How does the employer contribution for the federal employees health benefits program influence plan selection?

Health Affairs

Volumn 22, Issue 2, 2003, Pages 211-218

  Florence, Curtis S ^a   Thorpe, Kenneth E ^a  

^a EMORY UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ADULT; AGE; ARTICLE; CONSUMER; ECONOMICS; FEE; GOVERNMENT; HEALTH CARE COST; HEALTH INSURANCE; HUMAN; INSURANCE; MIDDLE AGED; MOTIVATION; ORGANIZATION AND MANAGEMENT; RISK ASSESSMENT; UNITED STATES;

ADULT; AGE FACTORS; CONSUMER SATISFACTION; EMPLOYER HEALTH COSTS; FEDERAL GOVERNMENT; FEES AND CHARGES; HEALTH BENEFIT PLANS, EMPLOYEE; HUMANS; INSURANCE SELECTION BIAS; MIDDLE AGED; MOTIVATION; RISK ADJUSTMENT; UNITED STATES; UNITED STATES GOVERNMENT AGENCIES;

EID: 0037361774     PISSN: 02782715     EISSN: 02782715     Source Type: Journal    
DOI: 10.1377/hlthaff.22.2.211     Document Type: Review

References (25)

1. For a discussion of plan choice in Medicare, see G. Wilensky and J. Newhouse, "Medicare: What's Right? What's Wrong? What's Next?" Health Affairs (Jan/Feb 1999): 92-106;
2. for private insurance, see S.M. Butler, "The Conservative Agenda for Incremental Reform," Health Affairs (Spring 1995): 150-160.
3. R. Feldman and B. Dowd, "Risk Segmentation: Goal or Problem?" Journal of Health Economics (July 2000): 499-512.
4. M. Rothschild and J. Stiglitz, "Equilibrium in Competitive Insurance Markets: An Essay in the Economics of Imperfect Information," Quarterly Journal of Economics (November 1976): 629-649. Even if plans had perfect information concerning potential enrollees, community rating would still generate some risk segmentation.
5. S. Jones, "Can Multiple Choice Be Managed to Constrain Health Care Costs?" Health Affairs (Fall 1989): 51-59;
6. and J. Robinson et al., "A Method for Risk-Adjusting Employer Contributions to Competing Health Plans," Inquiry (Summer 1991): 107-116.
7. See T. Selden, "Premium Subsidies for Health Insurance: Excessive Coverage versus Adverse Selection," Journal of Health Economics (December 1999): 709-725.
8. Five other nationally available plans are open only to certain groups, such as the Secret Service plan. We do not include these plans here.
9. Of course, one approach for managing selection within the FEHBP is to limit the variation in plan benefits (generosity). While the OPM does indeed try to compress the variation in plan generosity, the plans do differ greatly with respect to copayments and coverage of mental health and dental services and prescription drugs.
10. The 75 percent government premium payment applies to nonpostal, "general service" employees. Postal employees receive a higher premium subsidy with a higher maximum. Since we simulate the effect of changes in the subsidy cap, we focus on only general service employees.
11. M. Spence, "Product Differentiation and Performance in Insurance Markets," Journal of Public Economics (December 1978): 427-447. The Spence model takes each enrollee's health spending as given.
12. While the overall cost of insurance in the long run will theoretically be borne by the enrollee in the form of reduced wages, the marginal cost of the plan choice to the enrollee is the annual out-of-pocket premium.
13. Individual-coverage enrollees are slightly younger than family-coverage enrollees are (43.5 years versus 44.7 years) and are less likely to be male (44.9 percent for individual, compared with 66.8 percent for family enrollees).
14. A well-known feature of the conditional logit model is that it assumes the independence of irrelevant alternatives (IIA). That is, plans are assumed to be perfect substitutes, conditional on the plan characteristics controlled for in the model. We conducted a specification test on our model and found that it violated the IIA assumption. A typical way to relax this assumption is to estimate a nested logit model, where the nests are defined by the ability of enrollees to choose their own physician. See R. Feldman et al., "The Demand for Employment-Based Health Insurance," Journal of Human Resources (Winter 1989): 115-142.
15. We attempted a similar approach here but found that the nested logit model did not meet the IIA criteria within nests. Given the large number of choices in the model, other alternatives such as the multinomial probit are not computationally feasible. However, the effect of violating the IIA assumption is that the model underestimates the probability that a given choice will be made relative to any alternative. T. Amemiya, Advanced Econometrics (Cambridge: Harvard University Press, 1985), 298. Therefore, our estimates can be interpreted as being a lower-bound measure of premium-sensitivity in the FEHBP.
16. In the FEHBP, employees can enroll in the local plans if they either live or work in a list of counties that are provided in the plan brochure. These lists typically comprise the counties that are included in the Census Bureau's definition of an MSA.
17. Expected spending and age means are calculated by using the predicted probability of choosing each plan as a weight in calculated a weighted average of the statistic in question.
18. Feldman et al., "The Demand for Employment-Based Health Insurance."
19. Full regression results are available from the authors. Contact Ken Thorpe, Kthorpe@sph. emory.edu.
20. We report the predicted enrollment, cost, and age distribution from the model in order to have a consistent comparison for the simulated subsidy cap changes. The regression model predicts a slightly higher percentage of people choosing plans in the low- and high-premium categories than is observed in the raw data. However, the age distributions by category are very close to the same as those predicted by the model.
21. Our simulations slightly overestimate the share of enrollees that chose a plan in the top and bottom tier of premiums and understate the share in the middle. In the raw data, 48.2 percent chose a plan in the lowest third of premiums; 43.4 percent, in the middle third; and 8.3 percent in the top third. Our simulated average ages are similar to those in the raw data for the bottom and middle tiers (42.9 and 43.8 years, respectively). The simulations slightly understate the average age in the highest premium tier (44.4 years in the raw data).
22. To verify our simulated enrollment changes, we also performed the same analysis on people who chose family plans in the FEHBP. The subsidy cap for such plans is considerably lower in the distribution of plan premiums than it is for self-only plans (approximately the twentieth percentile of the distribution of all premiums). We found that even with a subsidy cap that is much lower in the distribution of premiums, there is little selection by age in family plans as well. The mean age of family plan enrollees in the low-cost category is 45 years; the middle category, 44.2 years; and the high-cost category, 44.2 years.
23. In a competitive labor market, such an increase in employee health insurance premiums would need to be offset by an increase in wages.
24. Estimates of the size of tax subsidy that would be required for purchasing insurance can be found in J. Gruber, "Tax Subsidies for Health Insurance: Evaluating Costs and Benefits," NBER Working Paper no. w7553 (Cambridge, Mass.: National Bureau of Economic Research, February 2000);
25. and K. Thorpe, "Incremental Approaches to Covering Uninsured Children: Design and Policy Issues," Health Affairs (July/Aug 1997): 64-78.