Year of Publication

2007

College

Martin School of Public Policy and Administration

Date Available

9-4-2014

Abstract

Due to the aging of the generation known as “Baby Boomers”, the nation is expected to witness extraordinary growth in the total population ages 65 and over. Population projections provided by the United States Bureau of the Census suggest that this segment of the population will double in size to 72 million by the year 2030. In order to prepare for the anticipated increase elderly Americans, policy officials have been analyzing the potential effects on the nation’s long-term care system. Although Baby Boomers can expect to live longer than their predecessors, as they age, it is predicted that this generation will experience dramatic increases in the incidence of chronic diseases. These health related factors, coupled with increased longevity of Baby Boomers, leads experts to contend that there will be heavy reliance on institutionalized care in the years to come.

As a result of the surge in the number of elderly individuals, Kentucky is expected to rank 14th in the number of persons age 65 and over by the year 2025. Long-term policy experts argue that this growth in the elderly population could place a strain on, or even cripple, the state’s ability to meet the health care needs of these individuals. In order to assess the state’s ability to provide access to long-term care, this report examined the state’s policy regarding the assessment nursing home bed capacity and alternative methods for estimating the future level of need for nursing home facilities. The methods analyzed in this report include: Kentucky’s Certificate of Need (CON) process, Tennessee and Mississippi population-based formulas and the development of a state-specific statistical regression methodology.

After examining the state’s CON policy regarding the establishment of nursing facility beds, it was concluded that the state policy does not lend itself to predicating future nursing home need. In an attempt to predict the needed capacity of nursing home beds in Kentucky, the two aforementioned methods were evaluated. Prior to applying the models to the state, validity assessments were made concerning the accuracy of the projections yielded by each model. The population-based formulas used by Tennessee and Mississippi were applied to all 50 states and were found to yield inaccurate results regarding the level of need for beds in a number of states. In several instances, the use of these formulas could potentially place an unnecessary financial burden on states. An empirical model was developed to account for factors that might lead to increased rates of institutionalization in Kentucky, an empirical model was developed. However, the estimated model explains 13% of the observed variation in per capita bed need. As a result of the lack of explanatory power and statistical significance of several of the independent variables used in the model, it was concluded that this model should not be applied to Kentucky in order to project the future level of bed need for Kentucky.

Given the inability of the methods presented in this report to accurately assess the future level of nursing home need, state policy makers may find it beneficial to take prudent steps toward analyzing and developing strategies to ensure that the state has the needed capacity to manage the projected increase in elderly population.

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