Estimating the frequency of automated dispensing cabinet discrepancy safety events using Markov models

Abstract

Background Medication errors are one of the most common types of adverse events in inpatient settings, accounting for nearly 5% of adverse events experienced by hospitalized patients. In this exploratory study, we modeled and estimated the frequency of automated dispensing cabinet (ADC) discrepancy safety events across three different data sources: ADC transaction logs, user ADC discrepancy reports, and user reports to a patient safety event (PSE) reporting system. [...]baseline information on the prevalence and scope of a safety hazard using the safety event report data alone will never be available. The aim of the study was to use a Markov modeling approach to understand the prevalence of discrepancy hazards and quantify the amount that get reported to the reporting system by estimating the frequency of ADC discrepancy safety events across three different data sources (i.e., ADC transaction logs, user ADC discrepancy reports, and user reports to a PSE reporting system).