Control strategies for medical tourism development in public hospitals considering waiting time and tourism attraction
Bibliographic record
Abstract
Medical tourism has become one of the fastest-growing emerging industries in the world. For some countries where public hospitals are dominant, as serving foreign customers may increase hospital congestion, whether public hospitals are allowed to develop medical tourism has become a significant issue. Thus, based on queueing and game theories, this paper explores the control strategies for the development of medical tourism in public hospitals in terms of social welfare. In a market that includes government, public hospitals, domestic and foreign patients, short-term and long-term cases where the public system (i.e. public hospitals) will invest the incomes from foreign patients into the capacity expansion or not are investigated respectively. The results show that if government’s total budget, profitability of the tourism industry, or tourism attraction (or patients’ delay sensitivity) is high enough (or low enough), the social planner should allow the public hospitals to participate in medical tourism projects and not otherwise. Furthermore, we find that under certain conditions, public hospitals engaging in medical tourism projects may compromise the welfare of domestic patients or increase the government’s budget expenditure on the public hospital system.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".