In 2011, 3.3 million hospital readmissions, with an associated cost of $41.3 billion, made reducing hospital readmissions a priority of the Affordable Care Act reform. To address the problem, Medicare created the Hospital Readmissions Reduction Program, which penalizes acute-care hospitals whose 30-day readmission rates are high relative to other facilities. The HRRP tracks readmissions for Medicare patients admitted initially for six targeted conditions: heart attack, heart failure, pneumonia, chronic obstructive pulmonary disease (COPD), elective hip and knee replacement, and coronary artery bypass graft (CABG).
Under the program, hospital readmissions have declined, but as with any attempt at systemic reform, there have been unexpected results, questions about how the data are captured and interpreted, and an abundance of criticism along with numerous appeals for policy change. To understand these challenges, it is important to understand how readmission rates are determined and how penalties are assessed.
Hospital Readmission Rates — How they are Determined by CMS
To calculate hospital readmission rates, CMS looks at three previous years of data. For the first two years of the program (FY 2013 and FY 2014), only readmissions for patients initially hospitalized for three conditions were tracked—acute myocardial infarction (AMI), heart failure (HF), and certain types of pneumonia (PN). In years three, four, and five of the program, the conditions were expanded. Chronic obstructive pulmonary disease (COPD) and elective primary total hip and/or total knee arthroplasty (THA/TKA) were included in FY 2015 and FY 2016. Coronary Artery Bypass Grafting (CABG), as well as additional types of pneumonia, were added in FY 2017.
Since Medicare’s readmission definition is any unplanned admission to any hospital within 30 days after discharge regardless of the reason for the new admission, even admissions unrelated to the original condition, or those that occur at different hospitals, count when CMS computes readmission rates. The only exception is for planned admissions.
After gathering readmission data for the six targeted conditions, CMS then adjusts for demographic factors such as age and overall health of the hospital’s patient population. It compares each hospital’s readmission rate to an average of other hospitals and then calculates its ERR, or excess readmission ratio, to determine the rate at which hospitals will be penalized.
Medicare Readmission Penalties
CMS reduces all of a hospital’s payments for Medicare admissions based on its ERR, not just payments for readmissions, and not just for the six targeted conditions. Hospitals with an ERR of one or less are not penalized. For hospitals with ERRs greater than one, the higher the ERR, the greater the rate of penalty. CMS caps penalties at 3% of a hospital’s reimbursement for its Medicare patient admissions. According to Kaiser, in FY 2017, the average hospital adjustment (among all hospitals) was -0.58%. The average hospital penalty (among penalized hospitals only) was -0.74%. Only 1.8% of hospitals had the maximum penalty of 3% applied. The penalty rate is applied to reimbursement for all of a hospital’s Medicare admissions for the subsequent year.
As a result of feedback that hospitals with a higher share of low-income patients are unfairly penalized, the 21st Century Cures Act, signed into law on December 2016, makes a significant change to the way a hospital’s performance is evaluated. Beginning in FY 2019, hospitals will be divided into five peer groups which means they will be compared to other hospitals with a similar proportion of patients who are eligible for both Medicare and Medicaid, rather than to a national average.
Of the 3,241 hospitals that were evaluated under the hospital readmissions reduction program in 2018, 80% or 2,573 of them will have penalties levied against them for Medicare inpatient stays occurring between October 2017 and September 2018. This represents a reduction in reimbursements for hospitals of $564 million, up from the $528 million in 2017.
HRRP — What Does the Data Show?
In January 2018, Medicare Payment Advisory Commission (MedPAC) analysts presented findings of their analysis on the HRRP ahead of their report due to Congress in June. According to their data, both raw and risk-adjusted readmission rates declined for conditions covered by the HRRP.
Earlier studies also tracked improvement. According to an Obama administration study, readmissions for targeted conditions fell from 21.5% in 2007 to 17.8% in 2015. Additionally, readmissions for targeted conditions fell significantly faster at hospitals that were subject to the Hospital Readmissions Reduction Program than those that were not, and readmissions for conditions covered by the HRRP were reduced more than non-covered conditions.
This data could indicate that the HRRP is responsible for reducing readmissions. But legislating, tracking, and analyzing something so complex is no easy undertaking, and indeed the program comes with its share of questions and criticisms.
Hospital Readmissions Reduction Program — Replete with Criticism
Given the substantial financial impact of the HRRP and the complicated nature of hospital readmissions, critics cite numerous areas where the program falls short. As expected, policy discussions are on-going in order to address some of the controversies.
Risk-adjustment, one of the biggest debates, is partially addressed by the 21st Century Act mentioned above. Although not a panacea due to new concerns around effectively lowering standards for some peer-groups as well as state variation in Medicare eligibility requirements, it does address the current gap by allowing for variation in socioeconomic and community-level factors.
