Advance care planning discussions among residents of LTC and DAL in Alberta
Bibliographic record
Abstract
Patients, physicians and the health care system are faced with the challenge of determining, and respecting, the medical wishes of an aging population. Patient autonomy and informed decision-making can only be maximised when the decision-making process is better understood. In 2008, Alberta Health Services initiated its “Advance Care Planning: Goals of Care Designation” (ACP:GCD) policy in the Calgary Zone. This policy encouraged discussions about goals of care (GOC) and used a tracking form to capture these conversations. Chart audits were performed at 3 time points: at baseline, at 6 months, and at 18 months post implementation. Recorded data included presence of an advance directive on the chart, indication of a personal representative/agent, and the number, participants and recorded key outcomes of documented ACP conversations. This study will perform a retrospective review of the results of those audits in both Long Term Care (LTC) and Designated Assisted Living sites (DAL). Specifically, we will address what elements of ACP were discussed including: prognosis and anticipated outcomes of treatment, patient's values and understanding/expectation of treatment options, life sustaining measures/degree of benefit, comfort measures, resources available and GOC. 166 charts had documented ACP discussions, representing 81% of LTC charts reviewed and 87% of those in DAL. The limitations of this study are those retrospective data and the reliance on accurate/thorough chart documentation. The study will identify current practice in the advance care planning process in LTC And DAL and potential gaps in that practice.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".