Preprint Article Version 1 This version is not peer-reviewed

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

Version 1 : Received: 17 May 2019 / Approved: 20 May 2019 / Online: 20 May 2019 (03:13:23 CEST)

How to cite: Yu, H.; Chen, J.; Wang, J.; Chiu, Y.; Qiu, H.; Wang, L. Identification of the Differential Effect of City-level on the Gini Coefficient of Healthcare Service Delivery in Online Health Community. Preprints 2019, 2019050230 (doi: 10.20944/preprints201905.0230.v1). Yu, H.; Chen, J.; Wang, J.; Chiu, Y.; Qiu, H.; Wang, L. Identification of the Differential Effect of City-level on the Gini Coefficient of Healthcare Service Delivery in Online Health Community. Preprints 2019, 2019050230 (doi: 10.20944/preprints201905.0230.v1).

Abstract

Inequality of health service for different specialty categories not only occurs in different areas inequality of health service for different specialty categories in the world, but also happens in the online service platform. In the online health community (OHC), health service was often of inequality for different specialty categories, including both online views and medical consultation for offline registered service. Moreover, how the factor city-level impacts the inequality of health service 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 largest OHC 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 of rich healthcare resources with the potential control cities. For the Gini coefficient of serviced patients in over 100 specialty categories, the average treatment effect of level-1 cities is 0.470, which is 0.029 higher than that of the matched group. Similarly, 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. For each of the specialty categories, we also estimated the average treatment effect the specialty category’s Gini coefficient ( ) with the balanced covariates. The results support the argument that the total Gini coefficient of all the doctors in OHC shows that the inequality of health service is still very serious. This study contributes to the development of the theoretically grounded understanding of the causal effect of city-level on the inequality of health service in an online to offline healthcare service setting.

Subject Areas

Gini coefficient; online health community; medical service delivery; Lorenz curve; inequality of health service; differential Effect

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