Using EHR Data to Evaluate the Burden of Diabetes Mellitus in a National Network of Children’s Hospital Health Systems
Study Dates
Last Modified
Tags
Publisher
Abstract
Study using electronic health record (EHR) data to assess the prevalence and incidence of pediatric diabetes mellitis (PDM), overall and by diabetes type and patient sociodemographic and clinical characteristics.
Affiliation(s)
Funder(s)
Provenance
Description
Diabetes mellitus is a group of disorders characterized by hyperglycemia resulting from defects in insulin production, insulin action, or both. In children and adolescents 0-17 years-old, pediatric diabetes mellitus (PDM) is one of the more common chronic diseases. Mounting evidence suggests that rates of both Type 1 and 2 diabetes mellitus in children and adolescents have been increasing over the past 30 years. Nonetheless, there has been limited research on how these rates differ by sociodemographics (e.g., race/ethnicity, geography) and clinical characteristics (e.g., body mass index) across diverse regions of the US. To help fill this gap, this study uses electronic health record (EHR) data to assess the prevalence and incidence of PDM, overall and by diabetes type and patient sociodemographic and clinical characteristics. Data will come from PEDSnet, a national pediatric clinical research network that has transformed EHR data to a common data model for over 6.5 million children. PEDSnet includes 8 pediatric medical centers that provide care to children in all 50 states; however, the 11 states with the greatest concentration of children are: CO, DE, FL, IL, IN, KY, MO, NJ, OH, PA, and WA.
Study Aims
In addition to participating in the DiCAYA consortium:
- Evaluate and improve the quality of the EHR data that will be used for identifying patients with PDM. Use PEDSnet’s well-established data quality program that evaluates both structural and semantic data quality and works with institutional data contributors to remediate data quality problems.
- Implement an EHR-based computable phenotype methodology for each type of PDM to support accurate, efficient, and timely surveillance. Implement validated algorithms for identifying children and adolescents with PDM.
- Compute prevalence and incidence rates of PDM, overall and by diabetes type and patient sociodemographic and clinical characteristics. The denominator population will be patients who reside in one of the 62 counties for which PEDSnet has representative data and who have >1 contacts with a PEDSnet institution during the observation period.
Development Code
Vocabulary
Related Publications
Creative Commons license
