• DocumentCode
    1791709
  • Title

    Duplicate drug discovery using Hadoop

  • Author

    Shao Hua Cheng ; Yu Shian Chiu ; Shih Yao Dai ; Hui-I Hsiao

  • Author_Institution
    Adv. Res. Inst., Inst. for Inf. Ind., Taipei, Taiwan
  • fYear
    2014
  • fDate
    27-30 Oct. 2014
  • Firstpage
    24
  • Lastpage
    26
  • Abstract
    Rising healthcare costs in recent years has become a major issue for many countries. This is especially prominent as baby boomers reaching their retirement age and thus demanding large shares of a country´s healthcare resources. Consequently, reducing healthcare cost or waste has become a top priority for many governments. However, integrating and analyzing large amount of healthcare data with variety of formats to identify cost saving opportunities is a very complex problem. To help addressing the problem, this paper proposes a Hadoop based approach that can efficiently discover duplicate drug usage by a patient in any given time period. Our experiment results show that our approach can discover cases of duplicate drug prescription much faster, up to 100 times faster, compared to a traditional approach using relational data warehouse.
  • Keywords
    data warehouses; distributed processing; medical information systems; pharmaceuticals; relational databases; Hadoop based approach; baby boomers; duplicate drug discovery; duplicate drug prescription; governments; healthcare costs; healthcare resources; healthcare waste; relational data warehouse; retirement age; Big data; Data warehouses; Drugs; Hospitals; Software architecture; Apache Hadoop; Apache Hive; Big Data; Duplicate Drug Discovery; Healthcare;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Big Data (Big Data), 2014 IEEE International Conference on
  • Conference_Location
    Washington, DC
  • Type

    conf

  • DOI
    10.1109/BigData.2014.7004388
  • Filename
    7004388