Closing the Loop
Bibliographic record
Abstract
OBJECTIVES: Providing emergency care to acutely ill or injured children is stressful and requires a high level of training. Paramedics who provide prehospital care are typically not involved in the circle of care and do not receive patient outcome information. The aim of this quality improvement project was to assess paramedics' perceptions of standardized outcome letters pertaining to acute pediatric patients that they had treated and transported to an emergency department. METHODS: Between December 2019 and December 2020, 888 outcome letters were distributed to paramedics who provided care for 370 acute pediatric patients transported to the Children's Hospital of Eastern Ontario in Ottawa, Canada. All paramedics who received a letter (n = 470) were invited to participate in a survey that collected their perceptions and feedback about the letters, as well as their demographic information. RESULTS: The response rate was 37% (172/470). Approximately half of the respondents were Primary Care Paramedics and half Advanced Care Paramedics. The respondents' median age was 36 years, median years of service was 12 years, and 64% identified as male. Most agreed that the outcome letters contained information pertinent to their practice (91%), allowed them to reflect on care they had provided (87%), and confirmed clinical suspicions (93%). Respondents indicated that they found the letters useful for 3 reasons: 1) increases capacity to link differential diagnoses, prehospital care, or patient outcomes; 2) contributes to a culture of continuous learning and improvement; and 3) gives closure, reduces stress, or provides answers for difficult cases. Suggestions for improvement included providing more information, provision of letters on all patients transported, faster turnaround time between call and receipt of letter and inclusion of recommendations or interventions/assessments. CONCLUSIONS: Paramedics appreciated receiving hospital-based patient outcome information after their provision of care and reported that the letters offered opportunities for closure, reflection, and learning.
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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 | 0.008 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.448 | 0.227 |
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".