Flipping the Script: Designing the System to Deliver for Patients

Annie Kennedy (Parent Project Muscular Dystrophy)

• Led the organization to pivot from sharing emotional narratives to generating "data language" for regulators after a 2011 regulator advised that "emotional parents aren't data."
• Authored and published FDA guidance and six patient preference studies while establishing a PRO and patient registry.
• Identified a critical gap: outcomes collected for regulators were not aligned with the language or metrics required by payers for reimbursement.

Marcus Schabacher (ECRI)

• ECRI, an independent medical technology evaluation laboratory, integrates patient voice into its "horizon scanning" for potentially disruptive technologies.
• Mandates a patient/caregiver stakeholder interview process for inclusion in disruptive technology reports, focusing on access, disparities, and affordability.
• Cited a case where a scientific team deemed a heart failure device non-disruptive, but patient feedback on affordability and equity for underrepresented minorities reversed the assessment.
• Proposes shifting from a provider-focused safety model to a patient-focused model, noting the patient is increasingly becoming the primary caregiver.

Gigi Hirsch (MIT Center for Biomedical Innovation / New DIGGS Initiative)

• Leads the LEAPS project, a "think and do tank" aiming to connect R&D with care delivery to get the "right treatment to the right patient at the right time."
• Is piloting a learning health system in Massachusetts for rheumatoid arthritis to address a "25% chance of wrong treatment" leading to irreversible progression.
• Rejects centralized data lakes; proposes tapping into existing data sources to create scalable, embedded infrastructures that improve over time.
• Focuses on longitudinal patient journeys rather than transactional clinical encounters to drive sustainable innovation.

Andy Schmeltz (Pfizer Oncology)

• Highlights a systemic shift needed from volume-based incentives to outcomes-based incentives across the U.S. healthcare ecosystem.
• Used real-world evidence (RWE) to secure a regulatory indication for male metastatic breast cancer by aggregating data from three sources (Flatiron, IQVIA, EHRs) since prospective trials were infeasible.
• Advocates for leveraging digital technologies and AI to make drug development more efficient and to ensure clinical trials include value assessments relevant to payers.

Dr. Jeff Schirr (FDA CDRH)

• Explicitly incorporated "patient preferences" and benefit-risk tradeoffs into the FDA's decision-making framework for medical devices.
• Established a patient engagement program that achieved 97% employee engagement with patients within two years.
• Developed a network called the "Patient and Caregiver Connection" for streamlined, organic outreach rather than transactional contact during decision points.
• Reports 17 completed or underway patient preference information studies impacting decisions for obesity, home-use dialysis, insulin pumps, and Parkinson's treatments.
• Proposes "collaborative communities" where the government acts as a facilitator rather than a commander, allowing non-government entities to lead solutions with patients at the table.

Marcus Wilson (Health Corps / Anthem)

• Health Corps leverages an ecosystem of 41 million individuals to generate insights for the payer, FDA, and industry.
• Identifies a fundamental gap: while generalizable evidence exists, specific data on "in whom" a treatment works for individuals is often missing.
• Is building a value assessment framework for Anthem that incorporates the patient voice as a core component rather than a contextual consideration.
• Supports shifting from volume-based contracting to robust value-based contracting where outcomes are specific to patient populations.

Barriers to Data and Evidence

• Fragmentation: Real-world data is siloed across multiple sources (e.g., EHRs, payers, registries) with no common standards, requiring significant effort to aggregate.
• Commercialization vs. Utility: Many data brokers monetize data without ensuring scientific utility; finding data that matches specific genetic biomarkers or rare populations (e.g., male breast cancer) is difficult.
• Capacity Constraints: Hundreds of small patient organizations are recreating infrastructure independently, leading to unsustainable resource burdens and fragmented efforts.
• Design Flaws: Medical devices often lack human factors testing for cognitive load and physical limitations, leading to usability errors in home settings (e.g., infusion pumps).
• Post-Market Gaps: High-risk devices with low annual usage volumes may not trigger clinical studies, necessitating mandated real-life evidence registries for safety surveillance.

Future Directions and Collaboration Models

• Patient-Led Research: Shift from external entities requesting data to patients and communities funding research agendas that address their specific needs.
• Coordinated Registry Networks: Linking disparate registries, EHRs, and payer claims to create datasets fit for purpose, governed by patient stakeholders.
• Learning Health Systems: Designing infrastructure where data owners are also evidence consumers, creating a "public good" that raises the tide for all stakeholders.
• Cognitive Safety: Evolving safety reporting to include patient and caregiver reports on near-misses and usability issues, similar to existing provider safety reporting.
• Codification: The "Patient-Focused Drug Development" (PFDD) model was codified into law via the 21st Century Cures Act, though implementation challenges regarding data integration and stakeholder alignment remain.