Post-Pandemic Growth in 9-1-1 Paramedic Calls and Emergency Department Transports Surpasses Pre-Pandemic Rates in the COVID-19 Era: Implications for Paramedic Resource Planning
Bibliographic record
Abstract
OBJECTIVES: The COVID-19 pandemic led to a decline in emergency department (ED) visits and a subsequent return to baseline pre-pandemic levels. It is unclear if this trend extended to paramedic services and if patient cohorts accessing paramedics changed. We examined trends and associations between paramedic utilization (9-1-1 calls and ED transports) and the COVID-19 timeframe. METHODS: We conducted a retrospective cross-sectional study using paramedic call data from the Hamilton Paramedic Services from January 2016 to December 2023. We included all 9-1-1 calls where paramedics responded to an incident, excluding paramedic interfacility transfers. We calculated lines of best fit for the pre-pandemic period (January 2016 to January 2020) and compared their predictions to the actual volumes in the post-pandemic period (May 2021 to December 2023). We used an interrupted time series regression model to determine the association between pandemic timeframes (pre-, during-, post-COVID-19) and paramedic utilization (9-1-1 calls and ED transports), while testing for annual seasonality. RESULTS: During the study timeframe, 577,278 calls for paramedics were received and 413,491 (71.6%) were transported to the ED. Post-pandemic, 9-1-1 calls exceeded predicted pre-pandemic levels by 1,298 per month, while ED transports exceeded by 543 per month. The pandemic significantly reduced monthly 9-1-1 calls (-588.2, 95% CI -928.8 to -247.5) and ED transports (-677.3, 95% CI -927.0 to -427.5). Post-pandemic, there was a significant and sustained resurgence in monthly 9-1-1 calls (1,208.0, 95% CI 822.1 to 1,593.9) and ED transports (868.8, 95% CI 585.8 to 1,151.7). Both models exhibited seasonal variations. CONCLUSIONS: Post-pandemic, 9-1-1-initiated paramedic calls experienced a substantial increase, surpassing pre-pandemic growth rates. ED transports returned to pre-pandemic levels but with a steeper and continuous pattern of growth. The resurgence in paramedic 9-1-1 calls and ED transports post-COVID-19 emphasizes an urgent necessity to expedite development of new care models that address how paramedics respond to 9-1-1 calls and transport to overcrowded EDs.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".