A comparative study of hospital services payment mechanism by insurance organizations in some selected countries and devising an appropriate plan for Iran
Bibliographic record
Abstract
Regarding an increase in the number of insured people and costs of treatment services, insurance organizations encounter problems in paying claims of their contractees. So that a delay in the payment of contractee hospital costs has made them reluctant in accepting and visiting the insured people. In order to compensate their fiscal deficit and prevent its increase, insurance organizations in Iran have restricted their commitments in front of insured people. Besides, they have increased the amount of money (franchise) paid by patients. These organizations believe that the difference between the income and costs of treatment services is because of low insurance cost per capita and increase of costs of treatment services. This research is an applied study and its administration is descriptive and is conducted as a comparative study. Data are collected from the study of documents, books, articles and information banks. The proposed plan in devised considering the opinions and comments of qualified experts in health care sectors and findings of other countries under this study. The Delphi technique is used to test the mentioned plan. Tariffs for treatment services and medicines are usually determined in Canada, Germany, Japan, France, England and South Korea based on fixed prices and calculated profit, and hospital activities are made in agreement with bazaar system. However, the tariff in public sectors is determined in Islamic republic of Iran, Pakistan and Turkey regarding the governmental subsides and below the fixed prices. Insurance organizations are more influencing in countries of Canada, Germany, France, South Korea, Japan and England in comparison with Iran, Turkey, Pakistan and Indonesia and play more powerful role in determining different tariffs. Definite paying of claims in contractee hospitals in Germany, England, Indonesia, South Korea, Japan and Canada lasts at most two months, but it is done with great delay in Iran. Insurance organizations in countries under our study employ control methods such as setting reference systems of patients, family physician, determining commitment area and the patient portion, and penalizing and nullifying contract of hospitals. Based on proposed plan in this study, tariffs are determined considering opinions of users in homogenized diseases' groups, hospitalization costs, and the features of different areas. Besides, factors such as fixed prices of hospital services and use pattern of treatment services for insured people affect the proposed plan. The proposed plan is applied in both direct and indirect treatment and the independence of insurance organizations from the government and providers of treatment services increases the usefulness and efficiency.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".