Hospital Readmissions Reduction Program Penalties Research Articles

Including socioeconomic status reduces readmission penalties to safety-net hospitals

ObjectiveMedicare’s Hospital Readmissions Reduction Program (HRRP) financially penalizes “excessive” postoperative readmissions. Concerned with creating a double standard for institutions treating a high percentage of economically vulnerable patients, Medicare elected to exclude socioeconomic status (SES) from its risk-adjustment model. However, recent evidence suggests that safety-net hospitals (SNHs) caring for many low-SES patients are disproportionately penalized under the HRRP. We sought to simulate the impact of including SES-sensitive models on HRRP penalties for hospitals performing lower extremity revascularization (LER). MethodsThis is a retrospective, cross-sectional analysis of national data on Medicare patients undergoing open or endovascular LER procedures between 2007 and 2009. We used hierarchical logistic regression to generate hospital risk-standardized 30-day readmission rates under Medicare’s current model (adjusting for age, sex, comorbidities, and procedure type) compared with models that also adjust for SES. We estimated the likelihood of a penalty and penalty size for SNHs compared with non-SNHs under the current Medicare model and these SES-sensitive models. ResultsOur study population comprised 1708 hospitals performing 284,724 LER operations with an overall unadjusted readmission rate of 14.4% (standard deviation: 5.3%). Compared with the Centers for Medicare and Medicaid Services model, adjusting for SES would not change the proportion of SNHs penalized for excess readmissions (55.1% vs 53.4%, P = .101) but would reduce penalty amounts for 38% of SNHs compared with only 17% of non-SNHs, P < .001. ConclusionsFor LER, changing national Medicare policy to including SES in readmission risk-adjustment models would reduce penalty amounts to SNHs, especially for those that are also teaching institutions. Making further strides toward reducing the national disparity between SNHs and non-SHNs on readmissions, performance measures require strategies beyond simply altering the risk-adjustment model to include SES.

The Long-Term Effect of Financial Penalties on 30-Day Hospital Readmission Rates.

Although the immediate effect of financial penalties imposed by the Hospital Readmissions Reduction Program (HRRP) was a decrease in 30-day hospital readmission rates, the long-term effects are unclear. The authors studied 30-day readmissions before and immediately after HRRP penalties and during the most recent period before the COVID-19 pandemic and examined whether readmission trends differed between penalized and non-penalized hospitals. Centers for Medicare & Medicaid Services hospital archive data and US Census Bureau data were used to analyze hospital characteristics, including readmission penalty status, and hospital service area (HSA) demographic information, respectively. These two datasets were matched by HSA crosswalk files, available through the Dartmouth Atlas files. Using data from 2005-2008 as baseline, the authors examined hospital readmission trends before (2008-2011) and after penalties (during three periods: 2011-2014, 2014-2017, 2017-2019). Mixed linear models were used to examine readmission trends through periods, and differences by hospital penalty status without and with adjustment for hospital characteristics and HSA demographic information. For all hospitals combined, rates for 2008-2011 vs. 2011-2014 were as follows: pneumonia, 18.6% vs. 17.0%; heart failure (HF), 24.8% vs. 22.0%; acute myocardial infarction (AMI), 19.7% vs. 17.0% (p < 0.001 for all three conditions). Rates for 2014-2017 vs. 2017-2019 were as follows: pneumonia, 16.8% vs. 16.8% (p = 0.87), HF, 21.7% vs. 21.9% (p < 0.001); AMI, 16.0% vs. 15.8% (p < 0.001). Compared to penalized hospitals, using difference-in-differences, non-penalized hospitals had a significantly greater increase for two conditions between the 2014-2017 and 2017-2019 periods: pneumonia 0.34%, p < 0.001; and HF 0.24%, p = 0.002. Long-term readmission rates are lower than pre-HRRP rates, with recent trends decreasing further for AMI, stabilizing for pneumonia, and increasing for HF.

Health care policy that relies on poor measurement is ineffective: Lessons from the hospital readmissions reduction program.

Health care policy that relies on poor measurement is ineffective: Lessons from the hospital readmissions reduction program.

Did the Hospital Readmissions Reduction Program Reduce Readmissions? An Assessment of Prior Evidence and New Estimates.

