摘要
目的 分析广东省57个县(市)域内住院率的时空特征及其影响因素.方法 利用2016-2019年广东省57个县(市)域内住院率及相关指标,采用时间趋势分析、空间自相关分析广东省县域内住院率的时空特征,采用贝叶斯时空模型分析影响县域住院率的因素.结果 广东省县域内住院率由2016年的79.8%上升到2019年84.1%,呈逐年上升趋势,但区域间差异仍然较大,整体上"西高东低".全局和局部空间自相关结果表明,广东省县域内住院率存在空间相关性,在部分区域形成了空间聚集,粤西地区存在"高-高"聚集,粤东地区存在"低-低"聚集.贝叶斯时空模型显示,影响县域内住院率的最主要因素是每千人口本科及以上医师人数和县(市)人民医院的病例组合指数(P＜0.05).结论 广东省可通过多种途径因地制宜引进或培养优质人才,实质性提高县级医院的医疗服务能力,持续提高县域内住院率.
Abstract
Objective To analyze the spatio-temporal characteristics and influencing factors of local hospitalization proportion in 57 counties of Guangdong Province.Methods Using local hospitalization proportion and related indicators in 57 counties of Guangdong Province from 2016 to 2019,temporal trend analysis and spatial autocorrelation analy-sis were used to analyze the spatiotemporal characteristics.Bayesian spatio-temporal model was used to explore in-fluencing factors of local hospitalization proportion.Results The local hospitalization proportion in Guangdong Province rose from 79.8%in 2016 to 84.1%in 2019,showing an increasing trend and the overall characteristics of"high in the west and low in the east".The global and local spatial autocorrelation results show that there is a spatial correla-tion in the local hospitalization proportion within the counties of Guangdong Province,and spatial aggregation has formed in some areas.There is a"high"aggregation in western Guangdong,and a"low"aggregation in eastern Guangdong Province.The Bayesian spatio-temporal model shows that the number of people with a bachelor's de-gree or above per 1 000 population and the CMI of county hospitals had an effect on the local hospitalization propor-tion(P＜0.05).Conclusion Guangdong Province can improve the medical service capacity of county hospitals sub-stantially and introduce or train high-quality talents through multiple measures,and continue to improve the local hospitalization proportion.
NETL
NSTL
维普
万方数据