OBJECTIVE: To examine how much pooling of risks occurs among potential purchasers in the individual market, how much pooling occurs among those who purchase coverage, and whether there is greater pooling among longer-term enrollees. DATA SOURCES: The data are administrative records for enrollees in individual insurance plans in California in 2001, and from a survey of Californians enrolled in the individual insurance market and the uninsured. STUDY DESIGN: Logit models were estimated for 5 health outcome measures to compare the insured and uninsured after adjusting for other factors that affect insurance status and health. Multivariate models were also estimated to explore the relationship between health and three measures of pooling in the market: plan type, pricing tier, and the actuarially adjusted premium paid by the enrollee. PRINCIPAL FINDINGS: Those who purchase individual health insurance are in better health than those who remain uninsured. On the other hand, a large share of people with health problems does obtain individual insurance. The distribution of subscribers across plan type and pricing tier varies with their health status. Those in poor health are less likely to purchase low benefit plans. There is less separation of risks for those who become sick after enrollment based on the measure of pricing tier. The distribution of subscribers across plan type for those who have health problems at enrollment and those who become sick differs, but so does the distribution of those who become sick and those who remain healthy. CONCLUSIONS: Despite small differences among the healthy and sick, our results support the conclusion that there is considerable risk pooling in the individual market. To some extent, this pooling occurs because underwriting happens at the time people enroll and there is greater pooling among those who become sick than those who enroll sick. Our results however suggest that health savings accounts may further fragment the market.
OBJECTIVE: To examine how much pooling of risks occurs among potential purchasers in the individual market, how much pooling occurs among those who purchase coverage, and whether there is greater pooling among longer-term enrollees. DATA SOURCES: The data are administrative records for enrollees in individual insurance plans in California in 2001, and from a survey of Californians enrolled in the individual insurance market and the uninsured. STUDY DESIGN: Logit models were estimated for 5 health outcome measures to compare the insured and uninsured after adjusting for other factors that affect insurance status and health. Multivariate models were also estimated to explore the relationship between health and three measures of pooling in the market: plan type, pricing tier, and the actuarially adjusted premium paid by the enrollee. PRINCIPAL FINDINGS: Those who purchase individual health insurance are in better health than those who remain uninsured. On the other hand, a large share of people with health problems does obtain individual insurance. The distribution of subscribers across plan type and pricing tier varies with their health status. Those in poor health are less likely to purchase low benefit plans. There is less separation of risks for those who become sick after enrollment based on the measure of pricing tier. The distribution of subscribers across plan type for those who have health problems at enrollment and those who become sick differs, but so does the distribution of those who become sick and those who remain healthy. CONCLUSIONS: Despite small differences among the healthy and sick, our results support the conclusion that there is considerable risk pooling in the individual market. To some extent, this pooling occurs because underwriting happens at the time people enroll and there is greater pooling among those who become sick than those who enroll sick. Our results however suggest that health savings accounts may further fragment the market.
Authors: Melinda Beeuwkes Buntin; José J Escarce; Kanika Kapur; Jill M Yegian; M Susan Marquis Journal: Health Aff (Millwood) Date: 2003 Jul-Dec Impact factor: 6.301