The Medicare Hospital Readmissions Reduction Program: potential unintended consequences for hospitals serving vulnerable populations

Systematic Review and Meta-Analysis of the Financial Impact of 30-Day Readmissions for Selected Medical Conditions: A Focus on Hospital Quality Performance

BACKGROUND

The Patient Protection and Affordable Care Act (ACA) established the Hospital Quality Initiative in 2010 to enhance patient safety, reduce hospital readmissions, improve quality, and minimize healthcare costs. In response, this study aims to systematically review the literature and conduct a meta-analysis to estimate the average cost of procedure-specific 30-day risk-standardized unplanned readmissions for Acute Myocardial Infarction (AMI), Heart Failure (HF), Pneumonia, Coronary Artery Bypass Graft (CABG), and Total Hip Arthroplasty and/or Total Knee Arthroplasty (THA/TKA).

METHODS

Eligibility Criteria: This study included English language original research papers from the USA, encompassing various study designs. Exclusion criteria comprise studies lacking empirical evidence on hospital financial performance.

INFORMATION SOURCES

A comprehensive search using relevant keywords was conducted across databases from January 1990 to December 2019 (updated in March 2021), covering peer-reviewed articles and gray literature. Risk of Bias: Bias in the included studies was assessed considering study design, adjustment for confounding factors, and potential effect modifiers.

SYNTHESIS OF RESULTS

The review adhered to PRISMA guidelines. Employing Monte Carlo simulations, a meta-analysis was conducted with 100,000 simulated samples. Results indicated mean 30-day readmission costs: USD 16,037.08 (95% CI, USD 15,196.01-16,870.06) overall, USD 6852.97 (95% CI, USD 6684.44-7021.08) for AMI, USD 9817.42 (95% CI, USD 9575.82-10,060.43) for HF, and USD 21,346.50 (95% CI, USD 20,818.14-21,871.85) for THA/TKA.

DISCUSSION

Despite the financial challenges that hospitals face due to the ACA and the Hospital Readmissions Reduction Program, this meta-analysis contributes valuable insights into the consistent cost trends associated with 30-day readmissions.

CONCLUSIONS

This systematic review and meta-analysis provide comprehensive insights into the financial implications of 30-day readmissions for specific medical conditions, enhancing our understanding of the nexus between healthcare quality and financial performance.

Including socioeconomic status reduces readmission penalties to safety-net hospitals

OBJECTIVE

Medicare'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).

METHODS

This 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.

RESULTS

Our 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.

CONCLUSIONS

For 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.

Association of persistent poverty and U.S. News and World Report hospital rankings among patients undergoing major surgery

BACKGROUND

We sought to determine the association of persistent poverty on patient outcomes relative to US News World Report (USNWR) rankings among individuals undergoing common major surgical procedures.

METHODS

Medicare beneficiaries who underwent AAA repair, CABG, colectomy, or lung resection were identified. Multivariable logistic regression was used to evaluate the relationship between care at USNWR hospitals, county-level duration of poverty (never-high poverty (NHP); intermittent high poverty (IHP): persistent-poverty (PP)) and 30-day mortality.

RESULTS

Among 916,164 beneficiaries, individuals residing in PP neighborhoods who received surgical care at ranked hospitals had lower risk-adjusted 30-day mortality (5.89% vs 8.89%; p ​< ​0.001). On multivariable analysis, 30-day mortality was lower at ranked hospitals across all poverty categories with greatest decrease among patients from PP regions (NHP: OR-0.91, 95%CI0.87-0.95; IHP: OR-0.78, 95%CI0.69-0.88; PP: OR-0.69, 95%CI0.57-0.83; p ​< ​0.001).

CONCLUSION

Receipt of surgical care at top-ranked hospitals was associated with improvement in postoperative mortality, especially among patients residing in persistent poverty..

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

BACKGROUND

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.

METHODS

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.

RESULTS

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.

CONCLUSION

Long-term readmission rates are lower than pre-HRRP rates, with recent trends decreasing further for AMI, stabilizing for pneumonia, and increasing for HF.

Racial/Ethnic Disparities in the Alzheimer's Disease Link with Cardio and Cerebrovascular Diseases, Based on Hawaii Medicare Data

Background

There is an expanding body of literature implicating heart disease and stroke as risk factors for Alzheimer's disease (AD). Hawaii is one of the six majority-minority states in the United States and has significant racial health disparities. The Native-Hawaiians/Pacific-Islander (NHPI) population is well-known as a high-risk group for a variety of disease conditions.

Objective

We explored the association of cardiovascular disease with AD development based on the Hawaii Medicare data, focusing on racial disparities.

Methods

We utilized nine years of Hawaii Medicare data to identify subjects who developed heart failure (HF), ischemic heart disease (IHD), atrial fibrillation (AF), acute myocardial infarction (AMI), stroke, and progressed to AD, using multistate models. Propensity score-matched controls without cardiovascular disease were identified to compare the risk of AD after heart disease and stroke. Racial/Ethnic differences in progression to AD were evaluated, accounting for other risk factors.

Results

We found increased risks of AD for AF, HF, IHD, and stroke. Socioeconomic (SE) status was found to be critical to AD risk. Among the low SE group, increased AD risks were found in NHPIs compared to Asians for all conditions selected and compared to whites for HF, IHD, and stroke. Interestingly, these observations were found reversed in the higher SE group, showing reduced AD risks for NHPIs compared to whites for AF, HF, and IHD, and to Asians for HF and IHD.

Conclusions

NHPIs with poor SE status seems to be mostly disadvantaged by the heart/stroke and AD association compared to corresponding whites and Asians.

Multimorbidity, 30-Day Readmissions, and Postdischarge Mortality Among Medicare Beneficiaries Using a New ICD-Coded Multimorbidity-Weighted Index

BACKGROUND

Medically complex, disabled adults have high 30-day readmission rates. However, physical functioning is not routinely included in risk-adjustment models. We examined the association between multimorbidity with readmissions and mortality using a physical functioning weighted International Classification of Diseases (ICD)-coded multimorbidity-weighted index (MWI-ICD) representing 84 conditions.

METHODS

We included Medicare beneficiaries with ≥1 hospitalization 2000-2015 who participated in a Health and Retirement Study interview before admission. We computed MWI-ICD by summing physical functioning weighted conditions from Medicare claims. We examined 30-, 90-, and 365-day postdischarge mortality using multivariable logistic regression and length of stay through zero-inflated negative binomials. Models adjusted for age, sex, race/ethnicity, body mass index, smoking status, physical activity, education, net worth, and marital status/living arrangement.

RESULTS

The final sample of 10 737 participants had mean ± standard deviation (SD) age 75.9 ± 8.7 years, MWI-ICD 14.9 ± 9.0, and 20% had a 30-day readmission. Adults in the highest versus lowest quartile MWI-ICD had 92% increased odds of 30-day readmission (odds ratio [OR] = 1.92, 95% confidence interval [CI]: 1.65-2.22). A 1-point increase in MWI-ICD was associated with 24% increased odds of 30-day readmission (OR = 1.24, 95% CI: 1.18-1.31). A 1-point increase in MWI-ICD was associated with 32% increased odds of death within 365-day postdischarge (OR = 1.32, 95% CI: 1.25-1.40). Readmitted participants with the highest versus lowest quartile MWI-ICD had 37% increased number of expected hospitalized days (incidence rate ratio = 1.37, 95% CI: 1.17-1.59).

CONCLUSION

Among Medicare beneficiaries, multimorbidity using MWI-ICD is associated with an increased risk of readmissions, mortality, and longer length of stay. MWI-ICD appears to be a valid measure of multimorbidity that embeds physical functioning and presents an opportunity to incorporate functional status into claims-based risk-adjustment models.

Social risk adjustment in the hospital readmission reduction program: Pitfalls of peer grouping, measurement challenges, and potential solutions

OBJECTIVE

To examine the limitations of peer grouping and associated challenges measuring social risk in Medicare's Hospital Readmission Reduction Program (HRRP). Under peer grouping, hospitals are divided into quintiles based on the proportion of a hospital's Medicare inpatients with Medicaid ("dual share"). This approach was implemented to address concerns that the HRRP unfairly penalized hospitals that disproportionately serve disadvantaged patients.

DATA

Public data on hospitals in the HRRP.

DESIGN

We examined the relationship between hospital dual share and readmission rates within peer groups; changes in hospitals' peer group assignments, readmission rates, and penalties; and the relationship between state Medicaid eligibility rules and peer groups.

DATA COLLECTION

Public data on hospital characteristics and readmission rates for 3119 hospitals from 2019 to 2020.

PRINCIPAL FINDINGS

The proportion of dual inpatients among hospitals of the same peer group varied by as much as 69 percentage points (ppt). Within peer groups, a one ppt increase in dual share was associated with a 0.01 ppt increase in the difference from the median readmission rate (p < 0.001). From 2019 to 2020, 8.8% of hospitals switched peer groups. Compared to hospitals that did not switch, those moving to a lower peer group had a higher mean penalty in 2020 (0.096 ppt; p = 0.006); those moving to a higher group had a lower mean penalty (-0.06 ppt; p = 0.079). However, changes in penalties did not correspond to changes in readmission rates. Hospitals in states with higher Medicaid income eligibility limits were more likely to be in higher peer groups.

