Analysis on Temporal and Spatial Evolution and Demand Prediction of TCM Human Resources in TCM Hospitals in China
- VernacularTitle:我国中医类医院中医药人力资源时空演进及需求预测分析
- Author:
Youshu YUAN
1
;
Siying SUN
;
Zhiwei WANG
Author Information
1. 北京中医药大学中医学院 北京 102400
- Publication Type:Journal Article
- Keywords:
Traditional Chinese Medicine Hospitals;
human resources;
evolution of time and space;
demand prediction
- From:
Chinese Hospital Management
2024;44(12):67-72
- CountryChina
- Language:Chinese
-
Abstract:
Objective Examining the expansion pattern and spatial distribution equilibrium of TCM staff in TCM-style hospitals between 2010 and 2021 in China,as well as projecting the shift in the overall staff's trend from 2022 to 2025,will serve as a guide for maximizing the distribution of TCM human resources.Methods The trend of the total number of employees from 2022 to 2025 was predicted using a combination of the ARIMA forecasting model,the GM (1,1) gray forecasting model,and the exponential smoothing model.Spatial autocorrelation analysis was utilized to determine the balance of resource allocation. Results TCM practitioners (assistant),TCM pharmacists (bachelor),and trainee TCM physicians in TCM-type hospitals in China had average annual growth rates of 8.11％,3.95％,and 1.35％,respectively,between 2010 and 2021.In terms of spatial distribution,in 2021,the high-high concentration of TCM practitioners (assistant) per 10000 population was concentrated in the East,TCM practitioners (sergeants) were concentrated in Tianjin and Heilongjiang Province,and trainee TCM practitioners were concentrated in the southwestern region.In terms of temporal changes,the compared to the"13th Five-Year Plan",the average yearly growth rate of TCM personnel in TCM hospitals during the"14th Five-Year Plan"period was comparatively slower.Conclusion There is a spatial clustering of the same qualities and an unequal overall growth tendency of TCM personnel in TCM hospitals in China.However,the spatial clustering trend of TCM workers over time is not consistent.
