Combating escalating harms associated with pharmaceutical opioid use in Australia: The POPPY II study
February 2019
Staff:
Dr Natasa Gisev
Associate Professor Timothy Dobbins
Dr Sarah Larney
Professor Richard Mattick
Professor Louisa Degenhardt
Other Collaborators:
Professor Sallie-Anne Pearson, Centre for Big Data Research in Health, UNSW
Professor David Currow, IMPACCT, Faculty of Health, University of Technology Sydney Professor Fiona Blyth, Concord Clinical School, The University of Sydney
Conjoint Professor Adrian Dunlop, School of Medicine and Public Health, Faculty of Health, The University of Newcastle
Professor Andrew Wilson, Menzies Centre for Health Policy, Faculty of Medicine and Health, The University of Sydney
Dr Andrea Schaffer, Centre for Big Data, UNSW
Dr Briony Larance, University of Wollongong
Dr Michael Coory, University of Melbourne
Professor Milton Cohen, St Vincent’s Hospital
Professor Nicholas Buckley, University of Sydney
Professor Paul Haber, University of Sydney
Professor Rebecca Ivers, George Institute for Global Health
Project description:
This project seeks to use linked administrative data to examine the patterns of use of prescribed opioids, quantify the risks of adverse outcomes, and examine the population-level impact of changes to regulation and subsidy of opioids.
Opioid prescribing has increased 15-fold in Australia in the past two decades, alongside increases in a range of opioid-related harms such as opioid dependence and overdose. However, despite concerns about increasing opioid use, extramedical use and harms, there is a lack of population-level evidence about the drivers of long-term prescribed opioid use, dependence, overdose and other harms.
We will form a cohort of all adult residents in New South Wales (NSW), Australia, who initiated prescribed opioids from 2002 using Pharmaceutical Benefits Scheme dispensing records. This cohort will be linked to a wide range of other datasets containing information on sociodemographic and clinical characteristics, health service use and adverse outcomes (eg, opioid dependence and non-fatal and fatal overdose). Analyses will initially examine patterns and predictors of prescribed opioid use and then apply regression and survival analysis to quantify the risks and risk factors of adverse outcomes associated with prescribed opioid use.
Read more on the NDARC website.
