How Efficient are Basic Public Health Services Between Urban and Rural in Shandong Province, China? A Data Envelopment Analysis and Panel Tobit Regression Approach

Abstract

Background Improving basic public health services efficiency becomes priority to guarantee its sustainability for Chinese government. This study aimed to explore basic public health services efficiency and its influencing factors between urban and rural in Shandong Province, China, providing policy implications to improve efficiency. Methods This research assessed basic public health services efficiency of 54 districts (representing urban) and 83 counties (representing rural) in Shandong, China, from 2014 to 2019. The data were obtained from Medical Management Service Center of Shandong Health Commission and Statistical Yearbooks. Input variables were subsidy funds, public health staffs and material expenditures. Output variables were assessment indicators covered all service contents from national standard. The data envelopment analysis and panel tobit regression were used to measure efficiency scores and efficiency influencing factors. Results Basic public health services efficiency scores of urban were higher than those of rural during 2014 to 2019. Scale efficiency change and technological change promoted basic public health services total factor productivity change of urban and rural respectively. Panel tobit regression indicated that proportion of health expenditures in general public budget expenditures (P<0.01), subsidy funds (P<0.01), public health personnel expenditures (P<0.01) and the frequency of professional health institutions’ guidance (P<0.01) were positively associated with efficiency in both urban and rural. The number of primary medical and health institutions and public health personnel were positively associated with urban (P<0.01), but those did not affect rural (P>0.10). Conclusion To improve basic public health services efficiency, urban should focus on health resource structure, especially increasing primary medical and health institutions and public health personnel. Rural should expand the input scale, paying more attention to subsidy funds and public health personnel expenditures. The government should also care strengthening the guidance to primary medical and health institutions from professional health institutions.

Data-Driven Evaluation and Optimisation of Livelihood Improvement Efficiency

“…Therefore, social conflicts are concentrated in more populated areas, and the government will face further challenges and difficulties in providing various livelihood services. (3) Regional GDP is a proxy for the level of economic development of a region, and the regression finds that the level of economic development in each region has a certain hindering effect on the efficiency of livelihood improvement, which is inconsistent with the findings of most studies [7,38,56]. On the one hand, this is because higher levels of economic development weaken the government's efforts in cost control, resulting in lower efficiency.…”

“…For example, Lin et al emphasise that population size and population structure can be important influencing factors but do not provide further evidence on their specific impact [55]. Cao et al found empirically that the total population of a region was negatively associated with the efficiency of health services [56]. Khan et al argue that this negative correlation is mainly because, as the population size of a region increases, it negatively affects the equity and fairness of public services, and, by extension, service efficiency [57].…”

“…Regional economic development is also an influential factor considered by scholars in their studies of social governance, and scholars often use gross regional product (GDP) as a measure of regional economic development. Cen et al and Cao et al suggest that regional economic development can effectively contribute to the efficiency of health services [7,56]. Moreover, in their study on the efficiency of government social security spending, Hu et al concluded that higher GDP contributes to more efficient government work [38].…”

“…(2) Population size (PS): An increase in population size may lead to the inequitable distribution of public service resources but may also increase the efficiency of government service delivery owing to the agglomeration effect of population. Based on previous research findings [ [55][56][57][58], it is speculated that the total population is a possible influence; however, based on the existing research literature, inconsistent conclusions have been reached, and further validation is needed to determine how this affects LIE. This study uses the total population of the region to represent the population size.…”

“…The urbanisation level is represented by urban population/total population of the region. (6) Economic Development Level (EDL): The regional level of economic development will affect the overall social governance efficiency of the region [7,38,56], and, as the income level of the residents changes, people will have higher demands on the level of social governance, resulting in changes in their evaluation. Thus, we assume that the regional level of economic development will impact LIE.…”