基于K-means决策树融合算法的医院财务共享中心管理策略研究  

Research on management strategy of Hospital Financial Sharing Center Based on K-means decision tree fusion algorithm

作　　者：李垚 杨蕊 何宝林 李国忠 Li Yao;Yang Rui;He Baolin;Li Guozhong(Kunming Third People’s Hospital,Yunnan Province 650041)

机构地区：[1]昆明市第三人民医院,云南昆明650041

出　　处：《现代科学仪器》2023年第6期241-246,共6页Modern Scientific Instruments

摘　　要：自最近一次人工智能技术革命以来,智能计算机技术被广泛应用于各行各业。在医院财务管理领域,基于智能计算机技术构建的财务共享中心能起到大幅提升医院财务管理效率并减少决策失误作用。此次研究构建了融合K-means与C4.5决策树算法的绩效评价优化和违规预测模型,并以某医院财务共享中心为对象为例,构建了基于大数据智能化的财务共享中心运营管理优化模型。测试结果显示,此次研究提出的基于改进K-means决策树算法的医院人员评价模型,较基于K-means++、经典K-means绩效评价模型,轮廓系数最大,为0.743,可见该模型聚类效果最好,而基于C4.5决策树构建的违规操作预测模型也具有良好的预测分类效果。Since the recent revolution in artificial intelligence technology,intelligent computer technology has been widely applied in various industries.In the field of hospital financial management,a financial sharing center based on intelligent computer technology can significantly improve the efficiency of hospital financial management and reduce decision-making errors.This research has built a performance evaluation optimization and violation prediction model integrating K-means and C4.5 decision tree algorithm.Taking a financial sharing center of a hospital as an example,it has built an operation management optimization model of financial sharing center based on Big data intelligence.The test results show that the hospital personnel evaluation model proposed in this study based on the improved K-means decision tree algorithm has the largest contour coefficient of 0.743 compared to the K-means++and classic K-means performance evaluation models.It can be seen that the clustering effect of this model is the best,and the violation operation prediction model constructed based on C4.5 decision tree also has good prediction and classification performance.

关 键 词：K-MEANS C4.5决策树 财务共享中心 管理策略 

分 类 号：R197.322[医药卫生—卫生事业管理]