In this article, we provide a comprehensive, empirical assessment of the hypothesis that the Hospital Readmissions Reduction Program (HRRP) affected hospital readmissions. In doing so, we provide evidence as to the validity of prior empirical approaches used to evaluate the HRRP and we present results from a previously unused approach to study this research question-a regression-kink design. Results of our analysis document that the empirical approaches used in most prior research assessing the efficacy of the HRRP often lack internal validity. Therefore, results from these studies may not be informative about the causal consequences of the HRRP. Results from our regression-kink analysis, which we validate, suggest that the HRRP had little effect on hospital readmissions. This finding contrasts with the results of most prior studies, which report that the HRRP significantly reduced readmissions. Our finding is consistent with conceptual considerations related to the assumptions underlying HRRP penalty: in particular, the difficulty of identifying preventable readmissions, the highly imperfect risk adjustment that affects the penalty determination, and the absence of proven tools to reduce readmissions.

Social Determinants Matter For Hospital Readmission Policy: Insights From New York City.

This study assessed the impact of individual social risk factor variables and social determinants of health (SDOH) measures on hospital readmission rates and penalties used in the Centers for Medicare and Medicaid Services (CMS) Hospital Readmissions Reduction Program (HRRP). Using 2012-16 hospital discharge data from New York City, we projected HRRP penalties by augmenting CMS's readmission model for heart attack, heart failure, and pneumonia with SDOH scores constructed at each of four geographic levels and a measure of individual-level social risk. Including additional SDOH scores in the model, especially those constructed with the most granular geographic data, along with social risk factor variables substantially affects projected penalties for hospitals treating the highest proportion of patients with high SDOH scores. Improved performance occurred even after we included peer-group stratification in the HRRP model pursuant to the 21st Century Cures Act. Small improvements in model accuracy were associated with substantial shifts in projected performance. Our results suggest that CMS's continued omission of relevant patient and geographic data from the HRRP readmission model misallocates penalties attributable to SDOH and social risk factor effects to hospitals with the largest share of high-risk patients.

Adverse Discharge Outcomes Associated With the Medicare Hospital Readmissions Reduction Program Among Commercially Insured Adults.

It is unknown if changes in the rate of discharges against medical advice (DAMA) are related to the implementation of the Medicare Hospital Readmissions Reduction Program (HRRP). We performed an interrupted time series analysis of monthly DAMA rates per 1,000 discharges of all enrolled individuals 18-64 years old with a hospitalization between January 1, 2006, and December 31, 2015, in a commercially insured population. We performed a segmented linear regression with two interruptions: (1) April 2010 to coincide with the passage of the HRRP and (2) October 2012 to coincide with the implementation of HRRP penalties. There were 1,087,812 discharges representing 668,823 individuals over 120 months. The downward trend in monthly DAMA rates was reversed significantly after April 2010 with a sustained 0.1 increase in the monthly rate that continued after the implementation of penalties in October 2012. Allowing for the two interruptions, there was a statistically significant positive trend (0.10; 0.06-0.13, p < .01) in April 2010. Relative to the first interruption, there was no statistically significant change in the slope in October 2012; the estimated slope was -0.04 (-0.08 to 0.002). Monthly DAMA rates increased in anticipation of and after HRRP implementation, suggesting a potential relationship between the HRRP and DAMA.

Readmission Rates for Chronic Obstructive Pulmonary Disease Under the Hospital Readmissions Reduction Program: an Interrupted Time Series Analysis.

Hospital readmission rates decreased for myocardial infarction (AMI), heart failure (CHF), and pneumonia with implementation of the first phase of the Hospital Readmissions Reduction Program (HRRP). It is not established whether readmissions fell for chronic obstructive pulmonary disease (COPD), an HRRP condition added in 2014. We sought to determine whether HRRP penalties influenced COPD readmissions among Medicare, Medicaid, or privately insured patients. We analyzed a retrospective cohort, evaluating readmissions across implementation periods for HRRP penalties ("pre-HRRP" January 2010-April 2011, "implementation" May 2011-September 2012, "partial penalty" October 2012-September 2014, and "full penalty" October 2014-December 2016). We assessed discharged patients ≥ 40years old with COPD versus those with HRRP Phase 1 conditions (AMI, CHF, and pneumonia) or non-HRRP residual diagnoses in the Nationwide Readmissions Database. HRRP was announced and implemented during this period, forming a natural experiment. We calculated differences-in-differences (DID) for 30-day COPD versus HRRP Phase 1 and non-HRRP readmissions. COPD discharges for 1.2 million Medicare enrollees were compared with 22 million non-HRRP and 3.4 million HRRP Phase 1 discharges. COPD readmissions decreased from 19 to 17% over the study. This reduction was significantly greater than non-HRRP conditions (DID - 0.41%), but not HRRP Phase 1 (DID + 0.02%). A parallel trend was observed in the privately insured, with significant reduction compared with non-HRRP (DID - 0.83%), but not HRRP Phase 1 conditions (DID - 0.45%). Non-significant reductions occurred in Medicaid (DID - 0.52% vs. non-HRRP and - 0.21% vs. Phase 1 conditions). In Medicare, HRRP implementation was associated with reductions in COPD readmissions compared with non-HRRP controls but not versus other HRRP conditions. Parallel findings were observed in commercial insurance, but not in Medicaid. Condition-specific penalties may not reduce readmissions further than existing HRRP trends.

