Pharmaceutical and health economist Dr. Nadine Zawadzki, Senior Director, FTI Consulting joins the Ron Lanton Report to discuss how value is defined and measured across healthcare.
This episode of The Ron Lanton Report features Dr. Nadine Zawadzki, a pharmaceutical and health economist and senior director at FTI Consulting’s Center for Healthcare Economics and Policy, in a wide-ranging conversation on what “value” actually means across the healthcare system and where that framework breaks down in practice.
Zawadzki opens by pushing back on the idea that value equals cheap, arguing instead that value means getting one’s money’s worth, and that innovation deserves reward when it genuinely beats the standard of care. She points to PCSK9 cholesterol drugs Repatha and Praluent, which launched at roughly $14,000 annually before payer pushback drove a 60% price cut, as evidence that market correction can work alongside regulatory backstops.
Both her and Lanton then explore how value is defined differently by patients, clinicians, and payers, noting that timing is a frequent point of misalignment: GLP-1 drugs deliver visible patient benefit quickly but impose heavy upfront payer costs well before downstream cardiovascular savings materialize. Zawadzki frames the broader upfront-cost dilemma, particularly for potentially curative therapies, as a solvable market failure requiring creative risk-sharing models, with CMMI’s sickle cell gene therapy model, where manufacturers tie payment to outcomes, as one example already underway.
On value-based care, Zawadzki argues the concept is sound but poorly executed, noting that tracking and reporting burdens often go unreimbursed, pushing costs onto providers and eventually patients through higher bills and premiums, while evidence of actual quality improvement remains unclear. She extends this to ACOs, explaining that cost is far easier to measure than quality, creating a structural bias toward cost minimization that can disadvantage high-value but expensive innovations like gene therapy. On provider risk-sharing, she argues providers are often asked to accept financial risk without the data or forecasting tools payers have long used, a gap she believes AI and better data integration could help close.
Looking ahead, Zawadzki argues the industry undervalues patient choice itself, even when one drug isn’t superior on average, and sees “revealed value,” what patients and providers actually choose between options, as an underused signal. She closes by describing ValueNav, a machine-learning tool she created that links a drug’s clinical, regulatory, and market characteristics to historical sales performance to forecast commercial uptake for new drug profiles.
