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1401例超长住院日患者分布与影响因素分析 被引量:12

Analysis of the Distribution and Influencing Factors of 1401 Cases of Patients with Prolonged Length of Stay in a Hospital
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摘要 目的分析超长住院患者分布及影响因素,探讨减少超长住院日的措施。方法从江苏省某三甲医院病案管理系统中调取2020年1月1日-2020年12月31日134016例出院患者的住院病案首页资料,对住院时间≥30天的1401例超长住院患者的分布特征进行统计描述,采用Logistic回归模型分析超长住院日的影响因素。结果2020年全院平均住院日为7.13天,其中超长住院患者平均住院日为41.85天。超长住院患者以60岁以上年龄组最多(39.61%);出院科室主要分布在血液科(42.18%)、普通外科(11.85%)、骨科(7.49%)等;疾病类别主要为肿瘤(47.32%)、影响健康状态和与保健机构接触的因素(10.56%)、循环系统疾病(7.07%)等;多因素Logistic回归结果显示,男性(OR=1.188)、离院方式为非医嘱离院或其他(OR=2.046)和死亡病例(OR=3.362)是超长住院的危险因素。结论控制超长住院日对平均住院日影响显著,医院应加强重点人群、重点科室和重点病种管理提高诊疗管理水平,缩短平均住院日。 Objectives To analyze the distribution status and influencing factors of patients with prolonged length of stay in a hospital in 2020, then find out the measures for shortening the length of stay. Methods A total of 134016 cases of medical record information in 2020 were collected. The 1401 cases of patients who had been stayed in hospital for more than 30 days were selected for the descriptive analysis. The Logistic regression model was used to analyze the influencing factors of patients with prolonged length of stay. Results The average hospitalization days in 2020 were 7.52 days, and the length of prolonged hospital stay were 42.24 days. Among patients stay more than 30 days, patients over 60 years old accounted for 39.61%, and mainly distributed in hematology department(42.18%), general surgical department(11.85%) and orthopedics department(7.49%). The main diseases were tumor(47.32%), factors affecting health status and contact with health care institutions(10.56%) and circulation system disease(7.07%). Logistic regression analysis showed that male(OR=1.188), the people who leaving hospital without medical advice or else(OR=2.046) and deaths case(OR=3.362) were the risk factors of extra-long hospitalization days. Conclusions The average length of stay was seriously affected by the control of extra long hospitalization days. The management of key patients, departments and diseases should be strengthened by the hospital. And it’s necessary to improve the level of diagnosis management for shortening the average length of stay.
作者 贺祥静 杨舒 董琼 He Xiangjing;Yang Shu;Dong Qiong(The First Affiliated Hospital of Suzhou University,Suzhou 215006,Jiangsu Province,China)
出处 《中国病案》 2022年第1期63-67,共5页 Chinese Medical Record
关键词 超长住院日 LOGISTIC回归模型 影响因素 医院管理 Prolonged length of stay Logistic regression model Influencing factors Medical management
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