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Hybrid data mining approaches for prevention of drug dispensing errors

机译：混合数据挖掘方法可防止药物分配错误

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摘要

Prevention of drug dispensing errors is an importance topic in medical care. In this paper, we propose a risk management approach, namely Hybrid Data Mining (HDM), to prevent the problem of drug dispensing errors. An intelligent drug dispensing errors prevention system based on the proposed approach is then implemented. The proposed approach consists of two main procedures: First, the classification modeling and logistic regression approaches are used to derive decision tree and regression function from the given dispensing errors cases and drug databases. In the second procedure, similar drugs are then gathered together into clusters by combing clustering technique (PoCluster) and the extracted logistic regression function. The drugs that may cause dispensing errors will then be alerted through the clustering results and the decision tree. Through experimental evaluation on real datasets in a medical center, the proposed approach was shown to be capable of discovering the potential dispensing errors effectively. Hence, the proposed approach and implemented system serve as very useful application of data mining techniques for risk management in healthcare fields.
机译：预防配药错误是医疗保健中的重要主题。在本文中，我们提出一种风险管理方法，即混合数据挖掘（HDM），以防止药物分配错误的问题。然后实现了基于所提出的方法的智能药物分配错误预防系统。所提出的方法包括两个主要程序：首先，使用分类建模和逻辑回归方法从给定的分配错误案例和药品数据库中得出决策树和回归函数。在第二个步骤中，然后通过组合聚类技术（PoCluster）和提取的逻辑回归函数将相似的药物聚集在一起。然后将通过聚类结果和决策树来警告可能引起分配错误的药物。通过对医疗中心真实数据集的实验评估，所提出的方法被证明能够有效地发现潜在的分配错误。因此，所提出的方法和实现的系统作为用于医疗领域风险管理的数据挖掘技术的非常有用的应用。

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  • 来源
    《Journal of Intelligent Information Systems》 |2011年第3期|p.305-327|共23页
  • 作者

    Lien-Chin Chen; Chun-Hao Chen; Hsiao-Ming Chen; Vincent S. Tseng;

  • 作者单位

    Department of Computer Science and Information Engineering, National Cheng Kung University, No. 1, Ta-Hsueh Road, Tainan, 701, Taiwan, Republic of China;

    Department of Computer Science and Information Engineering, Tamkang University, Taipei, 251, Taiwan, Republic of China;

    Department of Computer Science and Information Engineering, National Cheng Kung University, No. 1, Ta-Hsueh Road, Tainan, 701, Taiwan, Republic of China;

    Department of Computer Science and Information Engineering, National Cheng Kung University, No. 1, Ta-Hsueh Road, Tainan, 701, Taiwan, Republic of China Institute of Medical Informatics, National Cheng Kung University, Tainan, 701, Taiwan, Republic of China;

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  • 正文语种 eng
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  • 关键词

    dispensing errors; classification modeling; decision tree; logistic regression; medical risk management;

    机译：分配错误;分类建模;决策树;逻辑回归医疗风险管理;

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