Once a relatively rare occurrence, the incidence rates of type 2 diabetes among children and adolescents continues to increase (SEARCH). In adults, oral hyperglycemic agents in conjunction with diet and exercise is an important treatment option used to control blood sugar and minimize long-term complications of the disease. However, there are relatively few approved medication treatment options available treatment of 2 diabetes in children.
Conducting clinical trials in children is difficult and take many years to complete. Real world data can be used as a representative sample to assess clinical trial feasibility. Specifically, facets of clinical data derived from standard care that approximate individual criteria from the protocol can be examined to estimate the pool of eligible patients, and to identify protocol criteria that may deter enrollment.
The purpose of this project was to assess feasibility of using a data network to accelerate trial feasibility by being able to quickly screen and identify potential eligible patients with type 2 diabetes in the pediatric population.
The study objectives are to:
Understand how the pediatric diabetes population is coded in PEDSnet’s EHR-based core data
Understand how inclusion and exclusion criteria can be applied to the pediatric T2DM population
Understand the gaps in core data coverage as it relates to criteria in the protocol
Understand the impact of various changes in screening algorithm on identification of the index population