Social Determinants of Health in Managed Care Payment Formulas
Department of Quantitative Health Sciences
Health Economics | Health Policy | Health Services Administration | Health Services Research
Importance: Managed care payment formulas commonly allocate more money for medically complex populations, but ignore most social determinants of health (SDH).
Objective: To add SDH variables to a diagnosis-based payment formula that allocates funds to managed care plans and accountable care organizations.
Design, Setting, and Participants: Using data from MassHealth, the Massachusetts Medicaid and Children's Health Insurance Program, we estimated regression models predicting Medicaid spending using a diagnosis-based and SDH-expanded model, and compared the accuracy of their cost predictions overall and for vulnerable populations. MassHealth members enrolled for at least 6 months in 2013 in fee-for-service (FFS) programs (n = 357660) or managed care organizations (MCOs) (n = 524607).
Exposures: We built cost prediction models from a fee-for-service program. Predictors in the diagnosis-based model are age, sex, and diagnoses from claims. The SDH model adds predictors describing housing instability, behavioral health issues, disability, and neighborhood-level stressors.
Main Outcomes and Measures: Overall model explanatory power and overpayments and underpayments for subgroups of interest for all Medicaid-reimbursable expenditures excepting long-term support services (mean annual cost = $5590 per member).
Results: We studied 357660 people who were FFS participants and 524607 enrolled in MCOs with a combined 806889 person-years of experience. The FFS program experience included more men (49.6% vs 43.6%), older patients (mean age of 26.1 years vs 21.6 years), and sicker patients (mean morbidity score of 1.16 vs 0.89) than MCOs. Overall, the SDH model performed well, but only slightly better than the diagnosis-based model, explaining most of the spending variation in the managed care population (validated R2 = 62.4) and reducing underpayments for several vulnerable populations. For example, raw costs for the quintile of people living in the most stressed neighborhoods were 9.6% ($537 per member per year) higher than average. Since greater medical morbidity accounts for much of this difference, the diagnosis-based model underpredicts costs for the most stressed quintile by about 2.1% ($130 per member per year). The expanded model eliminates the neighborhood-based underpayment, as well as underpayments of 72% for clients of the Department of Mental Health (observed costs of about $30000 per year) and of 7% for those with serious mental illness (observed costs of about $16000 per year).
Conclusions and Relevance: Since October 2016, MassHealth has used an expanded model to allocate payments from a prespecified total budget to managed care organizations according to their enrollees' social and medical risk. Extra payments for socially vulnerable individuals could fund activities, such as housing assistance, that could improve health equity.
DOI of Published Version
JAMA Intern Med. 2017 Oct 1;177(10):1424-1430. doi: 10.1001/jamainternmed.2017.3317. Link to article on publisher's site
JAMA internal medicine
Ash AS, Mick EO, Ellis RP, Kiefe CI, Allison JJ, Clark MA. (2017). Social Determinants of Health in Managed Care Payment Formulas. UMass Chan Medical School Faculty Publications. https://doi.org/10.1001/jamainternmed.2017.3317. Retrieved from https://escholarship.umassmed.edu/faculty_pubs/1419