title: Drug prescription errors in a Brazilian hospital.
abstract: OBJECTIVE
  To identify the prevalence of clinically significant prescription errors in a Brazilian university hospital compared with their occurrence in 2003 and 2007.
  
  
  METHODS
  Variables and group of variables, such as readability, compliance with legal and institutional procedures of prescription, and prescription errors analysis were analyzed.
  
  
  RESULTS
  When the prevalence rates of clinically significant prescription errors were calculated, a statistically significant decrease was shown [year of 2003 (29.25%), year of 2007 (24.20%); (z = 2.99; p = 0.03)], reflecting on the safety rate [year of 2003 (70.75%), year of 2007 (75.80%); (z = 3.30; p =0.0001)].
  
  
  CONCLUSIONS
  Despite significant, the increased safety rate reflected the quantitative reduction of errors, with no observed difference in severity between the studied periods. Our results suggest the institutional steps taken could reduce the number of errors, but they were ineffective in reducing the severity of the errors.
authors.affiliation: Universidade Federal do Ceará, Fortaleza, CE, Brazil.
authors.forename: Eugenie Desiree Rabelo
authors.initials: ED
authors.lastname: Néri
authors.forename: Paulo Gean Chaves
authors.initials: PG
authors.lastname: Gadêlha
authors.forename: Sâmia Graciele
authors.initials: SG
authors.lastname: Maia
authors.forename: Ana Graziela da Silva
authors.initials: AG
authors.lastname: Pereira
authors.forename: Paulo César de
authors.initials: PC
authors.lastname: Almeida
authors.forename: Carlos Roberto Martins
authors.initials: CR
authors.lastname: Rodrigues
authors.forename: Milena Pontes
authors.initials: MP
authors.lastname: Portela
authors.forename: Marta Maria de França
authors.initials: MM
authors.lastname: Fonteles
mesh_terms: D001938:Brazil; D003430:Cross-Sectional Studies; D011307:Drug Prescriptions / Q000592:standards / Q000706:statistics & numerical data*; D006785:Hospitals, University / Q000706:statistics & numerical data; D006801:Humans; D008508:Medication Errors / Q000145:classification / Q000706:statistics & numerical data* / Q000639:trends; D011932:Reading; D018401:Sample Size