Association Between Financial Incentives in Medicare's Hospital Readmissions Reduction Program and Hospital Readmission Performance

The strongest evidence for the effectiveness of Medicare's Hospital Readmissions Reduction Program (HRRP) involves greater reductions in readmissions for hospitals receiving penalties compared with those not receiving penalties. However, the HRRP penalty is an imperfect measure of hospitals' marginal incentive to avoid a readmission for HRRP-targeted diagnoses. To assess the association between hospitals' condition-specific incentives and readmission performance and to examine the responsiveness of hospitals to condition-specific incentives compared with aggregate penalty amounts. This retrospective cohort analysis used Medicare readmissions data from 2823 US short-term acute care hospitals participating in HRRP to compare 3-year (fiscal years 2016-2019) follow-up readmission performance according to tertiles of hospitals' baseline (2016) marginal incentives for each of 5 HRRP-targeted conditions (acute myocardial infarction, heart failure, chronic obstructive pulmonary disease, pneumonia, and hip and/or knee surgery). Linear regression models were used to estimate mean change in follow-up readmission performance, measured using the excess readmissions ratio, with baseline condition-specific incentives and aggregate penalty amounts. Of 2823 hospitals that participated in the HRRP from baseline to follow-up, 2280 (81%) had more than 1 excess readmission for 1 or more applicable condition and 543 (19%) did not have any excess readmissions. The mean (SD) financial incentive to reduce readmissions for incentivized hospitals ranged from $8762 ($3699) to $58 158 ($26 198) per 1 avoided readmission. Hospitals with greater incentives for readmission avoidance had greater decreases in readmissions compared with hospitals with smaller incentives (45% greater for pneumonia, 172% greater for acute myocardial infarction, 40% greater for hip and/or knee surgery, 32% greater for chronic obstructive pulmonary disease, and 13% greater for heart failure), whereas hospitals with no incentives had increases in excess readmissions of 4% to 7% (median, 4% [percentage change for nonincentivized hospitals was 3.7% for pneumonia, 4.2% for acute myocardial infarction, 7.1% for hip and/or knee surgery, 3.7% for chronic obstructive pulmonary disease, and 3.7% for heart failure]; P < .001). During the study period, each additional $5000 in the incentive amount was associated with a 0.6- to 1.3-percentage point decrease, or up to a 26% decrease, in excess readmissions (P < .001). Regression to the mean explained approximately one-third of the results depending on the condition examined. The findings suggest that improvements in readmission avoidance are more strongly associated with incentives from the HRRP than with aggregate penalty amounts, suggesting that the program has elicited sizeable changes. Worsened performance among hospitals with small or no incentives may indicate the need for reconsideration of the program's lack of financial rewards for high-performing hospitals.

The association of hospital teaching intensity with 30-day postdischarge heart failure readmission and mortality rates.

