Palliative paramedicine: An interrupted time series analysis of pre-hospital guideline efficacy
Bibliographic record
Abstract
Background: Paramedics are increasingly involved in palliative care and often support community-based palliative care service delivery to facilitate integrated practice. However, the impact of specific palliative care guidelines on clinical practice remains unknown. Aim: To determine the impact of an ambulance service palliative care guideline on rates of supportive medication administration and non-transport. Design: A retrospective cohort study of electronic patient care records from January 2014 to June 2023. Baseline characteristics were compared pre- and post-guideline introduction. Interrupted time series analysis was performed to examine guideline efficacy. Setting/participants: Patients of all ages receiving palliative care who were attended by paramedics in Victoria, Australia. Results: A total of 31,579 patients were included. The median age was 75 years (IQR = 64–84 years), and 56.4% were men. Overall, 25.8% of patients were not transported to hospital. Following guideline introduction, there were no significant trend changes in administration of supportive medications. However, the non-transport rate increased significantly per month (0.2%, p = 0.007), amounting to a 9.9% ( p = 0.020) total increase by the end of the study period compared to a scenario in which the guideline had not been introduced. Subgroup analysis of patients diagnosed with ‘pain’ or attended after-hours also showed significant increases in non-transport (monthly increase: pain 0.3%, p = 0.003; after-hours 0.3%, p < 0.001; total increase: pain 29.7%, p < 0.001, after-hours 22.6%, p = 0.001). Conclusions: Introduction of a palliative care guideline was associated with a decrease in ambulance transport to emergency departments, allowing more patients continuity of care in the community.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".