Knowledge, Awareness, and Understanding of Pediatric Triage Among Nursing Officers in India: A Multicenter Study
Bibliographic record
Abstract
INTRODUCTION: Triage is crucial in patient screening within emergency departments (EDs) worldwide. It is one of the essential and standard medical practices in many developed countries. However, in India, there is a need for improvement in triage utilization, as it is predominantly performed by resident doctors or medical officers, leading to an uneven distribution of clinical skills among healthcare providers (HCPs). A comprehensive analysis incorporating literature review and data collection revealed that while mandatory screening is conducted in most Indian EDs, the formal implementation of standardized triage protocols remains limited. Like in developed countries, registered nurses or nursing officers (NOs) can be effectively trained and directed to play the role of dedicated triage personnel in EDs of most of the healthcare facilities in India. METHOD AND MATERIALS: This study aimed to examine the current state of triage utilization and its impact on the distribution of responsibilities among HCPs in Indian EDs. Through this online survey, the investigators assessed the knowledge and practical understanding of clinical triaging among NOs, working at various hospitals nationwide. RESULTS: The participants included 5,029 NOs working in various parts of India, predominantly nursing graduates (82.52%), the majority being employed in government healthcare settings (84.01%) and most having over five years of cumulative working experience in the ED (70.77%). Nurses showed inadequate knowledge and awareness about the Pediatric Assessment Triangle (PAT) used for quick initial evaluation (62.18% among all participants). Concerning the complete triage process applicable, especially in pediatric ED settings, they had even less satisfactory knowledge and understanding, e.g., identifying primary (28.27%) and secondary (22.69%) survey components via focused history and examination, properly using temperature assessment (23.32%) and instant blood glucose level assessment (22.95%) in triage, and knowing various types of internationally accepted triage systems for ED-based health facilities such as the Emergency Severity Index (ESI), Canadian Triage and Acuity Scale (CTAS), and Australasian Triage Scale (ATS) (15.87%). ANOVA and post hoc analysis revealed that the intergroup performance of the study participants with maximum correct responses to the knowledge-determining specified subset of the questionnaire depicts the significantly higher role of graduate nursing degree over diploma such as General Nursing and Midwifery (GNM)/Auxiliary Nursing and Midwifery (ANM) qualification, working in government hospital versus private setup, and ED working experience of >5 years over that of <5 years. CONCLUSIONS: Of the participants in the study, 50% were not evaluated for cognitive or psychomotor domains during their assessment examinations. The research illuminated a significant disparity in knowledge and proficiency levels among Indian nurses concerning pediatric triage, especially with the ability to effectively apply the PAT for initial patient evaluations, discern components of primary and secondary surveys, and comprehend various triage systems. This study underscores the importance of comprehensive reform in the Indian healthcare system and teaching curriculum by emphasizing clinical triage training and interprofessional collaboration, and establishing guidelines and regulations to ensure consistent and standardized triage practices across all EDs.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".