A HEALTHCARE SETTING TRANSITION MODEL FOR WISCONSIN MEDICAID LONG TERM CARE POPULATION

Purpose:

To improve the budget and healthcare facility planning for the Medicaid population, a better understanding of recipients’ healthcare setting transition is required as recipients’ healthcare setting is highly correlated with their actual healthcare expenditure.

Data:

The target population for this study were the Wisconsin managed Family Care program enrollees aged 60 and over from 2008 to 2010 (N=19,424).

Methods:

Recipients’ living situations were recorded in Wisconsin Long Term Care Functional Screen (WI-LTC-FS) and can be categorized into four types: Home-Alone, Home-With someone, community assisted living and skilled nursing facilities. Given a starting living situation, predictor candidates that were selected to predict future living situation were starting monthly capitation rate level, gender, age, and predicted future monthly capitation rate level based on maximum likelihood test. This research applied the Family Care capitation regression formula developed by PricewaterhouseCoopers on individuals’ WI-LTC-FS values to estimate capitation rate level from A to E, where A (<$1,050) is lowest and E (>$3,050) is the highest. This study used the relationship between current and future capitation levels which are improvement (lower than last year), impairment (higher than last year), and remained same as a potential predictor instead of future capitation rate level alone. Age and capitation rate level were coded cumulatively to solve spare data issues and provide a parsimonious parametric transition model.

Results:

Ages 60-72 female individuals with starting lowest capitation rate level living in nursing homes were more likely to move to community assisted living or home than to stay in a nursing home. The individuals in the lowest capitation rate group were more capable of recovering as they are considered relatively healthy, and the reasons they stayed in nursing homes may be temporary conditions. The probability of females staying at home with a helper was smaller than males, and females were more likely to be admitted to community assisted living or nursing homes. Since life expectancy of females is higher than males, males were more likely to receive care from their spouses. It is also unlikely that recipients with highest capitation rate level live at home without helpers across all age groups and both genders.

Conclusion:

The living arrangement was highly correlated to individuals’ independence; it was also correlated to recipients’ capitation rate level, gender and age