Jiang Luohua, Zhang Ben, Smith Matthew Lee, Lorden Andrea L, Radcliff Tiffany A, Lorig Kate, Howell Benjamin L, Whitelaw Nancy, Ory Marcia G
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.
Department of Epidemiology and Biostatistics, School of Public Health, Texas A&M Health Science Center , College Station, TX , USA.
Front Public Health. 2015 Oct 8;3:222. doi: 10.3389/fpubh.2015.00222. eCollection 2015.
To evaluate the concordance between self-reported data and variables obtained from Medicare administrative data in terms of chronic conditions and health care utilization.
Retrospective observational study.
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).
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.
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).
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.
评估自我报告数据与从医疗保险行政数据中获取的慢性病及医疗保健利用情况变量之间的一致性。
回顾性观察研究。
我们分析了医疗保险受益人的样本数据，这些受益人是全国慢性病自我管理项目（CDSMP）的一部分，并且有资格参与医疗保险和医疗补助服务中心（CMS）对CDSMP的试点评估（n = 119）。
对自我报告的和基于医疗保险理赔记录的慢性病及医疗保健利用情况进行了检查。使用一致数百分比、kappa统计量（κ）和Pearson相关系数来评估一致性。
两个数据源在糖尿病和慢性阻塞性肺疾病（COPD）方面具有高度一致性（κ分别为0.75和0.60），在癌症和心脏病方面具有中度一致性（κ分别为0.50和0.47），在抑郁症方面具有一般一致性（κ = 0.26）。在医疗保健利用方面，两个数据源在住院次数上几乎完全或高度一致（κ = 0.69 - 0.79），在急诊护理利用方面具有中度一致性（κ = 0.45 - 0.61），在医生就诊次数上总体一致性较低（κ≤0.31）。
在美国，对于糖尿病、COPD和住院情况，自我报告或基于理赔记录的行政数据均可用于分析医疗保险受益人。然而，当仅有一种数据源可用于其他类型的慢性病和医疗保健利用情况时，必须谨慎使用。
