Bridging Real-World Data Gaps: Connecting Dots across Ten Asian Countries (Preprint)

Guilherme Silva Julian, Hsu-Wen Chou,Wen-Yi Shau,Sajita Setia

crossref(2024)

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摘要
UNSTRUCTURED The economic trend and the healthcare landscape are rapidly evolving across Asia. Effective Real-World Data (RWD) for regulatory and clinical decision-making is a crucial milestone associated with this evolution. This necessitates a critical evaluation of Real-World Data (RWD) generation within distinct nations for utilization of various RWD warehouses in the generation of Real-World Evidence (RWE). In this article, we outline the RWD generation trends for two contrasting nation archetypes, ‘Solo Scholars’—nations with relatively self-sufficient RWD research systems—and ‘Global Collaborators’—countries largely reliant on international infrastructures for RWD generation. The key trends and patterns in RWD generation, country-specific insights into the predominant databases used in each country to produce RWE, and insights into the broader landscape of RWD database utilization across these countries are discussed. Conclusively, the data points out the heterogeneous nature of RWD generation practices across 10 different Asian nations and advocates for strategic enhancements in data harmonization. The evidence highlights the imperative for improved database integration and the establishment of standardized protocols and infrastructure for leveraging Electronic Medical Records (EMR) in streamlining RWD acquisition. The Clinical Data Analysis and Reporting System (CDARS) of Hong Kong is an excellent example of a successful EMR system that showcases the capacity of integrated robust EMR platforms to consolidate and produce diverse RWE. This, in turn, can potentially reduce the necessity for reliance on numerous condition-specific local and global registries or limited and largely unavailable medical insurance or claims databases in most Asian nations. Linking Health Technology Assessment (HTA) processes with open data initiatives like the Observational Medical Outcomes Partnership Common Data Model and the Observational Health Data Sciences and Informatics could enable the leveraging of global data resources to inform local decision-making. Advancing such initiatives is crucial for reinforcing healthcare frameworks in resource-limited settings and advancing towards cohesive, evidence-driven healthcare policy and improved patient outcomes in the region. International Registered Report Identifier (IRRID): RR2-10.2196/43741
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