摘要
目的:探讨上海市恶性肿瘤患者终末期住院费用的影响因素,并针对其影响因素提出合理控制住院费用的相关政策建议。方法:选取2014—2015年上海市医疗机构收治的10 065例恶性肿瘤患者为研究对象,运用多元线性回归分析恶性肿瘤患者终末期住院费用的影响因素。结果:10 065例患者住院时间的中位数为43 d,年龄为(70.73±12.87)岁;其中61.66%的住院患者为男性,恶性肿瘤患者住院费用的中位数为55 447.84元;住院费用的变化与转归情况、医疗保险类型、医院级别、医院类型、肿瘤部位、住院天数、是否手术、年龄、距离死亡时间、性别存在联系。结论:恶性肿瘤患者的终末期住院费用存在接近死亡效应,应当合理配置医疗资源,采取综合措施,合理控制终末期住院费用增长。
Objective： To explore the influential factors for hospitalization costs regarding the final phase of malignant tumor patients in Shanghai, and to explore the relevant policy for reasonable control of hospitalization costs. Methods： A total of 10 065 patients with malignant tumors were enrolled in this study. The multiple linear regression analysis was used to seek the determinants for hospitalization cost of malignant tumor patients during the final phase. Results. The median length of hospital stay was 43 days for the patients, with an average age of （70.73± 12.87） years. Among them 61.66% of hospitalized patients were male and the median hospitalization cost of malignancy was 55 447.84 yuan. Hospitalization cost showed the linear regression relationship with type of health care, hospital level, hospital types, tumor types, length of hospital sta^5 surger）5 age, gender, and time from hospital admission to death. Conclusion： Proximity to death in malignant tumor patients is an important factor for the hospitalization cost. Medical resources should be allocated rationally, and the comprehensive measures should be taken to control the cost reasonably.
作者
贺志敏
李芬
金春林
朱碧帆
张静航
杨土保
HE Zhimin;LI Fen;JIN Chunlin;ZHU Bifan;ZHANG Jinghang;YANG Tubao(Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha 410008;Health Policy Research Department, Shanghai Health Development Research Center, Shanghai 200031, China)
出处
《中南大学学报（医学版）》
CAS
CSCD
北大核心
2018年第1期68-75,共8页
Journal of Central South University ：Medical Science
基金
英国外交与联邦事务部"中国繁荣战略项目基金"(16SS23)~~
关键词
恶性肿瘤
住院费用
终末期
多元线性回归
影响因素
malignant tumor
hospitalization cost
final phase
multiple linear regression
influencial factors
