Trends in readmission rates for safety net hospitals and non-safety net hospitals in the era of the US Hospital Readmission Reduction Program: a retrospective time series analysis using Medicare administrative claims data from 2008 to 2015

Measuring Equity in Readmission as a Distinct Assessment of Hospital Performance

Importance

Equity is an essential domain of health care quality. The Centers for Medicare & Medicaid Services (CMS) developed 2 Disparity Methods that together assess equity in clinical outcomes.

Objectives

To define a measure of equitable readmissions; identify hospitals with equitable readmissions by insurance (dual eligible vs non-dual eligible) or patient race (Black vs White); and compare hospitals with and without equitable readmissions by hospital characteristics and performance on accountability measures (quality, cost, and value).

Design, Setting, and Participants

Cross-sectional study of US hospitals eligible for the CMS Hospital-Wide Readmission measure using Medicare data from July 2018 through June 2019.

Main Outcomes and Measures

We created a definition of equitable readmissions using CMS Disparity Methods, which evaluate hospitals on 2 methods: outcomes for populations at risk for disparities (across-hospital method); and disparities in care within hospitals' patient populations (within-a-single-hospital method).

Exposures

Hospital patient demographics; hospital characteristics; and 3 measures of hospital performance-quality, cost, and value (quality relative to cost).

Results

Of 4638 hospitals, 74% served a sufficient number of dual-eligible patients, and 42% served a sufficient number of Black patients to apply CMS Disparity Methods by insurance and race. Of eligible hospitals, 17% had equitable readmission rates by insurance and 30% by race. Hospitals with equitable readmissions by insurance or race cared for a lower percentage of Black patients (insurance, 1.9% [IQR, 0.2%-8.8%] vs 3.3% [IQR, 0.7%-10.8%], P < .01; race, 7.6% [IQR, 3.2%-16.6%] vs 9.3% [IQR, 4.0%-19.0%], P = .01), and differed from nonequitable hospitals in multiple domains (teaching status, geography, size; P < .01). In examining equity by insurance, hospitals with low costs were more likely to have equitable readmissions (odds ratio, 1.57 [95% CI, 1.38-1.77), and there was no relationship between quality and value, and equity. In examining equity by race, hospitals with high overall quality were more likely to have equitable readmissions (odds ratio, 1.14 [95% CI, 1.03-1.26]), and there was no relationship between cost and value, and equity.

Conclusion and Relevance

A minority of hospitals achieved equitable readmissions. Notably, hospitals with equitable readmissions were characteristically different from those without. For example, hospitals with equitable readmissions served fewer Black patients, reinforcing the role of structural racism in hospital-level inequities. Implementation of an equitable readmission measure must consider unequal distribution of at-risk patients among hospitals.

Social vulnerability is associated with increased postoperative morbidity following esophagectomy

OBJECTIVES

The effect of a patient's Social Vulnerability Index (SVI) on complication rates after esophagectomy remains unstudied. The purpose of this study was to determine how social vulnerability influences morbidity following esophagectomy.

METHODS

This was a retrospective review of a prospectively collected esophagectomy database at one academic institution, 2016 to 2022. Patients were grouped into low-SVI (<75%ile) and high-SVI (>75%ile) cohorts. The primary outcome was overall postoperative complication rate; secondary outcomes were rates of individual complications. Perioperative patient variables and postoperative complication rates were compared between the 2 groups. Multivariable logistic regression was used to control for covariates.

RESULTS

Of 149 patients identified who underwent esophagectomy, 27 (18.1%) were in the high-SVI group. Patients with high SVI were more likely to be of Hispanic ethnicity (18.5% vs 4.9%, P = .029), but there were no other differences in perioperative characteristics between groups. Patients with high SVI were significantly more likely to develop a postoperative complication (66.7% vs 36.9%, P = .005) and had greater rates of postoperative pneumonia (25.9% vs 6.6%, P = .007), jejunal feeding-tube complications (14.8% vs 3.3%, P = .036), and unplanned intensive care unit readmission (29.6% vs 12.3%, P = .037). In addition, patients with high SVI had a longer postoperative hospital length of stay (13 vs 10 days, P = .017). There were no differences in mortality rates. These findings persisted on multivariable analysis.

CONCLUSIONS

Patients with high SVI have greater rates of postoperative morbidity following esophagectomy. The effect of SVI on esophagectomy outcomes warrants further investigation and may prove useful in identifying populations that benefit from interventions to mitigate these complications.

Independent Associations of Neighborhood Deprivation and Patient-level Social Determinants of Health with Textbook Outcomes after Inpatient Surgery

Objective

Assess associations of Social Determinants of Health (SDoH) using Area Deprivation Index (ADI), race/ethnicity and insurance type with Textbook Outcomes (TO).

Summary Background Data

Individual- and contextual-level SDoH affect health outcomes, but only one SDoH level is usually included.

Methods

Three healthcare system cohort study using National Surgical Quality Improvement Program (2013-2019) linked with ADI risk-adjusted for frailty, case status and operative stress examining TO/TO components (unplanned reoperations, complications, mortality, Emergency Department/Observation Stays and readmissions).

Results

Cohort (34,251 cases) mean age 58.3 [SD=16.0], 54.8% females, 14.1% Hispanics, 11.6% Non-Hispanic Blacks, 21.6% with ADI>85, and 81.8% TO. Racial and ethnic minorities, non-Private insurance, and ADI>85 patients had increased odds of urgent/emergent surgeries (aORs range: 1.17-2.83, all P<.001). Non-Hispanic Black patients, ADI>85 and non-Private insurances had lower TO odds (aORs range: 0.55-0.93, all P<.04), but ADI>85 lost significance after including case status. Urgent/emergent versus elective had lower TO odds (aOR=0.51, P<.001). ADI>85 patients had higher complication and mortality odds. Estimated reduction in TO probability was 9.9% (CI=7.2%-12.6%) for urgent/emergent cases, 7.0% (CI=4.6%-9.3%) for Medicaid, and 1.6% (CI=0.2%-3.0%) for non-Hispanic Black patients. TO probability difference for lowest-risk (White-Private-ADI≤85-elective) to highest-risk (Black-Medicaid-ADI>85-urgent/emergent) was 29.8% for very frail patients.

