You won’t fix what you don’t value: Two reasons why traditional cost-effective analyses can perpetuate health inequities

A new report from Partnership for Health Analytic Research or PHAR describes how value assessments that use traditional cost-effectiveness analyses can overlook important health disparities and risk perpetuating health inequities.

These analyses, also known as CEAs, frequently are the basis for value assessments such as those performed by the Institute for Clinical and Economic Review (ICER) and other assessment organizations to evaluate the value of medicines and other tests and treatments. But using traditional cost-effectiveness analyses in coverage decisions can hinder progress toward an equitable U.S. health care system by failing to account for important differences among different patient groups. Here are two things you should know from the report.

1. Traditional CEAs ignore health disparities by overlooking patient differences. Traditional cost-effectiveness analyses use a population-wide average risk of disease, treatment utilization and therapy efficacy to judge care “value.” The prevalence or risk of disease in different groups can change the value of a treatment for that group, but traditional CEA ignores these differences. The risk of breast cancer disease in women ranges from 8% in American Indians and Alaskan Natives to 12% in Black Americans. Over the past two years, women over the age of 40 who had mammograms ranged from nearly 58% of Asians to 67% of white Americans. The significant nuances between health and treatment experiences across various demographics are not accounted for using general population averages within CEAs. This presents the potential risk of harmful bias on patient health outcomes.
   
   
2. This type of value assessment often undervalues treatments for certain populations. CEAs that rely on the quality-adjusted life year, or QALY, can devalue the lives of patients, particularly those who already experience health inequities like patients from communities of color and patients with disabilities. For instance, the COVID-19 pandemic has widened the life expectancy disparity between white and Black adults. When considering an intervention that can reverse a fatal condition, less value could be assigned to a treatment given to a Black patient than a white patient because of this difference in life expectancy. That’s not right.

Supporting a more affordable, sustainable health care system for all patients is essential. So is making sure the tools we use to do this reduce health disparities rather than reinforce them. To learn more about PhRMA’s efforts to improve value assessment frameworks and health equity, visit PhRMA.org/Value-Collaborative.