[Detection and classification of medication errors at Joan XXIII University Hospital]

Farm Hosp. 2004 Mar-Apr;28(2):90-6.
[Article in Spanish]

Abstract

Introduction: Medication errors are multifactorial and multidisciplinary, and may originate in processes such as drug prescription, transcription, dispensation, preparation and administration. The goal of this work was to measure the incidence of detectable medication errors that arise within a unit dose drug distribution and control system, from drug prescription to drug administration, by means of an observational method confined to the Pharmacy Department, as well as a voluntary, anonymous report system. The acceptance of this voluntary report system's implementation was also assessed.

Material and methods: A prospective descriptive study was conducted. Data collection was performed at the Pharmacy Department from a review of prescribed medical orders, a review of pharmaceutical transcriptions, a review of dispensed medication and a review of medication returned in unit dose medication carts. A voluntary, anonymous report system centralized in the Pharmacy Department was also set up to detect medication errors.

Results: Prescription errors were the most frequent (1.12%), closely followed by dispensation errors (1.04%). Transcription errors (0.42%) and administration errors (0.69%) had the lowest overall incidence. Voluntary report involved only 4.25% of all detected errors, whereas unit dose medication cart review contributed the most to error detection.

Conclusions: Recognizing the incidence and types of medication errors that occur in a health-care setting allows us to analyze their causes and effect changes in different stages of the process in order to ensure maximal patient safety.

Publication types

  • Comparative Study
  • English Abstract

MeSH terms

  • Hospital Units / statistics & numerical data
  • Hospitals, University / statistics & numerical data*
  • Humans
  • Medication Errors / classification
  • Medication Errors / statistics & numerical data*
  • Medication Systems, Hospital / statistics & numerical data*
  • Pharmacy Service, Hospital / statistics & numerical data
  • Prospective Studies