital Européen Georges Pompidou, Assistance Publique - Hôpitaux de Paris, Paris, France.
authors.forename: Emilie
authors.initials: E
authors.lastname: Lenain
authors.affiliation: Service de Pharmacie, Hôpital Européen Georges Pompidou, Assistance Publique - Hôpitaux de Paris, Paris, France.
authors.forename: Virginie
authors.initials: V
authors.lastname: Korb-Savoldelli
authors.affiliation: Unité d'Epidémiologie et de Recherche Clinique, Hôpital Européen Georges Pompidou, Assistance Publique - Hôpitaux de Paris, Paris, France.
authors.forename: Florence
authors.initials: F
authors.lastname: Gillaizeau
authors.affiliation: Département de Santé Publique et Informatique Médicale, Hôpital Européen Georges Pompidou, Assistance Publique - Hôpitaux de Paris, Paris, France.|INSERM UMR 1138, Equipe 22, Centre de Recherche des Cordeliers, Universités Paris 5 et 6, Paris, France.
authors.forename: Pierre
authors.initials: P
authors.lastname: Durieux
authors.affiliation: Service de Pharmacie, Hôpital Européen Georges Pompidou, Assistance Publique - Hôpitaux de Paris, Paris, France.|INSERM UMR 1138, Equipe 22, Centre de Recherche des Cordeliers, Universités Paris 5 et 6, Paris, France.
authors.forename: Brigitte
authors.initials: B
authors.lastname: Sabatier
mesh_terms: D000328:Adult; D016303:Clinical Pharmacy Information Systems; D011307:Drug Prescriptions / Q000706:statistics & numerical data*; D057286:Electronic Health Records; D005260:Female; D005602:France; D006302:Health Services Research; D006801:Humans; D008297:Male; D050316:Medical Order Entry Systems; D008508:Medication Errors / Q000517:prevention & control* / Q000706:statistics & numerical data*; D008510:Medication Systems, Hospital; D010607:Pharmacy Service, Hospital / Q000458:organization & administration*; D012189:Retrospective Studies; D000066908:Simulation Training
keywords: clinical pharmacist; individual performance; medication error