1458-P: Challenges for the Diagnostic Classification of Type 1 Diabetes (T1D) among Older Adults in Electronic Health Record (EHR) Data

Abstract

As T1D treatments improve and the US population ages, there is a growing number of older adults (≥65 years) with T1D. This patient population is distinct from their T2D counterparts yet remains understudied. Analyzing routine health care may yield real-world evidence to augment trial data and inform best practices. Yet, it is essential to properly classify patients with T1D vs. T2D. We aimed to assess the extent to which codes for T1D versus T2D overlap in EHR data among older adults with diabetes and assess the implications for identifying older adults with T1D, specifically. We analyzed electronic health record (EHR) data from a large, public health care system in the southeast US, including 12 affiliated hospitals and over 200 academic and community-based practices. We included data from adults ages 65+ years that had at least one code for T1D or T2D. Of the 7,436 patients withT1D or T2D listed among their medical conditions, 7,253 (97.5%) had a diagnostic code for T2D and 895 (12.0%) had a diagnostic code for T1D. Of those with a T1D code, 787 (87.9%) also had at least one T2D code. Among those with a code for T1D, the mean percentage of codes that indicate T1D is 49.4%. There is a high degree of co-occurring T1D and T2D diagnosis codes in EHR profiles of older adults, with implications for clinical care and research. Cohort classification in diabetes-oriented RWE studies warrants further research. Disclosure J.M.Weinstein: Research Support; Dexcom, Inc. R.Muthukkumar: None. L.A.Young: Research Support; Novo Nordisk, Rhythm Pharmaceuticals, Inc., Eli Lilly and Company, Jaeb Center for Health Research, Sanofi, Boehringer-Ingelheim. A.R.Kahkoska: None. Funding National Institutes of Health (KL2TR002490, UL1TR002489)