Online Program

Health benefits mandates and their potential effects by racial and ethnic groups: Measuring disproportionalities among insured populations

Monday, November 4, 2013 : 2:45 p.m. - 3:00 p.m.

Shana A. Lavarreda, PhD, MPP, Center for Health Policy Research, UCLA, Los Angeles, CA
Joy Melnikow, MD, MPH, UC Davis Medical Center, Sacramento, CA
Sylvia Guendelman, PhD, LCSW, School of Public Health, University of California Berkeley, Berkeley, CA
Dominique Ritley, MPH, Center for Healthcare Policy and Research, UC Davis Center, Sacramento, CA
Ninez Ponce, MPP, PhD, Department of Health Policy and Management, UCLA, Los Angeles, CA
John Lewis, MPA, California Health Benefits Review Program, Oakland, CA
Jennie Kempster, MS, Health Services Research Center, University of California, San Diego, San Diego, CA
Sophie Snyder, Department of Health Policy and Management, UCLA School of Public Health, Los Angeles, CA
Background: The effect of mandated health benefits coverage on racial/ethnic (R/E) health disparities is generally unknown. We present our method for estimating California's R/E distribution in the insured population and examine the potential implications of health insurance benefit mandates on access to care for different racial/ethnic groups. Study Design: We applied racial/ethnic information about the insured population from the 2009 California Health Interview Survey (CHIS) to the California Health Benefits Review Program (CHBRP) Costa and Coverage Model, which identifies the market segments that comprise the California health insurance market. The CHBRP model distinguishes segments in the private sector by regulator and group size; and in the public sector by type. For each R/E group, we constructed age- and gender-specific disproportionality measures by dividing the racial/ethnic distribution within each insurance market segment by the racial/ethnic distribution of the entire market. Coverage may vary considerably between these segments, thus mandates may affect segments differently. Mandated coverage for tobacco cessation treatment was used as an example. Principal Findings: Within California's insured population, R/E group representation is disproportional among the different market segments. Latinos constitute 31% of large group HMO plans, and 33% of the small group plans, but comprise 66% of nonelderly enrollees in Medicaid managed care. Non-Latino whites constitute 66% of the non-HMO individual policies, but only 45% of the large group HMO population, and 14% of the nonelderly Medi-Cal managed care group. Males (both Latino and non-Latino white) were overrepresented in large group non-HMO plans. African Americans comprised 11% of Medi-Cal managed care, but 2% of large group non-HMO plans. Mandating tobacco cessation coverage illustrate that these disproportionalities have differential impacts by R/E group. Since the individual market had the lowest rate of pre-existing coverage for tobacco cessation treatment, the projected impact of the mandate would disproportionally benefit non-Latino whites by providing more coverage that brings their insurance benefits up to par with the other market segments. Conclusions: The disproportional effects of health insurance benefit mandates on access to care by R/E can be evaluated using available demographic and health insurance market data. For the specific bill examined, the largest gains accrued to the mostly non-Latino white individual market. Because of racial/ethnic disproportionality by market segment, policymakers should be aware that benefit mandates will likely affect some market segments more than others and may have unintended consequences (both positive and negative) on R/E disparities.

Learning Areas:

Diversity and culture
Other professions or practice related to public health
Provision of health care to the public
Public health or related public policy

Learning Objectives:
Differentiate racial/ethnic groups using a combined survey/actuarial analysis approach. Analyze health benefits mandate coverage to racial/ethnic populations to ascertain disparities.

Keyword(s): Financing, Research

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I am Director of Health Insurance Studies at the UCLA Center for Health Policy Research, and a key member of the California Health Benefits Review Program. I update the annual cost model with the latest population data. I am also the Center's expert on health insurance questions in the California Health Interview Survey.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.

Back to: 3370.0: Health services research