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Volume 30 Issue 2
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Article Navigation >  Journal of Pharmaceutical Practice and Service  > 2012  >  30(2): 109-114

FU Xiang, YANG Zhang-wei, CHEN Sheng-xin, CHEN Chang-hong, HE Yu-tao. Data mining of antibiotic prophylactic use for cesarean section patients[J]. Journal of Pharmaceutical Practice and Service, 2012, 30(2): 109-114. doi: 10.3969/j.issn.1006-0111.2012.02.009
Citation: FU Xiang, YANG Zhang-wei, CHEN Sheng-xin, CHEN Chang-hong, HE Yu-tao. Data mining of antibiotic prophylactic use for cesarean section patients[J]. Journal of Pharmaceutical Practice and Service, 2012, 30(2): 109-114. doi: 10.3969/j.issn.1006-0111.2012.02.009
shu

Data mining of antibiotic prophylactic use for cesarean section patients

doi: 10.3969/j.issn.1006-0111.2012.02.009
  • 1.

    Department of Pharmacy and Medical Appliances, Hangzhou Sanatorium of Nanjing Military Region, Hangzhou 310000, China

  • 2.

    Department of Pharmacy, Changhai Hospital, Shanghai 200433, China

  • 3.

    Department of Pharmacy Administration, School of Pharmacy, SMMU, Shanghai 200433, China

  • 4.

    Department of Information, Changhai Hospital, Shanghai 200433, China

  • Received Date: 2011-10-08
  • Rev Recd Date: 2011-12-29
  • Objective To establish, compare and evaluate the classification models of antibiotic prophylactic use for cesarean section patients for the targeted intervention in future. Method PASW® Modeler 13 was applied to establish classification models and to get the influential variables (clinical factors) in antibiotic prophylactic use. Results With the data of 787 cases, the classification models were established, in which, Bayesian networks, logistic regression and CHAID were better. In 21 clinical factors, blood loss was the most influential variable. Conclusion The data mining technique was able to quickly create models reflecting the use of prophylactic antibiotics use for cesarean section, which would provide a new analysis tool for drug use survey.
  • [1] 王敬花.剖宫产围术期抗菌药物的使用干预与分析[J]. 中国医院用药评价与分析,2010,10(8):688.
    [2] 张 奕,李润萍,孟繁星.我院剖宫产手术预防感染应用抗菌药物的合理性分析[J]. 实用药物与临床,2010,13(3):218.
    [3] 姜 涛.785例产妇抗菌药物应用的合理性分析[J].中国医院药学杂志,2010,30(10):884.
    [4] 孟现民,丁天然,张 莉,等.HBsAg阳性孕产妇剖宫产术抗菌药物预防用药调查与分析[J].中国药物应用与监测,2010,7(1):29.
    [5] 傅 翔,陈盛新,杨樟卫.数据挖掘在合理用药信息分析中的应用[J].药学实践杂志,2009,27(6):411.
    [6] 李小毛,段 涛,杨慧霞主编.剖宫产热点问题解读[M]. 北京:人民军医出版社,2008.
    [7] 叶晨洲,杨 杰,耿道颖.应用数据挖掘技术从大脑胶质瘤病例中获取诊断知识[J].生物医学工程学杂志,2002,19(3):426.
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Data mining of antibiotic prophylactic use for cesarean section patients

doi: 10.3969/j.issn.1006-0111.2012.02.009
  • 1. Department of Pharmacy and Medical Appliances, Hangzhou Sanatorium of Nanjing Military Region, Hangzhou 310000, China
  • 2. Department of Pharmacy, Changhai Hospital, Shanghai 200433, China
  • 3. Department of Pharmacy Administration, School of Pharmacy, SMMU, Shanghai 200433, China
  • 4. Department of Information, Changhai Hospital, Shanghai 200433, China
  • Received Date: 2011-10-08
  • Rev Recd Date: 2011-12-29

Abstract: Objective To establish, compare and evaluate the classification models of antibiotic prophylactic use for cesarean section patients for the targeted intervention in future. Method PASW® Modeler 13 was applied to establish classification models and to get the influential variables (clinical factors) in antibiotic prophylactic use. Results With the data of 787 cases, the classification models were established, in which, Bayesian networks, logistic regression and CHAID were better. In 21 clinical factors, blood loss was the most influential variable. Conclusion The data mining technique was able to quickly create models reflecting the use of prophylactic antibiotics use for cesarean section, which would provide a new analysis tool for drug use survey.

FU Xiang, YANG Zhang-wei, CHEN Sheng-xin, CHEN Chang-hong, HE Yu-tao. Data mining of antibiotic prophylactic use for cesarean section patients[J]. Journal of Pharmaceutical Practice and Service, 2012, 30(2): 109-114. doi: 10.3969/j.issn.1006-0111.2012.02.009
Citation: FU Xiang, YANG Zhang-wei, CHEN Sheng-xin, CHEN Chang-hong, HE Yu-tao. Data mining of antibiotic prophylactic use for cesarean section patients[J]. Journal of Pharmaceutical Practice and Service, 2012, 30(2): 109-114. doi: 10.3969/j.issn.1006-0111.2012.02.009
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