To investigate risk-adjusted, 30-day postdischarge heart failure mortality and readmission rates stratified by hospital teaching intensity. A total of 709221 Medicare fee-for-service beneficiaries discharged from 3135 US hospitals between 1/1/2013 and 11/30/2014 with a principal diagnosis of heart failure. Hospitals were classified as Council of Teaching Hospitals and Health Systems (COTH) major teaching hospitals, non-COTH teaching hospitals, and nonteaching hospitals. Hospital teaching status was linked with MedPAR patient data and FY2016 Hospital Readmission Reduction Program penalties. Index hospitalization survival probabilities were estimated with hierarchical logistic regression and used to stratify index hospitalization survivors into severity deciles. Decile-specific models were estimated for 30-day postdischarge readmission and mortality. Thirty-day postdischarge outcomes were estimated by teaching intensity and penalty categories. Averaged across deciles, adjusted 30-day COTH hospital readmission rates were, on a relative scale ([COTH minus nonteaching]÷nonteaching), 1.63 percent higher (95% CI: 0.89 percent, 2.25 percent) than at nonteaching hospitals, but their average adjusted 30-day postdischarge mortality rates were 11.55 percent lower (95% CI: -13.78 percent, -9.37 percent). Penalized COTH hospitals had the highest readmission rates of all categories (23.99 percent [95% CI: 23.50 percent, 24.49 percent]) but the lowest 30-day postdischarge mortality (8.30 percent [95% CI: 7.99 percent, 8.57 percent] vs 9.84 percent [95% CI: 9.69 percent, 9.99 percent] for nonpenalized, nonteaching hospitals). Heart failure readmission penalties disproportionately impact major teaching hospitals and inadequately credit their better postdischarge survival.

Using machine learning to predict 30-day readmissions after posterior lumbar fusion: an NSQIP study involving 23,264 patients.

Unplanned preventable hospital readmissions within 30 days are a great burden to patients and the healthcare system. With an estimated $41.3 billion spent yearly, reducing such readmission rates is of the utmost importance. With the widespread adoption of big data and machine learning, clinicians can use these analytical tools to understand these complex relationships and find predictive factors that can be generalized to future patients. The object of this study was to assess the efficacy of a machine learning algorithm in the prediction of 30-day hospital readmission after posterior spinal fusion surgery. The authors analyzed the distribution of National Surgical Quality Improvement Program (NSQIP) posterior lumbar fusions from 2011 to 2016 by using machine learning techniques to create a model predictive of hospital readmissions. A deep neural network was trained using 177 unique input variables. The model was trained and tested using cross-validation, in which the data were randomly partitioned into training (n = 17,448 [75%]) and testing (n = 5816 [25%]) data sets. In training, the 17,448 training cases were fed through a series of 7 layers, each with varying degrees of forward and backward communicating nodes (neurons). Mean and median positive predictive values were 78.5% and 78.0%, respectively. Mean and median negative predictive values were both 97%, respectively. Mean and median areas under the curve for the model were 0.812 and 0.810, respectively. The five most heavily weighted inputs were (in order of importance) return to the operating room, septic shock, superficial surgical site infection, sepsis, and being on a ventilator for > 48 hours. Machine learning and artificial intelligence are powerful tools with the ability to improve understanding of predictive metrics in clinical spine surgery. The authors' model was able to predict those patients who would not require readmission. Similarly, the majority of predicted readmissions (up to 60%) were predicted by the model while retaining a 0% false-positive rate. Such findings suggest a possible need for reevaluation of the current Hospital Readmissions Reduction Program penalties in spine surgery.

Inaugural Readmission Penalties for Total Hip and Total Knee Arthroplasty Procedures Under the Hospital Readmissions Reduction Program

The Hospital Readmissions Reduction Program (HRRP) is a Centers for Medicare and Medicaid Services policy that levies hospital reimbursement penalties based on excess readmissions of patients with 4 medical conditions and 3 surgical procedures. A greater understanding of factors associated with the 3 surgical reimbursement penalties is needed for clinicians in surgical practice. To investigate the first year of HRRP readmission penalties applied to 2 surgical procedures-elective total hip arthroplasty (THA) and total knee arthroplasty (TKA)-in the context of hospital and patient characteristics. Fiscal year 2015 HRRP penalization data from Hospital Compare were linked with the American Hospital Association Annual Survey and with the Healthcare Cost and Utilization Project State Inpatient Database for hospitals in the state of Florida. By using a case-control framework, those hospitals were separated based on HRRP penalty severity, as measured with the HRRP THA and TKA excess readmission ratio, and compared according to orthopedic volume as well as hospital-level and patient-level characteristics. The first year of HRRP readmission penalties applied to surgery in Florida Medicare subsection (d) hospitals was examined, identifying 60 663 Medicare patients who underwent elective THA or TKA in 143 Florida hospitals. The data analysis was conducted from February 2016 to January 2017. Annual hospital THA and TKA volume, other hospital-level characteristics, and patient factors used in HRRP risk adjustment. The HRRP penalties with HRRP excess readmission ratios were measured, and their association with annual THA and TKA volume, a common measure of surgical quality, was evaluated. The HRRP penalties for surgical care according to hospital and readmitted patient characteristics were then examined. Among 143 Florida hospitals, 2991 of 60 663 Medicare patients (4.9%) who underwent THA or TKA were readmitted within 30 days. Annual hospital arthroplasty volume seemed to follow an inverse association with both unadjusted readmission rates (r = -0.16, P = .06) and HRRP risk-adjusted readmission penalties (r = -0.12, P = .14), but these associations were not statistically significant. Other hospital characteristics and readmitted patient characteristics were similar across HRRP orthopedic penalty severity. This study's findings suggest that higher-volume hospitals had less severe, but not significantly different, rates of readmission and HRRP penalties, without systematic differences across readmitted patients.

