Medical assistance in dying (MAiD) in Canada: practical aspects for healthcare teams
Bibliographic record
Abstract
In this paper we document some of the practical aspects of implementing medical assistance in dying (MAiD) since it became legal in Canada in 2016. The percentage of annual deaths in Canada due to MAiD varies widely, ranging from less than 0.5% in some areas to over 5% in others. By the end of 2019, approximately 13,000 people had an assisted death in Canada (1.6% of all deaths). The average age is 73 years and the majority have cancer (64%), followed by end-stage organ failure (17%), and neurological disease (11%). The safeguards in Canadian law include having two witnesses sign the patient request form, having two independent clinicians agree that the patient is eligible, and requiring a 10-day waiting period after the request is made. Although the criminal law is federal and applies throughout the nation, health services managed provincially, and there are many different models of care being used. Some provinces have standardized prescriptions and procedures for assisted dying with centralized care coordinators supporting both patients and providers. Other provinces expect individual providers to manage all aspects of assisted dying. The procedure and medications are provided free of charge to patients, but it took years before many providers were remunerated for their services. Access for patients has been a problem because there are too few providers of care (especially in rural areas), and many people have difficulty getting accurate information about the process. Many faith-based health care facilities continue to refuse to allow assisted dying within their facilities, so patients requesting MAiD need to be transferred to other locations in their last hours of life. Solutions to these problems have included the development of more training and support for providers and the creation of coordinating centres that provide information and support for patients throughout the process. Telemedicine is used for assessment of eligibility when required, especially during the COVID pandemic. There are similarities in problems of access to all end of life care options, including palliative care and residential hospices. The relationships between providers of assisted dying and specialists in palliative care vary, and examples exist throughout the spectrum from collegial to hostile. This is slowly improving, as individual clinicians gain more experience with patients choosing assisted dying. Public culture is changing as there are more conversations occurring about death and dying.
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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 | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".