Demand-Side Factors Associated with the Purchase of Long-Term Care Insurance
-
Mark A. Unruh
,
David G. Stevenson
Abstract
Demand-side barriers are known to be important toward explaining the limited purchase of private long-term care insurance (LTCI). In this study, we examine several factors associated with the demand for LTCI including the availability of less costly substitutes (e.g., Medicaid, family), consumer information, and risk perception. Using buyer surveys from 2000, 2005, and 2010, our results suggest that, among individuals not eliminated through medical underwriting, consumer risk perception and the presence of lower cost, imperfect substitutes are strongly associated with the limited purchase of LTCI. These factors were also predictive of the generosity of coverage purchased. If policymakers seek to stimulate demand for LTCI, new public policies might include Medicaid reform, integrating LTCI with Medicare Advantage plans, enhanced LTCI offerings through employers, and targeted informational campaigns.
Acknowledgments
We are thankful for grant support from the National Institute on Aging (R01 AG041109-01). Dr. Cohen is employed by LifePlans, Inc. and Dr. Unruh reports consulting fees from NaviHealth. No other authors report any potential conflicts of interest.
Appendix
Survey Methodology.
| Survey population | Buyers | Non-buyers |
|---|---|---|
| Survey instrument utilized | Mail survey | Mail survey |
| 2000 study | Individuals who had purchased a policy in late 1999 to early 2000, paid premiums, and did not return the policy within 30 days. | Individuals who had been approached by an agent or who had attended a sales seminar and been presented with the details of a policy or policies but who had chosen not to buy a policy. |
| 2005 study | Individuals who had purchased a policy in 2005, paid premiums, and did not return the policy within 30 days. | Individuals who had been approached by an agent or who had attended a sales seminar and been presented with the details of a policy or policies but who had chosen not to buy a policy. Additionally, individuals who had chosen a policy, paid the initial premium, but decided not to take the policy during the 30-day free look period. |
| 2010 study | Individuals who had purchased a policy in 2010, paid premiums, and did not return the policy within 30 days. | Individuals who had been approached by an agent or who had attended a sales seminar and been presented with the details of a policy or policies but who had chosen not to buy a policy. Additionally, individuals who had chosen a policy, paid the initial premium, but decided not to take the policy during the 30-day free look period. |
A general population survey that was conducted on a stratified random sample of 500 people was not included in data provided to the research team.
Characteristics of Non-Respondents for Each Survey Wave.
| LTCI buyers | 2000 | 2005 | 2010 | |||
|---|---|---|---|---|---|---|
| Respondents | Non-respondents | Respondents | Non-respondents | Respondents | Non-respondents | |
| Mean age | 65.7 | 65.1 | 61.6 | 59.9 | 61.9 | 58.2 |
| Female | 56% | 57% | 58% | 57% | 58% | 57% |
We do not have data on non-respondents among non-buyers. Response Rates for 1990, 1995 and 2000 survey were between 50% and 70% for buyers and 30%–40% for non-buyers. In 2005 and 2010, response rates dropped to around 23% for buyers and 9% for non-buyers.
Characteristics of Buyers and Non-Buyers in Each Survey Wave.
| 2000 | 2005 | 2010 | |||||||
|---|---|---|---|---|---|---|---|---|---|
| Buyer | Non-buyer | p-Value | Buyer | Non-buyer | p-Value | Buyer | Non-buyer | p-Value | |
| Demographics | |||||||||
| Male | 43.36% | 40.64% | 0.2854 | 41.82% | 50.00% | 0.0324 | 42.53% | 43.27% | 0.7954 |
| Married | 71.63% | 63.62% | 0.0013 | 100% | 100% | – | 100% | 100% | – |
