Health equity in the United States is shaped by many factors—socioeconomic status, race, geography, education, and access to care. The result is uneven outcomes: adults in lower income brackets are more than twice as likely to report poor health compared to those with higher incomes. Against this backdrop, the Inflation Reduction Act (IRA), signed into law in2022, aims to reduce prescription drug costs for Medicare beneficiaries while ensuring the sustainability of the healthcare system. For HealthEconomics.com’s recent webinar, “Closing Gaps in Care: Health Equity and the Inflation Reduction Act,” I shared how real-world data can help life sciences companies gauge the impact of the IRA in improving health equity and patient outcomes.

The IRA’s most visible provision allows the U.S. Department of Health and Human Services (HHS) and the Centers for Medicare & Medicaid Services (CMS) to negotiate drug prices directly with manufacturers. The first round of negotiations began in 2024, with the next slated for 2026. Other measures, such as the redesign of Medicare Part D benefits and a $2,000 cap on annual out-of-pocket (OOP) drug spending starting in 2025, are expected to change how patients access and afford therapies.

But how will these policies influence health equity and patient outcomes? That’s where real-world data (RWD) comes in.

Why RWD Matters for IRA Policy

Randomized controlled trials (RCTs) remain the gold standard for evaluating safety and efficacy, but they often exclude older adults, people with multiple comorbidities, and patients with disabilities—groups that represent a significant portion of the Medicare population. RWD, drawn from electronic health records (EHRs), claims, registries, and even unstructured clinical notes, fills these gaps by showing how treatments perform in broader, more diverse populations.

When linked across multiple sources, RWD can:

• Identify disparities in treatment adherence and outcomes, especially where socioeconomic or geographic barriers exist.
• Capture health outcomes, costs, and resource use that aren’t fully reflected in RCTs.
• Track how formulary or policy changes affect patient access and adherence over time.

For example, claims and EHR data have already been used to assess how out-of-pocket costs influence treatment adherence, while social determinants of health (SDOH) data—such as financial stress or food insecurity—offer additional context. These insights are critical for understanding whether IRA policies are achieving their intended goals across vulnerable populations.

Opportunities and Challenges

The potential of RWD is significant, but so are its limitations. Observational studies can introduce bias, data sources may be incomplete, and coding variability can skew results. Best practices—such as statistically balancing cohorts and linking data sources to minimize missingness—are essential for producing credible insights.

As CMS weighs evidence in drug price negotiations and evaluates the impact of access policy, RWD can help measure value not only in terms of cost savings, but also in terms of equity: Are patients filling prescriptions more consistently under lower OOP caps? Are marginalized groups gaining better access to therapies? And do negotiated prices translate into measurable improvements in outcomes across populations?

The IRA represents a unique convergence of pricing, policy, and evidence. While trade-offs are inevitable, RWD provides the tools to track how these policies affect patients in real time—highlighting where progress is being made and where inequities persist. By thoughtfully linking diverse data sources and incorporating SDOH, researchers and policymakers can ensure that the IRA not only reduces costs, but also promotes fairness and sustainability in patient care.

In short, real-world data can be the bridge between policy intent and patient impact—helping us answer the critical question: Are we making healthcare more equitable, or just less expensive?

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Learn more about how Panalgo and Norstella can help you make healthcare more equitable and get life saving treatments to patients faster with real-world data and analytics tools.