Putting a Population Health Lens to Multimorbidity in Ontario
Bibliographic record
Abstract
Almost all Ontarians die with multimorbidity, and most accumulate more than five conditions over their lifetime. Our health system is still largely focused on specialties and treating one disease at a time - an approach that is incompatible with the healthcare needs of patients with multiple and often complex chronic conditions. This burden requires a health system that recognizes that patients will more likely live and die with multiple chronic conditions than not (i.e., multimorbidity management versus specialized care). There are important and meaningful differences in the types and numbers of conditions that patients die with. In particular, increases in the most preventable conditions are greater among the most deprived members of our society. To address the worrying trends seen here, chronic disease prevention - not only management - must be a priority, with a strong focus on health equity. Chronic disease prevention and a strong focus on equity are signatures of a population health approach. This work echoes calls for a stronger emphasis on population health in the health system.
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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 | 0.000 | 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 | 0.000 | 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 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".