Conclusion

Multi-level SDoH had independent effects on TO, predominately affecting outcomes through increased rates/odds of urgent/emergent surgeries driving complications and worse outcomes. Lowest-risk versus highest-risk scenarios demonstrated the magnitude of intersecting SDoH variables. Combination of insurance type and ADI should be used to identify high-risk patients to redesign care pathways to improve outcomes. Risk adjustment including contextual neighborhood deprivation and patient-level SDoH could reduce unintended consequences of value-based programs.

Association of Insurance Type With Inpatient Surgery 30-Day Complications and Costs

INTRODUCTION

Safety-net hospitals (SNHs) have higher postoperative complications and costs versus low-burden hospitals. Do low socioeconomic status/vulnerable patients receive care at lower-quality hospitals or are there factors beyond providers' control? We studied the association of private, Medicare, and vulnerable insurance type with complications/costs in a high-burden SNH.

METHODS

Retrospective inpatient cohort study using National Surgical Quality Improvement Program (NSQIP) data (2013-2019) with cost data risk-adjusted by frailty, preoperative serious acute conditions (PASC), case status, and expanded operative stress score (OSS) to evaluate 30-day unplanned reoperations, any complication, Clavien-Dindo IV (CDIV) complications, and hospitalization variable costs.

RESULTS

Cases (Private 1517; Medicare 1224; Vulnerable 3648) with patient mean age 52.3 y [standard deviation = 14.7] and 47.3% male. Adjusting for frailty and OSS, vulnerable patients had higher odds of PASC (aOR = 1.71, CI = 1.39-2.10, P < 0.001) versus private. Adjusting for frailty, PASC and OSS, Medicare (aOR = 1.27, CI = 1.06-1.53, P = 0.009), and vulnerable (aOR = 2.44, CI = 2.13-2.79, P < 0.001) patients were more likely to undergo urgent/emergent surgeries. Vulnerable patients had increased odds of reoperation and any complications versus private. Variable cost percentage change was similar between private and vulnerable after adjusting for case status. Urgent/emergent case status increased percentage change costs by 32.31%. We simulated "switching" numbers of private (3648) versus vulnerable (1517) cases resulting in an estimated variable cost of $49.275 million, a 25.2% decrease from the original $65.859 million.

CONCLUSIONS

Increased presentation acuity (PASC and urgent/emergent surgeries) in vulnerable patients drive increased odds of complications and costs versus private, suggesting factors beyond providers' control. The greatest impact on outcomes may be from decreasing the incidence of urgent/emergent surgeries by improving access to care.

Retrospective cohort study comparing surgical inpatient charges, total costs, and variable costs as hospital cost savings measures

We analyzed differences (charges, total, and variable costs) in estimating cost savings of quality improvement projects using reduction of serious/life-threatening complications (Clavien-Dindo Level IV) and insurance type (Private, Medicare, and Medicaid/Uninsured) to evaluate the cost measures. Multiple measures are used to analyze hospital costs and compare cost outcomes across health systems with differing patient compositions. We used National Surgical Quality Improvement Program inpatient (2013-2019) with charge and cost data in a hospital serving diverse socioeconomic status patients. Simulation was used to estimate variable costs and total costs at 3 proportions of fixed costs (FC). Cases (Private 1517; Medicare 1224; Medicaid/Uninsured 3648) with patient mean age 52.3 years (Standard Deviation = 14.7) and 47.3% male. Medicare (adjusted odds ratio = 1.55, 95% confidence interval = 1.16-2.09, P = .003) and Medicaid/Uninsured (adjusted odds ratio = 1.41, 95% confidence interval = 1.10-1.82, P = .008) had higher odds of complications versus Private. Medicaid/Uninsured had higher relative charges versus Private, while Medicaid/Uninsured and Medicare had higher relative variable and total costs versus Private. Targeting a 15% reduction in serious complications for robust patients undergoing moderate-stress procedures estimated variable cost savings of $286,392. Total cost saving estimates progressively increased with increasing proportions of FC; $443,943 (35% FC), $577,495 (50% FC), and $1184,403 (75% FC). In conclusion, charges did not identify increased costs for Medicare versus Private patients. Complications were associated with > 200% change in costs. Surgical hospitalizations for Medicare and Medicaid/Uninsured patients cost more than Private patients. Variable costs should be used to avoid overestimating potential cost savings of quality improvement interventions, as total costs include fixed costs that are difficult to change in the short term.

Hospital value-based payment programs and disparity in the United States: A review of current evidence and future perspectives

Beginning in the early 2010s, an array of Value-Based Purchasing (VBP) programs has been developed in the United States (U.S.) to contain costs and improve health care quality. Despite documented successes in these efforts in some instances, there have been growing concerns about the programs' unintended consequences for health care disparities due to their built-in biases against health care organizations that serve a disproportionate share of disadvantaged patient populations. We explore the effects of three Medicare hospital VBP programs on health and health care disparities in the U.S. by reviewing their designs, implementation history, and evidence on health care disparities. The available empirical evidence thus far suggests varied impacts of hospital VBP programs on health care disparities. Most of the reviewed studies in this paper demonstrate that hospital VBP programs have the tendency to exacerbate health care disparities, while a few others found evidence of little or no worsening impacts on disparities. We discuss several policy options and recommendations which include various reform approaches and specific programs ranging from those addressing upstream structural barriers to health care access, to health care delivery strategies that target service utilization and health outcomes of vulnerable populations under the VBP programs. Future studies are needed to produce more explicit, conclusive, and consistent evidence on the impacts of hospital VBP programs on disparities.

Readmissions performance and penalty experience of safety-net hospitals under Medicare's Hospital Readmissions Reduction Program

BACKGROUND

The Hospital Readmissions Reduction Program (HRRP), established by the Centers for Medicare and Medicaid Services (CMS) in March 2010, introduced payment-reduction penalties on acute care hospitals with higher-than-expected readmission rates for acute myocardial infarction (AMI), heart failure, and pneumonia. There is concern that hospitals serving large numbers of low-income and uninsured patients (safety-net hospitals) are at greater risk of higher readmissions and penalties, often due to factors that are likely outside the hospital's control. Using publicly reported data, we compared the readmissions performance and penalty experience among safety-net and non-safety-net hospitals.

METHODS

We used nationwide hospital level data for 2009-2016 from the Centers for Medicare and Medicaid Services (CMS) Hospital Compare program, CMS Final Impact Rule, and the American Hospital Association Annual Survey. We identified as safety-net hospitals the top quartile of hospitals in terms of the proportion of patients receiving income-based public benefits. Using a quasi-experimental difference-in-differences approach based on the comparison of pre- vs. post-HRRP changes in (risk-adjusted) 30-day readmission rate in safety-net and non-safety-net hospitals, we estimated the change in readmissions rate associated with HRRP. We also compared the penalty frequency among safety-net and non-safety-net hospitals.

