Impact of time from discharge to readmission on outcomes: an observational study from the US National Readmission Database

Introduction

Medicare covers 64 million Americans, accounting for 21% of the gross national product.1 2 Hospital readmissions result in high economic, societal and health costs. In the previous fee-for-service model of the Centers for Medicare and Medicaid, health systems had no incentive to minimise readmissions. In 2007, the Medicare Payment Advisory Commission assembled specialist political appointees who advised Congress that the high rates of readmissions (13.3% of Medicare beneficiaries) may be a target for health spending remediation.3

US policy-makers targeted the metric of 30-day risk-standardised readmission rates (RSRRs) to reduce healthcare costs. The Patient Protection and Affordable Care Act of 2010 enacted the Hospital Readmissions Reduction Programme (HRRP), an approach to reduce readmissions by financially penalising hospitals with higher than average 30-day RSRR. To improve transparency and promote informed patient choice in health systems, public reporting of RSRRs began in June 2009. HRRP readmission penalties went into effect starting fiscal year 2013.4 5

Initially targeting heart failure (HF), acute myocardial infarction (AMI) and pneumonia (PNA), HRRP penalties could be up to 3% of a hospital’s Medicare reimbursements, thus affecting all payments and not just those related to the target conditions, providing a strong incentive to decrease readmissions.6 Not only was there no reward for achieving targets, but there was also a moving baseline due to changes in national trends of readmission rates. Thus, a hospital could face penalties even with improved readmission rates if their improvement was less than others.7 8

At its announcement, many health systems and analysts expressed concerns about unintended consequences, especially for the most vulnerable patients, less resourced systems and safety net health organisations. There was also concern about impacts on the quality of care delivered, including premature discharge of patients in a system prioritising readmissions over survival.9 ‘Gaming’ of the system from increasing observation stays, delaying readmissions beyond discharge day 30th and inappropriate triage strategies in emergency departments to achieve lower readmission rates may have avoided penalties but adversely impacted public health. A series of independent reports have now suggested that implementation of the HRRP was associated with an increase in 30-day, 90-day and 1-year risk-adjusted HF mortality in the USA with a reversal in the decade-long trend of declining HF mortality.7

Investigations into the impacts of the policy decision have shown variable results but essentially minimal improvement in publicly reported readmission trends. Reviews of the data from 2006 to 2012 showed no measurable change in 30-day readmissions for PNA, HF and MI.10 Even beyond, the policy had limited success in achieving its primary objective of reducing readmissions as the achieved reduction in HF readmissions was much smaller (~9%) than anticipated (~25%) with some of the decreases in RSRRs attributable to the artefact of administrative upcoding post-HRRP rather than an actual decline in readmissions. Initially, there was a decrease in reported readmissions (23.5% in 2008 to 21.4% in 2014), but systems could have quickly identified broken processes or target populations and implemented more successful strategies.11 There could have also been an artifactual component with increased use of observation status for those patients presenting after an index hospitalisation, eliminating tracking of readmissions.12 Some of the variability in readmission rates across health systems could also suggest areas for improvement in the discharge and postdischarge care process.13 14 These could include discharge care plans, coordination with primary care physicians, discharge instructions and reduction of inpatient complications.13 14

Methods

Discussion

Transitions of care, especially discharges, can be a vulnerable time for patients. Despite sizeable efforts to decrease readmissions across the USA, analysis of a large database demonstrated inconsistent findings with readmissions actually increasing for CABG and THA. Patient factors played a significant role as well with non-modifiable traits such as male gender and increased age increasing the risk for readmission. Other factors such as non-elective admissions could be explained by the fact that these individuals are likely sicker than those patients who can be scheduled for elective procedures. Readmitted patients as compared with those who were not readmitted were generally of a lower socioeconomic status, as demonstrated by lower income and a higher per cent enrolment in Medicaid. Healthcare disparities are not novel and it is not surprising that vulnerable patients with less social equity had an association with higher rates of readmissions and more complications. As an observational study, causation cannot be determined but directionality points to these as risk factors in readmissions.

Clinicians have not routinely been reliable judges of discharge readiness, with historical readmission rates of almost 20% for Medicare patients.18 19 Readmissions can be traumatic for patients and exact a significant cost on the healthcare finances, with the cost of readmissions in 2020 being 12.4% higher than the index admission (US$16 300 vs US$14,500)20 Addressing preventable hospital readmissions has been a national priority for years with large datasets, multiple interventions and toolkits developed.16 21 Single-component interventions are less successful at reducing readmissions significantly, and even multitiered interventions for patients discharged to postacute care facilities, such as enhanced communication, medication safety, advanced care planning and enhanced training to manage medical conditions, have had variable success. Those discharged to home may benefit from more robust home-care services, mental healthcare, caregiver support, community partnerships, telehealth and additional transitional care personnel focusing on ensuring continuity of care during transitions. Still, there has been no silver bullet to decrease readmissions.22