| Age <50 | 2.00% | 4.03% | 0.0372 | 6.37% | 6.31% | 0.9761 | 8.31% | 5.43% | 0.0341 |
| Age 50–64 | 40.74% | 24.38% | <0.0001 | 58.00% | 47.57% | 0.0062 | 53.18% | 42.64% | 0.0002 |
| Age 65–74 | 42.15% | 38.48% | 0.1433 | 28.29% | 31.07% | 0.4285 | 31.88% | 28.17% | 0.1514 |
| Age 75 or older | 15.12% | 33.11% | <0.0001 | 7.34% | 15.05% | 0.0035 | 6.63% | 23.77% | <0.0001 |
| Highest education: HS grad | 5.28% | 8.22% | 0.0372 | 5.80% | 8.37% | 0.2145 | 6.45% | 7.67% | 0.4177 |
| Highest education: Vocational/Tech school | 15.96% | 19.48% | 0.0872 | 16.95% | 21.18% | 0.1713 | 16.08% | 23.81% | 0.0013 |
| Highest education: Any college | 60.48% | 38.97% | <0.0001 | 63.07% | 52.71% | 0.0068 | 66.28% | 43.39% | <0.0001 |
| Are you/spouse currently working? | 42.59% | 20.99% | <0.0001 | 64.88% | 53.96% | 0.0043 | 61.04% | 36.63% | <0.0001 |
| Potential substitutes | |||||||||
| Children living within 25 miles | 55.80% | 61.56% | 0.0233 | 56.24% | 58.91% | 0.4795 | 53.74% | 56.88% | 0.2737 |
| Income <$35k | 26.17% | 58.58% | <0.0001 | 48.11% | 68.00% | <0.0001 | 12.67% | 38.97% | <0.0001 |
| Income $35k to <$75k | 43.52% | 30.87% | <0.0001 | 28.91% | 16.00% | 0.0001 | 32.62% | 37.54% | 0.0897 |
| Income $75k or more | 30.31% | 10.55% | <0.0001 | 22.98% | 16.00% | 0.035 | 54.71% | 23.50% | <0.0001 |
| Assets <$50k | 16.56% | 40.85% | <0.0001 | 24.07% | 40.16% | 0.0006 | 12.67% | 43.88% | <0.0001 |
| Assets $50k to <$100k | 10.48% | 15.49% | 0.0141 | 11.54% | 7.09% | 0.0789 | 32.62% | 11.04% | <0.0001 |
| Assets $100k to <$150k | 10.02% | 9.86% | 0.9258 | 15.60% | 9.45% | 0.0333 | 31.89% | 10.45% | <0.0001 |
| Assets $150k or more | 26.49% | 33.80% | 0.0106 | 48.79% | 100% | <0.0001 | 22.83% | 10.25% | <0.0001 |
| Consumer information | |||||||||
| Do not know monthly cost of a NH | 9.77% | 12.13% | 0.1595 | 11.13% | 16.26% | 0.0645 | 9.97% | 16.62% | 0.0014 |
| Ever cared for elderly friend/relative? | 49.04% | 59.35% | <0.0001 | 51.79% | 55.67% | 0.3083 | 51.15% | 57.87% | 0.0195 |
| Have you/relative/friend needed NH care before? | 75.43% | 74.94% | 0.829 | 77.60% | 76.96% | 0.8421 | 80.01% | 80.42% | 0.8593 |
| Risk perception | |||||||||
| Believe government pays for NH or HHC? | 14.59% | 31.31% | <0.0001 | 11.58% | 22.66% | 0.0004 | 11.08% | 30.95% | <0.0001 |
| Compared to others are you in good/excellent health? | 92.77% | 75.12% | <0.0001 | 92.49% | 85.57% | 0.0085 | 95.46% | 72.41% | <0.0001 |
| Believe 50+ %chance of needing NH care, HHC, AL later? | 81.22% | 70.40% | <0.0001 | 81.72% | 69.85% | 0.0007 | 79.73% | 79.53% | 0.9312 |
| It is important to plan for future now? | 99.03% | 91.42% | <0.0001 | 98.84% | 88.56% | <0.0001 | 98.52% | 92.61% | <0.0001 |
References
AHIP (2000–2010) Retirement and Long-Term Care Survey. Waltham, MA: Lifeplans Inc. for America’s Health Insurance Plans (AHIP).Suche in Google Scholar
AHIP (2011) Who Buys Long-Term Care Insurance 2010? A Summary of Findings from the General Population. Washington, DC: America’s Health Insurance Plans.Suche in Google Scholar
Brown, Jeffrey R. and Amy Finkelstein (2007) “Why is the Market for Long-Term Care Insurance So Small?,” Journal of Public Economics, 91(10):1967–1991.10.1016/j.jpubeco.2007.02.010Suche in Google Scholar
Brown, Jeffrey R. and Amy Finkelstein (2008) “The Interaction of Public and Private Insurance: Medicaid and the Long-Term Insurance Market,” American Economic Review, 98(3):1083–1102.10.3386/w10989Suche in Google Scholar
Brown, Jeffrey R. and Amy Finkelstein (2009) “The Private Market for Long-Term Care Insurance in the United States: A Review of the Evidence,” Journal of Risk and Insurance, 76(1):5–29.10.1111/j.1539-6975.2009.01286.xSuche in Google Scholar
