OP82 Identification, implementation and evaluation of indicators to monitor successful uptake of advance care planning in alberta
Bibliographic record
Abstract
<h3>Background</h3> In 2014, a province-wide policy for advance care planning (ACP) and Goals of Care Designation (GCD) was implemented in Alberta, Canada; nevertheless, few quality indicators have been rigorously developed or evaluated for measuring the uptake of ACP/GCD. <h3>Methods</h3> In phase I, we performed a systematic literature review and environmental scan to identify potential ACP/GCD indicators. A Delphi consensus-based approach, consisting of 3 rounds of face-to-face meetings and/or online surveys, was used to develop a short list of indicators. In phase II, the panelists met face-to-face to operationalize and implement the indicators. In phase III, two validated questionnaires and semi-structured interviews of 60 individuals (stratified by manager/practitioner and physician/nurse) are being used to evaluate the usability and acceptability of the implemented indicators on a dashboard interface. <h3>Results</h3> A total of 132 potential indicators were identified in phase I. The indicators were reduced and refined to 18 after 3 Delphi rounds. Phase II resulted in 9 valid and feasible indicators in a measurable format (i.e. numerator, denominator, data source defined). The Phase III protocol is under ethical review and potential participants’ recruitment is underway. <h3>Conclusions</h3> Of 132 quality indicators for ACP/GCD, 9 are feasible, valid, usable and acceptable for monitoring performance in the rollout of ACP/GCD. This set of indicators shows promise for describing and evaluating ACP/GCD uptake throughout a complex, multi-sector healthcare system.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".