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Development of an Individual Level Social Determinants of Health ( SDoH ) Model

Growing evidence in the health services literature suggests that social determinants of health (SDoH) can affect a person’s risk for adverse health events and increased cost of care. Individuals can be scored on those factors associated to SDoH measures that are individual in nature and weights can be created that can be used for generating greater insight into risk, costs, and health care utilization patterns. To develop this prototype model, data elements will consist of Z Codes from the claims data of a large Midwest Medicaid payer. Z Codes were created as a new set of supplemental codes with the advent of ICD-10 and are physician-coded attributes at a person level. We examine the subset of Z Codes (55-65) which indicate “Persons with potential health hazards related to socioeconomic and psychosocial circumstances.” These are set as binary indicators at the individual subject level. A subset of the Z Codes is selected for use in this analysis. SAS 9.4 will be used to research and develop this procedure. Initial research indicates the use of a Latent Class statistical model as best option for creating the classification model. This model will be developed and tested for optimization, feasibility, and accuracy. From this model predicted probabilities will be output which can then be used in a generalized linear regression model as weights to help define, adjust, and assess the outcomes of interest and combine with 3M Clinical Risk Group (CRG) scores as a model covariate.