Managed care payment models are foundational in healthcare, designed to allocate resources effectively, especially for populations with complex medical needs. However, a significant oversight in many current models is the lack of consideration for social determinants of health (SDH). While these formulas often adjust payments based on diagnosis and medical complexity, they largely ignore the profound impact of social factors on health outcomes and healthcare costs.
The crucial question is: How can we refine these payment structures to incorporate SDH variables, ensuring a more equitable and effective distribution of funds to managed care plans and accountable care organizations? This article delves into the importance of integrating SDH into diagnosis-based payment formulas, drawing insights from a compelling study conducted within MassHealth, Massachusetts’ Medicaid program.
The Limitation of Diagnosis-Based Payment Models
Traditional managed care payment models heavily rely on diagnostic data to predict healthcare costs. These models typically adjust payments based on age, sex, and diagnoses derived from medical claims. The rationale is straightforward: individuals with more severe and chronic conditions require more healthcare services and thus, higher payments are allocated to manage their care. While this approach acknowledges medical complexity, it operates under the assumption that medical needs are the primary drivers of healthcare expenditure.
However, this diagnosis-centric view overlooks the substantial influence of SDH. Factors such as housing instability, food insecurity, behavioral health challenges, disability, and neighborhood-level stressors significantly impact an individual’s health trajectory and healthcare utilization. Ignoring these factors can lead to inaccurate cost predictions and inadequate resource allocation, particularly for vulnerable populations disproportionately affected by adverse social conditions.
Integrating Social Determinants of Health: A More Holistic Approach
Recognizing the limitations of solely diagnosis-based models, researchers have explored the impact of incorporating SDH variables into payment formulas. The study within MassHealth provides a compelling example of this approach. Researchers utilized data from MassHealth, encompassing both fee-for-service (FFS) and managed care organization (MCO) programs, to compare the predictive accuracy of a diagnosis-based model against an SDH-expanded model.
The diagnosis-based model included standard predictors like age, sex, and diagnoses. The SDH-expanded model augmented these with predictors capturing housing instability, behavioral health issues, disability, and neighborhood-level stressors. The study’s primary outcome was the overall explanatory power of each model and their ability to predict costs accurately for various subgroups, focusing on Medicaid-reimbursable expenditures, excluding long-term support services.
Study Findings: The Value of SDH in Payment Models
The MassHealth study, encompassing a vast dataset of 357,660 FFS participants and 524,607 MCO enrollees, revealed insightful findings. While both models demonstrated considerable explanatory power, the SDH-expanded model exhibited a nuanced improvement, particularly in predicting costs for vulnerable populations. The validated R² value of 62.4% for the SDH model in the managed care population underscores its robust predictive capability.
Alt text: A comparative bar chart illustrating the demographic and health characteristics of participants in Fee-for-Service (FFS) and Managed Care Organizations (MCOs) within the MassHealth program, highlighting differences in gender distribution, age, and morbidity scores between the two groups.
One striking finding was the underestimation of costs for individuals residing in highly stressed neighborhoods by the diagnosis-based model. Raw healthcare costs for individuals in the most stressed neighborhoods were 9.6% higher than the average. Although medical morbidity accounted for a portion of this difference, the diagnosis-based model still underpredicted costs by approximately 2.1% for this quintile. Crucially, the SDH-expanded model effectively eliminated this neighborhood-based underpayment.
Furthermore, the SDH model significantly improved cost predictions for other vulnerable groups. It reduced underpayments for clients of the Department of Mental Health by a substantial 72% and for those with serious mental illness by 7%. These findings highlight the crucial role of SDH in accurately capturing the healthcare needs and associated costs for populations facing social vulnerabilities.
Implications for Managed Care and Health Equity
The MassHealth study provides compelling evidence for the integration of SDH into managed care payment models. Since October 2016, MassHealth has adopted an expanded model incorporating social and medical risk to allocate payments to managed care organizations. This pioneering move recognizes that addressing social needs is integral to achieving health equity and optimizing healthcare spending.
Alt text: A pie chart demonstrating the allocation of payments within the MassHealth managed care system, emphasizing the distribution of funds based on a payment model that incorporates Social Determinants of Health (SDH) alongside medical risk factors.
By providing additional payments for socially vulnerable individuals, these expanded models enable managed care organizations to invest in crucial interventions. These may include housing assistance, food programs, and behavioral health services, directly addressing the SDH that impact health outcomes. Such investments not only improve individual health but also hold the potential to reduce overall healthcare costs in the long run by preventing costly downstream medical complications.
Conclusion: Towards a More Equitable and Effective Payment System
Incorporating social determinants of health into Managed Care Payment By Diagnosis is not merely a matter of refining payment formulas; it represents a fundamental shift towards a more equitable and effective healthcare system. By acknowledging and addressing the social factors that profoundly influence health, we can create payment models that more accurately reflect the true cost of care and enable targeted interventions to improve health outcomes for all, particularly the most vulnerable among us. The MassHealth experience serves as a valuable blueprint for other healthcare systems striving to create payment models that promote both financial sustainability and health equity.
