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

Bibliographic Data

ID9099574
AuthorsChintan Pandya (0000-0002-4930-9709, Johns Hopkins University, corresponding author), Chintan J Pandya (Department of Health Policy and Management, Center for Population Health IT, Johns Hopkins School of Public Health, Baltimore, MD), JunBo Wu (0000-0002-5057-3574, Johns Hopkins University), Elham Hatef (0000-0003-2535-8191, Department of Health Policy and Management, Center for Population Health IT, Johns Hopkins School of Public Health, Baltimore, MD, corresponding author), Hadi Kharrazi (0000-0003-1481-4323, Department of Health Policy and Management, Center for Population Health IT, Johns Hopkins School of Public Health, Baltimore, MD, corresponding author)
Year2024
Volume62
Issue11
Pages724-731
Publication date2024-11-01
Open AccessNo
TypeARTICLE
VenueMedical Care (JOURNAL)
Journal identifiersISSN: 0025-7079 • E-ISSN: 1537-1948
PublisherOvid Technologies (Wolters Kluwer Health) (PUBLISHER)
DOI10.1097/mlr.0000000000001961
PMID38085115
OpenAlexW4389615046
LanguageEN
Citations received1
References cited27

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

Environmental health · Family medicine · Health care · Latent class model · Logistic regression · Medicaid · Population · Socioeconomic status · Chronic Disease Management Strategies · Computer Science · Food Security and Health in Diverse Populations · Health disparities and outcomes · Internal Medicine · Medicine · Gerontology

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Citations per year1
Citation span2025 - 2025 (1)
Highly citedNo

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