|Title||Using self-reports or claims to assess disease prevalence: It's complicated.|
|Publication Type||Journal Article|
|Year of Publication||2017|
|Authors||St Clair, PA, Gaudette, É, Zhao, H, Tysinger, B, Seyedin, R, Goldman, DP|
|Keywords||Medicare linkage, Medicare/Medicaid/Health Insurance, Survey Methodology|
BACKGROUND: Two common ways of measuring disease prevalence include (1) using self-reported disease diagnosis from survey responses; (2) using disease-specific diagnosis codes found in administrative data. Because they do not suffer from self-report biases, claims are often assumed to be more objective. However, it is not clear that claims always produce better prevalence estimates.
OBJECTIVE: Conduct an assessment of discrepancies between self-report and claims-based measures for 2 diseases in the US elderly to investigate definition, selection, and measurement error issues which may help explain divergence between claims and self-report estimates of prevalence.
DATA: Self-reported data from 3 sources are included: the Health and Retirement Study, the Medicare Current Beneficiary Survey, and the National Health and Nutrition Examination Survey. Claims-based disease measurements are provided from Medicare claims linked to Health and Retirement Study and Medicare Current Beneficiary Survey participants, comprehensive claims data from a 20% random sample of Medicare enrollees, and private health insurance claims from Humana Inc.
METHODS: Prevalence of diagnosed disease in the US elderly are computed and compared across sources. Two medical conditions are considered: diabetes and heart attack.
RESULTS: Comparisons of diagnosed diabetes and heart attack prevalence show similar trends by source, but claims differ from self-reports with regard to levels. Selection into insurance plans, disease definitions, and the reference period used by algorithms are identified as sources contributing to differences.
CONCLUSIONS: Claims and self-reports both have strengths and weaknesses, which researchers need to consider when interpreting estimates of prevalence from these 2 sources.
|User Guide Notes|
|Alternate Journal||Med Care|
|PubMed Central ID||PMC5507726|
|Grant List||P30 AG024968 / AG / NIA NIH HHS / United States |
P30 AG043073 / AG / NIA NIH HHS / United States