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Do Report Cards Predict Future Quality? The Case of Skilled Nursing Facilities

2018 Conference Presentation

Outcomes and quality United States

11 September 2018

Do Report Cards Predict Future Quality? The Case of Skilled Nursing Facilities

Portia Cornell, Brown University, United States

David Grabowski, Harvard University, United States
Edward Norton, University of Michigan, United States
Momotazur Rahman, Brown University, United States


Background and objectives: Report cards are intended to improve consumer decision-making and foster a market for quality. However, inadequate risk adjustment of report card measures often biases comparisons across firms. We test whether skilled nursing facility (SNF) star ratings causally predict quality outcomes.

Method: We exploit variation over time in the distance from a patient’s residential ZIP code to SNFs with different ratings to estimate the causal effect of admission to a higher-rated SNF on health care outcomes, including mortality. We ask, what effect do higher star ratings have on mortality, hospital readmissions, and length of stay for post-acute patients? The local average treatment effect for compliers is the effect of choosing a higher-rated nursing home because it happens be closer to where one lives. We use data from nearly 1.3 million new SNF Medicare patients in 2012-13.

Results: We found that patients who go to higher-rated SNFs achieved better outcomes, supporting the validity of the SNF report card ratings. Our methods also allow us to estimate an effect for each day post discharge. The effects of increased star ratings are not transitory, but generally increase in strength over time. Although the magnitudes of the effects are not enormous, nor are they miniscule. The mortality effect, for example, is a 5.8% reduction in days of death over the first six months. All these results are strongly statistically significant.

Implications and conclusion: There are important implications for the many pay-for-performance programs that the Centers for Medicare and Medicaid Services (CMS) has implemented over the last several years. These payment models create an incentive for hospitals to develop relationships with SNFs that can reasonably shorten the length of SNF stay while also reducing the likelihood of rehospitalization. As these payment models are expanded and shift from voluntary to mandatory participation, meaningful Star ratings will be a key source of information for hospitals looking to identify providers of high-value post-acute care. Therefore it is imperative to test whether the star ratings have a causal effect on meaningful patient outcomes, including mortality. Our results imply that if a hospital can direct patients to higher-rated SNFs (for those patients for whom it is appropriate to be discharged to SNF) that there will be a lower readmission rate, lower mortality, and more time at home. Therefore, hospitals have financial incentives to help patients choose a better SNF, leading to better outcomes for all.