在中国使用达特茅斯方法划定医院服务区域（HSA），并确定假设的需求方，HSA内卫生支出的供应方和地区特定因素。
基于人口的描述性研究。
我们选择了成都的大都市，中国人口最多的三个城市之一作为分析案例，大约1633万居民居住在那里。
四川省卫生健康委员会提取了2018年第四季度（9月1日至12月31日）的个人住院记录（n=904298）。从数据集中排除了非成都居民的病例。
我们进行了三组分析：（1）应用达特茅斯方法来描绘HSA；（2）使用基于地理信息系统（GIS）的方法来证明所描绘的HSA之间的卫生支出变化；（3）采用三级多级线性模型来检查卫生支出与需求方之间的关联，供给侧和特定地区的因素。
描绘了总共113个HSA，中位种群为60472（范围从7022到827750）。在调整了年龄和性别后，HSA每次入院的住院总支出差异超过三倍。除了需求方面的因素，越来越多的医生，较高水平的医疗设施和营利性医疗设施与住院总支出的增加显著相关.在HSA级别,位于单个HSA中的私人医疗保健设施的比例与该HSA产生的住院总支出增加有关，而HSA中医疗设施数量的增加与住院总支出呈负相关.
HSA被划定，以帮助建立一个负责任的医疗保健提供系统，作为当地医院市场，通过将需求者与特定HSA内的供应商联系起来，提供住院医疗保健。政策制定者应采用HSA，以确定不同地区之间住院总支出的差异以及潜在的相关因素。基于HSA的分析结果可以为相关卫生政策的制定和医疗资源分配的优化提供信息。
To delineate hospital service areas (HSAs) using the Dartmouth approach in
China and identify the hypothesised demand-side, supply-side and region-specific factors of health expenditure within HSAs.
Population-based descriptive study.
We selected the metropolis of Chengdu, one of the three most populous cities in
China as a case for the analysis, where approximately 16.33 million residents living.
Individual-level in-patient discharge records (n=904 298) during the fourth quarter of 2018 (from 1 September to 31 December) were extracted from Sichuan Health Commission. Cases of non-residents of Chengdu were excluded from the datasets.
We conducted three sets of analyses: (1) apply Dartmouth approach to delineate HSAs; (2) use Geographic Information System (GIS)-based method to demonstrate health expenditure variations across delineated HSAs and (3) employ a three-level multilevel linear model to examine the association between health expenditure and demand-side, supply-side and region-specific factors.
A total of 113 HSAs with a median population of 60 472 (ranging from 7022 to 827 750) was delineated. Total in-patient expenditure per admission varied more than threefold across HSAs after adjusting for age and gender. Apart from a list of demand-side factors, an increased number of physicians, healthcare facilities at higher levels and for-profit healthcare facilities were significantly associated with increased total in-patient expenditures. At the HSA level, the proportion of private healthcare facilities located in a single HSA was associated with increased total in-patient expenditure generated by that HSA, while the increased number of healthcare facilities in a HSA was negatively associated with the total in-patient expenditures.
HSAs were delineated to help establish an accountable healthcare delivery system, which serves as local hospital markets to provide in-patient healthcare via connecting demanders with suppliers inside particular HSAs. Policy-makers should adopt HSAs to identify variations of total in-patient expenditures among different areas and the potential associated factors. Findings from the HSA-based analysis could inform the formulation of relevant health policies and the optimisation of healthcare resource allocations.
