Frailty, Real-World Data, and the Access Imperative: A Q&A with Magnolia’s Mike Murphy

Frailty is more than a clinical condition—it’s a strategic blind spot.

In a healthcare landscape increasingly shaped by real-world data (RWD), one critical factor remains difficult to define, measure, and act on: frailty. For older adults—often excluded from clinical trials—frailty influences treatment decisions, health outcomes, and payer value assessments. And yet, it’s frequently overlooked in real-world studies.

At Magnolia Market Access, we see frailty as a key variable in evidence generation and access strategy. Ahead of ISPOR 2025, we sat down with Mike Murphy, Director of Real-World Evidence and HEOR Strategy, to discuss Magnolia’s latest research using administrative claims data to evaluate frailty indices. In this Q&A, Mike explains why frailty matters, how it’s being measured, and what biopharma needs to consider to better serve aging and high-risk populations.

Mike Murphy: Frail older adults are often excluded from clinical trials, which creates major evidence gaps in how treatments affect this population. That’s where real-world data has the potential to shine—if we can develop reliable methods to identify and adjust for frailty in large datasets.

MM: Frailty impacts how patients respond to treatment, their ability to adhere to medication, and their overall risk of adverse outcomes. While researchers often adjust for age or comorbidity scores, frailty is frequently overlooked. That’s partly due to a lack of awareness of frailty as a distinct clinical concept—and partly because it’s difficult to measure. It doesn’t have a single agreed-upon definition and is more of a syndrome than a binary state.

MM: The Kim and RAI indices were developed in different populations and use different types of input data. We wanted to see how they perform when applied to the same population. Our goal was to better understand their alignment—or lack thereof—when measuring frailty in real-world settings.

MM: Each index uses different data inputs—some rely on diagnosis codes, others on procedure codes or demographic information. They may also use different lookback periods. A longer lookback could provide a more complete picture but may exclude patients without continuous data. Meanwhile, shorter lookbacks could underestimate certain conditions. Researchers need to understand these nuances to choose the right index for their population and study question.

MM: Other researchers have shown that different indices identify different subsets of frail patients. At ISPOR, our work will highlight some of the key drivers behind those discrepancies and why they matter when interpreting study results or designing access strategies.

MM: Because the risk–benefit calculus changes in frail populations. Treatments that are standard of care in non-frail patients might not be appropriate—or safe—for those who are frail. If we want to address those gaps with real-world data, we have to be able to measure frailty accurately and consistently.

MM: If we fail to measure or adjust for frailty in real-world studies, we run the risk of producing biased outcomes. That can lead to flawed conclusions, missed opportunities, or even harm to patients. It’s critical to understand how these indices work—and how the patients they identify differ.

MM: Understanding frailty can help identify unmet needs and highlight product benefits in high-risk populations. It’s also important for long-term safety and effectiveness data. Frailty is a key lens through which to segment populations and refine evidence generation strategies.

MM: We take a collaborative approach—first understanding the client’s needs, then applying our team’s deep expertise to translate data into clear, strategic insights. We don’t just run the analysis—we provide the context to make it actionable.

MM: Our team brings years of experience working across datasets, disease states, and payer landscapes. We also know what kinds of evidence matter to payers and providers. That allows us to help clients develop strategies grounded in both data science and real-world expectations.

MM: With a deeper understanding of frailty, biopharma can better partner with healthcare systems to improve care delivery—and even explore value-based care models tailored to frail populations. It opens new doors for innovation and impact.

Failing to accurately measure frailty risks underrepresenting—or misrepresenting—entire patient segments in health outcomes research. For biopharma companies developing access strategies, modeling value, or preparing evidence for payer discussions, frailty can’t remain an afterthought. It’s time to bring it to the forefront.

At Magnolia Market Access, we help our clients decode complexity in datasets and make it actionable—from high-risk patient segmentation to value-based care strategy. Join us at ISPOR 2025 to explore how smarter frailty measurement can unlock smarter access decisions.

Our team will be presenting two posters exploring frailty measurement and its implications for access modeling and outcomes research.

Interested in how frailty impacts your evidence strategy?
Schedule a meeting with us in Montréal.