BOS2c.004 A provincial whole-systems approach to promoting conversations that matter
Bibliographic record
Abstract
Background In 2016, the British Columbia Centre for Palliative Care, Canada, broke new ground in adopting a province-wide, multifaceted approach to ACP promotion and engagement, using complementary strategies across key stakeholder groups: the health system, healthcare providers, students, community, and the public. Methods Informed by the four pillars within the Pan-Canadian ACP Framework, and provincial surveys with the public and healthcare providers, our programs focus on building capacity within the healthcare system and academic institutions using a train-the trainer strategy (e.g. Serious Illness Conversation (SIC) Training Program), empowering the community to support ACP awareness and education (e.g. Community-led ACP education sessions for the public), and developing culturally and linguistically appropriate ACP resources for the diverse population in BC. Research and evaluation activities informed the development of the programs and strategy overall. Results Our role as a catalyst for a collective impact in ACP engagement allowed us to bring together the healthcare and community partners from across the province to co-design, test and spread solutions that are based on evidence and inputs from experts, end users and people with lived experience. We focused on the mobilization of assets and pockets of excellence already existing, while acknowledging that adaptation for specific populations would be required. Examples of the successes achieved to-date are: thousands of clinicians completed the SIC training, incorporation of SIC training in the education curriculum for medical, nursing and social work students, more than 70 community organisations trained to deliver ACP education sessions with around half of these organizations serve rural and remote communities. Conclusion Based on our experience, an effective whole-systems approach to ACP engagement requires meaningful public engagement, ongoing collaboration with partners, culturally considerate messaging, user-friendly resources, and consistent education programs for everyone. Flexibility in programs and strategy was advantageous, with evaluation and research results informing new directions.
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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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.121 | 0.027 |
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".