P-31 Preparing for the evaluation of an enhanced community palliative support service (encompass)
Bibliographic record
Abstract
Research aims To document and analyse current operating practices for community palliative care services prior to the introduction of new technologies and changed working practices. Background In line with national priorities, one UK hospice is introducing new technologies to support the redesign of their community services; improve patient experience; and expand service provision. Rather than the existing model of 1:1 community-based nursing by senior specialist nurses, junior nurses will be delegated to deliver palliative care plans under online supervision by specialist palliative care nurses. The technologies provide online access to up-to-date clinical records to support effective team interaction and decision-making, enable point-of-care documenting of observations and care delivery, and immediate access to support from specialist clinicians. This initial study has benchmarked existing community palliative care delivery in preparation for the subsequent operational and financial evaluation of the new service and has: Identified and documented current working practices; Identified and isolated the key costs and benefits of the service; Established current data input and data use; and Assessed current patient outcomes. Methods A mixed methods approach was used to understand a wide range of organisational, economic, and patient-level factors; examine the barriers to, and facilitators of, the implementation of this innovative service modeland explain how and why specific changes are expected to occur. Data has been collected using interviews, focus groups, observation, routinely collected data and documents. Results This presentation will report on the study, including development of an organisational model incorporating proposed changes from the introduction of new technologies. This model will guide the gathering and analysis of evidence to describe the actual changes achieved and explain any differences between these and the anticipated model. Conclusions Developing and evidencing improved efficiency in community-based services poses a number of challenges for providers, requiring significant changes to current practice, together with technology-based enablers.
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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 | 0.030 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.039 | 0.008 |
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".