Evaluating Long-Term Care Insurance
Whether to purchase long-term care (LTC) insurance is one of the most difficult and consequential decisions a retiree will make. Because of the complexity of the products and the uncertainty of needing care, very few have attempted – as I did below – to provide an objective analysis.
I’ve written less analytically about LTC insurance and hybrid solutions for AARP, a demographic where the subject is of the utmost importance. As evidence of the contentious nature of this topic, I have no shortage of emails telling me how stupid I am.
Framework for the analysis – probabilities and net benefits
We must understand the probability of needing care and, if so, for how long and at what cost. This is a distribution curve rather than a discrete, binary “yes” or “no.” If you end up needing LTC for 100 days or less, you may pay very little. Medicare could cover most of the costs if you are admitted to a Medicare-certified nursing facility within 30 days of hospital stay of three days or longer. If you stay 10 years, however, the costs could be staggering.
All insurance companies, even mutual insurance companies, need to cover their costs (including commissions) and make a profit. Thus, the odds are that buying LTC insurance will be the “wrong” decision, in the sense that the expected benefits, net of costs (including opportunity costs one could earn if they invested the premium) will be less than zero. But that’s the same as any insurance policy. We buy insurance because the consequences of being wrong are significant. An example is a high-income earner needing term life insurance, which is likely to expire worthless, because the consequences of dying early and leaving the family exposed are just too high.
1. Approximately 56% of Americans will need at least one day of LTC but only 32% will pay anything out of pocket. The study notes the 56% needing LTC is substantially higher than previous estimates.
2. Among women, 64.1% will have some nursing home stays, versus 50.6% of men:
- Women average 301 days.
- Men average only 141 days.
3. The probability distribution with combined genders looks as follows:
- 10th percentile – 0 days
- 25th percentile – 0 days
- 50th percentile – 10 days
- 75th percentile – 240 days
- 90th percentile – 1,001 days
- 95th percentile – 1,495 days