School of Humanities and Social Sciences, Guangxi Medical University, Nanning, China.
BMC Prim Care. 2024 May 6;25(1):154. doi: 10.1186/s12875-024-02403-7.
This research aimed to identify the fundamental and geographic characteristics of the primary healthcare personnel mobility in Nanning from 2000 to 2021 and clarify the determinants that affect their transition to non-primary healthcare institutions.
Through utilizing the Primary Healthcare Personnel Database (PHPD) for 2000-2021, the study conducts descriptive statistical analysis on demographic, economic, and professional aspects of healthcare personnel mobility across healthcare reform phases. Geographic Information Systems (QGIS) were used to map mobility patterns, and R software was employed to calculate spatial autocorrelation (Moran's I). Logistic regression identified factors that influenced the transition to non-primary institutions.
Primary healthcare personnel mobility is divided into four phases: initial (2000-2008), turning point (2009-2011), rapid development (2012-2020), and decline (2021). The rapid development stage saw increased mobility with no spatial clustering in inflow and outflow. From 2016 to 2020, primary healthcare worker mobility reached its peak, in which the most significant movement occurred between township health centers and other institutions. Aside from their transition to primary medical institutions, the primary movement of grassroots health personnel predominantly directs towards secondary general hospitals, tertiary general hospitals, and secondary specialized hospitals. Since 2012, the number and mobility distance of primary healthcare workers have become noticeably larger and remained at a higher level from 2016 to 2020. The main migration of primary healthcare personnel occurred in their districts (counties). Key transition factors include gender, education, ethnicity, professional category, general practice registration, and administrative division.
This study provides evidence of the features of primary healthcare personnel mobility in the less developed western regions of China, in which Nanning was taken as a case study. It uncovers the factors that impact the flow of primary healthcare personnel to non-primary healthcare institutions. These findings are helpful to policy refinement and support the retention of primary healthcare workers.
本研究旨在识别 2000 年至 2021 年南宁市基层医疗卫生人员流动的基本特征和地理特征，并阐明影响其向非基层医疗卫生机构流动的决定因素。
利用 2000-2021 年的基层医疗卫生人员数据库（PHPD），对医疗改革各阶段医疗卫生人员流动的人口统计学、经济和专业方面进行描述性统计分析。地理信息系统（QGIS）用于绘制流动模式图，R 软件用于计算空间自相关（Moran's I）。采用 Logistic 回归分析确定影响向非基层机构流动的因素。
基层医疗卫生人员流动分为四个阶段：初始阶段（2000-2008 年）、转折点阶段（2009-2011 年）、快速发展阶段（2012-2020 年）和下降阶段（2021 年）。快速发展阶段，流入和流出均无空间集聚，流动增加。2016 年至 2020 年，基层卫生工作者流动达到高峰，其中乡镇卫生院与其他机构之间的流动最为显著。除向基层医疗机构流动外，基层卫生人员的主要流动方向是二级综合医院、三级综合医院和二级专科医院。自 2012 年以来，基层医疗卫生人员的数量和流动距离明显增加，且 2016 年至 2020 年保持在较高水平。基层医疗卫生人员的主要迁移发生在其所在的区（县）。主要的流动因素包括性别、教育、民族、专业类别、全科医生注册和行政区划。
本研究提供了中国欠发达西部地区基层医疗卫生人员流动特征的证据，以南宁市为例进行了研究。它揭示了影响基层医疗卫生人员流向非基层医疗卫生机构的因素。这些发现有助于政策的完善，并支持基层医疗卫生工作者的留用。
