Healthcare utilization costs of emerging adults with mood and anxiety disorders in an early intervention treatment program compared to a matched cohort
Bibliographic record
Abstract
AIM: The First Episode Mood and Anxiety Disorder Program (FEMAP) provides treatment to emerging adults with mood and anxiety disorders in an accessible, youth-friendly environment. We sought to investigate FEMAP's impact on the costs of care. METHODS: We conducted a retrospective observational study of one-year health service costs using linked administrative datasets to compare emerging adults treated at FEMAP (FEMAP users) to propensity-score matched controls (non-users). Costs from the perspective of the Ontario Ministry of Health and Long-Term Care, included drug benefit claims, inpatient, physician and ambulatory care services. We used bootstrapping to perform unadjusted comparisons between FEMAP users and non-users, by cost category and overall. We performed risk-adjusted comparison of overall costs using generalized estimating equations. RESULTS: FEMAP users (n = 366) incurred significantly lower costs compared to non-users (n = 660), for inpatient services (-$784, 95% confidence interval [CI] -$1765, -$28), ambulatory care services (-$90, 95% CI -$175, -$14) and drug benefit claims (-$47, 95% CI -$115,-$4) and significantly higher physician services costs ($435, 95% CI $276, $581) over 1 year. The unadjusted difference in overall costs was not significant (-$853, 95% CI -$2048, $142). Following adjustment for age, sex and age at first mental health diagnosis, the difference of -$914 (95% CI (-$2747, $919)) was also not significant. CONCLUSIONS: FEMAP was associated with significantly lower costs of inpatient and ambulatory care services, and higher costs of physician services, however we are unable to conclude that FEMAP is cost-saving overall.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".