中国循证医学杂志

中国循证医学杂志

四川大学华西医院呼吸科门诊入院优先级决策影响因素的 Logistic 回归分析

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目的 通过住院患者相关历史数据,建立 Logistic 回归模型,识别患者入院排程决策的影响因素,并和现有排程规则进行对比分析,找出差异和不足。 方法 以 2016 年 1 月 1 日至 2016 年 12 月 31 日四川大学华西医院呼吸科门诊就诊与申请入院的患者信息为基础,对原始数据进行标准化处理,利用 R 软件和 glm 包建立二元多因素 Logistic 回归模型。 结果 经多因素 Logistic 回归分析发现医保类型、入院申请时间、等候时间、疾病类型和收治优先级这 5 个变量对患者入院排程的影响有统计学意义。 结论 本研究构建的 Logistic 回归模型对于患者入院排程具有良好的效果,有利于通过识别因素为入院排程提供决策支持

Objective Based on the historical data of inpatients, a logistic regression model was established. It aimed to identify the influencing factors of patient's admission scheduling decisions, and compare with the actual scheduling rules, to find out the differences and deficiencies. Methods We extracted the data of outpatients and inpatients in department of respiration in West China Hospital of Sichuan University from January 1st, 2016 to December 31st, 2016, and standardized the original dataset. We established the binary multivariate logistic regression model through R software and ‘glm’ package. Results The analysis of multivariate stepwise regression showed that the effect of the five variables (type of medical insurance, time of registration, waiting time, type of disease and admission priority) on patient schedule was statistically significant. Conclusion The logistic regression model constructed in this study has a good effect on patient planning, which is helpful to provide decision support for admission schedule through identification factors.

关键词: logistic回归; 入院排程; 优先级决策; 影响因素

Key words: Logistic regression; Admission schedule; Priority decision; Influence factors

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