An empirical study of preventive healthcare policy under the synergy of education and corporate financial monitoring
IntroductionPreventive healthcare policies are critical for improving public health outcomes and reducing the socioeconomic burden of diseases, aligning closely with the theme of enhancing residents' health welfare through robust social security systems. However, traditional approaches often ov...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2025-04-01
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| Series: | Frontiers in Public Health |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpubh.2025.1540618/full |
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| author | Jin Zhao |
| author_facet | Jin Zhao |
| author_sort | Jin Zhao |
| collection | DOAJ |
| description | IntroductionPreventive healthcare policies are critical for improving public health outcomes and reducing the socioeconomic burden of diseases, aligning closely with the theme of enhancing residents' health welfare through robust social security systems. However, traditional approaches often overlook the dynamic interplay between economic factors and health outcomes, limiting their effectiveness in designing sustainable interventions.MethodsTo address these gaps, this study leverages corporate financial monitoring as a novel lens for assessing the effectiveness of preventive healthcare policies. Utilizing the Advanced Financial Monitoring Neural Framework (AFMNF) and the Dynamic Risk-Adaptive Framework (DRAF), we integrate deep learning techniques with dynamic risk modeling to analyze the financial and health impacts of such policies. Our methodology involves monitoring corporate financial metrics, anomaly detection, and trend analysis to identify correlations between policy implementation and economic indicators.Results and discussionThe results demonstrate that integrating financial insights with health policy evaluation improves prediction accuracy of socioeconomic outcomes by 40% and enhances anomaly detection in policy performance by 30%. This adaptive framework offers a scalable, real-time approach to monitoring, providing actionable insights for policymakers to optimize preventive healthcare strategies. This study underscores the importance of interdisciplinary methods in advancing public health outcomes through innovative, data-driven frameworks. |
| format | Article |
| id | doaj-art-d5a0c6a7e0764cfa80171d76fd3e1b86 |
| institution | DOAJ |
| issn | 2296-2565 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Public Health |
| spelling | doaj-art-d5a0c6a7e0764cfa80171d76fd3e1b862025-08-20T03:05:18ZengFrontiers Media S.A.Frontiers in Public Health2296-25652025-04-011310.3389/fpubh.2025.15406181540618An empirical study of preventive healthcare policy under the synergy of education and corporate financial monitoringJin ZhaoIntroductionPreventive healthcare policies are critical for improving public health outcomes and reducing the socioeconomic burden of diseases, aligning closely with the theme of enhancing residents' health welfare through robust social security systems. However, traditional approaches often overlook the dynamic interplay between economic factors and health outcomes, limiting their effectiveness in designing sustainable interventions.MethodsTo address these gaps, this study leverages corporate financial monitoring as a novel lens for assessing the effectiveness of preventive healthcare policies. Utilizing the Advanced Financial Monitoring Neural Framework (AFMNF) and the Dynamic Risk-Adaptive Framework (DRAF), we integrate deep learning techniques with dynamic risk modeling to analyze the financial and health impacts of such policies. Our methodology involves monitoring corporate financial metrics, anomaly detection, and trend analysis to identify correlations between policy implementation and economic indicators.Results and discussionThe results demonstrate that integrating financial insights with health policy evaluation improves prediction accuracy of socioeconomic outcomes by 40% and enhances anomaly detection in policy performance by 30%. This adaptive framework offers a scalable, real-time approach to monitoring, providing actionable insights for policymakers to optimize preventive healthcare strategies. This study underscores the importance of interdisciplinary methods in advancing public health outcomes through innovative, data-driven frameworks.https://www.frontiersin.org/articles/10.3389/fpubh.2025.1540618/fullpreventive healthcarefinancial monitoringpublic health policiesdynamic modelingsocioeconomic analysis |
| spellingShingle | Jin Zhao An empirical study of preventive healthcare policy under the synergy of education and corporate financial monitoring Frontiers in Public Health preventive healthcare financial monitoring public health policies dynamic modeling socioeconomic analysis |
| title | An empirical study of preventive healthcare policy under the synergy of education and corporate financial monitoring |
| title_full | An empirical study of preventive healthcare policy under the synergy of education and corporate financial monitoring |
| title_fullStr | An empirical study of preventive healthcare policy under the synergy of education and corporate financial monitoring |
| title_full_unstemmed | An empirical study of preventive healthcare policy under the synergy of education and corporate financial monitoring |
| title_short | An empirical study of preventive healthcare policy under the synergy of education and corporate financial monitoring |
| title_sort | empirical study of preventive healthcare policy under the synergy of education and corporate financial monitoring |
| topic | preventive healthcare financial monitoring public health policies dynamic modeling socioeconomic analysis |
| url | https://www.frontiersin.org/articles/10.3389/fpubh.2025.1540618/full |
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