Advancing Surveillance of Congenital Heart Defects: Using Unparalleled Informatics and Data Science to Improve the Health of Children, Adolescents, and Adults
| Start Date: 9/30/2024
End Date: 9/29/2029 |
Funder: |
To better understand the magnitude and burden of CHD in Indiana, this project uses population-based surveillance approaches to: (1) employ available methods for identification of CHD cases among children, adolescents, and adults living in Indiana; (2) integrate comprehensive clinical and administrative data on individuals with CHD; (3) utilize integrated data to measure outcomes for individuals with CHD; and (4) train a machine learning model to more accurately identify CHD cases. Under Component A, we will use multiple data sources, including the Indiana Birth Defects and Problems Registry (IBDPR), vital records, immunization registry records, and electronic health records (EHRs) to identify CHD cases and build an integrated database of relevant information for surveillance of prevalence and outcomes. Under Component B, we will train and refine a machine learning algorithm that accurately identifies CHD in the EHR, including cases of mild-to-moderate CHD, which are often omitted from surveillance.
