Emergency Medical and Health Providers' Perceptions of Key Issues in Prehospital Patient Safety
Bibliographic record
Abstract
OBJECTIVES: To date, most patient safety studies have been conducted in relation to the hospital rather than the prehospital setting and data regarding emergency medical services (EMS)-related errors are limited. To address this gap, a study was conducted to gain an in-depth understanding of the views of highly experienced EMS practitioners, educators, administrators, and physicians on major issues pertaining to EMS patient safety. The intent of the study was to identify key issues to give direction to the development of best practices in education, policy, and fieldwork. METHODS: A qualitative study was conducted using processes described by Lincoln and Guba (1985) to enhance the quality and credibility of data and analysis. Purposive sampling was used to identify informants with knowledge and expertise regarding policy, practice, and research who could speak to the issue of patient safety. Sixteen participants, the majority of whom were Canadian, participated in in-depth interviews. RESULTS: Two major themes were identified under the category of key issues: clinical decision making and EMS's focus and relationship with health care. An education gap has developed in EMS, and there is tension between the traditional stabilize-and-transport role and the increasingly complex role that has come about through "scope creep." If, as expected, EMS aligns increasingly with the health sector, then change is needed in the EMS educational structure and process to develop stronger clinical decision-making skills. CONCLUSION: The results of this study indicate that many individual organizations and health regions are addressing issues related to patient safety in EMS, and there are important lessons to be learned from these groups. The broader issues identified, however, are system-wide and best addressed through policy change from health regions and government.
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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 | 0.013 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".