Spurred by federal policy makers, US hospitals have made substantial efforts to address the problem of high rates of patients being readmitted to the hospital within 30 days of discharge. Underlying this policy focus is a straightforward idea: when patients are discharged from the hospital, with some exceptions, they shouldn’t have to return within 30 days. The Hospital Readmissions Reduction Program (HRRP), part of the Affordable Care Act (ACA), codified this notion by penalizing hospitals with higher-than-expected readmission rates up to 3% of their total Medicare payments.
The early evidence on HRRP’s effects was largely positive. Readmission rates declined nationally and the Centers for Medicare & Medicaid Services (CMS) touted these results as evidence that the ACA had begun to bend the cost curve. From 2008 through 2013, the likelihood of a Medicare beneficiary being readmitted within 30 days decreased from 19.0% to 17.8%, translating to hundreds of millions of dollars in savings to Medicare.
However, new evidence is raising concerns about both the penalty program and the readmissions measure in general. We have known for some time that HRRP primarily penalizes academic and safety-net hospitals. While many saw this as proof that the readmissions measure did not adequately account for severity of illness or patients’ socioeconomic status, HRRP supporters argued that safety-net and major teaching hospitals were likely just providing worse care. Now we have more definitive data confirming what has been widely suspected: much of what drives readmissions is the underlying patient population.
A new study published in JAMA Internal Medicine found that patients who are sicker, poorer, less educated and who have fewer social supports are readmitted far more often than other patients. More pointedly, the findings confirm that hospitals receiving the bulk of readmission penalties have a disproportionate number of these high-need patients and that most of the patient characteristics associated with high readmission rates are not included in Medicare’s current risk-adjustment methods. Thus, HRRP penalizes hospitals based on their underlying patient population—something hospitals cannot control—rather than on their performance.
These findings are not surprising. The frequency with which patients are readmitted is a utilization measure, not a quality measure—an important distinction. It is unsurprising that people who are sicker, have more complex illness, or have fewer social supports use more health care services. Utilization measures quantify how often health care services are used, but provide no insights into the appropriateness of the services. They don’t distinguish between necessary utilization that occurred despite high-quality care and utilization that results from failure in the discharge process or care transitions.
Additionally, new data have emerged showing that the decrease in the readmission rate may be partly due to changes in coding, not improvements in care. More than a third of the reduction in readmissions is due to an increase in classifying patients admitted to the hospital as “observation status,” an administrative designation that allows for in-hospital care without counting as a readmission. Furthermore, the proportion of patients returning to the emergency department after discharge has actually increased for some conditions, but many of these patients are not being readmitted within the 30-day time period.
These findings are troubling. Although many hospitals have clearly taken steps to improve discharge planning (such as clarifying a patient’s discharge instructions) and coordination of care with a patient’s primary care physician and other clinicians, others appear to have taken the easier path of reclassifying patients as observation to avoid readmitting them from the emergency department.
Measuring What Matters
These new data raise important questions about HRRP and whether we are actually measuring what matters to patients. During an acute illness, patients prioritize survival, maintaining functional status, cognitive clarity, being treated with dignity, and avoiding pain. Avoiding hospital readmission, while important, is likely a lower priority for patients.
Advocates of HRRP have argued that the readmissions measure is useful not because readmissions are bad per se but because it embeds accountability in the system. Hospitals, no longer able to abdicate responsibility for patients after they leave, instead remain accountable for what happens to patients in the postdischarge period. More resources are being dedicated to communicating with postdischarge rehabilitation facilities and with patients directly when they are at home. This shift in mindset is surely good for patients.
HRRP clearly has substantial shortcomings and is inconsistent with patient priorities, but by getting hospitals to focus on accountability, it has improved discharge planning and care coordination, at least at some institutions. Can we keep the benefits while addressing the underlying problems?
We could begin with accounting for socioeconomic status, and a recent JAMA article advocated for legislation that would require CMS to do so. There is broad political agreement in this area because it’s the obvious thing to do.
But how do we address the more fundamental problem, that avoiding hospital readmissions within 30 days of discharge doesn’t always equal high-quality care and often incentivizes gaming? Might we be able to build measures that create accountability while still focusing on what matters to patients?
One approach might be to expand our use of bundled payments. Under bundled payments, hospitals receive one payment for all services associated with an episode of care, including inpatient, postacute care, and outpatient physician services. The CMS has been experimenting with payment bundles, but much of the effort has focused on surgical conditions. It is time to be bolder with bundled payments for medical conditions, such as heart failure and pneumonia.
For this effort to be successful, 3 principles are important. First, bundles should encompass a broad range of medical conditions, not a select few. Second, given that 30 days is an arbitrary line in the sand and lacks a clinical basis (making it too long for some conditions and too short for others), the length of the bundle should be clinically guided and empirically derived. An average patient admitted with pneumonia may take as long as 45 or 60 days before he or she is back to baseline, whereas a patient admitted for gastrointestinal hemorrhage might return to baseline within 15 days. Finally, a robust set of quality measures—not just mortality but also complications, functional status, pain, patient experience—must be tied to bundled payments, so hospitals don’t save money by skimping on care.
Formulating bundles for medical conditions will be hard. We lack a strong scientific base for how best to do it, and key questions remain unanswered. Should certain services be excluded, such as coronary artery bypass surgery in an acute myocardial infarction bundle? How do we choose the optimal time period? Who receives the payment and how is it distributed? How do we ensure that we invest in the kind of quality measures that will enable us to deliver high-value health care?
These are important questions that require careful study as bundles are rolled out. But we’ve done this before: in the 1980s, we successfully shifted from piecemeal to bundled hospital payments. Bundling over a clinical episode will undoubtedly be harder, but it will be better for patient care. And when it comes to measuring and paying for high-value health care, doing what is easy is no substitute for doing what is right.
About the author: Ashish K. Jha, MD, MPH, is K. T. Li Professor of Global Health and Health Policy at the Harvard T. H. Chan School of Public Health and a practicing internist at the Veterans Affairs Boston Healthcare System. He received his MD from Harvard Medical School and was trained in Internal Medicine at the University of California, San Francisco. He received his MPH from Harvard School of Public Health. Dr Jha’s major research interests lie in improving the quality and costs of health care. His work has focused on 4 primary areas—public reporting, pay-for-performance, health information technology, and leadership—and the roles they play in fixing the US health care system.
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