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
Link To Document :
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