Healthcare access, quality of care and efficiency as healthcare performance measures: A Canadian health service view
Bibliographic record
Abstract
While most performance judgements are value-relative, in health systems reform it is important to focus on intermediate performance measures like healthcare access, quality of care and efficiency in healthcare on health status of population, the satisfaction of patients, and the degree to which services are made equi- table. However, to date these concepts are not well-defined, remain fairly ambiguous and, consequently, are also not well-measured. Therefore, such concepts do not provide sufficient information to inform changes to the health system that may improve population level outcomes related to structural factors. Our paper established an argument and from our viewpoints we provide a more conceptual clarification on how these three intermediate variables may shape assessments in health system performance, while drawing from the Canadian healthcare system performance gaps and placing them as evidence. We found an immediate need for patient-centred outcome measures in service and clinical quality instead of surrogate outcome measures, need for improved measures on the rate of service utilization such as in terms of service-orientation and pa- tient satisfaction, and a need for more robust approach in measuring allocative efficiency in healthcare to be the key areas of strengthening performance assessments. These intermediate variables can play an important role in Canadian policy and also would have dominant roles in legislative agenda and outcome, which can be both responsive and influential.
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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 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.015 | 0.017 |
| Science and technology studies | 0.005 | 0.028 |
| Scholarly communication | 0.015 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.005 |
| 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".