31 Experience of ambulance workers, nurses and doctors of handover of patients who are transported by ambulances to emergency departments in iceland: a qualitative interview study
Bibliographic record
Abstract
Background Adverse events healthcare are often caused by communication failure. Patient handover from ambulance personnel to specialized nurses and doctors in Emergency Departments carries the risk that that important information will be lost during the process, with consequences that may adversely affect patient well-being. The objective of this qualitative study was to analyze communication and transfer of responsibility during handover of patients arriving with ambulances in Emergency Departments in Iceland. Method Vancouver school method of phenomenology was used. Participants were selected with a purpose sampling. Semi-structured individual interviews were conducted and supported by interview guide. The interviews were themed, followed by construction of an individual analysis model and overall analysis model. Results A total of 17 ambulance workers, registered nurses and doctors described their experience of a patient handover in Emergency Department and the process of exchange of written and verbal information between health professionals involved in the handover of care. The main finding of the study was that structured communication and information disclosure have a great impact on the quality of patient handover. This is described in four main themes (Transfer of professional responsibility; Information dialogue; Personal and professional factors and Organizational factors) and nine sub-themes. Conclusion Standardized handover protocol, clear procedures and education to healthcare professionals can potentially improve communication and transfer of responsibility for patients brought to emergency departments with ambulances, thus potentially improving patient safety. Conflict of interest None. Funding None.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".