The Concordance of Chronic Conditions Between Survey Reports and Medicare Claims in Older Mexican Americans

• Activity Number: 358 - Contributed Poster Presentations: Section on Statistics in Epidemiology
• Type: Contributed
• Date/Time: Tuesday, July 30, 2019 : 10:30 AM to 12:20 PM
• Sponsor: Section on Statistics in Epidemiology
• Author(s): Lin-Na Chou* and Yong-Fang Kuo and Kenneth John Ottenbacher and Soham Al Snih
• Companies: The University of Texas Medical Branch and The University of Texas Medical Branch and The University of Texas Medical Branch and The University of Texas Medical Branch
• Keywords: Concordance; chronic condition; claim data; survey; health service

Abstract

Self-reported and administrative data are two common methods to measure chronic conditions in health service research. The concordance between the two resources varies according to the condition and respondent characteristics. Several researchers have investigated the concordance between self-reports and administrative data, however, little information is available in the Hispanic population. We used the Hispanic Established Populations for the Epidemiological Study of the Elderly (Hispanic EPESE) survey and Medicare linkage data to estimate the agreement and Kappa statistics for eleven medical conditions. The measurement bias, prevalence index, and prevalence-adjusted and biased-adjusted k statistic (PABAK) are reported. Multiple logistic regression models were applied to estimate adjusted odds ratio of participant characteristics on concordant reporting. In a cohort of 1094 participants, we found that diabetes and dementia had higher Kappa statistics (K=0.67 and 0.44). Stroke, dementia, diabetes, kidney disease and emphysema had higher concordance based on PABAK (range: 0.70-0.82). Age, gender, cognitive function and global health were significant predictors of concordance.