To examine the relationship between socioeconomic deprivation and complex needs, defined as mental and physical comorbidities, we conducted a cross-sectional retrospective cohort analysis of adult Utah Medicaid beneficiaries. Our analysis included Medicaid beneficiaries with geocoded addresses aged ≥18 years in Utah (N = 157,739). We geocoded beneficiary addresses and assigned them to census block groups. We compared the socioeconomic status of block groups (Singh's area deprivation index) with the proportion of complex needs, defined based on cluster analysis as 1 physical condition with depression or ≥ 2 physical with ≥1 mental health condition. Spatial mapping was performed of prevalence quantiles grouped by count overlaid with Medicaid-covered mental health facilities. Prevalence of complex needs was 18.9% (n = 29,742); beneficiaries with >3 emergency department visits had 12.8 odds of having complex needs; 39.7% of beneficiaries with >$5,000 in annual costs had complex needs. Common comorbid conditions among beneficiaries with complex needs were hypertension (56.0%), hyperlipidemia (35.5%), depression (68.8%), anxiety (56.2%), drug use (16.0%), and alcohol use disorders (15.2%). Census block groups with higher deprivation had a higher proportion of complex needs (ρ = 0.21, p < 0.001). There was a statistically significant spatial autocorrelation of the prevalence of complex needs (Moran's I index: 0.65; p < 0.001). Six high-count census blocks had no mental health facilities. Areas with increased socioeconomic deprivation had a greater proportion of complex needs and fewer mental health facilities. Integrated programs addressing both physical and mental health conditions with a focus on socioeconomically deprived areas might benefit Medicaid recipients in populations such as those in Utah.

A limited number of patients, commonly termed super-utilizers, account for the bulk of health care expenditures. Multiple criteria for identifying super-utilizers exist, but no standard methodology is available for determining which criteria should be used for a specific population. Application is often arbitrary, and poorly aligned super-utilizer criteria might result in misallocation of resources and diminished effects of interventions. This study sought to apply an innovative, data-driven approach to classify super-utilizers among Utah Medicaid beneficiaries. The authors conducted a literature review of research methods to catalogue applied super-utilizer criteria. The most commonly used criteria were applied to Utah Medicaid beneficiaries enrolled during July 1, 2016-June 30, 2017, using their previous 12 months of claims data (N = 309,921). The k-medoids algorithm cluster analysis was used to find groups of beneficiaries with similar characteristic based on criteria from the literature. In all, 180 super-utilizer criteria were identified in the literature, 21 of which met the inclusion criteria. When these criteria were applied to Utah Medicaid data, 5 distinct subpopulation clusters were found: non-super-utilizers (n = 163,118), beneficiaries with multiple chronic or mental health conditions (n = 68,054), beneficiaries with a single chronic health condition (n = 43,939), emergency department super-utilizers with chronic or mental health conditions (n = 7809), and beneficiaries with uncomplicated hospitalizations (n = 27,001). This study demonstrates how cluster analysis can aid in selecting characteristics from the literature that systematically differentiate super-utilizer groups from other beneficiaries. This methodology might be useful to health care systems for identifying super-utilizers within their patient populations.