基于BP神经网络的不同分娩方式产妇住院费用因素分析  

Hospitalization Expense Analysis of Different Delivery Methods Puerpera Based on BP Neural Network

作　　者：李铁锋[1] 古丽华[1] 陆建奇 钟晓[1] 

机构地区：[1]深圳市龙岗中心医院,深圳市518116

出　　处：《中国病案》2017年第9期67-70,共4页Chinese Medical Record

摘　　要：目的分析不同分娩方式产妇住院费用的影响因素,为减少住院费用,合理分配医疗资源提供参考依据。方法利用BP神经网络模型对深圳市某三甲医院2012年10月-2016年12月间的24 481例住院分娩产妇的住院费用及相关影响因素进行分析。结果 24 481例产妇的平均住院费用为2876.7元,近5年产妇住院分娩费用呈增长的趋势,剖宫产的产妇住院费用5118.9元显著高于顺产产妇的住院费用为2451.9元。无论对于顺产还是剖宫产产妇,产科并发症和抢救的发生都是产妇住院费用较高的重要原因。对于顺产产妇,新生儿出生体重也是产妇住院费用的重要影响因素。结论减少剖宫产率,重点预防常见并发症的发生及妊娠期间监测婴儿体重变化等情况,可以有效控制和减少产妇的住院分娩费用。Objectives To analyze hospitalization expenses and its＂ possible influential factors of different delivery methods puerpera in order to provide evidence for reducing the hospitaiization expense and distributions for the limited medical resource. Methods 24481 obstetric medical cases was collected from/~ Three A and Tertiary hospital between October 2012 and December 2014 and BP neural network was used to explore influential factors of hospitalization expense. Results The average cost of all the deliveries in our study was 2876.7 yuan, which had a increasing tendency in the past five years. The cost of hospitalization in caesarean section was 5118.9 yuan, which was significantly higher than the hospitalization fee of 2451.9 yuan. The delivery complications and whether given emergency treatment could play important roles in affecting hospitalization costs no matter cesarean section and vaginal delivery. For vaginal delivery, the new born weight also affected the hospitalization costs. Conclusions Cesarean section rate reduction, the control of the delivery classifications and monitoring the baby weight during pregnancy could effectively reduce the hospitalization expenses of delivery.

关 键 词：BP神经网络 住院分娩 住院费用 影响因素 

分 类 号：R197.323[医药卫生—卫生事业管理]