Model-Informed Precision Dosing of Vancomycin in Hospitalized Children: Implementation and Adoption at an Academic Children’s Hospital

Abstract

Background: Model-informed precision dosing (MIPD) can serve as a powerful tool during therapeutic drug monitoring (TDM) to help individualize dosing in populations with large pharmacokinetic variation. Yet, adoption of MIPD in the clinical setting has been limited. Overcoming technologic hurdles that allow access to MIPD at the point-of-care and placing it in the hands of clinical specialists focused on medication dosing may encourage adoption. Objective: To describe the hospital implementation and usage of a MIPD clinical decision support (CDS) tool for vancomycin in a pediatric population. Methods: Within an academic children's hospital, MIPD for vancomycin was implemented via a commercial cloud-based CDS tool that utilized Bayesian forecasting. Clinical pharmacists were recognized as local champions to facilitate adoption of the tool and operated as end-users. Integration within the electronic health record (EHR) and automatic transmission of patient data to the tool were identified as important requirements. A web-link icon was developed within the EHR which when clicked sends users and needed patient-level clinical data to the CDS platform. Individualized pharmacokinetic predictions and exposure metrics for vancomycin are then presented in the form of a web-based dashboard. Use of the CDS tool as part of TDM was tracked and users were surveyed on their experience. Results: After a successful pilot phase in the neonatal intensive care unit, implementation of MIPD was expanded to the pediatric intensive care unit, followed by availability to the entire hospital. During the first 2+ years since implementation, a total of 853 patientcourses (n = 96 neonates, n = 757 children) and 2,148 TDM levels were evaluated using the CDS tool. For the most recent 6 months, the CDS tool was utilized to support 79% (181/230) of patient-courses in which TDM was performed. Of 26 users surveyed, > 96% agreed or strongly agreed that automatic transmission of patient data to the tool was a

Area under the curve achievement of once daily tobramycin in children with cystic fibrosis during clinical care

“…However, recent advances in health care technology have fostered the development of more user‐friendly BF dosing support software 27 . Adoption of BF approaches in clinical care has also been facilitated through integration of dosing support software within the EHR, which allows access within the clinical workflow of providers and supports automatic transmission relevant patient data (ie, age, serum creatinine, dose and drug concentration history, serum creatinine) 17 . We recently integrated within our EHR (Epic Systems, Verona, Wisconsin) a commercially available cloud‐based web app (InsightRx, San Francisco, CA) that supports BF dosing and which we now use to estimate AUC 24 in all patients with CF receiving tobramycin at our center.…”

“…The BF approach applies a population pharmacokinetic model as a Bayesian prior and integrates information known about the patient (eg, age, weight, renal function, drug concentrations) to predict the individual pharmacokinetics of a patient, which are then used to estimate AUC 24 . Recent advances in health care technology now offer the opportunity to implement BF approaches in clinical care 16,17 …”

Model-Informed Precision Dosing of Antibiotics in Pediatric Patients: A Narrative Review

“…Additionally, gentamicin model-based dosing in neonates and infants (neoGent) utilized a freely available MIPD tool which aids gentamicin TDM ( 76 ). The integration of a MIPD tool within the EHR can facilitate the adoption of precision dosing in routine clinical care ( 77 ). Kantasiripitak et al evaluated 10 MIPD software tools and they concluded that improvements should still be made concerning EHR integration, standardization of software and model validation strategies, and prospective evidence for the software tools' clinical and cost benefits ( 34 ).…”

“…To fully exploit the potential benefits of MIPD, the tools must be implemented in an easy-to-use framework for the team of healthcare providers. Importantly, the role of clinical pharmacists is considered as a success factor to implement MIPD ( 77 ). As suggested by Keizer et al, the struggles of MIPD from bench-to-bedside involves the many workflow steps as described in Figure 1 ( 28 ).…”

Continuous Learning in Model‐Informed Precision Dosing: A Case Study in Pediatric Dosing of Vancomycin

“…Pharmacokinetic (PK) models have been brought to the point of care, aided by development and deployment of software tools that allow clinicians to estimate their patients’ PK parameters and simulate dosing regimens 1–3 . Preliminary studies suggest that this model‐informed precision dosing (MIPD) facilitates attainment of therapeutic targets, reduces drug‐induced adverse events, and improves clinical outcomes 4–6 .…”