Healthcare reform established several programs to measure provider performance in an effort to improve the quality of care and curb rising healthcare costs.  A key program is the Hospital Readmissions Reduction Program (HRRP), which is a payment penalty program that rewards hospitals for reducing preventable readmissions and penalizes those with above-average readmissions.  Several stakeholders have questioned the fairness and long-term sustainability of the program.  A central argument against the current program is the lack of risk-adjustment for vital demographic and socioeconomic factors (such as income, occupation, literacy, primary language, race, ethnicity, etc.) that are beyond the hospital’s control, but show a high correlation to the probability of readmission.

The onset of value-based payments that are designed to promote delivery of higher quality and more cost-effective care has necessitated a need to risk adjust payments to payers and/or providers for these socioeconomic factors.  This should be implemented to help ensure equitable reimbursement that is commensurate with the risk, social and economic characteristics of the underlying population being treated and the quality of care delivered.

In October 2015, CMS announced that the agency’s current risk model (CMS-HCC) “underpredicts” the payments to health plans for dual eligible beneficiaries (high-cost members who, because of both their income levels and age or disability status, are dually eligible for Medicaid and Medicare) and announced plans to tweak its payment models in hopes of predicting costs more accurately.  This move will presumably yield a higher reimbursement rate for health plans that service these high-cost dual eligibles.  The proposed change to the risk adjustment model is expected to be effective for Payment Year 2017.  In addition, the agency is also considering changes to its five-star quality ratings programs for health plans that serve large populations of disadvantaged patients.

These recent announcements by CMS clearly indicate the agency recognizes the impact of an individual’s economic and social characteristics on his or her health status.  This further strengthens the case that similar measures need to be adopted in the provider market to adjust for demographic and socioeconomic factors when measuring performance.  Historically, CMS has resisted adjusting for additional risk, as they believe these factors may mask the disparities in quality of care provided.

However, a number of industry experts, including a National Quality Forum expert panel, believe that socioeconomic adjustments should be made while determining provider performance measures.  They argue that by not doing so providers serving vulnerable populations will be unfairly penalized, which will further reduce resources and worsen disparities in care.  Proponents argue that proper socioeconomic adjustments doesn’t excuse poor care for the disadvantaged population, but rather avoids penalizing safety-net hospitals simply for taking care of more of them.  Industry experts believe that CMS’ current policies disincentivize provision of care to the vulnerable populations, who often depend on these safety-net hospitals for access to entire spectrum of care.

Their view is supported by a growing body of evidence that suggests correlation between socioeconomic factors and a member’s health status and thus adjustment is necessary for equitable hospital assessments.

  • The Missouri Hospital Association augmented the CMS’ readmissions methodology to include Medicaid status, poverty and risk factors attributable to patients’ communities. Further, the augmented methodology was applied to the Missouri hospital data.  A side-by-side analysis of the current system vs. the socioeconomic augmented methodology suggested that 43% – 88% of the quality variances can be explained by socioeconomic factors.
  • In June 2014, Truven Center for Healthcare Analytics found that race and financial status were strong predictors of higher readmission rates. About 18% of a community’s readmissions can be attributed to unemployment.  The analysis also found that about 6% of readmissions could be attributed to poverty among the elderly, and that the chances of hospital readmission were almost 15% higher for certain demographics based on race vs. others who were otherwise similar.

These recent studies clearly suggest that socioeconomic adjusters are important not only for provider performance measurement but also broadly in the value-based payment paradigm.  The debate continues and time will tell if CMS continues its stance on the exclusion of socioeconomic factors for determining provider performance measures.  In the interim, let us know what you think.

Ashish