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

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 <i>clinical decision support systems</i> (CDSSs). Janusmed Risk Profile is a...

Full description

Saved in:
Bibliographic Details
Main Authors: Tora Hammar, Emma Jonsén, Olof Björneld, Ylva Askfors, Marine L. Andersson, Alisa Lincke
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Pharmacy
Subjects:
Online Access:https://www.mdpi.com/2226-4787/12/6/168
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1846103180727812096
author Tora Hammar
Emma Jonsén
Olof Björneld
Ylva Askfors
Marine L. Andersson
Alisa Lincke
author_facet Tora Hammar
Emma Jonsén
Olof Björneld
Ylva Askfors
Marine L. Andersson
Alisa Lincke
author_sort Tora Hammar
collection DOAJ
description 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 <i>clinical decision support systems</i> (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 (<i>n</i> = 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.
format Article
id doaj-art-ec13dfd28c2548329ed26332f0a4ec0d
institution Kabale University
issn 2226-4787
language English
publishDate 2024-11-01
publisher MDPI AG
record_format Article
series Pharmacy
spelling doaj-art-ec13dfd28c2548329ed26332f0a4ec0d2024-12-27T14:46:49ZengMDPI AGPharmacy2226-47872024-11-0112616810.3390/pharmacy12060168Potential Adverse Drug Events Identified with Decision Support Algorithms from Janusmed Risk Profile—A Retrospective Population-Based Study in a Swedish RegionTora Hammar0Emma Jonsén1Olof Björneld2Ylva Askfors3Marine L. Andersson4Alisa Lincke5The eHealth Institute, Department of Medicine and Optometry, Linnaeus University, S-391 82 Kalmar, SwedenThe eHealth Institute, Department of Medicine and Optometry, Linnaeus University, S-391 82 Kalmar, SwedenThe eHealth Institute, Department of Medicine and Optometry, Linnaeus University, S-391 82 Kalmar, SwedenThe eHealth Institute, Department of Medicine and Optometry, Linnaeus University, S-391 82 Kalmar, SwedenDivision of Clinical Pharmacology, Department of Laboratory Medicine, Karolinska Institute and Clinical Pharmacology, Medical Diagnostics Karolinska, Karolinska University Hospital, S-141 86 Stockholm, SwedenLinnaeus 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, SwedenAdverse 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 <i>clinical decision support systems</i> (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 (<i>n</i> = 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.https://www.mdpi.com/2226-4787/12/6/168adverse drug eventsclinical decision support systemdrug-related problemspharmacoepidemiologyside effectsdrug–drug interactions
spellingShingle Tora Hammar
Emma Jonsén
Olof Björneld
Ylva Askfors
Marine L. Andersson
Alisa Lincke
Potential Adverse Drug Events Identified with Decision Support Algorithms from Janusmed Risk Profile—A Retrospective Population-Based Study in a Swedish Region
Pharmacy
adverse drug events
clinical decision support system
drug-related problems
pharmacoepidemiology
side effects
drug–drug interactions
title Potential Adverse Drug Events Identified with Decision Support Algorithms from Janusmed Risk Profile—A Retrospective Population-Based Study in a Swedish Region
title_full Potential Adverse Drug Events Identified with Decision Support Algorithms from Janusmed Risk Profile—A Retrospective Population-Based Study in a Swedish Region
title_fullStr Potential Adverse Drug Events Identified with Decision Support Algorithms from Janusmed Risk Profile—A Retrospective Population-Based Study in a Swedish Region
title_full_unstemmed Potential Adverse Drug Events Identified with Decision Support Algorithms from Janusmed Risk Profile—A Retrospective Population-Based Study in a Swedish Region
title_short Potential Adverse Drug Events Identified with Decision Support Algorithms from Janusmed Risk Profile—A Retrospective Population-Based Study in a Swedish Region
title_sort potential adverse drug events identified with decision support algorithms from janusmed risk profile a retrospective population based study in a swedish region
topic adverse drug events
clinical decision support system
drug-related problems
pharmacoepidemiology
side effects
drug–drug interactions
url https://www.mdpi.com/2226-4787/12/6/168
work_keys_str_mv AT torahammar potentialadversedrugeventsidentifiedwithdecisionsupportalgorithmsfromjanusmedriskprofilearetrospectivepopulationbasedstudyinaswedishregion
AT emmajonsen potentialadversedrugeventsidentifiedwithdecisionsupportalgorithmsfromjanusmedriskprofilearetrospectivepopulationbasedstudyinaswedishregion
AT olofbjorneld potentialadversedrugeventsidentifiedwithdecisionsupportalgorithmsfromjanusmedriskprofilearetrospectivepopulationbasedstudyinaswedishregion
AT ylvaaskfors potentialadversedrugeventsidentifiedwithdecisionsupportalgorithmsfromjanusmedriskprofilearetrospectivepopulationbasedstudyinaswedishregion
AT marinelandersson potentialadversedrugeventsidentifiedwithdecisionsupportalgorithmsfromjanusmedriskprofilearetrospectivepopulationbasedstudyinaswedishregion
AT alisalincke potentialadversedrugeventsidentifiedwithdecisionsupportalgorithmsfromjanusmedriskprofilearetrospectivepopulationbasedstudyinaswedishregion