基于广义估计方程的某三级甲等医院超长住院日影响因素分析

Analysis of Influencing Factors of Prolonged Length of Stay in a Tertiary Class A Hospital Based on Generalized Estimating Equation

目的了解三级甲等医院超长住院日患者的分布特征,采用广义估计方程探讨超长住院日的影响因素。方法选取某三级甲等医院2019—2021年住院日大于等于30天的全部患者为研究对象,收集其病案首页信息。对超长住院日患者进行描述性分析,采用非参数秩和检验对超长住院日患者进行单因素分析,采用广义估计方程对超长住院日的影响因素进行分析。结果对各年度超长住院日患者进行描述发现,超长住院日患者人次及平均住院天数呈现逐年降低的趋势,超长住院日患者占用医院床位资源逐年降低;广义估计方程分析结果显示,年龄、合并症、手术及病人费用的自付比例是超长住院日的影响因素。结论超长住院日患者对床位资源占用量较大,影响医院的运行效率、破坏了公众享用医疗资源的公平性,医院应该以强化管理为切入点,提高医院内部的诊疗效率、发挥分级诊疗的优势,进一步提高优质医疗资源的效率。

Objective To analyze the distribution characteristics and risk factors of inpatients with prolonged length of stay based on a Generalized Estimation Equation(GEE).Methods All patients with inpatient days longer than or equal to 30 days in a tertiary care hospital from 2019—2021 were selected as the study population and information on the first page of their cases was collected.Descriptive analyses were performed on patients with extra-long hospitalization days,one-way analyses were performed on patients with extra-long hospitalization days using nonparametric rank-sum tests,and generalized estimating equations were used to analyze the influencing factors of extra-long hospitalization days.Results The number of patients with prolonged length of stay and the average hospitalization days showed a decreasing trend year by year.The hospital bed resources occupied by patients with prolonged lengths of stay decreased year by year.The results of the GEE model showed that age,complications,surgery and patient expenses are the influencing factors of the prolonged length of stay.Conclusion Patients with prolonged length of stay occupy a large number of bed resources,which affects the operational efficiency of the hospital and destroys the fairness of the public to enjoy medical resources.Hospitals should strengthen management as the starting point,improve the efficiency of diagnosis and treatment within the hospital,give full play to the advantages of hierarchical diagnosis and treatment,and furtherly,improve the efficiency of high-quality medical resources.