Analysis of Research Trends and Output Effectiveness in the Medical Field Based on the National Natural Science Foundation of China

This study aims to analyze the trends in research focus and output effectiveness in the medical field supported by the National Natural Science Foundation of China (NSFC) over the past 15 years, providing a basis for the optimal allocation of scientific research resources.

Based on the NSFC Big Data Knowledge Management Service Database, a retrospective approach was adopted to retrieve data on completed projects and output achievements from 2009 to 2023. Indicators, including compound annual growth rate (CAGR) and output‐to‐project ratio, were used to evaluate the growth of project completion and research productivity across 35 secondary medical categories.

Over the 15‐year period, a total of 439,637 NSFC projects were completed, with the Division of Medical Science ranking first in both scale (23%) and growth rate (CAGR 11%). The 35 secondary categories (H01–H35) under the Division of Medical Science showed differentiated development characteristics, namely “a few growing rapidly, most growing steadily, and a small number lagging behind”: six directions including biomedical engineering had a CAGR of ≥ 15%; oncology and traditional chinese medicine contributed large output volumes but showed low output‐to‐project ratios, whereas neuroscience, imaging medicine, and biomedical engineering achieved high efficiency. Key Programs achieved the highest output‐to‐project ratios, followed by the General Program and then the Young Scientists Fund.

The completion and output of NSFC‐funded medical projects reflect national strategic orientations and disciplinary development laws, but imbalance remains between project scale and output efficiency across subfields. It is suggested to establish a dynamic evaluation mechanism, promote the “basic research‐application‐transformation” collaborative model, support small‐scale yet high‐efficiency fields, and conduct long‐term tracking of output achievements. These measures are expected to optimize the allocation of NSFC funding resources.