Brooke Kenney

Brooke Kenney, MPH, is a data analyst for MVC and MSHOP.

According to the World Health Organization (WHO), social determinants of health (SDH) are the conditions in which people are born, grow, work, live, and age, and the wider set of forces and systems shaping the conditions of daily life. As key players in health inequity and outcomes these conditions have received a lot of attention lately from health care delivery systems and the U.S. government.1

Value-based payment models (VBP), which aim to apply payment to the quality and efficiency of care delivered, are, in part, a response to help address populations with SDH and to support the providers that serve these communities. However, caring for patients with social risk factors may cost more and make it harder to achieve high performance on quality metrics, thus VBP could actually promote unintended consequences, especially because some social risk factors may be outside the provider’s realm of influence.

In October 2014, Congress passed the Improving Medicare Post-Acute Care Transformation (IMPACT) Act, which required an evaluation of Medicare payment programs using socioeconomic status (SES) as a predictor of quality measures and resource utilization. Study A, the first installation, focuses on socioeconomic information currently available in Medicare data. The full report, released in December 2016, can be found here. The second installation or Study B, to be completed by October 2019, will expand the analyses by using non-Medicare datasets to quantify SES. The major findings and conclusions from Study A in the Report to Congress are given below.2

Scope: The social risk factors examined were dual enrollment in Medicare and Medicaid as a marker for low income, residence in a low-income area, race, Hispanic ethnicity, residence in a rural area, and disability. The scope of these social risk factors is expected to be expanded on in Study B.

Finding 1) 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.

For the most part, these findings persisted after risk adjustment, across care settings, measure types, and programs, and were moderate in size. Risk-adjusted mortality rates (from HVBP), risk-adjusted admissions for heart failure (from Medicare Shared Savings Program), and risk-adjusted inpatient readmissions of Medicare SNF beneficiaries to IPPS hospitals and critical access hospitals (from SNF VBP) were the noted exceptions.

Finding 2) Providers that disproportionately served beneficiaries with social risk factors tended to have worse performance on quality measures, even after accounting for their beneficiary mix, and incurred penalties under all five current value-based purchasing programs in which penalties are currently assessed.

As a result, safety-net providers were more likely to face financial penalties across all but one of the Medicare value-based purchasing programs. This exception was that ACOs with a high proportion of dually-enrolled beneficiaries were more likely to share in savings under the Medicare Shared Savings Program. However, in every setting there were some providers that served a high proportion of beneficiaries with social risk factors who achieved high levels of performance.

Conclusions: This study seeks to answer whether beneficiaries with social risk factors have worse outcomes due to their social risk profile, or because of the providers they see as well as whether providers serving high numbers of beneficiaries with social risk factors provide worse care overall or perform worse due to this high proportion. The conclusion is that dual enrollment status is independently associated with worse outcomes, and dually enrolled beneficiaries are more likely to see lower-quality providers. Therefore, solutions that address only social risk factors or only provider performance will be less effective at navigating the complex relationship between social risk factors and performance.

Evaluation alone cannot explain why these observed patterns exist, primarily because a host of outside factors influence patient health which are not easily measured with current data. In light of these limitations, the Office of the Assistant Secretary for Planning and Evaluation (ASPE) have proposed 3 key strategies to enable all Medicare beneficiaries to receive the highest quality of healthcare services.

Strategy 1: Measure and report quality of care for beneficiaries with social risk factors. This will involve enhancing data collection and developing statistical techniques to allow measurement and reporting of performance on key quality and resource-use measures for such subgroups.

Strategy 2: Set high, fair quality standards for all beneficiaries. 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.

Strategy 3: Reward and support better outcomes for beneficiaries with social risk factors. 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.


1WHO: World Conference on Social Determinants of Health. Rio Political Declaration on Social Determinants of Health (2011) Retrieved from http://www.who.int/sdhconference/declaration/Rio_political_declaration.pdf. Web 10 Apr. 2017

2United States Department of Health and Human Services Office of the Assistant Secretary for Planning and Evaluation (2016) Social Risk Factors and Performance Under Medicare’s Value-Based Purchasing Programs: A Report Required by the Improving Medicare Post-Acute Care Transformation (IMPACT) Act of 2014. Washington, D.C.


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