RESULTS

Our study cohort included 1915 hospitals, of which 479 were safety-net hospitals. At baseline (2009), safety-net hospitals had a slightly higher readmission rate compared to non-safety net hospitals for all three conditions: AMI, 20.3% vs. 19.8% (p value< 0.001); heart failure, 25.2% vs. 24.2% (p-value< 0.001); pneumonia, 18.7% vs. 18.1% (p-value< 0.001). Beginning in 2012, readmission rates declined similarly in both hospital groups for all three cohorts. Based on difference-in-differences analysis, HRRP was associated with similar change in the readmissions rate in safety-net and non-safety-net hospitals for AMI and heart failure. For the pneumonia cohort, we found a larger reduction (0.23%; p < 0.001) in safety-net hospitals. The frequency of readmissions penalty was higher among safety-net hospitals. The proportion of hospitals penalized during all four post-HRRP years was 72% among safety-net and 59% among non-safety-net hospitals.

CONCLUSIONS

Our results lend support to the concerns of disproportionately higher risk of performance-based penalty on safety-net hospitals.

Factors Associated With Disparities in Hospital Readmission Rates Among US Adults Dually Eligible for Medicare and Medicaid

Importance

Low-income older adults who are dually eligible (DE) for Medicare and Medicaid often experience worse outcomes following hospitalization. Among other federal policies aimed at improving health for DE patients, Medicare has recently begun reporting disparities in within-hospital readmissions. The degree to which disparities for DE patients are owing to differences in community-level factors or, conversely, are amenable to hospital quality improvement, remains heavily debated.

Objective

To examine the extent to which within-hospital disparities in 30-day readmission rates for DE patients are ameliorated by state- and community-level factors.

Design Setting and Participants

In this retrospective cohort study, Centers for Medicare & Medicaid Services (CMS) Disparity Methods were used to calculate within-hospital disparities in 30-day risk-adjusted readmission rates for DE vs non-DE patients in US hospitals participating in Medicare. All analyses were performed in February and March 2019. The study included Medicare patients (aged ≥65 years) hospitalized for acute myocardial infarction (AMI), heart failure (HF), or pneumonia in 2014 to 2017.

Main Outcomes and Measures

Within-hospital disparities, as measured by the rate difference (RD) in 30-day readmission between DE vs non-DE patients following admission for AMI, HF, or pneumonia; variance across hospitals; and correlation of hospital RDs with and without adjustment for state Medicaid eligibility policies and community-level factors.

Results

The final sample included 475 444 patients admitted for AMI, 898 395 for HF, and 1 214 282 for pneumonia, of whom 13.2%, 17.4%, and 23.0% were DE patients, respectively. Dually eligible patients had higher 30-day readmission rates relative to non-DE patients (RD >0) in 99.0% (AMI), 99.4% (HF), and 97.5% (pneumonia) of US hospitals. Across hospitals, the mean (IQR) RD between DE vs non-DE was 1.00% (0.87%-1.10%) for AMI, 0.82% (0.73%-0.96%) for HF, and 0.53% (0.37%-0.71%) for pneumonia. The mean (IQR) RD after adjustment for community-level factors was 0.87% (0.73%-0.97%) for AMI, 0.67% (0.57%-0.80%) for HF, and 0.42% (0.29%-0.57%) for pneumonia. Relative hospital rankings of corresponding within-hospital disparities before and after community-level adjustment were highly correlated (Pearson coefficient, 0.98).

Conclusions and Relevance

In this cohort study, within-hospital disparities in 30-day readmission for DE patients were modestly associated with differences in state Medicaid policies and community-level factors. This suggests that remaining variation in these disparities should be the focus of hospital efforts to improve the quality of care transitions at discharge for DE patients in efforts to advance equity.

Trends in the quality and cost of inpatient surgical procedures in the United States, 2002-2015

OBJECTIVES

This study documents trends in risk-adjusted quality and cost for a variety of inpatient surgical procedures among Medicare beneficiaries from 2002 through 2015, which can provide valuable insight on future strategies to improve public health and health care.

METHODS

We focused on 11 classes of inpatient surgery, defined by the Agency for Health Research and Quality's (AHRQ's) Clinical Classification System. The surgical classes studied included a wide range of surgeries, including tracheostomy, heart valve procedures, colorectal resection, and wound debridement, among others. For each surgical class, we assessed trends in treatment costs and quality outcomes, as defined by 30-day survival without unplanned readmissions, among Medicare beneficiaries receiving these procedures during hospital stays. Quality and costs were adjusted for patient severity based on demographics, comorbidities, and community context. We also explored surgical innovations of these 11 classes of inpatient surgery from 2002-2015.

RESULTS

We found significant improvements in quality for 7 surgical classes, ranging from 0.08% (percutaneous transluminal coronary angioplasty) to 0.74% (heart valve procedures) per year. Changes in cost varied by surgery, the significant decrease in cost ranged from -2.59% (tracheostomy) to -0.34% (colorectal resection) per year. Treatment innovation occurred with respect to surgical procedures utilized for heart valve procedures and colorectal resection, which may be associated with the decrease in surgical cost.

CONCLUSIONS

Our results suggest that there was significant quality improvement for 7 surgery categories over the 14-year study period. Costs decreased significantly for 6 surgery categories, and increased significantly for 3 other categories.

Association Between Racial Disparities in Hospital Length of Stay and the Hospital Readmission Reduction Program

Background:

On average Black patients have longer LOS than comparable White patients. Longer hospital length of stay (LOS) may be associated with higher readmission risk. However, evidence suggests that the Hospital Readmission Reduction Program (HRRP) reduced overall racial differences in 30-day adjusted readmission risk. Yet, it is unclear whether the HRRP narrowed these LOS racial differences.

Objective:

We examined the relationship between Medicare-insured Black-White differences in average, adjusted LOS (ALOS) and the HRRP’s implementation and evaluation periods.

Methods:

Using 2009-2017 data from State Inpatient Dataset from New York, New Jersey, and Florida, we employed an interrupted time series analysis with multivariate generalized regression models controlling for patient, disease, and hospital characteristics. Results are reported per 100 admissions.

