Healthcare Data as a Quasi-Public Good: A Tripartite Distribution Framework for Equity and Efficiency
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Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
Popul. Med. 2026;8(Supplement Supplement 1):A939
ABSTRACT
INTRODUCTION:
this study argues that healthcare data, characterized by its quasi-public good attributes such as low rivalry and low excludability, high fixed costs, low marginal costs, and significant externalities, should be integrated into a tripartite distribution framework to enhance both equity and efficiency.
METHODS:
we analyze the techno-economic traits of healthcare data and justify the role of tertiary distribution in amplifying its social value beyond pure market logic. multi-stakeholder benefit-sharing mechanisms are designed to formalize this integration.
RESULTS:
the proposed framework synergizes market allocation, government redistribution, and social philanthropy. this tripartite approach effectively balances efficiency with equity in the distribution of healthcare data benefits.
CONCLUSIONS:
by embedding healthcare data within a structured tripartite model, the framework advances data governance and promotes common prosperity, offering a scalable pathway to equitably manage data as a quasi-public good.