OBJECTIVE: Linkages between registries and administrative data may provide a valuable resource for comparative effectiveness research. However, personal identifiers that uniquely identify individuals are not always available. Here we describe methods to link a de-identified arthritis registry and US Medicare data. The linked data set was also used to evaluate the generalizability of the registry to the US Medicare population. METHODS: Rheumatoid arthritis (RA) patients participating in the Consortium of Rheumatology Researchers of North America (CORRONA) registry were linked to Medicare data restricted to rheumatology claims or claims for RA. Deterministic linkage was performed using age, sex, provider identification number, and geographic location of the CORRONA site. We then searched for visit dates in Medicare matching visit dates in CORRONA, requiring ≥1 exact matching date. Linkage accuracy was quantified as a positive predictive value in a subcohort (n = 1,581) with more precise identifiers. RESULTS: CORRONA participants with self-reported Medicare (n = 11,001) were initially matched to 30,943 Medicare beneficiaries treated by CORRONA physicians. A total of 8,431 CORRONA participants matched on ≥1 visit; 5,317 matched uniquely on all visits. The number of patients who linked and linkage accuracy (from the subcohort) were high for patients with >2 visits (n = 3,458, 98% accuracy), exactly 2 visits (n = 822, 96% accuracy), and 1 visit (n = 1,037, 79% accuracy) that matched exactly on calendar date. Demographics and comorbidity profiles of registry participants were similar to nonparticipants, except participants were more likely to take disease-modifying antirheumatic drugs and biologic agents. CONCLUSION: Linkage between a national, de-identified outpatient arthritis registry and Medicare data on multiple nonunique identifiers appears feasible and valid.
OBJECTIVE: Linkages between registries and administrative data may provide a valuable resource for comparative effectiveness research. However, personal identifiers that uniquely identify individuals are not always available. Here we describe methods to link a de-identified arthritis registry and US Medicare data. The linked data set was also used to evaluate the generalizability of the registry to the US Medicare population. METHODS:Rheumatoid arthritis (RA) patients participating in the Consortium of Rheumatology Researchers of North America (CORRONA) registry were linked to Medicare data restricted to rheumatology claims or claims for RA. Deterministic linkage was performed using age, sex, provider identification number, and geographic location of the CORRONA site. We then searched for visit dates in Medicare matching visit dates in CORRONA, requiring ≥1 exact matching date. Linkage accuracy was quantified as a positive predictive value in a subcohort (n = 1,581) with more precise identifiers. RESULTS:CORRONAparticipants with self-reported Medicare (n = 11,001) were initially matched to 30,943 Medicare beneficiaries treated by CORRONA physicians. A total of 8,431 CORRONAparticipants matched on ≥1 visit; 5,317 matched uniquely on all visits. The number of patients who linked and linkage accuracy (from the subcohort) were high for patients with >2 visits (n = 3,458, 98% accuracy), exactly 2 visits (n = 822, 96% accuracy), and 1 visit (n = 1,037, 79% accuracy) that matched exactly on calendar date. Demographics and comorbidity profiles of registry participants were similar to nonparticipants, except participants were more likely to take disease-modifying antirheumatic drugs and biologic agents. CONCLUSION: Linkage between a national, de-identified outpatientarthritis registry and Medicare data on multiple nonunique identifiers appears feasible and valid.
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