DocumentCode :
1791733
Title :
Investigating the accuracy of the openFDA API using the FDA Adverse Event Reporting System (FAERS)
Author :
Shin, Jeyong
fYear :
2014
fDate :
27-30 Oct. 2014
Firstpage :
48
Lastpage :
53
Abstract :
The US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) is a database that contains information on adverse event and medication error reports submitted to the FDA. Each quarter the FDA releases the data to the public, but accessing the data requires researchers to download, import, and consolidate data for every quarter starting from 2004. In an effort to provide easier access to this, the FDA launched the openFDA initiative in June 2014, which gives the public API access to information about adverse events reports. Although the API enables easier access to the FAERS data, the quality of the API design and the features of the data set will determine the reliability of the information retrieved. Thus, errors in the API can result in inaccurate and unreliable data analysis. Furthermore, the number of adverse events reports retrieved by the API for a particular drug can differ from the FAERS data files due to the openFDA harmonization process and the existence of multiple entries and variations for any given drug name in the FAERS data files. Since there are no universal rule that can be used to identify errors or potential issues, we propose evaluating the openFDA API by searching for a particular drug (brand name), Yaz, and the generic name, Drospirenone Ethinyl Estradiol, and comparing the results against the FAERS data files. Our results show that in the case of Yaz, the openFDA API and the drug harmonization process is inaccurate and inconsistent.
Keywords :
application program interfaces; data analysis; database management systems; drugs; information retrieval; API access; API design quality; FAERS data files; FDA adverse event reporting system; US Food and Drug Administration; data access; data analysis; drug name; information database; information retrieval; medication error reports; openFDA API; openFDA harmonization process; openFDA initiative; Accuracy; Big data; Databases; Drugs; IEEE Potentials; US Government agencies; FAERS; FDA; FDA Adverse Events Reporting System; adverse events; openFDA;
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.2014.7004412
Filename :
7004412
Link To Document :
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