A Comparison of Mental Health Performance Indicators in Canada
Bibliographic record
Abstract
BackgroundThere is growing recognition of the need for consistent and reliable reporting on mental health and addiction (MHA) services in Canada. While there have been improvements in the area of reporting within provinces, comparable measures across provinces are often confined to hospitalization data. The aim of this project was to test the feasibility of creating MHA performance indicators that could be compared across Canadian provinces. MethodsA team of scientists from five provinces collaboratively developed the following six MHA performance indicators for ages 10 and up, using hospital, emergency, physician billing and mortality data (pop. 33.2 million): Access to the same family physician for people with MHA problems First contact for MHA problems was in an emergency department Physician follow-up after hospitalization for MHA problems Rate of suicide attempts among people diagnosed with MHA problems Suicide rates among people diagnosed with MHA problems Mortality of people diagnosed with MHA problems To facilitate meaningful inter-provincial comparisons, consensus definitions and standardized analytic processes were developed. Within age groups, 95% CI’s were calculated to determine if there were significant differences across years within age bands. Results are presented in a comparative format. FindingsWe found similar patterns across provinces but significant variation in the absolute rates, with no province consistently best across all indicators. In general, outcomes were poor among adolescents and young adults compared to older groups. ConclusionsThe results of this pilot indicate the process is feasible and meaningful. Future work could include generating comparisons on a regular basis to track system improvement; development of other measures of importance to stakeholders; and the expansion of the process to other provinces and territories. To our knowledge, this is the first report of provincial teams working collaboratively to generate comparable data on the performance of mental health services in Canada.
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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 | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.016 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".