Economic Evaluation of Extended Early Intervention Service vs Regular Care Following 2 Years of Early Intervention: Secondary Analysis of a Randomized Controlled Trial
Bibliographic record
Abstract
Cost-effectiveness studies of early intervention services (EIS) for psychosis have not included extension beyond the first 2 years. We sought to evaluate the cost-effectiveness of a 3-year extension of EIS compared to regular care (RC) from the public health care payer's perspective. Following 2 years of EIS in a university setting in Montreal, Canada, patients were randomized to a 3-year extension of EIS (n = 110) or RC (n = 110). Months of total symptom remission served as the main outcome measure. Resource use and cost data for publicly covered health care services were derived mostly from administrative systems. The incremental cost-effectiveness ratio (ICER) and cost-effectiveness acceptability curve were produced. Relative cost-effectiveness was estimated for those with duration of untreated psychosis (DUP) of 12 weeks or less vs longer. Extended early intervention had higher costs for psychiatrist and nonphysician interventions, but total costs were not significantly different. The ICER was $1627 per month in total remission. For the intervention to have an 80% chance of being cost-effective, the decision-maker needs to be willing to pay $5942 per month of total symptom remission. DUP ≤ 12 weeks was associated with a reduction in costs of $12 276 even if no value is placed on additional months in total remission. Extending EIS for psychosis for people, such as those included in this study, may be cost-effective if the decision-maker is willing to pay a high price for additional months of total symptom remission, though one commensurate with currently funded interventions. Cost-effectiveness was much greater for people with DUP ≤12 weeks.
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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 | 0.029 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 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) | 0.003 | 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".