Protocol and Statistical Analysis Plan for a Comparative Interrupted Time Series Evaluation of the Impact of Deemed Consent for Organ Donation Legislative Reform in Nova Scotia, Canada
Bibliographic record
Abstract
The Canadian province of Nova Scotia recently became the first North American jurisdiction to implement deemed consent for deceased organ donation as part of a comprehensive legislative reform of their donation and transplantation system. This study will examine the performance metrics and effectiveness of this policy in comparison with other Canadian provinces via a natural experiment evaluation. We will use a cross-sectional controlled interrupted time series quasi-experimental design. Our primary outcome will be consent for deceased donation as confirmed at the time of eligibility (prior registered intent to donate will be noted but not be considered positive unless affirmed at the time of eligibility). Secondary outcomes will include identification and referral of patients who are potential donors, rates of family override of previously registered intent to donate, and donation and transplantation rates per million population. Data will be collected from potential donor audits in Nova Scotia and 3 control provinces (provinces in Canada without deemed consent policies). Study outcomes will be compared in Nova Scotia relative to control provinces in the 3 y before and 3 y after the implementation of legislative reform. These provinces were selected as having systems resembling those of Nova Scotia but without deemed consent.Using controlled interrupted time series methodology compared with other Canadian provinces with otherwise similar systems, we aim to isolate the impact of the deemed consent aspect of legislative reform in Nova Scotia using a robust natural experiment evaluation design as much as possible. Careful selection of outcome measures will allow donation and transplantation stakeholders to properly evaluate if similar reforms should be considered in their jurisdictions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".