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PEDAL: Pediatric Data Science and Analytics

​Group Designation: Subgroup

Group Description

PEDAL is a subgroup of the Pediatric Acute Lung Injury and Sepsis Investigators (PALISI) network with the purpose of connecting the pediatric critical-care medicine community to gain insights and improve care through data science, artificial intelligence, machine learning, and informatics.

Current Research

  • PICU Clinical Decision Support – Use, Knowledge and Perceptions: Clinical decision support systems are designed to provide clinicians or patients with clinical knowledge and patient-related information, at the appropriate time, to enhance patient care (Osheroff 2009). Among intensivists, such systems include both electronic health record (EHR) based tools, such as order sets and alerts, and non-EHR based tools such as clinical pathways and online references. However, broad consensus around the goals and challenges of CDS implementation does not exist among intensivists. This study aims to characterize CDS knowledge and perceptions at multiple institutions. We aim to understand (1) what tools exist and what strategies are used to implement these tools, (2) what CDS goals and concerns are most meaningful to practicing intensivists, and (3) what evaluation processes are in place for these CDS tools. Results will guide framework development for new CDS implementations as well as support intervention studies of effective CDS. (PI: Adam Dziorny, University of Rochester)

  • PICU Data Collaborative – The PICU Data Collaborative is comprised of institutions who contribute anonymized pediatric critical care electronic health record data to a shared data platform which resides in a private cloud-computing environment hosted by the Laura P. and Leland K. Whittier Virtual Pediatric Intensive Care Unit (VPICU) at Children’s Hospital Los Angeles.

  • Data-Driven Sepsis Phenotypes (R21HD096402) – The goals of this study are to: (1) re-calibrate and validate an existing measure of organ dysfunction based on data collected in the electronic health records of critically ill children; (2) analyze the early patterns of organ dysfunction in critically ill children with sepsis to uncover novel phenotypes; and (3) determine whether these phenotypes are associated with different outcomes and response to therapy. This research is being supported by the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) of the National Institutes of Health (NIH).


Twitter:  @PalisiPedal

Connect with pedal

Contact Person: Adam Dziorny

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