Identifying high-risk medications and error types in Danish patient safety database using disproportionality analysis

Background: Medication error (ME) surveillance in Danish healthcare relies on the mandatory national incident reporting system, the Danish Patient Safety Database (DPSD). Individual case reviews and descriptive statistics with frequency counts are the most often used approaches when analyzing MEs in incident reporting systems, including the DPSD. However, incident reporting systems often generate a large number of reports and may suffer from underreporting; consequently, additional approaches are needed to overcome these challenges. Disproportionality analysis (DPA) is a statistical tool used for signal detection of adverse drug reactions in pharmacovigilance reports, but the evidence for using DPA on ME analysis in safety reporting systems is limited. Objectives: We aimed to test the feasibility of DPA by analysing harmful MEs reported to DPSD 2014–2018. Methods: We utilized proportional reporting ratios (PRR) to identify signals of diproportionality. Results: We identified well-known high-risk medicines, including anticoagulants, opioids, insulins, antiepileptic, and antipsychotic drugs, and their association with several ME types and stages in a medication process. Conclusion: DPA might be suggested as an additional tool for screening MEs and identifying priority areas for further investigation in safety reporting systems.