Barbara O M Claus, Delphine De Smedt, Pieter A De Cock
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ROI was calculated against AUC-based software cost. One-way and probabilistic sensitivity analyses (respectively OWSA and PSA) were performed to check for robustness.</p><p><strong>Results: </strong>In base case, an overall cost per patient of €621.0 with TDM and €543.6 with AUC-based dosing resulted in a treatment saving of €77.4 per patient when applying AUC-based dosing. This saving against the software cost (€26.9/patient) generated an ROI per patient of €1.9 per invested € in software [€1.9 (95% CI 1.6-2.2) in PSA]. Enrolling 900 AUC-based dosed patients annually translated to a net saving of €45 469. Software break-even was reached after 313 patients. 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引用次数: 0
摘要
背景:推荐使用经过验证的贝叶斯软件以auc为基础给药,作为指导床边万古霉素给药的好方法。目的:比较基于贝叶斯auc的剂量和使用稳定血浆浓度持续输注万古霉素的常规治疗药物监测(TDM)对住院的严重革兰氏阳性感染的非危重病人的治疗和万古霉素相关急性肾损伤(AKI)的成本。方法:采用决策树模型(TDM vs . auc给药)从医院角度进行投资回报率(ROI)分析,以模拟治疗成本(人员、血清采样和药物成本)、万古霉素相关AKI风险和长达14天的成本。ROI是根据基于auc的软件成本计算的。进行单向和概率敏感性分析(分别为OWSA和PSA)以检查稳健性。结果:在基本情况下,TDM患者的总成本为621.0欧元,基于auc的剂量为543.6欧元,采用基于auc的剂量时,每位患者的治疗成本为77.4欧元。相对于软件成本(26.9欧元/患者)的节省,每位患者的投资回报率为1.9欧元/软件投资欧元[PSA为1.9欧元(95% CI 1.6-2.2)]。每年有900名在auc接受药物治疗的患者入组,净节省了45 469欧元。313例患者达到软件盈亏平衡。在OWSA中,TDM患者较高的AKI风险强烈促进了正的ROI。结论:当应用万古霉素相关AKI风险、治疗和AKI成本的基本情况设置时,与传统TDM相比,基于auc的给药似乎是一种节省成本的策略。
Therapeutic drug monitoring versus Bayesian AUC-based dosing for vancomycin in routine practice: a cost-benefit analysis.
Background: AUC-based dosing with validated Bayesian software is recommended as a good approach to guide bedside vancomycin dosing.
Objectives: To compare treatment and vancomycin-associated acute kidney injury (AKI) costs between Bayesian AUC-based dosing and conventional therapeutic drug monitoring (TDM) using steady-state plasma concentrations of vancomycin administered as continuous infusion in hospitalized non-critically ill patients with severe Gram-positive infection.
Methods: A cost-benefit analysis presented as a return on investment (ROI) analysis from a hospital perspective was conducted using a decision tree model (TDM versus AUC-based dosing) to simulate treatment cost (personnel, serum sampling and drug cost), vancomycin-associated AKI risk and cost up to 14 days. ROI was calculated against AUC-based software cost. One-way and probabilistic sensitivity analyses (respectively OWSA and PSA) were performed to check for robustness.
Results: In base case, an overall cost per patient of €621.0 with TDM and €543.6 with AUC-based dosing resulted in a treatment saving of €77.4 per patient when applying AUC-based dosing. This saving against the software cost (€26.9/patient) generated an ROI per patient of €1.9 per invested € in software [€1.9 (95% CI 1.6-2.2) in PSA]. Enrolling 900 AUC-based dosed patients annually translated to a net saving of €45 469. Software break-even was reached after 313 patients. In OWSA, a higher AKI risk with TDM strongly contributed to a positive ROI.
Conclusions: AUC-based dosing appeared a cost-saving strategy compared with conventional TDM when applying base-case settings of vancomycin-associated AKI risk, treatment and AKI costs.
期刊介绍:
The Journal publishes articles that further knowledge and advance the science and application of antimicrobial chemotherapy with antibiotics and antifungal, antiviral and antiprotozoal agents. The Journal publishes primarily in human medicine, and articles in veterinary medicine likely to have an impact on global health.