OP29 ‘While my thinking is clear’: outcomes from a feasibility pilot of a multidisciplinary, step-wise pathway for ACP in family medicine
Bibliographic record
Abstract
Background Advance care planning (ACP) and goals of care (GCD) discussions with patients align with the tenets of patient-centred shared decision-making central to family medicine (FM). We sought to determine whether a multidisciplinary pathway is feasible in family medicine to enable effective ACP conversations. This pathway reorders Ariadne Lab’s Serious Illness Conversation Guide (SICG) with a values clarification tool in a step-wise approach to ACP. Methods Mixed-methods feasibility pilot study of pathway implementation in an urban FM clinic in Alberta, Canada. We recruited community-dwelling patients age 60 or older with indications of frailty (multi-morbidity, unplanned hospitalizations), and their surrogate decision-maker (SDM). An allied health professional initiated the ACP pathway, which preceded an appointment with the family physician (FP) to complete the SICG discussion. We conducted a survey of patients and SDMs, and a focus group with clinicians to evaluate feasibility, acceptability and perceived impact. Results Nine patients, seven SDMs, and four clinicians participated in the pilot. All patients and SDMs rated the process as “very good” or “excellent”. Eight patients and two SDMs reflected that discussing and documenting their preferences helped them feel more prepared for future illness, and that involving SDMs was essential. Clinicians found the pathway and SICG improved their skills and empowered them to facilitate these conversations more effectively. Conclusions This pathway that adapts use of the SICG was acceptable and effective for all participants. The pathway fits well into FM as the trusting relationship between the patient and FP provides the foundation for these meaningful conversations.
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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 | 0.020 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".