PP19.001Re-imaging a regional advance care planning team
Bibliographic record
Abstract
Background In Canada and most of the world, Advance Care Planning (ACP) programs in health care are temporary projects, and funded by minimal full-time equivalent (FTE) staffing. Health care professionals solely dedicated to systems level ACP implementation is rare, often voluntary in nature or added to an overwhelming list of health care professionals’ responsibilities. Methods Innovative Approaches Results Fraser Health Authority had 1 FTE dedicated ACP systems level HCP for 13 years. In 2019, FH expanded its ACP program from a single HCP to three nurses and three social workers. The team works at a regional level to improve ACP practice across 12 hospitals, 20 communities, in all settings of care and with all health care disciplines – a first for Canada! Conclusion Recognizing that education alone is not sufficient to improve HCP engagement in ACP, the team developed an innovative systems improvement approach. In addition to education, this approach prioritizes the following: systems and needs assessment; cohorted education; systems and workflow redesign; coaching and mentoring; and outcome measurement. This poster will highlight how this unique team was built and more importantly, the innovative approach to their work: the Fraser Health Advance Care Planning Systems Approach 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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.694 | 0.406 |
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".