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基于决策树模型的早产儿病例住院费用的分组研究*
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彭伊婧(1994—),女,硕士学位,助理研究员;研究方向:医保支付与改革;E-mail:727182031@qq.com

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R1-9;F840.613

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江苏省妇幼保健重点学科项目(SFY-EK2021);无锡市医学创新团队项目(CXTD2021013)


Research on Grouping Hospitalization Costs of Patients with Premature Infants Based on Decision Tree
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    摘要:

    目的:研究早产儿住院患者的病例组合方式及费用支付标准,为制定住院费用分组以及提高医疗效率提供参考依据。方法:收集样本三级妇幼专科医院2019—2021年3061例早产儿病例,采用多元线性逐步回归分析,确定住院费用的主要影响因素,运用决策树模型中CHAID方法构建早产儿患者住院费用分组方案及付费标准。结果:住院天数、合并症或并发症个数、出生体重、有无操作、使用呼吸机时长及转归情况作为影响早产儿病例住院费用的分类节点,利用决策树模型对 3061例早产儿患者分组,形成7个DRG组合和并对应住院费用标准。结论:早产儿病例DRG分组能够客观反映医疗资源消耗水平,可为其他地区医疗机构分组进行验证并优化分组方案提供参考依据。

    Abstract:

    Objective: To study the case mix mode and cost payment standard of patients with premature infants,and to provide a reference for formulating hospitalization expenses groups and improving medical efficiency. Methods: A total of 3,061 cases of premature infants in a tertiary maternity and children's hospital from 2019 to 2021 were collected. Multiple linear stepwise regression analysis was used to determine the main influencing factors of hospitalization expenses. The CHAID method in decision tree model was used to construct the hospitalization expense grouping plan and payment standard for premature infants. Results: The number of days in hospital,number of comorbidities or complications,neonatal birth weight,presence or absence of operations,length of time on ventilator,and transfer status were used as classification nodes to influence the hospitalization cost of preterm cases,and a total of 7 DRG combinations and corresponding hospitalization cost criteria were formed using a decision tree model to group 3,061 preterm patients. Conclusion: Case-mix diagnosis related groups of premature infants could objectively reflect the level of medical resource consumption,and provide a reference for medical institutions in other regions to verify the grouping and optimize the grouping plan.

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彭伊婧,孙琰,余仁强,等.基于决策树模型的早产儿病例住院费用的分组研究*[J].中国卫生经济,2023,42(4):30-33./PENG Yi-jing, SUN Yan, YU Ren-qiang, et al.基于决策树模型的早产儿病例住院费用的分组研究*[J]. CHINESE HEALTH ECONOMICS,2023,42(4):30-33.

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  • 在线发布日期: 2023-04-26
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