SUN-844 - Socioeconomic Predictors of Readmission and Resource Utilization in Hyperglycemic Crises: A Nationwide Analysis

Introduction: Diabetic ketoacidosis (DKA) and hyperosmolar hyperglycemic state (HHS) impose a substantial burden on healthcare systems through frequent, preventable readmissions. Effective prevention requires medication access and stability factors disrupted by social determinants of health. We quantified the independent impact of housing instability, insurance status, and income on readmission rates and resource utilization. A p-value < 0.05 was considered statistically significant.

Methods: We analyzed the Nationwide Readmissions Database (NRD) 2022 for adult DKA/HHS hospitalizations. Survey-weighted regression models assessed the impact of housing status (housed vs. unhoused), payer, and neighborhood income (Q1–Q4) on outcomes, adjusted for age, sex, and comorbidities. Longitudinal analysis calculated annual readmission frequency.

Results: Of 237,904 weighted admissions, unhoused patients (0.9%) were younger (42.2 vs. 45.4 years) and 70% male. They exhibited a distinct profile: significantly higher rates of diabetes with chronic complications (50.0% vs. 40.0%; p=0.007), drug abuse (40.0% vs. 10.0%), and psychiatric illness (28.8% vs. 18.6%) (all p< 0.001). Conversely, unhoused patients had lower burdens of obesity (10.0% vs. 20.0%), kidney disease (10.0% vs. 20.0%), and heart failure (4.7% vs. 8.0%)(all p< 0.05).

The population was predominantly low-income (38.6% in Q1 vs 12.7% in Q4) and Medicaid-insured (36.7%). Medicaid beneficiaries had higher rates of complicated diabetes (40.0% vs. 30.0%) than privately insured patients. However, diabetes severity did not differ by income quartile (43.9% in Q1 vs. 44.2% in Q4; p=0.75).

Housing instability was the strongest readmission predictor (aOR 2.33; p< 0.001). Unhoused patients averaged 2.27 readmissions/year versus 1.01 for housed. Medicaid (aOR 1.89) and uninsured (aOR 1.32) status increased risk; Medicaid patients averaged 1.33 readmissions/year vs 0.63 for private insurance. Q1 patients had higher odds (aOR 1.24) and frequency (1.15 vs. 0.87/year) compared with Q4. Unhoused status increased length of stay (+1.1 days) and charges (+$7,443). Conversely, Q1 patients incurred lower charges (−$8,150) than Q4.

Conclusion: In this national analysis, structural barriers were strong independent predictors of readmission, independent of baseline characteristics. Vulnerable populations experienced higher readmission frequencies despite having a lower prevalence of physical comorbidities. Notably, low income was associated with frequent readmissions despite no difference in diabetes severity, suggesting that disrupted access to care drives recurrent hospitalization. Integrating housing stability, mental health support, and tailored discharge planning into diabetes care pathways is critical to reducing preventable readmissions and improving outcomes in this high-risk population.

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