The Michigan Value Collaborative

Helping Michigan hospitals achieve their best possible patient outcomes at the lowest reasonable cost

Tag: Medicare (page 1 of 5)

Providing high quality care to Medicare beneficiaries

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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Moneyball in Medicare

Edward Norton

Edward Norton, Ph.D., is a health economist working with MVC.

The Center for Medicare and Medicaid Services (CMS) is increasingly using financial incentives in pay-for-performance programs to encourage higher quality care at lower cost. Michigan hospitals might want to know: “How much are we penalized if one additional Medicare patient dies?”  A National Bureau of Economic Research (NBER) working paper by several members of the MVC team addresses that question for the Hospital Value-Based Purchasing Program (HVBP), with surprising results.  This study finds that about one-third of Michigan hospitals face no financial penalty if one additional patient with AMI, heart failure, or pneumonia dies.  For most other hospitals, the penalties for an additional death are modest, typically less than $10,000, but a few hospitals face penalties of up to around $40,000.

CMS created HVBP to reward or penalize hospitals based on their quality and episode-based costs of care. Within HVBP, each patient affects hospital performance on a variety of spending and quality measures (including mortality), and that performance translates directly to changes in program points and ultimately dollars.  For example, when a patient with AMI dies, the hospital’s AMI mortality rate increases, which reduces their points for the mortality measure, which reduces their total performance score, which lowers their percent bonus paid in two years, which lowers their future Medicare revenue.  But until now, the magnitude of this penalty was unknown. 

A recent NBER study — authored by myself, doctoral student Jun Li, medical student Anup Das, and MVC Associate Director Lena M. Chen — estimates how much money each Michigan hospital would lose if mortality increases by one, for each of three conditions, AMI, heart failure and pneumonia. The MVC data were essential to conduct the simulations.

One reason that the magnitude of financial incentives are hard to calculate is that there is no simple formula. Hospitals are rewarded more points if they have a low mortality rate relative to other hospitals or if they improve their mortality rate relative to their own performance in a prior year. 

The magnitude of the HVBP penalty for one additional death ranges widely across Michigan hospitals, from $0 to more than a $40,000 penalty (see Figure 1). For roughly one-third of all hospitals, there is no penalty.   The specific numbers are 17 hospitals (out of 50) for AMI, 33 out of 73 for heart failure, and 25 out of 75 for pneumonia (some hospitals do not have enough patients to meet the minimum threshold).  On the other hand, for the two-thirds of hospitals that do face a penalty, it can be as large as -$44,683 for AMI, -$41,303 for heart failure, and -$29,345 for pneumonia. 

Michigan hospitals with larger penalties tend to be larger and to be safety-net hospitals. These hospitals also tend to have mortality rates in the middle of the distribution, because those that have the best or worst rates are not penalized much by a single additional death. 

We do not know yet if these financial incentives affect behavior, although this is the premise of the HVBP Program. However, if provider behavior responds to financial incentives, these findings suggest that CMS may need to adjust how it calculates points and creates incentives for hospitals in the HVBP program.  The research by the MVC team on the national CMS pay-for-performance programs will help us design better pay-for-performance programs in Michigan, and achieve the goal of delivering high-value care to Michigan residents.

Figure 1.

This work was supported by the National Institute on Aging (P01-AG019783). Support for MVC is provided by Blue Cross Blue Shield of Michigan as part of the BCBSM Value Partnerships program; however, the opinions, beliefs and viewpoints expressed by the author do not necessarily reflect those of BCBSM or any of its employees. 


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