Healthcare in Canada: Choices Going Forward
Bibliographic record
Abstract
The overarching purpose of serial Health Care in Canada (HCIC) surveys of the adult Canadian public and a broad spectrum of healthcare professionals over the past two decades has been the development of an evidence-based map to inform strategic and clinical decisions to improve care and outcomes for Canadians. Recent surveys reveal a growing concern that medicare may require complete rebuilding or major strategic repairs. On the other hand, a majority of stakeholders perceive continuing underlying quality in our clinical care and look forward to both system- and patient-centred initiatives to improve future care. Currently, the most strongly supported strategic improvement target among the public and professional caregivers is enhanced availability of less expensive prescription medications. With regard to practical implementation of this strategy, the public's (39%) and healthcare professionals' (39-54%) preference was institution of a nation-wide pharmacare plan, funded by a federal tax. There was also pan-stakeholder concordance around the two least favoured potential strategies: increasing taxes and shifting money from other funded services. In terms of improving clinical care, the public and all professional groups were also concordant in most strongly supporting increases in home and community care services, disease prevention/wellness education and use of non-physician care providers and electronic health records. There was also remarkable concordance regarding who is most responsible for implementing these preferred innovations: research hospitals/health authorities, government funding agencies and pharmaceutical/biotech industries. In summary, contemporary Canadian public and health professionals agree on key strategic and practical priorities to improve future care and outcomes. Moreover, they concur on who should lead their implementation. This public/professional concordance supporting evidence-driven choices and leadership for improving care is not common. It is, however, an opportunity, providing a call to arms for other stakeholders, particularly governments and industry, to recognize the opportunity and their leadership expectations and to act upon them. Things can be better.
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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 | 0.012 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.025 | 0.015 |
| Scholarly communication | 0.024 | 0.010 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.014 | 0.016 |
| Insufficient payload (model declined to judge) | 0.017 | 0.002 |
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".