Canadian Certificates of Added Competency in Palliative Care: A Pan-Canadian Qualitative Study of Roles and Impact
Bibliographic record
Abstract
Context: Since 2015, the College of Family Physicians of Canada’s Certificates of Added Competence (CAC) program has included enhanced skill certification in Palliative Care (PC) to support the scope of Family Medicine services available to patients and communities. Objective: To describe the ways in which family physicians with a CAC in palliative care contribute within their communities, the factors that influence the models in which these physicians work, and the perceived impacts of this work. Study Design: Secondary unconstrained content analysis of qualitative data from a multiple case study on the role and impacts of family physicians with a CAC. Population: Six family medicine practices across Canada, between September 2018 and June 2019. Data Source: Interviews with PC and generalist physicians, trainees, and administrators, which included discussion of the PC role, associated with these cases. Outcome Measure: Qualitative descriptions of the models of care, factors influencing the way PC physicians work, and their impacts in the community. Results: Twenty-one participants (nine PC physicians, five generalist family physicians, two residents, five physicians with enhanced skills in other domains) contributed data. PC physicians enhanced the workforce to meet palliative care needs in communities. PC physicians worked in various models, ranging from maintaining and enhancing their own family practice through to working exclusively as a PC physician. In the latter case, PC physicians worked in a collaborative model with other physicians by providing consultations to other physicians, co-managing patients (shared care), or assuming care of the patient as the main provider (transfer of care). PC physicians intentionally built capacity among their colleagues, with some activities not being remunerated. Funding models and other structures favoured the PC physician taking over care. Conclusion: PC physicians with added competency facilitate comprehensive care of people until the end of life, through direct patient care models and by building capacity among others. Remuneration models should support system capacity and relationships that enable family physicians to provide primary palliative care, especially outside the transfer of care model.
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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 | 0.011 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.021 | 0.008 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".