Establishing consensus on emergency department interventions that could be conducted in sub-acute care settings for non-emergent paramedic transported visits: A RAND/UCLA modified Delphi study
Bibliographic record
Abstract
ABSTRACT Background Patients transported by paramedics for non-emergent conditions are increasing in Ontario and contribute to an emergency department (ED) crisis. Redirecting certain patients to sub-acute healthcare may be beneficial and suitable. We examined if ED interventions conducted on non-emergent paramedic transported patients could be conducted in sub-acute health centres. Methods A RAND/UCLA modified Delphi study was conducted. Twenty emergency and primary care physicians rated the suitability of the 150 most frequently recorded interventions for completion in sub-acute healthcare centres and provided comments to augment ratings. Interventions were performed on non-emergent adult patients transported by paramedics to an ED, and abstracted from the National Ambulatory Care Reporting System database (January 1, 2014 to March 31, 2018). We used two rounds of a modified Delphi process and set consensus at 70% agreement. Results Consensus was reached on 146 (97.3%) interventions; 103 interventions (68.7%) were suitable for sub-acute centres, 43 (28.7%) for ED only; 4 (2.6%) did not receive consensus. For sub-acute centres, all 103 interventions were rated for urgent care centres; walk-in medical centres were applicable for 46 (30.6%) and nurse practitioner-led clinics for 47 (31.3). Diagnostic imaging availability, physician preferences and staffing were determining factors for discrepancies in sub-acute centre ratings. Interpretation The majority of included ED interventions performed on non-emergent patients transported by paramedics were identified as suitable for urgent care clinics, with one-third being suitable for either walk-in medical centres or nurse practitioner-led clinics. In combination with additional patient details and supports, knowledge of interventions suitable for sub-acute healthcare centres will inform a patient classification model for paramedic-initiated redirection of patients from ED. Study registration ID ISRCTN22901977 .
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.287 | 0.250 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".