CONCLUSIONS

Peer grouping is limited in the extent to which it accounts for differences in hospitals' patient populations, and it may not fully insulate hospitals from penalties linked to changes in patient mix. These problems arise from the construction of peer groups and the measure of social risk used to define them.

Racial and Ethnic Disparities in Hospital-Based Care Among Dual Eligibles Who Use Health Centers

Introduction

Health center use may reduce hospital-based care among Medicare-Medicaid dual eligibles, but racial and ethnic disparities in this population have not been widely studied. We examined the extent of racial and ethnic disparities in hospital-based care among duals using health centers and the degree to which disparities occur within or between health centers.

Methods

We used 2012-2018 Medicare claims and health center data to model emergency department (ED) visits, observation stays, hospitalizations, and 30-day unplanned returns as a function of race and ethnicity among dual eligibles using health centers.

Results

In rural and urban counties, age-eligible Black individuals had more ED visits (7.9 [4.0, 11.7] and 13.7 [10.0, 17.4] per 100 person-years) and were more likely to experience an unplanned return (1.4 [0.4, 2.4] and 1 [0.4, 1.6] percentage points [pp]) than White individuals, but were less likely to be hospitalized (-3.3 [-3.9, -2.8] and -1.2 [-1.6, -0.9] pp). In urban counties, age-eligible Black individuals were 1.2 [0.9, 1.5] pp more likely than White individuals to have observation stays. Other racial and ethnic groups used the same or less hospital-based care than White individuals. Including state and health center fixed effects eliminated Black versus White disparities in all outcomes, except hospitalization. Results were similar among disability-eligible duals.

Conclusion

Racial and ethnic disparities in hospital-based care among dual eligibles are less common within than between health centers. If health centers are to play a more central role in eliminating racial and ethnic health disparities, these differences across health centers must be understood and addressed.

Assessing Hospital Quality Scores By Proportion Of Patients Dually Eligible For Medicare And Medicaid

The Centers for Medicare and Medicaid Services has been reporting hospital star ratings since 2016. Some stakeholders have criticized the star ratings methodology for not adjusting for social risk factors. We examined the relationship between 2021 star rating scores and hospitals' proportion of Medicare patients dually eligible for Medicaid. We found that, on average, hospitals caring for a greater proportion of dually eligible patients had lower star ratings, but there was significant overlap in performance among hospitals when we stratified them by quintile of dually eligible patients. Hospitals in the highest quintile (those with the greatest proportion of dually eligible patients) had the best mean mortality scores (0.28) but the worst readmission (-0.44) and patient experience (-0.78) scores. We assigned star ratings after stratifying the readmission measure group by proportion of dually eligible patients and found that a total of 142 hospitals gained a star and 161 hospitals lost a star, of which 126 (89 percent) and 1 (<1 percent) were in the highest quintile, respectively. Adjusting public reporting tools such as star ratings for social risk factors is ultimately a policy decision, and views on the appropriateness of accounting for factors such as proportion of dually eligible patients are mixed, depending on the organization and stakeholder.

Emergency department returns and early follow-up visits after heart failure hospitalization: Cohort study examining the role of race

Health disparities in heart failure (HF) show that Black patients face greater ED utilization and worse clinical outcomes. Transitional care post-HF hospitalization, such as 7-day early follow-up visits, may prevent ED returns. We examine whether early follow-up is associated with lower ED returns visits within 30 days and whether Black race is associated with receiving early follow-up after HF hospitalization. This was a retrospective cohort analysis of all Black and White adult patients at 13 hospitals in Michigan hospitalized for HF from October 1, 2017, to September 30, 2020. Adjusted risk ratios (aRR) were estimated from multivariable logistic regressions. The analytic sample comprised 6,493 patients (mean age = 71 years (SD 15), 50% female, 37% Black, 9% Medicaid). Ten percent had an ED return within 30 days and almost half (43%) of patients had 7-day early follow-up. Patients with early follow-up had lower risk of ED returns (aRR 0.85 [95%CI, 0.71-0.98]). Regarding rates of early follow-up, there was no overall adjusted association with Black race, but the following variables were related to lower follow-up: Medicaid insurance (aRR 0.90 [95%CI, 0.80-1.00]), dialysis (aRR 0.86 [95%CI, 0.77-0.96]), depression (aRR 0.92 [95%CI, 0.86-0.98]), and discharged with opioids (aRR 0.94 [95%CI, 0.88-1.00]). When considering a hospital-level interaction, three of the 13 sites with the lowest percentage of Black patients had lower rates of early follow-up in Black patients (ranging from 15% to 55% reduced likelihood). Early follow-up visits were associated with a lower likelihood of ED returns for HF patients. Despite this potentially protective association, certain patient factors were associated with being less likely to receive scheduled follow-up visits. Hospitals with lower percentages of Black patients had lower rates of early follow-up for Black patients. Together, these may represent missed opportunities to intervene in high-risk groups to prevent ED returns in patients with HF.

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.

Social Risk Adjustment In The Hospital Readmissions Reduction Program: A Systematic Review And Implications For Policy

Value-based payment programs adjust payments to providers based on spending, quality, or health outcomes. Concern that these programs penalize providers disproportionately serving vulnerable patients prompted calls to adjust performance measures for social risk factors. We reviewed fourteen studies of social risk adjustment in Medicare's Hospital Readmissions Reduction Program (HRRP), a value-based payment model that initially did not adjust for social risk factors but subsequently began to do so. Seven studies found that adding social risk factors to the program's base risk-adjustment model (which adjusts only for age, sex, and comorbidities) reduced differences in risk-adjusted readmissions and penalties between safety-net hospitals and other hospitals. Three studies found that peer grouping, the HRRP's current approach to social risk adjustment, reduced penalties among safety-net hospitals. Two studies found that differences in risk-adjusted readmissions and penalties were further narrowed when augmentation of the base model was combined with peer grouping. Two studies showed that it is possible to adjust for social risk factors without obscuring quality differences between hospitals. These findings support the use of social risk adjustment to improve provider payment equity and highlight opportunities to enhance social risk adjustment in value-based payment programs.

Obamacare: A bibliometric perspective

Obamacare is the colloquial name given to the Affordable Care Act (ACA) signed into law by President Obama in the USA, which ultimately aims to provide universal access to health care services for US citizens. The aim of this paper is to provide an overview of the political-legal, economic, social, management (or administrative), and medical (or health) repercussions of this law, using a bibliometric methodology as a basis. In addition, the main contributors to research on ACA issues have been identified in terms of authors, organizations, journals, and countries. The downward trend in scientific production on this law has been noted, and it has been concluded that a balance has not yet been reached between the coexistence of private and public health care that guarantees broad social coverage without economic or other types of barriers. The law requires political consensus to be implemented in a definitive and global manner for the whole of the United States.

Neighborhood-Level Socioeconomic Deprivation, Rurality, and Long-Term Outcomes of Patients Undergoing Total Joint Arthroplasty: Analysis from a Large, Tertiary Care Hospital

Objective

To assess the impact of neighborhood-level socioeconomic status factors (area deprivation index [ADI] and rural classification) and their interaction with individual-level socioeconomic status (education-level) on long-term outcomes following total joint arthroplasty (TJA) surgery.

Patients and Methods

This was a cohort study of 46,828 TJA surgeries performed on patients at a tertiary care hospital between January 1, 2000 and December 31, 2019. Cox proportional hazards models were used to examine the association between ADI and rurality and their interaction with individual-level education on the risk of periprosthetic joint infections, revision surgery, and mortality.

Results

At the time of surgery, 2589 (6%) patients lived in the most deprived neighborhoods (ADI quintile >80%) and 10,728 (23%) lived in small isolated rural towns. Patients from the most deprived neighborhoods were more likely to experience revision surgery (hazard ratio, [HR], 1.39; 95% CI, 1.10-1.76) and mortality (HR, 1.24; 95% CI, 1.09-1.42). Patients from small rural towns were also more likely to undergo revision surgery (HR, 1.14; 95% CI, 1.01-1.28). The mortality risk was 13%, 18%, and 24% higher for patients in the 3 highest ADI quintiles than those from the lowest quintile. Education gradient was more notable in the least deprived neighborhoods than in the most deprived neighborhoods.

Conclusion

Neighborhood disadvantage and rurality are negatively associated with the risk of revision surgery and both independently and in interaction with individual-level education with the risk of mortality. There is a need for population-level health interventions to mitigate area-based socioeconomic disadvantages in TJA.

Association of Rurality and Neighborhood Level Socioeconomic Deprivation with Perioperative Health Status in Total Joint Arthroplasty Patients: Analysis from a Large, Tertiary Care Hospital

BACKGROUND

Individual socioeconomic status (SES) is associated with disparities in access to care and worse outcomes in total joint arthroplasty (TJA). Neighborhood-level SES measures are sometimes used as a proxy for individual-level SES, but the validity of this approach is unknown. We examined neighborhood level SES and rurality on perioperative health status in TJA.

