CLINICAL OUTCOME MEASURES WITHIN A SPECIALIST PALLIATIVE CARE SERVICE (SPCS): DO THEY PROVIDE ADDED VALUE?
Bibliographic record
Abstract
Background Using clinical outcome measures helps support the delivery of high quality care which is amenable to critical evaluation. The project aims were to: identify potential outcome measures; pilot them within clinical settings; and provide recommendations regarding routine clinical use within a SPCS. Methods Potential outcome measures were identified and critically evaluated. Three instruments - Palliative care Outcome Scale version 2 (POS-2); Palliative Performance Status (PPS); and Edmonton Functional Assessment Tool (EFAT) – were further assessed in a 2 month pilot within in-patient; out-patient; day therapy and outreach services. Each instrument was assessed on two consecutive occasions (unless the patient died or was discharged). Results From 97 patients, 52 (54%) were female and mean age was 68 years (range 27–89 years). POS-2 scores ranged from 1–27 (total score 40=very symptomatic and distressed) with highest scores present for in-patients. Seven patients had POS-2 score >20. All expressed high levels of psychological distress for themselves and their family. Seventeen (73.9%) of the 25 in-patients had a low PPS score (<50%=considerable assistance needed for self-care). For 9 in-patients with a length of stay >14 days, all bar one had a low PPS score on admission. EFAT scores showed highest levels of dysfunction were for outreach and in-patients. EFAT's ability to sufficiently discriminate clinically meaningful variations in function within each care setting limited its recommendation for regular use. Day therapy patients tended to have the lowest POS-2 and EFAT scores. Conclusions Following this project, POS-2 and PPS have been incorporated into routine clinical practice within the day therapy unit and more recently in-patient unit. Initial reflections suggest they aid multi-disciplinary team working and highlight particular patient concerns requiring interventions. PPS scores could potentially be linked with length of stay to help anticipate patients with particular complexity and dependency.
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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 | 0.028 | 0.093 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".