Identifying newly approved medications in Medicare claims data: a case study using tocilizumab. - PubMed - NCBI
Identifying newly approved medications in Medicare claims data: a case study using tocilizumab.
Abstract
BACKGROUND:
After U.S. licensure, parenterally administered medications are identified using non-specific drug codes. Accurately identifying these medications is critical to safety and effectiveness research. Methods to identify medications prior to assignment of specific drug codes have not been well described.
OBJECTIVES:
To describe a generalized approach using non-specific drug codes to identify parenteral therapies in Medicare claims and to assess the ability of that approach to identify tocilizumab (TCZ), a new biologic agent approved in 2010.
METHODS:
We used 2008-2010 Medicare data for a cohort of rheumatoid arthritis patients for algorithm development. Our algorithm classified non-specific drug codes based upon: 1) ICD9 codes; 2) unit values (i.e. dose); 3) codes for infusion/injection procedures; 4) expected versus observed total reimbursement amount and reimbursement per unit. We assessed algorithm performance by linking to an arthritis registry to examine external validity.
RESULTS:
Of 472 803 claims with non-specific drug codes, 9762 claims satisfied the TCZ algorithm. 74.3% of 9762 claims were classified as TCZ by exact unit price or allowed amount, 4.4% by unique doses, 21.3% by diagnosis code and small deviation from unit price or allowed amount. The algorithm demonstrated good performance characteristics: sensitivity 94% (95% CI 80-99), specificity 100% (99-100) and PPV 97% (84-100).
CONCLUSION:
Claims-based algorithms in Medicare or similar data systems can accurately identify newly approved biologics administered parenterally prior to the assignment of specific drug codes.
Copyright © 2013 John Wiley & Sons, Ltd.
KEYWORDS:
Medicare; Part D; biologics; certolizumab; denosumab; linkage; pharmacoepidemiology; registry; rheumatoid arthritis; tocilizumab
- PMID:
- 24038595
- [PubMed - indexed for MEDLINE]
- PMCID:
- PMC3856178
Free PMC Article
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