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

Area of Science:

• Healthcare safety
• Pharmacovigilance
• Medication error analysis

Background:

• Medication error (ME) surveillance in Denmark uses the national Danish Patient Safety Database (DPSD).
• Current analysis methods like case reviews and descriptive statistics have limitations, including underreporting and large data volumes.
• Disproportionality analysis (DPA), a tool for adverse drug reaction signal detection, has limited evidence for ME analysis in safety reporting systems.

Purpose of the Study:

• To assess the feasibility of using Disproportionality Analysis (DPA) for analyzing harmful medication errors (MEs).
• To evaluate DPA's potential as a supplementary tool for ME surveillance in healthcare safety reporting.

Main Methods:

• Utilized proportional reporting ratios (PRR) to detect disproportionality signals.
• Analyzed harmful medication errors reported to the Danish Patient Safety Database (DPSD) between 2014 and 2018.

Main Results:

• Successfully identified associations between high-risk medications (e.g., anticoagulants, opioids, insulins) and various medication error types and stages.
• Demonstrated the identification of well-known high-risk drug classes through DPA.

Conclusions:

• Disproportionality analysis (DPA) shows feasibility for screening medication errors in safety reporting systems.
• DPA can serve as an additional tool to identify priority areas for further investigation of medication errors.