METHODS

The study population comprised 46,828 TJA surgeries performed at a tertiary care hospital. Community area deprivation index (ADI) was derived from the 2015 American Census Survey. Logistic regression was used to examine perioperative characteristics by ADI and rurality.

RESULTS

Compared to patients from the least deprived neighborhoods, patients from the most deprived neighborhoods were likely to be female (odds ratioOR 1.46, 95% confidence interval CI: 1.33-1.61), non-white (OR 1.36, 95% CI: 1.13-1.64), with education high school or less (OR 4.85, 95% CI: 4.35-5.41), be current smokers (OR 2.20, 95% CI: 1.61-2.49), have BMI>30 kg/m² (OR 1.43, 95% CI: 1.30-1.57), more limitation on instrumental activities of daily living (OR 1.75, 95% CI: 1.55-1.97) and American Society of Anesthesiologists (ASA) score > II (OR 2.0, 95% CI: 1.11-1.37). There was a progressive association between the degree of area level deprivation with preexisting comorbidities. Patients from rural communities were more likely to be male, white, have body mass index (BMI)>30 kg/m² and lower education levels. However, rurality was either not associated or negatively associated with comorbidities.

CONCLUSION

TJA patients from lower SES neighborhoods have worse behavioral risk factors and higher comorbidity burden than patients from higher SES neighborhoods. Patients from rural communities have worse behavioral risk factors but not comorbidities.

Assessment of Ethno-racial and Insurance-based Disparities in Pediatric Forearm and Tibial Fracture Care in the United States

INTRODUCTION

Despite growing attention to healthcare disparities and interventions to improve inequalities, additional identification of disparities is needed, particularly in the pediatric population. We used state and nationwide databases to identify factors associated with the surgical treatment of pediatric forearm and tibial fractures.

METHODS

The Healthcare Cost and Utilization Project State Inpatient, Emergency Department, and Ambulatory Surgery and Services Databases from four US states and the Nationwide Emergency Department Sample database were quarried using International Classification of Diseases codes to identify patients from 2006 to 2015. Multivariable regression models were used to determine factors associated with surgical treatment.

RESULTS

State databases identified 130,006 forearm (1575 open) and 51,979 tibial fractures (1339 open). Surgical treatment was done in 2.6% of closed and 37.5% of open forearm fractures and 7.9% of closed and 60.5% of open tibial fractures. A national estimated total of 3,312,807 closed and 46,569 open forearm fractures were included, 59,024 (1.8%) of which were treated surgically. A total of 719,374 closed and 26,144 open tibial fractures were identified; 52,506 (7.0%) were treated surgically. Multivariable regression revealed that race and/or insurance status were independent predictors for the lower likelihood of surgery in 3 of 4 groups: Black patients were 43% and 35% less likely to have surgery after closed and open forearm fractures, respectively, and patients with Medicaid were less often treated surgically for open tibial fractures in state (17%) and nationwide (20%) databases.

CONCLUSIONS

Disparities in pediatric forearm and tibial fracture care persist, especially for Black patients and those with Medicaid; identification of influencing factors and interventions to address them are important in improving equality and value of care.

Adjusting for Social Risk Factors in Pediatric Quality Measures: Adding to the Evidence Base

BACKGROUND

Outcome and utilization quality measures are adjusted for patient case-mix including demographic characteristics and comorbid conditions to allow for comparisons between hospitals and health plans. However, controversy exists around whether and how to adjust for social risk factors.

OBJECTIVE

To assess an approach to incorporating social risk variables into a pediatric measure of utilization from the Pediatric Quality Measures Program (PQMP).

METHODS

We used data from California Medicaid claims (2015-16) and Massachusetts All Payer Claims Database (2014-2015) to calculate health plan performance using measure specifications from the Pediatric Asthma Emergency Department Use measure. Health plan performance categories were assessed using mixed effect negative binomial models with and without adjustment for social risk factors, with both models adjusting for age, gender and chronic condition category. Mixed effects linear models were then used to compare patient social risk for health plans that changed performance categories to patient social risk for health plans that did not.

RESULTS

Of 133 health plans, serving 404,649 pediatric patients with asthma, 7% to 13% changed performance categories after social risk adjustment. Health plans that moved to higher performance categories cared for lower socioeconomic status (SES) patients whereas those that moved to lower performance categories cared for higher SES patients.

CONCLUSIONS

Adjustment for social risk factors changed performance rankings on the PQMP Pediatric Asthma Emergency Department Use measure for a substantial number of health plans. Some health plans caring for higher risk patients performed more poorly when social risk factors were not included in risk adjustment models. In light of this, social risk factors are incorporated into the National Quality Forum-endorsed measure; whether to incorporate social risk factors into pediatric quality measures will differ depending on the use case.

Three-Year Impact Of Stratification In The Medicare Hospital Readmissions Reduction Program

The Medicare Hospital Readmissions Reduction Program (HRRP) financially penalizes hospitals with high readmission rates. In fiscal year 2019 the program was changed to account for the association between social risk and high readmission rates. The new approach stratifies hospitals into five groups by hospitals' proportion of patients dually enrolled in Medicare and Medicaid, and it evaluates performance within each stratum instead of within the national cohort. Its impact on hospitals caring for vulnerable populations has not been studied. We calculated the change in average annual penalty percentage, before and after stratification, for safety-net hospitals, rural hospitals, and hospitals caring for a high share of Black and Hispanic or Latino patients. We found that stratification by proportion of dual enrollees was associated with a decrease in penalties by -0.09 percentage points at hospitals with the highest proportion of dual enrollees, -0.08 percentage points at rural hospitals, and -0.06 percentage points at hospitals with a large share of Black and Hispanic or Latino patients. Fully adjusted analyses suggest that these patterns were driven by penalty reductions at rural hospitals and hospitals disproportionately serving Black and Hispanic or Latino patients. Given the allocation of fewer penalties to these hospitals, we conclude that the stratification mandate was a modest step toward equity within the HRRP.

Residual Confounding in Health Plan Performance Assessments: Evidence From Randomization in Medicaid

BACKGROUND

Risk adjustment is used widely in payment systems and performance assessments, but the extent to which it distinguishes plan or provider effects from confounding due to patient differences is typically unknown.

OBJECTIVE

To assess the degree to which risk-adjusted measures of health plan performance adequately adjust for the variation across plans that arises because of differences in patient characteristics (residual confounding).

DESIGN

Comparison between plan performance estimates based on enrollees who made plan choices (observational population) and estimates based on enrollees assigned to plans (randomized population).

SETTING

Natural experiment in which more than two thirds of a state's Medicaid population in 1 region was randomly assigned to 1 of 5 plans.

PARTICIPANTS

137 933 enrollees in 2013 to 2014, of whom 31.1% selected a plan and 68.9% were randomly assigned to 1 of the same 5 plans.

MEASUREMENTS

Annual total spending (that is, payments to providers), primary care use, dental care use, and avoidable emergency department visits, all scored as plan-specific deviations from the "average" plan performance within each population.

RESULTS

Enrollee characteristics were appreciably imbalanced across plans in the observational population, as expected, but were not in the randomized population. Annual total spending varied across plans more in the observational population (SD, $147 per enrollee) than in the randomized population (SD, $70 per enrollee) after accounting for baseline differences in the observational and randomized populations and for differences across plans. On average, a plan's spending score (its deviation from the "average" performance) in the observational population differed from its score in the randomized population by $67 per enrollee in absolute value (95% CI, $38 to $123), or 4.2% of mean spending per enrollee (P = 0.009, rejecting the null hypothesis that this difference would be expected from sampling error). The difference was reduced modestly by risk adjustment to $62 per enrollee (P = 0.012). Residual confounding was similarly substantial for most other performance measures. Further adjustment for social factors did not materially change estimates.

LIMITATION

Potential heterogeneity in plan effects between the 2 populations.

CONCLUSION

Residual confounding in risk-adjusted performance assessments can be substantial and should caution policymakers against assuming that risk adjustment isolates real differences in plan performance.

PRIMARY FUNDING SOURCE

Arnold Ventures.

Association between unmet medication needs after hospital discharge and readmission or death among acute respiratory failure survivors: the addressing post-intensive care syndrome (APICS-01) multicenter prospective cohort study

Introduction

Survivors of acute respiratory failure (ARF) commonly experience long-lasting physical, cognitive, and/or mental health impairments. Unmet medication needs occurring immediately after hospital discharge may have an important effect on subsequent recovery.

Methods and analysis

In this multicenter prospective cohort study, we enrolled ARF survivors who were discharged directly home from their acute care hospitalization. The primary exposure was unmet medication needs. The primary outcome was hospital readmission or death within 3 months after discharge. We performed a propensity score analysis, using inverse probability weighting for the primary exposure, to evaluate the exposure–outcome association, with an a priori sample size of 200 ARF survivors.

