This project will use linked administrative data to understand risk for mortality and other adverse outcomes during and after opioid agonist treatment (OAT). It will use standard biostatistical approaches and sophisticated machine learning techniques. There is also an OATS II study underway.
Matthew Hickman
Bristol University
David Fiellin
Yale University
Timothy Dobbins
School of Public Health and Community Medicine, UNSW
Suzanne Nielsen
Monash Addiction Research Centre, Monash University
Robert Ali
Adelaide Medical School, University of Adelaide
North America is in the midst of an opioid use epidemic, and opioid use is also increasing dramatically in Australia. OAT is an effective treatment for opioid dependence, but there are important questions regarding risk of adverse clinical outcomes, including death, that are yet to be answered. Who is most at risk of adverse outcomes? What patient, provider and treatment setting actors may influence this risk? Answers to these and other questions are critical to inform the massive scale-up of OAT internationally that will be required to respond to the opioid epidemic.
Aim 1: Determine the magnitude of risk for specific adverse clinical outcomes (e.g. mortality, hospitalization and ED presentation, and unplanned treatment cessation) during and after OAT with methadone and buprenorphine
Aim 2: Identify patient, treatment setting, and provider risk factors associated with adverse clinical outcomes during and after OAT with methadone and buprenorphine
Aim 3: Develop a risk prediction model to identify patients at greatest risk of adverse clinical outcomes during and after OAT
The study used a population cohort of OAT patients (n≈45,000) treated between 2001 (when buprenorphine became available for OAT in New South Wales) and 2018. These data were probabilistically linked to State-wide hospitalization, emergency department, incarceration and mortality data. Linkage was undertaken by the Centre for Health Record Linkage (CHeReL) using probabilistic record linkage methods and ChoiceMaker software. We examined incidence (Aim 1) and risk (Aim 2) for specific adverse clinical outcomes during OAT, with a special focus on the period of OAT induction, as well as the remainder of time in OAT and the 4 weeks immediately following cessation of OAT. Adverse clinical outcomes examined included all-cause and cause-specific (drug, self-harm/suicide, and injury-related) emergency department visits, hospitalisation and mortality and unplanned treatment cessation. We are currently developing a risk prediction model to identify patients at greatest risk of self-harm during OAT (Aim 3) as the final piece of work from this study.
This project is coming to its finalisation, aim 3 is expected to be complete by the close of the year. The results from the project are summarised below.
1. Larney S, Hickman M, Fiellin DA, et al. Using routinely collected data to understand and predict adverse outcomes in opioid agonist treatment: Protocol for the Opioid Agonist Treatment Safety (OATS) Study. BMJ open 2018; 8(8): e025204.
2. Larney S, Jones N, Fiellin DA, et al. Data resource profile: The Opioid Agonist Treatment and Safety (OATS) Study, New South Wales, Australia. Int J Epidemiol 2020.
3. Jones NR, Shanahan M, Dobbins T, et al. Reductions in emergency department presentations associated with opioid agonist treatment vary by geographic location: A retrospective study in New South Wales, Australia. Drug Alcohol Rev 2019; 38(6): 690-8.
4. Jones NR, Hickman M, Larney S, et al. Hospitalisations for non-fatal overdose among people with a history of opioid dependence in New South Wales, Australia, 2001-2018: Findings from the OATS retrospective cohort study. Drug Alcohol Depend 2020: 108354.
5. Lewer D, Jones NR, Hickman M, et al. Risk of discharge against medical advice among hospital inpatients with a history of opioid agonist therapy in New South Wales, Australia: A cohort study and nested crossover-cohort analysis. Drug Alcohol Depend 2020; 217: 108343.
6. Lewer D, Jones NR, Hickman M, Nielsen S, Degenhardt L. Life expectancy of people who are dependent on opioids: A cohort study in New South Wales, Australia. J Psychiatr Res 2020; 130: 435-40.
7. Jones NR, Nielsen S, Farrell M, et al. Retention of opioid agonist treatment prescribers across New South Wales, Australia, 2001–2018: Implications for treatment systems and potential impact on client outcomes. Drug and Alcohol Dependence 2021; 219: 108464.
8. Bharat C, Larney S, Barbieri S, et al. The effect of person, treatment and prescriber characteristics on retention in opioid agonist treatment: a 15-year retrospective cohort study. Addiction 2021.
9. Chaillon A, Bharat C, Stone J, et al. Modeling the population-level impact of opioid agonist treatment on mortality among people accessing treatment between 2001 and 2020 in New South Wales, Australia. Addiction 2021.
10. Colledge-Frisby S, Jones N, Larney S, et al. The impact of opioid agonist treatment on hospitalisations for injecting-related diseases among an opioid dependent population: A retrospective data linkage study. Drug and Alcohol Dependence 2022; 236: 109494.
11. Brothers TD, Lewer D, Jones N, et al. Opioid agonist treatment and risk of death or rehospitalization following injection drug use-associated bacterial and fungal infections: A cohort study in New South Wales, Australia. PLoS Med 2022; 19(7): e1004049.
12. Jones NR, Hickman M, Nielsen S, et al. The impact of opioid agonist treatment on fatal and non-fatal drug overdose among people with a history of opioid dependence in NSW, Australia, 2001-2018: Findings from the OATS retrospective linkage study. Drug Alcohol Depend 2022; 236: 109464.
13. Larney S, Jones NR, Hickman M, Nielsen S, Ali R, Degenhardt L. Does opioid agonist treatment reduce overdose mortality risk in people who are older or have physical comorbidities? Cohort study using linked administrative health data in New South Wales, Australia, 2002-17. Addiction 2023.
14. Colledge-Frisby S, Jones N, Degenhardt L, et al. Incidence of suicide and self-harm among people with opioid use disorder and the impact of opioid agonist treatment: A retrospective data linkage study. Drug Alcohol Depend 2023; 246: 109851.