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.


METHODS
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.


CONCLUSIONS
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.
Centers for Medicare & Medicaid Services-Office of Information Products & Data Analytics.
Jessie L
JL
Parker
Centers for Medicare & Medicaid Services-Office of Information Products & Data Analytics.
Joseph F
JF
Regan
Centers for Medicare & Medicaid Services-Office of Information Products & Data Analytics.
Jason
J
Petroski
D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D005260:Female; D006304:Health Status; D006801:Humans; D008297:Male; D017533:Marital Status; D006278:Medicare / Q000706:statistics & numerical data*; D008875:Middle Aged; D010358:Patient Participation / Q000706:statistics & numerical data*; D012737:Sex Factors; D014481:United States
Medicare; access; aging; demand; elderly; geriatrics; health care costs; utilization of services