Automated detection of medication administration errors in neonatal intensive care.

ABSTRACT:

Objective

To improve neonatal patient safety through automated detection of medication administration errors (MAEs) in high alert medications including narcotics, vasoactive medication, intravenous fluids, parenteral nutrition, and insulin using the electronic health record (EHR); to evaluate rates of MAEs in neonatal care; and to compare the performance of computerized algorithms to traditional incident reporting for error detection.

Methods

We developed novel computerized algorithms to identify MAEs within the EHR of all neonatal patients treated in a level four neonatal intensive care unit (NICU) in 2011 and 2012. We evaluated the rates and types of MAEs identified by the automated algorithms and compared their performance to incident reporting. Performance was evaluated

SUBMITTER: Li Q 

PROVIDER: S-EPMC4715992 | biostudies-literature | 2015 Oct

REPOSITORIES: biostudies-literature