新形势下精细化统计方法对恶性肿瘤患者经济负担的分析  

Analysis of Direct Economic Burden of Malignant Tumor Patients under the New Situation Refined Statistical Method

作　　者：李君[1] 曹良海 LI Jun;CAO Lianghai(Yibin Hospital of Sichuan University,Yibin 644000,China)

机构地区：[1]四川大学华西医院宜宾医院,四川宜宾644000

出　　处：《经济研究导刊》2024年第15期153-156,共4页Economic Research Guide

基　　金：宜宾市卫健委科研立项课题(2022YW020)。

摘　　要：探讨DRG付费下恶性肿瘤患者住院费用影响因素,以期为降低恶性肿瘤患者的直接经济负担提供参考。采用SPSS26.0建立BP神经网络模型,运用回顾性分析方法,对某地级市三级甲等医院实施DRG前后(2022—2023年)恶性肿瘤患者住院费用影响因素进行分析。通过统计模型分析,按重要性进行排序,影响住院费用的主要因素为:住院天数(0.264)、年龄(0.173)、性别(0.167)、是否手术(0.146)、是否输血(0.125)、入院途径(0.076)、离院方式(0.049)。Exploring the influencing factors of hospitalization expenses for malignant tumor patients under DRG payment,in order to provide reference for reducing the direct economic burden of malignant tumor patients.A BP neural network model was established using SPSS 26.0,and a retrospective analysis method was used to analyze the influencing factors of hospitalization costs for malignant tumor patients before and after the implementation of DRG in a tertiary hospital in a certain prefecture level city(2022-2023).Through statistical model analysis,ranked by importance,the main factors affecting hospitalization costs are:length of hospital stay(0.264),age(0.173),gender(0.167),whether surgery was performed(0.146),whether blood transfusion was administered(0.125),admission route(0.076),and discharge method(0.049).The BP neural network model can effectively analyze the influencing factors of hospitalization costs for patients with malignant tumors.

关 键 词：BP神经网络模型 恶性肿瘤患者 住院费用 影响因素 

分 类 号：F224[经济管理—国民经济]