Implementing the British Columbia practice support program in end of life care
Bibliographic record
Abstract
The British Columbia (BC) Practice Support Program, supported by the General Practice Services Committee (a joint program of the BC Medical Association, the Ministry of Health), has been an effective strategy to change and influence the care being offered in GP offices throughout BC. This innovative program has engaged 2000 GPs (of ∼3500 caring for 4.5 million people) in practice redesign since 2007 and now is providing a module to improve the identification, assessment and management of patients at the end of life, including redesign of office processes and procedures that need to be implemented to support a new approach. It integrates aspects of the Gold Standards Framework (UK), the BC Chronic disease management framework, the triple aim of the Institute for Health Care Improvement, with the norms and practices of Hospice Palliative Care in Canada. Participants include GP champions as the teachers together with local palliative care providers, home care nurses, specialist physicians and general practitioners and their MOAs. There are 3 learning sessions interspersed with 2 action periods during which physicians are supported to implement changes in practice like a registry; flags to alert the physician to key changes; more collaborative practice and supports for Advance Care Planning. The algorithm and the clinical support tools embedded in the algorithm have been well received and reinforce a best practice approach. The results of the evaluation will be presented. This may enable others tasked with physician education and practice support to learn from a successful, innovative provincial implementation.
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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 | 0.009 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".