Capture of biologic and biosimilar dispensings in a consortium of U.S.-based claims databases: Utilization of national drug codes and Healthcare Common Procedure Coding System modifiers in medical claims.
Medical Claim National Drug Code
biologics
biosimilars
healthcare common procedure coding system modifiers
pharmacoepidemiology
Journal
Pharmacoepidemiology and drug safety
ISSN: 1099-1557
Titre abrégé: Pharmacoepidemiol Drug Saf
Pays: England
ID NLM: 9208369
Informations de publication
Date de publication:
07 2020
07 2020
Historique:
received:
15
04
2019
revised:
17
08
2019
accepted:
18
11
2019
pubmed:
6
12
2019
medline:
27
4
2021
entrez:
6
12
2019
Statut:
ppublish
Résumé
To assess the capture of biologics (originator and biosimilar) in the Biologics and Biosimilars Collective Intelligence Consortium (BBCIC) Distributed Research Network (DRN), with a focus on medical claim National Drug Code (NDC), a new data field, and Healthcare Common Procedure Coding System (HCPCS) modifier. We conducted a repeated cross-sectional study among patients with medical and pharmacy benefits enrolled in insurance plans participating in the BBCIC DRN between 1 January 2013 and 30 September 2017. We calculated the proportion of medical claims with ≥1 NDC and identified select biologics using four different approaches: (a) specific HCPCS alone, (b) specific HCPCS and NDC, (c) non-specific HCPCS with NDC, and (d) HCPCS with modifiers (applicable to biosimilars). Numbers of dispensings were calculated for each biologic by approach and select patient and claim characteristics. More than 1.5 million eligible participants contributed approximately 4 million person-years of data, including 1.2 billion medical claims. The proportion of medical claims with ≥1 NDC increased from 1.2% in 2013 to 3.0% in 2017. Medical claim NDCs identified 39% and 28% of vedolizumab dispensed in 2014 and 2015 and 30% of Epogen/Procrit dispensed overall. Out of 26,381 filgrastim biosimilar dispensings identified, 51% had a HCPCS modifier and 12% had a medical claim NDC for Zarxio. HCPCS modifiers and medical claim NDCs were present for 38% and 3% of all infliximab biosimilars dispensed (total n = 1,244). Medical claim NDC and HCPCS modifier improves identification of select biologics without product-specific HCPCS code, thereby facilitating product-specific biologic research.
Substances chimiques
Biosimilar Pharmaceuticals
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
778-785Informations de copyright
© 2019 John Wiley & Sons, Ltd.
Références
Strom BL, Kimmel SE, Hennessy S. Pharmacoepidemiology. 5th ed. Hoboken, NJ: Wiley-Blackwell; 2012.
Centers for Medicare & Medicaid Services. Medicare Part B drug average sales price: Part B Biosimilar biological product payment and required modifiers. 2018. https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Part-B-Drugs/McrPartBDrugAvgSalesPrice/Part-B-Biosimilar-Biological-Product-Payment.html. Accessed October 23, 2018.
National Drug Code Requirement: UnitedHealthcare Commercial and UnitedHealthcare Medicare Advantage Professional and Hospital Outpatient Claims. https://www.uhcprovider.com/content/dam/provider/docs/public/claims/NDC-Requirement-FAQ.pdf. Accessed March 30, 2019.
ATFoBCI S, Baldziki M, Brown J, et al. Utilizing data consortia to monitor safety and effectiveness of biosimilars and their innovator products. J Manag Care Spec Pharm. 2015;21(1):23-34.
Mendelsohn AB, Barr CE, Brown JS, et al. Development and management of a distributed research network for evaluating real-would outcomes for originator biologics and biosimilars. J Manag Care Pharm. 2018;24(10-a suppl):S101-S102.
Levin KA. Study design III: cross-sectional studies. Evid Based Dent. 2006;7:24.
Ray WA. Evaluating medication effects outside of clinical trials: new-user designs. Am J Epidemiol. 2003;158(9):915-920.
Schneeweiss S. A basic study design for expedited safety signal evaluation based on electronic healthcare data. Pharmacoepidemiol Drug Saf. 2010;19(8):858-868.
Choudhry NK, Shrank WH, Levin RL, et al. Measuring concurrent adherence to multiple related medications. Am J Manag Care. 2009;15(7):457-464.
Curtis JR, Xie F, Chen R, et al. Identifying newly approved medications in Medicare claims data: a case study using tocilizumab. Pharmacoepidemiol Drug Saf. 2013;22(11):1214-1221.
Hoffman V, Xue F, Gardstein B, Skerry K, Critchlow CW, Enger C. Development and evaluation of an algorithm to identify users of Prolia((R)) during the early postmarketing period using health insurance claims data. Pharmacoepidemiol Drug Saf. 2014;23(9):993-998.
Fernandez-Lopez S, Kazzaz D, Bashir M, McLaughlin T. Assessment of pharmacists' views on biosimilar naming conventions. J Manag Care Spec Pharm. 2015;21(3):188-195.
Palmaro A, Boucherie Q, Dupouy J, Micallef J, Lapeyre-Mestre M. Immeasurable time bias due to hospitalization in medico-administrative databases: which impact for pharmacoepidemiological studies? Pharmacoepidemiol Drug Saf. 2017;26(5):544-553.