Comparison of prioritisation algorithms for the selection of patients for medication reviews in the emergency department: a cross-sectional study

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Background: Risk prioritisation algorithms provide patients with a risk category that guides pharmacists to choose those needing medication reviews (MRs) the most. For this study the Medicine Risk Score (MERIS) and a modified Assessment of Risk Tool (ART) were used. Aim: To examine how the selection of patients by the clinical pharmacists in an emergency department for MRs compared with the categorisation provided by MERIS and a modified version of ART (mART). Furthermore, examine the agreement between MERIS and mART. Method: A cross-sectional study was conducted using data on all admitted patients during a two-month period. Data were entered into the prioritisation algorithms and independently ranked by the six pharmacists who were observed as they selected patients for MR. Risk scores and categorisations were compared between the algorithms and the pharmacists’ ranking using t-test, Z-test, Chi square, Kruskal Wallis H-test, or Kappa statistics. Results: The study included 1133 patients. Significant differences were found between the pharmacists and the algorithms. The sensitivity and specificity of MERIS were 37.8% and 73.6%, for mART, 33.0% and 75.9%. Kappa was 0.58, showing moderate agreement. No significant differences were observed between the individual pharmacists’ selection, but differences were significant between how pharmacists ranked the importance of the provided MRs. Conclusion: Pharmacists disagreed with the risk categorisation provided by MERIS and mART. However, MERIS and mART had similar sensitivity, specificity, and moderate agreement. Further research should focus on how clinical algorithms affect the selection of patients and on the importance of the MRs carried out by pharmacists.

Original languageEnglish
JournalInternational Journal of Clinical Pharmacy
Volume45
Pages (from-to)884–892
ISSN2210-7703
DOIs
Publication statusPublished - 2023

    Research areas

  • Assessment of risk tool, Drug-related problems, Medication review, Medicine risk score, Risk assessment

ID: 346244119