Beneficiary activation in the Medicare population.

OBJECTIVE: Patient activation questions from a major national Medicare survey are used to highlight characteristics of Medicare beneficiaries with low activation. We demonstrate that Medicare Current Beneficiary Survey (MCBS) data is an untapped resource for further research on patient activation within Medicare beneficiaries and programs. DATA SOURCE: Data are from the 2012 MCBS Access to Care file and include 10,650 beneficiaries. METHODS: Patient Activation levels were derived by taking the weighted average responses to the Patient Activation Supplement. Cut points for high, moderate, and low activation were assigned at +/- ½ standard deviation of the mean. Data were analyzed using SAS survey procedures. Within group comparisons were tested using chi-square tests with post hoc pairwise comparisons. Logistic regression identified predictors of low patient engagement. RESULTS: In a multiple logistic regression, beneficiary characteristics associated with low activation included Hispanic origin, being widowed or never married, select age groups, male gender, fair or poor health, difficulty with an IADL or ADLs, and having no usual source of care, with failure to complete high school as the strongest predictor (OR=2.22, p<.001). Utilization and costs were also examined in descriptive analyses. DISCUSSION: Overall, findings on the characteristics of low activation patients in the Medicare population resemble previous research. In a regression analysis, less education and no usual source of care are the strongest predictors of low activation levels in Medicare beneficiaries. The MCBS Patient Activation Supplement is a rich resource for examining patient activation in the Medicare population, and can be used for a wide range of analyses.

Ever enrolled Medicare population estimates from the MCBS Access to Care files.

OBJECTIVE: The Medicare Current Beneficiary Survey's (MCBS) Access to Care (ATC) file is designed to provide timely access to information on the Medicare population, yet because of the survey's complex sampling design and expedited processing it is difficult to use the file to make both "always-enrolled" and "ever-enrolled" estimates on the Medicare population. In this study, we describe the ATC file and sample design, and we evaluate and review various alternatives for producing "ever-enrolled" estimates. METHODS: We created "ever enrolled" estimates for key variables in the MCBS using three separate approaches. We tested differences between the alternative approaches for statistical significance and show the relative magnitude of difference between approaches. RESULTS: Even when estimates derived from the different approaches were statistically different, the magnitude of the difference was often sufficiently small so as to result in little practical difference among the alternate approaches. However, when considering more than just the estimation method, there are advantages to using certain approaches over others. CONCLUSION: There are several plausible approaches to achieving "ever-enrolled" estimates in the MCBS ATC file; however, the most straightforward approach appears to be implementation and usage of a new set of "ever-enrolled" weights for this file.