Is Cost-Effectiveness Analysis Racist?

By: Michael Broder & Jesse Ortendahl 

Performing and using cost-effectiveness analyses is a core activity for many of us working in HEOR. Many shortcomings of CEA are well known (it fails to account for budget impact, “real option value”, “the value of hope”, etc.), but CEA as currently performed has an even bigger problem than any of those: equity.

There is a racial divide in the US healthcare system. We state this as a fact because it is. Not convinced? Read the Lancet 2021 Commission on Public Policy and Health in the Trump Era report, or AHRQ’s most recent report on National Healthcare Quality and Disparities.

Black Americans are more likely to be uninsured, get worse care when they are insured, and die younger than their White counterparts. The idea that these profoundly divergent outcomes are predictable, much less intentional, might be hard to swallow, but the evidence is hard to ignore.

Disparate racial outcomes were the predictable result of a “War on Drugs” that incarcerated 10 Black people for every White one, despite similar rates of drug use (the literal poster child for this “war” was the wildly over-hyped “crack baby,” nearly always illustrated as Black or brown); the predictable result of the decisions by nine Southern states with large Black populations not to expand Medicaid as part of the ACA; and the clearly intentional result of many policy decisions like redlining of Black neighborhoods by the Federal Housing Authority.

How does this relate to cost-effectiveness analysis? Even if we assume no current health professionals have inaccurate beliefs about Black people (clearly a false presumption: many physicians still believe Black patients have a higher pain tolerance, and Black patients are treated less aggressively for pain in the ED), racially motivated policies from the past have left their mark on current health outcomes.

By failing to address or even acknowledge racially divergent outcomes, CEA serves to perpetuate racial inequities.

Imagine a CEA comparing a screening test for peripheral artery disease, an often asymptomatic condition that can lead to amputation, to usual care. The risk of amputation is modeled as 8% over 10 years, and the test is found to have an incremental cost effectiveness ratio (ICER) of $65,000. But the risk of amputation in Black people (12%) is nearly double that in White people (7%), producing ICERs of $40,000 and $70,000, respectively. Considering the wide range of conditions for which US health outcomes differ by race, you can see how producing a single estimate of cost-effectiveness can hide dramatic variation in cost-effectiveness.

More subtle problems exist, too. Black Americans have overall worse health and, according to the most recent HHS statistics, dramatically shorter life expectancy overall. But simply using race-specific inputs for models can make things worse, not better. Prior to COVID, the racial gap in life expectancy had narrowed to 1-2 years at age 65 (an average difference which itself hides huge variation by income and region). A pill that completely reversed a deadly condition with a high mortality rate that affected Black people and White people equally would add 10% fewer QALY for Black people, making the pill look less attractive in the population with a shorter life expectancy. People of Hispanic origin have longer life expectancy non-Hispanic White people—3 years longer pre-COVID—so that same pill would look much more attractive in the Hispanic population. As modelers, we often concern ourselves with getting accurate inputs for things that matter far less and have a far smaller impact on the results of our models.

“But,” one might argue, “It’s not the job of CEA to address societal inequities.” To which we would reply, CEA already “addresses” these inequities. It addresses them by assuming they are unimportant and that the existing structure of the society it serves is inherently equal. In this way, CEA inherently perpetuates existing inequities.

Society leans too hard toward people who look like the authors already. Let’s try as health economists to make CEA lean toward justice instead.