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The magnitude and nature of risk selection in employer-sponsored health plans

Authors :
M. Kate Bundorf
Rebecca M. Stein
Sean Nicholson
Daniel Polsky
Source :
Health services research. 39(6 Pt 1)
Publication Year :
2004

Abstract

Managed care health plans currently cover about 90 percent of the people who receive employer-sponsored health insurance. The extent to which managed care plans disproportionately enroll low-risk relative to high-risk individuals has been a major concern from a policy perspective. Managed care plans may either be inherently more attractive to low- than high-risk enrollees or they may be more likely to design their plans to attract low-risk and repel high-risk enrollees. A number of studies have shown that Medicare HMOs attract a disproportionate share of the healthy elderly population (Eggers 1980; Eggers and Prihoda 1982; Brown et al. 1993; Cox and Hogan 1997; Call et al. 1999). Unlike the Medicare risk selection studies that are national in scope, most studies of risk selection in the employer-sponsored health insurance market examine single employers or employer coalitions, and the available evidence is mixed. Cutler and Zeckhauser (1998) found substantial favorable risk selection among state government employees in Massachusetts for the HMO plan relative to the fee-for-service plan. Altman, Cutler, and Zeckhauser (2003), examining the same dataset, find that almost half of the expenditure difference between indemnity and HMO plans for eight medical conditions is due to a lower incidence rate among HMO patients (favorable risk selection), with the remaining difference due to lower provider reimbursement. In contrast, the RAND Health Insurance Experiment did not find that a Seattle HMO experienced a favorable selection of patients (Manning, Newhouse, and Duan 1987), and Polsky and Nicholson (2004) conclude that HMOs in 60 metropolitan areas were not experiencing favorable selection with respect to non-HMOs in 1996 and 1997. Risk selection occurs when a certain type of health plan attracts a disproportionate share of enrollees with relatively low (or high) expected medical costs. Risk selection between managed care and nonmanaged care plans may reflect differences between low- and high-risk individuals in their preferences for a style of health care. In this case, risk selection is not necessarily inefficient. However, if premiums are not risk-adjusted to reflect the expected utilization of enrollees, health plans will have incentives to attract and retain relatively low-risk enrollees. In this case, risk selection may be inefficient with too few people in nonmanaged care plans (Cutler and Zeckhauser 1998). Eighty percent of the non-elderly who had health insurance in 1999 received it from their employer or from a family member's employer.1 In the employer-sponsored market, inefficient risk selection may occur because only 1 percent of U.S. employers adjust the premium payment to a health plan based on an employee's risk, or expected medical expenditures (Keenan et al. 2001).2 As a result, most health insurance companies receive the same revenue for enrolling a young healthy worker as an old sick worker, although the expected medical costs of the two workers could differ substantially. If health insurers design their plans to attract the relatively profitable, low-risk enrollees, an inefficient allocation of individuals to plans may result. A plan that attracts low-risk enrollees can charge a lower premium than a plan attracting high-risk enrollees. As a result, some people who would enroll in a relatively expensive plan (usually a non-HMO) if premiums were risk-adjusted to reflect their unique expected costs, will enroll instead in a less expensive plan (often an HMO) once the premium difference becomes sufficiently large (Cutler and Zeckhauser 1998). Even though few firms formally risk-adjust premium payments to health plans, risk selection may not be creating substantial inefficiencies. An estimated 20 percent of the employer-sponsored market is enrolled in self-insured plans where health insurance companies usually receive a fixed payment per employee to administer the plans and do not bear the financial risk of uncertain medical expenditures (McDonnell and Fronstin 1999; InterStudy 2000). Furthermore, about 50 percent of the people insured in the employer-sponsored market were offered a plan or a choice of plans from a single insurance carrier (Keenan et al. 2001). In these two situations health insurers have no incentive to design plans to attract low-risk employees. Some firms may also be implementing implicit (to the analyst) risk adjustment by setting the employer's contribution for plans experiencing adverse selection higher than the employer's contribution for plans experiencing favorable risk selection. Such behavior would encourage employees to enroll in the plan experiencing unfavorable selection. With the exception of Polsky and Nicholson (2004), all of the studies cited above that examine risk selection of HMOs in the non-elderly, employer-sponsored market are case studies of a single employer or employer coalition in a single market. Since many employers have instituted measures to mitigate incentives for health plans to target low-risk enrollees, the results from the case studies mentioned above may not be representative of national conditions. In this paper we examine whether HMO plans experience favorable risk selection in the employer-sponsored market by applying a “switcher” methodology to the Community Tracking Study Household Survey (CTSHS), a recently released national, panel dataset of enrollees in employer-sponsored health plans. The switcher methodology compares medical expenditures in the initial year for people who chose to switch from a non-HMO (a fee-for-service indemnity plan or a preferred provider organization) to an HMO plan versus the expenditures in the initial year for the people who remained in the non-HMO plan both years (and likewise for people who initially were enrolled in an HMO). By applying this methodology to a household survey rather than an employer-based survey, we are able to include switches that occur when people change employers. Finally, to provide a practical test of whether a simple risk-adjustment system can equate premiums with the associated costs of an enrollee, we further decompose risk selection into a component based on enrollee characteristics that health plans and employers clearly observe (e.g., gender and age) and a component based on enrollee characteristics that are more difficult to observe (e.g., preferences for medical care or health status). This decomposition will help determine whether risk-adjusting individual enrollee premiums based on easily observed characteristics is likely to minimize or eliminate the inefficiency associated with risk selection. We find that HMOs are experiencing favorable selection and that this selection would probably persist even if employers adjusted premiums based on an enrollee's gender and age. People who switched from a non-HMO to an HMO plan used 11 percent fewer medical services in the period prior to switching than people who remained in non-HMO plans, and this relatively low use persists once they enroll in an HMO, relative to those already enrolled in an HMO. We also find that people who switched from an HMO to a non-HMO plan used 18 percent more medical services in the period prior to switching than people who remained in the HMO plan. This relatively high use rate does persist once they enroll in the non-HMO, but the differential is not statistically significant. Ten percent of HMO enrollees switched to a non-HMO between the first and second round of the CTSHS survey, and their departure is predicted to reduce an HMO's aggregate medical expenditures by 2.0 percent per year. Favorable risk selection by HMOs would most likely persist even if employers adjusted health plan payments based on enrollees' gender and age, because the selection appears to occur based on enrollee characteristics that are difficult to observe, such as preferences for medical care and health status.

Details

ISSN :
00179124
Volume :
39
Issue :
6 Pt 1
Database :
OpenAIRE
Journal :
Health services research
Accession number :
edsair.doi.dedup.....a1267243ff9eeb75cfaf3ac38de4e31c