Results

We enrolled 200 ARF survivors, of whom 107 (53%) were female and 77 (39%) were people of color. Median (IQR) age was 55 (43–66) years, APACHE II score 20 (15–26) points, and hospital length of stay 14 (9–21) days. Of the 200 participants, 195 (98%) were in the analytic cohort. One hundred fourteen (57%) patients had at least one unmet medication need; the proportion of medication needs that were unmet was 6% (0–15%). Fifty-six (29%) patients were readmitted or died by 3 months; 10 (5%) died within 3 months. Unmet needs were not associated (risk ratio 1.25; 95% CI 0.75–2.1) with hospital readmission or death, although a higher proportion of unmet needs may have been associated with increased hospital readmission (risk ratio 1.7; 95% CI 0.96–3.1) and decreased mortality (risk ratio 0.13; 95% CI 0.02–0.99).

Discussion

Unmet medication needs are common among survivors of acute respiratory failure shortly after discharge home. The association of unmet medication needs with 3-month readmission and mortality is complex and requires additional investigation to inform clinical trials of interventions to reduce unmet medication needs.

Study registration number: NCT03738774. The study was prospectively registered before enrollment of the first patient.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13054-021-03848-3.

Luck of the draw: Role of chance in the assignment of medicare readmissions penalties

Pay-for-performance programs are one strategy used by health plans to improve the efficiency and quality of care delivered to beneficiaries. Under such programs, providers are often compared against their peers in order to win bonuses or face penalties in payment. Yet luck has the potential to affect performance assessment through randomness in the sorting of patients among providers or through random events during the evaluation period. To investigate the impact luck can have on the assessment of performance, we investigated its role in assigning penalties under Medicare's Hospital Readmissions Reduction Policy (HRRP), a program that penalizes hospitals with excess readmissions. We performed simulations that estimated program hospitals' 2015 readmission penalties in 1,000 different hypothetical fiscal years. These hypothetical fiscal years were created by: (a) randomly varying which patients were admitted to each hospital and (b) randomly varying the readmission status of discharged patients. We found significant differences in penalty sizes and probability of penalty across hypothetical fiscal years, signifying the importance of luck in readmission performance under the HRRP. Nearly all of the impact from luck arose from events occurring after hospital discharge. Luck played a smaller role in determining penalties for hospitals with more beds, teaching hospitals, and safety-net hospitals.

Socio-demographic and -economic factors associated with 30-day readmission for conditions targeted by the hospital readmissions reduction program: a population-based study

Background

Early hospital readmissions remain common in patients with conditions targeted by the CMS Hospital Readmission Reduction Program (HRRP). There is still no consensus on whether readmission measures should be adjusted based on social factors, and there are few population studies within the U.S. examining how social characteristics influence readmissions for HRRP-targeted conditions. The objective of this study was to determine if specific socio-demographic and -economic factors are associated with 30-day readmissions in HRRP-targeted conditions: acute exacerbation of chronic obstructive pulmonary disease, pneumonia, acute myocardial infarction, and heart failure.

Methods

The Nationwide Readmissions Database was used to identify patients admitted with HRRP-targeted conditions between January 1, 2010 and September 30, 2015. Stroke was included as a control condition because it is not included in the HRRP. Multivariate models were used to assess the relationship between three social and economic characteristics (gender, urban/rural hospital designation, and estimated median household income within the patient’s zip code) and 30-day readmission rates using a hierarchical two-level logistic model. Age-adjusted models were used to assess relationship differences between Medicare vs. non-Medicare populations.

Results

There were 19,253,997 weighted index hospital admissions for all diagnoses and 3,613,488 30-day readmissions between 2010 and 2015. Patients in the lowest income quartile (≤$37,999) had an increased odds of 30-day readmission across all conditions (P < 0.0001). Female gender and rural hospital designation were associated with a decreased odds of 30-day readmission for most targeted conditions (P < 0.05). Similar findings were also seen in patients ≥65 years old.

Conclusions

Socio-demographic and -economic factors are associated with 30-day readmission rates and should be incorporated into tools or interventions to improve discharge planning and mitigate against readmission.

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.

Stability over time of the "hospital effect" on 30-day unplanned readmissions: Evidence from administrative data

Past studies showed that hospital characteristics affect hospital performance in terms of 30-day unplanned readmissions, proving the existence of a "hospital effect". However, the stability over time of this effect has been under-investigated. This study offers new evidence about the stability over time of the hospital effect on 30-day unplanned readmissions. Using 78,907 heart failure (HF) records collected from 116 hospitals in the Lombardy Region (Northern Italy) over three years (2010-2012), this study analysed hospital performance in terms of 30-day unplanned readmissions. Hospitals with unusually high and low readmission rates were identified through multi-level regression that combined both patient and hospital covariates in each year. Our results confirm that although hospital covariates - and the connected managerial choices - affect the 30-day unplanned readmissions of a specific year, their effect is not stable in the short-term (3 years). This has important implications for pay-for-performance schemes and quality improvement initiatives.

The Association with COPD Readmission Rate and Access to Medical Institutions in Elderly Patients

Purpose

Up to 20% of patients with chronic obstructive pulmonary disease (COPD) require re-admission within 30 days of discharge after hospitalization for acute exacerbations of the disease. These re-admissions can increase morbidity and the economic burden of COPD. Reducing re-admissions has become a policy target in many developed countries. We investigated the risk factors for COPD re-admissions among older adults with COPD.

Patients and Methods

Data obtained from the National Health Insurance Service-Senior Cohort (NHIS-SC) in Korea were analyzed. The subjects included 558,147 patients aged ≥70 who had been admitted for COPD between 2013 and 2015. Re-admission was defined as being re-hospitalized within 30 days after discharge. The key variables selected from the database included income-based insurance contributions, demographical variables, information on inpatient medical services, types of healthcare facilities, and emergency time relevance index (TRI). The TRI is a regional medical-use analysis index that evaluates whether the capacity of the medical services available is appropriate for the medical needs of the target residents.

Results

In 814 COPD re-admission cases among 4867 total admissions due to COPD in elderly subjects, higher re-admission rates were associated with male sex, admission to district hospitals, medical aid recipients, and a longer hospital stay. When additionally adjusting the TRI to identify the difference in re-admission rates due to medical service accessibility, the same results were found, except for the areas of residence. The TRI was lower in re-admission cases (odds ratio 0.991 [95% CI, 0.984‒0.998], P = 0.013).

Conclusion

In this study, COPD re-admission rates among older adults were significantly associated with sex, length of hospital stay, and the type of hospital. The capacity of the medical services provided was also related to the COPD re-admission rate. Better access to appropriate emergency services is associated with reduction of COPD re-admission rates.

The Effects of Harm Events on 30-Day Readmission in Surgical Patients

ABSTRACT

Readmission is an increasingly important focus for improvement regarding quality, value, and patient burden in our surgical patient population. We hypothesized that inpatient harm events increase the likelihood of readmission in surgical patients. We created a system-wide inpatient registry with 30-day readmission. A surgical subset was created, and harm events were tracked through the electronic health record system. Between 2015 and 2017, 37,048 surgical patient encounters met inclusion criterion. A total of 2,887 patients (7.69%) were readmitted. After multiple logistic regression of the highly significant harm measures, seven harm measures remained statistically significant (p < .05). Those with the three highest odds ratios were mucosal pressure ulcer, Clostridium difficile, and glucose <40. Incorporating harm measures to the traditional risk, predictive model for 30-day readmission improved our model performance (area under the ROC curve from 0.68 to 0.71). This study demonstrated that inpatient hospital-based harm events can be electronically monitored and used to predict 30-day readmission.

Diverse perspectives on hospitalisation events among people with dementia: protocol for a multisite qualitative study

INTRODUCTION

People living with dementia (PLWD) are more likely to experience hospitalisation events (hospitalisation, rehospitalisation) than those without dementia. Many hospitalisation events, particularly rehospitalisation within 30 days of discharge, are thought to be avoidable. Yet our understanding of dementia-specific risk and protective factors surrounding avoidable hospitalisation is limited to specific intersetting transitions and predominantly clinician perspectives. Broader insights are needed to design accessible and effective solutions for reducing avoidable hospitalisations. We have designed the Stakeholders Understanding of Prevention Protection and Opportunities to Reduce HospiTalizations (SUPPORT) Study to address these gaps. The objectives of the SUPPORT Study are to elicit and examine family caregiver, community and hospital providers' perspectives on avoidable hospitalisation events among PLWD, and to identify opportunities for effective prevention.

METHODS AND ANALYSIS

We will conduct a multisite, descriptive qualitative study to interview around 100 family caregivers, community and hospital providers. We will identify and sample from regions and communities with higher socio-contextual disadvantage and hospital utilisation, and will aim to recruit individuals representing diverse racial/ethnic backgrounds. Interviews will follow a descriptive qualitative design in conjunction with constant comparison techniques to sample divergent situations and events. We will employ a range of analytical approaches to address specific research questions including thematic (inductive and deductive), comparative and dimensional analysis. Interviews will be conducted individually or in focus groups and follow a semistructured interview guide.

