Impact of government health coverage for ART: The results of a 5-year experience in Quebec
Bibliographic record
Abstract
An analysis of national registry data for 5 years of in-vitro fertilization (IVF) funding in Quebec, Canada was compared with the previous complete year of non-funded IVF cycles, as well as the first complete year following the end of funding.The number of cycles, livebirth rates, age group of patients treated, use of donor gametes, multiple pregnancy rates and cycle cancellation rates were assessed.The total number of IVF cycles performed increased dramatically during the funded period, averaging over 10,000 cycles per year.There was no change in the age group distribution of patients treated, but less egg donation was performed.Interestingly, funding was also associated with an increase in the IVF cycle cancellation rate (17.0%versus 34.4%, P b 0.001), a dramatic decline in the multiple pregnancy rate (25.6% versus 4.9%, P b 0.001), and a decline in the livebirth rate per fresh embryo transfer in stimulated IVF cycles (32.3% versus 25.5%, P b 0.001).Although the livebirth rate for stimulated IVF declined, over 9000 babies were born as a result of the coverage.Lessons learned from this experience could help develop a more fiscally responsible programme that still facilitates access to IVF care.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 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) | 0.003 | 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".