Impact of Hospital Readmissions Reduction Program Penalties on Hip and Knee Replacement Readmissions: Comparison of Hospitals at Risk of Varying Penalty Amounts.

Little is known about the impact of the U.S. Centers for Medicare & Medicaid Services' Hospital Readmissions Reduction Program (HRRP) expansion to include readmissions following elective primary total hip and knee replacements; the expansion was finalized in 2013 and was implemented in 2014. We examined whether hospitals at risk of relatively large penalties from this expansion experienced greater declines in joint replacement readmissions compared with hospitals at risk of smaller penalties. We used Medicare's 2009 to 2016 Hospital Compare data sets to examine the impact of the HRRP's expansion in the July 2013 to June 2016 period (post-expansion) compared with the July 2009 to June 2012 period (pre-expansion). The primary outcome was the hospital-level, 30-day, risk-standardized readmission rate (hereafter called the readmission rate) following joint replacement surgical procedures. We used the percentage of a hospital's total inpatient revenue attributed to Medicare (categorized into quartiles) to represent the risk of penalties. We used hierarchical linear regression models to examine the adjusted impact of the HRRP's expansion. Our study cohort included 2,326 acute care hospitals. In the pre-HRRP expansion phase, the mean readmission rate was 5.36% among hospitals with the highest proportion of Medicare revenues (quartile 4) and 5.46% among hospitals with the lowest proportion of Medicare revenues (quartile 1). With the HRRP expansion, the readmission rate declined by 18.92% (1.01 percentage points) among quartile-4 hospitals and by 17.97% (0.98 percentage point) among quartile-1 hospitals (p = 0.45). This nonsignificant difference in readmission rate declines between quartiles persisted in multivariable analysis (a decline of 18.41% [0.98 percentage point] in quartile 4 and a decline of 17.35% [0.94 percentage point] in quartile 1; p = 0.35). The HRRP's expansion to include joint replacements did not lead to greater reductions in postoperative readmissions among hospitals at risk of larger penalties in comparison with hospitals at risk of smaller penalties. Readmission rates were declining at similar rates among all hospitals, before and after the HRRP's expansion. Readmissions and complications following joint replacements are measures of the quality of surgical care. These events have important clinical and economic implications for patients and providers. This study is clinically relevant because it examines whether policy interventions, such as the HRRP, have the potential to reduce these unintended consequences of surgical care.

Thirty-Day Postdischarge Mortality Among Black and White Patients 65 Years and Older in the Medicare Hospital Readmissions Reduction Program