Results:

We found that for those discharged home, Black-White ALOS differences significantly widened by 4.15 days per 100 admissions (95% CI: 1.19 to 7.11, P < 0.001) for targeted conditions from before to after the HRRP implementation period, but narrowed in the HRRP evaluation period by 1.84 days per 100 admissions for every year-quarter (95% CI: −2.86 to −0.82, P < 0.001); for those discharged to non-home destinations, there was no significant change between HRRP periods, but ALOS differences widened over the study period. Black-White ALOS differences for non-targeted conditions remained unchanged regardless of HRRP phase and discharge destination.

Conclusion:

Increased LOS for Black patients may have played a role in reducing Black-White disparities in 30-day readmission risks for targeted conditions among patients discharged to home.

Characteristics and Trends of the Hospital Standardized Readmission Ratios for Pneumonia: A Retrospective Observational Study Using Japanese Administrative Claims Data from 2010 to 2018

Previous studies indicated that optimal care for pneumonia during hospitalization might reduce the risk of in-hospital mortality and subsequent readmission. This study was a retrospective observational study using Japanese administrative claims data from April 2010 to March 2019. We analyzed data from 167,120 inpatients with pneumonia ≥15 years old in the benchmarking project managed by All Japan Hospital Association. Hospital-level risk-adjusted ratios of 30-day readmission for pneumonia were calculated using multivariable logistic regression analyses. The Spearman’s correlation coefficient was used to assess the correlation in each consecutive period. In the analysis using complete 9-year data including 54,756 inpatients, the hospital standardized readmission ratios (HSRRs) showed wide variation among hospitals and improvement trend (r = −0.18, p = 0.03). In the analyses of trends in each consecutive period, the HSRRS were positively correlated between ‘2010–2012’ and ‘2013–2015’ (r = 0.255, p = 0.010), and ‘2013–2015’ and ‘2016–2018’ (r = 0.603, p < 0.001). This study denoted the HSRRs for pneumonia could be calculated using Japanese administrative claims data. The HSRRs significantly varied among hospitals with comparable case-mix, and could relatively evaluate the quality of preventing readmission including long-term trends. The HSRRs can be used as yet another measure to help improve quality of care over time if other indicators are examined in parallel.

Effectiveness of Discharge Education With the Teach-Back Method on 30-Day Readmission: A Systematic Review

OBJECTIVES

Teach-back methods are reported to improve patient outcomes by encouraging patient understanding and participation and are increasingly being used in various clinical settings. This study attempts to identify the effectiveness of discharge education using the teach-back method on 30-day readmission.

METHODS

MEDLINE, CINAHL, Embase, The Cochrane Library, and Web of Science were used to search experimental studies. The search terms were "discharged patient," "teach-back," and "30-day readmission" published in English up until July 2017. Two trained reviewers performed a critical appraisal of retrieved studies using the Risk of Bias Assessment tool for Nonrandomized Studies. Data were analyzed using Cochrane Review Manager (Revman) software 5.2.

RESULTS

A total of five studies were analyzed (3 studies on heart failure, 1 study on total joint replacement, and 1 study on a coronary artery bypass graft). The main content of the teach-back education was to confirm and reinforce the patients' comprehension of health-related information. Among the five studies, three studies were included in the meta-analysis. The odds ratio of 30-day readmission for discharge education with the teach-back method and usual care was 0.55 (95% confidence interval, 0.34-0.91; P = 0.02). The I2 score was 0%, which means that the analyzed studies are homogeneous.

CONCLUSIONS

The results indicate that discharge education with the teach-back method resulted in a 45% reduction in 30-day readmission. However, only a few studies were included in the analysis, and they showed a high risk of selection bias. Therefore, we suggest that well-designed randomized controlled trials be conducted.

Adjustment For Social Risk Factors Does Not Meaningfully Affect Performance On Medicare's MIPS Clinician Cost Measures

Medicare's Merit-based Incentive Payment System (MIPS) includes episode-based cost measures that evaluate Medicare expenditures for specific conditions and procedures. These measures compare clinicians' cost performance and, along with other MIPS category scores, determine Medicare Part B clinician payment adjustments. The measures do not include risk adjustment for social risk factors. We found that adjusting for individual and community social risk did not have a meaningful impact on clinicians' cost measure performance. Across eight cost measures, 1.4 percent of clinician groups, on average, had an absolute change in their cost measure performance percentile of 10 percent or more (range, 0.4-3.4 percent). Prior analyses have generally found higher health care costs for patients with increased social risk. MIPS episode-based cost measures are distinct from previous cost measures because they only include costs related to the specific condition being evaluated. This unique approach may explain why costs were similar for patients with high and low social risk before any risk adjustment. MIPS episode-based cost measures do not appear to penalize clinicians who primarily care for patients with increased social risk.

Defining safety net hospitals in the health services research literature: a systematic review and critical appraisal

Background

The aim of this study was to identify the range of ways that safety net hospitals (SNHs) have been empirically operationalized in the literature and determine the extent to which patterns could be identified in the use of empirical definitions of SNHs.

Methods

We conducted a PRISMA guided systematic review of studies published between 2009 and 2018 and analyzed 22 articles that met the inclusion criteria of hospital-level analyses with a clear SNH definition.

Results

Eleven unique SNH definitions were identified, and there were no obvious patterns in the use of a definition category (Medicaid caseload, DSH payment status, uncompensated care, facility characteristics, patient care mix) by the journal type where the article appeared, dataset used, or the year of publication.

Conclusions

Overall, there is broad variability in the conceptualization of, and variables used to define, SNHs. Our work advances the field toward the development of standards in measuring, operationalizing, and conceptualizing SNHs across research and policy questions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-021-06292-9.

Association of Socioeconomic Area Deprivation Index with Hospital Readmissions After Colon and Rectal Surgery

BACKGROUND

Risk adjustment for reimbursement and quality measures omits social risk factors despite adversely affecting health outcomes. Social risk factors are not usually available in electronic health records (EHR) or administrative data. Socioeconomic status can be assessed by using US Census data. Distressed Communities Index (DCI) is based upon zip codes, and the Area Deprivation Index (ADI) provides more granular estimates at the block group level. We examined the association of neighborhood disadvantage using the ADI, DCI, and patient-level insurance status on 30-day readmission risk after colorectal surgery.

METHODS

Our 677 patient cohort was derived from the 2013-2017 National Surgical Quality Improvement Program at a safety net hospital augmented with EHR data to determine insurance status and 30-day readmissions. Patients' home addresses were linked to the ADI and DCI.

