Simplifying palliative symptom management: elastomeric infusions in hospice and home care
Bibliographic record
Abstract
BACKGROUND: Palliative care patients often require frequent, resource-intensive, intermittent subcutaneous injections or complex infusion pumps for end-of-life symptom management. PURPOSE: We aimed to explore the feasibility of using non-electronic elastomeric infusion devices for continuous subcutaneous medication delivery in hospice and home care. METHODS: A quality improvement initiative included an environmental scan to evaluate elastomeric devices and treatment protocols, followed by a stepwise implementation of elastomeric infusion devices for symptom management of palliative care patients. RESULTS: During five years, 4,754 elastomeric devices were dispensed with non-narcotic medication mixtures to 265 patients in hospice and home care and 585 devices with narcotic mixtures for 62 patients during a 12-month period. No adverse events were reported. A total of 110 unique medication combinations involving 11 symptom management medications were dispensed. Qualitative feedback revealed strong nursing, physician, patient, and caregiver support. The acceptability of elastomeric subcutaneous infusions of symptom management medications was supported by the reported simplicity, safety, efficacy, and efficiency of this treatment modality. The protocol was adopted in hospice and is in the pilot phase for home care. CONCLUSION: Our findings suggest that continuous subcutaneous infusions via elastomeric infusion pumps offer a promising and feasible approach to end-of-life symptom management in hospice and home care. Elastomeric infusions may enhance simplicity, acceptability, safety, efficacy, and efficiency of care, compared to traditional routine subcutaneous injections. While results lay a foundation for treatment protocols that reduce care complexity, further research is warranted to optimize medication combinations and evaluate outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".