The Medicare Hospital Readmissions Reduction Program (HRRP) has disproportionately penalized hospitals that treat many black patients, which could worsen health outcomes in this population. To determine whether short-term mortality rates increased among black and white adults 65 years and older after initiation of the HRRP and whether trends differed by race. In a cohort study using an interrupted time-series analysis conducted from March 15, 2018, to January 23, 2019, in 3263 eligible acute care hospitals nationally, risk-adjusted mortality rates observed after Medicare started to impose penalties (October 1, 2012, to November 30, 2014) were compared with projections based on pre-HRRP trends (January 1, 2007, to March 31, 2010) among adults 65 years and older with acute myocardial infarction (AMI), heart failure (HF), or pneumonia. Observed-to-projected differences were then compared between racial groups. Hospital discharge during pre-HRRP and HRRP penalty periods. Thirty-day postdischarge all-cause mortality. In the 3263 acute care hospitals included in the analysis, black patients (627 373 index discharges) were more likely than white patients (5 845 130 index discharges) to be younger (mean [SD] age, 77.8 [8.3] vs 80.5 [8.2] years; P < .001), women (60.5% vs 53.7%; P < .001), dually covered by Medicare and Medicaid (45.7% vs 17.2%; P < .001), and treated at a penalized hospital (AMI, 82.8%; HF, 83.8%; and pneumonia, 82.6% vs 69.6%; 73.3%; and 71.7%; all P < .001). Pre-HRRP mortality rates for black vs white patients were 7.04% (95% CI, 6.75% to 7.33%) vs 7.47% (95% CI, 7.37% to 7.57%) for AMI, 6.69% (95% CI, 6.56% to 6.82%) vs 8.56% (95% CI, 8.48% to 8.64%) for HF, and 8.08% (95% CI, 7.88% to 8.27%) vs 8.27% (95% CI, 8.19% to 8.35%) for pneumonia. By the HRRP penalty period, observed mortality for AMI decreased more, relative to projections, among black than white patients (difference-in-differences, -1.65 percentage points; 95% CI, -3.19 to -0.10; P = .04). For HF, mortality increased relative to projections among white patients but not among black patients; however; mortality trends did not differ by race (difference-in-differences, -0.37 percentage points; 95% CI, -1.08 to 0.34; P = .31). For pneumonia, observed mortality was similar to projections in both racial groups, and trends did not differ by race (difference-in-differences, -0.54 percentage points; 95% CI, -1.66 to 0.59; P = .35). At both penalized and nonpenalized hospitals, mortality trends were similar or decreased more among black patients than white patients. In this study of patients 65 years and older, short-term postdischarge mortality did not appear to increase for black patients under the HRRP, suggesting that certain value-based payment policies can be implemented without harming black populations. However, mortality seemed to increase for white patients with HF and this situation warrants investigation.

Adjusting for social risk factors impacts performance and penalties in the hospital readmissions reduction program.

Medicare's Hospital Readmissions Reduction Program (HRRP) does not account for social risk factors in risk adjustment, and this may lead the program to unfairly penalize safety-net hospitals. Our objective was to determine the impact of adjusting for social risk factors on HRRP penalties. Retrospective cohort study. Claims data for 2952605 fee-for-service Medicare beneficiaries with acute myocardial infarction (AMI), congestive heart failure (CHF) or pneumonia from December 2012 to November 2015. Poverty, disability, housing instability, residence in a disadvantaged neighborhood, and hospital population from a disadvantaged neighborhood were associated with higher readmission rates. Under current program specifications, safety-net hospitals had higher readmission ratios (AMI, 1.020 vs 0.986 for the most affluent hospitals; pneumonia, 1.031 vs 0.984; and CHF, 1.037 vs 0.977). Adding social factors to risk adjustment cut these differences in half. Over half the safety-net hospitals saw their penalty decline; 4-7.5 percent went from having a penalty to having no penalty. These changes translated into a $17 million reduction in penalties to safety-net hospitals. Accounting for social risk can have a major financial impact on safety-net hospitals. Adjustment for these factors could reduce negative unintended consequences of the HRRP.

Comparison of the change in heart failure readmission and mortality rates between hospitals subject to hospital readmission reduction program penalties and critical access hospitals

The Hospital Readmission Reduction Program (HRRP), announced in 2010, penalizes hospitals with high readmissions for multiple conditions including heart failure. We compared heart failure readmission and mortality rates in hospitals exposed to HRRP financial penalties with critical access hospitals (CAHs) not subject to the penalty between 2005 and 2016 using 3-year moving averages from Hospital Compare. After HRRP introduction, CAHs experienced a 0.60% annual decrease (95% CI: -0.61 to -0.59%) in heart failure readmissions. HRRP-exposed hospitals experienced an additional 0.13% annual decrease (95% CI: -0.14 to -0.12%) compared with CAHs. The association between HRRP penalties and mortality varied with model specifications. Using CAHs as a control group, we found the introduction of financial penalties was only associated with modest reductions in readmissions and an uncertain association with mortality. Cluster-randomized rollouts of health care policy interventions will allow us to better evaluate the impact of our interventions.

