Public Expenditures for Mental Health Services in Canadian Provinces
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study is to measure provincial spending for mental health services in fiscal year (FY) 2013 and to compare these cost estimates to those of FY 2003. METHODS: This study estimated the costs of publicly funded provincial mental health services in FY 2013 and compared them to the estimates for FY 2003 from a previously published report. Our data were obtained from publicly accessible databases. The cross-year cost comparisons for provincial mental health services were restricted to general and psychiatric hospital inpatients, clinical payments to physicians and psychologists, and prescribed psychotropic medications. Total public expenditures were inflation adjusted and expressed per capita and as a percentage of the total provincial health spending. RESULTS: Total public spending for mental health and addiction programs/services was estimated to be $6.75 billion for FY 2013. The largest component of the expenditures was hospital inpatient services ($4.02 billion, 59.6%), followed by clinical payments to physicians or psychologists ($1.69 billion, 25%), and then publicly funded prescribed psychotherapeutic medications ($1.04 billion, 15.4%). Nationally, the portion of total public spending on health that was spent on mental health decreased from FY 2003 to FY 2013 from 5.4% to 4.9%. CONCLUSION: Our results reveal that mental health spending, as a proportion of public health care expenditures, decreased in the decade from FY 2003 to FY 2013. Due to large differences in how the provinces report community mental health services, we still lack a comprehensive picture of the mental health system.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".