Background: Unequal access to primary healthcare (PHC) has become a critical issue in global health inequalities, requiring governments to implement policies tailored to communities’ needs and abilities. However, the place-based facility dimension of PHCs is oversimplified in current healthcare literature, and formulating the equity-oriented PHC spatial planning remains challenging without understanding the multiple impacts of community socio-spatial dynamics, particularly in remote areas. This study aims to push the boundary of PHC studies one step further by presenting a nuanced and dynamic understanding of the impact of community environments on the uneven primary healthcare supply. Methods: Focusing on Shuicheng, a remote rural area in southwestern China, multiple data are included in this village-based study, i.e., the facility-level healthcare statistics data (2016–2019), the statistical yearbooks, WorldPop, and Chinese GDP’s spatial distribution data. We evaluate villages’ PHC service capacity using the number of doctors and essential equipment per capita, which are the major components of China’s PHC delivery. The indicators describing community environments are selected based on extant literature and China’s planning paradigms, including town- and village-level factors. Gini coefficients and local spatial autocorrelation analysis are used to present the divergences of PHC capacity, and multilevel regression model and (heterogeneous) difference in difference model are used to examine the driving role of community environments and the dynamics under the policy intervention. Results: Despite the general improvement, PHC inequalities remain significant in remote rural areas. The village’s location, aging, topography, ethnic autonomy, and economic conditions significantly influence village-level PHC capacity, while demographic characteristics and healthcare delivery at the town level are also important. Although it may improve the hardware setting in village clinics (coef. = 0.350), the recent equity-oriented policy attempts may accelerate the loss of rural doctors (coef. = − 0.517). Notably, the associations between PHC and community environments are affected inconsistently by this round of policy intervention. The town healthcare centers with higher inpatient service capacity (coef. = − 0.514) and more licensed doctors (coef. = − 0.587) and nurses (coef. = − 0.344) may indicate more detrimental policy effects that reduced the number of rural doctors, while the centers with more professional equipment (coef. = 0.504) and nurses (coef. = 0.184) are beneficial for the improvement of hardware setting in clinics. Conclusions: The findings suggest that the PHC inequalities are increasingly a result of joint social, economic, and institutional forces in recent years, underlining the increased complexity of the PHC resource allocation mechanism. Therefore, we claim the necessity to incorporate a broader understanding of community orientation in PHC delivery, particularly the interdisciplinary knowledge of the spatial lens of community, to support its sustainable development. Our findings also provide timely policy insights for ongoing primary healthcare reform in China.

Background The primary care facilities in a region play a vital role in maintaining the health of the local residents as the gatekeeper. At present，there is a lack of research on the allocation of primary care resources in Tibet，a remote autonomous region in northwestern China. Objective To analyze the current situation and equity of the allocation of primary care resources in Tibet，to provide a scientific basis for optimizing the allocation of primary care resources in Tibet. Methods Data used in this study were from six volumes（2015—2020） of Tibetan Health Statistics Yearbook and China Health Statistics Yearbook，as well as the human resource information in the Primary Care Direct Reporting System of Tibet Health Commission from 2015 to 2020. Descriptive analysis was used to analyze the allocation of primary care resources in Tibet from 2015 to 2020. Gini coefficient and concentration index were used to evaluate the equity of primary care resource allocation in Tibet in 2020. Results The number of beds in primary hospitals in Tibet increased from 3 393 in 2015 to 3 867 in 2020. The number of （assistant）practicing physicians per 1 000 people increased from 0.37 in 2015 to 0.61 in 2020. The utilization rate of beds in primary hospitals decreased from 30.9% in 2015 to 11.5% in 2020. The daily visits per primary care physician decreased from 13.80 in 2015 to 9.95 in 2020. The daily number of hospital bed days of care per primary care physician decreased from 0.44 in 2015 to 0.10 in 2020. In 2020，the Gini coefficients of health resources allocated in primary hospitals according to population in Tibet were greater than 0.3，which were better than those allocated according to geography. The difference in the concentration degree between number of beds，number of health technicians，number of（assistant） practicing physicians or number of registered nurses and population，was -6.93，-4.50，-2.50，-6.15，respectively，in Lhasa，and 0.05，-0.21，-0.80，-0.22，respectively，in Changdu，and -0.88，0.10，0.47，-0.05，respectively，in Shannan，but was all greater than 0 in other cities. Conclusion The primary health workers in Tibet showed a trend of "low growth in number，low capability and low efficiency". It is suggested to pay attention to regional characteristics to improve the allocation standards of primary care resources，promote the equity of the allocation of primary care resources based on geographical classification，reform the employment mechanism and human resource management system in primary care，innovate the system and mechanism of aiding Tibet and establish a new model of financial investment at the primary level.

In Australia，28% of the population live in remote and rural areas，where they face many health service utilization challenges due to geographical conditions，and generally have lower health status than those living in coastal metropolitan areas. To address the challenges of accessing health services in remote and rural areas，the Australian Government Department of Health and Aged Care has introduced a geographical classification system to help healthcare providers to improve healthcare services since 1994，and regularly updated the system to adapt to the latest sociodemographic and healthcare status，as well as formulated a range of complementary health policies to support rural and remote areas. From 2018，Australian Government Department of Health and Aged Care has adopted a new classification standard，the Modified Monash Model. We reviewed Australia's practices and concluded that，to better deliver high-quality and accessible healthcare services to areas with weak healthcare resources in China，Australia's experience could be used for reference，during taking actions to promote and refine the geographic classification system for healthcare services in a timely manner，formulating policies supporting the enhancement of access to health workers systematically，and taking advantage of modern，high and new technologies.