This 4-module continuing education program provides best practice guidance for optimizing the health of individuals at-risk and living with gestational diabetes mellitus (GDM).

 2 CME  2 ACPE  2 ANCC  2 AAPA  2 CDR  2 COP

This activity will address evidence-based, peer-reviewed clinical data and expert opinion on quality diabetes management.

 1 CME  1 ACPE  1 ANCC  1 AAPA  1 CDR  1 COP

Recorded Webinar

In this webinar, panelists discuss the disparities disproportionately affecting Black birthing individuals and provide solutions to address risks and disparities associated with GDM.

 1 CME  1 ABIM-MOC  1 ACPE  1 ANCC  1 CDR  1 COP

 1.5 CME  1.5 ABIM-MOC  1.5 ACPE  1.5 ANCC  1.5 AAPA  1.5 CDR  1.5 COP

This webinar discusses current best practices in treating diabetes during pregnancy. Participants will have the opportunity to hear both the U.S and European approaches to incorporating continuous glucose monitoring (CGM) and time in range (TIR) to achieve therapeutic goals.

 No Credit

Recorded Webinar

In this webinar, speakers discuss key findings from their recent study which assessed the predictive performance of A1C, continuous glucose monitor (CGM) metrics such as time in range, and alternative biochemical markers of glycemia in predicting obstetric and neonatal outcomes.

 No Credit

Recorded Webinars

This three-part series will explore the complexities of GDM, from preconception risk management and early detection to optimizing care during pregnancy and continuing through postpartum support.

 1.5 CME  1.5 ABIM-MOC  1.5 ACPE  1.5 ANCC  1.5 AAPA  1.5 CDR  1.5 COP

Recorded Webinar 

In this webinar, representatives from the NIH and the ADA present and participate in a panel discussion on the topic of funding for diabetes in pregnancy-related research. We discuss funding for both gestational diabetes and pre-existing diabetes (of all types) in pregnancy. In the interactive portion of the session, the panel takes questions from the moderators and participants. 

 No Credit

Recorded Webinar

In this webinar, we will discuss the potential of applying AI in screening articles for systematic reviews and how that can help with addressing the labor-intensiveness of conducting systematic reviews.

 No Credit