基于关联规则算法构建急性上呼吸道感染用药提示系统

Development of Medication Reminder System for Acute Upper Respiratory Tract Infection Based on Association Rules Algorithm

随着医院信息系统的不断完善扩大,各项业务的数据库日益膨胀。面对海量的临床信息数据,需要应用数据挖掘技术手段发掘出其中潜在的信息。急性上呼吸道感染(简称上感),广义上是一系列疾病的总称,具有常见多发的特点,所以选择一种有效的治疗方法对提高诊疗质量将起到关键性作用。利用数据挖掘的手段,应用关联规则算法对患有急性上呼吸道感染的病人进行分析,找到病人相关特征信息与用药之间的关联规则;并基于该关联规则构建急性上呼吸道感染用药的提示系统,对医生为病人用药进行评估,提高病人安全和整体医疗质量。

Along with the constant improvement and expansion of the hospital information system, the database of various businesses are also increasingly expanding. In face of massive clinical information data, we need to apply techniques of Data Mining to discover useful information. Acute upper respiratory tract infection is called AURTI for short. Broadly speaking AURTI is not just one disease, but a group of diseases. As a common disease, AURTI is frequent and complicated rather than a single disease. Thus, how to choose the most effective treatment methods to improve the treatment efficiency has played a key role. In this paper, we apply the methods of data mining and use association rules algorithm to analyze the associations between vital signs and medications. We design and develop a reminder system of AURTI medication based on association algorithm to determine which drug should be taken according to the specific signs and to offer suggestions to doctors. The system helps to reduce medication errors, improves the patients＇ safety and overall quality of care.