Assessing the Costs and Benefits of Insuring Psychological Services as Part of Medicare for Depression in Canada
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: The study estimated costs and effects associated with increasing access to publicly funded psychological services for depression in a public health care system. METHODS: Discrete event simulation modeled clinical events (relapse, recovery, hospitalizations, suicide attempts, and suicide), health service use, and cost outcomes over 40 years in a population with incident depression. Parameters included epidemiologic and economic data from the literature and data from a secondary analysis of the 2012 Canadian Community Health Survey on mental health. Societal costs were measured with the human capital approach. Analyses estimated the incremental cost-effectiveness ratio associated with improved access to psychological services among individuals not receiving adequate mental health care and reporting an unmet need for such care compared with present use of health services for mental health reasons. RESULTS: Over 40 years, increased access to mental health services in a simulated population of adults with incident depression would lead to significantly lower lifetime prevalence of hospitalizations (27.9% versus 30.2% base case) and suicide attempts (14.1% versus 14.6%); fewer suicides (184 versus 250); a per-person gain of .17 quality-adjusted life years; and average societal cost savings of $2,590 CAD per person (range $1,266-$6,320). Publicly funding psychological services would translate to additional costs of $123,212,872 CAD ($67,709,860-$190,922,732) over 40 years. Savings to society would reach, on average, $246,997,940 CAD ($120,733,356-$602,713,120). CONCLUSIONS: In Canada, every $1 invested in covering psychological services would yield $2.00 ($1.78 to $3.15) in savings to society. Covering psychological services as part of Medicare for individuals with an unmet need for mental health care would pay for itself.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it