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Journal of medical systems
Sep 30, 2024;48 (1): 93.

The Impact of Customized Screening Intervals on the Burden of Drug-Drug Interaction Alerts: An Interrupted Time Series Analysis.

Greet Van De Sijpe, Karolien Walgraeve, Eva Van Laer, Charlotte Quintens, Christophe Machiels, Veerle Foulon, Minne Casteels, Lorenz Van der Linden, Isabel Spriet
Author Information
  1. Greet Van De Sijpe: Pharmacy Department, University Hospitals Leuven, Herestraat 49, Leuven, 3000, Belgium. greet.vandesijpe@uzleuven.be. ORCID
  2. Karolien Walgraeve: Pharmacy Department, University Hospitals Leuven, Herestraat 49, Leuven, 3000, Belgium.
  3. Eva Van Laer: Pharmacy Department, University Hospitals Leuven, Herestraat 49, Leuven, 3000, Belgium.
  4. Charlotte Quintens: Pharmacy Department, University Hospitals Leuven, Herestraat 49, Leuven, 3000, Belgium.
  5. Christophe Machiels: Department of Information Technology, nexuzhealth, Belgium.
  6. Veerle Foulon: Clinical Pharmacology and Pharmacotherapy, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium.
  7. Minne Casteels: Clinical Pharmacology and Pharmacotherapy, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium.
  8. Lorenz Van der Linden: Pharmacy Department, University Hospitals Leuven, Herestraat 49, Leuven, 3000, Belgium. ORCID
  9. Isabel Spriet: Pharmacy Department, University Hospitals Leuven, Herestraat 49, Leuven, 3000, Belgium.
PMID: 39347841 DOI: 10.1007/s10916-024-02113-8

Abstract

Fixed and broad screening intervals for drug-drug interaction (DDI) alerts lead to false positive alerts, thereby contributing to alert fatigue among healthcare professionals. Hence, we aimed to investigate the impact of customized screening intervals on the daily incidence of DDI alerts. An interrupted time series analysis was performed at the University Hospitals Leuven to evaluate the impact of a pragmatic intervention on the daily incidence of DDI alerts per 100 prescriptions. The study period encompassed 100 randomly selected days between April 2021 and December 2022. Preceding the intervention, a fixed and broad screening interval of 7 days before and after prescribing an interacting drug was applied. The intervention involved implementing customized screening intervals for a subset of highly prevalent or clinically relevant DDIs into the hospital information system. Additionally, the sensitivity of the tailored approach was evaluated. During the study period, a mean of 5731 (± 2909) new prescriptions per day was generated. The daily incidence of DDI alerts significantly decreased from 9.8% (95% confidence interval (CI) 8.4;11.1) before the intervention, to 6.3% (95% CI 5.4;7.2) afterwards, p < 0.0001. This corresponded to avoiding 201 (0.035*5731) false positive DDI alerts per day. Sensitivity was not compromised by our intervention. Defining and implementing customized screening intervals was feasible and effective in reducing the DDI alert burden without compromising sensitivity.

Keywords

Advanced clinical decision support systems Alert fatigue Alert specificity Clinical decision support systems Drug interactions

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MeSH Term

Interrupted Time Series Analysis
Humans
Drug Interactions
Medical Order Entry Systems
Medication Errors
Alert Fatigue, Health Personnel
Hospital Information Systems
Time Factors
Belgium
Journal Article

Word Cloud

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