摘要
目的针对目前医用耗材分类主观性较强、分类标准模糊、库存成本较高的问题,探讨一种科学的医用耗材分类方法,以降低医用耗材库存成本,提高库存的有效性。方法在杭州某儿童医院2020年医用耗材的历史数据中随机抽取100种耗材为研究对象,通过主成分分析(Principal Component Analysis,PCA)算法和K-means聚类算法对研究对象进行分类。结果确定轮廓系数为0.656的分类数3为最佳分类数,将100种医用耗材分为3类,其中有44种医用耗材归为第一类,42种医用耗材归为第二类,14种医用耗材归为第三类。将本文研究的医用耗材分类方法模拟运用到某儿童医院2021年第一季度的医用耗材库存管理中,模拟结果表明本文研究的分类方法能够降低库存成本,提高库存有效性。结论基于PCA算法和K-means聚类算法的医用耗材分类方法能够为医用耗材的库存分类管理提供可靠依据。
Objective To explore a scientific method for classifying medical consumables aiming at the current problems of strong subjectivity, ambiguous classification standard and high inventory cost, which is expected to reduce the inventory cost of medical consumables and improve the effectiveness. Methods A total of 100 kinds of consumables were randomly selected as research subjects from the historical data of medical supplies provided by a children’s hospital in Hangzhou in 2020, and the research subjects were classified by principal component analysis(PCA) and K-means clustering algorithms. Results The classification number 3 with a silhouette coefficient of 0.656 was determined as the optimal classification number, and 100 kinds of medical supplies were classified into three categories, of which 44 kinds of medical supplies were classified into the first category, 42 kinds of medical supplies were classified into the second category, and 14 kinds of medical supplies were classified into the third category.The classification method of medical consumables studied in this paper was simulated and applied to the inventory management of medical supplies in the children’s hospital in the first quarter of 2021. The simulation results showed that the classification method can reduce the inventory cost and improve the inventory effectiveness. Conclusion The classification method for medical consumables based on PCA algorithm and K-means clustering algorithm can provide a reliable basis for the inventory classification management of medical consumables.
作者
张林灵
郑焜
ZHANG Linling;ZHENG Kun(Department of Medical Equipment,The Children’s Hospital,Zhejiang University School of Medicine,Hangzhou Zhejiang 310052,China;Department of Logistics Support,The Children’s Hospital,Zhejiang University School of Medicine,Hangzhou Zhejiang 310052,China;National Clinical Research Center for Child Health,Hangzhou Zhejiang 310000,China)
出处
《中国医疗设备》
2022年第1期5-8,19,共5页
China Medical Devices
关键词
医用耗材分类
PCA算法
K-MEANS聚类算法
医用耗材库存管理
classification of medical consumables
principal component analysis algorithm
K-means clustering algorithm
inventory management of medical consumables
