An Examination of the Socio-political Forces Shaping End-of-life Conversations in Interprofessional Primary Care with Medically Frail Older Adults
Bibliographic record
Abstract
Scholarship in the field of end-of-life (EOL) conversations has grown over the last three decades. However, despite a large body of work, there remain theoretical, methodological, and substantive gaps to inform an understanding of the issue of delayed or avoided EOL conversations in primary care. This critical ethnography informed by biomedicalization attempts to build an understanding, rooted in empirical data, of how EOL conversations happen and also why they might not happen in the primary care of medically frail older adults. Data includes observations of 25 clinical appointments involving clinicians and medically frail older patients and/or their care partners at an urban Family Health Team in Ontario, Canada as well as 94.5 hours of structured observations of clinicians’ day-to-day activities excluding direct patient care, and 27 interviews with participants. Key findings highlight the multiple and competing discourses circulating in primary care that constrain EOL conversations. In appointments with patients’ ‘most responsible providers’ (MRPs), the more life discourse constrains talk of decline and dying, making EOL conversations less possible. More life is aligned with the culture of biomedicine and clinical practice guidelines as well as the culture of life extension in the West, giving this discourse influence. Interprofessional collaboration (IPC) in EOL conversations is also limited, with nurses and allied health clinicians rarely being involved in EOL conversations. Neoliberal-biomedical discourse shapes factors at the structural, organizational, and practice levels, encouraging efficiency and biomedical dominance in ways that limit opportunities for IPC in EOL conversations. I recommend primary care as a specialty reflects on its entrenchment in a culture of care that valorizes more life and (re)create clinical practice guidelines and measures to align with person-centredness more meaningfully. Additionally, for nurses and allied health clinicians to become involved in EOL conversations with frail older adults, they need to share in clinical decision-making. Structurally, improving IPC must address constraints from neoliberal and biomedical ideologies. Clinicians can also collectively work at the practice level to create change. Future research should take a participator approach with patients, care partners, and interprofessional clinicians to develop ways of supporting holistic relational care & communication in primary 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 | 0.010 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.015 | 0.009 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.003 |
| 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".