OP54 Delivering system-wide advance care planning support in real-world settings: economic considerations. An exploratory, qualitative study in twelve international healthcare organisations
Bibliographic record
Abstract
Background Facilitation of ACP conversations is time consuming, whether undertaken in one or multiple shorter discussions. Our exploratory, qualitative study in twelve healthcare systems (US, Canada, New Zealand, Australia) providing system-wide ACP support explored: organizational rationales for provision, including perspectives on the economic case type and organization of staffing ways of providing high–quality, system–wide support cost–efficiently. Methods Interviews with leaders, ACP specialists, physicians, nurses, social workers and others (average n=13) were conducted in twelve purposively-sampled healthcare systems. Data were transcribed and thematically analysed using NVivo software. Results System-wide ACP support was primarily a strategic response to risks associated with increased availability and use of life-prolonging interventions in serious illness and frailty. Overall cost-savings were not expected. Staffing ACP support was challenging. While professionals often needed more protected time, promising approaches included team-based provision, especially physicians working with nurses and social workers, and systematic incorporation into chronic and routine care. Skilled and experienced staff underpinned cost-effective provision. While dedicated facilitators were not scalable or sustainable, some level of specialism and voluntarism, with plentiful opportunities to develop skills in practice, was indicated. ACP support was provided equally efficiently by experienced staff regardless of guides or approach used. Serious illness conversations could build on earlier ACP support. Community- and group-based approaches were thought cost-efficient, increasing reach and supporting later planning and decision-making. Conclusions Investments in ACP support were justified by management of organizational risk and high-quality patient care. Our findings identify areas where cost-efficiencies in provision of system-wide ACP support may be found
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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 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.008 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".