Presentation (CTI)

OBJECTIVES: Health Technology Assessment (HTA) and regulatory frameworks increasingly demand patient lived-experience data beyond traditional clinical efficacy endpoints. However, a standardized, structured pathway to translate qualitative patient narratives into decision-relevant, quantitative measures is lacking. This study proposes a novel, conceptual medical anthropology-based framework designed to systematically capture patient-based evidence and translate it into structured, decision-relevant constructs for HTA and integrated evidence planning.
METHODS: The proposed framework applies principles of medical anthropology and ethnographic inquiry to explore how disease and treatment alter patients' physical, emotional, social, and structural dimensions of life. The model utilizes strict qualitative rigor principles, including data triangulation and empirical saturation. Rather than viewing patients in isolation, the framework integrates illness-network analysis and socio-cultural variables to situate evidence within real-world healthcare contexts. A structured three-step translation matrix is then applied to convert these lived-experience insights into formalized HTA evidence domains. This includes mapping qualitative concepts directly to patient-relevant endpoints, Clinical Outcome Assessments (COAs), meaningful change thresholds, treatment-burden measures, discrete choice experiment (DCE) patient preference attributes, and health state utility assumptions
RESULTS: The framework generates a systematic pathway linking patient lived experience to measurable evidence constructs relevant for Phase III development, regulatory evaluation, payer requirements, and HTA appraisal. The model enables earlier identification of patient-relevant outcomes, supports conceptual validity, and translates treatment burden and daily-life impacts into evidence informing benefit-risk assessment and value demonstration. Potential applications include identification of under-measured dimensions of fatigue, independence, caregiver burden, treatment inconvenience, productivity loss, and social participation that may not be adequately captured through traditional clinical endpoints alone.
CONCLUSIONS: This conceptual framework bridges a critical methodological gap between qualitative patient experience and quantitative HTA decision-making needs. By translating lived experience into formalized, decision-relevant evidence concepts, the model provides a scalable strategy to strengthen patient-centric value demonstration within global regulatory and payer framework.