Abstract
Background and aims
Opioid agonist treatment (OAT) is currently the most effective treatment for people with opioid dependence. In most countries, however, access to the whole range of effective medications is restricted. This study aims to model the distribution of different OAT medications within a naturalistic and relatively unrestricted treatment setting (Zurich, Switzerland) over time, and to identify patient characteristics associated with each medication.
Methods
We used generalized estimating equation analysis with data from the OAT register of Zurich and the Swiss register for heroin‐assisted treatment (HAT) to model and forecast the annual proportion of opioids applying exponential distributions until 2018 and patient characteristics between 1992 and 2015.
Results
Data from 11 895 patients were included in the analysis. Methadone remains the mainstay of OAT, being prescribed to two‐thirds of patients. Following its approval, the proportion of HAT increased rapidly and is now constant at 12.16% [95% confidence interval (CI) = 11.15–13.17]. The initial increase of proportions of buprenorphine or slow‐release oral morphine (SROM) following their approval for OAT was slower. While in 2014 both medications had a proportion of 10.2% and 10.3%, respectively, our model predicts a further increase of SROM to 19.9% in 2018, with a ceiling level of 25.19% (21.40–28.98%) thereafter. SROM patients display characteristics similar to those treated with methadone; buprenorphine patients show the highest social integration; and HAT patients are the most homogeneous group, with highest mean age, most widespread injecting experience and lowest social integration.
Conclusions
Based on data from Zurich, Switzerland from 1992 to 2015, there is no evidence for an excessive demand for a single medication in a naturalistic and liberal opioid agonist treatment setting. Rather, the specific patient characteristics associated with each medication underline the need for diversified treatment options for opioid dependence.
Nordt, C