Increased patient satisfaction by integration of palliative care into geriatrics—A prospective cohort study
Bibliographic record
Abstract
BACKGROUND: Integration of oncology and palliative care has been shown to increase quality of life in advanced disease. To meet the needs of the growing older population, integration of palliative care and geriatrics has been proposed but scarcely described. OBJECTIVES: The aim of this study was to integrate palliative care into geriatrics by a structured care guide, the Swedish Palliative Care Guide, and to evaluate its effect on patient satisfaction, health-related quality of life and symptom burden, compared to a control group. METHODS: Geriatric in-patients over 65 years of age were included in the study, those with cognitive impairment were excluded. Data was collected before (baseline) and after the implementation (intervention) of the Swedish Palliative Care Guide. Patient satisfaction was evaluated two weeks after discharge with questions from a national patient survey. Health-related quality of life was measured with EQ-5D-3L and symptom burden with Edmonton Symptom Assessment Scale. RESULTS: In total, 400 patients were included, 200 in the baseline- and intervention group, respectively. Mean age was 83 years in both groups. Patient satisfaction was significantly higher in nine out of ten questions (p = 0.02-<0.001) in the intervention group compared to baseline. No differences between the groups were seen in health-related quality of life or symptom burden. CONCLUSION: A significant effect on patient satisfaction was seen after implementation of the Swedish Palliative Care Guide in geriatric care. Thus, integration of palliative care and geriatrics could be of substantial benefit in the growing population of older adults with multimorbidity and frailty.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".