1. Conferences Overview
    2. 32. Jahrestagung der Gesellschaft für Arzneimittelanwendungsforschung und Arzneimittelepidemiologie (GAA)
    3. ALERT – analysis of adverse drug reactions and medication errors in adults in Germany
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32. Jahrestagung der Gesellschaft für Arzneimittelanwendungsforschung und Arzneimittelepidemiologie (GAA)

Gesellschaft für Arzneimittelanwendungsforschung und Arzneimittelepidemiologie (GAA) e. V.
13.-14.11.2025
Jena


Meeting Abstract

ALERT – analysis of adverse drug reactions and medication errors in adults in Germany

Justin Weal 1
Diana Dubrall 2,1
Claudia Kayser 1
Birte Albrecht 3
Jakob Sommer 4
Maike Below 3
Matthias Schmid 2
Julia Stingl 4
Sven Zenker 5
Bernhardt Sachs 1,6
1Federal Institute for Drugs and Medical Devices (BfArM), Bonn, Germany
2University Hospital Bonn - Institute for Medical Biometry, Informatics and Epidemiology (IMBIE), Bonn, Germany
3Central institute for statutory health care (Zi), Berlin, Germany
4Department of Clinical Pharmacology and Pharmacoepidemiology at Heidelberg University Hospital (UKHD), Heidelberg, Germany
5University Hospital Bonn - Staff unit for medical-scientific technology development and coordination (MWTek), Bonn, Germany
6Department for Dermatology and Allergy, University Hospital RWTH Aachen, Aachen, Germany

Text

Background: 30-60% of all adverse drug reactions (ADRs) are estimated to be avoidable [1]. To reduce ADRs, further knowledge about their occurrence, types and associated factors, is necessary. Medication errors (MEs) are defined as unintended failures in the drug treatment process that lead to, or have the potential to lead to, harm to the patient. They are considered to be avoidable in all cases [2].

Funded by the Innovation fund of the Federal Joint Committee, ALERT aims to characterize ADRs and MEs in adults in Germany with a particular focus set on polymedicated patients, older patients and severe ADRs by generating quantifying data regarding frequency, severity and associated factors. In conjunction with an in-depth analysis of the subgroups of particular interest these analyses should allow for conclusions on the causes of ADRs and MEs and the establishing of key facts as a basis for recommendations to reduce ADRs and MEs.

Materials and Methods: In ALERT we conduct a retrospective, non-interventional pharmacoepidemiological study using five complementary real-world data sources referring to inpatients and outpatients. These include:

  1. spontaneous ADR reports with and without MEs from EudraVigilance;
  2. ME reports without ADRs from the German Federal Institute for Drugs and Medical Devices (BfArM) drug therapy safety database;
  3. systematically collected ADR/ME cases, which led to a presentation in emergency departments, from the ADRED study;
  4. electronic health records from the University Hospital Bonn (UKB), comprising diagnoses, drug therapies, and inpatient clinical records; and
  5. nationwide outpatient routine data according to § 300 (2) SGB V and § 295 SGB V from the Associations of Statutory Health Insurance Physicians provided by the Central Research Institute for Ambulatory Health Care (Zi), covering drug prescriptions and diagnostic codes across all statutory health insurers.

Notably, each dataset carries inherent limitations. Hence, our methodological approach was to perform a complementary analysis of all data sources with a view to compensate for some of these individual limitations.

Results: About 280,000 spontaneous reports of ADRs were found in the EudraVigilance database with over 43,000 cases regarding polymedicated patients, over 103,000 regarding older patients (≥65 years) and over 120,000 reports with serious ADRs. Of these, almost 9,000 involved MEs, and another about 3,000 ME-reports were found in the drug therapy safety database of the BfArM. Results from the reports will be linked to outpatient routine data from the Zi (drug prescriptions and diagnoses of approximately 47,4 million adult patients per year) to allow quantification of drug use frequency and estimation of ADR reporting rates. For further analysis of the inpatient sector, around 115,000 cases regarding 79,000 patients from the electronic health records of the university hospital Bonn (UKB) as well as around 8,000 cases from the ADRED cohort including in- and outpatient data are available for further in-depth analyses.

Conclusion: The data sources mentioned above are in general suitable for further in-depth analyses of ADRs and MEs in both, inpatient and outpatient care. These analyses will target factors being associated with ADRs and MEs such as polymedication and age.

References

[1] Hakkarainen KM, Hedna K, Petzold M, Hägg S. Percentage of patients with preventable adverse drug reactions and preventability of adverse drug reactions--a meta-analysis. PLoS One. 2012;7(3):e33236. DOI: 10.1371/journal.pone.0033236
[2] European Medicines Agency. Good practice guide on recording, coding, reporting and assessment of medication errors. EMA/762563/2014. EMA; 2015. Available from: https://www.ema.europa.eu/en/documents/regulatory-procedural-guideline/good-practice-guide-recording-coding-reporting-and-assessment-medication-errors_en.pdf