Derivation and preliminary validation of an administrative claims-based algorithm for the effectiveness of medications for rheumatoid arthritis

Department of Medicine, University of Alabama, 510 20th Street South, FOT 805D, Birmingham, AL 35294, USA.
Arthritis research & therapy (Impact Factor: 3.75). 09/2011; 13(5):R155. DOI: 10.1186/ar3471
Source: PubMed


Administrative claims data have not commonly been used to study the clinical effectiveness of medications for rheumatoid arthritis (RA) because of the lack of a validated algorithm for this outcome. We created and tested a claims-based algorithm to serve as a proxy for the clinical effectiveness of RA medications.
We linked Veterans Health Administration (VHA) medical and pharmacy claims for RA patients participating in the longitudinal Department of Veterans Affairs (VA) RA registry (VARA). Among individuals for whom treatment with a new biologic agent or nonbiologic disease-modifying agent in rheumatic disease (DMARD) was being initiated and with registry follow-up at 1 year, VARA and administrative data were used to create a gold standard for the claims-based effectiveness algorithm. The gold standard outcome was low disease activity (LDA) (Disease Activity Score using 28 joint counts (DAS28) ≤ 3.2) or improvement in DAS28 by > 1.2 units at 12 ± 2 months, with high adherence to therapy. The claims-based effectiveness algorithm incorporated biologic dose escalation or switching, addition of new disease-modifying agents, increase in oral glucocorticoid use and dose as well as parenteral glucocorticoid injections.
Among 1,397 patients, we identified 305 eligible biologic or DMARD treatment episodes in 269 unique individuals. The patients were primarily men (94%) with a mean (± SD) age of 62 ± 10 years. At 1 year, 27% of treatment episodes achieved the effectiveness gold standard. The performance characteristics of the effectiveness algorithm were as follows: positive predictive value, 76% (95% confidence interval (95% CI) = 71% to 81%); negative predictive value, 90% (95% CI = 88% to 92%); sensitivity, 72% (95% CI = 67% to 77%); and specificity, 91% (95% CI = 89% to 93%).
Administrative claims data may be useful in evaluating the effectiveness of medications for RA. Further validation of this effectiveness algorithm will be useful in assessing its generalizability and performance in other populations.


Available from: Jeffrey R Curtis
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Observational studies, particularly those using large administrative claims databases, have become increasingly popular sources of comparative effectiveness or comparative safety research. Studies using claims data often face challenges and criticisms due to the lack of certain clinical information, such as lifestyle risk factors, disease severity, and questionable accuracy of disease diagnoses. A novel, claims-based algorithm to evaluate the clinical effectiveness of rheumatoid arthritis medications has been developed and its performance seems promising, although further validation is needed.
    Arthritis research & therapy 10/2011; 13(5):129. DOI:10.1186/ar3472 · 3.75 Impact Factor
  • Source

    Arthritis research & therapy 03/2013; 15(2):404. DOI:10.1186/ar4161 · 3.75 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Purpose of review: To provide an overview of recently published articles describing or applying newer methods for evaluating comparative effectiveness research (CER) in rheumatoid arthritis (RA). Recent findings: Historically, clinical trials in RA have compared newer therapies against placebo. Newer trials designed to increase the relevance of trial results to real-world settings include head-to-head comparisons, some that incorporate noninferiority, factorial and crossover designs. Extensions of traditional meta-analysis through network meta-analysis can combine direct and indirect evidence together and can compare multiple treatments with each other.Observational data used to support CER include disease registries, administrative claims data and electronic medical records. Pooling and linking across these data sources and applying newer epidemiologic methods to analyse such data can provide more valid inferences regarding optimal treatment regimens for RA. Summary: CER methods in RA include head-to-head clinical trials, advanced techniques to summarize and aggregate data across studies, enrich the data available in observational settings and enhance the methods used for analysis. Efforts to continue to apply and improve these methodologies will address key needs of clinicians, patients and health policy decision-makers to generate evidence regarding real-world risks and benefits.
    Current opinion in rheumatology 03/2013; 25(3). DOI:10.1097/BOR.0b013e32835fd8c0 · 4.89 Impact Factor
Show more