RESULTS

Our cohort consisted of 53.9% males and 63.8% Hispanics with a 22.9% 30-day readmission rate from the date of discharge; > 50% lived in highly deprived neighborhoods. Controlling for medical comorbidities and complications, ADI was associated with increased risk of 30 days from the date of discharge readmissions among patients living in medium (OR = 2.15, p = .02) or high (OR = 1.88, p = .03) deprived areas compared to less-deprived neighborhoods, but not insurance status or DCI.

CONCLUSIONS

The ADI identified patients living in deprived communities with increased readmission risk. Our results show that block-group level ADI can potentially be used in risk adjustment, to identify high-risk patients and to design better care pathways that improve health outcomes.

Improving evidence-based grouping of transitional care strategies in hospital implementation using statistical tools and expert review

BACKGROUND

As health systems transition to value-based care, improving transitional care (TC) remains a priority. Hospitals implementing evidence-based TC models often adapt them to local contexts. However, limited research has evaluated which groups of TC strategies, or transitional care activities, commonly implemented by hospitals correspond with improved patient outcomes. In order to identify TC strategy groups for evaluation, we applied a data-driven approach informed by literature review and expert opinion.

METHODS

Based on a review of evidence-based TC models and the literature, focus groups with patients and family caregivers identifying what matters most to them during care transitions, and expert review, the Project ACHIEVE team identified 22 TC strategies to evaluate. Patient exposure to TC strategies was measured through a hospital survey (N = 42) and prospective survey of patients discharged from those hospitals (N = 8080). To define groups of TC strategies for evaluation, we performed a multistep process including: using ACHIEVE'S prior retrospective analysis; performing exploratory factor analysis, latent class analysis, and finite mixture model analysis on hospital and patient survey data; and confirming results through expert review. Machine learning (e.g., random forest) was performed using patient claims data to explore the predictive influence of individual strategies, strategy groups, and key covariates on 30-day hospital readmissions.

RESULTS

The methodological approach identified five groups of TC strategies that were commonly delivered as a bundle by hospitals: 1) Patient Communication and Care Management, 2) Hospital-Based Trust, Plain Language, and Coordination, 3) Home-Based Trust, Plain language, and Coordination, 4) Patient/Family Caregiver Assessment and Information Exchange Among Providers, and 5) Assessment and Teach Back. Each TC strategy group comprises three to six, non-mutually exclusive TC strategies (i.e., some strategies are in multiple TC strategy groups). Results from random forest analyses revealed that TC strategies patients reported receiving were more important in predicting readmissions than TC strategies that hospitals reported delivering, and that other key co-variates, such as patient comorbidities, were the most important variables.

CONCLUSION

Sophisticated statistical tools can help identify underlying patterns of hospitals' TC efforts. Using such tools, this study identified five groups of TC strategies that have potential to improve patient outcomes.

Identifying Actionable Causes of Potentially Avoidable Readmissions to an Oncology Service at a Safety Net Hospital

PURPOSE

Hospital readmissions occur commonly in those receiving cancer care and result in impaired quality of life and increased costs. Causes of readmission in safety net hospitals that serve vulnerable populations are not well understood. The primary goal of this project was to identify potentially avoidable and intervenable causes of readmissions to an urban safety net hospital.

METHODS

A retrospective chart review was performed on patients who were readmitted within 30 days of discharge from the hematology and oncology service at Boston Medical Center over the 6-month period between October 2018 and March 2019. Charts were reviewed by three internal medicine residents and discussed under the supervision of an attending oncologist.

RESULTS

Two hundred ninety-one patient encounters involving 203 unique patients were identified in the 6-month study period. Of these 291 encounters, 80 encounters (27.5%) were followed by a readmission within 30 days and occurred in 61 (30.0%) unique patients. Nineteen (31.1%) of these 61 patients experienced two readmissions within 30 days of discharge. Twenty-five readmissions (31.3%) were classified as potentially avoidable, with the most common cause of potentially avoidable readmissions attributed to ascitic or pleural fluid reaccumulation (8, 32%). The majority of presumed nonpreventable readmissions were due to expected complications of cancer progression and treatment-related side effects.

DISCUSSION

In conclusion, readmissions were common, and a modifiable reason for 30-day readmissions was identified. Addressing recurrent ascitic and pleural fluid reaccumulation in the outpatient setting could help to reduce inpatient hospital readmission on an inpatient oncology service.

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

BACKGROUND

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.

OBJECTIVE

We sought to determine whether HRRP penalties influenced COPD readmissions among Medicare, Medicaid, or privately insured patients.

DESIGN

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).

PATIENTS

We assessed discharged patients ≥ 40 years old with COPD versus those with HRRP Phase 1 conditions (AMI, CHF, and pneumonia) or non-HRRP residual diagnoses in the Nationwide Readmissions Database.

INTERVENTIONS

HRRP was announced and implemented during this period, forming a natural experiment.

MEASUREMENTS

We calculated differences-in-differences (DID) for 30-day COPD versus HRRP Phase 1 and non-HRRP readmissions.

KEY RESULTS

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).

CONCLUSIONS

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.

The Financial Impact of an Avoided Readmission for Teaching and Safety-Net Hospitals Under Medicare's Hospital Readmission Reduction Program

We examined the financial incentives to avoid readmissions under Medicare's Hospital Readmission Reduction Program for safety-net hospitals (SNHs) and teaching hospitals (THs) compared with other hospitals. Using Medicare's FY2016 Hospital Compare and readmissions data for 2,465 hospitals, we tested for differential revenue gains for SNHs (n = 658) relative to non-SNHs (n = 1,807), and for major (n = 231) and minor (n = 591) THs relative to non-THs (n = 1,643). We examined hospital-level factors predicting differences in revenue gains by hospital type. The revenue gains of an avoided readmission were 10% to 15% greater for major THs compared with non-THs ($18,047 vs. $15,478 for acute myocardial infarction) but no different for SNHs compared with non-SNHs. The greater revenue gains for THs were strongly positively predicted by hospitals' poor initial readmission performance. We found little evidence that the Hospital Readmission Reduction Program creates disincentives for SNHs and THs to invest in readmission reduction efforts, and THs have greater returns from readmissions avoidance than non-THs.

Trends in 30-Day Readmission for Medicaid and Privately Insured Pediatric Patients: 2010-2017

BACKGROUND

Children insured by Medicaid have higher readmission rates than privately insured children. However, little is known about whether this disparity has changed over time.

