Potential Adverse Drug Events Identified with Decision Support Algorithms from Janusmed Risk Profile-A Retrospective Population-Based Study in a Swedish Region.

Tora Hammar, Emma Jons��n, Olof Bj��rneld, Ylva Askfors, Marine L Andersson, Alisa Lincke
Author Information
  1. Tora Hammar: The eHealth Institute, Department of Medicine and Optometry, Linnaeus University, S-391 82 Kalmar, Sweden. ORCID
  2. Emma Jons��n: The eHealth Institute, Department of Medicine and Optometry, Linnaeus University, S-391 82 Kalmar, Sweden.
  3. Olof Bj��rneld: The eHealth Institute, Department of Medicine and Optometry, Linnaeus University, S-391 82 Kalmar, Sweden. ORCID
  4. Ylva Askfors: The eHealth Institute, Department of Medicine and Optometry, Linnaeus University, S-391 82 Kalmar, Sweden.
  5. Marine L Andersson: Division of Clinical Pharmacology, Department of Laboratory Medicine, Karolinska Institute and Clinical Pharmacology, Medical Diagnostics Karolinska, Karolinska University Hospital, S-141 86 Stockholm, Sweden. ORCID
  6. Alisa Lincke: Linnaeus University Centre for Data Intensive Sciences and Applications (LnuC DISA), Department of Computer Science and Media Technology (CM), Faculty of Technology, Linnaeus University, S-391 82 Kalmar, Sweden. ORCID

Abstract

Adverse drug events (ADEs) occur frequently and are a common cause of suffering, hospitalizations, or death, and can be caused by harmful combinations of medications. One method used to prevent ADEs is by using (CDSSs). Janusmed Risk Profile is a CDSS evaluating the risk for nine common or serious ADEs resulting from combined pharmacodynamic effects. The aim of this study was to examine the prevalence of potential ADEs identified using CDSS algorithms from Janusmed Risk Profile. This retrospective, cross-sectional study covered the population of a Swedish region ( = 246,010 inhabitants in year 2020) using data on all medications dispensed and administered. More than 20% of patients had an increased risk of bleeding, constipation, orthostatism, or renal toxicity based on their medications. The proportion of patients with an increased risk varied from 3.5% to almost 30% across the nine categories of ADEs. A higher age was associated with an increased risk of potential ADEs and there were gender differences. A cluster analysis identified groups of patients with an increased risk for several categories of ADEs. This study shows that combinations of medications that could increase the risk of ADEs are common. Future studies should examine how this correlates with observed ADEs.

Keywords

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Grants

  1. 2022-00643/Swedish Research Council for Health Working Life and Welfare
  2. Decision date 2021-07-04/DISA: Linnaeus University Centre for Data Intensive Sciences and Applications

Word Cloud

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