Evaluation of attitudes and perceptions of key clinical stakeholders regarding out-of-hospital diagnosis and treatment of ST elevation myocardial infarction patients using a region-wide survey
Bibliographic record
Abstract
INTRODUCTION: In ST elevation myocardial infarction (STEMI), prehospital management (PHM) may improve clinical outcomes through a reduction in reperfusion delay. The purpose of this study was to evaluate perceptions among healthcare stakeholder groups relating to the barriers and facilitators of implementing a PHM programme. METHODS: A 25-question cross-sectional survey, using a four-point Likert scale assessing barriers and facilitators of PHM, was distributed to paramedics, cardiologists, emergency physicians and emergency nurses within the Edmonton region, where prehospital STEMI treatment is established. The proportion of responses on each question was compared and differences between groups were determined using chi(2) and Fisher's exact tests. RESULTS: 57% (355/619) of subjects responded: 69% paramedics, 50% cardiologists, 54% emergency physicians and 45% emergency nurses. A majority believed PHM reduced treatment delays in both rural (96-100%) and urban (86-96%) areas, while decreasing patient mortality (paramedics 97%, cardiologists 74%, emergency physicians 85%, emergency nurses 88%). Regarding the capability of paramedics to deliver PHM, paramedics 25%, cardiologists 33%, emergency physicians 67%, and emergency nurses 47% stated that urban paramedics are better equipped and trained than rural paramedics. Although 81% of paramedics supported the possibility of PHM delivery without physician overview, 0% of cardiologists, 98% of emergency physicians and 95% emergency nurses agreed. A majority (71-88%) favoured mandatory signed informed consent. CONCLUSIONS: While stakeholders agreed on the benefits of PHM, perceptual differences existed on paramedics' ability to deliver PHM without physician overview. Addressing real and perceived barriers through communication and educational programmes may enhance PHM within this healthcare region and facilitate the implementation of PHM programmes.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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 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".