Changes to Racial Disparities in Readmission Rates After Medicare’s Hospital Readmissions Reduction Program Within Safety-Net and Non–Safety-Net Hospitals

Although readmission rates are declining under Medicare's Hospital Readmissions Reduction Program (HRRP), concerns remain that the HRRP will harm quality at safety-net hospitals because they are penalized more often. Disparities between white and black patients might widen because more black patients receive care at safety-net hospitals. Disparities may be particularly worse for clinical conditions not targeted by the HRRP because hospitals might reallocate resources toward targeted conditions (acute myocardial infarction, pneumonia, and heart failure) at the expense of nontargeted conditions. To examine disparities in readmission rates between white and black patients discharged from safety-net or non-safety-net hospitals after the HRRP began, evaluating discharges for any clinical condition and the subsets of targeted and nontargeted conditions. Cohort study conducting quasi-experimental analyses of patient hospital discharges for any clinical condition among fee-for-service Medicare beneficiaries from 2007 to 2015 after controlling for patient and hospital characteristics. Changes in disparities were measured within safety-net and non-safety-net hospitals after the HRRP penalties were enforced and compared with prior trends. These analyses were then stratified by targeted and nontargeted conditions. Analyses were conducted from October 1, 2017, through August 31, 2018. Trends in 30-day readmission rates among white and black patients by quarter and differences in trends across periods. The study sample included 58 237 056 patient discharges (black patients, 9.8%; female, 57.7%; mean age [SD] age, 78.8 [7.9] years; nontargeted conditions, 50 372 806 [86.5%]). Within safety-net hospitals, disparities in readmission rates for all clinical conditions widened between black and white patients by 0.04 percentage point per quarter in the HRRP penalty period (95% CI, 0.01 to 0.07; P = .01). This widening was driven by nontargeted conditions (0.05 percentage point per quarter [95% CI, 0.01 to 0.08]; P = .006), whereas disparities for the HRRP-targeted conditions did not change (with an increase of 0.01 percentage point per quarter [95% CI, -0.07 to 0.10]; P = .74). Within non-safety-net hospitals, racial disparities remained stable in the HRRP penalty period across all conditions, whether the conditions were HRRP-targeted or nontargeted. Findings from this study suggest that disparities are widening within safety-net hospitals, specifically for non-HRRP-targeted conditions. Although increases in racial disparities for nontargeted conditions were modest, they represent 6 times more discharges in our cohort than targeted conditions.

Unintended Consequences of Hospital Regulation: The Case of the Hospital Readmissions Reduction Program

This paper examines the impact of the Hospital Readmissions Reduction Program (HRRP) on hospitals' admission decisions. HRRP provides incentives for hospitals to reduce readmissions by imposing penalties to hospitals that exhibited higher than average 30-day risk-adjusted readmission rates. Indeed, after HRRP was introduced in 2012, readmission rates have fallen by 1.2% on average across monitored conditions. In this paper, we show that part of this reduction may be due to hospitals admitting more patients for observation as opposed to inpatient admission. Under this classification, patients receive hospital-level care but do not count towards admissions for HRRP purposes. To show that this is the case, we combine four hospital-level datasets. We exploit variation in hospitals' financial exposure to HRRP due to: i) readmission performance relative to national average; and ii) financial constraints. We find that hospitals exposed to HRRP penalties increased observation bed usage by 16.9% more compared to non-penalized hospitals, and by as much as 40.6% if they were also financially constrained. A back-of-the-envelope calculation suggests that if just 10% of the change in observation admissions was done to avoid readmissions, the observed reduction in readmissions following HRRP would be 21% smaller than reported. Furthermore, if hospitals are indeed using observation admissions to avoid readmissions then one would expect that post-HRRP readmissions of patients originally discharged from the same hospital would have decreased at a higher rate compared to readmissions to hospitals other than the discharging hospital. Using a detailed patient-level dataset, we confirm that this is indeed the case.

Impact of Behavioral Health Screening on Proactive Identification of Patients at Risk for Hospital Readmission.

Improving the ability to predict which patients are at increased risk for readmission can lead to more effective interventions and greater compliance with CMS Hospital Readmissions Reduction Program (HRRP) requirements. This study evaluated the performance of a risk model that used data from a health system's electronic medical record (EMR) to predict all-cause readmission among adult inpatients with acute medical conditions, with a specific focus on the impact of including behavioral health screening data. The study included 39,155 unique adult patients admitted during 2015 to 4 acute care inpatient facilities within a nonprofit community-based health care system. The risk model integrated a comprehensive set of data elements including demographics, psychosocial characteristics, medical history, assessment results, and clinical events. Predictive models were constructed using a multivariable logistic regression with a stepwise selection approach. Among study participants, the mean age was 62.9 years, 48.0% were male, 31.2% had comorbid psychiatric conditions, and 6986 had medical conditions/procedures subject to HRRP penalties. Results from exploratory predictive analyses demonstrated that any patients with a Serious Mental Illness (SMI) diagnosis were 28% more likely to be readmitted within 30 days, and the likelihood of readmission associated with SMI increased to 56% for patients with medical conditions subject to HRRP penalties. As health care systems face increasing pressures to reduce readmissions and avoid CMS HRRP financial penalties, study results indicate the importance of including behavioral health data from EMRs and screening assessments for all inpatients to improve discharge planning and patient outcomes.

