Telementoring With Project ECHO: A New Era in Diabetes-Related Continuing Education for Primary Care to Address Health Disparities

Abstract

Project ECHO® is a telementoring workforce development model that targets under-resourced communities lacking access to specialty care. The model builds virtual communities of practice, including specialists and community primary care professionals (PCPs) to combat clinical inertia and health disparities. While the ECHO model has gained global recognition, implementation of the model related to diabetes is lagging compared to other specialty conditions. This review highlights diabetes-endocrine (ENDO)-focused ECHOs using data reported in the ECHO Institute’s centralized data repository (iECHO) and the learning collaborative for diabetes ECHOs. It also describes the implementation of diabetes ECHOs and their evaluation. Learner and patient-centered outcomes related to diabetes ECHOs are reviewed. Program implementation and evaluations have demonstrated utility of the ECHO model for diabetes programs to (1) address unmet needs of diabetes care in the primary care setting, (2) improve knowledge and confidence in managing complex diabetes and change provider prescribing habits, (3) improve patient outcomes, and (4) address diabetes quality improvement practices in primary care. More studies with broader collaboration among sites are needed to evaluate the model related to diabetes, especially applied to addressing therapeutic inertia, adoption of diabetes technology, and reducing health disparities.

Technology and health inequities in diabetes care: How do we widen access to underserved populations and utilize technology to improve outcomes for all?

“…The diabetes ECHO tele‐mentoring programmes have been shown to improve primary care clinician knowledge and confidence in managing diabetes. Patients treated by ECHO‐trained physicians were more likely to have an HbA1c concentration less than 64 mmol/mol (8%) than those who were not 33 . Going forward, advances in the application of machine learning and artificial intelligence to support remote patient monitoring have the potential for identification of high‐risk patients for targeted intervention and may serve as a mechanism by which to reduce inequities in health outcomes.…”

“…Patients treated by ECHO-trained physicians were more likely to have an HbA1c concentration less than 64 mmol/mol (8%) than those who were not. 33 Going forward, advances in the application of machine learning and artificial intelligence to support remote patient monitoring have the potential for identification of high-risk patients for targeted intervention and may serve as a mechanism by which to reduce inequities in health outcomes. Recommendation: Tele-mentoring should be considered as a means to upskill clinicians involved in diabetes care.…”