The concordance of survey reports and Medicare claims in a nationally representative longitudinal cohort of older adults.
BACKGROUND
Concordance between survey reports and claims data is not well established. We compared them for disease histories, preventative, and other health services use in a large, nationally representative sample of older Medicare beneficiaries with special attention given to evaluating age, aging, memory, and respondent status effects.


METHODS
Baseline (1993) and biennial follow-up data (through 2010) from the Survey on Assets and Health Dynamics among the Oldest-Old were linked to Medicare claims from 1991 to 2010, for 4910 participants yielding 19,556 person-periods. Concordance was measured by simple, weighted, and prevalence and bias-adjusted κ, and Lin's concordance statistics. Generalized estimating equation negative binomial models were used to predict the summary counts of concordant reports, survey underreports, and survey overreports.


RESULTS
Concordance was highly variable overall, unacceptably low for arthritis and physician visits, and less than substantial for angina, heart disease, hypertension, and outpatient surgery. Generalized estimating equation negative binomial models revealed reductions in reporting accuracy (more underreporting and overreporting) associated with both age (interindividual) and aging (intraindividual) effects, countervailing memory effects on concordance due to less underreporting but more overreporting, and countervailing proxy-respondent effects on concordance due to less underreporting but more overreporting.


CONCLUSIONS
Further research should explore whether these findings are time or cohort bound, address the potential heterogeneity of the proxy-respondent effects based on the reason for and relationship of the proxy to the target person, and evaluate the effects of a broader spectrum of performance-based cognitive abilities. In the interim, the significant predictors identified here should be included in future studies.
Departments of *Health Management and Policy †Biostatistics College of Public Health, University of Iowa, Iowa City, IA.
Fredric D
FD
Wolinsky
Michael P
MP
Jones
Fred
F
Ullrich
Yiyue
Y
Lou
George L
GL
Wehby
D000368:Aged; D003071:Cognition; D003625:Data Collection / Q000379:methods* / Q000706:statistics & numerical data*; D005260:Female; D006296:Health Services / Q000706:statistics & numerical data; D006304:Health Status; D006306:Health Surveys / Q000706:statistics & numerical data; D006801:Humans; D007345:Insurance Claim Review / Q000706:statistics & numerical data*; D008137:Longitudinal Studies; D008297:Male; D006278:Medicare / Q000706:statistics & numerical data*; D012959:Socioeconomic Factors; D014481:United States