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

children clinical decision support pharmacokinetics therapeutic drug monitoring vancomycin

Journal

Frontiers in pharmacology
ISSN: 1663-9812
Titre abrégé: Front Pharmacol
Pays: Switzerland
ID NLM: 101548923

Informations de publication

Date de publication:
2020
Historique:
received: 27 12 2019
accepted: 09 04 2020
entrez: 16 5 2020
pubmed: 16 5 2020
medline: 16 5 2020
Statut: epublish

Résumé

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. To describe the hospital implementation and usage of a MIPD clinical decision support (CDS) tool for vancomycin in a pediatric population. Within an academic children's hospital, MIPD for vancomycin was implemented 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. 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.

Sections du résumé

BACKGROUND 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 OBJECTIVE
To describe the hospital implementation and usage of a MIPD clinical decision support (CDS) tool for vancomycin in a pediatric population.
METHODS METHODS
Within an academic children's hospital, MIPD for vancomycin was implemented
RESULTS 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 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.

Identifiants

pubmed: 32411000
doi: 10.3389/fphar.2020.00551
pmc: PMC7201037
doi:

Types de publication

Journal Article

Langues

eng

Pagination

551

Informations de copyright

Copyright © 2020 Frymoyer, Schwenk, Zorn, Bio, Moss, Chasmawala, Faulkenberry, Goswami, Keizer and Ghaskari.

Références

J Biomed Inform. 2009 Apr;42(2):377-81
pubmed: 18929686
J Antimicrob Chemother. 2009 May;63(5):1050-7
pubmed: 19299472
Clin Transl Sci. 2017 Nov;10(6):443-454
pubmed: 28875519
Clin Infect Dis. 2009 Aug 1;49(3):325-7
pubmed: 19569969
N Engl J Med. 2010 May 6;362(18):1698-707
pubmed: 20445181
Pediatr Infect Dis J. 2013 Apr;32(4):e155-63
pubmed: 23340565
Clin Pharmacol Ther. 2017 May;101(5):646-656
pubmed: 28182269
Ther Drug Monit. 1999 Feb;21(1):63-73
pubmed: 10051056
J Clin Pharmacol. 2018 Sep;58(9):1134-1139
pubmed: 29746714
Springerplus. 2015 Jul 19;4:364
pubmed: 26203410
Antimicrob Agents Chemother. 2014 Nov;58(11):6454-61
pubmed: 25136027
Infect Control Hosp Epidemiol. 2015 Feb;36(2):214-6
pubmed: 25633005
J Pharm Sci. 1982 Dec;71(12):1344-8
pubmed: 7153881
J Biomed Inform. 2012 Aug;45(4):726-35
pubmed: 22226933
Pediatr Infect Dis J. 2013 Oct;32(10):1077-9
pubmed: 23652479
Pediatr Infect Dis J. 2015 Jul;34(7):742-7
pubmed: 25629890
Am J Hematol. 2019 Aug;94(8):871-879
pubmed: 31106898
Clin Ther. 2010 Mar;32(3):534-42
pubmed: 20399990
Pediatrics. 2017 Jun;139(6):
pubmed: 28562258
Clin Infect Dis. 2011 Feb 1;52(3):285-92
pubmed: 21217178
Ann Pharmacother. 2015 Sep;49(9):1009-14
pubmed: 25991831
J Pharmacokinet Biopharm. 1981 Aug;9(4):503-12
pubmed: 7310648
Eur J Clin Microbiol Infect Dis. 2018 Aug;37(8):1503-1510
pubmed: 29770901
J Am Med Inform Assoc. 2018 May 1;25(5):585-592
pubmed: 29126196
EGEMS (Wash DC). 2015 Jul 09;3(2):1150
pubmed: 26290888
Br J Clin Pharmacol. 2015 Jan;79(1):85-96
pubmed: 24251868
Pharmacol Res. 2020 Apr;154:104278
pubmed: 31108184
J Biomed Inform. 2016 Dec;64:87-92
pubmed: 27693565
J Am Med Inform Assoc. 2007 Mar-Apr;14(2):141-5
pubmed: 17213487
Cochrane Database Syst Rev. 2011 Oct 05;(10):CD001452
pubmed: 21975734
Drugs Aging. 2016 Mar;33(3):169-77
pubmed: 26895454
N Engl J Med. 2003 Sep 18;349(12):1157-67
pubmed: 13679531
J Pediatric Infect Dis Soc. 2019 May 11;8(2):97-104
pubmed: 29294072
Chemotherapy. 2016;61(1):3-7
pubmed: 26555724
Clin Pharmacol Ther. 2017 Mar;101(3):368-372
pubmed: 27984653
Antimicrob Agents Chemother. 2018 Jan 25;62(2):
pubmed: 29203493
Am J Perinatol. 2014 Oct;31(9):811-21
pubmed: 24347262
Pediatr Crit Care Med. 2018 Jun;19(6):519-527
pubmed: 29533352
BMJ. 2005 Apr 2;330(7494):765
pubmed: 15767266
Clin Perinatol. 2016 Jun;43(2):375-83
pubmed: 27235214
J Am Soc Nephrol. 2009 Mar;20(3):629-37
pubmed: 19158356
Stud Health Technol Inform. 2012;180:472-6
pubmed: 22874235
Jt Comm J Qual Patient Saf. 2009 May;35(5):256-62
pubmed: 19480378
Pharmacotherapy. 2018 Dec;38(12):1174-1183
pubmed: 30362592
Clin Pharmacol Ther. 2016 Apr;99(4):405-18
pubmed: 26785109
Infect Dis Ther. 2015 Jun;4(2):187-98
pubmed: 25998107
Haemophilia. 2017 Jan;23(1):e50-e54
pubmed: 28074560
J Am Med Inform Assoc. 2014 Jan-Feb;21(1):23-6
pubmed: 23886922
J Biomed Inform. 2008 Apr;41(2):387-92
pubmed: 18029232
J Am Med Inform Assoc. 2003 Nov-Dec;10(6):523-30
pubmed: 12925543
Pediatr Infect Dis J. 2009 May;28(5):398-402
pubmed: 19295465

Auteurs

Adam Frymoyer (A)

Department of Pediatrics, Stanford University School of Medicine, Palo Alto, CA, United States.

Hayden T Schwenk (HT)

Department of Pediatrics, Stanford University School of Medicine, Palo Alto, CA, United States.

Yvonne Zorn (Y)

Department of Clinical Pharmacy, Lucile Packard Children's Hospital Stanford, Palo Alto, CA, United States.

Laura Bio (L)

Department of Clinical Pharmacy, Lucile Packard Children's Hospital Stanford, Palo Alto, CA, United States.

Jeffrey D Moss (JD)

Department of Clinical Pharmacy, Lucile Packard Children's Hospital Stanford, Palo Alto, CA, United States.

Bhavin Chasmawala (B)

Information Services, Lucile Packard Children's Hospital Stanford, Palo Alto, CA, United States.

Joshua Faulkenberry (J)

Information Services, Lucile Packard Children's Hospital Stanford, Palo Alto, CA, United States.

Srijib Goswami (S)

InsightRx, San Francisco, CA, United States.

Ron J Keizer (RJ)

InsightRx, San Francisco, CA, United States.

Shabnam Ghaskari (S)

Information Services, Lucile Packard Children's Hospital Stanford, Palo Alto, CA, United States.

Classifications MeSH