• Elena Andreyeva, Winnie Chi, Yongkang Zhang, Rainu Kaushal, and Kevin Haynes.
• Department of Health Policy and Management, School of Public Health, Texas A&M University, 212 Adriance Lab Rd, 1266 TAMU, College Station, TX 77843-1266. Email: andreyeva@tamu.edu.
• Am J Manag Care. 2023 Jul 1; 29 (7): e199e207e199-e207.

ObjectivesTo assess the impact of adding neighborhood social determinants of health (SDOH) data to demographic and clinical characteristics for predicting high-cost utilizers and to examine variations across age groups.Study DesignUsing US Census data and 2017-2018 commercial claims from a large national insurer, we estimated association between neighborhood-level SDOH and the probability of being a high-cost utilizer.MethodsObservational study using administrative claims from a national insurer and US Census data. Data included a 50% random sample of commercially insured individuals who were younger than 89 years and had 1 year of continuous eligibility in 2017 and at least 30 days in 2018. Probit models assessed impact of SDOH and neighborhood conditions on predicting cost status.ResultsSDOH did not improve predictive power of evaluated models. However, disadvantaged neighborhood residence was still associated with being a high-cost utilizer. Adults 65 years and older in disadvantaged neighborhoods had increased likelihood of high-cost utilization. Children and younger adults in disadvantaged neighborhoods had lower risk of becoming high-cost utilizers.ConclusionsPolicy makers and industry stakeholders should be aware of the mechanisms behind the relationship between neighborhood social conditions and health outcomes and how the relationship differs across age groups.

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