Drug‐Event Pairs as Indicators for the Detection of Adverse Drug Reactions during Hospitalization in Routinely Collected Electronic Data Sources

Adverse drug reactions (ADRs) are a common cause of morbidity and mortality in hospitalized patients. Identification of ADRs in clinical practice, surveillance and research is essential to prevent further harm. The aim of this study was to assess the likelihood of drugs contributing to clinically important inpatient adverse events, in order to provide a list of drug-event pairs indicating ADRs in electronic health record (EHR) data, referred to as "indicators of ADRs". We conducted a consensus process based on the RAND/UCLA Appropriateness Method for 14 ADRs. Experts were asked to rate the strength of the causal link between adverse events and potentially causative drugs on a 4-point Likert scale. Based on the median rating, drug-event pairs were categorized according to the likelihood of an ADR being present. Drug-event pairs with a median rating of ≥ 3 without disagreement were defined as indicators of certain and probable ADRs. Of the 255 drug-event pairs evaluated, 2 (1%) and 42 (16%) achieved consensus validation that they certainly and probably indicate an ADR. In addition, 137 drug-event pairs were considered as indicators of possible (54%) and 74 drug-event pairs were considered as indicators of unlikely (29%) ADRs. The provided set of content-validated indicators of clinically important inpatient ADRs can be used in clinical practice (e.g., decision support), surveillance (e.g., quality indicators) and research (e.g., outcome measures). They will be implemented in EHR data from German university hospitals to determine the prevalence of ADRs, support efficient use of pharmacist resources, and develop models predicting ADRs.

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Publication Details

Journal
Clinical Pharmacology & Therapeutics
Published
2025-03-18
DOI
https://doi.org/10.1002/cpt.3635
Citations
2
Primary Topic
Pharmacovigilance and Adverse Drug Reactions
Type
article
Field-Weighted Citation Impact
2.61
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article

Drug‐Event Pairs as Indicators for the Detection of Adverse Drug Reactions during Hospitalization in Routinely Collected Electronic Data Sources

Tobias Dreischulte, Annette Haerdtlein, Ulrich Jaehde, Wolfgang Fehrmann et al.
2 citations
Clinical Pharmacology & Therapeutics
Pharmacovigilance and Adverse Drug Reactions
2.61
article

Drug‐Event Pairs as Indicators for the Detection of Adverse Drug Reactions during Hospitalization in Routinely Collected Electronic Data Sources

Tobias Dreischulte, Annette Haerdtlein, Ulrich Jaehde, Wolfgang Fehrmann, Anna Maria Wermund, Clara Weglage
article en
2 citations

Abstract

Adverse drug reactions (ADRs) are a common cause of morbidity and mortality in hospitalized patients. Identification of ADRs in clinical practice, surveillance and research is essential to prevent further harm. The aim of this study was to assess the likelihood of drugs contributing to clinically important inpatient adverse events, in order to provide a list of drug-event pairs indicating ADRs in electronic health record (EHR) data, referred to as "indicators of ADRs". We conducted a consensus process based on the RAND/UCLA Appropriateness Method for 14 ADRs. Experts were asked to rate the strength of the causal link between adverse events and potentially causative drugs on a 4-point Likert scale. Based on the median rating, drug-event pairs were categorized according to the likelihood of an ADR being present. Drug-event pairs with a median rating of ≥ 3 without disagreement were defined as indicators of certain and probable ADRs. Of the 255 drug-event pairs evaluated, 2 (1%) and 42 (16%) achieved consensus validation that they certainly and probably indicate an ADR. In addition, 137 drug-event pairs were considered as indicators of possible (54%) and 74 drug-event pairs were considered as indicators of unlikely (29%) ADRs. The provided set of content-validated indicators of clinically important inpatient ADRs can be used in clinical practice (e.g., decision support), surveillance (e.g., quality indicators) and research (e.g., outcome measures). They will be implemented in EHR data from German university hospitals to determine the prevalence of ADRs, support efficient use of pharmacist resources, and develop models predicting ADRs.

Clinical Pharmacology & TherapeuticsVol. 117(6)
University of Bonn (DE), LMU Klinikum (DE), Ludwig-Maximilians-Universität München (DE)
Good health and well-being
Openalex Percentile: Top 13%
Pharmacovigilance and Adverse Drug Reactions
2.61
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