Modeling the cost and impact of injectable opioid agonist therapy on overdose and overdose deaths

Original research
par
Tse, Wai Chung et al

Date de publication

2022

Géographie

Australia

Langue de la ressource

English

Texte disponible en version intégrale

Non

Open Access / OK to Reproduce

Non

Évalué par des pairs

Yes

L’objectif

We aimed to model whether unsupervised iOAT may be effective in reducing fatal and non–fatal overdose, and estimate the cost per life saved.

Constatations/points à retenir

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.

La conception ou méthodologie de recherche

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.

Mots clés

Overdose
Evidence base
Policy/Regulatory