OA58 Community capacity development for enhanced hospice palliative care: exploring the value of community engagement
Bibliographic record
Abstract
BACKGROUND: Over time, palliative care has become "professionalised", placing a burden on health care systems to manage the suffering of individuals and families with advancing, life-limiting illness. The need to develop resources, infrastructure and policy to enhance the capacity for communities to facilitate and support individuals and families can add value to communities, enrich hospice-palliative care and reduce health care system burden. AIM: Few examples of communities developing such capacity exist, however, this oral presentation will describe the results of one study that examined, in one rural community in western Canada, key factors that influenced their ability to address their own hospice palliative care needs. We will report on factors that helped and factors that hindered them in their initial stages of planning for better care. A follow up study that is just at its initial stages (i.e. to start in Jan./Feb., 2015) will examine the value and outcomes of a model where communities collaborate with health care providers to strengthen their hospice palliative care community level capacities. In two rural communities in western Canada, such questions asked will be: What expertise and infrastructure is required to nurture community-based palliative care initiatives? What criteria constitute community engagement and leadership in hospice palliative care development? When using a model where communities collaborate with health care providers to strengthen their hospice palliative care, what are the direct outcomes? And are these of value, and if so, in what way, and if not why not? METHODS: The two studies use multiple research methods. Both use a case study approach and framework. Results are also generated from a systematic literature review; semi-structured key informant interviews and focus group interviews. RESULTS: Results from the first study reveal significant barriers to a community planning their hospice palliative care needs, such as: a lack of provincial guidelines or funds; unforeseen workload; community expectations for a hospice building versus improved care; and an overall fear of failure. Key factors supporting their planning were: improved community awareness; putting hospice palliative 'on the map' at a provincial level; substantial donations for new services etc. Although our second, follow study to determine more concrete outcomes to community leadership and collaboration with health care providers are unknown, we imagine results will speak to the need for specific and tangible resources, infrastructure and specific policy direction.
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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 | 0.009 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".