A Call for Collaboration: Knowledge Dissemination to Improve the Emergency Care of Children
Bibliographic record
Abstract
To the Editor: Most children seeking emergency care are evaluated and treated in general emergency departments (EDs) that are not pediatric focused. Data from the 2013 Pediatric Readiness Survey have shown that many general EDs are not prepared to treat pediatric patients and that critically ill patients treated in ED with low readiness scores have a higher mortality.1 General EDs and nonpediatric hospitals often lack the equipment and expertise to implement treatment plans according to the latest pediatric guidelines and procedures. Furthermore, they are often located in hospitals without pediatric inpatient capabilities, resulting in transfers and delayed care.2 The well-documented 17-year lag between bench to bedside directly impacts patient outcomes. The Pediatric Emergency Care Applied Research Network (PECARN) has been conducting impactful research in pediatric emergency medicine for almost 20 years.3 The information garnered from their research endeavors has been an available resource to practitioners and patient families. However, the network acknowledges that the future challenge is disseminating and implementing those research findings into emergency medicine practice.3 One major barrier to knowledge dissemination and implementation is the lack of communication and collaboration between researchers and clinicians. The findings of research conducted in academic medical centers rather than in community settings are less likely to be adopted by physicians in their daily practice, including emergency medicine providers.4 Researchers may not have considered practical issues such as varied practice settings and differing knowledge bases and experiences of the practitioners tasked with implementing new evidence-based care. Knowledge dissemination frameworks take into consideration the knowledge generated, who will utilize the knowledge, how will the knowledge be utilized, and how will it impact patient care. Translating Emergency Knowledge for Kids (TREKK), an initiative by the Pediatric Emergency Research Canada (PERC), has had success in pediatric emergency medicine knowledge dissemination. TREKK has been successful in creating collaboration among PERC research centers and general EDs across Canada to determine knowledge needs and create resources to optimize patient care.5 As the collection of high-impact pediatric emergency medicine evidence grows, research networks in the United States are uniquely situated to lead knowledge dissemination efforts. Formalizing a collaboration between dedicated clinicians, researchers, content experts, professional societies, and clinical leaders from varied practice settings is the most appropriate next step. This collaboration will lead to utilization of research findings for the emergency care of children, regardless of the clinical setting. Attending periodic meetings, involvement in telehealth and simulation exercises, creating newsletters for circulation, and developing tools or mobile apps are some of the potential products of this collaboration. Knowledge dissemination and implementation will improve access to timely, evidence-based guidelines and treatment decision tools to ensure the best outcomes during the emergency care of children.
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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 | 0.088 | 0.368 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.013 | 0.021 |
| Open science | 0.007 | 0.014 |
| Research integrity | 0.034 | 0.029 |
| Insufficient payload (model declined to judge) | 0.023 | 0.005 |
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".