[Medication errors on hospital admission]

Ugeskr Laeger. 2006 Aug 28;168(35):2887-90.
[Article in Danish]

Abstract

Introduction: This study investigated the number of medication errors on hospital admission and the clinical relevance of these errors. The new personal electronic medicine profile (PEM) was tested to establish whether it can contribute further information about the patient's medication on admission.

Materials and methods: This cross-sectional study included patients admitted to an acute medical admissions ward. In addition to the ward's usual admission procedure, a clinical pharmacist created an extra medication history by carrying out semi-structured interviews and obtaining additional information from the patient's GP. Information was then obtained from the PEM. A clinical expert panel assessed the potential clinical relevance of the discrepancies.

Results: Of 67 patients admitted, 48 were interviewed. The patients' average age was 71, and they used an average of 6.4 medications each. There were 309 prescriptions registered, producing 85 errors: the extra medication history highlighted 73 of these errors, and the subsequent check of the PEM revealed a further 12 errors. Thirty-three patients (69%) were affected by one or more errors, of which the expert panel considered six (18%) to be potentially serious.

Conclusion: Medication errors on admission to hospital reduce the quality of treatment and can lead to adverse events. The PEM cannot replace the traditional medication history, but the use of a PEM and the increased focus on medication histories can contribute to an improved hospital stay.

Publication types

  • English Abstract
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Clinical Pharmacy Information Systems
  • Cross-Sectional Studies
  • Denmark
  • Drug Prescriptions
  • Emergency Service, Hospital
  • Female
  • Humans
  • Interviews as Topic
  • Male
  • Medical Records Systems, Computerized
  • Medication Errors* / prevention & control
  • Medication Errors* / statistics & numerical data
  • Middle Aged
  • Patient Admission*
  • Quality Assurance, Health Care
  • Safety Management