Reconsidering Hospital Readmission Measures
Current hospital readmission measures are part of the Centers for Medicare & Medicaid Services Five-Star Quality Rating System but are inadequate for reporting hospital quality. We review potential biases in the readmission measures and offer policy recommendations to address these biases. Hospital readmission rates are influenced by multiple sources of variation (eg, mix of patients served, bias in the performance measure); true differences in quality of care are often a much smaller source of this variation. Thus, variation from caring for large proportions of socioeconomically disadvantaged or tertiary-care patients will bias a hospital’s ratings. Ratings aside, readmission measures may indirectly harm patients because low readmission rates do not correlate with reduced mortality, yet the Five-Star Quality Rating System weighs readmission equally with mortality. We propose that hospital quality rankings not use readmission measures as currently constructed.
© 2017 Society of Hospital Medicine
Revisiting the Hospital Readmission Measures
Given significant bias in the hospital readmission measures and the ethical challenges imposed by reducing readmissions, potentially at the expense of survival, we believe CMS needs to take action to remedy the problem. First, CMS should drop hospital readmissions as a quality measure from its hospital rankings. Other hospital-rating groups and insurers should do the same. When included in payment schemes, readmissions should not be construed as a quality measure but as a utilization measure, like length of stay.
Second, the Department of Health & Human Services (HHS) should invest in maturing the hospital readmission measures to ensure construct, content, and criterion validity and reliability. No doubt the risk adjustment is complex and may be inherently limited using Medicare claims data. In the case of SES adjustment, for example, limited numbers of SES measures can be constructed from current data sources.8,13 There are other approaches to address this recommendation. For example, HHS could define a preventable readmission as one linked to some process or outcome of hospital care, such as whether the patient was discharged on an inhaler. The National Quality Forum used this approach to define a preventable venous thromboembolic event as one occurring when a patient did not receive appropriate prophylaxis. In this way, only hospital 1 in the 3 scenarios for the patient with COPD would be penalized. However, we recognize that it is not always simple to define specific process measures (eg, prescribing an inhaler) that link to readmission outcomes and that there may be other important yet hard-to-measure interventions (eg, patient and family education) that are important components of patient-centered care and readmission prevention. This is why readmissions are so challenging as a quality measure. If experts cannot define clinician behaviors that have a strong theory of change or are causally related to reduced readmissions, it is hard to call readmissions a modifiable quality measure. Another potential strategy to level the playing field would be to compare readmission rates across peer institutions only. For instance, tertiary-care safety net hospitals would be compared to one another and rural community hospitals would be compared to one another.14 Lastly, new data sources could be added to account for the social, community-level, public health, and personal health factors that heavily influence a patient’s risk for readmission, in addition to hospital-level factors. Appropriate methods will be needed to develop statistical models for risk adjustment; however, this is a complex topic and beyond the scope of the current paper.
Third, HHS could continue to use the current readmission measures as population health measures while supporting multistakeholder teams to better understand how people and their communities, public health agencies, insurers, and healthcare providers can collaborate to help patients thrive and avoid readmissions by addressing true defects in care and care coordination.
While it is understandable why policy makers chose to focus on hospital readmissions, and while we recognize that concerns about the measures were unknown when they were created, emerging evidence demonstrates that the current readmission measures (particularly when used as a quality metric) lack construct validity, contain significant bias and systematic errors, and create ethical tension by rewarding hospitals both financially and reputationally for turning away sick and socially disadvantaged patients who may, consequently, have adverse outcomes. Current readmission measures need to be reconsidered.
Acknowledgments
The authors thank Christine G. Holzmueller, BLA, with the Armstrong Institute for Patient Safety and Quality, Johns Hopkins Medicine, for her assistance in editing the manuscript and preparing it for journal submission.
Disclosure
Dr. Pronovost errs on the side of full disclosure and reports receiving grant or contract support from the Agency for Healthcare Research and Quality, the Gordon and Betty Moore Foundation (research related to patient safety and quality of care), the National Institutes of Health (acute lung injury research), and the American Medical Association Inc. (improve blood pressure control); honoraria from various healthcare organizations for speaking on patient safety and quality (the Leigh Bureau manages engagements); book royalties from the Penguin Group for his book Safe Patients, Smart Hospitals; and was receiving stock and fees to serve as a director for Cantel Medical up until 24 months ago. Dr. Pronovost is a founder of Patient Doctor Technologies, a startup company that seeks to enhance the partnership between patients and clinicians with an application called Doctella. Dr. Brotman, Dr. Hoyer, and Ms. Deutschendorf report no relevant conflicts of interest.
