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基于31792例住院患者病案首页数据的乳腺癌病例分组打包付费研究 被引量:4

Study on bundled payment for breast cancer based on the medical record homepage data of 31792 inpatient cases
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摘要 目的研究乳腺癌患者住院诊治费用及影响因素,探讨按病种分组打包付费的方法及支付标准,为制定诊治费用合理补偿机制和补偿标准提供依据。方法研究纳入2015年北京市16家三级甲等医院共31792例乳腺癌住院患者的病案首页数据,采用非参数检验和有序多分类变量的logistic回归分析费用的影响因素,利用决策树模型对乳腺癌进行分组及费用测算。结果决策树模型根据患者是否手术、手术方式、是否进行淋巴结清扫、是否进行放射治疗和化学治疗、是否有合并症等因素,将乳腺癌诊治分为17个组。方差减少值为0.26,表示分组方法解释性较好。各组变异系数为0.24~0.97,均小于1,表示组内同质性较好。结论按照病种分组打包付费方式支付乳腺癌住院诊治费用更符合乳腺癌临床诊治实际,且方法可行,可作为医疗服务费用补偿依据。 Objective To explore influencing factors of hospitalization cost for breast cancer inpatients,develop an applicable standard using bundled payment approach,so as to provide reference for health insurance organizations to formulate reasonable imbursement method.Methods 31792 inpatients′medical records from 16 tertiary hospitals in Beijing,2015 were included in the present study.Non-parametric tests and logistic regression model for ordinal categorical variable were applied to explore potential influencing factors.Decision tree model was performed to yield case-mix related groups.Results The breast cancer inpatients were classified into 17 groups based on the following factors:surgical treatment/non-surgical treatment,surgical modality,radiology treatment,lymphadenectomy,comorbidity.RIV(reduction in variance)was 0.26.CV(coefficient of variation)was 0.24~0.97.Conclusions It was feasible to apply the case-mix bundled payment method as a reimbursement method for breast cancer inpatients.The present study served as reference for formulating related policies.
作者 田欣 包小源 周子君 Tian Xin;Bao Xiaoyuan;Zhou Zijun(Department of Health Policy and Management,School of Public Health,Peking University,Beijing 100191,China;Peking University Medical Informatics Center,Beijing 100191,China)
出处 《中华医院管理杂志》 CSCD 北大核心 2020年第3期193-197,共5页 Chinese Journal of Hospital Administration
关键词 支付标准制定和审核 乳腺癌 分组打包付费 病例组合 诊断相关患者组 Rate setting and review Breast cancer Bundled payment Case-mix Diagnosis-related groups
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