These calculations assume that there are no changes in spending behavior and health at ages 65 and 66, which precede the first MCBS observations of medical spending at age 67. It has been suggested that behavior at age 65 is most sensitive to insurance coverage prior to Medicare eligibility, as previously uninsured individuals seek services they were unable to afford in the preceding years (Lichtenberg 2002
; McWilliams et al. 2003
). Since the MCBS sample does not include beneficiaries in their first year of coverage, we are unable to estimate this effect. If it exists, our estimates may understate future cost savings of universal insurance coverage of the near-elderly. Similarly, because we are only able to observe behavior for a 3-year period in the MCBS, we assume that after age 70, the effects of universal insurance under Medicare “wear off.” If the health benefits continue, our estimates again understate future cost savings of universal insurance.
On the other hand, other researchers have suggested that increased longevity may not result in lower lifetime Medicare expenditures (Miller 2001
), but will only delay them. More recently, Lubitz et al. (2003)
found that Medicare beneficiaries with no functional limitations at age 70 had a life expectancy of 14.3 years and spent $136,000 over their remaining lifetime, while beneficiaries with at least one ADL limitation had a life expectancy of 11.6 years and slightly higher cumulative spending of $145,000. To the extent that health improvements produced by insurance are not “permanent,” but only constitute a delay of the onset of disease and death, our estimates may overstate lifetime cost savings. However, if end-of-life care is less costly as people age, then increased longevity may not lead to greater lifetime spending. Without a longer follow-up period, however, we are unable to evaluate these possibilities.
Our analysis is subject to a number of qualifications that could affect the precise magnitudes of the coefficients estimated and the subsequent simulation results. First, we were only able to measure insurance at 2-year intervals without knowing the exact times when insurance status may have changed. To some extent, however, measurement error in insurance coverage as an independent variable is mitigated by the fact that our IV estimation method replaces observed insurance status with predicted insurance status (Kmenta 1971
, p. 309). We were also unable to estimate our two-stage nonlinear model using a joint estimation routine, which may have caused some bias in the estimated standard errors. However, given the high significance levels of the key variables, it is unlikely that a joint estimation routine would have altered the findings substantially.
Another measurement limitation of our analysis is that exit health was not measured exactly at the time of or just before the respondent's 65th birthday. Since the HRS is conducted approximately every 2 years, respondents were either 63 or 64 at the date of their last interview before turning 65. As we controlled for age in the analyses, we do not believe that the estimates of the effect of insurance coverage on health prior to turning 65 were likely to have been biased because of the variation in the exact age at the time of the last interview.
A similar age qualification applies to the simulation sample from the MCBS, since it begins data collection for elderly beneficiaries at age 66, after people have been covered for a year. This may bias our estimates of spending downward, since it has been hypothesized that many newly eligible beneficiaries experience a spike in medical spending because of improved insurance coverage relative to their pre-65 insurance state. However, this bias would presumably affect both the baseline and simulated spending patterns for ages 67–70, and is thus unlikely to create a substantial error in the estimates of the differences in spending associated with the change in the distribution of initial health status.
As noted above, our analysis did not attempt to estimate an explicitly dynamic model of the intertemporal relationship between insurance status and health. Nor were we able to account for the possibly differential effects associated with variations in the timing of periods of uninsurance prior to turning 65. Future work, which will have the advantage of larger eligible samples, as more of the initial set of age-eligible people turns 65, may be able to address these limitations. We do not believe, however, that our simplified approach to measuring insurance coverage resulted in significant upward bias of the results.8
For example, if someone lost insurance coverage, experienced a subsequent deterioration in health, regained coverage, and had health return to the initial level, we would be likely to understate the effect of insurance on health as we measured the loss of coverage over the observation period, but not the health decline.
Finally, our analysis makes no attempt to quantify the value of the additional years of healthier life projected by our model. Recent calculations (Vigdor 2003
) of the value of improved health accruing from universal coverage for the entire nonelderly population suggest that they can be substantial. Depending on whether it is assumed that insurance affects only mortality or both mortality and morbidity, the annual value of improved health from universal health coverage was estimated to range from $65 to $130 billion, compared with an estimated annual cost of providing coverage of $34 to $69 billion (IOM 2003
, pp. 69, 104). Thus, valuing the improved health gained by the near-elderly from complete coverage would only add to the estimate of Medicare and Medicaid savings for new Medicare beneficiaries.
Implications for Policy
The primary policy implication of our research is that extending insurance coverage to all Americans between the ages of 55 and 64 would improve health (increase survival and shift people from good–fair–poor health to excellent–very good health) at age 65, and possibly reduce total short-term spending by Medicare and Medicaid for newly eligible Medicare beneficiaries, even though more people enter the program because of increased survival. The various sensitivity tests we conducted suggest that the precise magnitudes of these effects are somewhat sensitive to the choice of functional form, exogenous identifying variables for the IV estimation, and the measurement of insurance coverage. However, all of the estimates indicate that insurance coverage has a statistically significant effect on health and that accounting for endogeneity bias increases the magnitude of the insurance effect.
The illustrative simulation of the impact of improved health at age 65 on the health care spending of new Medicare beneficiaries estimated that the potential savings to public insurance programs would be $270 million per year (in 2001 dollars) for each new group of 65-year-old Medicare beneficiaries over the first few years they are in the program. If these savings persist over the first 5 years in the program, Medicare and Medicaid would spend about $1.35 billion less for each cohort of new beneficiaries.
This estimate is significant because it represents a potential offset against the cost of expanding insurance coverage to the nonelderly uninsured. Even if our estimate of potential savings is too high, the fact that there are any savings at all is significant, because it is often thought that reducing mortality increases morbidity, with the implication that not only would more people survive to qualify for Medicare, but that they would also be in poorer health, causing Medicare expenditures to increase.
Our analysis suggests that the increased medical care use that presumably accompanies expanded insurance coverage also improves morbidity as well as reduces mortality. Fewer people reach age 65 in fair or poor health with a disability. As people in these health states are much more costly to care for under Medicare, even small reductions in the number of people in these health categories can offset higher spending because of increased numbers of people in better health states.
If expanding health insurance coverage of the nonelderly or near-elderly improves the health of those who ultimately qualify for Medicare coverage, then anticipated savings in Medicare and Medicaid spending on the elderly could provide some of the funds to cover the cost of expanding insurance coverage to the uninsured. One policy option to consider might be to lower the age of eligibility for Medicare, perhaps to age 55, and allow people to buy Medicare coverage on an actuarially fair basis, but with premium subsidies for lower income people. Potentially, some of the cost of subsidizing coverage for low-income near-elderly would be offset by lower medical spending in the years after age 65.