A study on national nursing human resources forecast based on grey model
10.3969/j.issn.1671-332X.2024.12.004
- VernacularTitle:基于灰色模型的全国护理人力资源预测研究
- Author:
Cuiling ZHANG
1
;
Suiyun WENG
1
;
Min YU
1
;
Ziling CHEN
1
;
Xiangyun LU
1
;
Jianer XIE
1
;
Miaoling JIANG
1
Author Information
1. 广州医科大学附属脑科医院//广东省神经科学疾病研究重点实验室、神经致病基因和离子通道教育部重点实验室 广东 广州 510370
- Publication Type:Journal Article
- Keywords:
Grey model;
Nursing;
Human resources;
Forecast
- From:
Modern Hospital
2024;24(12):1817-1820,1827
- CountryChina
- Language:Chinese
-
Abstract:
Objective To forecast the national nursing human resources situation and provide policy basis for promoting the development of the nurse team.Methods The registered nurse numbers,the total population,the registered(assistant)physician numbers,and the bed numbers in medical and health institutions(in thousands)were selected from 2013 to 2023,and the bed-to-nurse ratio,doctor-to-nurse ratio,and the number of nurses per thousand population were calculated and analyzed to study the changes in national nursing human resources over the past decade.A grey GM(1,1)model was established to predict the number of nurses per thousand population from 2024 to 2030.Results ① The number of nurses per thousand population has increased year by year in the past decade,with an average annual growth rate of 11.38％;② The precision of the grey GM(1,1)model for the number of nurses per thousand population is precise(α=-0.065 9,b=2.014 1,C value=0.003 3,P=1.000),with high fitting degree.And the predicted number of registered nurses per thousand population from 2024 to 2030 are 4.291,4.584,4.896,5.229,5.585,5.965,and 6.371 respectively.Conclusion The national nursing human resources allocation has been optimized in the past decade,and the GM(1,1)model predicts that the national nursing human resources change is also in an upward trend.However,relevant policies still need to be formulated to improve the bed-to-nurse ratio and doctor-to-nurse ratio.
