Variation in Cost and Quality in Kidney Transplantation
Bibliographic record
Abstract
BACKGROUND: Bending the cost curve in medical expenses is a high national priority. The relationship between cost and kidney allograft failure has not been fully investigated in the United States. METHODS: Using Medicare claims from the United States Renal Data System, we determined costs for all adults with Medicare coverage who underwent kidney transplant January 1, 2007, to June 30, 2009. We compared relative cost (observed/expected payment) for year 1 after transplantation for all transplant centers, adjusting for recipient, donor, and transplant characteristics, region, and local wage index. Using program-specific reports from the Scientific Registry of Transplant Recipients, we correlated relative cost with observed/expected allograft failure between centers, excluding small centers. RESULTS: Among 19,603 transplants at 166 centers, mean observed cost per patient per center was $65,366 (interquartile range, $55,094-$71,624). Mean relative cost was 0.99 (± 0.20); mean observed/expected allograft failure was 1.03 (± 0.46). Overall, there was no correlation between relative cost and observed/expected allograft failure (r = 0.096, P = 0.22). Comparing centers with higher than expected costs and allograft failure rates (lower performing) and centers with lower than expected costs and failure rates (higher-performing) showed differences in donor and recipient characteristics. As these characteristics were accounted for in the adjusted cost and allograft failure models, they are unlikely to explain the differences between higher- and lower-performing centers. CONCLUSIONS: Further investigations are needed to determine specific cost-effective practices of higher- and lower-performing centers to reduce costs and incidence of allograft failure.
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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 | 0.007 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".