决策树和logistic回归评价非重症社区获得性肺炎患者住院费用
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摘要
目的分析不同病例组合下非重症社区获得性肺炎患者的住院费用。为DRGs的实行、合理控制医疗费用提供理论依据。方法采用R语言中的glm()函数进行Logistic回归,筛选出影响非重症社区获得性肺炎患者住院费用的所有因素,再使用R语言rpart包中的rpart()和rpart.lpot()函数建立决策树模型的和绘制决策树图形。结果经logistic回归分析,影响非重症社区获得性肺炎患者住院费用的主要影响因素为年龄、住院天数、入院病情、有无手术。通过决策树分析,纳入住院天数、年龄和入院病情三个变量,最终确定7种病例组合。结论决策树和logistic回归结合能够评价不同病例组合下非重症社区获得性肺炎患者的住院费用。
Objectives To analyze the hospitalization costs of patients with non severe community acquired pneumonia in different cases, and provide theoretical basis for DRGs in local practice and reasonable control of medical expenses. Methods Using R language in glm() function of Logistic regression, to find out the influence factors of all non pneumonia hospitalization expenses in patients with severe community acquired, and then use the R language in the rpart package rpart() and rpart.lpot() function to establish the model of decision tree and decision tree graph drawing. Results By logistic regression analysis, it was concluded that the main influencing factors of the hospitalization expenses of patients with non severe community acquired pneumonia were age, hospital days, hospital admission and operation. Through decision tree analysis, three variables were included in the length of hospital stay, age and hospital admission, and finally identified 7 cases. Conclusion Decision tree combined with logistic regression could be used to evaluate the hospitalization costs of patients with non severe community acquired pneumonia in different cases.
Objectives To analyze the hospitalization costs of patients with non severe community acquired pneumonia in different cases, and provide theoretical basis for DRGs in local practice and reasonable control of medical expenses. Methods Using R language in glm() function of Logistic regression, to find out the influence factors of all non pneumonia hospitalization expenses in patients with severe community acquired, and then use the R language in the rpart package rpart() and rpart.lpot() function to establish the model of decision tree and decision tree graph drawing. Results By logistic regression analysis, it was concluded that the main influencing factors of the hospitalization expenses of patients with non severe community acquired pneumonia were age, hospital days, hospital admission and operation. Through decision tree analysis, three variables were included in the length of hospital stay, age and hospital admission, and finally identified 7 cases. Conclusion Decision tree combined with logistic regression could be used to evaluate the hospitalization costs of patients with non severe community acquired pneumonia in different cases.
引文
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[11]周琦荟,刘海容,葛惠雄,等.医疗保险总额预算控制下的按服务单元浮动付费制:机遇与挑战并存[J].中国卫生经济,2013,11(32):21-23.
[2]刘海霞,王玖,田考聪,等.决策树与回归技术在农村居民就诊服务研究中的应用[J].中国卫生事业管理,2012,(5):376-378.
[3]李君荣,李孝叶,马方.卫生费用适度合理增长的探讨[J].中国卫生经济,2013,32(3):17-19.
[4]吴晓云,刘莉,俞长荣.基于MS-DRGs的急性心肌梗死DRGs分组及费用研究[J].中国病案,2014,15(8):47-50.
[5]Suner A,Eliko Lu CC,Dicle O,et al.Sequential decision tree using the analytic hierarchy process for decision support in rectal cancer[J].Artif Intell Med,2012,56(1):59-68.
[6]杜军,郭慧敏,杜静静,等.基于关联规则的病案首页数据挖掘[J].中国病案,2016,17(8):45-47.
[7]张芬,余金明,王家宏,等.Exhaustive CHAID分类树与logistic回归在脑卒中危险因素中的应用[J].中国预防医学杂志,2011,12(7):573-576.
[8]黄文,王正林.数据挖掘:R语言实战[M].北京:电子工业出版社,2014.
[9]赵红梅,张海澄.DRGs与公立医院改革[J].中国医院.2010,14(1):20-21.
[10]王才有.“十二五”卫生信息化发展规划研读[J].中国卫生信息管理杂志,2012,9(2):13-16.
[11]周琦荟,刘海容,葛惠雄,等.医疗保险总额预算控制下的按服务单元浮动付费制:机遇与挑战并存[J].中国卫生经济,2013,11(32):21-23.