Brown, Jeffrey R., Norma B. Coe and Amy Finkelstein (2006) Medicaid Crowd-Out of Private Long-Term Care Insurance Demand: Evidence from the Health and Retirement Survey. Cambridge, MA: National Bureau of Economic Research, Working Paper No. 12536.10.3386/w12536Suche in Google Scholar
Brown, Jeffrey R., Norma B. Coe and Amy Finkelstein (2007) “Medicaid Crowd-out of Private Long-Term Care Insurance Demand: Evidence from the Health and Retirement Survey.” In Tax Policy and the Economy, Volume 21. Cambridge: MIT Press, pp. 1–34.10.1086/tpe.21.20061913Suche in Google Scholar
Brown, Jeffrey R., Gopi Shah Goda and Kathleen McGarry (2012) “Long-Term Care Insurance Demand Limited by Beliefs About Needs, Concerns About Insurers, and Care Available from Family,” Health Affairs, 31(6):1294–1302.10.1377/hlthaff.2011.1307Suche in Google Scholar
Cutler, D. M. (1993) Why Doesn’t the Market Fully Insure Long-Term Care? In NBER Working Paper #4301. Cambridge, MA: National Bureau of Economic Research.10.3386/w4301Suche in Google Scholar
Davis, K. and S. R. Collins (2005) “Medicare at Forty,” Health Care Financing Review, 27(2):53–62.Suche in Google Scholar
Goda, Gopi Shah (2011) “The Impact of State Tax Subsidies for Private Long-Term care insurance on coverage and Medicaid expenditures,” Journal of Public Economics 95(7):744–757.10.3386/w16406Suche in Google Scholar
Kemper, P., H. L. Komisar and L. Alecxih (2005) “Long-Term Care Over an Uncertain Future: What Can Current Retirees Expect?,” Inquiry, 42(4):335–350.10.5034/inquiryjrnl_42.4.335Suche in Google Scholar
Lifeplans (2010) A Profile of Declined Long-Term Care Insurance Applicants: A View of Selected Socio-Demographic Characteristics. Waltham: Lifeplans Inc.Suche in Google Scholar
LifePlans Inc. (2007) Who Buys Long-Term Care Insurance: A 15-Year Study of Buyers and Non-Buyers, 1990–2005. Washington, DC: America’s Health Insurance Plans.Suche in Google Scholar
Moses, Stephen A. (2005) Aging America’s Achilles Heel: Medicaid Long-Term Care. Washington, DC: Cato Institute.Suche in Google Scholar
Moulton, B. R. (1990) “An Illustration of a Pitfall in Estimating the Effects of Aggregate Variables on Micro Units.” The Review of Economics and Statistics, 72(2):334–338.10.2307/2109724Suche in Google Scholar
Munnell, Alicia H., Anthony Webb and Francesca Golub-Sass (2009) “The National Retirement Risk Index: After the Crash.” Issue in Brief no. 22.Suche in Google Scholar
Pauly, M. (1990) “The Rational Non-purchase of Long-Term-Care Insurance.” Journal of Political Economy, 98(1):153–168.10.1086/261673Suche in Google Scholar
Webb, A. and N. Zhivan (2010) “How Much is Enough? The Distribution of Lifetime Health Care Costs.” In Center for Retirement Research at Boston College Working Paper. Chestnut Hill, MA.Suche in Google Scholar
©2016 by De Gruyter
Artikel in diesem Heft
- Frontmatter
- Articles
- Salience and Health Campaigns
- Demand-Side Factors Associated with the Purchase of Long-Term Care Insurance
- Competitive Spillovers and Regulatory Exploitation by Skilled Nursing Facilities
- Returns to Society from Investment in Cancer Research and Development
- How Effective is Population-Based Cancer Screening? Regression Discontinuity Estimates from the US Guideline Screening Initiation Ages
- Quantifying Gains in the War on Cancer Due to Improved Treatment and Earlier Detection
Artikel in diesem Heft
- Frontmatter
- Articles
- Salience and Health Campaigns
- Demand-Side Factors Associated with the Purchase of Long-Term Care Insurance
- Competitive Spillovers and Regulatory Exploitation by Skilled Nursing Facilities
- Returns to Society from Investment in Cancer Research and Development
- How Effective is Population-Based Cancer Screening? Regression Discontinuity Estimates from the US Guideline Screening Initiation Ages
- Quantifying Gains in the War on Cancer Due to Improved Treatment and Earlier Detection
