Cost‐effectiveness of pathogen reduction technology for plasma and platelets in Québec: A focus on potential emerging pathogens
Bibliographic record
Abstract
BACKGROUND: The last economic evaluation of pathogen reduction technology (PRT) in Canada was conducted in 2007. We reassessed the cost-effectiveness of PRT in the province of Québec (which has its own blood supplier) and included an evaluation of the potential impact of emerging pathogens on cost-effectiveness. STUDY DESIGN AND METHODS: Decision analytic Markov models were developed to simulate the costs and quality-adjusted life-years (QALY) associated with PRT as an addition to existing safety measures for plasma and platelet products (except for bacterial culture). Models accounted for several infectious and noninfectious transfusion reactions, recipients' productivity losses ensuing from these reactions, and the impact of PRT on platelet function. Scenario analyses were conducted to evaluate the impact of a new highly contagious human immunodeficiency virus (HIV)-like or West Nile virus (WNV)-like pathogen, assuming various epidemiological scenarios. RESULTS: In the base case, the incremental cost-effectiveness ratio (ICER) of PRT was estimated at $8,088,974/QALY gained. Assuming the presence of an HIV-like pathogen, the ICER was $265,209/QALY gained in the "average transmission" scenario, $1,274,445/QALY gained in the "rapid testing scenario," and $123,063/QALY gained in the "highly contagious" scenario. Assuming the presence of a WNV-like pathogen, the ICER was $7,469,167/QALY gained in the "average transmission" scenario and $6,652,769/QALY gained in the "highly contagious" scenario. CONCLUSION: The cost-effectiveness of PRT may substantially improve in the event of a new, blood-borne pathogen. Given their significant impact on cost-effectiveness, the emergence of new pathogens should be considered when deciding whether to adopt PRT.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".