Medical assistance in dying in Canada: A review of regulatory practice standards and guidance documents for physicians
Bibliographic record
Abstract
Background: Medical assistance in dying ("MAiD") became legal across Canada in 2016, and in Québec in 2015. Provincial/territorial regulatory bodies play a critical role in MAiD as they can issue binding requirements on health practitioners. Law and regulatory standards are the "twin pillars" of MAiD regulation, yet the content of MAiD practice standards for physicians is unstudied. Design: This article analysed MAiD guidance for physicians from Canadian medical regulators (often called the "College of Physicians and Surgeons"), using a qualitative descriptive approach, informed by regulatory space theory. Methods: We identified MAiD-specific regulatory documents (practice standards and related documents) using web-based searches and follow-up inquiries. We analysed the documents using qualitative descriptive analysis and the Framework Method, facilitated by NVivo. The analysis focused on identifying areas where regulators issued guidance beyond the law. Results: We identified 15 regulatory documents from 11 of the 13 provinces and territories. We determined that these documents primarily outline the law without detailed guidance on how to apply it. We identified eight areas for which regulators provided guidance that went beyond the MAiD-specific legislation, most relating to core aspects of medical practice, such as competency, documentation, and patient-centred care. The rights and obligations of conscientious objectors were a predominant focus in all documents. The documents largely lacked guidance about the meaning of terms in the legislation. There was also variation in standards between provinces and territories; the documents focused on similar topics but varied in their policy choices. Physicians in each province/territory are therefore subject to differing expectations (to some extent). Conclusion: MAiD provisions and highlights interprovincial/territorial variability in MAiD practice standards and guidance for physicians. The study demonstrates the risks of fragmentation inherent in polycentric regulation, which can be challenging for physicians to navigate.
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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 | 0.002 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".