Brian V Lee1, Gary Fong2, Michael Bolaris3, Michael Neely4, Emi Minejima1, Amy Kang2, Grace Lee5, Cynthia L Gong6. 1. School of Pharmacy, University of Southern California, Los Angeles, CA, USA. 2. School of Pharmacy, Chapman University, Irvine, CA, USA; Department of Pediatrics, The Lundquist Institute, Torrance, CA, USA; Harbor-UCLA Medical Center, Torrance, CA, USA. 3. Department of Pediatrics, The Lundquist Institute, Torrance, CA, USA; Division of Pediatric Infectious Diseases, Harbor-UCLA Medical Center, Torrance, CA, USA. 4. Division of Infectious Diseases, Children's Hospital Los Angeles, Los Angeles, CA, USA; Department of Pediatrics, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Laboratory of Applied Pharmacokinetics and Bioinformatics, The Saban Research Institute, Los Angeles, CA, USA. 5. Harbor-UCLA Medical Center, Torrance, CA, USA. 6. Department of Pediatrics, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Fetal & Neonatal Institute, Division of Neonatology, Children's Hospital Los Angeles, Los Angeles, CA, USA; Schaeffer Center for Health Policy & Economics, University of Southern California, Los Angeles, CA, USA. Electronic address: gongc@usc.edu.
Abstract
OBJECTIVES: Area under the time-concentration curve (AUC) -guided dosing provides better estimates of exposure than vancomycin trough concentrations. Though clinical benefits have been reported, the costs of AUC-guided dosing are uncertain. The objective of this study was to quantify the costs of single-sample Bayesian or two-sample AUC strategies versus trough-guided dosing. METHODS: A cost-benefit analysis from the institutional perspective was conducted using a decision tree to model the probabilities and costs of acute kidney injury (AKI) associated with vancomycin administered over 48 hours up to 21+ days. Costs included vancomycin concentrations, Bayesian software and AKI hospitalization costs, and probabilities were obtained from primary literature. Robustness was assessed via both one-way and probabilistic sensitivity analyses. RESULTS: In the base-case model, two-sample AUC versus trough dosing saved an average of US$ 846 per patient encounter, and single-sample Bayesian AUC versus trough dosing saved an average of US$ 2065 per patient encounter. This translates into annual cost-savings of US$ 846 810 and US$ 2 065 720 for two-sample and single-sample Bayesian methods versus trough dosing, respectively, assuming 1000 vancomycin-treated patients per year. Assuming a budget of US$ 100 000 per year for Bayesian software, an institution would need to treat ≥41 patients with vancomycin for at least 48 hours to break even. CONCLUSIONS: There are significant institutional cost benefits using two-sample AUC or single-sample Bayesian methods over trough dosing, even after accounting for the annual costs of Bayesian programs. The potential to decrease rates of AKI, improve clinical outcomes and reduce costs to the institution strongly warrants consideration of improved dosing methods for vancomycin.
OBJECTIVES: Area under the time-concentration curve (AUC) -guided dosing provides better estimates of exposure than vancomycin trough concentrations. Though clinical benefits have been reported, the costs of AUC-guided dosing are uncertain. The objective of this study was to quantify the costs of single-sample Bayesian or two-sample AUC strategies versus trough-guided dosing. METHODS: A cost-benefit analysis from the institutional perspective was conducted using a decision tree to model the probabilities and costs of acute kidney injury (AKI) associated with vancomycin administered over 48 hours up to 21+ days. Costs included vancomycin concentrations, Bayesian software and AKI hospitalization costs, and probabilities were obtained from primary literature. Robustness was assessed via both one-way and probabilistic sensitivity analyses. RESULTS: In the base-case model, two-sample AUC versus trough dosing saved an average of US$ 846 per patient encounter, and single-sample Bayesian AUC versus trough dosing saved an average of US$ 2065 per patient encounter. This translates into annual cost-savings of US$ 846 810 and US$ 2 065 720 for two-sample and single-sample Bayesian methods versus trough dosing, respectively, assuming 1000 vancomycin-treated patients per year. Assuming a budget of US$ 100 000 per year for Bayesian software, an institution would need to treat ≥41 patients with vancomycin for at least 48 hours to break even. CONCLUSIONS: There are significant institutional cost benefits using two-sample AUC or single-sample Bayesian methods over trough dosing, even after accounting for the annual costs of Bayesian programs. The potential to decrease rates of AKI, improve clinical outcomes and reduce costs to the institution strongly warrants consideration of improved dosing methods for vancomycin.
Authors: Jason A Roberts; Rinaldo Bellomo; Menino O Cotta; Birgit C P Koch; Haifa Lyster; Marlies Ostermann; Claire Roger; Kiran Shekar; Kevin Watt; Mohd H Abdul-Aziz Journal: Intensive Care Med Date: 2022-08-23 Impact factor: 41.787