综合医院患者出院量影响因素研究

Study on the influencing factors of general hospital discharge volume

目的综合探讨出院量的影响因素及变动趋势,从而为出院量的精细化管理提供参考。方法基于一省级综合性医院2013年1月至2016年12月每月出院量等数据,采用相关分析、主成分及回归分析研究对出院量的影响因素,采用时间序列分析探讨出院量最优预测模型。结果相关分析显示出院量与平均住院日、平均开放床位数、病床使用率、病床周转次数、平均病床工作日、工作天数及门急诊量呈显著相关性。主成分回归分析显示平均开放床位数、病床使用效率、工作天数及平均住院日是影响出院量的因素(P值均<0.01)。Winters加法指数平滑模型被确定为最优预测模型,决定系数(R^(2))、贝叶斯信息准则(BIC)、平方残差Q(Ljung-Box Q)统计量分别为0.723、11.808及26.431,平均相对预测误差为3.87%。结论平均住院日及病床使用效率是出院量的主要影响因素,医务管理者可结合出院量预测模型对其进行更有针对性地主动管理。

Objective To discuss the influencing factors and changing trends of hospital discharge volume comprehensively and provide a reference for the refined management of the discharge volume.Method Based on the monthly discharge volume data of a provincial general hospital in Shandong Province from January 2013 to December 2016,correlation analysis,principal component,and regression analysis were used to study the influencing factors of discharge volume,and the time-series analysis were used to explore the optimal prediction model of discharge volume.Results Pearson correlation analyses showed that hospital discharge volume was significantly correlated with the average days of hospital stays,the average number of available hospital beds,the utilization rate of hospital beds,the number of hospital beds turnovers,the average occupied days of hospital beds,the number of legal workdays,and the number of outpatient and emergency services.Principal component regression analysis showed that the average number of available hospital beds,bed utilization efficiency,the number of legal workdays,and the average days of hospital stays were the factors that affected discharge volume(P<0.01).Winters′additive exponential smoothing model was determined to be the optimal prediction model.The coefficient of determination(R^(2)),Bayesian information criterion(BIC)and the square residual Q(Ljung-Box Q)statistics were 0.723,11.808,and 26.431.The average relative forecast error is 3.87%.Conclusions The average days of hospital stay and the hospital beds utilization efficiency are the main influencing factors of the discharge volume,and medical administrators combining with the discharge volume prediction model to manage it pointedly and actively.