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Applicability of drug-related problem (DRP) classification system for classifying severe medication errors.

Carita Linden-Lahti1,2, Anna Takala3, Anna-Riia Holmström3

  • 1Division of Pharmacology and Pharmacotherapy, Faculty of Pharmacy, University of Helsinki, Viikinkaari 5 E, 00014, Helsinki, Finland. carita.linden-lahti@hus.fi.

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|July 10, 2023
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Summary

This study shows a cause-based Drug-Related Problem (DRP) classification system effectively categorizes severe medication errors (MEs) and their origins. This approach aids in understanding and preventing future MEs in healthcare.

Keywords:
Classification systemDrug-related problemMedication errorMedication safetySevere medication errorTaxonomy

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Area of Science:

  • Pharmacovigilance
  • Patient Safety
  • Healthcare Quality Improvement

Background:

  • Existing medication error (ME) classification systems are suboptimal for severe MEs.
  • Identifying the root causes of severe MEs is crucial for effective prevention and risk management.

Purpose of the Study:

  • To evaluate the applicability of a cause-based Drug-Related Problem (DRP) classification system for severe MEs.
  • To analyze the causes of severe medication errors.

Main Methods:

  • Retrospective analysis of medication-related complaints and authoritative statements (2013-2017).
  • Application of an aggregated DRP classification system (Basger et al.).
  • Qualitative content analysis to identify error characteristics and patient harm.

Main Results:

  • Over half of analyzed ME cases (52%) resulted in patient death or severe harm.
  • A total of 100 MEs were identified, with an average of 1.7 MEs per case.
  • The DRP classification system successfully categorized all MEs, with only 8% falling into the 'Other' category.

Conclusions:

  • The cause-based DRP classification system shows promise for classifying and analyzing severe MEs.
  • This system effectively categorizes both the medication error and its underlying cause.
  • Further research with diverse ME incident data is recommended to validate these findings.