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International Journal for Quality in Health Care Advance Access originally published online on September 10, 2008
International Journal for Quality in Health Care 2008 20(6):400-405; doi:10.1093/intqhc/mzn038
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© The Author 2008. Published by Oxford University Press in association with the International Society for Quality in Health Care; all rights reserved

Analysis of overridden alerts in a drug–drug interaction detection system

Frédéric Mille1,2, Céline Schwartz1, Francoise Brion1, Jean-Eudes Fontan4, Olivier Bourdon1, Patrice Degoulet2 and Marie-Christine Jaulent3

1 AP-HP Hôpital Robert Debré, service pharmacie, 48 boulevard serrurier 75018 Paris
2 INSERM UMRS 872 eq 20 Université Paris VI, laboratoire SPIM, Rue de l'école de médecine 75006 Paris
3 INSERM, U872, Éq. 20, Paris, F-75006 France; Université Pierre et Marie Curie - Paris6, UMR S 872, Paris, F-75006 France; Université Paris Descartes, UMR S 872, Paris, F-75006, France
4 AP-HP Hôpital Jean Verdier, service pharmacie, 93143 Bondy

Objective. The aim of this study was to evaluate the relevance of the signals generated by a computerized drug–drug interaction detection system and to design a classification of overridden drug–drug interaction alerts.

Study Design. Prospective study over two months.

Setting. Five hundred and ten-bed university paediatric hospital.

Main Outcome Measures. In Robert Debré Hospital physicians generate drug orders online using a computerized physician order entry system that also detects drug–drug interactions in real time. We analysed the relevance of a sample of alerts overridden by physicians.

Results. We analysed a sample of 613 overridden alerts. We defined three categories of overridden alerts: informational errors (35); system errors (244) and accurate alerts (334). Two reasons account for 40% of false-positive alerts: an inability of the system to recognize real conflicts between drug treatments and guidelines stating that the two drugs can be used together, because the benefit outweighs the risk of side effects due to the drug–drug interaction.

Conclusions. We created a classification of overridden alerts, in the context of computerized physician order entry system coupled with a drug–drug interaction detection system. There is clearly room for improvement in the development of drug–drug interaction software. This classification should make it possible to break this work down into smaller tasks, making it possible to decrease the sensitivity to background noise of drug–drug interaction detection systems.

Keywords: drug–drug interaction, clinical decision support systems, alert relevance

Address reprint requests to: Frédéric Mille, Tel: +33 (0) 1 40 03 57 41; Fax: +33 (0) 1 40 03 24 81; E-mail: fredericmille{at}rdb.aphp.fr

Accepted for publication August 14, 2008.


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