Digital phenotyping of CGM engagement reveals distinct glycemic outcomes.

Bowen Zhang^1,2, Tomoki Okuno^1,2, Emma Li³, Ethan Riggins⁴, Evie L Shen⁵, Joleen Vansomphone⁶, Estelle M Everett^7,8, Gregory J Norman⁹, Donald R Miller^10,11, Peter D Reaven², Hua Zhou¹, Jin J Zhou^1,2,8

¹Department of Biostatistics, University of California, Los Angeles, California, United States of America.

²Phoenix VA Health Care System (111E), Phoenix, Arizona, United States of America.

³Castilleja School, Palo Alto, California, United States of America.

⁴Department of Mathematics, University of California, Berkeley, California, United States of America.

⁵Union County Magnet High School, Scotch Plains, New Jersey, United States of America.

⁶Huntington Beach High School, Huntington Beach, California, United States of America.

⁷David Geffen School of Medicine, University of California, Los Angeles, California, United States of America.

⁸VA Greater Los Angeles Health Care, Los Angeles, California, United States of America.

⁹Dexcom, Inc., San Diego, California, United States of America.

¹⁰Department of Biomedical and Nutritional Sciences, University of Massachusetts, Lowell, Massachusetts, United States of America.

¹¹VA Center for Medication Safety, Department of Veterans Affairs, Chicago, Illinois, United States of America.

PubMed DOI

Abstract

Benefits from continuous glucose monitors (CGMs) may depend on how devices are used over time-not only how often they are used. We linked one year of device-generated CGM wear data from 2,351 U.S. Veterans to electronic health records (EHRs) to characterize real-world usage during the first year after CGM initiation. To compare longitudinal use patterns in the presence of unsynchronized sensor rep…

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