ETHICS AND DISSEMINATION

The study is approved by the University of Wisconsin-Madison Institutional Review Board. Informed consent procedures will incorporate steps to evaluate capacity to provide informed consent in the event that participants express concerns with thinking or memory or demonstrate challenges recalling study details during the consent process to ensure capacity to consent to participation. A series of publicly available reports, seminars and symposia will be undertaken in collaboration with collaborating organisation partners.

Temporal Trends in Racial Differences in 30-Day Readmission and Mortality Rates After Acute Myocardial Infarction Among Medicare Beneficiaries

Importance

The association of the Hospital Readmission Reduction Program (HRRP) with reductions in racial disparities in 30-day outcomes for myocardial infarction (MI), is unknown, including whether this varies by HRRP hospital penalty status.

Objective

To assess temporal trends in 30-day readmission and mortality rates among black and nonblack patients discharged after hospitalization for acute MI at low-performing and high-performing hospitals, as defined by readmission penalty status after HRRP implementation.

Design, Setting, and Participants

This observational cohort analysis used data from the multicenter National Cardiovascular Data Registry Chest Pain-MI Registry centers that were subject to the first cycle of HRRP, between January 1, 2008, and November 30, 2016. All patients hospitalized with MI who were included in National Cardiovascular Data Registry Chest Pain-MI Registry were included in the analysis. Data were analyzed from April 2018 to September 2019.

Exposures

Hospital performance category and race (black compared with nonblack patients). Centers were classified as high performing or low performing based on the excess readmission ratio (predicted to expected 30-day risk adjusted readmission rate) for MI during the first HRRP cycle (in October 2012).

Main Outcomes and Measures

Thirty-day all-cause readmission and mortality rates.

Results

Among 753 hospitals that treated 155 397 patients with acute MI (of whom 11 280 [7.3%] were black), 399 hospitals (53.0%) were high performing. Thirty-day readmission rates declined over time in both black and nonblack patients (annualized 30-day readmission rate: 17.9% vs 20.8%). Black (compared with nonblack) race was associated with higher unadjusted odds of 30-day readmission in both low-performing and high-performing centers (odds ratios: before HRRP: low-performing hospitals, 1.14 [95% CI, 1.03-1.26]; P = .01; high-performing hospitals, 1.17 [95% CI, 1.04-1.32]; P = .01; after HRRP: low-performing hospitals, 1.23 [95% CI, 1.13-1.34]; P < .001; high-performing hospitals, 1.25 [95% CI, 1.12-1.39]; P < .001). However, these racial differences were not significant after adjustment for patient characteristics. The 30-day mortality rates declined significantly over time in nonblack patients, with stable (nonsignificant) temporal trends among black patients. Adjusted associations between race and 30-day mortality showed that 30-day mortality rates were significantly lower among black (compared with nonblack) patients in the low-performing hospitals (odds ratios: pre-HRRP, 0.79 [95% CI, 0.63-0.97]; P = .03; post-HRRP, 0.80 [95% CI, 0.68-0.95]; P = .01) but not in high-performing hospitals. Finally, the association between race and 30-day outcomes did not vary after the HRRP period began in either high-performing or low-performing hospitals.

Conclusions and Relevance

In this analysis, 30-day readmission rates among patients with MI declined over time for both black and nonblack patients. Differences in race-specific 30-day readmission rates persisted but appeared to be attributable to patient-level factors. The 30-day mortality rates have declined for nonblack patients and remained stable among black patients. Implementation of the HRRP was not associated with improvement or worsening of racial disparities in readmission and mortality rates.

Do penalty-based pay-for-performance programs improve surgical care more effectively than other payment strategies? A systematic review

Background

The aim of this systematic review is to assess if penalty-based pay-for-performance (P4P) programs are more effective in improving quality and cost outcomes compared to two other payment strategies (i.e., rewards and a combination of rewards and penalties) for surgical care in the United States. Penalty-based programs have gained in popularity because of their potential to motivate behavioral change more effectively than reward-based programs to improve quality of care. However, little is known about whether penalties are more effective than other strategies.

Materials and methods

A systematic literature review was conducted according to the PRISMA guideline to identify studies that evaluated the effects of P4P programs on quality and cost outcomes for surgical care. Five databases were used to search studies published from 2003 to March 1, 2020. Studies were selected based on the PRISMA guidelines. Methodological quality of individual studies was assessed based on ROBINS-I with GRADE approach.

Results

This review included 22 studies. Fifteen cross-sectional, 1 prospective cohort, 4 retrospective cohort, and 2 case-control studies were found. We identified 11 unique P4P programs: 5 used rewards, 3 used penalties, and 3 used a combination of rewards and penalties as a payment strategy. Five out of 10 studies reported positive effects of penalty-based programs, whereas evidence from studies evaluating P4P programs with a reward design or combination of rewards and penalties was little or null.

Conclusions

This review highlights that P4P programs with a penalty design could be more effective than programs using rewards or a combination of rewards and penalties to improve quality of surgical care.

•

Evidence on the effectiveness of pay-for-performance programs in quality improvement is mixed.

•

Five out of 10 studies reported positive effects of penalty-based programs.

•

Evidence from studies evaluating P4P programs with a reward design or combination of rewards and penalties was little or null.

•

The increasing use of penalty-based pay-for-performance programs has the potential to improve surgical care quality.

•

Penalties may induce stronger provider and hospital behavioral change than other payment strategies.

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.

Are Improvements Still Needed to the Modified Hospital Readmissions Reduction Program: a Health and Retirement Study (2000-2014)?

BACKGROUND

To address concerns that the Hospital Readmissions Reduction Program (HRRP) unfairly penalized safety net hospitals treating patients with high social and functional risks, Medicare recently modified HRRP to compare hospitals with similar proportions of high-risk, dual-eligible patients ("peer group hospitals"). Whether the change fully accounts for patients' social and functional risks is unknown.

OBJECTIVE

Examine risk-standardized readmission rates (RSRRs) and hospital penalties after adding patient-level social and functional and community-level risk factors.

DESIGN

Using 2000-2014 Medicare hospital discharge, Health and Retirement Study, and community-level data, latent factors for patient social and functional factors and community factors were identified. We estimated RSRRs for peer groups and by safety net status using four hierarchical logistic regression models: "base" (HRRP model); "patient" (base plus patient factors); "community" (base plus community factors); and "full" (all factors). The proportion of hospitals penalized was calculated by safety net status.

PATIENTS

20,255 fee-for-service Medicare beneficiaries (65+) with eligible index hospitalizations MAIN MEASURES: RSRRs KEY RESULTS: Half of safety net hospitals are in peer group 5. Compared with other hospitals, peer group 5 hospitals (most dual-eligibles) treated sicker, more functionally limited patients from socially disadvantaged groups. RSRRs decreased by 0.7% for peer groups 2 and 4 and 1.3% for peer group 5 under the patient and full (versus base) models. Measured performance improved after adjusting for patient risk factors for hospitals in peer group 4 and 5 hospitals, but worsened for those in peer groups 1, 2, and 3. Under the patient (versus base) model, fewer safety net hospitals (48.7% versus 51.3%) but more non-safety net hospitals (50.0% versus 49.1%) were penalized.

CONCLUSIONS

Patient-level risk adjustment decreased RSRRs for hospitals serving more at-risk patients and proportion of safety net hospitals penalized, while modestly increasing RSRRs and proportion of non-safety net hospitals penalized. Results suggest HRRP modifications may not fully account for hospital variation in patient-level risk.

Association of State Certificate of Need Regulation With Procedural Volume, Market Share, and Outcomes Among Medicare Beneficiaries

IMPORTANCE

Certificate of need laws provide state-level regulation of health system expenditure. These laws are intended to limit spending and control hospital expansion in order to prevent excess capacity and improve quality of care. Several states have recently introduced legislation to modify or repeal these regulations, as encouraged by executive order 13813, issued in October 2017 by the Trump administration.

OBJECTIVE

To evaluate the difference in markers of hospital activity and quality by state certificate of need status. These markers include hospital procedural volume, hospital market share, county-level procedures per 10 000 persons, and patient-level postoperative outcomes.

DESIGN, SETTING, AND PARTICIPANTS

A cross-sectional study involving Medicare beneficiaries aged 65 years or older who underwent 1 of the following 10 procedures from January 1, 2016, through November 30, 2018: total knee or hip arthroplasty, coronary artery bypass grafting, colectomy, ventral hernia repair, lower extremity vascular bypass, lung resection, pancreatic resection, cystectomy, or esophagectomy.

EXPOSURES

State certificate of need regulation status as determined by data from the National Conference of State Legislatures.

MAIN OUTCOMES AND MEASURES

Outcomes of interest included hospital procedural volume; hospital market share (range, 0-1; reflecting 0%-100% of market share); county-level procedures per 10 000 persons; and patient-level postoperative 30-day mortality, surgical site infection, and readmission.

