title: [A new tool for evaluation of medication errors applied to pediatric hematology].
abstract: This study was conducted in a haematological paediatric department and was aimed at evaluating drug medication errors. Their frequency was studied, but also and mainly their degree of severity and preventability. Only adverse drug events that were identified as possibly due to pharmacological properties of drugs or medication errors were collected. An original method was used, based on a multidimensional mathematical tool, called Factorial Analysis of Multiple Correspondences (FAMC), in order to assess the grade of severity and preventability for each adverse drug event. A total of 155 adverse drug events were detected for 34 out of 52 patients hospitalized during the study period. The prevalence rate was 65 per cent and among these adverse drug events, 16 per cent were serious and 53 per cent were avoidable. Apart from the fact that the FAMC helped to determine the grade of preventability, FAMC allowed one to demonstrate that allergy and medication errors were the most avoidable adverse drug events. In this way the method used was validated. This study permitted the assessment of drug medication errors in this department and helped to choose the priorities for the management of preventive actions.
authors.affiliation: Service Pharmaceutique, Hôpital Debrousse, 29 rue Soeur Bouvier, 69322 Lyon, France.
authors.forename: E
authors.initials: E
authors.lastname: Queuille
authors.forename: N
authors.initials: N
authors.lastname: Bleyzac
authors.forename: J P
authors.initials: JP
authors.lastname: Auray
authors.forename: Y
authors.initials: Y
authors.lastname: Bertrand
authors.forename: G
authors.initials: G
authors.lastname: Souillet
authors.forename: N
authors.initials: N
authors.lastname: Philippe
authors.forename: G
authors.initials: G
authors.lastname: Duru
authors.forename: G
authors.initials: G
authors.lastname: Aulagner
mesh_terms: D002648:Child; D064420:Drug-Related Side Effects and Adverse Reactions; D006801:Humans; D019300:Medical Errors / Q000517:prevention & control / Q000706:statistics & numerical data*; D015233:Models, Statistical; D010372:Pediatrics / Q000706:statistics & numerical data*