Optimal pricing and budget decisions in public health systems with delay sensitive patients
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The congestion of public hospitals for elective treatment in some countries and regions, such as Canada and Hong Kong where the free health policy is implemented, is a serious issue. The main reason is the excessive demand generated by the provision of free service. In response, the government can set appropriate service price and budget for public hospitals to moderate such demand. This is often referred to as the charging policy, implemented in countries such as China. A Stackelberg game is established for a health system consisting of a government, a public health provider and delay sensitive patients. The results show that when the customers' waiting cost is low (e.g., the market demand, the patients delay sensitivity, or the unit capacity cost is low), the free health policy outperforms the charging policy; otherwise, the charging policy is better. Moreover, we find that the equilibrium waiting time and the equilibrium price decrease with the market demand when the funder attaches more importance to patients’ welfare than the budget surplus and the total budget is sufficient.
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.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 it