GR.1 Cost-effectiveness of multidisciplinary palliative care interventions in advanced Parkinsonism Syndromes
Bibliographic record
Abstract
Background: Advanced parkinsonian syndromes represent a growing challenge for healthcare systems as their care needs are complex and costly. Current care models often lack integration of specialized neurology and palliative care, leading to suboptimal outcomes. The Advanced Care Team for Parkinson’s program (ACT-PD) addresses this gap by enhancing care quality and reducing costs. This study evaluates the cost-effectiveness of ACT-PD interventions compared to standard care (SC). Methods: A retrospective analysis compared 27 deceased ACT-PD patients (2022–2024) with 1,439 deceased SC patients (2011–2017). It assessed healthcare utilization, place of death, and patient Quality-Adjusted Life Years (QALYs). Healthcare utilization measures included hospitalizations, Intensive Care Unit (ICU) admissions, emergency department (ED) visits, and palliative care consultations. The analysis incorporated the incremental cost-effectiveness ratio (ICER) using Calgary Zone cost data from 2021–2022. Results: ACT-PD patients experienced fewer hospital deaths (33.33% vs. 45.90%) and more deaths at home (22.22% vs. 7.90%). They also had greater neurology (48.00% vs. 37.20%) and palliative care engagement (36.00% vs. 17.40%). ACT-PD avoided ICU admissions, saving $2.56 million annually, with total cost savings of $2.66 million. The ICER was $1,459 per QALY gained. Conclusions: Multidisciplinary palliative care interventions provided by ACT-PD are highly cost-effective, improving care quality while reducing healthcare costs.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| 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) | 0.005 | 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".