Despite these overarching strategies and years of research on readmissions, the association of increased readmission rates among patients receiving CABG or THA call into question the overall success of the HRRP. CABG patients are known to be a high-risk patient population, and predictive risk factors for readmission have been identified, including age, prior HF or MI, total albumin before surgery and history of diabetes.23 Patients undergoing THA have an association with an even greater increase in readmission rate. While differences in surgical techniques and underlying patient comorbidities may account for some readmissions, as THA resulted in higher readmission rates compared with open reduction internal fixation, this is certainly not the only factor in a complex equation.24 Prior studies suggest that risk factors for these populations correlate with health disparities such as non-private insurance (Medicare or Medicaid), identifying as black or living in a low-income area.20 25 26

Hospital readmission rates and reasons vary depending on disease and patient-specific characteristics.27 Infection and falls are among the top reasons for readmission after THA28 while infection, HF and arrhythmia were the most common after CABG.29 For those readmissions attributable to postoperative complications, the health system is penalised twice: once for the readmission and again through pay-for-performance programmes centred on postoperative complications such as surgical site infections.30 Another concerning trend is associated with readmission factors beyond the hospital’s control, such as ileus, falls and readmissions unrelated to the initial admission.30 These critical outliers, CABG and THA, suggest that evidence-based risk factor identification and tailored approaches for individual conditions may be effective strategies to optimise patient outcomes. Still, a penalty system likely has unintended but negative consequences on the health system and downstream patient care and little effect on meaningful readmission reduction.

Demographic differences predicting increased rates of readmission include being older and male. Older age is an explicable risk factor, likely associated with increased comorbidity, frailty and possibly more significant social needs. However, the association of male sex with increased readmission has not been shown in meta-analyses and other studies.29 31 32 Socioeconomic considerations were also significantly predictive of readmission. Those with a lower reported income or on Medicaid were at higher risk.26 31 Such risk factors are not modifiable and could lead hospitals to preferentially screen patients for surgery based on these characteristics, ultimately harming patients and contributing to health inequities.

Care at teaching institutions was also a risk factor for readmission, like many other extensive studies.28 There are many unique aspects of teaching hospitals that may contribute beyond care from trainees that could affect this. Teaching institutions are also frequently safety net hospitals and essential institutions in communities. Teaching hospitals also have a great deal to lose with readmissions. Revenue gains from an avoided readmission were 10%–15% greater for significant teaching hospitals than non-teaching hospitals. Thus, without the HRRP, systems would have a financial reason to minimise readmissions.33 This is not a universally consistent finding, however, with some studies reporting no association with procedure volume, hospital size, hospital quality and teaching status.32

Although this database study could not assess the severity of illness, the implication that readmitted patients are a sicker population may be inferred as these patients incurred a longer LOS. Readmitted patients’ mortality risk was similarly elevated, but the timing of readmission determined the degree of mortality risk. Those readmitted very soon after discharge (within 10 days) had the highest mortality. These individuals may have had very severe conditions that rapidly developed or could have had incomplete recovery from the primary admission. While there may be modifiable opportunities in quality patient care management, an outcome of mortality may have many additional causes leading to adverse outcomes beyond premature discharge.

General population differences among the readmitted and non-readmitted groups may inform some of these tailored interventions among all groups. Many studies have sought to identify predictors of readmission that may be amenable to intercessions, although most readmission risk prediction models performed poorly.34 Newer models using mobile data streams35 and machine learning36 may have improved prediction capabilities over traditional systems such as LACE. Patient-centred models of care for hospital discharge centred on these risk factors may be more effective at moderating change.37

Aspects of the policy may be considered successful. The decrease in readmission rates for five of the seven conditions could be seen as a success, but none achieved readmission rates under 1%. This non-zero readmission rate is likely contingent on factors beyond the hospital’s control, not least of which may be the diminishing social support structures and family proximity and availability. Patients need assistance with daily personal and medical care, transportation, and support navigating the health system after discharge. Patients without solid social support after discharge have experienced increased hospital readmissions.38 Additionally, trends in reduced readmission rates were shown to be similar in Canada despite no penalties assessed on their hospitals.39

Given the discrepant results, the policy should be reviewed for its utility in the current healthcare landscape. Nine in 10 general acute care hospitals have been penalised at least once in the past decade, and those hospitals with more low-income beneficiaries and teaching hospitals have experienced a disproportionate share of the penalties.6 Average HRRP penalties have not declined despite improved readmission rates since the programme’s inception. Thus, the HRRP has saved the government billions of dollars, but impacts on patients with various conditions have been less specific.40 The high rate of hospital closures may further exacerbate quality care delivery.41 Priority alignment should be recalibrated given that the HRRP-exacted readmission penalties are 15 times higher than penalties for 30-day mortality. While readmission is undoubtedly an outcome patients would relish, focusing on mortality outcomes may be more beneficial. Creating a system of financial incentives rather than penalties, which is not linked to the performance of other hospitals, may generate sustainable and positive patient outcomes.