Subscribe to be notified of changes or updates to this page.

4 + 15 =
Solve this simple math problem and enter the result. E.g. for 1+3, enter 4.

PEDSnet is a large, national community of patients, families, clinicians, scientists, and healthcare system leaders who work together in a distributed learning health system (LHS) that is dedicated to discovering and implementing new ways of providing the best care and ensuring the best outcomes most efficiently. PEDSnet’s goal is to conduct research as inexpensively and quickly as possible, while engaging all stakeholders in the research process along the way.

PEDSnet’s eight founding institutions include Children’s Hospital of Philadelphia, Boston Children’s Hospital, Children’s Hospital Colorado, Cincinnati Children’s Hospital Medical Center, Nationwide Children’s Hospital, Nemours Children’s Health System, St. Louis Children’s Hospital, and Seattle Children’s Hospital. CHOP serves as the PEDSnet Coordinating Center and helps to facilitate research projects from all over the country.

PEDSnet is producing reusable and expandable governance, logistical, informatics, regulatory, scientific, and training resources, organized as a Pediatric Research Commons. PEDSnet has ratified important policies that lay the groundwork for the network’s governance. These include a Steering Board Charter, Data Network Policy, and Single Institutional Review Board Policy. PEDSnet institutions have entered into a Use Agreement and are also all participants in the SMART IRB Master Reliance Agreement, which promotes efficiencies in the ethical oversight of a multi-institutional pediatric, clinical research network. Across its eight founding institutions, PEDSnet has created a 10-year, analysis-ready database for more than 6.2 million children.

Research Project Highlights:

PEDSnet has an expanding and diversified research portfolio composed of industry, foundation, and public funding. Below are highlights of PEDSnet studies conducted by researchers from CHOP:

  • PEDSnet Scholars, PI: Christopher Forrest, MD, PhD
    The PEDSnet Scholars K12 career development program will prepare promising junior faculty to conduct learning health system research (LHS) that will improve both care delivery and outcomes for children. It will build upon prior efforts of a multidisciplinary faculty with decades of experience in research mentorship and the resources of eight nationally renowned pediatric academic medical centers that already collaborate in the PEDSnet clinical research network. These scholars will use new methods that leverage modern data systems and test interventions in pragmatic child/family-centered outcomes research studies, embedded in diverse delivery systems and communities. In so doing, they will provide the evidence base for shared clinical decisions and effective delivery system interventions that will bring us closer to the goal of improved health for individual children and populations.
  • Establishing a National Pediatric Glomerular Disease Learning Network, PI: Michelle Denburg, MD, MSCE
    The goal of this study is to create a sustainable and expandable Pediatric Glomerular Disease Learning Network to address fundamental limitations of current observational cohorts and registries and focus on practice pattern variation, observational outcomes and comparative effectiveness research, and ultimately pragmatic clinical trials. This study will develop and validate a computable phenotype for the identification of glomerular disease in PEDSnet, establish a collaborative of nephrologists from the eight participating institutions committed to the creation and maintenance of a Pediatric Glomerular Disease Learning Network, and promote the standardization of data collected in the course of clinical care.
  • PEDSnet Computable Phenotype Project, PI: Charles Bailey, MD, PhD
    The primary objective of the study is to conduct medical record reviews to test the classification accuracy of phenotype algorithms that use EHR data. While this mechanism will be applied to multiple cases going forward, our initial testing will focus on four conditions: univentricular heart disease with Stage 1 Palliation, type 2 diabetes, Crohn’s disease, and glomerular disease.
  • SPARK registry linkage to CHOP EHR data, PI: Charles Bailey, MD, PhD
    This project aims to test the feasibility of linking patients from the SPARK registry and the PEDSnet database, to increase the depth and breadth of phenotype information available to SPARK-based studies. These results will inform decisions about larger-scale efforts to obtain research-ready EHR data from additional PEDSnet sites, and then link, store, and make available these data as part of the SPARK dataset.
  • Inpatient Initiation of Propranolol for Infantile Hemangiomas: A Prospective Cohort Study Utilizing PEDSnet, PI: Jenna Streicher, MD
    The goal of this study is to investigate the prevalence of inpatient admissions for infants 8 weeks of age or under (corrected for prematurity) for propranolol initiation and evaluate the incidence of side effects, specifically bradycardia, hypotension, and hypoglycemia, as compared to infants older than 8 weeks who under current consensus guidelines are initiated on propranolol in the outpatient setting.
  • Advancing Collaborative Pediatric Brain Tumor Research Through Temporally Based Predictive Modeling of a Large Scale National CDRN, PI: Alex Felmeister, MS
    CHOP is a data contributor in addition to one PEDSnet site. This research focuses on the intersection of two national longitudinal health data collection projects: The Children’s Brain Tumor Tissue Consortium (CBTTC) and the PEDSnet Clinical Data Research Network (CDRN) with the intention of harmonizing the two national projects as they grow to aid in the human annotation of biologically based resources with large-scale automated health data networks. The methods in this proposal will use two common observational research methods utilized by two national organizations to develop ways of doing large scale data and system integration for rare and deadly diseases by opening this data to others outside the biomedical domain.