Two new studies whose findings have been published as articles in the October issue of Health Affairs are implicitly challenging two fundamental assumptions undergirding the federal Hospital Readmissions Reduction Program (HRRP), which the Centers for Medicare and Medicaid Services (CMS) manages under terms of the Affordable Care Act (ACA). That program, which is being used, with payment reductions for the poorest-performing U.S. hospitals, is mandatory for all Medicare-participating inpatient hospitals, and the levels of penalties for poorly performing hospitals are rising every fiscal year.
Meanwhile, the two articles are questioning two fundamental assumptions about how the program is architected. The first article, entitled “Rethinking Thirty-Day Hospital Readmissions: Shorter Intervals Might Be Better Indicators Of Quality Of Care,” was written by a team of researchers: David L. Chin, Heejung Bang, Raj J. Manickam, and Patrick S. Romano; and those researchers conclude that the HRRP needs to shift away from a broad focus on 30-day readmissions, and instead look at the differences in readmissions during the first seven days following discharge, where they found dramatic variations in readmission, variations that they found leveled off tremendously as the 30-day timeframe approached a close. The second article, entitled “Hospital Readmissions Reduction Program: Safety-Net Hospitals Show Improvement, Modifications To Penalty Formula Still Needed,” by Kathleen Carey and Men-Yun Lin, looked at the readmissions reduction results among hospitals that the researchers determined to be safety-net hospitals, and those researchers conclude that CMS needs to drastically change the parameters of its HRRP, in order to account for the dramatically more compromised socioeconomic status of many patients in safety-net hospitals, in order both to be fair to those hospitals, and to adjust the program in order to achieve better outcomes overall.
So, let’s sort through some of what both teams of researchers have found, around the Medicare readmissions reduction program. As the team of researchers noted in the abstract for the first article, “Public reporting and payment programs in the United States have embraced thirty-day readmissions as an indicator of between-hospital variation in the quality of care, despite limited evidence supporting this interval. We examined risk-standardized thirty-day risk of unplanned inpatient readmission at the hospital level for Medicare patients ages sixty-five and older in four states and for three conditions: acute myocardial infarction, heart failure, and pneumonia. The hospital-level quality signal captured in readmission risk was highest on the first day after discharge and declined rapidly until it reached a nadir at seven days,” Chin et all noted. “The rapid decay in the quality signal,” the added suggest that most readmissions after the seventh day post-discharge were explained by community- and household-level factors beyond hospitals’ control. Shorter intervals of seven or fewer days might improve the accuracy and equity of readmissions as a measure of hospital quality for public accountability,” they conclude.
Getting down to the specifics of their analysis, David L. Chin et al state this: “The CMS condition-specific technical reports state: ‘Outcomes occurring within 30 days… can be influenced by hospital care and the early transition to the outpatient setting.’ The HRRP was built on this premise that hospitals’ scope responsibility should include post-discharge care coordination, although essentially no empirical evidence supports the use of a thirty-day readmission interval for assessing hospital-modifiable quality in all settings and clinical domains. Despite substantial economic impact on facilities, and potential impact on the care that patients receive, it is not clear whether hospitals can practicably affect care for such a long period after discharge.”
So here are the two key sets of findings. Per the first set of findings, the researchers found that the intracluster correlation coefficient (ICC), which represents the proportion of risk explained by hospitals (between-hospital variation) compared to the total risk in the population (all variation), “for all three specific medical conditions dropped rapidly from 2.7 percent (acute myocardial infarction), 1.6 percent (heart failure), and 3.2 percent (pneumonia) on the first day after discharge, to less than 1.0 percent (all three cohorts) by day four, reaching a minimum of 0.8 percent or less at seven days after discharge. Across all three of these measures,” the researchers write, “most of the hospital quality signal dissipated by the seventh day after discharge—for example, the ICC decreased between the first day and the seventh day by 78 percent, 48 percent, and 76 percent among patients with acute myocardial infarction, heart failure, and pneumonia, respectively.”
In layperson speak, that means simply this: though hospitals are being made responsible under the HRRP for readmissions to inpatient care through 30 days, the fact of this is that it is really only in the first seven days that such readmissions are effectively meaningful.
On the other hand, the researchers note that “Patients who resided in ZIP codes in the lowest household income quartile had higher thirty-day readmissions risk… Similarly, patients residing in the smallest rural communities, compared to the largest urban communities, experienced at least 41 percent greater thirty-day readmission risk.”
These findings in this first study speak to two major implications. First, CMS officials should strongly consider reworking the readmissions program to focus on the first seven days post-discharge, rather than the far longer 30-day period they are focused on at presents. Second, the blunt tool of generalized measurement is failing to take into account vast divergences in outcomes based on household income (using the statistically based proxy of zip code residence).
Second study focuses on safety-net facilities
Now, the second study, by Carey and Lin, adds further weight to the suggestion that CMS officials should do some rethinking on the HRRP. In their article in the same issue, those researchers note that “We measured hospitals’ improvement for each condition as the percentage-point change in the readmission rate between the first and fourth years of the program, for each combination of hospital and condition having a reported readmission rate in both years. We defined safety-net hospitals as the highest quartile of hospitals according to their percentage of patients eligible for Supplemental Security Income,” the write, “and we used Medicare’s healthcare Cost Report Information System (HCRIS) to identify those hospitals.”
The authors found a small but statistically significant difference in readmissions rates between safety-net hospitals (as they had defined them), and other hospitals. In 2016, for heart attack, the rates were 17.4 percent versus 17.0 percent; for heart failure, they were 22.9 percent versus 21.9 percent; and for pneumonia, they were 17.3 percent versus 17.0 percent. To some casual observers, these differences may not seem egregiously large; but, as these authors write, “Concern over the impact of the HRRP is widespread, and policy makers have recommended various approaches to leveling the play field for hospitals in the program. One option,” they write, “is formally adjusting the penalty algorithm for patients’ socioeconomic status.”
The bottom line? “In refining the HRRP,” Carey and Chin say, “policy makers should bear in mind that a penalty program may not provide the best lever for incentivizing performance improvement in safety-net hospitals. Hospitals face mixed incentives, and it is reasonable to assume that for some hospitals, the HRRP’s financial penalties may not provide sufficient motivation for reducing readmission rates.” Indeed, they assert, “CMS faces considerable challenges in designing an incentive program that will accomplish that goal without triggering adverse effects. It would be advisable for CMS to pay attention to characteristics of hospitals that succeed in reducing readmissions at it modifies and expands the HRRP.”
These two studies, taken together, should clearly give policy leaders pause, on two significant fronts. First, there is the fundamental question of whether federal healthcare officials are measuring the right time interval in the HRRP. And second, there is the issue of whether the program should be modified to prevent unexpected negative impacts on safety-net hospitals, the very hospitals already most pressured by policy and reimbursement dynamics.
In the meantime, all of these study findings also speak to the tremendous importance of strong information systems and analytics processes, as hospital leaders move further into a readmissions program that is putting increasing pressure, via growing payment cuts, on hospitals nationwide. And regardless of what modifications might be made to the Hospital Readmissions Reduction Program, there is no question that the time is now to leverage information systems and data analytics solutions to achieve success in the program as it now stands, particularly as the penalties in that program will only increase over time.