A 2-Phase Survey to Assess a Facility's Readiness for Pediatric Essential Emergency and Critical Care in Resource-Limited Settings
Bibliographic record
Abstract
OBJECTIVE: Infectious diseases, including pneumonia, malaria, and diarrheal diseases, are the leading causes of death in children younger than 5 years worldwide. The vast majority of these deaths occur in resource-limited settings where there is significant variation in the availability and type of human, physical, and infrastructural resources. The ability to identity gaps in healthcare systems that may hinder their ability to deliver care is an important step to determining specific interventions for quality improvement. Our study objective was to develop a comprehensive, digital, open-access health facility survey to assess facility readiness to provide pediatric critical care in resource-limited settings (eg, low- and lower middle-income countries). METHODS: A literature review of existing facility assessment tools and global guidelines was conducted to generate a database of survey questions. These were then mapped to one of the following 8 domains: hospital statistics, services offered, operational flow, facility infrastructure, staff and training, medicines and equipment, diagnostic capacity, and quality of clinical care. A 2-phase survey was developed and an iterative review process of the survey was undertaken with 12 experts based in low- and middle-income countries. This was built into the REDCap Mobile Application for electronic data capture. RESULTS: The literature review process yielded 7 facility assessment tools and 7 global guidelines for inclusion. After the iterative review process, the final survey consisted of 11 sections with 457 unique questions in the first phase, "environmental scan," focusing on the infrastructure, availability, and functionality of resources, and 3 sections with 131 unique questions in the second phase, "observation scan," focusing on the level of clinical competency. CONCLUSIONS: A comprehensive 2-phase survey was created to evaluate facility readiness for pediatric critical care. Results will assist hospital administrators and policymakers to determine priority areas for quality improvement, enabling them to implement a Plan-Do-Study-Act cycle to improve care for the critically ill child.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".