The United States is rapidly moving to a health care delivery system in which value-based payment models are the predominant way of reimbursing clinicians for care. Since caring for patients with social risk factors may cost more and make it harder to achieve high performance on quality metrics, there is long-standing concern about how these patients might fare under such systems and how the systems might affect providers who disproportionately provide care to socially at-risk populations.
In October 2014, Congress passed the Improving Medicare Post-Acute Care Transformation (IMPACT) Act, which required the Office of the Assistant Secretary for Planning and Evaluation (ASPE) of the Department of Health and Human Services to review the evidence linking social risk factors with performance under existing federal payment systems — and to suggest strategies to remedy any deficits they found. That report was sent to Congress in December 2016.1
Because the report focuses primarily on Medicare, the analyses centered on social risk factors covered in current Medicare data, including dual enrollment in Medicare and Medicaid as a marker for low income, residence in a low-income area, race, Hispanic ethnicity, and residence in a rural area. Disability was also examined. Medicare payment programs were analyzed if they were currently operational or defined in statute and if they incorporated quality or efficiency metrics into payment decisions. These criteria led to the inclusion of nine programs: the Hospital Readmissions Reduction Program, Hospital Value-Based Purchasing Program, Hospital-Acquired Condition Reduction Program, Medicare Advantage Quality Star Rating Program, Medicare Shared Savings Program (MSSP), Physician Value-Based Payment Modifier Program, End-Stage Renal Disease Quality Incentive Program, Skilled Nursing Facility Value-Based Purchasing Program, and Home Health Value-Based Purchasing Program.
There were two main findings. First, beneficiaries with social risk factors had worse outcomes on many quality measures, regardless of the providers they saw, and dual enrollment status was the most powerful predictor of poor outcomes. Dually enrolled beneficiaries had poorer outcomes on process measures (e.g., cancer screening), clinical outcome measures (e.g., diabetes control, readmissions), safety (e.g., infection rates), and patient-experience measures (e.g., communication from doctors and nurses), as well as higher resource use (e.g., higher spending per hospital admission episode). These associations held even when the beneficiaries being compared were in the same hospital, health plan, accountable care organization (ACO), physician group, or facility. These findings generally persisted after risk adjustment, across care settings, measure types, and programs and were moderate in size.
Second, in every type of care setting examined, providers that disproportionately served beneficiaries with social risk factors tended to have worse performance on quality measures. Some of the performance differences were driven by beneficiary mix, but part of the difference persisted even after adjustment for beneficiary characteristics. As a result, safety-net providers were more likely to face financial penalties in most of the value-based purchasing programs in which penalties are currently assessed, though some of the differences were small because of the methods applied in calculating such penalties. The single exception was that ACOs with a high proportion of dually enrolled beneficiaries were more likely to share in savings under the MSSP, despite slightly worse quality scores, because their cost performance was better.
However, in every setting, there were some providers serving a high proportion of beneficiaries with social risk factors that achieved high performance levels — indicating that high performance is feasible with the right strategies and supports.
These findings underscore several challenges. How do we ensure that we can monitor quality of care for different social groups? How do we judge performance fairly across providers that serve beneficiaries with a different mix of social risk factors? And how do we ensure that payment reflects the resources required to provide high-quality care while also providing incentives to ameliorate existing disparities in care?
We suggest three general strategies (see table). The first strategy is foundational: we should measure and report quality of care for beneficiaries with social risk factors. For that to happen, data collection will need to be enhanced and statistical techniques developed to allow measurement and reporting of performance on key quality and resource-use measures for such subgroups.
Another important component of this strategy is to measure equity itself. Health equity measures or domains should be developed and introduced into existing payment programs to measure disparities and provide incentives for reducing them. The final component of this strategy is to monitor the financial impact of Medicare payment programs on providers that disproportionately serve beneficiaries with social risk factors. For example, as the Merit-Based Incentive Payment System is implemented, it will be important to ensure that providers caring for large numbers of socially at-risk beneficiaries are not themselves put at risk.
