An analysis of the complexities of advance care planning implementation : insights gained from a review of the literature
Bibliographic record
Abstract
Background: Advance care planning (ACP) is a process for patients and families to engage in discussions around future wishes for health care. It offers a means to increase dialogue about end of life care and has the potential to improve patient outcomes. Despite the benefits demonstrated in literature, there are still many challenges to ACP implementation. This thesis investigated why ACP is so difficult to implement by reflecting on the following stakeholders: patients and families of older adults and individuals living with chronic illnesses, health care providers, and health care organizations. Particular examples are drawn from the context in British Columbia, Canada. Methods: A purposeful search strategy modifying the rapid evidence assessment approach was used to synthesize the literature. Research studies, summary reports, and policy documents were used to build a balanced picture of perspectives for policy makers. Bryant’s (2009) Policy Change Model and critical theoretical perspectives shaped this analysis and highlighted the complexities and ideologies behind public, professional, and organizational sentiment. Findings: The analysis of literature on patient and provider perspectives shows the biomedical dominance in health care culture and the disinclination to discuss end of life issues. A shift is needed where recognition and prioritization of ACP implementation is supported by leaders in health organizations. Organization-wide multi-component ACP efforts combined with goals of care documentation have been shown to be most successful in improving patient outcomes, but organizational commitment to development of processes and policies is necessary. There is opportunity for nursing leadership and research to move ACP efforts forward in organizations. Conclusion: The analysis presented in this thesis maps evidence for policy makers, stakeholders, and nursing leaders interested in promoting strategic ACP implementation and future ACP research. Process and policy changes are needed to support public and provider engagement.
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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 | 0.047 | 0.105 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.025 | 0.029 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| 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".