Latent Class Analysis to Represent Social Determinant of Health Risk Groups in the Medicaid Cohort of the District of Columbia

Datos Bibliográficos

ID9103860
AutoresMelissa L McCarthy (0000-0002-0092-2748, Health Policy and Management, Milken Institute School of Public Health, autor de correspondencia), Zhaonian Zheng (Health Policy and Management, Milken Institute School of Public Health, autor de correspondencia), Marcee E Wilder (Emergency Medicine, Medical Faculty Associates), Marcee Wilder (0000-0001-6508-4573, Medical Research Associates), Angelo Elmi (0000-0002-5786-5801, George Washington University), Paige Kulie (0000-0002-6250-8075, George Washington University), Samuel Johnson (0000-0003-4032-2058, Tulane University School of Medicine, Tulane University, New Orleans, LA), Scott L Zeger (0000-0001-8907-1603, Johns Hopkins University)
Año2021
Volumen59
Número3
Páginas251-258
Fecha de publicación2021-03-01
Peer ReviewedSí
Open AccessNo
TipoARTICLE
RevistaMedical Care (JOURNAL)
Identificadores de la revistaISSN: 0025-7079 • E-ISSN: 1537-1948
EditorialOvid Technologies (Wolters Kluwer Health) (PUBLISHER)
DOI10.1097/mlr.0000000000001468
PMID33273298
OpenAlexW3108558568
IdiomaEN
Citas recibidas3
Referencias citadas13

OBJECTIVE: To develop distinct social risk profiles based on social determinants of health (SDH) information and to determine whether these social risk groups varied in terms of health, health care utilization, and costs. METHODS: We prospectively enrolled 8943 beneficiaries insured by the District of Columbia Medicaid program between September 2017 and December 2018. Participants completed a SDH survey and we obtained their Medicaid claims data for a 2-year period before study enrollment. We used latent class analysis (LCA) to identify distinct social risk profiles based on their SDH responses. We assessed the relationship among different SDH as well as the relationship among the social risk classes and health, health care use and costs. RESULTS: The majority of SDH were moderately to strongly correlated with one another. LCA yielded 4 distinct social risk groups. Group 1 reported the least social risks with the most employed. Group 2 was distinguished by financial strain and housing instability with fewer employed. Group 3 were mostly unemployed with limited car and internet access. Group 4 had the most social risks and most unemployed. The social risk groups demonstrated meaningful differences in health, acute care utilization, and health care costs with group 1 having the best health outcomes and group 4 the worst (P<0.05). CONCLUSIONS: LCA is a practical method of aggregating correlated SDH data into a finite number of distinct social risk groups. Understanding the constellation of social challenges that patients face is critical when attempting to address their social needs and improve health outcomes

Cohort · Cohort study · Economic growth · Economics · Environmental health · Family medicine · Health care · Latent class model · Medicaid · Political science · Social class · Sociology · Statistics · Demography · Food Security and Health in Diverse Populations · Health disparities and outcomes · Health, Environment, Cognitive Aging · Internal Medicine · Mathematics · Medicine · Gerontology