362 Group Model Building to characterize the experiences of older adults with type 1 diabetes (T1D) with continuous glucose monitoring (CGM) therapy and uncover suboptimal response patterns. (April 2022)

• Record Type: Journal Article
• Authors: Kahkoska, Anna R; Batsis, John A.; Kosorok, Michael R.; Mayer-Davis, Elizabeth J.; Pratley, Richard; Weinstock, Ruth; Young, Laura A.; Lich, Kristen Hassmiller
• Is Part Of: Journal of clinical and translational science. Volume 6(2022)Supplement 1
• Page Start: 67
• Page End: 67
• Publication Date: 2022-04
• Subjects: Clinical medicine -- Research -- Periodicals; Medicine, Experimental -- Periodicals; Human experimentation in medicine -- Periodicals; 616.027
• DOI: 10.1017/cts.2022.205
• Languages: English
• ISSNs: 2059-8661

Abstract

Abstract : OBJECTIVES/GOALS: As the number of older adults (≥65 years) with T1D grows, there are limited data to guide care. In a six-month trial, CGM reduced hypoglycemia in older adults, yet there are challenges for widespread uptake. Our objective is to characterize older adults experiences with using CGM and define suboptimal responses signaling a need for resources or support. METHODS/STUDY POPULATION: The study will engage key stakeholders (i.e., older adults with T1D, caregivers [recruited as patient-caregiver dyads], and providers [endocrinologists, geriatricians, diabetes educators]) for a Group Model Building (GMB). GMB is a participatory approach to system dynamics in which participants share perceptions and experiences with a problem and collaboratively explore the system structure that shapes those trends. A series of 8 GMB workshops will be held with 3-8 participants. The final study n will be determined by thematic saturation. Workshops comprise 1) a questionnaire, 2) a GMB session, and 3) a focus group discussion. GMB will follow a replicable process to generate a model of the complex web of causal determinants affecting CGM-related experiences, including optimal and suboptimal CGM responses. RESULTS/ANTICIPATED RESULTS: To date, the study has enrolled 33 participants, including 28 older adults living with T1D and 5 caregivers (mean age = 74 years, range 67-83 years). Twenty-four patient participants will be active CGM users and 4 will be CGM non-users. The study will report on patient data capture from the questionnaire and EMR, including demographics, experiences, familiarity, and confidence surrounding CGM use; diabetes duration; insulin pump use; history of severe hypoglycemia. Analysis of aggregated data will generate causal loop diagrams that integrate pertinent theoretical frameworks, lived experiences, and CGM outcomes. Maps will be used to identify a set of suboptimal CGM responses (i.e., key outcome trajectories) that signal a need for action, with a diagram of factors that interact to produce each response. DISCUSSION/SIGNIFICANCE: Delivering CGM to older adults with T1D demands new approaches. This study will yield critical evidence to tailor support and resources for effective CGM use in older adults. Findings may be translated into suite of pragmatic interventions to bolster CGM use and matched to individual patients expected to benefit using a precision medicine framework.