Transforming health care: the policy and politics of service reconfiguration in the UK's four health systems
Bibliographic record
Abstract
Public involvement in service change has been identified as a key facilitator of health care transformation (Foley et al., 2017) but little is known about how health policy influences whether and how organisations involve the public in change processes. This qualitative study compares policy and practice for involving the public in major service changes across the UK's four health systems (England, Northern Ireland, Wales and Scotland). We analysed policy documents, and conducted interviews with officials, stakeholders, NHS staff and public campaigners (total number of interviewees = 47). Involving the public in major service change was acknowledged as a policy challenge in all four systems. Despite ostensible similarities, there were some clear differences between the four health systems' processes for involving patients and the public in major changes to health services. The extent of central Government oversight, the prescriptiveness of Government guidance, the role for intermediary bodies and arrangements for independent scrutiny of contentious decisions all vary. We analyse how health policy in the four systems has used 'sticks' and 'sermons' to promote particular approaches, and conclude that both policy and the wider system context within which health care organisations try to effect change are significant, and understudied aspect of contemporary practice.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".