Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/115638
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Type: Journal article
Title: Using routinely collected data to understand and predict adverse outcomes in opioid agonist treatment: Protocol for the Opioid Agonist Treatment Safety (OATS) Study
Author: Larney, S.
Hickman, M.
Fiellin, D.
Dobbins, T.
Nielsen, S.
Jones, N.
Mattick, R.
Ali, R.
Degenhardt, L.
Citation: BMJ Open, 2018; 8(8):e025204-1-e025204-6
Publisher: BMJ Journals
Issue Date: 2018
ISSN: 2044-6055
2044-6055
Statement of
Responsibility: 
Sarah Larney, Matthew Hickman, David A Fiellin, Timothy Dobbins, Suzanne Nielsen, Nicola R Jones, Richard P Mattick, Robert Ali, Louisa Degenhardt
Abstract: Introduction: North America is amid an opioid use epidemic. Opioid agonist treatment (OAT) effectively reduces extramedical opioid use and related harms. As with all pharmacological treatments, there are risks associated with OAT, including fatal overdose. There is a need to better understand risk for adverse outcomes during and after OAT, and for innovative approaches to identifying people at greatest risk of adverse outcomes. The Opioid Agonist Treatment and Safety study aims to address these questions so as to inform the expansion of OAT in the USA. Methods and analysis: This is a retrospective cohort study using linked, routinely collected health data for all people seeking OAT in New South Wales, Australia, between 2001 and 2017. Linked data include hospitalisation, emergency department presentation, mental health diagnoses, incarceration and mortality. We will use standard regression techniques to model the magnitude and risk factors for adverse outcomes (eg, mortality, unplanned hospitalisation and emergency department presentation, and unplanned treatment cessation) during and after OAT, and machine learning approaches to develop a risk-prediction model. Ethics and dissemination: This study has been approved by the Population and Health Services Research Ethics Committee (2018HRE0205). Results will be reported in accordance with the REporting of studies Conducted using Observational Routinely-collected health Data statement.
Keywords: buprenorphine
Description: First published August 5, 2018
Rights: © Author(s) (or their employer(s)) 2018. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
RMID: 0030098408
DOI: 10.1136/bmjopen-2018-025204
Grant ID: http://purl.org/au-research/grants/nhmrc/1140938
http://purl.org/au-research/grants/nhmrc/1135991
http://purl.org/au-research/grants/nhmrc/1132433
Appears in Collections:Pharmacology publications

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