title: Indicators for the automated analysis of drug prescribing quality.
abstract: Irrational and inconsistent drug prescription has considerable impact on morbidity, mortality, health service utilization, and community burden. However, few studies have addressed the methodology of processing the information contained in these drug orders used to study the quality of drug prescriptions and prescriber behavior. We present a comprehensive set of quantitative indicators for the quality of drug prescriptions which can be derived from a drug order. These indicators were constructed using explicit a priori criteria which were previously validated on the basis of scientific data. Automatic computation is straightforward, using a relational database system, such that large sets of prescriptions can be processed with minimal human effort. We illustrate the feasibility and value of this approach by using a large set of 23,000 prescriptions for several diseases, selected from a nationally representative prescriptions database. Our study may result in direct and wide applications in the epidemiology of medical practice and in quality control procedures.
authors.affiliation: Département de Biostatistique et d'Informatique Médicale, Faculté Cochin, Université Paris V, Paris, France.
authors.forename: J
authors.initials: J
authors.lastname: Coste
authors.forename: B
authors.initials: B
authors.lastname: Séné
authors.forename: C
authors.initials: C
authors.lastname: Milstein
authors.forename: S
authors.initials: S
authors.lastname: Bouée
authors.forename: A
authors.initials: A
authors.lastname: Venot
mesh_terms: D000328:Adult; D000368:Aged; D000704:Analysis of Variance; D016303:Clinical Pharmacy Information Systems; D011307:Drug Prescriptions / Q000706:statistics & numerical data*; D004363:Drug Utilization; D005260:Female; D005602:France; D006801:Humans; D008297:Male; D008875:Middle Aged; D011786:Quality Control; D019984:Quality Indicators, Health Care