Early Integrated Palliative Care Bundle Impacts Location of Death in Interstitial Lung Disease: A Pilot Retrospective Study
Bibliographic record
Abstract
Background: Interstitial lung diseases (ILDs) comprise a heterogeneous group of fibrotic, progressive pulmonary diseases characterized by poor end-of-life care and hospital deaths. In 2012, we launched our Multidisciplinary Collaborative (MDC) ILD clinic to deliver integrated palliative approach throughout disease trajectory to improve care. We sought to explore the effects of palliative care and other factors on location of death (LOD) of patients with ILD. Methods: The MDC-ILD clinic implemented a palliative care bundle including advance care planning (ACP), opiates use, allied health home care engagement, and use of supplemental oxygen and early caregiver engagement in care. Data from patients with ILD who attended the clinic and died between 2012 and 2019 were used to generate scores representing the components and duration of palliative care (palliative care bundle score) and caregiver involvement (caregiver engagement score). We examined the impact of these scores on patients’ LOD. Results: A total of 92 MDC-ILD clinic patients were included, 57 (62%) had home or hospice deaths. Patients who died at home or hospice had higher palliative care bundle scores (10.0 ± 4.0 vs 7.8 ± 3.9, P = .01) and caregiver engagement scores (1.7 ± 0.6 vs 1.3 ± 0.7, P = .01) compared to those who died in hospital. Patients were 1.13 times more likely to die at home or hospice following a 1-point increase in palliative care bundle score (95% CI: 1.01-1.29, P = .04) and 2.38 times more likely following a 1-point increase in caregiver engagement score (95% CI: 1.17-5.15, P = .02). Conclusions: Home and hospice deaths are feasible in ILD. Early initiation of palliative care bundle components such as ACP discussions, symptom self-management, caregiver engagement, and close collaboration with allied health home care supports can promote adherence to patient preference for home or hospice deaths.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".