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

被引:45
|
作者
Frymoyer, Adam [1 ]
Schwenk, Hayden T. [1 ]
Zorn, Yvonne [2 ]
Bio, Laura [2 ]
Moss, Jeffrey D. [2 ]
Chasmawala, Bhavin [3 ]
Faulkenberry, Joshua [3 ]
Goswami, Srijib [4 ]
Keizer, Ron J. [4 ]
Ghaskari, Shabnam [3 ]
机构
[1] Stanford Univ, Sch Med, Dept Pediat, Palo Alto, CA 94304 USA
[2] Lucile Packard Childrens Hosp Stanford, Dept Clin Pharm, Palo Alto, CA USA
[3] Lucile Packard Childrens Hosp Stanford, Informat Serv, Palo Alto, CA USA
[4] InsightRx, San Francisco, CA USA
关键词
vancomycin; children; pharmacokinetics; clinical decision support; therapeutic drug monitoring; CLINICAL DECISION-SUPPORT; STAPHYLOCOCCUS-AUREUS INFECTIONS; DISEASES SOCIETY; DATA-ENTRY; GUIDELINES; SYSTEM; HYPERBILIRUBINEMIA; CHALLENGES; EVOLUTION; PHARMACY;
D O I
10.3389/fphar.2020.00551
中图分类号
R9 [药学];
学科分类号
1007 ;
摘要
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 implementedviaa 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 patient-courses (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 feature that helped them complete tasks more efficiently; 81% agreed or strongly agreed that they were satisfied with the CDS tool. Conclusions Integration of a vancomycin CDS tool within the EHR, along with leveraging the expertise of clinical pharmacists, allowed for successful adoption of MIPD in clinical care.
引用
收藏
页数:13
相关论文
共 50 条
  • [21] How promising is model-informed precision dosing in tamoxifen therapy?
    Klopp-Schulze, Lena
    Joerger, Markus
    Kloft, Charlotte
    INTERNATIONAL JOURNAL OF CLINICAL PHARMACY, 2018, 40 (01) : 220 - 221
  • [22] Model-Informed Artificial Intelligence: Reinforcement Learning for Precision Dosing
    Ribba, Benjamin
    Dudal, Sherri
    Lave, Thierry
    Peck, Richard W.
    CLINICAL PHARMACOLOGY & THERAPEUTICS, 2020, 107 (04) : 853 - 857
  • [23] Model-Informed Reinforcement Learning for Enabling Precision Dosing Via Adaptive Dosing
    Tosca, Elena Maria
    De Carlo, Alessandro
    Ronchi, Davide
    Magni, Paolo
    CLINICAL PHARMACOLOGY & THERAPEUTICS, 2024, 116 (03) : 619 - 636
  • [24] Model-Informed Precision Dosing at the Bedside: Scientific Challenges and Opportunities
    Keizer, Ron J.
    ter Heine, Rob
    Frymoyer, Adam
    Lesko, Lawrence J.
    Mangat, Ranvir
    Goswami, Srijib
    CPT-PHARMACOMETRICS & SYSTEMS PHARMACOLOGY, 2018, 7 (12): : 785 - 787
  • [25] Model-informed precision dosing: State of the art and future perspectives
    Minichmayr, I. K.
    Dreesen, E.
    Centanni, M.
    Wang, Z.
    Hoffert, Y.
    Friberg, L. E.
    Wicha, S. G.
    ADVANCED DRUG DELIVERY REVIEWS, 2024, 215
  • [26] Pharmacokinetic Model-Informed Precision Dosing of Natalizumab in Multiple Sclerosis
    van den Berg, Stefan P. H.
    Toorop, Alyssa A.
    Hooijberg, Femke
    Wolbink, Gertjan
    Voelkner, Nivea M. F.
    Gelissen, Liza M. Y.
    Killestein, Joep
    van Kempen, Zoe L. E.
    Dorlo, Thomas P. C.
    Rispens, Theo
    CPT-PHARMACOMETRICS & SYSTEMS PHARMACOLOGY, 2025,
  • [27] Pharmacokinetic equations versus Bayesian guided vancomycin monitoring: Pharmacokinetic model and model-informed precision dosing trial simulations
    Aljutayli, Abdullah
    Thirion, Daniel J. G.
    Bonnefois, Guillaume
    Nekka, Fahima
    CTS-CLINICAL AND TRANSLATIONAL SCIENCE, 2022, 15 (04): : 942 - 953
  • [28] Developing Parametric and Nonparametric Models for Model-Informed Precision Dosing: A Quality Improvement Effort in Vancomycin for Patients With Obesity
    Hughes, Maria-Stephanie A.
    Hughes, Jasmine H.
    Endicott, Jeffrey
    Langton, Meagan
    Ahern, John W.
    Keizer, Ron J.
    THERAPEUTIC DRUG MONITORING, 2024, 46 (05) : 575 - 583
  • [29] AUC-based monitoring and model-informed precision dosing of vancomycin in critically ill patients: why and how?
    Goutelle, Sylvain
    Wallet, Florent
    Thoma, Yann
    Peclard, Jean-Remix
    Bourguignon, Laurent
    Cohen, Sabine
    Kipnis, Eric
    Roberts, Jason
    Allaouchiche, Bernard
    Friggeri, Arnaud
    ANAESTHESIA CRITICAL CARE & PAIN MEDICINE, 2023, 42 (06)
  • [30] Model-Informed Vancomycin Dosing Optimization to Address Delayed Renal Maturation in Infants and Young Children with Critical Congenital Heart Disease
    Shimamoto, Yuko
    Fukushima, Keizo
    Mizuno, Tomoyuki
    Ichikawa, Hajime
    Kurosaki, Kenichi
    Maeda, Shinichiro
    Okuda, Masahiro
    CLINICAL PHARMACOLOGY & THERAPEUTICS, 2024, 115 (02) : 239 - 247