Concordance between Self-Reports and Medicare Claims among Participants in a National Study of Chronic Disease Self-Management Program

• Main Authors: Luohua eJiang, Ben eZhang, Matthew Lee eSmith, Andrea eLorden, Tiffany eRadcliff, Kate eLorig, Benjamin Lee Howell, Marcia G Ory
• Format: Article
• Language: English
• Published: Frontiers Media S.A. 2015-10-01
• Series: Frontiers in Public Health
• Subjects: Aging; Chronic Disease; Health Services; Disease Management; claims data
• Online Access: http://journal.frontiersin.org/Journal/10.3389/fpubh.2015.00222/full

Objectives: To evaluate the concordance between self-reported data and variables obtained from Medicare administrative data in terms of chronic conditions and health care utilization. Design: Retrospective observational study. Participants: We analyzed data from a sample of Medicare beneficiaries who were part of the National Study of Chronic Disease Self-Management Program (CDSMP) and were eligible for the Centers for Medicare and Medicaid Services (CMS) pilot evaluation of CDSMP (n = 119). Methods: Self-reported and Medicare claims-based chronic conditions and health care utilization were examined. Percent of consistent numbers, kappa statistics (κ), and Pearson’s correlation coefficient were used to evaluate concordance. Results: The two data sources had substantial agreement for diabetes and COPD (κ = 0.75 and κ = 0.60, respectively), moderate agreement for cancer and heart disease (κ = 0.50 and κ = 0.47, respectively), and fair agreement for depression (κ = 0.26). With respect to health care utilization, the two data sources had almost perfect or substantial concordance for number of hospitalizations (κ: 0.69 – 0.79), moderate concordance for ED care utilization (κ: 0.45 – 0.61), and generally low agreement for number of physician visits (κ ≤ 0.31). Conclusions: Either self-reports or claim-based administrative data for diabetes, COPD, and hospitalizations can be used to analyze Medicare beneficiaries in the U.S. Yet, caution must be taken when only one data source is available for other types of chronic conditions and health care utilization.