Stakeholder Views on Solutions to Improve Health System Performance
Bibliographic record
Abstract
Context: Significant reforms are needed to improve healthcare system performance in Quebec. Even though the characteristics of high-performing healthcare systems are well-known, Quebec's reforms have not succeeded in implementing many critical elements. Converging evidence from political science models suggests stakeholders' preferences are central in determining policy content, adoption, and implementation. Objective: To analyze whether doctors', nurses', pharmacists' and health administrators' preferences could explain the observed inability to implement known characteristics of high-performing healthcare systems. Design: A questionnaire on various propositions identified in the scientific literature was sent to 2,491 potential respondents. Results: Overall response rate was 37%. There was considerable consensus on identified solutions to improve the healthcare system. Resistance was observed in two major areas: information systems and changes directly affecting doctors' practice. The groups' positions cannot explain the inability to implement important characteristics of high-performing systems. The findings raise new questions on the actual sources of resistance.
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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 | 0.010 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 0.027 |
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; both teacher heads agree on what is shown here.
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".