摘要
目的 分析并预测四川省医疗服务需求整体演变趋势,为政府及相关职能部门拟定卫生发展规划和配置医疗资源提供对策建议。方法 本研究选取诊疗人数和入院人数为因变量,采用LASSO回归模型对所筛选的10个自变量进行建模处理与预测分析。结果 通过模型筛选可得,65周岁以上人口比重、地区生产总值、居民消费水平、医疗机构数、灾害人员伤亡数量对医疗服务需求有统计学意义。2001—2020年四川全省诊疗人数近约增涨785.9%;入院人数约增涨854.5%;自2008年以后,医疗机构诊疗人数上升趋势相对较为明显。统计预测结果表明,到2025年四川省诊疗人数近约6.7亿人,入院人数达2463.7万人。结论 四川省未来5年的医疗服务需求仍持续增加,地方政府既要注重从宏观角度适当调控医疗卫生资源整体布局使卫生服务供给均等化,又要优化卫生系统内部结构合理性;探寻医养结合等新型养老模式,提高城乡医保报销合理比例;配备紧急医疗物资,加强突发灾害预警机制。
Objective To analyze and predict the overall evolution trend of medical service demand in Sichuan Province,and to provide suggestions for the government and related departments to formulate health development plans and allocate medical resources.Methods In this study,the number of patients and the number of admissions were selected as dependent variables,and the LASSO regression model was used to model and predict the 10 independent variables screened.Results There was a statistical significance on the demand for medical services in the proportion of the population over 65 years old,the GDP of the region,the consumption level of residents,the number of medical institutions,and the number of disaster casualties.From 2001 to 2020,the number of diagnosis and treatment in Sichuan province increased by approximately 785.9%;the number of hospital admissions increased by approximately 854.5%;especially since 2008.Statistical prediction results show that by 2025,the number of patients in Sichuan Province would reach approximately 670 million,and the number of admissions would reach 24.637 million.Conclusion The demand for medical services in Sichuan Province will continue to increase in the next five years.It is the important responsibility of local government and health departments to explore new pension models;to increase the reasonable proportion of urban and rural medical insurance reimbursement;to equip emergency medical supplies,and to strengthen the forecast for disasters.
作者
张宁
宁宁
王冰洁
刘莹
ZHANG Ning;NING Ning;WANG Bingjie;LIU Ying(Harbin Medical University,Harbin Heilongjiang 150081,China)
出处
《中国急救复苏与灾害医学杂志》
2023年第11期1448-1451,共4页
China Journal of Emergency Resuscitation and Disaster Medicine
基金
国家自然科学基金(编号:71874044
71473065)。
关键词
LASSO
医疗服务需求
分析
预测
LASSO
Medical service requirements
Analysis
Forecast