Barriers to Self-Reporting Patient Safety Incidents by Paramedics: A Mixed Methods Study
Bibliographic record
Abstract
BACKGROUND: A minimal amount of research exists examining the extent to which patient safety events occur within paramedicine and even fewer studies investigating patient safety systems for self-reporting by paramedics. The purpose of this study was to identify barriers to paramedic self-reporting of patient safety incidents (PSIs). METHODS: We randomly distributed paper-based surveys among 1,153 paramedics in an Ontario region in Canada. The survey described one of 5 different PSI clinical scenarios (near miss, adverse event, and minor, major or critical patient care variances) and listed 18 potential barriers to self-reporting PSIs as statements presented for rating on a 5-point Likert scale (very significant = 1 - very insignificant = 5). We invited comments on PSI self-reporting with 2 open-ended questions. We analyzed data with descriptive statistics, chi-square tests and Kruskal-Wallis H test. We used an inductive approach to qualitatively analyze emerging themes. RESULTS: We received responses from 1,133 paramedics (98.3%). Almost one third (28.4%) were Advanced Care Paramedics and 45.1% had >10 years' experience. The top 5 barriers to PSI self-reporting (very significant or significant, %) were the fear of being: punished (81.4%), suspended (79.6%), terminated (79.1%), investigated by Ministry of Health and Long-Term Care (78.4%), and decertified (78.0%). Overall, 64.1% responded they would self-report a given PSI. Intention to self-report a PSI varied according to scenario (22.8% near miss, 46.6% adverse event, 74.4% minor, 92.6% major, 95.6% critical). No association was found between level of training (p = 0.55) or years of experience (p = 0.10) and intention to self-report a PSI. Seven themes to improve PSI self-reporting by paramedics emerged from the qualitative data. CONCLUSIONS: A high proportion of fear-based barriers to self-reporting of PSIs exist among this study population. This suggests that a culture change is needed to facilitate the identification of future patient safety threats.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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 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".