A microsimulation cost–utility analysis of alcohol screening and brief intervention to reduce heavy alcohol consumption in <scp>Canada</scp>
Bibliographic record
Abstract
BACKGROUND AND AIMS: Screening and brief intervention (SBI) is a public health intervention that has been shown to be effective in reducing heavy alcohol consumption. The aim of this study is to estimate the cost-effectiveness of implementing universal alcohol SBI in primary care in Canada. DESIGN: We developed a microsimulation model of alcohol consumption and its effects on 18 alcohol-related causes of death. SETTING: The model simulates a Canadian population. PARTICIPANTS: The model simulates individuals and their alcohol consumption on a continuous scale starting from age 17 years to death. INTERVENTIONS: The reference case assumes no SBI in Canada. The base case assumes screening was conducted using the Alcohol Use Disorders Identification Test (AUDIT) at a threshold score of 8. Additional analyses included evaluating SBI using the AUDIT at threshold scores between 4 and 8 or the Derived Alcohol Use Disorders Identification Test (AUDIT-C) at threshold scores between 3 and 7. MEASUREMENTS: The model estimates the direct health-care costs, life years gained and quality-adjusted life years (QALY) gained, which are then used to estimate the incremental cost-effectiveness ratio (ICER) of SBI versus no SBI. FINDINGS: SBI with AUDIT (at a threshold score of 8) had an ICER of $8729/QALY. Our results suggest that using AUDIT thresholds between 8 and 4, inclusive, would be cost-effective for the whole population, as well as for men and women individually. Our results suggest that the AUDIT-C would be cost-effective at thresholds of 7 to 3, inclusive, for men, women and the whole population. CONCLUSIONS: In Canada, screening and brief intervention via Alcohol Use Disorders Identification Test (AUDIT) and Derived Alcohol Use Disorders Identification Test (AUDIT-C) to reduce heavy alcohol consumption appears to be cost-effective for men and women at Alcohol Use Disorders Identification Test (AUDIT) thresholds of 8 and lower and at Derived Alcohol Use Disorders Identification Test (AUDIT-C) thresholds of 7 and lower.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".