Translation and adaptation of a tool prescribing errors related to computerized physician order entry coding to the French hospital background. Traduction et adaptation au contexte hospitalier français d’un outil de codification des erreurs de prescription liées aux logiciels

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Videau, Manon | Charpiat, Bruno | Conort, Ornella | Janoly-Dumenil, Audrey | Bedouch, Pierrick

Edité par CCSD ; Elsevier Masson -

International audience. Prescribing errors related to computerized physician order entry are current and may have serious consequences for patients. They can be detected by pharmacists during prescriptions analysis and lead to pharmacist's interventions. In France, few monocentric studies have studied Pharmacist Interventions triggered by prescribing errors identified as System-Related Errors (PISREs) in French hospitals. However, their respective analysis method prevent any comparison between computerized physician order entry systems in order to identify the safest and rule out the most dangerous. A computerized physician prescribing error related to the software is characterized by its causes, consequences and mechanism of occurrence. US researchers have developed and validated a tool to classify and illustrate these three characteristics. The objectives of this article are to present this tool, to propose a French adaptation and to describe the perspectives analyze and understand prescription errors related to computerized physician order entry based on data of Act-IP©. The adaptation was performed using PISREs extracted from the Act-IP© observatory of the French Society of Clinical Pharmacy. Each item of the codification is illustrated with an example of PI. We are considering a training plan in order to allow wide use of this tool. Once adopted this tool, the next step will be to organize a prospective multicenter study including as many computerized prescription order entry systems as possible. The aim of this study will be identifying the safest systems. Consequently, it will then be possible to have arguments to qualify the most dangerous and thus propose their withdrawal from the market.

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