Exploring paramedic perspectives on emergency medical service (EMS) delivery in Alberta: a qualitative study
Bibliographic record
Abstract
PURPOSE: Emergency Medical Services (EMS) in Alberta are facing critical challenges. This qualitative study aims to describe and understand the frontline perspective regarding system level issues and propose provider-informed policy recommendations. METHODS: 19 semi-structured one-on- one interviews were conducted with Primary or Advanced Care Paramedics (PCP/ACP) across Alberta. Participants were asked to share their perspectives, experiences and recommendations in relation to EMS response times and the working environment. Interviews were analyzed using thematic analysis to identify themes and subthemes. RESULTS: Two core themes were identified as areas of concern: poor response times and the EMS working environment, which each influence and impact the other. Within response times, paramedics highlighted specific difficulties with ED offloading, a lack of resources, low-acuity calls, and rural challenges. In terms of the EMS working environment, four subthemes were apparent including attrition, unhealthy culture, organizational barriers and the need for paramedic empowerment. Providers made many recommendations including creating and expanding emergency mobile integrated health (MIH) branches, sharing 811 and 911 responses, and enforcing ED target offload times amongst other suggestions. CONCLUSIONS: While response times are a key and highly visible problem, there are many critical factors like the EMS working environment that degrade patient care and cause concern amongst frontline practitioners. Multifaceted policy changes are to be explored to reduce disfunction within EMS services, enhance the well-being of the workforce and deliver improved patient care. Specific EMS-oriented policies are important for moving forward to reduce transfers to EDs, but the broader health system which is over capacity is causing downstream effects into EMS must be addressed by government and health administrators.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.011 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".