Original research
by
Tse, Wai Chung et al
Release Date
2022
Geography
Australia
Language of Resource
English
Full Text Available
No
Open Access / OK to Reproduce
No
Peer Reviewed
Yes
Objective
We aimed to model whether unsupervised iOAT may be effective in reducing fatal and non–fatal overdose, and estimate the cost per life saved.
Findings/Key points
An implementation scenario with greater unsupervised iOAT compared to supervised iOAT allows for an increased reduction in overdose and overdose deaths per annum at the same cost, with the additional benefit of increased treatment coverage among PWIO.
Design/methods
Decision tree model based on Australian and international parameters for overdose risk in people who inject opioids who are: not on OAT; new/stable to methadone/buprenorphine treatment; on iOAT; or on unsupervised iOAT.
Keywords
Overdose
Evidence base
Policy/Regulatory
