HTA Evidence Evolution

MarcusWelcome to the Access Brief — your daily briefing on what's moving in HEOR, HTA, and market access. I'm Marcus, health economist, and it's great to have you with us today.

SaraAnd I'm Sara, market access strategy. Always good to be here — and I'll say, I've had today's topics circled since this morning. The evidence landscape is shifting faster than we can map sometimes.

MarcusSame here. We're looking at RWE integration in HTA submissions — the operational hurdles that keep surfacing. Then digital therapeutics clinical utility — how HTA bodies are grappling with their value propositions. And orphan drug RWE requirements — the evidence standards that are raising questions. Finally, AI integration in HTA decision frameworks — the practical applications starting to emerge.

SaraThat second one about digital therapeutics is particularly timely. The clinical utility question is one where payers are still searching for a reliable framework.

MarcusExactly. Let's get into it.

MarcusStarting with RWE integration in HTA submissions. We're seeing more submissions incorporating real-world data, but the operational challenges persist. HTA bodies are increasingly demanding standardized methodologies, yet the heterogeneity of data sources remains a significant barrier.

SaraThat's one read — I'd frame it slightly differently. What strikes me is the budget impact question. When RWE shows real-world effectiveness differs from clinical trials, how do we reconcile that with health economic models built on RCT data? The opportunity cost implications are substantial.

MarcusThat connects to something I keep coming back to: the methodological maturity gap. HTA bodies are developing RWE-specific guidance, but the industry's ability to generate high-quality, comparable datasets hasn't fully caught up. The DARWIN EU network is helping, but scalability remains a question.

SaraThe part that gives me pause is the regulatory-HTA evidence disconnect. FDA may accept RWE for approvals, but HTA bodies often require different endpoints or comparators. That creates redundant evidence generation and delays access.

MarcusThat's fair, though I think payers would see it differently. They need to ensure real-world evidence reflects their population, not just trial populations. The tension between innovation speed and evidence rigor is real.

SaraI wonder if that's the full picture though. The operational burden of cleaning and standardizing RWE for multiple HTA submissions is often underestimated. It's not just about data quality—it's about sustainable processes.

MarcusExactly. And what's striking here is how this varies by therapeutic area. Oncology submissions often integrate RWE more readily than, say, neurology, due to more mature registries. The heterogeneity in readiness is becoming a market access factor itself.

SaraThat's one of those stories where the technical details have real-world consequences. Companies without robust RWE infrastructure may find themselves at a disadvantage regardless of clinical data strength.

MarcusShifting to digital therapeutics clinical utility. HTA bodies are increasingly evaluating these interventions, but the clinical utility assessment is still evolving. How do we measure value for interventions that exist outside traditional healthcare settings?

SaraThat's fair, though I think payers would see it differently. Their primary concern is integration into existing care pathways. A digital therapeutic with strong efficacy data but no workflow integration faces an uphill battle regardless of clinical value.

MarcusThat connects to something I keep coming back to: the evidence standard dilemma. Most HTA frameworks were built for drugs and devices. Digital therapeutics require different endpoints—engagement metrics, adherence patterns, real-time behavior change. The methodological adaptation is still catching up.

SaraThe part that gives me pause is the reimbursement model question. How do we value continuous monitoring versus discrete interventions? The budget impact calculations differ fundamentally from traditional pharmaceuticals.

MarcusI'd push back slightly on that. The core value proposition remains improving patient outcomes—whether through biological or behavioral mechanisms. The challenge is demonstrating that convincingly within HTA's evidence hierarchy.

SaraWhat strikes me about that is the implementation gap. Even with strong evidence, digital therapeutics require patient buy-in and clinician adoption. HTA bodies are starting to consider these factors, but the assessment remains fragmented.

MarcusExactly. And this is one of those stories where the regulatory landscape is moving faster than HTA. FDA approvals for digital therapeutics are increasing, but HTA bodies still lack standardized approaches to their evaluation. That creates access delays.

SaraHonestly, this one caught me off guard. I expected more progress by now. The potential to democratize access is enormous, but the evidence translation remains stubbornly complex.

MarcusNow to orphan drug RWE requirements. As rare disease treatments proliferate, HTA bodies are demanding more real-world evidence to supplement limited trial data. But the operational challenges of generating RWE in ultra-rare populations are immense.

SaraThat's one read — I'd frame it slightly differently. What strikes me is the opportunity cost question. When HTA bodies require RWE for ultra-rare diseases, they're diverting resources from evaluating more common conditions with greater population impact. The trade-offs are rarely discussed.

MarcusThat connects to something I keep coming back to: the statistical power dilemma. How do you generate meaningful RWE when a disease affects fewer than 1,000 patients globally? The methodological innovations needed are significant.

SaraThe part that gives me pause is the natural history data requirement. Many HTA bodies now want baseline RWE before treatment initiation, but establishing that for ultra-rare diseases is practically impossible. That creates evidence catch-22s.

MarcusI'd push back slightly on that. While challenging, federated networks and patient registries are showing promise. The real issue is standardization—ensuring data comparability across regions and time.

SaraWhat strikes me about that is the timeline mismatch. RWE generation takes years, but market access decisions often happen within months of approval. The temporal disconnect creates access barriers regardless of evidence quality.

MarcusExactly. And this is one of those stories where patient advocacy groups are becoming critical evidence intermediaries. Their role in generating real-world data is evolving beyond traditional patient-reported outcomes.

SaraThat's one of those stories where the technical details have real-world consequences. Companies must build RWE generation into development timelines from the outset, not as an afterthought.

MarcusFinally, AI integration in HTA decision frameworks. We're seeing early applications in evidence synthesis, endpoint prediction, and model validation. But the operationalization within HTA processes remains nascent.

SaraThat's fair, though I think payers would see it differently. Their primary concern is algorithmic transparency and reproducibility. Black-box AI models contradict HTA's core principles of evidence transparency.

MarcusThat connects to something I keep coming back to: the validation gap. While AI can process vast datasets, HTA bodies require independent validation of predictive models. That creates additional evidence generation burdens.

SaraThe part that gives me pause is the bias question. AI trained on historical data perpetuates existing disparities. HTA bodies are increasingly concerned about algorithmic bias in evidence generation, particularly for underrepresented populations.

MarcusI'd push back slightly on that. The real opportunity is in augmenting—not replacing—human judgment. AI can identify patterns in complex datasets that humans miss, but the final assessment requires contextual understanding.

SaraWhat strikes me about that is the governance vacuum. There are no standardized frameworks for AI validation in HTA. Each submission becomes a bespoke exercise, creating inconsistent assessments.

MarcusExactly. And this is one of those stories where regulatory precedents are emerging. FDA's recent guidance on AI/ML in drug development is starting to influence HTA expectations, but harmonization is lacking.

SaraHonestly, this one caught me off guard. The potential to accelerate evidence synthesis is enormous, but the implementation challenges are substantial. We need more practical case studies, not just theoretical frameworks.

SaraA lot to think about today. I'll be watching how HTA bodies develop standardized approaches for digital therapeutics—their utility assessments are still too fragmented to be operationally useful.

MarcusSame — and for me the thread running through today is the operationalization gap. We have methodological concepts, but the practical implementation across HTA systems remains inconsistent. That creates market access friction regardless of evidence strength.

SaraThanks so much for listening — really glad you're here with us.

MarcusWe'll be back tomorrow. Show notes and transcripts at outcomes-analytica.no. See you then.

SaraThanks for listening — see you tomorrow.

MarcusBack tomorrow on Access Brief. Show notes at outcomes-analytica.no.