RESULTS

A total of 1 545 952 patients (58.0% women; median age 72 years; interquartile range, 68-77 years) at 3631 hospitals underwent 1 of the 10 operations. Of these patients, 468 236 (30.3%) underwent procedures in the 15 states without certificate of need regulations and 1 077 716 (69.7%) in the 35 states with certificate of need regulations. The total number of procedures ranged between 729 855 total knee arthroplasties (47.21%) and 4558 esophagectomies (0.29%). When comparing states without vs with certificate of need regulations, there were no significant differences in overall hospital procedural volume (median hospital procedure volume, 241 vs 272 operations per hospital for 3 years; absolute difference, 31; 95% CI, -27.64 to 89.64; P = .30). There were no statistically significant differences between states without vs with certificate of need regulations for median hospital market share (median, 28% vs 52%; absolute difference, 24%; 95% CI, -5% to 55%; P = .11); procedure rates per 10 000 Medicare-eligible population (median, 239.23 vs 205.41 operations per Medicare-eligible population in 3 years; absolute difference, 33.82; 95% CI, -84.08 to 16.43; P = .19); or 30-day mortality (1.17% vs 1.33%, odds ratio [OR], 1.04; 95% CI, 0.93 to 1.16; P = .52), surgical site infection (1.24% vs 1.25%; OR, 0.93; 95% CI, 0.83 to 1.04; P = .21), or readmission rate (9.69% vs 8.40%; OR, 0.80; 95% CI, 0.57 to 1.12; P = .19).

CONCLUSIONS AND RELEVANCE

Among Medicare beneficiaries who underwent a range of surgical procedures from 2016 through 2018, there were no significant differences in markers of hospital volume or quality between states without vs with certificate of need laws. Policy makers should consider reevaluating whether the current approach to certificate of need regulation is achieving the intended objectives and whether those objectives should be updated.

Potentially Preventable Hospitalizations Among Older Adults: 2010-2014

PURPOSE

We undertook a study to examine national trends in potentially preventable hospitalizations-those for ambulatory care-sensitive conditions that could have been avoided if patients had timely access to primary care-across 3,200 counties and various subpopulations of older adults in the United States.

METHODS

We used 2010-2014 Medicare claims data to examine trends in potentially preventable hospitalizations among beneficiaries aged 65 years and older and developed heat maps to examine county-level variation. We used a generalized estimating equation and adjusted the model for demographics, comorbidities, dual eligibility (Medicare and Medicaid), ZIP code-level income, and county-level number of primary care physicians and hospitals.

RESULTS

Across the 3,200 study counties, potentially preventable hospitalizations decreased in 327 counties, increased in 123 counties, and did not change in the rest. At the population level, the adjusted rate of potentially preventable hospitalizations declined by 3.45 percentage points from 19.42% (95% CI, 18.4%-20.5%) in 2010 to 15.97% (95% CI, 15.3%-16.6%) in 2014; it declined by 2.93, 2.87, and 3.33 percentage points among White, Black, and Hispanic patients to 14.96% (95% CI, 14.67%-15.24%), 17.92% (95% CI, 17.27%-18.58%), and 17.10% (95% CI, 16.25%-18.0%), respectively. Similarly, the rate for dually eligible patients fell by 3.71 percentage points from 21.62% (95% CI, 20.5%-22.8%) in 2010 to 17.91% (95% CI, 17.2%-18.7%) in 2014. (P <.001 for all).

CONCLUSIONS

During 2010-2014, rates of potentially preventable hospitalization did not change in the majority of counties. At the population level, although the rate declined among all subpopulations, dually eligible patients and Black and Hispanic patients continued to have substantially higher rates compared with non-dually eligible and White patients, respectively.

Impact of Instrumental Activities of Daily Living Limitations on Hospital Readmission: an Observational Study Using Machine Learning

BACKGROUND

Limitations in instrumental activities of daily living (IADL) hinder a person's ability to live independently in the community and self-manage their conditions, but its impact on hospital readmission has not been firmly established.

OBJECTIVE

To test the importance of IADL dependency as a predictor of 30-day readmissions and quantify its impact relative to other morbidities.

DESIGN

A retrospective cohort study of the population-based Health and Retirement Study linked to Medicare claims data. Random forest was used to rank each predictor variable in terms of its ability to predict readmission. Classification and regression tree (CART) was used to identify complex multimorbidity combinations associated with high or low risk of readmission. Generalized linear regression was used to estimate the adjusted relative risk of readmission for IADL limitations.

SUBJECTS

Hospitalizations of adults age 65 and older (n = 20,007), from 6617 unique subjects.

MAIN MEASURES

The main outcome was 30-day all-cause unplanned readmission. The main predictor of interest was self-reported IADL limitation. Other key predictors were self-reported complex multimorbidity including chronic diseases, geriatric syndromes, and activities of daily living (ADL) limitations, along with demographic, socioeconomic, and behavioral factors.

KEY RESULTS

The overall 30-day readmission rate in the study was 16.4%. Random forest analysis ranked ADLs and IADL limitations as the two most important predictors of 30-day readmission. CART identified hospitalizations of patients with IADL limitations and diabetes as a subgroup at the highest risk of readmission (26% readmitted). Multivariable regression analyses showed that ADL limitations were associated with 1.17 (1.06-1.29) times higher risk of readmission even after adjusting for other patient covariates. Risk prediction was modest though for even the best model (AUC = 0.612).

CONCLUSIONS

IADL limitations are key predictors of 30-day readmission as demonstrated using several machine learning methods. Routine assessment of functional abilities in hospital settings could help identify those most at risk.

Dual eligible patients are not the same: How social risk may impact quality measurement's ability to reduce inequities

BACKGROUND

CMS recently decided to produce private "healthcare disparities reports" that include dual eligibility (DE) as the sole stratifying variable used to assess pneumonia readmission disparities.

RESEARCH DESIGN

We measure the relationship between DE status and readmissions, both with and without conceptually relevant social risk factors, including air pollution, severe housing problems, and food insecurity, using data from county- and hospital-level readmission rates, DE status, and social risk factors.

RESULTS

At the county level, the relationship between DE status and readmissions is partially confounded by at least three social risk factors. DE populations vary widely across hospitals, creating unequal between-hospital comparisons.

CONCLUSIONS

Because of differences in the DE population, between-hospital comparisons could be misleading using a methodology that stratifies by DE only. We suggest viable alternatives to sole-factor stratification to properly account for social risk factors and better isolate quality differences that might yield readmission rate inequities.

IMPLICATIONS

CMS's healthcare disparities reports provided to hospitals are limited by relying exclusively on DE proportion as the measure of social risk, undercutting the power of quality measurement and its related incentives to close or minimize healthcare inequities.

Effects of quality-based procedure hospital funding reform in Ontario, Canada: An interrupted time series study

Background

The Government of Ontario, Canada, announced hospital funding reforms in 2011, including Quality-based Procedures (QBPs) involving pre-set funds for managing patients with specific diagnoses/procedures. A key goal was to improve quality of care across the jurisdiction.

Methods

Interrupted time series evaluated the policy change, focusing on four QBPs (congestive heart failure, hip fracture surgery, pneumonia, prostate cancer surgery), on patients hospitalized 2010–2017. Outcomes included return to hospital or death within 30 days, acute length of stay (LOS), volume of admissions, and patient characteristics.

Results

At 2 years post-QBPs, the percentage of hip fracture patients who returned to hospital or died was 3.13% higher in absolute terms (95% CI: 0.37% to 5.89%) than if QBPs had not been introduced. There were no other statistically significant changes for return to hospital or death. For LOS, the only statistically significant change was an increase for prostate cancer surgery of 0.33 days (95% CI: 0.07 to 0.59). Volume increased for congestive heart failure admissions by 80 patients (95% CI: 2 to 159) and decreased for hip fracture surgery by 138 patients (95% CI: -183 to -93) but did not change for pneumonia or prostate cancer surgery. The percentage of patients who lived in the lowest neighborhood income quintile increased slightly for those diagnosed with congestive heart failure (1.89%; 95% CI: 0.51% to 3.27%) and decreased for those who underwent prostate cancer surgery (-2.08%; 95% CI: -3.74% to -0.43%).

Interpretation

This policy initiative involving a change to hospital funding for certain conditions was not associated with substantial, jurisdictional-level changes in access or quality.

Financial Performance of Hospitals in the Appalachian Region Under the Hospital Readmissions Reduction Program and Hospital Value-Based Purchasing Program

PURPOSE

The Hospital Readmission and Reduction Program (HRRP) and Hospital Value-Based Purchasing Program (HVBP) propose to improve quality of patient care by either rewarding or penalizing hospitals through inpatient reimbursement. This study analyzes the effect of both programs on profitability of hospitals located in the Appalachian Region (AR) compared to hospitals in Appalachian states and the rest of the United States.

