Latent Class Analysis of Social Needs in Medicaid Population and Its Impact on Risk Adjustment Models

Abstract

Background: A growing number of US states are implementing programs to address the social needs (SNs) of their Medicaid populations through managed care contracts. Incorporating SN might also improve risk adjustment methods used to reimburse Medicaid providers. Objectives: Identify classes of SN present within the Medicaid population and evaluate the performance improvement in risk adjustment models of health care utilization and cost after incorporating SN classes. Research Design: A secondary analysis of Medicaid patients during the years 2018 and 2019. Latent class analysis (LCA) was used to identify SN classes. To evaluate the impact of SN classes on measures of hospitalization, emergency (ED) visits, and costs, logistic and linear regression modeling for concurrent and prospective years was used. Model performance was assessed before and after incorporating these SN classes to base models controlling for demographics and comorbidities. Subjects: 262,325 Medicaid managed care program patients associated with a large urban academic medical center. Results: 7.8% of the study population had at least one SN, with the most prevalent being related to safety (3.9%). Four classes of SN were determined to be optimal based on LCA, including stress-related needs, safety-related needs, access to health care–related needs, and socioeconomic status–related needs. The addition of SN classes improved the performance of concurrent base models’ AUC (0.61 vs. 0.58 for predicting ED visits and 0.61 vs. 0.58 for projecting hospitalizations). Conclusions: Incorporating SN clusters significantly improved risk adjustment models of health care utilization and costs in the study population. Further investigation into the predictive value of SN for costs and utilization in different Medicaid populations is merited.