RESOURCE ALLOCATION, FINANCING AND SUSTAINABILITY IN THE HEALTH SECTOR. ESRI Research Bulletin 2010/3/1
Bibliographic record
Abstract
The focus on acute, episodic care in the conventional health-care model fails to provide adequately for changing health-care needs arising from increased longevity and increasing prevalence of chronic disease. Integrated care involves coherent and co-ordinated delivery of health-care services across a broad range of health and social care providers. A principal aim of integrated health care is to improve the patient’s journey through the system by co-ordinating care among providers and by strengthening the role of primary care. Effective resource allocation mechanisms, supported by appropriate financing arrangements, have an important role to play in delivering integrated health care. In addition, more efficient use of scarce health-care resources is required, and can be influenced by the resource allocation and financing mechanisms. This article summarises research undertaken by the ESRI to provide evidence for the Expert Group on Resource Allocation and Financing in Health Care, which reported in July 2010 (Brick et al., 2010a, b; Ruane, 2010). The research: • reviewed the theoretical and international empirical literature on resource allocation, financing and sustainability in health care (focusing on eight comparator countries – Australia, Canada, Germany, Netherlands, New Zealand, Sweden, UK, USA); • evaluated current Irish systems of resource allocation and financing and issues associated with sustainability; • proposed a framework for health-care entitlements and user fees that would support the delivery of integrated health care in Ireland.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".