Considerations for implementation of vancomycin Bayesian software monitoring in a level IV NICU population within a multisite health system

Abstract

AbstractPurposeThe updated 2020 vancomycin therapeutic drug monitoring guideline advocates for area under the curve (AUC)–based monitoring in neonates, preferably with Bayesian estimation. This article describes the selection, planning, and implementation of vancomycin model-informed precision dosing (MIPD) software with Bayesian estimation in the neonatal intensive care unit (NICU) within an academic health system.SummaryThe selection, planning, and implementation of vancomycin MIPD software was completed in approximately 6 months throughout a health system with multiple NICU sites. The chosen software captures data on medications in additional to vancomycin, provides analytics support, includes specialty populations (eg, neonates), and offers the ability to integrate MIPD into the electronic health record. Pediatric pharmacy representatives served on a system-wide project team with key responsibilities including development of educational materials, drafting changes to policies and procedures, and assistance with department-wide software training. Additionally, pediatric and neonatal pharmacist super users trained other pediatric pharmacists on software functionality, were available the week of go-live for in-person support, and contributed to the identification of pediatric and NICU-specific nuances related to software implementation. Neonatal-specific considerations when implementing MIPD software include: the selection of appropriate pharmacokinetic model(s), continued evaluation of such model(s), selection of appropriate model(s) in infants as they age, input of significant covariates, determination of the site-specific serum creatinine assay, decision of the number of vancomycin serum concentrations obtained, discernment of patients excluded from AUC monitoring, and the utilization of actual versus dosing weight.ConclusionThis article serves to share our experience with selecting, planning, and implementing Bayesian software for vancomycin AUC monitoring in a neonatal population. Other health systems and children’s hospitals can utilize our experience to evaluate a variety of MIPD software and consider neonatal nuances prior to implementation.