Geographical Disparity in Access to Organ Transplant in the United States and Other Western Countries: A Prolegomenon to A Solution
Bibliographic record
Abstract
Abstract Background: Disparities in access to and in outcome of organ transplantation are widely discussed topics among transplant researchers in many Western countries. Among various types of disparities examined in existing studies, “geographic disparity,” i.e., disparity due to a recipient's location, is most common. Despite a number of articles that acknowledge the existence of geographic disparities, the literature has been relatively silent about the historical and international efforts to address these issues. Literature discussing remedies or proposing analytical tools to identify remedies is even rarer. This paper investigates potential causes of geographic disparity and advocates possible methodological approaches to analyze and address the disparity. Methods: The paper conducts an in‐depth review of geographic disparity and the policy efforts to reduce the disparity in the United States, Canada, France, Spain, the United Kingdom, and Australia. The current organ allocation systems in these countries are also reviewed and compared. Possible causes of the disparity and future analytical approaches are discussed based on the findings of these reviews. Findings: Geographic disparity in organ transplant service is ubiquitous in all countries studied. Many Western countries have a similar organ allocation system with some difference in the degree of interregional and national‐level sharing enforced by the government. The organ allocation system in these countries tends to have some inherent mechanism to favor a “home region” where organs are harvested, implying that the locations of candidates matter in accessing a transplant. Geographic allocation boundaries prevalent in the United States were found to be another potential source of geographic disparity. Conclusions: Developing an equitable organ allocation system is a multifaceted problem. The allocation procedure needs to reflect priorities of urgent cases and some geographic areas, patient's severity level, waiting time, cold ischemia time (CIT) and associated travel distance, condition of and compatibility between organ and recipient, etc. Failing to reflect these factors adequately results in disparity of some sort. The implications of geographic boundaries in organ allocation need to be studied further. Utilization of relatively new methodological approaches, such as Geographic Information Systems (GIS) and system dynamic modeling, would help develop a system that allocates organs more equitably.
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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 | 0.010 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.009 |
| Scholarly communication | 0.004 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| 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".