METHODS

Data from the 2010 to 2017 Healthcare Cost and Utilization Project Nationwide Readmissions Database were used to compare trends in 30-day readmission rates for children insured by Medicaid and private insurers. Patient-level crude and risk-adjusted readmission rates were compared by using Poisson regression. Hospital-level risk-adjusted readmission rates were compared between Medicaid- and privately insured patients within a hospital by using linear regression.

RESULTS

Approximately 60% of pediatric admissions were covered by Medicaid. From 2010 to 2017, the percentage of children with a complex or chronic condition increased for both Medicaid- and privately insured patients. Readmission rates were consistently higher for Medicaid beneficiaries from 2010 to 2017. Readmission rates declined slightly for both Medicaid- and privately insured patients; however, they declined faster for privately insured patients (rate ratio: 0.988 [95% confidence interval: 0.986-0.989] vs 0.995 [95% confidence interval: 0.994-0.996], P for interaction <.001]). After adjustment, readmission rates for Medicaid- and privately insured patients declined at a similar rate (P for interaction = .87). Risk-adjusted hospital readmission rates were also consistently higher for Medicaid beneficiaries. The within-hospital difference in readmission rates for Medicaid versus privately insured patients remained stable over time (slope for difference: 0.015 [SE 0.011], P = .019).

CONCLUSIONS

Readmission rates for Medicaid- and privately insured pediatric patients declined slightly from 2010 to 2017 but remained substantially higher among Medicaid beneficiaries suggesting a persistence of the disparity by insurance status.

Increased 30-day readmission rate after craniotomy for tumor resection at safety net hospitals in small metropolitan areas

PURPOSE

Unplanned readmission of post-operative brain tumor patients is often attributed to hospital and patient characteristics and is associated with higher mortality and cost. Previous studies demonstrate multiple patient outcome disparities in safety net hospitals (SNHs) when compared to non-SNHs. This study uses the Nationwide Readmissions Database (NRD) to determine if initial brain tumor resection at SNHs is associated with increased 30-day non-elective readmission rates.

METHODS

Patients with benign or malignant primary or metastatic brain tumor undergoing craniotomy for surgical resection were retrospectively identified in the NRD from 2010 to 2014. SNHs were defined as hospitals with Medicaid and uninsured patient burden in the top quartile. Descriptive and multivariate analyses employing survey-adjusted logistic regression evaluated patient and hospital level factors influencing 30-day readmissions.

RESULTS

During the study period, 83,367 patients met inclusion criteria. 44.7% of patients had a benign tumor, and 55.3% had a malignant tumor. Secondary CNS neoplasm (5.99%), post-operative infection (5.96%), and septicemia (4.26%) caused most readmissions within 30 days. Patients had increased unplanned readmission rates if they underwent craniotomy for tumor resection at a SNH in a small metropolitan area (OR 1.11, 95% CI 1.02-1.21, p = 0.01), but not at a SNH in a large metropolitan area (OR 0.99, 95% CI 0.93-1.05, p = 0.73).

CONCLUSION

This finding may reflect differences in access to care and disparities in neurosurgical resources between small and large metropolitan areas. Inequities in expertise and capacity are relevant as surgical volume was also related to readmission rates. Further studies may be warranted to address such disparities.

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

IMPORTANCE

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.

OBJECTIVES

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.

DESIGN, SETTING, AND PARTICIPANTS

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).

MAIN OUTCOMES AND MEASURES

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.

RESULTS

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.

CONCLUSIONS AND RELEVANCE

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.

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

BACKGROUND

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.

METHODS

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.

RESULTS

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).

CONCLUSIONS

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.

CLINICAL RELEVANCE

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.

Relative Effects of the Hospital Readmissions Reduction Program on Hospitals That Serve Poorer Patients

IMPORTANCE

Hospitals that serve poorer populations have higher readmission rates. It is unknown whether these hospitals effectively lowered readmission rates in response to the Hospital Readmissions Reduction Program (HRRP).

OBJECTIVE

To compare pre-post differences in readmission rates among hospitals with different proportion of dual-eligible patients both generally and among the most highly penalized (ie, low performing) hospitals.

DESIGN

Retrospective cohort study using piecewise linear model with estimated hospital-level risk-standardized readmission rates (RSRRs) as the dependent variable and a change point at HRRP passage (2010). Economic burden was assessed by proportion of dual-eligibles served.

SETTING

Acute care hospitals within the United States.

PARTICIPANTS

Medicare fee-for-service beneficiaries aged 65 years or older discharged alive from January 1, 2003 to November 30, 2014 with a principal discharge diagnosis of acute myocardial infarction (AMI), congestive heart failure (CHF), and pneumonia.

MAIN OUTCOME AND MEASURE

Decrease in hospital-level RSRRs in the post-law period, after controlling for the pre-law trend.

RESULTS

For AMI, the pre-post difference between hospitals that service high and low proportion of dual-eligibles was not significant (-65 vs. -64 risk-standardized readmissions per 10000 discharges per year, P=0.0678). For CHF, RSRRs declined more at high than low dual-eligible hospitals (-79 vs. -75 risk-standardized readmissions per 10000 discharges per year, P=0.0006). For pneumonia, RSRRs declined less at high than low dual-eligible hospitals (-44 vs. -47 risk-standardized readmissions per 10000 discharges per year, P=0.0003). Among the 742 highest penalized hospitals and all conditions, the pre-post decline in rate of change of RSRRs was less for high dual-eligible hospitals than low dual-eligible hospitals (-68 vs. -74 risk-standardized readmissions per 10000 discharges per year for AMI, -88 vs. -97 for CHF, and -47 vs. -56 for pneumonia, P<0.0001 for all).

CONCLUSIONS AND RELEVANCE

For all hospitals, differences in pre-post trends in RSRRs varied with disease conditions. However, for the highest-penalized hospitals, the pre-post decline in RSRRs was greater for low than high dual-eligible hospitals for all penalized conditions. These results suggest that high penalty, high dual-eligible hospitals may be less able to improve performance on readmission metrics.

Reliability of the American Community Survey Estimates of Risk-Adjusted Readmission Rankings for Hospitals Before and After Peer Group Stratification

IMPORTANCE

Since the transition to the American Community Survey, data uncertainty has complicated its use for policy making and research, despite the ongoing need to identify disparities in health care outcomes. The US Centers for Medicare & Medicaid Services' new, stratified payment adjustment method for its Hospital Readmissions Reduction Program may be able to reduce the reliance on data linkages to socioeconomic survey estimates.