Will Hospital Peer Grouping by Patient Socioeconomic Status Fix the Medicare Hospital Readmission Reduction Program or Create New Problems?

In 2016 the U.S. Congress directed the Centers for Medicare & Medicaid Services (CMS) to implement the 21st Century Cures Act to fix a flaw in the Hospital Readmissions Reduction Program (HRRP). One section of the Act is intended to remove bias in calculating penalties for hospitals treating large percentages of low socioeconomic status (SES) patients. A study was conducted to analyze the effect of the introduction of SES hospital peer groups on the number and distribution of the hospitals being penalized. The CMS analysis files for the fiscal year 2017 HRRP final rule and Disproportionate Share Hospital adjustments were used to assign hospital peer groups. The median excess readmission ratios for hospital peer groups were calculated, and the resulting pattern of hospital penalties within peer groups was analyzed. The findings suggest that because CMS assigns individual HRRP penalties on six clinical conditions but proposes to assign hospitals to a single SES peer group based on all admissions, it will ignore substantial differences in the distribution of peer group medians across these conditions. For surgical cases, as expected, hospitals with fewer patients had higher readmission rates, while for medical cases, hospitals with fewer patients had fewer readmissions. These findings may result in distortion of the peer group adjustment intended to correct for SES. Hospital peer groups may create unintended redistributions of penalties through distortion of peer group medians. An observed relationship between lower-volume hospitals and fewer readmissions for medical conditions requires additional research to establish its basis.

Association of the Hospital Readmissions Reduction Program Implementation With Readmission and Mortality Outcomes in Heart Failure

Public reporting of hospitals' 30-day risk-standardized readmission rates following heart failure hospitalization and the financial penalization of hospitals with higher rates have been associated with a reduction in 30-day readmissions but have raised concerns regarding the potential for unintended consequences. To examine the association of the Hospital Readmissions Reduction Program (HRRP) with readmission and mortality outcomes among patients hospitalized with heart failure within a prospective clinical registry that allows for detailed risk adjustment. Interrupted time-series and survival analyses of index heart failure hospitalizations were conducted from January 1, 2006, to December 31, 2014. This study included 115 245 fee-for-service Medicare beneficiaries across 416 US hospital sites participating in the American Heart Association Get With The Guidelines-Heart Failure registry. Data analysis took place from January 1, 2017, to June 8, 2017. Time intervals related to the HRRP were before the HRRP implementation (January 1, 2006, to March 31, 2010), during the HRRP implementation (April 1, 2010, to September 30, 2012), and after the HRRP penalties went into effect (October 1, 2012, to December 31, 2014). Risk-adjusted 30-day and 1-year all-cause readmission and mortality rates. The mean (SD) age of the study population (n = 115 245) was 80.5 (8.4) years, 62 927 (54.6%) were women, and 91 996 (81.3%) were white and 11 037 (9.7%) were black. The 30-day risk-adjusted readmission rate declined from 20.0% before the HRRP implementation to 18.4% in the HRRP penalties phase (hazard ratio (HR) after vs before the HRRP implementation, 0.91; 95% CI, 0.87-0.95; P < .001). In contrast, the 30-day risk-adjusted mortality rate increased from 7.2% before the HRRP implementation to 8.6% in the HRRP penalties phase (HR after vs before the HRRP implementation, 1.18; 95% CI, 1.10-1.27; P < .001). The 1-year risk-adjusted readmission and mortality rates followed a similar pattern as the 30-day outcomes. The 1-year risk-adjusted readmission rate declined from 57.2% to 56.3% (HR, 0.92; 95% CI, 0.89-0.96; P < .001), and the 1-year risk-adjusted mortality rate increased from 31.3% to 36.3% (HR, 1.10; 95% CI, 1.06-1.14; P < .001) after vs before the HRRP implementation. Among fee-for-service Medicare beneficiaries discharged after heart failure hospitalizations, implementation of the HRRP was temporally associated with a reduction in 30-day and 1-year readmissions but an increase in 30-day and 1-year mortality. If confirmed, this finding may require reconsideration of the HRRP in heart failure.