基于关联算法的临床路径变异研究

Research on Clinical Path Variation Based on Associat ion Algorithm

临床路径是针对特定诊断制定的一整套标准化的治疗模式,旨在规范医疗行为、提升医疗质量、控制医疗成本和优化医疗服务。笔者在考虑到保持临床路径原本规范性的前提下,为提高它的灵活性,提出一种通过分析变异数据,从而减少路径变异率的改进方案。该方案选取200个符合诊断要求且进入临床路径的患者医嘱数据作为样本,对这些数据进行过滤以及筛查,得到患者的医嘱列表,并利用关联分析Apriori算法发现医嘱频繁项集,从而发现医嘱之间的关联规则。实验结果表明,所提出的方案能起到完善路径表单、减少变异率的作用。

The clinical pathway is a set of standardized treatment models formulated for a specific diagnosis,aimed at standardizing medical behavior,improving medical quality,controlling medical costs and optimizing medical services.In order to improve the flexibility of the clinical pathway while maintaining the original standardization of the clinical pathway,the author proposes an improvement plan that reduces the rate of pathway mutation by analyzing mutation data.The program selects 200 patient order data that meet the diagnostic requirements and enter the clinical path as samples,filter and screen these data to obtain a list of patient orders,and use the correlation analysis Apriori algorithm to find the frequent item set of doctor orders,thereby discovering the order of the doctors.Association rules between.The experimental results show that the proposed scheme can improve the path form and reduce the mutation rate.