四川省护理人力资源发展变化及预测研究

Development and prediction of nursing human resources in Sichuan

目的对四川省2000~2019年护理人力资源的发展趋势进行统计分析,预测2020~2022年护理人力资源的数量变化,为今后制定科学合理的护理人力卫生规划提供参考依据。方法采用描述统计学方法和基尼系数法分析护理人力资源及公平性发展情况,运用R语言统计软件构建ARIMA时间序列模型预测护理人力需求量。结果四川省2000~2019年注册护士数量整体呈上升趋势,护士总数由59665人增加至270616人,年均增长率为8.10%;每千人口注册护士由0.71人增至2.97人,高于全国平均水平;按地理分布护理人力资源基尼系数均值为0.6028,按人口分布护理人力资源基尼系数均值为0.1922;确定ARIMA(1,2,0)为最优拟合模型,MAPE为2.15%,2020~2022年注册护士数分别为292256人、314493人和336515人。结论四川省护理人力资源总量得到改善,未来三年将呈递增趋势,注册护士配置不均衡,护理人力资源人口分布公平性明显优于地理分布,政府应重视地区人员分配,严格把控护理人力资源供需平衡关系。

Objective To analyze the development trend of nursing human resources in Sichuan Province from 2000 to 2019,and predict the change of nursing human resources from 2020 to 2022,so as to provide reference for making scientific and reasonable nursing human health planning in the future.Methods Descriptive statistics and Gini coefficient were used to analyze the development of nursing human resources and equity.ARIMA time series model was constructed by R language statistical software to predict the demand of nursing human resources.Results The total number of registered nurses from 2000 to 2019 increased from 59665 to 270616,with an average annual growth rate of 8.10%.The number of registered nurses per thousand people increased from0.71 to 2.97,higher than the national average.The average Gini coefficient of nursing human resources was 0.6028 by geographical distribution and 0.1922 by population distribution.The results showed that ARIMA(1,2,0)was the best fitting model,MAPE was2.15%,and the number of registered nurses in 2020-2022 was predicted to be 292256,314493 and 336515 respectively.Conclusion The total amount of nursing human resources in Sichuan Province has been improved and will show an increasing trend in the next three years.The allocation of registered nurses is not balanced.The equity of nursing human resources allocation by population distribution is obviously superior to that by geographical distribution.The government should attach importance to regional personnel distribution and strictly control the balance between supply and demand of nursing human resources.