Excerpted From: Sidney D. Watson, Community Engagement, Public Reporting, and Financial Incentives: Lessons from Michigan on Tackling Racial and Ethnic Disparities in Medicaid Managed Care, 23 Houston Journal of Health Law & Policy 111 (2024) (179 Footnotes) (Full Document)

SidneyWatsonTwo stories set the background for this article. The first is a personal experience. The second appeared as a news report in the New York Times.

In the fall of 2021, I sat in a law school classroom as a talented health insurance enrollment counselor taught our law students how to help people fill out Medicaid applications. Our students were part of a community-led effort to find and enroll 275,000 people newly eligible for Medicaid expansion in Missouri. The enrollment counselor got to the questions on the Medicaid application asking about race and ethnicity. She looked up and said, “You can skip these questions. They are voluntary. People can leave them blank. They aren't needed to process the application.”

In the fall 2022, Max Li chose not to declare his race when it came time to fill out his college application form. Even though Max knew his last name sounded Chinese, he selected “prefer not to say.” A few months before, the Supreme Court had heard oral arguments in a case accusing Harvard and North Carolina of systematically discriminating against Asian American applicants. Max feared his race would be used against him in the college admissions process. In June 2022, the Supreme Court ruled that the colleges' admissions systems had disadvantaged and stereotyped Asian-Americans students.

This article is about Medicaid and the intertwined issues of obtaining and stratifying health care quality data by race and ethnicity for Medicaid patients. For over twenty years, the Institute of Medicine and others have recommended that state Medicaid agencies, health plans, and providers stratify health care quality measures--like prenatal care, child immunization rates, medication for diabetes--by race and ethnicity to be able to identify and remedy racial and ethnic disparities in care. For just as long, state agencies, plans, and providers have struggled with how to obtain data from Medicaid enrollees about their race and ethnicity to be able to stratify their quality measures.

The preferred and best source of data about an individual's race and ethnicity is the information they provide. Race is not a biological construct, it is a social identity. is not what we think someone else looks like, but how they self-identify. While zip code data and surnames can be helpful proxies for self-reported information about race and ethnicity when doing population level analysis, they are less accurate than self-identified data and should be used with caution in informing assessments and patient-level interventions.

But why should people trust Medicaid agencies with sensitive information about their race and ethnicity? For far too long, government agencies, health care providers, and others have used race and ethnicity to exclude, harm, and abuse patients. During the early years of this country, doctors performed horrific “experiments” on African American enslaved women. During the Tuskegee Syphilis Project, doctors and public health nurses withheld life-saving treatment for African American men. Still today, researchers continue to report that minority patients typically receive less treatment and poorer quality treatment than white patients do.

This article offers lessons from one motivated state Medicaid program-- Michigan--that has embraced a health equity approach to quality improvement in managed care that puts reducing racial and ethnic disparities front and center. For twenty years, Michigan state law and policy has been at the forefront of using Medicaid managed care quality data, stratified by race and ethnicity, to report, track, and tackle health care disparities.

Part I explains the importance of Medicaid to minority health and the studies documenting long-standing, pervasive disparities in the quality of care that Medicaid provides to minority patients. It also presents an overview of two decades of collaborations showing how state Medicaid agencies and managed care plans can use Medicaid enrollee data stratified by race to drive equity-focused quality improvement efforts.

Part II describes how the lack of federal Medicaid policy has contributed to the failure of many states to collect and use data stratified by race and ethnicity for quality improvement purposes. It also discusses recent rulemaking that will finally require states to begin reporting Medicaid quality measures stratified by race and ethnicity effective 2027.

Part III shows how Michigan has used state law and policies and managed care contracts to put health equity and healthcare disparities reduction at the center of its Medicaid managed care quality efforts. For almost two decades, the state has partnered with minority communities to develop policies and strategies to reduce racial and ethnic disparities. Public reporting and tracking of quality data stratified by race and ethnicity identifies where disparities exist and whether interventions are successful. State-led performance improvement projects and financial incentives to reduce disparities assure that managed care plans prioritize reducing racial and ethnic disparities.

Part IV offers lessons from Michigan for other states struggling to collect enough data about the race and ethnicity of their Medicaid enrollees to be able to stratify quality data by race and ethnicity. It concludes that the key to success may be connected to how states use the race and ethnicity they collect. States, like Michigan, that lead the way in collecting race and ethnicity data on their Medicaid applications are typically states that have a clearly articulated public policy and rely on such data to identify and address disparities in health care and health outcomes, seeking to help rather than harm minority patients. They are also states that engage with communities of color to enlist them as allies and partners in designing health equity quality improvement initiatives.

[. . .]

Michigan has used a three-prong approach to put disparities reduction at the center of its Medicaid managed care quality efforts. For almost two decades, the state has built partnership with minority communities so that their voices and lived experiences inform the development of policies and quality improvement efforts. Public reporting and tacking of quality data stratified by race and ethnicity identifies where disparities exist and whether interventions are successful. State-led performance improvement projects and financial incentives to reduce disparities assure that managed care plans prioritize reducing racial and ethnic disparities in care.

Michigan is not alone. Other states have adopted all or part of Michigan's three-prong approach to health equity in managed care. According to an analysis commissioned by Princeton's State Health & Value Strategies, at least seventeen states and the District of Columbia have provisions in their Medicaid managed care contracts requiring that certain quality measures be stratified by race and ethnicity. least fourteen require managed care plans to create a disparities' plan or report. At least nine states provide financial incentives to incentivize plans to reduce racial and ethnic disparities. At least seven states are leveraging managed care contracts to ensure that plans are listening to, understanding, and reflecting the priorities and experiences of their enrollees through meaningful enrollee involvement in policy development, implementation, evaluations, and improvements efforts. North Carolina, the most recent state to adopt Medicaid managed care, seems to be closely following Michigan's three-prong play book.

At the federal level, momentum towards race and ethnicity disparities reporting has picked up momentum. HHS has finally issued regulations requiring states to report a set of core quality measures stratified by race and ethnicity and the agency seems poised to issue regulations requiring states to stratify Medicaid managed care plan quality measures by race and ethnicity. Together, these regulations will create minimum standards for state collection and reporting of quality disparities for both managed care and fee for service Medicaid. Since 2022, NCQA is requiring all health plans it accredits (commercial, Medicare, and Medicaid) to stratify select HEDIS measures by race and ethnicity with the number of stratified measures growing to twenty-two by 2024.

Yes, embracing racial and ethnicity disparities reduction and a health equity framework requires that states have good quality, voluntarily provided data about the race and ethnicity data of Medicaid enrollees. Michigan's experience shows how state law, agency policy, managed care contracts, and managed care quality strategies can create the legal framework needed to see and fix racial and ethnic disparities in health care. All states should be partnering with minority communities to understand their concerns and to collaborate with them to develop and disseminate resources about why Medicaid agencies ask about race and ethnicity and how it will be used to advance health equity. Community input is critical in assuring that race and ethnicity data is collected and shared by the states and in a way that respects enrollees' privacy, while furthering the goal of using race and ethnicity data effectively to advance health equity and reduce disparities in the Medicaid program.

Professor of Law, Saint Louis University School of Law Center for Health Law Studies.