OBJECTIVE

To determine whether there are differences in the reliability of socioeconomically risk-adjusted hospital readmission rates among hospitals that serve a disproportionate share of low-income populations after stratifying hospitals into peer group-based classification groups.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study uses data from the 2014 New York State Health Cost and Utilization Project State Inpatient Database for 96 278 hospital admissions for acute myocardial infarction, pneumonia, and congestive heart failure. The analysis included patients aged 18 years and older who were not transferred to another hospital, who were discharged alive, who did not leave the hospital against medical advice, and who were discharged before December 2014.

MAIN OUTCOMES AND MEASURES

The main outcomes were 30-day hospital readmissions after acute myocardial infarction, pneumonia, and congestive heart failure assessed using hierarchical logistic regression.

RESULTS

The mean (SD) age of the patients was 69.6 (16.0) years for the safety-net hospitals and 74.9 (14.7) years for the non-safety-net hospitals; 9382 (48.8%) and 7003 (48.5%) patients, respectively, were female. For safety net designations, 20% (3 of 15) of all evaluations concealed and distorted differences in risk, with factors such as poverty failing to identify similar risk of acute myocardial infarction readmission until unreliable estimates were excluded from the analysis (OR, 1.23 [95% CI, 1.00-1.52], P = .02; vs OR, 1.17 [95% CI, 0.94-1.46], P = .15). By comparison, 2 of the 60 models (3%) for the peer group-based classification altered the association between socioeconomic status and readmission risk, concealing similarities in congestive heart failure readmission when adjusted using high school completion rates (OR, 1.27 [95% CI 1.02-1.58], P = .04; vs OR, 1.23 [95% CI, 0.98-1.53], P = .06) and distorting similarities in pneumonia readmissions when accounting for the proportion of lone-parent families (OR, 1.27 [95% CI, 0.98-1.66], P = .07; vs OR, 1.35 [95% CI, 1.02-1.80], P = .04) between the lowest and highest socioeconomic status hospitals in quartile 1.

CONCLUSIONS AND RELEVANCE

There was greater precision in socioeconomic adjusted readmission estimates when hospitals were stratified into the new payment adjustment criteria compared with safety net designations. A contributing factor for improved reliability of American Community Survey estimates under the new payment criteria was the merging of patients from low-income neighborhoods with greater homogeneity in survey estimates into groupings similar to those for higher-income patients, whose neighborhoods often exhibit greater estimate variability. Additional efforts are needed to explore the effect of measurement error on American Community Survey-adjusted readmissions using the new peer group-based classification methods.

ACO Affiliated Hospitals Increase Implementation of Care Coordination Strategies

BACKGROUND

Hospitals affiliated with Accountable Care Organizations (ACOs) may have a greater capacity to collaborate with providers across the care continuum to coordinate care, due to formal risk sharing and payment arrangements. However, little is known about the extent to which ACO affiliated hospitals implement care coordination strategies.

OBJECTIVES

To compare the implementation of care coordination strategies between ACO affiliated hospitals (n=269) and unaffiliated hospitals (n=502) and examine whether the implementation of care coordination strategies varies by hospital payment model types.

MEASURES

We constructed a care coordination index (CCI) comprised of 12 indicators that describe evidence-based care coordination strategies. Each indicator was scored on a 5-point Likert scale from 1="not used at all" to 5="used widely" by qualified representatives from each hospital. The CCI aggregates scores from each of the 12 individual indicators to a single summary score for each hospital, with a score of 12 corresponding to the lowest and 60 the highest use of care coordination strategies.

RESEARCH DESIGN

We used state-fixed effects multivariable linear regression models to estimate the relationship between ACO affiliation, payment model type, and the use care coordination strategies.

RESULTS

We found ACO affiliated hospitals reported greater use of care coordination strategies compared to unaffiliated hospitals. Fee-for-service shared savings and partial or global capitation payment models were associated with a greater use of care coordination strategies among ACO affiliated hospitals.

CONCLUSION

Our findings suggest ACO affiliation and multiple payment model types are associated with the increased use of care coordination strategies.

How Have 30-Day Readmission Penalties Affected Racial Disparities in Readmissions?: an Analysis from 2007 to 2014 in Five US States

BACKGROUND

Thirty-day readmission penalties implemented with the Hospital Readmission Reduction Program (HRRP) place a larger burden on safety-net hospitals which treat a disproportionate share of racial minorities, leading to concerns that already large racial disparities in readmissions could widen.

OBJECTIVE

To examine whether there were changes in Black-White disparities in 30-day readmissions for acute myocardial infarction (AMI), congestive heart failure (CHF), or pneumonia following the passage and implementation of HRRP, and to compare disparities across safety-net and non-safety-net hospitals.

DESIGN

Repeated cross-sectional analysis, stratified by safety-net status.

SUBJECTS

1,745,686 Medicare patients over 65 discharged alive from hospitals in 5 US states: NY, FL, NE, WA, and AR.

MAIN MEASURES

Odds ratios comparing 30-day readmission rates following an index admission for AMI, CHF, or pneumonia for Black and White patients between 2007 and 2014.

KEY RESULTS

Prior to the passage of HRRP in 2010, Black and White readmission rates and disparities in readmissions were decreasing. These reductions were largest at safety-net hospitals. In 2007, Blacks had 13% higher odds of readmission if treated in safety-net hospitals, compared with 5% higher odds in 2010 (P < 0.05). These trends continued following the passage of HRRP.

CONCLUSIONS

Prior to HRRP, there were large reductions in Black-White disparities in readmissions at safety-net hospitals. Although HRRP tends to assess higher penalties for safety-net hospitals, improvements in readmissions have not reversed following the implementation of HRRP. In contrast, disparities continue to persist at non-safety-net hospitals which face much lower penalties.

Unplanned Readmissions After Acute Myocardial Infarction: 1-Year Trajectory Following Discharge From a Safety Net Hospital

BACKGROUND

Financial penalties rendered by the Centers for Medicare and Medicaid Services have brought about new challenges for safety net hospitals that serve a vulnerable patient population with risk factors associated with high readmission rates. Our goal was to determine the 1-year trajectory of unplanned readmissions in post-myocardial infarction (MI) patients, and to identify factors associated with readmission.

METHODS

A total of 261 acute MI patients admitted from April 2015 to April 2016 were evaluated in a multidisciplinary cardiology clinic within 10 days of hospital discharge and baseline characteristics and medical comorbidities were collected. Readmission and mortality data were obtained at 1 year through chart review and telephone follow-up.

