基于数据挖掘的中医特色治疗绩效考核指标研究
Research on Performance Appraisal Indicators of Traditional Chinese Medicine Characteristic Treatment Based on Data Mining
陈思萱 1刘莉莉1
作者信息
- 1. 甘肃省中医院 信息科,甘肃 兰州 730050
- 折叠
摘要
基于现行三级公立中医医院绩效考核办法,使用数据挖掘技术对中医特色治疗相关指标进行深入分析.采用无监督学习算法,将中医特色治疗项目数据进行分类,实现对科室绩效考核目标的多维度评价.该研究通过构建CK-means聚类模型,使用三种特征工程方法对中医特色治疗相关指标进行预处理,然后使用优化后的CK-means模型进行无监督的聚类训练.改变传统科室考核划分模式,将全院科室分为 5 类.根据分类结果,制定并优化更具有中医特色的科室考核方法,为三级中医医院的良好发展提供支持与保障.
Abstract
Based on the current performance appraisal method for tertiary public Traditional Chinese Medicine hospitals,this paper uses data mining technology to analyze the related indicators of TCM characteristic treatment.In order to achieve multi-dimensional evaluation of department performance appraisal goals,the Unsupervised Learning algorithm is used to classify data on the TCM characteristic treatment projects.The research uses three feature engineering methods to preprocess TCM characteristic treatment related indicators through constructing CK-means clustering model,then uses the improved CK-means model for unsupervised clustering training.It changes the traditional division mode of department assessment and divides the entire departments of the hospital into 5 clusters.Based on the classification results,department assessment methods with more TCM characteristics can be developed and optimized to provide support and guarantee for the good development of tertiary TCM hospitals.
关键词
精细化运营/中医特色/聚类算法/绩效考核Key words
refine operation/Traditional Chinese Medicine characteristic treatment/clustering algorithm/performance appraisal引用本文复制引用
出版年
2024
国家科技期刊平台
NSTL
万方数据