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Collaboration Around Technology Using Community Health Workers in Type 1 Diabetes (CATCH-T1D): Protocol and
Shivani Agarwal1,2, Molly Finnan1, Kevin P Fiori3,4,5
1Fleischer Institute of Diabetes and Metabolism, Montefiore Medical Center-Albert Einstein College of Medicine, Bronx, New York, USA.
Background:
Diabetes technology use in Type 1 diabetes (T1D) is the standard of care given broad biological and psychosocial benefits. Hispanic and Non-Hispanic Black young adults are the fastest-growing demographic with T1D in the United States and face inequity in technology use, leading to poor outcomes. We explored whether community health workers (CHWs) could coaddress unmet social needs and navigation of T1D technology to improve standard of care and outcomes in this high-risk population.
Methods:
The collaboration around technology using community health workers in Type 1 diabetes (CATCH-T1D) intervention enhances the CHW model by integrating social needs management with T1D technology navigation. CHWs trained at the Montefiore-Einstein CHW Institute navigate YA with T1D to technology by offering information access, shared decision-making, and health system-pharmacy coordination. We are performing an ongoing trial testing CATCH-T1D against usual care using a 9-month hybrid effectiveness-implementation design for 130 Hispanic and/or non-Hispanic Black young adults (18-35 years) with T1D at Montefiore Medical Center in the Bronx.
Results:
One hundred and eighteen participants have been randomized (48% F, 67% Hispanic, 72% Medicaid, mean HbA1c: 9.2%). Thus far, CHWs have conducted 476 follow-up encounters and resolved 24% of identified health-related social needs. Postintervention interviews showed high participant satisfaction and increased engagement with diabetes self-management due to CHWs' flexible communication, support with diabetes technology, and assistance with social needs, fostering trust in the healthcare system.
Discussion:
CATCH-T1D is a specialized CHW model that simultaneously addresses social needs and navigation to diabetes technology, with potential to provide a new scalable model of care.
