The brutal murder of George Floyd has brought renewed attention to systemic inequality that African Americans and other minorities face in the United States and around the world. These inequalities also appear in health outcomes statistics. According to the Centers for Disease Control and Prevention (CDC), while African Americans represented 13 percent of the US population, as of May 30, 22 percent of COVID-19 patients were black. Furthermore, as of March 30, 33 percent of hospitalized COVID-19 patients were African American. These health disparities were well known before the COVID-19 pandemic; life expectancy for African Americans in the US is 3.5 years lower than for the American population as a whole. Furthermore, the average African American can expect to spend 13 years of his or her life without health insurance, compared to only eight years for the typical non-Hispanic white. Although there is a universal acknowledgement that health inequalities need to be addressed, the question is “How?”
Are We Appropriately Incentivizing Drug Development For Minorities?
One potential way to reduce inequality in health outcomes is to incentivize research and development efforts to create new drugs in therapeutic areas that disproportionately impact minorities. While there were some recent successes on this front, such as the development of two new treatments for sickle cell disease (crizanlizumab and voxelotor), there is much more work to be done. For example, according to the Food and Drug Administration, drugs approved in 2019 included a smaller proportion of African Americans in their clinical trials than are represented in the population as a whole. This finding highlights the underrepresentation of African Americans’ health needs in life sciences research and development.
A potential barrier to developing treatments for patients in disadvantaged communities is that traditional value assessment frameworks, such as cost-effectiveness analysis, are based on improving overall population health and assume all health gains are valued equally. These frameworks do not explicitly consider where health gains are achieved and the overall impact on achieving equity in health outcomes. For example, in the US, the 2020 Value Framework from the Institute for Clinical and Economic Review (ICER) notes that a treatment’s impact on racial or socioeconomic inequality is important. However, the report goes on to state that since there is no standard health technology assessment approach for incorporating a treatment’s impact on inequality, ICER will only “explore through scenario analyses methods to capture the impact of new technologies on disparities in life expectancy across different subpopulations.” Furthermore, these scenario analyses would only be conducted if it were “judged feasible.” In the United Kingdom, although the National Institute for Health and Care Excellence (NICE) consider equity, the agency also states that innovators in their base-case cost-effectiveness analysis should assume “an additional QALY [quality-adjusted life year] has the same weight regardless of the other characteristics of the people receiving the health benefit.” This guidance by NICE has directly impacted innovation. Helen Dakin and colleagues reviewed all NICE submissions up to 2011 and found that cost-effectiveness alone correctly predicted 82 percent of NICE’s reimbursement decisions. Other factors, such as severity of the disease, lack of alternative treatment options, or conditions impacting pediatric populations, had little predictive power.
Incorporating The Value Of Reduced Inequality Into Value Assessment
To incentivize innovators to develop treatments for disadvantaged communities, traditional value assessment frameworks need to be expanded to more explicitly consider equity in health outcomes. We agree with others calling for value assessment to take a more holistic, societal approach to measuring value. In fact, there have been a number of methodologies adopted to quantify explicitly the value of treatments that reduce health disparities. For instance, multicriteria decision analysis is one way that stakeholders could formally trade off different treatment attributes, including cost per quality-adjusted life year, as well as a treatment’s impact on inequality. Under this framework, new therapies would be prioritized based on their impact on a number of pre-specified criteria, among which health inequality can be included.
An alternative approach—building on cost-effectiveness analysis—is the distributional cost-effectiveness analysis (DCEA) methodology. Under this framework, new therapies are evaluated for different groups within a population (for example, based on income, gender, and ethnicity), and health gains are evaluated for those specific groups and for the population as a whole, allowing decision makers to see explicitly the trade-off between improving health for a specific group (that is, improving health equity) and improving overall population health. As Richard Cookson of the University of York has highlighted, the advantage of the DCEA approach is that it encourages a “deliberative decision making process, not imposing a fully pre-specified theory of justice.” There are a handful of other DCEA methodologies that have been developed (see also James Love-Koh and colleagues, 2020; James Love-Koh and colleagues, 2019; and Miqdad Asaria and colleagues, 2015, among others). These DCEA approaches place a premium on QALY gains when incurred by disadvantaged communities and discount QALYs that accrue to patients with better expected health outcomes at baseline. In short, the gap in addressing health inequality is not due to a lack of methodological tools.
In a time when calls for equity are ringing through all sectors of society, symbolized most prominently by the Black Lives Matter movement, value assessment frameworks must change. The solution to the problem is not to have the government favor treatments for one race compared to another. Rather, treatments developed for patient populations with disproportionately poor outcomes should be valued more than those for individuals who already can expect good health outcomes. As discussed above, researchers have already developed a methods toolkit to enable decision makers to measure this equity-efficiency tradeoff. While improving health outcomes for African Americans and other marginalized groups requires leveraging a multifaceted approach, appropriately incentivizing innovations that help those who need it most is one step that both policy makers and life sciences firms can agree on is a way to fairly make sure that equity is appropriately valued.
Authors’ Note
Jason Shafrin is an employee of PRECISIONheor and holds equity in the Precision Medicine Group, a consulting firm to the life sciences industry. Meena Venkatachalam is an employee of PRECISIONheor, a consulting firm to the life sciences industry.
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