RESULTS

At 1 year, there were 90 (34%) unplanned readmissions of which half were for noncardiac diagnoses. Of these, 69 patients (77%) were readmitted once, 16 (18%) were readmitted twice, 2 (2%) were readmitted 3 times, and 3 (3%) were readmitted 4 times over the subsequent year. Cardiac causes of 1-year readmission included recurrent MI in 23 (9%) and decompensated heart failure in 18 (7%) patients. Depressed left ventricular systolic function (hazard ratio, 2.23; 95% confidence interval, 2.00-2.44; P = 0.0003) and diabetes mellitus (hazard ratio, 1.60; 95% confidence interval, 1.38-1.82; P = 0.029) were associated with a significantly higher risk of readmission at 1 year.

CONCLUSION

Following acute MI, patients are readmitted for cardiac and noncardiac diagnoses well beyond the 30-day mark. This is likely a function of the vulnerability of the patient population rather than a reflection of the medical care provided. More frequent surveillance may attenuate this problem.

Applicability of Publicly Reported Hospital Readmission Measures to Unreported Conditions and Other Patient Populations: A Cross-sectional All-Payer Study

BACKGROUND

Readmission rates after hospitalizations for heart failure (HF), acute myocardial infarction (AMI), and pneumonia among Medicare beneficiaries are used to assess quality and determine reimbursement. Whether these measures reflect readmission rates for other conditions or insurance groups is unknown.

OBJECTIVE

To investigate whether hospital-level 30-day readmission measures for publicly reported conditions (HF, AMI, and pneumonia) among Medicare patients reflect those for Medicare patients hospitalized for unreported conditions or non-Medicare patients hospitalized with HF, AMI, or pneumonia.

DESIGN

Cross-sectional.

SETTING

Population-based.

PARTICIPANTS

Hospitals in the all-payer Nationwide Readmissions Database in 2013 and 2014.

MEASUREMENTS

Hospital-level 30-day all-cause risk-standardized excess readmission ratios (ERRs) were compared for 3 groups of patients: Medicare beneficiaries admitted for HF, AMI, or pneumonia (Medicare reported group); Medicare beneficiaries admitted for other conditions (Medicare unreported group); and non-Medicare beneficiaries admitted for HF, AMI, or pneumonia (non-Medicare group).

RESULTS

Within-hospital differences in ERRs varied widely among groups. Medicare reported ratios differed from Medicare unreported ratios by more than 0.1 for 29% of hospitals and from non-Medicare ratios by more than 0.1 for 46% of hospitals. Among hospitals with higher readmission ratios, ERRs for the Medicare reported group tended to overestimate ERRs for the non-Medicare group but underestimate those for the Medicare unreported group.

LIMITATION

Medicare groups and risk adjustment differed slightly from those used by the Centers for Medicare & Medicaid Services.

CONCLUSION

Hospital ERRs, as estimated by Medicare to determine financial penalties, have poor agreement with corresponding measures for populations and conditions not tied to financial penalties. Current publicly reported measures may not be good surrogates for overall hospital quality related to 30-day readmissions.

PRIMARY FUNDING SOURCE

Richard A. and Susan F. Smith Center for Outcomes Research in Cardiology.

Medicare Program Associated With Narrowing Hospital Readmission Disparities Between Black And White Patients

The Hospital Readmissions Reduction Program has been associated with improvements in readmission rates, yet little is known about its effect on racial disparities. We compared trends in thirty-day readmission rates for congestive heart failure, acute myocardial infarction, and pneumonia among non-Hispanic whites versus non-Hispanic blacks, and among minority-serving hospitals versus others. During the penalty-free implementation period (April 2010-September 2012), readmission rates improved over pre-implementation trends (January 2007-March 2010) for both whites and blacks, with a significantly greater decline among blacks than among whites (-0.45 percent versus -0.36 percent per quarter, respectively). In the period October 2012-December 2014, after penalties began, readmission improvements slowed for both races. Following a similar pattern, minority-serving hospitals saw greater reductions in readmissions than other hospitals did. Despite the narrowing of the two race-based gaps after announcement of the Hospital Readmissions Reduction Program, both persist. It remains to be seen whether new policy efforts will narrow these gaps and reduce the disproportionately high penalties that minority-serving hospitals face.

National trends in emergency readmission rates: a longitudinal analysis of administrative data for England between 2006 and 2016

OBJECTIVE

To assess trends in 30-day emergency readmission rates across England over one decade.

DESIGN

Retrospective study design.

SETTING

150 non-specialist hospital trusts in England.

PARTICIPANTS

23 069 134 patients above 18 years of age who were readmitted following an initial admission (n=62 584 297) between April 2006 and February 2016.

PRIMARY AND SECONDARY OUTCOMES

We examined emergency admissions that occurred within 30 days of discharge from hospital ('emergency readmissions') as a measure of healthcare quality. Presented are overall readmission rates, and disaggregated by the nature of the indexed admission, including whether it was elective or emergency, and by clinical health condition recorded. All rates were risk-adjusted for patient age, gender, ethnicity, socioeconomic status, comorbidities and length of stay.

RESULTS

The average risk-adjusted, 30-day readmission rate increased from 6.56% in 2006/2007 to 6.76% (P<0.01) in 2012/2013, followed by a small decrease to 6.64% (P<0.01) in 2015/2016. Emergency readmissions for patients discharged following elective procedures decreased by 0.13% (P<0.05), whereas those following emergency admission increased by 1.27% (P<0.001). Readmission rates for hip or knee replacements decreased (-1.29%; P<0.001); for acute myocardial infarction (-0.04%; P<0.49), stroke (+0.62%; P<0.05), chronic obstructive pulmonary disease (+0.41%; P<0.05) and heart failure (+0.15%; P<0.05) remained stable; and for pneumonia (+2.72%; P<0.001), diabetes (+7.09%; P<0.001), cholecystectomy (+1.86%; P<0.001) and hysterectomy (+2.54%; P<0.001) increased.

CONCLUSIONS

Overall, emergency readmission rates in England remained relatively stable across the observation period, with trends of slight increases contained post 2012/2013. However, there were large variations in trends across clinical areas, with some experiencing marked increases in readmission rates. This highlights the need to better understand variations in outcomes across clinical subgroups to allow for targeted interventions that will ensure highest standards of care provided for all patients.