Despite the very large amounts spent by some individuals and households on long-term care, the market for long-term care insurance (LTCI) in the United States is not well developed. The overall goal of this project is to find the reasons why. The research is framed in the context of life-cycle models of spending that cover such health-related components as out-of-pocket spending on health care, long-term care in nursing homes, and LTCI. Two complementary modeling approaches will be employed: the first constructs a rich simulation model based on empirical estimates of initial conditions, taking into account all financial resources of the household and relevant transition rates (spending, health, mortality, long-term care status) stratified by marital status, sex and education. These estimates are used to simulate a person's risk of exhausting wealth before death, with and without LTCI. The fraction of the population for whom the risk of exhausting wealth is reduced by LTCI below some defined level would provide an estimate of the additional demand for LTCI in a market in which the participants behaved rationally to maximize their welfare. The second modeling approach will construct and estimate a dynamic programming model for married and single persons. Both models will be used to simulate the effects of different long-term care insurance policies, including the provisions of the CLASS Act. The research combines data from the Health and Retirement Study, including the detailed spending data from its supplemental study, the Consumption and Activities Mails survey, with newly collected data on consumer preferences to better understand behavioral or informational barriers (e.g., misinformation about the probabilities of nursing-home entry) to the purchase of LTCI. It also includes analyses of how individuals' information about Medicaid rules and private insurance interacts with individuals' private information about their own likelihood of needing long-term care to influence people's decisions to purchase LTCI. These results are combined with estimates of how insurance characteristics affect market penetration across subpopulations to design insurance packages that are better matched to the needs of different market segments, potentially increasing take-up rates.

Public Health Relevance

Increasing longevity accompanied with increased rates of dementia will drive up the need for long-term care. This research shows which groups in the population would benefit most from purchasing long-term care insurance, taking into account their health and their financial resources. It suggests improved policy designs that would increase take up of LTCI, increasing the chances that people will get the help they need when they can no longer live independently and reducing the financial risk related to long-term care.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Research Project (R01)
Project #
5R01AG041116-05
Application #
8892953
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Bhattacharyya, Partha
Project Start
2011-09-30
Project End
2017-06-30
Budget Start
2015-07-15
Budget End
2017-06-30
Support Year
5
Fiscal Year
2015
Total Cost
Indirect Cost
Name
Rand Corporation
Department
Type
DUNS #
006914071
City
Santa Monica
State
CA
Country
United States
Zip Code
90401
Hurd, Michael D; Michaud, Pierre-Carl; Rohwedder, Susann (2017) Distribution of lifetime nursing home use and of out-of-pocket spending. Proc Natl Acad Sci U S A 114:9838-9842