Opioid agonist treatment in transition: A cross-country comparison between Austria, Germany and Switzerland
Bibliographic record
Abstract
BACKGROUND AND AIMS: OAT is a well developed and successful treatment strategy for opioid dependent patients in Europe. It has significantly contributed to the fight against the HIV and HCV pandemics, leading to an increased life expectancy in this population. Building on the OAT experiences in Austria, Germany, and Switzerland and their models of care, the objective of this study is to analyse experiences and changes in patient structures to identify necessary adaptations for the system of care. METHODS: We analysed national register-based data from patients receiving OAT during the period spanning from 2010 to 2020 in Austria, Germany (cases), and Switzerland. We examined and compared OAT policies and practice at national levels through a review of literature and publicly available policy documents. RESULTS: Across these three countries, the life expectancy of OAT patients increased substantially. The mean age increased from 33.0 in 2010 to 39.1 in 2020 in Austria, from 35.6 years to 41.5 years in Germany (cases), and from 39.6 to 47.1 in Switzerland, respectively. In all three countries, the percentage of patients/cases aged 60 years and older increased more than tenfold between 2010 and 2020. CONCLUSIONS: Integrated support models, reliable care structures, internationally comparable high treatment coverage, flexible prescribing practices, and a wide range of available OAT medications are successful strategies. The experiences in these countries indicate that it is possible to address the complex and chronic nature of opioid dependence and its concurrent mental and physical health challenges, resulting in an increasing life expectancy of OAT patients.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".