Appl Clin Inform 2014; 05(03): 621-629
DOI: 10.4338/ACI-2014-04-RA-0036
Research Article
Schattauer GmbH

JADE: A tool for medical researchers to explore adverse drug events using health claims data

D. Edlinger
1  Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna, Austria
,
S.K. Sauter
1  Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna, Austria
,
C. Rinner
1  Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna, Austria
,
L.M. Neuhofer
1  Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna, Austria
,
M. Wolzt
2  Department of Clinical Pharmacology, Medical University of Vienna, Austria
,
W. Grossmann
3  Research Group Scientific Computing, University of Vienna, Austria
,
G. Endel
4  Main Association of Austrian Social Security Organizations, Vienna, Austria
,
W. Gall
1  Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna, Austria
› Author Affiliations
Further Information

Correspondence to:

Doron Edlinger
Center for Medical Statistics, Informatics and Intelligent
Systems, Medical University of Vienna
Spitalgasse 23
A-1090 Vienna
Austria

Publication History

received: 04 April 2014

accepted: 25 May 2014

Publication Date:
19 December 2017 (online)

 

Summary

Objective: The objective of our project was to create a tool for physicians to explore health claims data with regard to adverse drug reactions. The Java Adverse Drug Event (JADE) tool should enable the analysis of prescribed drugs in connection with diagnoses from hospital stays.

Methods: We calculated the number of days drugs were taken by using the defined daily doses and estimated possible interactions between dispensed drugs using the Austria Codex, a database including drug-drug interactions. The JADE tool was implemented using Java, R and a PostgreSQL database.

Results: Beside an overview of the study cohort which includes selection of gender and age groups, selected statistical methods like association rule learning, logistic regression model and the number needed to harm have been implemented.

Conclusion: The JADE tool can support physicians during their planning of clinical trials by showing the occurrences of adverse drug events with population based information.

Citation: Edlinger D, Sauter SK, Rinner C, Neuhofer LM, Wolzt M, Grossmann W, Endel G, Gall W. JADE: A tool for medical researchers to explore adverse drug events using health claims data. Appl Clin Inf 2014; 5: 621–629

http://dx.doi.org/10.4338/ACI-2014-04-RA-0036


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Conflicts of interest

G. Endel is an employee of the Main Association of Austrian Social Security Institutions. No other conflict of interest is declared.


Correspondence to:

Doron Edlinger
Center for Medical Statistics, Informatics and Intelligent
Systems, Medical University of Vienna
Spitalgasse 23
A-1090 Vienna
Austria