Leveraging the Random Assignment of Medicaid Managed Care Plans to Study Plan Choices, Treatment Effects, and Cream Skimming
In South Carolina, the Medicaid program is administered through Managed Care Organizations (MCOs), which offer different health care plans to Medicaid beneficiaries. These plans differ in their generosity, network coverage, and other attributes, and they are ranked by the state using a system of “star ratings.” The system of MCOs offers choices to health care consumers and allows plans to compete for consumers. In South Carolina, when consumers do not make an active plan choice, the state uses an algorithm to assign plans to consumers automatically. Starting earlier this year (in 2017), this auto-assignment is now being made using an explicitly random process. We propose to use this randomized assignment feature to study the effect of plan assignment on patient outcomes such as health care utilization and health care expenditures (both overall and by category). This prospective analysis will be complemented with a retrospective analysis that takes advantage of the state’s historical quasi-random round-robin assignment procedure to allocate households to plans. Additionally, we propose to combine the analysis of the randomly assigned population with the population that made active choices to try to distinguish between treatment and selection in accounting for which plans perform better.