The impact of slow economic growth on health sector reform: a cross-national perspective
Bibliographic record
Abstract
This paper assesses recent health sector reform strategies across Europe adopted since the onset of the 2008 financial crisis. It begins with a brief overview of the continued economic pressure on public funding for health care services, particularly in tax-funded Northern European health care systems. While economic growth rates across Europe have risen a bit in the last year, they remain below the level necessary to provide the needed expansion of public health sector revenues. This continued public revenue shortage has become the central challenge that policymakers in these health systems confront, and increasingly constrains their potential range of policy options. The paper then examines the types of targeted reforms that various European governments have introduced in response to this increased fiscal stringency. Particularly in tax-funded health systems, these efforts have been focused on two types of changes on the production side of their health systems: consolidating and/or centralizing administrative authority over public hospitals, and revamping secondary and primary health services as well as social services to reduce the volume, cost and less-than-optimal outcomes of existing public elderly care programs. While revamping elderly care services also was pursued in the social health insurance (SHI) system in the Netherlands, both the Dutch and the German health systems also made important changes on the financing side of their health systems. Both types of targeted reforms are illustrated through short country case studies. Each of these country assessments flags up new mechanisms that have been introduced and which potentially could be reshaped and applied in other national health sector contexts. Reflecting the tax-funded structure of the Canadian health system, the preponderance of cases discussed focus on tax-funded countries (Norway, Denmark, Sweden, Finland, England, Ireland), with additional brief assessments of recent changes in the SHI-funded health systems in the Netherlands and Germany. The paper concludes that post-2008 European reforms have helped stretch existing public funds more effectively, but seem unlikely to resolve the core problem of inadequate overall public funding, particularly in tax-based health systems. This observation suggests that ongoing Canadian efforts to consolidate and better integrate its health care providers, while important, may not eliminate long-term health sector-funding dilemmas.
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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 | 0.011 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.014 | 0.008 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".