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GRP-131 Patient Safety – Analysing Medication-Related Adverse Events
  1. M Gudik-Sørensen
  1. Region Zealand, Logistics and Clinical Pharmacy, Roskilde, Denmark

Abstract

Background Medication-related adverse events (AEs) lead to increased morbidity, mortality and costs. In Denmark, frontline personnel in hospitals and in the primary care sector are obligated to report adverse events to a national reporting system ‘The Danish Patient Safety Database’. Since September 2011 it is also possible for patients and relatives to report AEs to the database.

An increased understanding of the causes of AEs may assist in preventing them.

Purpose The aim was to analyse medication-related AEs reported to the Danish Patient Safety Database in Zealand Region.

Materials and Methods Medication-related AEs are categorised by the person reporting the AE using the WHO classification system available in the Danish Patient Safety Database. The reported AE is subsequently analysed by a clinical pharmacist.

The analysis is performed using a modified version of the classification system, which was proposed by Ferner & Aronson. Errors are divided in two major categories:

  • Mistakes (errors in planning actions), which are divided into knowledge-based errors and rule-based errors

  • Skill-based errors (errors in executing correctly planned actions), which are divided into action-based errors (slips, including technical errors) and memory-based errors (lapses)

Data were received Oct. 2011–May 2012.

Results During the study period, 741 AE reports concerning events associated with medication in hospitals were filed in Zealand Region. They averaged 93 events every month.

The Danish Patient Safety Database showed that the medication-related AEs are mainly categorised as prescribing (31%) and administration (29%), and some as dispensing (19%).

For comparison, results from Ferner & Aronson showed that 60% are rule-based errors, 31% action-based errors, 8% knowledge-based errors and 1% memory-based errors.

Results Ferner & Aronson’s classification tool by is useful in categorising medication-related AEs, and the resulting subgroups can add to our knowledge about how errors may be prevented.

No conflict of interest.

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