To properly promote health equity in population-based models, risk adjustment should be seen as more than just a predictive exercise, a new study says.
The study, published in Health Affairs this month, explored the problem of using risk adjustment only to accurately predict spending for patient populations. Historical and current levels of spending are unlikely to be the actual desired levels for marginalized communities, it argues.
Population-based payment models, unlike fee-for-service, have the potential to redistribute resources to those in need. Yet adding social factors to risk adjustment can entrench health disparities rather than reduce them, the study argues. For instance, marginalized patients may use less healthcare and have lower spending while having great medical needs.
The study analyzed Medicare claims from 2012 through 2017 for its analysis. It found that when adding race and ethnicity as a predictor to the current risk adjustment model, spending was lower for Black and Hispanic beneficiaries than their white counterparts, despite them having worse overall health. Conversely, the current risk adjustment model for the Medicare population—which does not include race and ethnicity—overpredicts annual spending for Black and Hispanic beneficiaries.
Setting payments above current levels for those with worse access to care incentivizes a redistribution of resources to them and can help address disparities, according to the researchers.
At the same time, the study found more minimal overpredictions for less-educated beneficiaries and those living in historically disadvantaged areas, suggesting additional work is needed to ensure payment adjustments overpredict spending. One example of doing this in ACO REACH models is increasing benchmarks for beneficiaries living in communities with a higher area deprivation index.
Overall, promoting health equity within population-based payment models might look like omitting social factors or setting the risk adjustment higher for groups that are disadvantaged, according to the researchers.
“We as a society have not deliberately decided to spend more on underserved populations in our main approaches to payment reform,” J. Michael McWilliams, M.D., the study’s lead and a professor of medicine at Harvard Medical School, told Fierce Healthcare via email. “That decision is an application of our social values and not the conclusion of a predictive model. We have to depart from accurate predictions of spending to change the way we spend.”
With models like ACO REACH, he added, “we are starting to now.”