METHODS

This study used a retrospective research design with a longitudinal unbalanced panel dataset from 2008 to 2015. Hospitals participating in both HRRP and HVBP during this time frame were included in the study. A difference-in-difference model with hospital-level fixed effects, controlling for hospital and market characteristics, was used to determine effects of both programs on profitability of hospitals serving the AR, Appalachian states, and the rest of the United States.

FINDINGS

After implementation of HRRP and HVBP, only hospitals located in Appalachian states experienced a significant decrease in operating margin (-1.14 percentage points). Unexpectedly, during the same time period, total margin increased significantly for hospitals located in the AR (1.05 percentage points), Appalachian states (1.71 percentage points), and the rest of the United States (2.38 percentage points).

CONCLUSIONS

HRRP and HVBP financially incentivize hospitals to focus efforts on improving patient care. The programs may not have the anticipated results. Increases in total margin for all hospitals during the study period indicate access to nonpatient revenues, offsetting the financial penalties from both programs. This revenue source may undermine the program's objectives of delivering value and achieving quality outcomes.

Composite Outcomes of Mortality and Readmission in Patients with Heart Failure: Retrospective Review of Administrative Datasets

Background

Controlling the quality of care through readmissions and mortality for patients with heart failure (HF) is a national priority for healthcare regulators in developed countries. In this longitudinal cohort study, using administrative data such as hospital discharge forms (HDFs), emergency departments (EDs) accesses, and vital statistics, we test new covariates for predicting mortality and readmissions of patients hospitalized for HF and discuss the use of combined outcome as an alternative.

Methods

Logistic models, with a stepwise selection method, were estimated on 70% of the sample and validated on the remaining 30% to evaluate 30-day mortality, 30-day readmissions, and the combined outcome. We followed an extraction method for any-cause mortality and unplanned readmission within 30 days after incident HF hospitalization. Data on patient admission and previous history were extracted by HDFs and ED dataset.

Results

Our principal findings demonstrate that the model’s discriminant ability is consistent with literature both for mortality (AUC=0.738, CI (0.729–0.748)) and readmissions (AUC=0.578, CI (0.562–0.594)). Additionally, the discriminant ability of the composite outcome model is satisfactory (AUC=0.675, CI (0.666–0.684)).

Conclusion

Hospitalization characteristics and patient history introduced in the logistic models do not improve their discriminant ability. The composite outcome prediction is led more by mortality than readmission, without improvements for the comprehension of the readmission phenomenon.

Association of Medicaid Eligibility With Surgical Readmission Among Medicare Beneficiaries

IMPORTANCE

The Centers for Medicare & Medicaid Services is beginning to consider adjusting for social risk factors, such as dual eligibility for Medicare and Medicaid, when evaluating hospital performance under value-based purchasing programs. It is unknown whether dual eligibility represents a unique domain of social risk or instead represents clinical risk unmeasured by variables available in traditional Medicare claims.

OBJECTIVE

To assess how dual eligibility for Medicare and Medicaid is associated with risk-adjusted readmission rates after surgery.

DESIGN, SETTING, AND PARTICIPANTS

A retrospective cohort study was conducted of 55 651 Medicare beneficiaries undergoing general, vascular, and gynecologic surgery at 62 hospitals in Michigan between January 1, 2014, and December 1, 2016. Representative cohorts were derived from traditional Medicare claims (n = 29 710) and the Michigan Surgical Quality Collaborative (MSQC) clinical registry (n = 25 941), which includes additional measures of clinical risk. Statistical analysis was conducted between April 10 and July 15, 2019. The association between dual eligibility and risk-adjusted 30-day readmission rates after surgery was compared between models inclusive and exclusive of additional measurements of clinical risk. The study also examined how dual eligibility is associated with hospital profiling using risk-adjusted readmission rates.

EXPOSURES

Dual eligibility for Medicare and Medicaid.

MAIN OUTCOMES AND MEASURES

Risk-adjusted all-cause 30-day readmission after surgery.

RESULTS

There were a total of 3986 dual-eligible beneficiaries in the Medicare claims cohort (2554 women; mean [SD] age, 72.9 [6.9] years) and 1608 dual-eligible beneficiaries in the MSQC cohort (990 women; mean [SD] age, 72.9 [6.8] years). In both data sets, higher proportions of dual-eligible beneficiaries were younger, female, and nonwhite than Medicare-only beneficiaries (Medicare claims cohort: female, 2554 of 3986 [64.1%] vs 12 879 of 25 724 [50.1%]; nonwhite, 1225 of 3986 [30.7%] vs 2783 of 25 724 [10.8%]; MSQC cohort: female, 990 of 1608 [61.6%] vs 12 578 of 24 333 [51.7%]; nonwhite, 416 of 1608 [25.9%] vs 2176 of 24 333 [8.9%]). In the Medicare claims cohort, dual-eligible beneficiaries were more likely to be readmitted (15.5% [95% CI, 13.7%-17.3%]) than Medicare-only beneficiaries (13.3% [95% CI, 12.7%-13.9%]; difference, 2.2 percentage points [95% CI, 0.4-3.9 percentage points]). In the MSQC cohort, after adjustment for more granular measures of clinical risk, dual eligibility was not significantly associated with readmission (difference, 0.6 percentage points [95% CI, -1.0 to 2.2 percentage points]). In both the Medicare claims and MSQC cohorts, adding dual eligibility to risk-adjustment models had little association with hospital ranking using risk-adjusted readmission rates.

CONCLUSIONS AND RELEVANCE

This study suggests that dual eligibility for Medicare and Medicaid may reflect unmeasured clinical risk of readmission in claims data. Policy makers should consider incorporating more robust measures of social risk into risk-adjustment models used by value-based purchasing programs.

Neighborhood Disadvantage and Hospital Quality Ratings in the Medicare Hospital Compare Program

BACKGROUND

The Centers for Medicare and Medicaid Services provide nationwide hospital ratings that may influence reimbursement. These ratings do not account for the social risk of communities and may inadvertently penalize hospitals that service disadvantaged neighborhoods.

OBJECTIVE

This study examines the relationship between neighborhood social risk factors (SRFs) and hospital ratings in Medicare's Hospital Compare Program.

RESEARCH DESIGN

2017 Medicare Hospital Compare ratings were linked with block group data from the 2015 American Community Survey to assess hospital ratings as a function of neighborhood SRFs.

SUBJECTS

A total of 3608 Medicare-certified hospitals in 50 US states.

MEASURES

Hospital summary scores and 7 quality group scores (100 percentile scale), including effectiveness of care, efficiency of care, hospital readmission, mortality, patient experience, safety of care, and timeliness of care.

RESULTS

Lower hospital summary scores were associated with caring for neighborhoods with higher social risk, including a reduction in hospital score for every 10% of residents who reported dual-eligibility for Medicare/Medicaid [-3.3%; 95% confidence interval (CI), -4.7 to -2.0], no high-school diploma (-0.8%; 95% CI, -1.5 to -0.1), unemployment (-1.2%; 95% CI, -1.9 to -0.4), black race (-1.2%; 95% CI, -1.7 to -0.8), and high travel times to work (-2.5%; 95% CI, -3.3 to -1.6). Associations between neighborhood SRFs and hospital ratings were largest in the timeliness of care, patient experience, and hospital readmission groups; and smallest in the safety, efficiency, and effectiveness of care groups.

CONCLUSIONS

Hospitals serving communities with higher social risk may have lower ratings because of neighborhood factors. Failing to account for neighborhood social risk in hospital rating systems may reinforce hidden disincentives to care for medically underserved areas in the United States.

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.

Quality Measures in Postmastectomy Breast Reconstruction: Identifying Metrics to Improve Care

BACKGROUND

Specific measures tailored to the properties of individual procedures will ensure the appropriate evaluation of quality. Because postmastectomy breast reconstruction (PMBR) is becoming increasingly common, a review of the literature is timely to identify potential breast reconstruction-specific measures that can be applied by institutions and national healthcare organizations to improve quality.

METHODS

We searched PubMed and Embase for studies examining the quality of care for patients undergoing PMBR. Data extracted from the articles include basic study characteristics, the number of quality metrics, type of quality metric (defined by Donabedian model), and the domain of quality (defined by the National Academy of Medicine).

RESULTS

A total of 2,158 articles were identified in the initial search, and 440 studies were included for data extraction. The most common type of quality measure was outcome measures (91%), and the least common measure was structure measures (1%). The most common metrics were operative time (41%), hospital type (28%), and aspects of the patient-provider interactions (20%). Additionally, we found that timeliness and equity were least common among the 6 National Academy of Medicine domains.

CONCLUSIONS

We identified metrics utilized in the PMBR, some of which can be further investigated through high-level evidence studies and incorporated into policy. Because many factors influence surgical outcomes and breast reconstruction is driven by patient preferences, an inclusion of structure, process, and outcome metrics will help improve care for this patient population. Moreover, nonpunitive initiatives, specifically quality collaboratives, may provide an avenue to improve care quality without compromising patient safety.

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

OBJECTIVE

To investigate risk-adjusted, 30-day postdischarge heart failure mortality and readmission rates stratified by hospital teaching intensity.

