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Chronology of prescribing error during the hospital stay and prediction of pharmacist's alerts overriding: a prospective analysis

Thibaut Caruba12*, Isabelle Colombet3456, Florence Gillaizeau3456, Vanida Bruni1, Virginie Korb1, Patrice Prognon1, Dominique Bégué12, Pierre Durieux3456 and Brigitte Sabatier17

Author Affiliations

1 Department of pharmacy, APHP, Georges Pompidou European Hospital, 75015 Paris, France

2 Laboratoire Interdisciplinaire de Recherche en Economie de Santé, Paris, France

3 Department of Hospital Informatics, Evaluation and Public Health, APHP, Georges Pompidou European Hospital, 75015 Paris, France

4 INSERM, UMR S 872, Equipe 20, Paris, France

5 Centre de Recherche des Cordeliers, Université Paris Descartes, Paris, France

6 INSERM, Centre D'investigation Épidémiologique 4, Paris, France

7 Université Paris Descartes, INSERM U765, 4 avenue de l'Observatoire, 75006 Paris, France

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BMC Health Services Research 2010, 10:13  doi:10.1186/1472-6963-10-13

Published: 12 January 2010



Drug prescribing errors are frequent in the hospital setting and pharmacists play an important role in detection of these errors. The objectives of this study are (1) to describe the drug prescribing errors rate during the patient's stay, (2) to find which characteristics for a prescribing error are the most predictive of their reproduction the next day despite pharmacist's alert (i.e. override the alert).


We prospectively collected all medication order lines and prescribing errors during 18 days in 7 medical wards' using computerized physician order entry. We described and modelled the errors rate according to the chronology of hospital stay. We performed a classification and regression tree analysis to find which characteristics of alerts were predictive of their overriding (i.e. prescribing error repeated).


12 533 order lines were reviewed, 117 errors (errors rate 0.9%) were observed and 51% of these errors occurred on the first day of the hospital stay. The risk of a prescribing error decreased over time. 52% of the alerts were overridden (i.e error uncorrected by prescribers on the following day. Drug omissions were the most frequently taken into account by prescribers. The classification and regression tree analysis showed that overriding pharmacist's alerts is first related to the ward of the prescriber and then to either Anatomical Therapeutic Chemical class of the drug or the type of error.


Since 51% of prescribing errors occurred on the first day of stay, pharmacist should concentrate his analysis of drug prescriptions on this day. The difference of overriding behavior between wards and according drug Anatomical Therapeutic Chemical class or type of error could also guide the validation tasks and programming of electronic alerts.