Evaluation of Cost-Effectiveness for Lung Transplant and Ex-Vivo Lung Perfusion
Bibliographic record
Abstract
Demand for lung transplantation exceeds the supply of suitable donor lungs. Ex-vivo lung perfusion (EVLP) is a technology that enables further objective evaluation of potentially-useable organs, as well as rehabilitation of “marginal-risk” donor lungs, outside the body prior to transplantation, which together may increase organ supply and overcome this bottleneck. However, the decision of whether to fund EVLP and integrate it into lung transplant programs must be supported by evidence that considers the clinical, economic, and humanistic consequences of the technology; for EVLP to justifiably receive healthcare resources, the costs, health outcomes, and incremental cost-utility of the technology must be determined. The goal of this thesis was to conduct an economic evaluation of lung transplantation with versus without EVLP at the largest lung transplant center in North America. Our first study determined the impact of EVLP on the cumulative and phase-specific hospital-perspective costs of lung transplantation in Ontario, Canada. This retrospective before-after cohort study presented a novel methodology for phase-based costing that uses multi-state survival regression to overcome the limitations of conventional costing methods. Study 2 evaluated the impact of EVLP on organ transplantation and patient outcomes, using linked health administrative data from the only adult lung transplantation centre in Ontario, Canada, and identified the health resource and clinical implications of having EVLP available. Study 3 involved a cost-utility analysis using an individual patient simulation. This study used input parameters from our antecedent studies to inform a decision-analytic model that estimates the number of transplants, cumulative lifetime costs, and projected health outcomes expressed as quality-adjusted life-years (QALYs). Results from our observational studies suggest that the implementation of EVLP in the Toronto Lung Transplant Program at the University Health Network has been associated with improved accessibility to transplantation, improvements in several clinical outcomes, but no significant difference in phase-specific or cumulative costs. We found that having EVLP available should be considered cost- effective across a range of commonly accepted cost-effectiveness thresholds. Collectively, this thesis synthesized evidence that EVLP was economically justifiable at our centre; these findings may be used by clinicians, administrators, and other institutional stakeholders involved in resource allocation and funding decisions.
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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 | 0.015 | 0.042 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".