DATA SOURCES AND STUDY SETTING

A total of 709 221 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.

STUDY DESIGN

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.

PRINCIPAL FINDINGS

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).

CONCLUSIONS

Heart failure readmission penalties disproportionately impact major teaching hospitals and inadequately credit their better postdischarge survival.

Evidence of the Linkage Between Hospital-based Care Coordination Strategies and Hospital Overall (Star) Ratings

BACKGROUND

In the new era of value-based payment models and pay for performance, hospitals are in search of the silver bullet strategy or bundle of strategies capable of improving their performance on quality measures.

OBJECTIVES

To determine whether there is an association between adoption of hospital-based care coordination strategies and Centers for Medicare and Medicaid Services overall hospital quality (star) ratings and readmission rates.

RESEARCH DESIGN

We used survey data from the American Hospital Association (AHA) and categorized respondents by the number of care coordination strategies that they reported having widely implemented. We used multiple logistic regression models to examine the association between the number of strategies and hospital overall rating performance and disease-specific 30-day excess readmission ratios, while controlling for hospital and county characteristics and state-fixed effects.

SUBJECTS

A total of 710 general acute care noncritical access hospitals that received star ratings and responded to the 2015 AHA Care Systems and Payment Survey.

MEASURES

Centers for Medicare and Medicaid Services overall hospital ratings, 30-day excess readmission ratios.

RESULTS

As compared with hospitals with 0-2 strategies, hospitals with 3 to 4 strategies (P=0.007), 5-7 strategies (P=0.002), or 8-12 strategies (P=0.002) had approximately 2.5× the odds of receiving a top rating (4 or 5 stars). Care coordination strategies were positively associated with lower 30-day readmission ratios for patients with chronic medical conditions, but not for surgical patients. Medication reconciliation, visit summaries, outreach after discharge, discharge care plans, and disease management programs were each individually associated with top ratings.

CONCLUSIONS

Care coordination strategies are associated with high overall hospital ratings.

Impact of the Medicare hospital readmissions reduction program on vulnerable populations

BACKGROUND

The Hospital Readmissions Reduction Program (HRRP) was established by the 2010 Patient Protection and Affordable Care Act (ACA) in an effort to reduce excess hospital readmissions, lower health care costs, and improve patient safety and outcomes. Although studies have examined the policy's overall impacts and differences by hospital types, research is limited on its effects for different types of vulnerable populations. The aim of this study was to analyze the impact of the HRRP on readmissions for three targeted conditions (acute myocardial infarction, heart failure, and pneumonia) among four types of vulnerable populations, including low-income patients, patients served by hospitals that serve a high percentage of low-income or Medicaid patients, and high-risk patients at the highest quartile of the Elixhauser comorbidity index score.

METHODS

Data on patient and hospital information came from the Nationwide Readmission Database (NRD), which contained all discharges from community hospitals in 27 states during 2010-2014. Using difference-in-difference (DD) models, linear probability regressions were conducted for the entire sample and sub-samples of patients and hospitals in order to isolate the effect of the HRRP on vulnerable populations. Multiple combinations of treatment and control groups and triple difference (DDD) methods were used for testing the robustness of the results. All models controlled for the patient and hospital characteristics.

RESULTS

There have been statistically significant reductions in readmission rates overall as well as for vulnerable populations, especially for acute myocardial infarction patients in hospitals serving the largest percentage of low-income patients and high-risk patients. There is also evidence of spillover effects for non-targeted conditions among Medicare patients compared to privately insured patients.

CONCLUSIONS

The HRRP appears to have created the right incentives for reducing readmissions not only overall but also for vulnerable populations, accruing societal benefits in addition to previously found reductions in costs. As the reduction in the rate of readmissions is not consistent across patient and hospital groups, there could be benefits to adjusting the policy according to the socioeconomic status of a hospital's patients and neighborhood.

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

IMPORTANCE

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.

OBJECTIVE

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.

DESIGN, SETTING, AND PARTICIPANTS

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.

EXPOSURES

Annual hospital THA and TKA volume, other hospital-level characteristics, and patient factors used in HRRP risk adjustment.

MAIN OUTCOMES AND MEASURES

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.

RESULTS

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.

CONCLUSIONS AND RELEVANCE

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.

Changes in coding of pneumonia and impact on the Hospital Readmission Reduction Program

OBJECTIVE

To evaluate whether changes in diagnosis assignment explain reductions in 30-day readmission for patients with pneumonia following the Hospital Readmission Reduction Program (HRRP).

DATA SOURCES

100 percent MedPAR, 2008-2015.

STUDY DESIGN

Retrospective cohort study of Medicare discharges in HRRP-eligible hospitals. Outcomes were 30-day readmission rates for pneumonia under a "narrow" definition (used for the HRRP until October 2015; n = 2 288 644) and a "broad" definition that included certain diagnoses of sepsis and aspiration pneumonia (used since October 2015; n = 3 618 215). We estimated changes in 30-day readmissions in the pre-HRRP period (January 2008-March 2010), the HRRP implementation period (April 2010-September 2012), and the HRRP penalty period (October 2012-June 2015).

PRINCIPAL FINDINGS

Under the narrow definition, adjusted annual readmission rates changed by +0.07 percentage points (pp) during the pre-HRRP period (95% CI: -0.03 pp, +0.18 pp), -1.07 pp during HRRP implementation (95% CI: -1.15 pp, -0.99 pp), and -0.09 pp during the penalty period (95% CI: -0.18 pp, -0.00 pp). Under the broad definition, 30-day readmissions changed by +0.21 pp during the pre-HRRP period (95% CI: +0.12 pp, +0.30 pp), -1.28 pp during HRRP implementation (95% CI: -1.35 pp, -1.21 pp), and -0.09 pp during the penalty period (95% CI: -0.16 pp, -0.02 pp).

CONCLUSIONS

Changes in the coding of inpatient pneumonia admissions do not explain readmission reduction following the HRRP.

Multilevel Analysis of Readmissions After Radical Cystectomy for Bladder Cancer in the USA: Does the Hospital Make a Difference?

BACKGROUND

Hospitals are increasingly being held responsible for their readmissions rates. The contribution of hospital versus patient factors (eg, case mix) to hospital readmissions is unknown.

OBJECTIVE

To estimate the relative contribution of hospital and patient factors to readmissions after radical cystectomy (RC) for bladder cancer.

DESIGN, SETTING, AND PARTICIPANTS

We identified individuals who underwent RC in 2014 in the Nationwide Readmissions Database (NRD). The NRD is a nationally representative (USA), all-payer database that includes readmissions at index and nonindex hospitals. Survey weights were used to generate national estimates.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

The main outcome was readmission within 30 d after RC. Using a multilevel mixed-effects model, we estimated the statistical association between patient and hospital characteristics and readmission. A hospital-level random-effects term was used to estimate hospital-level readmission rates while holding patient characteristics constant.

RESULTS AND LIMITATIONS

We identified a weighted sample of 7095 individuals who underwent RC at 341 hospitals in the USA. The 30-d readmission rate was 29.5% (95% confidence interval [CI] 27.8-31.2%), ranging from 1.4% (95% CI 0.6-2.2%) in the bottom quartile to 73.6% (95% CI 68.4-78.7) in the top. In our multilevel model, female sex and comorbidity score were associated with a higher likelihood of readmission. The hospital random-effects term, encompassing both measured and unmeasured hospital characteristics, contributed minimally to the model for readmission when patient characteristics were held constant at population mean values (pseudo-R²<0.01% for hospital effects). Surgical volume, bed size, hospital ownership, and academic status were not significantly associated with readmission rates when these terms were added to the model.

CONCLUSIONS

After adjusting for patient characteristics, hospital-level effects explained little of the large between-hospital variability in readmission rates. These findings underscore the limitations of using 30-d post-discharge readmissions as a hospital quality metric.

PATIENT SUMMARY

The chance of being readmitted after radical cystectomy varies substantially between hospitals. Little of this variability can be explained by hospital-level characteristics, while far more can be explained by patient characteristics and random variability.

Strategies to Reduce Hospital Readmission Rates in a Non-Medicaid-Expansion State

On October 1, 2012, as part of the Affordable Care Act, the Centers for Medicare and Medicaid Services began to reduce payments to hospitals with excessive rehospitalization rates through the Hospital Readmissions Reduction Program. These financial penalties have intensified hospital leaders' efforts to implement strategies to reduce readmission rates. The purpose of this multiple case study was to explore organizational strategies that leaders use to reduce readmission rates in hospitals located in a non-Medicaid-expansion state. The data collection included semistructured interviews with 15 hospital leaders located in five metropolitan and rural hospitals in southwest Missouri. Consistent with prior research, the use of predictive analytics stratified by patient population was acknowledged as a key strategy to help reduce avoidable rehospitalization. Study findings suggest that leveraging data from the electronic health records to identify at-risk patients provides comprehensive health information to reduce readmissions. Hospital leaders also revealed the need to understand and address the health needs of their local population, including social determinants such as lack of access to transportation as well as food and housing.