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Abstract Number: 924

Methods to Link a U.S. Arthritis Cohort with Medicare Administrative Claims Data

Jeffrey R. Curtis1, Lang Chen2, Timothy Beukelman3, Aseem Bharat4, Fenglong Xie5, Kenneth G. Saag6 and Elizabeth S. Delzell7, 1Rheumatology & Immunology, Univ of Alabama-Birmingham, Birmingham, AL, 2Clinical Immunology and Rheumatology, University of Alabama at Birmingham, Birmingham, AL, 3Pediatric Rheumatology, University of Alabama at Birmingham, Birmingham, AL, 4Medicine/Rheumatology, University of Alabama at Birmingham, Birmingham, AL, 5Rheumatology & Immunology, University of Alabama at Birmingham, Birmingham, AL, 6Div Clinical Immun & Rheum, Univ of Alabama-Birmingham, Birmingham, AL, 7Epidemiology, University of Alabama at Birmingham, Birmingham, AL

Meeting: 2012 ACR/ARHP Annual Meeting

Keywords: Claims data and Rheumatoid Arthritis

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Session Information

Session Title: Epidemiology and Health Services Research: Epidemiology and Outcomes of Rheumatic Disease II

Session Type: Abstract Submissions (ACR)

Background/Purpose:

Linkages between clinical and administrative data may provide a valuable resource for pharmacoepidemiologic and health services research. Objective To describe methods and validity of a linkage between a de-identified national arthritis registry and U.S. Medicare data.

Methods:

Data from 2006-9 for rheumatoid arthritis (RA) patients participating in the Consortium of Rheumatology Researchers of North America (CORRONA) was linked to Medicare (100% sample selected using ICD-9 codes).  Deterministic linkage was performed using age (in years), sex, provider identification number, and U.S. state of the CORRONA site. Medicare data were restricted to rheumatology claims or with an RA diagnosis occurring in CORRONA provider’s state. Visit dates from CORRONA were matched to Medicare visit dates. At least 1 visit date was required to match exactly.

An ‘all-visit match’ was defined when a CORRONA participant had all CORRONA visits match to all Medicare visits. If a CORRONA participant had an all-visit match to >1 Medicare beneficiary, unique matches selected to be the beneficiary with the greatest number of matched CORRONA visits.  In the event of ties, the participant was considered not matched. A fuzzy match was done for CORRONA participants without any all-visit match allowing date mismatches of +- 2 week, or +-1 digit in month, day or year.

Linkage accuracy was evaluated in a sub-cohort with more complete information (including full date of birth [DOB]); exact match on full DOB was used as a gold standard.

Results:

CORRONA participants with self-reported Medicare coverage at any time (n=9326) were identified to be matched to 32,788 Medicare beneficiaries with arthritis treated by CORRONA physicians. A total of 7,441 CORRONA participants matched exactly on at least 1 visit, and 4413 (59%) had an all-visit match to 1 or more beneficiaries; 4013 (54%) were uniquely matched with a median (IQR) of 3 (2, 6) matched visits. For those without any all-visit matches (n=3028), only 346 (11.4%) were able to achieve at least 1 all-visit match after fuzzy matching.

For the 837 participants in the validation subcohort with an all-visit match to a single Medicare beneficiary, match accuracy was 95% for patients with > 2 matched visits, 87% for patients with exactly 2 matched visits, and 73% for those with exactly 1 matched visit. For additional patients who initially matched exactly on at least one but not all visit dates and achieved an all-visit match after fuzzy matching (n=162), linkage accuracy was < 15%. Ongoing work is refining the linkage strategy for resolution of ties and improvement of matching validity and to expand the validation sample

Conclusion:

A novel linkage between a national, de-identified outpatient arthritis registry and U.S. Medicare claims data on multiple non-unique identifiers appears both feasible and valid.


Disclosure:

J. R. Curtis,

Roche/Genetech, UCB, Centocor, CORRONA, Amgen Pfizer, BMS, Crescendo, Abbott,

5,

Roche/Genetech, UCB, Centocor, CORRONA, Amgen Pfizer, BMS, Crescendo, Abbott,

2;

L. Chen,
None;

T. Beukelman,

Pfizer Inc,

2,

Novartis Pharmaceutical Corporation,

5,

Genentech and Biogen IDEC Inc.,

5;

A. Bharat,
None;

F. Xie,
None;

K. G. Saag,
None;

E. S. Delzell,
None.

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