The impacts on population health by China's regional health data centers and the potential mechanism of influence
Background China recently established a series of pilot regional health data centers with a mandate to acquire, consolidate, analyze, and translate data into evidence for health policy decision-making. This experiment with “big data” has the potential to influence population health and is the focus...
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| Format: | Article |
| Language: | English |
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SAGE Publishing
2025-01-01
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| Series: | Digital Health |
| Online Access: | https://doi.org/10.1177/20552076251314102 |
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| author | Jiaoli Cai Yue Li Peter C Coyte |
| author_facet | Jiaoli Cai Yue Li Peter C Coyte |
| author_sort | Jiaoli Cai |
| collection | DOAJ |
| description | Background China recently established a series of pilot regional health data centers with a mandate to acquire, consolidate, analyze, and translate data into evidence for health policy decision-making. This experiment with “big data” has the potential to influence population health and is the focus of this study. Methods This study used national longitudinal survey data from the China Family Panel Studies over the period 2014–2020 to empirically assess the impact of China's establishment of pilot regional health data centers on population health and health inequality. A difference-in-differences model was employed to investigate the policy effect on population health, with additional exploration of possible mechanisms of influence. The corrected concentration index was used to measure health inequality, while Wagstaff decomposition method was applied to examine the marginal influence of the policy effect on health inequality. Results Overall health status of local residents has improved after the establishment of the pilot regional health data centers. Using mechanism analysis, the findings demonstrated that improvements to population health were driven by promoting healthy lifestyles and innovations in medical practices. Furthermore, due to differences in individual e-health literacy, the pilot centers produced “pro-rich” health inequality where high-income groups benefited more from the establishment of the pilot centers in terms of health than low-income groups. Conclusions This study has highlighted the potential to improve population health, in general, with the advent of big data centers, but for these benefits be unevenly distributed among the resident population. |
| format | Article |
| id | doaj-art-d2991d5f06be43c7a31a7012f0c99f4f |
| institution | Kabale University |
| issn | 2055-2076 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | Digital Health |
| spelling | doaj-art-d2991d5f06be43c7a31a7012f0c99f4f2025-01-17T17:04:09ZengSAGE PublishingDigital Health2055-20762025-01-011110.1177/20552076251314102The impacts on population health by China's regional health data centers and the potential mechanism of influenceJiaoli Cai0Yue Li1Peter C Coyte2 Research Center for Central and Eastern Europe, , Beijing, China School of Economics and Management, , Beijing, China Institute of Health Policy, Management and Evaluation, , Toronto, Ontario, CanadaBackground China recently established a series of pilot regional health data centers with a mandate to acquire, consolidate, analyze, and translate data into evidence for health policy decision-making. This experiment with “big data” has the potential to influence population health and is the focus of this study. Methods This study used national longitudinal survey data from the China Family Panel Studies over the period 2014–2020 to empirically assess the impact of China's establishment of pilot regional health data centers on population health and health inequality. A difference-in-differences model was employed to investigate the policy effect on population health, with additional exploration of possible mechanisms of influence. The corrected concentration index was used to measure health inequality, while Wagstaff decomposition method was applied to examine the marginal influence of the policy effect on health inequality. Results Overall health status of local residents has improved after the establishment of the pilot regional health data centers. Using mechanism analysis, the findings demonstrated that improvements to population health were driven by promoting healthy lifestyles and innovations in medical practices. Furthermore, due to differences in individual e-health literacy, the pilot centers produced “pro-rich” health inequality where high-income groups benefited more from the establishment of the pilot centers in terms of health than low-income groups. Conclusions This study has highlighted the potential to improve population health, in general, with the advent of big data centers, but for these benefits be unevenly distributed among the resident population.https://doi.org/10.1177/20552076251314102 |
| spellingShingle | Jiaoli Cai Yue Li Peter C Coyte The impacts on population health by China's regional health data centers and the potential mechanism of influence Digital Health |
| title | The impacts on population health by China's regional health data centers and the potential mechanism of influence |
| title_full | The impacts on population health by China's regional health data centers and the potential mechanism of influence |
| title_fullStr | The impacts on population health by China's regional health data centers and the potential mechanism of influence |
| title_full_unstemmed | The impacts on population health by China's regional health data centers and the potential mechanism of influence |
| title_short | The impacts on population health by China's regional health data centers and the potential mechanism of influence |
| title_sort | impacts on population health by china s regional health data centers and the potential mechanism of influence |
| url | https://doi.org/10.1177/20552076251314102 |
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