Common data elements for predictors of pediatric sepsis: A framework to standardize data collection

Area of Science:

• Pediatric critical care
• Epidemiology
• Health informatics

Background:

• Pediatric sepsis prediction requires standardized data collection for research compatibility.
• Resource-limited settings face challenges in collecting reliable sepsis predictor data.

Purpose of the Study:

• To define common data elements for pediatric sepsis predictors at triage.
• To establish a standardized framework for data collection in resource-limited settings.

Main Methods:

• Systematic literature review and guideline examination to identify potential predictors.
• A 5-round modified Delphi process involving voting and discussion to select, standardize, and prioritize predictors.
• Consideration of predictive value, reliability, and resource requirements for data collection.

Main Results:

• 116 common data elements were generated, including standardized prompts, response values, and prioritization tiers.
• Branching logic was incorporated for efficient data collection, supporting mobile applications.
• The data elements are publicly available, with a feedback mechanism for future updates.

Conclusions:

• Routine use of these elements will enable data sharing and the development of robust risk prediction algorithms.
• These algorithms can support clinical decision-making at triage in resource-limited areas.
• Ongoing community feedback is crucial for maintaining the applicability of these elements across diverse settings.