ArticleFrontiers in public health2026
Quantitative evaluation of China's smart aging healthcare policy under the background of silver economy development: based on PMC model.
Article in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Against the backdrop of deep integration between population aging and digital technologies, smart aging care has emerged as a pivotal approach to alleviating caregiving pressures, optimizing resource allocation for senior care, and driving high-quality development of the silver economy. As a top-level institutional design, the quality of smart aging care policies directly determines the effectiveness of older adult care services and the inclusiveness of digital technology applications in older adult care. Conducting a scientific and systematic quantitative evaluation of such policy documents is essential. This study aims to quantitatively evaluate the overall quality and regional heterogeneity of China's smart aging care policies, identify policy shortcomings, and propose optimization pathways for improvement. Methods: The PMC-Index model is the quantitative policy evaluation method that constructs a multi-dimensional indicator system and assigns equal weights to each indicator. Based on this, this study has constructed an evaluation index system for the PMC model of smart aging care policies. This study systematically reviewed 83 smart aging care policies issued by China's government from 2020 to 2025.10 representative policies were selected based on screening criteria that encompass regional coverage across eastern, central, and western regions, uneven economic development, reflection of aging disparities, and responsiveness to the digitalization process.The PMC index was calculated through integrated methods including text mining and multi-input-output tables, combined with visual analysis to evaluate policy structures and regional heterogeneity, thereby identifying optimization pathways. Results: The findings indicate that the overall quality of China's smart aging healthcare policies has reached the "excellent" level, characterized by clear objectives, comprehensive domain coverage, and rigorous textual logic, demonstrating the strong orientation toward technology empowerment and industrial synergy. However, challenges remain: insufficient policy continuity, imbalanced tool mixes, and underdeveloped safeguards. Moreover, policy quality exhibits regional heterogeneity, with eastern regions prioritizing innovation and industrial cultivation, whereas central and western regions focus more on basic service provision and inclusive implementation. Conclusion: This study employs the PMC-Index model to conduct the multidimensional quantitative assessment of China's smart aging care policies. This research provides the reference framework for optimizing and refining smart aging care policies in China, which may also offer insights for other countries and regions addressing population aging and fostering silver economy development. Ultimately, it aims to support the coordinated advancement and continuous improvement of global smart aging care policies.
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