Another factor keeping policy discussions energized is whether the current method of calculating penalties based on national averages is better than setting fixed rate-reduction targets. The former means that even hospitals that significantly reduce their readmission rates can incur penalties if those reductions are less than the national averages (or, going forward, averages for their peer-group). This not only penalizes improvement, it makes HRRP harder to manage and forecast against. On the other hand, by setting fixed-rate targets, it is also possible that the rates would have the unintended consequence of setting a floor for improvement without built-in incentives to make continuous improvements.
Critics also state that it is unfair to determine payment adjustments based on averages when many hospitals have a much larger share of low-income and multiple-comorbidity patients or do not have the same resources as larger or more urban hospitals to treat complex patients. In fact, hospitals that serve the fewest numbers of low-income Medicare patients are least likely to receive any penalty, and teaching and critical access hospitals, which tend to serve more socioeconomically disadvantaged populations and complex patients, have been penalized at higher rates. This means that the HRRP may be diverting resources away from the hospitals and patients who need them most, possibly resulting in heightened readmissions among those populations. While the new peer group stratifications based on dual Medicare and Medicaid eligibility should mitigate some of these factors, the HRRP will still not compare apples to apples under the changes when assessing penalties because Medicaid eligibility varies by state.
Detractors further argue that hospitals should not bear the full burden for hospital readmissions since numerous risk factors are outside their control and because other providers such as home health agencies, primary care physicians, and long-term care facilities play a significant role in whether patients are readmitted. Brand new research published in the Annals of Internal Medicine supports this analysis.
Another debate spurred by recent research indicates that some readmission reductions seen after implementation of HRRP may be attributed to changes in the way admitted patients were coded for severity of illness rather than the program itself. However, MedPac reports a 17% reduction in the risk-adjusted data and asserts that “Decline in risk-adjusted readmissions is largely real, not explained by coding.”
Perhaps most notable of the myriad criticisms, the HRRP may be having a fatal unintended consequence. Some research suggests that since sicker patients are at the greatest risk of being readmitted, the program may unintentionally discourage necessary admissions resulting in preventable deaths. Since it is not possible to readmit deceased patients, their deaths may be propping up the data on lower readmissions, skewing the results, and inadvertently promoting higher mortality rates.
Reducing Hospital Readmissions
Despite the bevy of criticisms, some hospital administrators and policymakers agree that progress has been made. Better patient care and outcomes have resulted from efforts to reduce hospital readmissions, and while it may seem that hospitals have little control over what happens once a patient leaves the facility, there are strategies hospitals can deploy to reduce unnecessary bounce-backs:
- Coach Patients on Discharge Instructions and Self-Management
Improve patient education procedures and create checklists to ensure patients understand post-care instructions and changes in medication and can also recognize red flags. Confirm patient comprehension and provide translation services for non-English-speakers.
- Provide Care Coordination and Care Setting Transition Planning
Utilize transitional care nurses (TCNs) and other care coordination professionals to smooth the transition to outpatient care. Coordinate closely to reduce common communication gaps between inpatient and outpatient providers. Also, actively engage with and educate family members, schedule follow-up appointments, and arrange for transportation to appointments.
- Perform Medication Reconciliation
During times of transition in care, new medications or changes to existing ones are common, putting patients at greater risk for adverse drug events (ADEs). A thorough examination and comparison of a patient’s regimen at admission, during stay, and at discharge can help prevent unintended complications and reduce readmissions.
- Tackle the Social Determinants of Health
The social determinants of health play a significant role in readmissions. Patients with little family support, low health literacy, a lack of transportation, and inability to afford medications or nutritious food are missing the resources that promote healing and prevent complications. Strive to offset these factors by supplying medications upon discharge and work with community partners who can provide social, emotional, financial, nutritional, and logistical support to low-income and socially isolated patients.
- Leverage Data
Identify higher-risk patients to effectively allocate resources by using demographic, psychographic, and geographic data along with hospital and payer data to detect and manage social, behavioral, and location-based risk factors. By understanding patients’ non-medical issues, hospitals can strategically allocate resources to vulnerable patients and more effectively manage factors not entirely within their control.
Hospital Readmissions Reduction Program’s Outlook
During the first six years of the hospital readmissions reduction program, readmissions have gone down as hospitals have implemented improvement strategies such as those listed above. Nevertheless, reductions in readmissions have begun to level off since 2015, suggesting that further improvements by hospitals alone are elusive. Hospital administrators, policymakers, payers, and community organizations must collaborate on innovative ways to reduce hospital readmissions such as providing free nutritious foods, promoting population health literacy, and addressing social isolation. Furthermore, they must work together to redistribute the responsibility for reducing readmissions more fairly and appropriately among all care providers positioned to affect change, and they must retool how the penalties are applied so that providers are rewarded for their breakthroughs and progress.