title: [Detection of prescription errors in drug dispensing: incidence and typology].
abstract: OBJECTIVE
  Description and quantification of the types of prescribing errors during dispensing activities at community pharmacies.
  
  
  METHODS
  Descriptive transversal study carry out along four weekly periods. SITE. Eighteen pharmacies from six of the spanish autonomous regions dispensing prescription orders mainly issued by the National Health Service. PATIENTS AND OTHER TAKING PART: 37,321 prescriptions of specialties dispensed by the mentioned pharmacies along the four week period.
  
  
  RESULTS
  An unstructured questionnary was applied to all persons asking for one of the mentioned prescriptions. When an error was suspected, a second structured questionnary was applied by the pharmacist to the order bearer and the answers plus the information contents at the prescription form was collected on a data-sheet. Data were processed on a dBase and SPSS programs. Incidence detected error of 1.35%. Types of error classified into five categories. Study of the variability of error detection by week and by pharmacy. Analysis and comparison with references of the "order author" data and "prescriptor" data.
  
  
  CONCLUSIONS
  Our global incidence of detected error was lower in relation with other studies. We found short differences by weeks and large by pharmacies. Inadequate definition of the drug was the most frequent type of error. The detection frequency of posology error was higher following the use of the new prescription order model. The number of orders from different prescriptor/author was larger in our study in relation to the notified by other studies.
authors.affiliation: Red Española de Atención Primaria, Facultad de Medicina, Universidad de Oviedo.
authors.forename: F
authors.initials: F
authors.lastname: Alvarez de Toledo
authors.forename: E
authors.initials: E
authors.lastname: Zardain
authors.forename: T
authors.initials: T
authors.lastname: Eyaralar
authors.forename: A M
authors.initials: AM
authors.lastname: Dago
authors.forename: P
authors.initials: P
authors.lastname: Arcos
mesh_terms: D008508:Medication Errors / Q000706:statistics & numerical data*; D010594:Pharmacies; D012044:Regression Analysis