Abstract

In 2006 Massachusetts implemented a substantial reform of its health insurance market that included a new program for uninsured individuals with income between 100% of Federal Poverty (the upper limit for state Medicaid benefits) and 300% of Federal Poverty. Enrollment was compulsory for all citizens because of a mandate. Consumers who enrolled in this program, which offered generous benefits with low copays, received graduated subsidies depending on their income. Five insurers were contracted to underwrite the program, and consumers were able to choose their insurer. Insurers bid annually, and the member contribution was set according to an affordability schedule for the lowest-bidding insurer. Consumers could choose from the range of insurers, but if they chose a plan other than the lowest cost, their contributions reflected the difference. Premiums were changed annually at July 1, and members were eligible to move to a different plan at this date; a number of members migrated each year. This study aims to quantify the effect of this premium-induced switching behavior. Prior studies of member switching behavior have looked at employer plans and estimated the elasticity of response to changes in member contributions. The Massachusetts environment is unique in that there is a mandate (so being uninsured is not an option) and members may choose insurer but not benefit plan. Thus a study of migration in Massachusetts is uniquely able to quantify the effect of price (contribution rates) on member switching behavior. We find elasticity averaging −0.21 for 2013 (the last year of the study) to be somewhat lower (in absolute value) than previous studies of employer populations. Elasticity has also been significantly increasing with time and appeared to have at least doubled over the studied period (i.e., 2008–2013). Prior studies have estimated higher elasticities in the range −0.3 to −0.6. We found that the data contained many outliers in terms of both changes in contributions and percentage of members switching plans. The effect of outliers was moderated by the choice of robust regression models, leading us to question whether other studies may have been affected by outliers, leading to overestimates of the elasticities.

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