ArticleBMC public health2025
Policy text analysis of high-quality development of integrated elderly care and medical services in China based on PMC index model.
Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Quantitative evaluation of the medical resource allocation policy in China: a PMC-index model approach.Cost effectiveness and resource allocation : C/E · 2026Article
- Measuring supply-demand coupling coordination in China's older adult care services: spatiotemporal evolution, spatial spillover effects, and driving factors based on the spatial Durbin model.BMC health services research · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
objectiveThis study aims to conduct a content analysis of policies pertaining to the high-quality development of Integrated Elderly Care and Medical Services (IECMS) introduced in China from January 2016 to December 2024. Utilizing the Policy Modeling Consistency (PMC) index model, we seek to achieve a quantitative assessment of these relevant policies.
methodsUtilizing the indicator design method of PMC index model, we constructed first-level indicators for policy evaluation. Second-level indicators were developed with reference to the structure of the IECMS high-quality development support system as outlined by the World Health Organization, the State Council, and the National Health Commission, following a comprehensive literature review. Ultimately, an evaluation system for assessing the high-quality development of IECMS was established, comprising 9 first-level indicators and 44 s-level indicators. The study text-mined 12 policy documents that met predefined inclusion criteria and employed the PMC index model for quantitative evaluation.
resultsThe mean PMC score across these 12 policies was found to be 6.76, indicating that the overall policy system is generally robust; specifically, it includes 8 policies rated as excellent and 4 as good. Notably, areas such as policy concern (X3), party leadership (X8), policy recipients (X2), and carer care (X7) demonstrated comprehensive strengths. However, further improvements are necessary in aspects related to care systems (X6), policy nature (X1), policy measures (X4), and care capacity (X5).
conclusionTo ensure a high-quality supply of elderly care services amidst ongoing developments towards quality enhancement in China's IECMS-related policies must embrace systemic thinking alongside principles of synergy, innovation, and sharing. It is essential to adjust and optimize supply structures while stimulating effective demand; balancing supply-demand elements; focusing on talent cultivation; and innovating within industry environments. These efforts will enable us to meet evolving public expectations for improved living standards in this new era while continuously enriching our understanding of what constitutes high-quality development in IECMS services.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.