门诊处方药物关联的数据挖掘
Data mining the association rules in outpatient service prescriptions
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摘要: 目的 对某医院门诊处方数据进行分析,挖掘处方中药物的关联规则,揭示处方模式,发现问题。 方法 应用数据挖掘软件PASW Modeler 13,建立Apriori关联分析模型。 结果 在抽样获得的47 132张处方中,防治心血管等慢性疾病药物使用最为频繁;祛痰药、镇咳药、清热解毒中成药等与头孢菌素类抗菌药有较为明显的关联。 结论 数据挖掘技术能较快速地处理和分析处方数据,反映处方模式,适用于当前药物利用研究中对大量数据的分析。Abstract: Objective To mine the association rules in and to identify the patterns of the prescription. Methods PASW Modeler 13 was applied to establish Apriori model and analyze the data. Results In 47 132 prescriptions, the drugs for prophylaxis and treatment of some chronic disease were present frequently. Expectorants, cough suppressants and prepared Chinese medicine for "Qing Re Jie Du" played dominant roles in the associations with cephalosporins. Conclusion The data mining technique was able to process and analyze prescription data effectively, which will be widely applicable to drug utilization research.
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Key words:
- prescription /
- association /
- data-mining
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