食管癌患者超长住院日影响因素分析
Influencing Factors Analysis on the Extra Long Hospital Stay of Esophageal Cancer Patients
拜里克孜·胡吉 1韩芳 1赵婷 1陈思雨 1艾克热木·玉苏甫1
作者信息
- 1. 新疆医科大学附属肿瘤医院病案室,乌鲁木齐市,830011
- 折叠
摘要
目的 通过对新疆某三甲医院877例患有食管癌患者住院时间的情况进行综合性分析,找到影响住院日的原因,提出缩短超长住院日的方法.方法 从医院信息系统调取2015年下半年出院患者信息,采用SPSS18.0,利用非条件Logistic回归模型以及Excel表格功能,了解超长住院日的影响因素.结果 Logistic回归分析显示,食管癌患者的肿瘤分期、治疗方案、转科情况、疑难病例、抢救情况、手术等级、切口等级以及是否伴有消化系统疾病或出现术后感染、并发症对病人的住院天数的影响有统计学意义(P<0.05).结论 超长住院日主要受到疾病本身因素、医院治疗方案、医疗操作水平以及是否患有伴随性疾病的影响;合理对病人进行分科、会诊、病例讨论是缩短住院天数的有效措施;只有统筹观察所有影响因素,有重点地控制主要影响因素,才能最大程度地控制住院时间.
Abstract
Objectives To find the reasons of influencing the length of hospital stay and put forward the method to shorten the length of hospital stay through the comprehensive analysis on 877 cases of patients with esophageal cancer in a Three A and Tertiary Hospital In Xinjiang. Methods The discharged lung cancer patient' information in the second half of 2015 were extracted from the hospital information retrieval system and analyzed with the application of non conditional logistic regression model and excel function by SPSS18.0 for the influencing factors of overstay hospitalization.Results Logistic regression analysis showed that the tumor staging, treatment, transfer, difficult cases, emergency treatment, operation level, accompanying digestive tract diseases, postoperative infection or complications after surgery were statistically significant for patients with esophageal cancer (P <0.05).Conclusions The long hospitalization days were mainly affected by the disease itself, hospital treatment schedule, medical operation level and whether it is suffering from concomitant diseases. To conduct rational division, consultation and discussion toward the patient's cases were the effective ways to shorten the days of hospitalization. The hospitalization days could be controlled efficiently only if all the influence factors were taken into consideration and the main influencing factors were controlled sufficiently.
关键词
食管癌/超长住院日/影响因素/统计分析Key words
Esophageal cancer/Extra long hospital stay/Influencing factors/Statistical analysis引用本文复制引用
出版年
2017
NETL
NSTL
维普
万方数据