Types and Severity of Medication-Errors with Automated Systems within Medication-Use Process: Systematic-Review

Abstract

Automated systems have been crucial to reducing medication errors and improving patient safety. However, their use has increased medication-errors associated with other factors:socio-technical interactions, automation bias, workarounds, and overrides. This comprehensive systematic review was conducted to identify types and severity of medication-errors associated with the use of automated system in all stages of the medication use process. This provides new perspectives that contribute significantly to global knowledge in the research area. Three databases were searched to include English-language observational and experimental studies(from 2000-2019) focused on types and severity of medication errors. A data-extraction form was developed, and quality was assessed using Hoy-et-al tool. The search yielded 860 articles after deduplication and thirteen were eligible. The bias risk was low for eight studies(62%) and moderate for five(38%). The medication-error types, and prevalence were omitted information(4-61%), wrong dose(4-30%), incorrect medication(1-18%), incorrect administration time(3-18%), and incorrect frequency(0.6%-21%) and occurred in the prescribing(62%) and administration(69%) stage. The error severity assessment used was NCC-MERP-index(46%), other(23%), or not conducted(31%). Omitted information and incorrect dose were the most common errors associated with automated systems in the prescribing and administration stages. However, the error severity and classification was inconclusive due to differences in study design and assessment criteria.