摘要
目的:分析宁夏居民基层医疗卫生机构就诊率的主要关联因素,并预测2023-2027年基层就诊率,以期为政府进一步优化基层首诊秩序提供决策参考。方法:选取2013-2022年宁夏居民基层医疗卫生机构就诊率作为参考数列,以基层医疗卫生机构数、床位数、卫生技术人员数、次均门诊费用、次均住院费用等指标作为比较数列,运用灰色关联分析验证主要关联因素,利用GM(1,1)模型预测各关联因素2023-2027年数据,构建预测模型,选取相对最优的遗传算法优化BP神经网络模型预测2023-2027年基层就诊率。结果:各指标与居民基层就诊率的灰色关联度均大于0.6,基层医疗卫生机构数(γ=0.9199)与基层就诊率的关联度最高,其后为城乡居民基本医疗保险参保人数(γ=0.9055)、人口死亡率(γ=0.8526)、基层医疗卫生机构床位数(γ=0.8464)、城镇职工基本医疗保险参保人数(γ=0.8230)和65岁及以上人口数(γ=0.8100)等。通过模型预测,2023年基层就诊率为42.6827%,2027年逐渐上升为45.2257%。结论:宁夏居民基层就诊率与基层医疗卫生资源配置、基本医疗保险参保人数、人群健康状况、老年人口数量、医疗费用及居民收入水平强关联。灰色-GA-BP神经网络组合模型预测精度较高,2023-2027年基层就诊率将逐步提升。
Objective:To analyze the main correlation factors of the visit rate of grassroots medical and health institutions among residents in Ningxia,and predict the visit rate of grassroots medical and health institutions from 2023 to 2027,so as to provide decision-making reference for the government to further optimize the order of first visit at the grassroots level.Methods:The visit rate of grassroots medical and health institutions among residents in Ningxia from 2013 to 2022 as the reference series were selected,and the indicators including number of grassroots medical and health institutions,number of beds,number of health technicians,average outpatient expenses and average hospitalization expenses were compared.This study used grey correlation analysis to verify the main correlation factors,used the GM(1,1)model to predict the data of each correlation factor from 2023 to 2027,constructed a prediction model,and selected the relatively optimal genetic algorithm to optimize the BP neural network model to predict the grassroots medical treatment rate from 2023 to 2027.Results:The grey correlation degree between each index and the grassroots medical treatment rate was greater than 0.6 among residents.The number of grassroots medical and health institutions(γ=0.9199)had the highest correlation degree with the grassroots medical treatment rate,followed by the number of urban and rural residents covered by basic medical insurance(γ=0.9055),the population mortality rate(γ=0.8526),the number of beds in grassroots medical and health institutions(γ=0.8464),the number of urban workers covered by basic medical insurance(γ=0.8230)and the number of people aged 65 and over(γ=0.8100).The model showed that the rate of grassroots care visits would rise to 42.6827%in 2023 and 45.2257%in 2027.Conclusion:The rate of grassroots consultation among residents in Ningxia is strongly related to the allocation of grassroots medical and health resources,the number of people enrolled in basic medical insurance,the health status of the population,the number of elderly population,medical expenses and residents'income level.The prediction accuracy of gray-GA-BP neural network combination model is high,and the grassroots consultation rate will gradually increase from 2023 to 2027.
作者
吕彩鹏
苏源
杨静
余芳
王娜
LV Caipeng(School of Humanities and Management,Ningxia Medical University,Yinchuan,Ningxia,750004,China)
出处
《医学与社会》
北大核心
2024年第1期71-77,共7页
Medicine and Society
基金
国家自然科学基金资助项目,编号为71964028
教育部人文社会科学研究青年项目,编号为19YJC630144
宁夏医科大学特殊人才启动项目,编号为XT2020020。
关键词
基层医疗卫生机构
就诊率
居民
宁夏
Grassroots Medical and Health Institution
Visit Rate
Resident
Ningxia
