A Systematic Review and Implications for Policy
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Friday, September 9, 2022 | The Latest Research, Commentary, And News
From Health Affairs

Dear John,

Today's newsletter is written by Teresa Rogstad, one of the authors of
the article "Social Risk Adjustment In The Hospital Readmissions
Reduction Program: A Systematic Review And Implications For Policy
."

Social Risk Adjustment In the Hospital Readmissions Reduction Program

I am a semi-retired medical writer and consultant with a long-standing
desire to apply the systematic review skills I developed conducting
health technology assessments to health delivery and health policy
questions.

The systematic review that colleagues and I published in the September
issue of Health Affairs shows the value of this form of secondary
research in health policy.

I am very grateful for the encouragement and initial guidance provided
by Rajender Agarwal (see prior examples of systematic reviews led by
Agarwal and published by Health Affairs: Medicare Advantage versus
Traditional Medicare

and the impact of bundled payments
)
and to the four colleagues who joined me in this unfunded but
labor-intensive project.

Our team wanted to explore social risk adjustment in the context of
value-based payment.

Policy experts increasingly acknowledge the research showing that
factors such as low income, food insecurity and inadequate housing are
associated with poorer health outcomes, independent of conventional risk
adjustment measures.

But there is considerable controversy over how and whether provider
payment methods should take this association into account.

The evidence we reviewed suggests that social risk adjustment achieves
more equitable provider reimbursement without unintended consequences.

We focused on the CMS Hospital Readmissions Reduction Program (HRRP).

Under the HRRP, a hospital receives an annual penalty (reduced
reimbursement) if its adjusted thirty-day readmission rates for any of a
small set of admission conditions are below the average for hospitals
with a similar patient mix.

Current HRRP methodology compares hospitals against only those hospitals
in the same quintile defined by proportion of patients dually eligible
for Medicaid and Medicare. This peer grouping methodology retains the
original CMS risk adjustment model.

Our objective was to synthesize the evidence concerning how HRRP peer
grouping and other approaches to social risk adjustment affect
readmission performance measures and financial penalties for hospitals
subject to the HRRP.

The controversy over social risk adjustment stems from two competing
goals.

One goal is fairness in provider reimbursement. It stands to reason that
hospitals with a relatively large proportion of socially vulnerable
patients (safety net hospitals) would find it more difficult to achieve
good health outcomes for their patient populations.

These hospitals are also usually characterized by fewer financial
resources and thus are limited in their ability to compensate for social
risks through enhanced care delivery.

Data collected soon after the HRRP went into effect, and prior to the
peer grouping approach, showed that safety-net hospitals received
disproportionately larger penalties.

The other goal contributing to the controversy is continuous improvement
in patient care. It is not clear whether the poorer outcomes achieved by
safety net hospitals are primarily due to the characteristics of the
patients served or to a pattern of lower-quality care delivery in safety
net hospitals.

Social risk adjustment could have the unintended effect of "adjusting
away" poor quality care. So, in our review we also looked for evidence
that might speak to this question.

Our team identified fourteen studies that served our objective. The
selected studies investigated one or more of three general approaches:
addition of social risk variables to the CMS risk adjustment model,
which we referred to as model augmentation; peer grouping (the current
approach used by HRRP); or a combination of model augmentation and peer
grouping.

In ten of the fourteen selected studies social risk adjustment reduced
adjusted readmission rates and/or penalties for safety net hospitals and
increased those measures or made no difference for hospitals serving
populations with the smallest proportion of socially vulnerable
patients.

Although study heterogeneity clinical populations and measurement
methods prevented a quantitative summary of outcomes across studies, the
general consistency in the direction of findings despite these
methodological inconsistencies strengthens the general conclusion of our
review.

An especially interesting discovery was evidence that the differences in
readmissions performance between safety-net hospitals and other
hospitals was primarily attributable to differences in patient
characteristics rather than differences in the quality of care or other
hospital characteristics.

Three of four studies that addressed this question came to this
conclusion.

Two studies provided particularly compelling evidence by using fixed
effect hospital variables, which allowed any potential systematic
differences in quality of care to influence adjusted readmission rates
while still adjusting for patient-level social risk and other
characteristics.

The evidence regarding patient versus hospital effects speaks to the
skepticism often voiced about the feasibility of expecting providers to
satisfy health-related social needs.

The evidence we reviewed suggests that the full answer to healthcare
inequities goes beyond provider responsibilities.

Some have argued that even though adjustments to payment models or
subsidies may be warranted for providers who disproportionately serve
more socially at-risk patients, public reporting should remain
transparent-that payers and patients need to know which hospitals
actually have higher readmission rates after adjusting only for
conventional risk factors.

However, a small body of research suggests that differences in outcomes
are influenced primarily by patient characteristics (clinical and
social) rather than differences in quality of care, at least in the
HRRP.

If this is generally the case, are performance measures that remain
unadjusted for a key set of patient characteristics fully transparent?

Would a failure to adjust for social risk lead to the false conclusion
that better health outcomes for socially at-risk patients could be
achieved if the patients just went to a different provider?

We trust our work underscores the need to consider these questions as
policy makers seek to foster efforts to address social determinants of
health.

If you enjoyed reading today's newsletter, you might also like our
Social Determinants of Health newsletter, which is available to Health
Affairs Insiders
.
Use discount code HAInsider10 to get $10 off if you sign up before
October 5.

Join Insider

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