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Drug Safety
Published in: Drug Safety 12/2017

01-12-2017 | Original Research Article

A Pharmacoepidemiology Database System for Monitoring Risk Due to the Use of Medicines by New Zealand Primary Care Patients

Authors: Andrew M. Tomlin, David M. Reith, David J. Woods, Hywel S. Lloyd, Alesha Smith, John S. Fountain, Murray W. Tilyard

Published in: Drug Safety | Issue 12/2017

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Abstract

Introduction

The use of large record-linked healthcare databases for drug safety research and surveillance is now accepted practice. New Zealand’s standardized national healthcare datasets provide the potential to automate the conduct of pharmacoepidemiological studies to provide rapid validation of medicine safety signals.

Objectives

Our objectives were to describe the methodology undertaken by a semi-automated computer system developed to rapidly assess risk due to drug exposure in New Zealand’s population of primary care patients and to compare results from three studies with previously published findings.

Methods

Data from three national databases were linked at the patient level in the automated studies. A retrospective nested case–control design was used to evaluate risk for upper gastrointestinal bleeding (UGIB), acute kidney failure (AKF), and serious arrhythmia associated with individual medicines, therapeutic classes of medicines, and concurrent use of medicines from multiple therapeutic classes.

Results

The patient cohort available for each study included 5,194,256 patients registered between 2007 and 2014, with a total of 34,630,673 patient-years at risk. An increased risk for UGIB was associated with non-steroidal anti-inflammatory drugs (NSAIDs) (adjusted odds ratio [AOR] 4.16, 95% confidence interval [CI] 3.90–4.43, p < 0.001) and selective serotonin reuptake inhibitors (AOR 1.39, 95% CI 1.20–1.62, p < 0.001); an increased risk for AKF was associated with NSAIDs (AOR 1.78, 95% CI 1.73–1.83, p < 0.001) and proton pump inhibitors (AOR 1.78, 95% CI 1.72–1.83, p < 0.001); and an increased risk for serious arrhythmia was associated with fluoroquinolones (AOR 1.38, 95% CI 1.26–151, p < 0.001) and penicillins (AOR 1.69, 95% CI 1.61–1.77, p < 0.001).

Conclusions

Automated case–control studies using New Zealand’s healthcare datasets can replicate associations of risk with drug exposure consistent with previous findings. Their speed of conduct enables systematic monitoring of risk for adverse events associated with a wide range of medicines.
Appendix
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Metadata
Title
A Pharmacoepidemiology Database System for Monitoring Risk Due to the Use of Medicines by New Zealand Primary Care Patients
Authors
Andrew M. Tomlin
David M. Reith
David J. Woods
Hywel S. Lloyd
Alesha Smith
John S. Fountain
Murray W. Tilyard
Publication date
01-12-2017
Publisher
Springer International Publishing
Published in
Drug Safety / Issue 12/2017
Print ISSN: 0114-5916
Electronic ISSN: 1179-1942
DOI
https://doi.org/10.1007/s40264-017-0579-1

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