摘要
[目的]探讨数据挖掘中的关联规则在患者就医行为模式研究中的应用价值,为卫生服务研究提供方法学上的借鉴。[方法]利用关联规则中的Apriori算法,通过设置最小支持度和最小置信度对患者就医行为等信息进行挖掘。[结果]不同收入水平、不同报销渠道与疾病不同严重程度等情况的患者就医行为模式存在差异。[结论]关联规则引入到卫生服务研究的资料分析中,可以探讨影响患者就医行为各种因素间潜在的、有价值的关系,较传统的多元回归方法具有独特的优势。
[Objective] To provide a methodology reference for health service research according to explore the value of association rules mining in the research of patients＇ behavior of choosing hospitals. [ Methods] The Apriori algorithm which is a classic algorithm in association rules mining was used to analyze the patients＇ information by setting minimum support anti minimum confidence. [Results] Patients who had different income, different reimbursement way and illness severity and so on had differences in their behavial model of choosing hospitals. [Conclusion] Applying association roles in the information analysis of health service research can discover some potential and valuable relationships in different factors which influence patents＇ behavior of choosing hospitals and have much more advantages than the traditional multiple regression.
出处
《现代预防医学》
CAS
北大核心
2007年第9期1663-1664,1669,共3页
Modern Preventive Medicine
关键词
数据挖掘
关联规则
卫生服务
就医行为
Data Mining
Association Rules
Health Service
Behavior of choosing hospitals
