目的分析按疾病诊断相关分组(DRG)付费下胃癌患者分组效果及住院费用影响因素,为DRG付费改革提供参考。方法采用变异系数(Coefficient of Variation,CV)和总体方差减少系数评价DRG分组效果;采用结构变动值和结构变动度分析不同DRG组住...目的分析按疾病诊断相关分组(DRG)付费下胃癌患者分组效果及住院费用影响因素,为DRG付费改革提供参考。方法采用变异系数(Coefficient of Variation,CV)和总体方差减少系数评价DRG分组效果;采用结构变动值和结构变动度分析不同DRG组住院费用结构变动情况,通过灰色关联度分析计算次均住院费用的关联程度;采用非参数检验和多元线性回归分析住院费用的影响因素。结果DRG分组效果不佳,组间异质性不够明显;住院费用结构不合理,耗材费占比过高,排在住院费用灰色关联度首位,综合医疗服务费、治疗费分别排在第三、五位;影响住院费用的主要因素是治疗方式、住院日、是否伴有并发症、是否首次住院,差异有统计学意义(P<0.05)。结论应增加分组节点或提高CV标准,增强胃癌DRG分组效果;优化住院费用结构,体现医务人员劳动和技术价值;加强内部管理,控制不合理药品、耗材使用。展开更多
This paper is devoted to identifying the biomarkers of rat liver regeneration via the adaptive logistic regression. By combining the adaptive elastic net penalty with the logistic regression loss, the adaptive logisti...This paper is devoted to identifying the biomarkers of rat liver regeneration via the adaptive logistic regression. By combining the adaptive elastic net penalty with the logistic regression loss, the adaptive logistic regression is proposed to adaptively identify the important genes in groups. Furthermore, by improving the pathwise coordinate descent algorithm, a fast solving algorithm is developed for computing the regularized paths of the adaptive logistic regression. The results from the experiments performed on the microarray data of rat liver regeneration are provided to illustrate the effectiveness of the proposed method and verify the biological rationality of the selected biomarkers.展开更多
基金Supported by National Basic Research Program of China （973Program） （2005CB321902） National Natural Science Foundation of China （90916024 60727002 60774003 60850004）+1 种基金 the Ph.D. Programs Foundation of Ministry of Education of China （20030006003） the Commission on Science Technology and Industry for National Defense （A2120061303）
基金Supported by National Basic Research Program of China （973 Program） （2005CB321902） National Natural Science Foundation of China （90916024,60727002,60774003）+1 种基金 the Ph.D. Programs Foundation of Ministry of Education of China （20030006003） the Commission on Science,Technology,and Industry for National Defense （A2120061303）
文摘目的分析按疾病诊断相关分组(DRG)付费下胃癌患者分组效果及住院费用影响因素,为DRG付费改革提供参考。方法采用变异系数(Coefficient of Variation,CV)和总体方差减少系数评价DRG分组效果;采用结构变动值和结构变动度分析不同DRG组住院费用结构变动情况,通过灰色关联度分析计算次均住院费用的关联程度;采用非参数检验和多元线性回归分析住院费用的影响因素。结果DRG分组效果不佳,组间异质性不够明显;住院费用结构不合理,耗材费占比过高,排在住院费用灰色关联度首位,综合医疗服务费、治疗费分别排在第三、五位;影响住院费用的主要因素是治疗方式、住院日、是否伴有并发症、是否首次住院,差异有统计学意义(P<0.05)。结论应增加分组节点或提高CV标准,增强胃癌DRG分组效果;优化住院费用结构,体现医务人员劳动和技术价值;加强内部管理,控制不合理药品、耗材使用。
基金supported by National Nature Science Foundation of China(No.61203293)Key Scientific and Technological Project of Henan Province(No.122102210131)+3 种基金Program for Science and Technology Innovation Talents in Universities of Henan Province(No.13HASTIT040)Foundation of Henan Educational Committee(No.13A120524)Henan Normal University Doctoral Topics(No.qd14156)Henan Higher School Funding Scheme for Young Teachers(No.2012GGJS-063)
文摘This paper is devoted to identifying the biomarkers of rat liver regeneration via the adaptive logistic regression. By combining the adaptive elastic net penalty with the logistic regression loss, the adaptive logistic regression is proposed to adaptively identify the important genes in groups. Furthermore, by improving the pathwise coordinate descent algorithm, a fast solving algorithm is developed for computing the regularized paths of the adaptive logistic regression. The results from the experiments performed on the microarray data of rat liver regeneration are provided to illustrate the effectiveness of the proposed method and verify the biological rationality of the selected biomarkers.
