Assessing financing methods and payment system for health service providers in selected countries: designing a model for Iran
Bibliographic record
Abstract
Introduction: Majority of health systems across the world are experiencing challenges in their performance, quality, equity, and efficacy because financial resources limitation. To deal with, they use different method of financial allocation resources and payment systems. Methods: This comparative descriptive research is dedicated to financing methods and payment systems to the health service providers in the health sector of 12 countries: Australia, United Kingdom, United State of America, Turkey, Sweden, Norway, Japan, Netherlands, Canada, Denmark, France, and Germany. The model, based on the operated common mechanisms in the aforementioned countries, is designed for health system of Iran and it is validated by the masters and recognized as Delphi method. Results: financing for health service providers in the selected countries mainly is annual global allocation budget and the criterion of allocation especially in the current cost based on quality, cost, and performance. The calculation of cost is based on estimated cost. Payment system on the first level is based on per capita and fee for service in other levels based on fee for services. Also the model was statistically confirmed the significant of results (p<0/05). Conclusion: Given to the low rate of GDP and low portion of health sector from GDP in Iran, we recommended payment to the first level as combination of per capita and fee for service. The performance and justice of health system will promote with payment as fee for service for other of health service provider and indirect financial resources allocation to the health service providers (through insurance organizations) and make same tariff between public and private sector.
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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 | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".