<p>Patient characteristics by DM type.</p>

Background
Diabetes mellitus (DM) imposes substantial healthcare costs with documented disparities among African Americans and Hispanic patients. To inform care delivery and resource allocation, this study identified hospitalization cost predictors among African American and Hispanic patients with diabetes in Southeastern Virginia.
Methods
We analyzed 6,011 hospital discharges from the Virginia Health Information database (2016–2020) for adults aged 18–85 with diabetes. Discharges were classified by Medicare Severity Diagnosis-Related Groups: DM with complications/comorbidities (DCC, n = 3,328), DM with major complications/comorbidities (DMCC, n = 1,518), and DM without major complications/comorbidities (DWO, n = 1,165). Because cost distributions were right-skewed (skewness 3.5–8.24), we used log-linear regression with robust standard errors and back-transformed coefficients to percentage changes.
Results
Mean age differed by classification: DWO 38.7 ± 17.2 years, DCC 47.4 ± 17.4, DMCC 54.9 ± 17.4. The cohort was predominantly African American (98.2–99.1%). For DWO, urgent admission was the strongest predictor, associated with 239.5% higher costs versus emergency admissions (95% CI, 220.8–258.2; p < 0.001). Other significant predictors included skilled nursing facility discharge (SNF) (69.7–119.2% increase), primary procedures (11.0–53.8% increase), and peptic ulcer disease (66.1–135.8% increase. Readmission effects varied by classification: in univariable models, readmission was associated with 5.8% lower costs in DMCC (p < 0.001); in multivariable models, this association attenuated and was not statistically significant (−3.5%; 95% CI, −9.0 to 2.3; p = 0.230). By contrast, DCC and DWO showed increases of 13.7% and 6.0%, respectively.
Conclusions
Admission type particularly urgent admissions among patients without major complications, was a key cost driver. Findings support risk stratification in all emergency departments, with priority in systems serving large proportions of minority patients. Heterogeneous readmission effects across classifications indicated the need for nuanced quality metrics. These results provided baseline data for predictive modeling to improve diabetes care and reduce disparities in minority populations.