Concordance between Self-Reports and Medicare Claims among Participants in a National Study of Chronic Disease Self-Management Program.
OBJECTIVE
To evaluate the concordance between self-reported data and variables obtained from Medicare administrative data in terms of chronic conditions and health care utilization.


METHODS
Retrospective observational study.


METHODS
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 statistic (κ), and Pearson's correlation coefficient were used to evaluate concordance.


RESULTS
The two data sources had substantial agreement for diabetes and chronic obstructive pulmonary disease (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 US. Yet, caution must be taken when only one data source is available for other types of chronic conditions and health care utilization.
Department of Epidemiology, School of Medicine, University of California Irvine , Irvine, CA , USA ; Department of Epidemiology and Biostatistics, School of Public Health, Texas A&M Health Science Center , College Station, TX , USA.
Luohua
L
Jiang
Department of Epidemiology and Biostatistics, School of Public Health, Texas A&M Health Science Center , College Station, TX , USA.
Ben
B
Zhang
Department of Health Promotion and Behavior, College of Public Health, University of Georgia , Athens, GA , USA.
Matthew Lee
ML
Smith
Department of Health Policy and Management, School of Public Health, Texas A&M Health Science Center , College Station, TX , USA.
Andrea L
AL
Lorden
Department of Health Policy and Management, School of Public Health, Texas A&M Health Science Center , College Station, TX , USA.
Tiffany A
TA
Radcliff
Division of Immunology and Rheumatology, Department of Medicine, Stanford University , Stanford, CA , USA.
Kate
K
Lorig
CVS Health , Baltimore, MD , USA.
Benjamin L
BL
Howell
Center for Healthy Aging, National Council on Aging , Washington, DC , USA.
Nancy
N
Whitelaw
Department of Health Promotion and Community Health Sciences, School of Public Health, Texas A&M Health Science Center , College Station, TX , USA.
Marcia G
MG
Ory
aging; chronic disease; claims data; disease management; health services