Congress Should Think Bigger as It Looks to Address Health Disparities

The urgent mission to make health care in the United States more just and equitable got a major boost recently when a congressional committee sent the CARING for Social Determinants Act of 2021 to a full vote on the House floor.

If passed, this bipartisan piece of legislation would jumpstart a much-needed effort to better understand the enormous role economic and social factors – everything from access to fresh food to proximity to medical facilities – play in the vast health disparities that have been laid bare by the pandemic. It would also help us build the foundation for a more equitable, data-driven health care system in which all Americans, no matter where they happen to live, have access to the resources they need.

Specifically, the CARING Act would require the head of the Department of Health and Human Services to issue guidance every three years to states about what strategies they should use to mitigate poor health outcomes that are in part caused by Social Determinants of Heath factors, which recent research suggests account for more than third of total deaths in the United States annually. This guidance would apply to the Medicaid program in which more than 74 million Americans are enrolled, and the Children’s Health Insurance Program, in which 38.5 million Americans are enrolled.

As written, the CARING Act is a major step in the right direction. But while it’s welcome news that Washington is waking up to the importance of SDOH in health care, Congress should not stop there. Lawmakers should enlist HHS to fully reimagine how this country uses all kinds of data in service of closing growing health inequities, especially because many sources of data, including SDOH, cannot be understood in a vacuum.

For example, SDOH factors and environmental data can show health officials that the air quality in certain ZIP codes is poor due to the presence of, say, pollution-emitting factories and facilities. But that’s only one part of the risk picture. Anonymized clinical data can show exactly how these SDOH factors are impacting health outcomes, such as higher rates of asthma, cardiovascular disease and lung cancer. This more complete picture of community-level risk, in turn, can enable health officials to better direct resources and help to neighborhoods and communities that need it the most.

Anonymized and aggregated clinical data is essential to a data-driven health system that allows states to precisely measure community-level risk and develop targeted interventions where necessary. By combining the power of SDOH and these clinical and environmental data sets, we can better understand who is most at risk for adverse health outcomes.

While the task ahead may seem daunting, there are already examples out there of how private insurers have helped almost instantaneously improve their clients’ health outcomes: Before the widespread availability of COVID-19 vaccines, my data science company, Cogitativo, built a machine-learning tool to make sense of the clinical and SDOH data and provide actionable insights.

We then partnered with a major health insurer in California to identify its most vulnerable members so that it could tailor personalized outreach and support to those individuals, including free meal and medication delivery.

It will require more work to do this type of work at scale, but now is the time to think big about tackling some of the problems that have dogged our health care system for decades.

Congress should pass the bipartisan CARING Act and send it to President Joe Biden’s desk for his signature. That would be a major step in the right direction toward tackling the health inequities so apparent in this country. But this legislation must also ensure that states are able to leverage anonymized payer data wherever possible as a complement to SDOH information, and thus provide the best health care available to all Americans.


Gary Velasquez is the co-founder and CEO of Cogitativo, a data science company.

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