

OBJECTIVE The objective of this study was to develop and internally validate a mathematical model of the relationships between patient clinical and social risk factors and outcomes using data from a multiethnic population with type 2 diabetes. RESEARCH DESIGN AND METHODS We constructed an incidence cohort of all adults (18 years or older) with newly diagnosed type 2 diabetes in the Kaiser Permanente Northern California (KPNC) health care system between 2005 and 2016 ( n = 129,000), following patients for at least 1 year, but up to 12 years. Using this cohort, we modeled 17 distinct diabetes-related outcomes related to micro- and macrovascular disease, as well as atrial fibrillation, depression, dementia, relevant biomarkers, and mortality. RESULTS Data were randomly split into 50%, 25%, and 25% samples to perform model estimation, calibration, and validation, respectively. Empirical and simulated data were similar for the events and biomarkers, but some factors required calibration. After calibration, they closely aligned with empirical estimates. CONCLUSIONS The resulting Diabetes Outcome Model of the U.S. (DOMUS) is a major step forward in understanding diabetes progression and the role of social determinants of health. This model can be used by scientists, policymakers, and health system managers to better understand how choices can affect population health and health disparities, including the broad diversity of U.S. races and ethnicities. Moreover, this model can be used to realize longer-term comparative effectiveness in cost-effectiveness analyses for diabetes management in the future.
Medical Journal
|15th Jan, 2026
|Nature Medicine's Advance Online Publication (AOP) table of contents.
Medical Journal
|15th Jan, 2026
|Wiley
Medical Journal
|15th Jan, 2026
|Wiley
Medical Journal
|15th Jan, 2026
|Wiley
Medical Journal
|15th Jan, 2026
|Wiley
Medical Journal
|15th Jan, 2026
|Wiley
Medical Journal
|15th Jan, 2026
|Wiley