914-P: The Impact of Racial and Ethnic Health Disparities in Diabetes Management on Clinical Outcomes: A Reinforcement Learning Analysis of Health Inequity

It is not known how racial/ethnic disparities in pediatric type 1 diabetes (T1D) treatment regimens contribute to the disparate clinical outcomes across racial/ethnic subgroups. Data were analyzed from the SEARCH for Diabetes in Youth study (diagnosed 2002-2005, 47.5% female, 77.5% non-Hispanic white (NHW), mean age at diagnosis=12.8±2.4 years). Youth were classified as nonwhite race/Hispanic ethnicity (nonwhite youth) or NHW race (white youth). Multivariate propensity scores estimated T1D treatment regimens (i.e., insulin delivery and glucose monitoring modality) in white versus nonwhite subgroups. Reinforcement learning, a machine learning technique, estimated the effect of each treatment regimen on HbA1c over time for nonwhite youth. Observed mean HbA1c over available visits for each individual was 9.0% and 8.2% for the nonwhite and white subgroups, respectively, difference=0.8%. Estimated mean HbA1c decreased by 0.33% (95%CI: -0.45%, -0.21%; p Disclosure A. Kahkoska: Other Relationship; Self; Novo Nordisk A/S. A. K. Mottl: Advisory Panel; Self; Bayer U. S. C. Pihoker: None. S. Saydah: None. M. R. Kosorok: None. E. J. Mayer-davis: None. T. Pokaprakarn: None. G. Alexander: None. T. L. Crume: None. D. Dabelea: None. J. Divers: None. L. M. Dolan: None. E. T. Jensen: None. S. M. Marcovina: None. Funding National Institutes of Health (1UC4DK108173, F30DK113728); Centers for Disease Control and Prevention (00097, DP-05-069, DP-10-001)