This study examined the association between change in A1c and CGM data interpretation by health care providers (HCPs) among people with T2D using a personal CGM, stratified by insulin therapy. US administrative claims data for this retrospective analysis were from Optum’s deidentified Clinformatics® Database. Commercially insured people with T2D using any personal CGM with evidence of CGM data interpretation (billing code 95251) between 1/1/2020 and 12/31/2021 (index = earliest observed billing claim) were identified. Those with evidence of professional CGM use (billing code 95250), prior CGM data interpretation, and pregnancy were excluded. Cohorts were stratified by insulin and non-insulin therapy. A1c change was assessed 12 months pre- and post-index date. A total of 2,099 individuals (mean age=54 (SD=10.1) years, 55% male) met inclusion criteria. Across stratified cohorts, two groups were defined as ‘CGM + data interpretation’ and ‘CGM without data interpretation’. Independent of insulin therapy, use of data interpretation by HCPs was associated with a greater decrease in A1c among people with T2D using a personal CGM (Table). These results suggest a significant benefit from incorporation of CGM data interpretation by HCPs. Integration of CGM data interpretation may facilitate collaborative care plan development between patient and HCP.
K. Hannah: Employee; Dexcom, Inc. P. Nemlekar: Employee; Dexcom, Inc. G.J. Norman: Employee; Dexcom, Inc.
