Why Accounting for Our Differences Matter in Assessing Drug Value

This was written by Jennifer Bright, MPA, executive director, Innovation and Value Initiative, and Amy Miller, PhD, former CEO, Society for Women’s Health Research.

One size doesn’t fit all in health care. Research reveals a long list of diseases and conditions that can have different effects on women and men, the young and the old, and people of different races and ethnicities.

Despite the heterogeneity of patients and their response to treatments, current methods for measuring the clinical efficacy of new therapies and determining their value are often blind to the effects of biological sex, gender, age, and race/ethnicity. As a result, while clinical trials and economic models attempt to tell us that “drug X” for cardiovascular disease is worth its price tag, these conclusions likely do not consider the variation in clinical appropriateness or cost-effectiveness of drug X for different patients.

The failure to account for and understand the impact of patient heterogeneity on optimized treatment outcomes begins long before a drug is brought to market. Women and people of color were historically excluded from medical research, and while this has improved over the past 25 years, the disparity persists in some areas of research.

The FDA Drug Trials Snapshots report shows that for FDA-approved oncology drugs in 2018, only 38% of clinical trial participants were women. Furthermore, African Americans made up only 4% of participants and Hispanics only 5%. Given these numbers, it’s unlikely that we truly know how these new drugs will work for many different groups of people. In addition, randomized clinical trials often exclude many other types of patients (such as those with co-occurring conditions and those who have been previously treated), so these studies are even less representative of typical patients.

While medical researchers work (albeit slowly) to make clinical data more relevant to the real world by increasing the diversity of patients studied, we must also do more to ensure the methods used to measure the “value” of new therapies include factors that reflect patient heterogeneity.

For example, the Society for Women’s Health Research developed a set of principles to help ensure value assessments consider women’s unique needs as patients, caregivers, and health care decision-makers, and provide them with appropriate access to innovative therapies.

There is also a need for better models that examine factors affecting variable responses to treatment as well as adherence to treatment, such as geographical proximity to treatment, tolerability, or side effects of importance to the patient.

Greater use of real-world data to augment our clinical view is an important trend in the right direction. Real-world data can provide important insight into the role of patient preferences and life circumstances in treatment outcomes. Understanding patients’ experiences with a given disease—and their priorities—can improve our ability to measure quality of life with more sensitivity.

For example, if a new blockbuster drug can only be taken in a hospital or infusion center, is that a deterrent to some patients who prefer to remain at home or take a medication in pill form? And does this ultimately affect their adherence rates and success on this drug? More effort is needed within the research community to define the factors that matter to patients and to quantify their impact on both clinical and quality-of-life outcomes.

We need to accelerate initiatives to incorporate real-world data into value assessment through partnership between researchers and decision-makers—including providers, payer, and patients. We must also firmly position patients in lead roles to define meaningful factors that should be inherent components of assessing value.

In the ever-accelerating discussion about paying for “value” we are at a crossroads in the United States. We all know there is more we can all do to make value assessment methods and models more relevant to real patients. Together, researchers, patients, innovators, regulators, clinicians, payers, and employers should commit to finding and accelerating improved methods and tools. We must work together to both develop and deploy data sets that can help us answer the questions most important to patients. We must continue to think strategically about the most effective way to directly engage patients in research.

By making the commitment and forming new partnerships, we can help ensure we are truly identifying the therapies and treatment paths most valuable for the vast diversity of patients served by our healthcare system.