The Drive towards Sustainable Health Systems Needs an Alignment: Where are the Innovations in Health Systems Planning?
Bibliographic record
Abstract
Clarifying the healthcare innovation agenda is critical in order to advance the impact of system innovations. As part of this agenda-setting it is important to address the four conditions within which innovations can enhance system sustainability: 1) the innovation agenda reflects and is aligned with healthcare objectives and policy; 2) planning methodologies for services, workforce and funding are aligned with healthcare objectives and policy; 3) innovations in services are accommodated in systems through innovations in policy, planning and funding; and 4) innovations are systematically monitored and evaluated. In order to illustrate these conditions, the authors present a case study of an evaluation of one Canadian Health Authority's efforts to transform healthcare delivery. This case study reveals that aligning innovations in policy, planning, funding and health services is critical to transforming health systems and that, in the absence of such alignment, sustainable health systems are difficult to achieve.
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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 | 0.068 | 0.069 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.013 | 0.058 |
| Scholarly communication | 0.038 | 0.031 |
| Open science | 0.004 | 0.016 |
| Research integrity | 0.011 | 0.015 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".