Back to Annual Meeting Page		American Public Health Association 133rd Annual Meeting & Exposition December 10-14, 2005 Philadelphia, PA

Abstract #109724

Gerald F. Kominski, PhD¹, Jay Ripps, FSA, MAAA², Miriam Laugesen, PhD³, Robert Cosway, FSA, MAAA⁴, and Nadereh Pourat, PhD³. (1) Department of Health Services, UCLA School of Public Health, Box 951772, Los Angeles, CA 90095-1772, 310-794-2686, kominski@ucla.edu, (2) Milliam, Inc., 650 California Street, San Francisco, CA 94108, (3) Center for Health Policy Research, University of California, Los Angeles, 10911 Weyburn Ave, Suite 300, Los Angeles, CA 90024, (4) Milliman, Inc., 9255 Towne Centre Drive, Suite 900, San Diego, CA 92121

Research Objective: To develop a model for estimating financial impacts of proposed health insurance benefit mandates introduced in the California legislature.

Study Design/Methods: Using three primary data sets (The California Health Interview Survey, the Health Research and Education Trust's California Employer Health Benefits Survey, health care cost guidelines and claims data compiled by Milliman), we developed a cost and coverage model to produce baseline estimates of California's insured population, grouped by insurer and type of coverage (HMO, PPO, POS, FFS), and the average expenditures for each group, including insurance premiums and out-of-pocket expenditures. We then estimate changes in the covered population affected by a mandate and changes in utilization resulting from the mandate to produce estimates of the overall change in total expenditures, including both insurance premiums and out-of-pocket expenditures.

Population Studied: California's privately insured population (n=16,261,000). The specific population studied varies by mandate based on the treatment mandated and the covered populations affected by the mandate.

Principal Findings: (1) To date, the estimated impact of the seven mandates examined as part of this project on per-member per-month (PMPM) expenditures among insured Californians has been very small, usually less than 0.1%. (2) The impact is low in most cases because coverage of mandated benefits is already high. (3) The impact varies by market segment, with low impact for most large employer groups and a greater impact on small employer groups. (4) Mandates have a greater impact on the individual market, and particularly affects some subgroups within the individual market who may face substantial premium increases resulting from proposed mandates, however.

Conclusion: Our model is the first comprehensive effort to develop an “open source” model by actuaries and health services researchers to estimate the effects of health insurance benefit mandates for different types of insurers and for different employer firm sizes and individuals. Benefit mandates are not necessarily costly, but their impact is much greater in the individual market.

Policy Implications: When making policy on mandates, policymakers should consider the differential impact among individuals and groups, rather than ‘averaging' costs. Analysis of financial impacts of proposed state health benefit mandates, combined with analyses of evidence of medical effectiveness and public health impacts produced as part of this project, provides state legislators with evidence-based information for public decision making.

Learning Objectives:

• Describe our model and process for examining the financial impacts of legislative proposals for health insurance benefit mandates.

Keywords: Economic Analysis, Policy/Policy Development

Related Web page: www.chbrp.org/index.html

Presenting author's disclosure statement:

I wish to disclose that I have NO financial interests or other relationship with the manufactures of commercial products, suppliers of commercial services or commercial supporters.

Recorded presentation