Institutional non-participation in medical assistance in dying: Why non-participation policies persist within Saskatchewan hospitals and their impact on patients and providers
Bibliographic record
Abstract
Medical assistance in dying (MAiD) was thrust into the policy spotlight a decade ago when the Supreme Court of Canada unanimously ruled that prohibiting assisted dying infringed upon the constitutional rights to life, liberty, and security of the person for consenting patients with grievous, irremediable medical conditions who experience intolerable suffering (Carter v. Canada, 2015). Since then, Canadian policymakers have been tasked with balancing the rights of MAiD-seeking patients with the interests of potentially vulnerable persons and those who oppose MAiD. Given the profound impact of MAiD, empirical evidence is vital to inform these policies. One policy that has garnered considerable controversy is institutional non-participation, which occurs when an entire institution opts out of MAiD provision. I conducted a patient-orientated, theory-driven case study to examine the existence of institutional non-participation in MAiD within Saskatchewan (SK) hospitals and to explore the impacts of these polices. SK is considered a critical case as it is one of the most rural provinces in Canada with a long history of Christian involvement in hospital care. Data were collected through semi-structured interviews with 24 participants, including policymakers, healthcare providers, and family members of MAiD patients, and review of relevant policy documents. Analysis was both deductive based on theoretical propositions of the guiding frameworks and inductive to identify novel themes and advance knowledge in this area. Results are presented using the three-paper-model with each addressing a distinct research question. First, historical institutionalism (Campbell, 2004) was used to examine how MAiD non-participation policies emerged and evolved within SK hospitals (Chapter 2). Faith-based conscientious objections appear to underpin all hospital non-participation in SK. These policies are maintained by powerful actors within the Catholic church and government, the dominance of traditional paradigms, and the existence of drifts in practice that emerged prior to MAiD legalization. However, non-participation policies have softened over time due to policy diffusion, patient advocacy groups, and an alternate policy paradigm rooted in patient autonomy. Second, the impacts of institutional non-participation in MAiD were explored from the perspective of the patient-and-family-centered care model (Brown et al., 2022) and Levesque’s (2012) conceptual framework for access to health (Chapter 3). Positive impacts included safe havens, enhanced trust, and opportunity for improved locations or final visits. However, negative impacts were more salient and affected MAiD-seeking patients (physical pain, emotional, relational, disruptions, delays, and constrained choice), family members (vicarious trauma, complicated grief, time consumption at end of life, costs, and stigma), care providers (relational, emotional, moral injury, limited autonomy, increased workload, fear of misstep, and targets of abuse), and healthcare systems (increased complexity, resource strain, and MAiD process). SK’s unique model of centralized MAiD delivery appeared to be intimately related to both the impact and evolution of institutional non-participation policy in SK. Chapter 4 first applies the multiple streams model (Kingdon, 1984) to the adoption of centralized delivery; it then explores the benefits and challenges of this delivery model. Benefits of centralized delivery included improved quality of care (continuity, coordination, efficiency, consistency, accessibility, and patient-centeredness), enhanced supports for providers, and system-level benefits. Challenges include urban concentration, shortage of providers, and perceived lack of resources. This study provides a deeper understanding of the complex policy space in which non-participation policies persist, which is necessary to inform future policy development regarding institutional non-participation in controversial healthcare practices, including MAiD. Keywords: medical assistance in dying, institutional non-participation, conscientious objection
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.021 | 0.028 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.002 | 0.005 |
| 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".