Medicare began reimbursing for outpatient diabetes self-management training (DSMT) in 2000; however, little is known about program utilization. Individuals diagnosed with diabetes in 2010 were identified from a 20% random selection of the Medicare fee-for-service population (N = 110,064). Medicare administrative and claims files were used to determine DSMT utilization. Multivariate logistic regression analyses evaluated the association of demographic, health status, and provider availability factors with DSMT utilization. Approximately 5% of Medicare beneficiaries with newly diagnosed diabetes used DSMT services. The adjusted odds of any utilization were lower among men compared with women, older individuals compared with younger, non-Whites compared with Whites, people dually eligible for Medicare and Medicaid compared with nondual eligibles, and patients with comorbidities compared with individuals without those conditions. Additionally, the adjusted odds of utilizing DSMT increased as the availability of providers who offered DSMT services increased and varied by Census region. Utilization of DSMT among Medicare beneficiaries with newly diagnosed diabetes is low. There appear to be marked disparities in access to DSMT by demographic and health status factors and availability of DSMT providers. In light of the increasing prevalence of diabetes, future research should identify barriers to DSMT access, describe DSMT providers, and explore the impact of DSMT services. With preventive services being increasingly covered by insurers, the low utilization of DSMT, a preventive service benefit that has existed for almost 15 years, highlights the challenges that may be encountered to achieve widespread dissemination and uptake of the new services.

Medicare's 5-star rating program for Medicare Advantage is associated with beneficiaries' enrollment decisions.

Findings demonstrate benefits from DSMT use, including lower health service utilization and costs. The low cost of DSMT relative to the reduction in Medicare expenditures highlights an opportunity to reduce the burden of diabetes on both individuals and the health care system.

Population-level data on obesity are difficult to obtain. Claims-based data sets are useful for studying public health at a population level but lack physical measurements. The objective of this study was to determine the validity of a claims-based measure of obesity compared to obesity diagnosed with clinical data as well as the validity among older adults who suffer from chronic disease. This study used data from the National Health and Nutrition Examination Survey 1999-2004 for adults aged ≥ 65 successfully linked to 1999-2007 Medicare claims (N = 3,554). Sensitivity, specificity, positive and negative predictive values, κ statistics as well as logistic regression analyses were computed for the claims-based diagnosis of obesity versus obesity diagnosed with body mass index. The claims-based diagnosis of obesity underestimates the true prevalence in the older Medicare population with a low sensitivity (18.4%). However, this method has a high specificity (97.3%) and is accurate when it is present. Sensitivity was improved when comparing the claim-based diagnosis to Class II obesity (34.2%) and when used in combination with chronic conditions such as diabetes, congestive heart failure, chronic obstructive pulmonary disease, or depression. Understanding the validity of a claims-based obesity diagnosis could aid researchers in understanding the feasibility of conducting research on obesity using claims data.

ObjectivesTo evaluate the concordance between self-reported data and variables obtained from Medicare administrative data in terms of chronic conditions and health care utilization.DesignRetrospective observational study.ParticipantsWe 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).MethodsSelf-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.ResultsThe 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).ConclusionEither 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.