The current state of paediatric publishing utilising high-fidelity physiologic data streaming with sickbay or...

Area of Science:

• Biomedical Informatics
• Pediatric Critical Care
• Health Technology Research

Background:

• Physiologic data streaming and aggregation platforms (Sickbay®, Etiometry) are increasingly adopted in pediatric acute care.
• This adoption has spurred a parallel increase in scholarly research interest.
• Understanding research trends is crucial for evaluating the impact and future direction of these technologies.

Purpose of the Study:

• To characterize research productivity and trends in the use of Sickbay® or Etiometry platforms.
• To analyze the landscape of publications utilizing high-fidelity physiologic streaming data in pediatric acute care.
• To identify key characteristics and trends of research in this domain.

Main Methods:

• Systematic literature review to identify relevant pediatric publications.
• Analysis of identified publications to characterize research trends, author contributions, and institutional involvement.
• Categorization of studies based on platform used, patient population, study design, and methodology (e.g., AI/ML).

Main Results:

• A total of 41 publications were identified over a 9-year period.
• Research involved 179 authors from 21 institutions, with a significant increase in publication volume over time.
• The majority of studies utilized Sickbay®, focused on cardiac patients, were single-center, and did not employ machine learning or artificial intelligence.

Conclusions:

• Publication volume demonstrates a growing utilization of high-fidelity physiologic data in pediatric acute care.
• Current research predominantly focuses on single-center studies, often involving cardiac patients.
• Increased multicenter collaboration could enhance research capacity and drive clinical care improvements.