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Identification of the Differential Effect of City-Level on the Gini Coefficient of Health Service Delivery in Online Health Community

Bibliographic Data

ID15501501
AuthorsHaiyan Yu (0000-0003-0295-6471, corresponding author), Hai-Yan Yu (0000-0002-6473-8552, Chongqing University of Posts and Telecommunications, corresponding author), Jingjing Chen (0000-0002-5814-8695, Chongqing University of Posts and Telecommunications), Jing-Jing Chen (Chongqing University of Posts and Telecommunications), Jying-Nan Wang (0000-0002-2315-2520, Zhejiang Yuexiu University), Jying‐Nan Wang, Ya-Ling Chiu (0000-0002-0573-6979, Zhejiang Yuexiu University), Hang Qiu (0000-0002-5380-2870, University of Electronic Science and Technology of China), Liya Wang (0000-0002-4343-3442, University of Electronic Science and Technology of China), Li-Ya Wang (Big Data Research Center, University of Electronic Science and Technology of China, Chengdu 611731, China)
Year2019
Volume16
Issue13
Pages2314-2314
Publication date2019-06-29
Open AccessYes
TypeARTICLE
VenueInternational Journal of Environmental Research and Public Health (JOURNAL)
Journal identifiersISSN: 1661-7827 • E-ISSN: 1660-4601
PublisherMultidisciplinary Digital Publishing Institute (PUBLISHER • CH)
DOI10.3390/ijerph16132314
PMID31261952
OpenAlexW2950734464
LanguageEN
Citations received2
References cited32

Inequality of health services for different specialty categories not only occurs in different areas in the world, but also happens in the online service platform. In the online health community (OHC), health services often display inequality for different specialty categories, including both online views and medical consultations for offline registered services. Moreover, how the city-level factors impact the inequality of health services in OHC is still unknown. We designed a causal inference study with data on distributions of serviced patients and online views in over 100 distinct specialty categories on one of the largest OHCs in China. To derive the causal effect of the city-levels (two levels inducing 1 and 0) on the Gini coefficient, we matched the focus cases in cities with rich healthcare resources with the potential control cities. For each of the specialty categories, we first estimated the average treatment effect of the specialty category's Gini coefficient (SCGini) with the balanced covariates. For the Gini coefficient of online views, the average treatment effect of level-1 cities is 0.573, which is 0.016 higher than that of the matched group. Similarly, for the Gini coefficient of serviced patients, the average treatment effect of level-1 cities is 0.470, which is 0.029 higher than that of the matched group. The results support the argument that the total Gini coefficient of the doctors in OHCs shows that the inequality in health services is still very serious. This study contributes to the development of a theoretically grounded understanding of the causal effect of city-level factors on the inequality of health services in an online to offline health service setting. In the future, heterogeneous results should be considered for distinct groups of doctors who provide different combinations of online contributions and online attendance

Business · Economic inequality · Family medicine · Gini coefficient · Inequality · Lorenz curve · Service (business · Sociology · Specialty · Advanced Causal Inference Techniques · Demography · Healthcare Policy and Management · Healthcare Systems and Reforms · Mathematics · Medicine · Marketing

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Citations per year0.33
Citation span2020 - 2023 (4)
Highly citedNo

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