William H Polonsky1,2, Addie L Fortmann3. 1. Behavioral Diabetes Institute, San Diego, California. 2. Department of Medicine, University of California, San Diego, California. 3. Scripps Whittier Diabetes Institute, Scripps Health, La Jolla, California, USA.
Abstract
Background: To examine experiences with real-time continuous glucose monitoring (RT-CGM) data sharing and its impact on health-related outcomes. Methods: Adults with type 1 diabetes (T1D) (N = 302) using the Dexcom G5 Mobile or G6 RT-CGM system and sharing data with ≥1 family/friend follower completed a survey exploring their perceived value of data sharing, the impact of sharing on health and quality of life (QoL) outcomes, and how their chief follower (CF) used shared data to support their diabetes management. Regression analyses examined whether CF actions were linked to reported changes in health and QoL outcomes for the T1D adult. Results: The majority had lived with T1D >10 years, (76.5%), used RT-CGM >1 year (58.0%), and identified their spouse/partner as CF (51.9%). Data sharing reportedly contributed to improved hypoglycemic confidence (for 89.4% of respondents), improved overall well-being (54.3%), and reduced diabetes distress (36.1%). Benefits related to data sharing included fewer episodes of severe hypoglycemia (62.2%), better sleep (52.4%), and A1C improvement (47.3%). In particular, three positive CF actions were independent predictors of health and QoL benefits: celebrating success related to glycemic control, providing encouragement when glycemic control is challenging, and teamwork discussions about how CF should respond to out-of-range values. Conclusions: RT-CGM data sharing was associated with a range of health and QoL-related benefits. The occurrence of benefits was influenced by the collaborative management approaches taken by RT-CGM users and their data-sharing followers. Longitudinal trials are needed to determine the most effective patterns of collaborative data sharing, leading to their implementation into routine diabetes management.
Background: To examine experiences with real-time continuous glucose monitoring (RT-CGM) data sharing and its impact on health-related outcomes. Methods: Adults with type 1 diabetes (T1D) (N = 302) using the Dexcom G5 Mobile or G6 RT-CGM system and sharing data with ≥1 family/friend follower completed a survey exploring their perceived value of data sharing, the impact of sharing on health and quality of life (QoL) outcomes, and how their chief follower (CF) used shared data to support their diabetes management. Regression analyses examined whether CF actions were linked to reported changes in health and QoL outcomes for the T1D adult. Results: The majority had lived with T1D >10 years, (76.5%), used RT-CGM >1 year (58.0%), and identified their spouse/partner as CF (51.9%). Data sharing reportedly contributed to improved hypoglycemic confidence (for 89.4% of respondents), improved overall well-being (54.3%), and reduced diabetes distress (36.1%). Benefits related to data sharing included fewer episodes of severe hypoglycemia (62.2%), better sleep (52.4%), and A1C improvement (47.3%). In particular, three positive CF actions were independent predictors of health and QoL benefits: celebrating success related to glycemic control, providing encouragement when glycemic control is challenging, and teamwork discussions about how CF should respond to out-of-range values. Conclusions: RT-CGM data sharing was associated with a range of health and QoL-related benefits. The occurrence of benefits was influenced by the collaborative management approaches taken by RT-CGM users and their data-sharing followers. Longitudinal trials are needed to determine the most effective patterns of collaborative data sharing, leading to their implementation into routine diabetes management.
Entities:
Keywords:
Continuous glucose monitoring; Data sharing; Quality of life; Type 1 diabetes
Authors: Korey K Hood; Lori M Laffel; Thomas Danne; Revital Nimri; Stuart A Weinzimer; Judy Sibayan; Ryan J Bailey; Desmond Schatz; Natasa Bratina; Rachel Bello; Alina Punel; Peter Calhoun; Roy W Beck; Richard M Bergenstal; Moshe Phillip Journal: Diabetes Technol Ther Date: 2021-10-26 Impact factor: 6.118