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The network and effects of long-term care insurance policy innovation diffusion in health industry of China

Year: 2026
Type: article
Abstract: Objectives This paper aims to evaluate long-term care insurance (LTCI) policies from the perspective of policy innovation diffusion, which can detect the difference between LTCI policies in different pilot cities and the mechanism of the various diffusion mode. Methods: The longest common subsequence (LCS) algorithm are applied to identify the policy cluster in health industry policies. The policy citation relationship is extracted by policy number to establish the policy innovation network, and the time weighted PageRank model is combined to highlight the earlier policy. The time-varying DID model is suitable to evaluate the policy effect of LTCI under various diffusion patterns, and detecting the reason for differences can explain the mechanism of policy diffusion through the SimCSE (Simple Contrastive Sentence Encoder) policy text similarity. Results: In the perspectives of policy innovation diffusion, the LTCI policy effects of the pilot cities in spontaneous initiation (SI) and upward diffusion (UD) are effective and significant. Qingdao in SI area has initiative funding in 2012 might be the reason of significant effect detecting by the policy text similarity comparison between Qingdao and other cities. Conclusions: The policy effect is not replicable in pilot cities through the different policy effect, and the earlier policy publication time and efficient policy instrument, such as funding support, should be the policy innovation. Other pilot cities cannot only imitate and learn in policy formulation, the demands of nursing resources in different regions should be considered, and policy innovation in the policy text, such as new financing pattern, should be encouraged, which can promote the comprehensive and coordinated development of long-term care insurance policies.
DOI: 10.1186/s12913-026-16011-x
Language: English
Open Access status: gold
Estimated APC paid: $3,290
OpenAlex ID: W7225659037
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