S31 Mapping Hidden Type 3c Diabetes Across the United States

Introduction: Type 3c diabetes (pancreatic diabetes) may comprise 8% of all diabetes cases but remains underdiagnosed. This study develops a novel diagnostic gap methodology integrating pancreatic cancer mortality, diabetes mortality, and pancreatitis prevalence to identify geographic areas with systematic Type 3c diabetes underrecognition. Methods: We conducted a comprehensive analysis integrating CDC WONDER mortality data (2018 to 2023) for pancreatic cancer (ICD-10: C25) and diabetes mellitus (ICD-10: E10-E14) with Global Burden of Disease 2019 prevalence estimates for pancreatitis and diabetes across 51 United States states/territories. A novel diagnostic gap score was calculated as: (pancreatic cancer/diabetes mortality ratio) - (pancreatitis/diabetes prevalence ratio) to identify states with disproportionate pancreatic cancer mortality after controlling for underlying pancreatic disease burden. Results: Analysis included 283,255 pancreatic cancer deaths, 574,474 diabetes deaths (CDC WONDER), and state-level prevalence data for 6.6 million pancreatitis cases and 166 million diabetes cases (Global Burden of Disease 2019). Diagnostic gap scores varied significantly from 28.1% to 71.4% (mean: 48.2%, SD: 9.4%, CV: 19.5%). Five states showed statistically significant underdiagnosis (gap score >62.3%): Connecticut (71.4%), Massachusetts (70.3%), Vermont (66.1%), New Jersey (63.8%), and Hawaii (63.5%). Three states demonstrated superior recognition (gap score <34.1%): West Virginia (28.1%), Arkansas (32.0%), and New Mexico (33.6%). The diagnostic gap score methodology controls for underlying pancreatic disease burden, providing more precise identification of diagnostic disparities than mortality ratios alone. Conclusion: A novel diagnostic gap score reveals significant geographic disparities in Type 3c diabetes recognition. Five states (Connecticut, Massachusetts, Vermont, New Jersey, Hawaii) show marked underdiagnosis, while 3 (West Virginia, Arkansas, New Mexico) demonstrate better diagnostic alignment. These findings highlight Northeast states as priority targets for intervention and offer a framework for tracking diagnostic quality. Future studies should validate this methodology using electronic health record data and investigate targeted provider education interventions in high-gap states.