The second strategy is to set and maintain high, fair quality standards for the care of all beneficiaries. That does not mean that all measures should be adjusted for social risk, nor that no measures should be so adjusted. Rather, measures should be individually examined to determine whether adjustment for social risk factors is appropriate to make them as equitable as possible. This determination will depend on the measure and its empirical relationship to social risk factors. For example, for process measures, an important concern is whether the process being measured is entirely under the provider’s control. Some observers argue that adherence to annual mammography or periodic colonoscopy, for instance, is influenced not only by provider recommendations but also by patient preferences and other related factors. By contrast, provision of aspirin to patients with acute myocardial infarction is more directly under the control of hospital-based providers.
For outcome measures, determining whether or not a measure should be adjusted may depend on the pathway by which the social risk factor is related to worse outcomes. For example, dual enrollment status may be associated with a higher risk of frailty, worse functional status, and lower levels of social support and education, all of which may affect readmission rates, diabetes control, and other outcome measures. Such associations might make adjustment more appropriate. In addition, research should be conducted to determine whether better ascertainment of these unmeasured medical and social factors and their use in statistical adjustment might improve the ability to delineate true differences in performance between providers.
The third strategy recognizes that regardless of whether or not measures are adjusted for social risk, we need to make strides in addressing the underlying issues themselves, and we can leverage value-based payment programs to do so. Therefore, strategy 3 focuses on directly rewarding and supporting better outcomes for socially at-risk beneficiaries. First, whereas value-based purchasing programs reward achievement of high quality and good outcomes among all beneficiaries, we should also consider creating additional targeted financial incentives to reward achievement or improvement specifically for socially at-risk beneficiaries. Such targeted incentives could help harness the power of value-based payment to improve care and outcomes for our most vulnerable patients, and simultaneously offset any real or perceived disincentives under value-based purchasing programs to caring for these beneficiaries.
Second, we should use existing or new quality-improvement programs to provide targeted technical assistance to providers that serve beneficiaries with social risk factors, recognizing that they may face unique challenges in both participating and succeeding in new payment models.
Third, we should develop demonstrations or models focusing on care innovations that may help achieve better outcomes for beneficiaries with social risk factors but that might not be testable under current payment and delivery structures. Examples include the demonstration programs in Medicare Advantage that focus on coordinating benefits between Medicare and Medicaid and the Center for Medicare and Medicaid Innovation’s Accountable Health Communities model.
Fourth, we should pursue further research to examine the costs of achieving good outcomes for beneficiaries with social risk factors and to determine whether current payments adequately account for any differences in care needs. Disproportionate Share Hospital payments are one current example of such add-on payments for social risk, and payments to Medicare Advantage contracts are higher for dually eligible beneficiaries. However, these payment adjustments are not uniform across care settings.
Social factors are powerful determinants of health. Beneficiaries with social risk factors may have poorer outcomes because of higher levels of medical risk, worse living environments, greater challenges in adherence and lifestyle, and bias or discrimination. Providers serving these beneficiaries may have poorer performance due to fewer resources, more challenging clinical workloads, lower levels of community support, or worse quality. These problems are complex and will not yield to simple fixes.
However, the strategies we propose may be an important starting point. As the scope, reach, and financial risk associated with value-based payment models grow, Medicare can use the strategies outlined above to administer fair, balanced programs that promote quality and value, provide incentives to reduce disparities, and avoid inappropriately penalizing providers that serve socially at-risk beneficiaries, ultimately helping to ensure that the best health outcomes possible can be achieved for all beneficiaries.
From the Harvard T.H. Chan School of Public Health and Brigham and Women’s Hospital, Boston (K.E.J., A.M.E.); the Office of the Assistant Secretary for Planning and Evaluation, Department of Health and Human Services, Washington, DC (K.E.J., N.D.L., S.H.S.); and the Centers for Medicare and Medicaid Services, Baltimore (P.H.C., K.G.).
1. Department of Health and Human Services, Office of the Assistant Secretary of Planning and Evaluation. Report to Congress: social risk factors and performance under Medicare’s value-based payment programs (https://aspe.hhs.gov/pdf-report/report-congress-social-risk-factors-and-performance-under-medicares-value-based-purchasing-programs).
This Perspective article originally appeared in The New England Journal of Medicine.