Karen E. Joynt

Thirty-Day Readmission Rates for Medicare Beneficiaries by Race and Site of Care

CONTEXT Understanding whether and why there are racial disparities in readmissions has implications for efforts to reduce readmissions. OBJECTIVE To determine whether black patients have higher odds of readmission than white patients and whether these disparities are related to where black patients receive care. DESIGN Using national Medicare data, we examined 30-day readmissions after hospitalization for acute myocardial infarction (MI), congestive heart failure (CHF), and pneumonia. We categorized hospitals in the top decile of proportion of black patients as minority-serving. We determined the odds of readmission for black patients compared with white patients at minority-serving vs non-minority-serving hospitals. SETTING AND PARTICIPANTS Medicare Provider Analysis Review files of more than 3.1 million Medicare fee-for-service recipients who were discharged from US hospitals in 2006-2008. MAIN OUTCOME MEASURE Risk-adjusted odds of 30-day readmission. RESULTS Overall, black patients had higher readmission rates than white patients (24.8% vs 22.6%, odds ratio [OR], 1.13; 95% confidence interval [CI], 1.11-1.14; P < .001); patients from minority-serving hospitals had higher readmission rates than those from non-minority-serving hospitals (25.5% vs 22.0%, OR, 1.23; 95% CI, 1.20-1.27; P < .001). Among patients with acute MI and using white patients from non-minority-serving hospitals as the reference group (readmission rate 20.9%), black patients from minority-serving hospitals had the highest readmission rate (26.4%; OR, 1.35; 95% CI, 1.28-1.42), while white patients from minority-serving hospitals had a 24.6% readmission rate (OR, 1.23; 95% CI, 1.18-1.29) and black patients from non-minority-serving hospitals had a 23.3% readmission rate (OR, 1.20; 95% CI, 1.16-1.23; P < .001 for each); patterns were similar for CHF and pneumonia. The results were unchanged after adjusting for hospital characteristics including markers of caring for poor patients. CONCLUSION Among elderly Medicare recipients, black patients were more likely to be readmitted after hospitalization for 3 common conditions, a gap that was related to both race and to the site where care was received.

Depression and cardiovascular disease: Mechanisms of interaction

This article explores the relationship between depression and cardiovascular disease from a mechanistic standpoint. Depression and cardiovascular disease are two of the most prevalent health problems in the United States and are the two leading causes of disability both in the United States and worldwide. Although depression is a known risk factor for the development of cardiovascular disease, as well as an independent predictor of poor prognosis following a cardiac event, the mechanistic relationship between the two remains unclear. Depression is associated with changes in an individuals health status that may influence the development and course of cardiovascular disease, including noncompliance with medical recommendations, as well as the presence of cardiovascular risk factors such as smoking and hypertension. In addition, depression is associated with physiologic changes, including nervous system activation, cardiac rhythm disturbances, systemic and localized inflammation, and hypercoagulability, that negatively influence the cardiovascular system. Further, stress may be an underlying trigger that leads to the development of both depression and cardiovascular disease. This article reviews seven potential mechanisms for the relationship between depression and cardiovascular disease and presents the available evidence surrounding each mechanism. Finally, future directions for research are discussed.

Variation in Surgical-Readmission Rates and Quality of Hospital Care

BACKGROUND Reducing hospital-readmission rates is a clinical and policy priority, but little is known about variation in rates of readmission after major surgery and whether these rates at a given hospital are related to other markers of the quality of surgical care. METHODS Using national Medicare data, we calculated 30-day readmission rates after hospitalization for coronary-artery bypass grafting, pulmonary lobectomy, endovascular repair of abdominal aortic aneurysm, open repair of abdominal aortic aneurysm, colectomy, and hip replacement. We used bivariate and multivariate techniques to assess the relationships between readmission rates and other measures of surgical quality, including adherence to surgical process measures, procedure volume, and mortality. RESULTS For the six index procedures, there were 479,471 discharges from 3004 hospitals. The median risk-adjusted composite readmission rate at 30 days was 13.1% (interquartile range, 9.9 to 17.1). In a multivariate model adjusting for hospital characteristics, we found that hospitals in the highest quartile for surgical volume had a significantly lower composite readmission rate than hospitals in the lowest quartile (12.7% vs. 16.8%, P<0.001), and hospitals with the lowest surgical mortality rates had a significantly lower readmission rate than hospitals with the highest mortality rates (13.3% vs. 14.2%, P<0.001). High adherence to reported surgical process measures was only marginally associated with reduced readmission rates (highest quartile vs. lowest quartile, 13.1% vs. 13.6%; P=0.02). Patterns were similar when each of the six major surgical procedures was examined individually. CONCLUSIONS Nearly one in seven patients hospitalized for a major surgical procedure is readmitted to the hospital within 30 days after discharge. Hospitals with high surgical volume and low surgical mortality have lower rates of surgical readmission than other hospitals.

Thirty-Day Readmissions — Truth and Consequences

Under the Affordable Care Act, hospitals with “worse than expected” 30-day readmission rates will be penalized by Medicare. But though a focus on readmissions may have good face validity, the policy attention to 30-day readmissions may be misguided.

Characteristics of Hospitals Receiving Penalties Under the Hospital Readmissions Reduction Program

To the Editor: The federal Hospital Readmissions Reduction Program (HRRP) took effect on October 1, 2012, the first day of fiscal year 2013. Under this program, using claims data from July 2008 through June 2011, the Centers for Medicare & Medicaid Services (CMS) determined, for each eligible US hospital, whether their readmission rates were higher than would be predicted by CMS models based on their case mix. Hospitals with higher-than-predicted readmission rates will have their total Medicare reimbursement for fiscal year 2013 cut by up to 1% based on these calculations. The CMS recently made these payment cuts public. Because prior studies have shown that readmissions are related to severity of illness and socioeconomic status, we sought to examine the risk of penalties for US hospitals that care for medically complex or socioeconomically vulnerable patients, namely large teaching hospitals and safetynet hospitals. Methods. We used the publicly available HRRP Supplemental Data File and categorized hospitals as having high penalties (top half of penalized hospitals), low penalties (bottom half), and no penalties. We linked these data to the 2011 American Hospital Association annual survey to identify hospitals that likely care for sicker patients (large hospitals with 400 beds and major teaching hospitals with membership in the Council of Teaching Hospitals) as well as safety-net hospitals (SNHs, those in the highest quartile of the disproportionate share hospital index, a measure used by the CMS to quantify care provided for the poor). We compared the readmission penalties for these hospitals with other types of institutions. Subsequently, we used multinomial logistic regression analyses to calculate the odds of receiving high vs no penalties and low vs no penalties for each hospital type of interest. We considered a 2-tailed P value of less than .05 as significant. Analyses were performed using Stata version 12.1 (StataCorp). This study was approved by the Office of Human Research Administration at the Harvard School of Public Health. Results. Of the 3282 hospitals in our sample, 2189 (66.7%) will receive payment cuts as a result of the HRRP. Forty percent of large hospitals (n=178) vs 28% of small hospitals (n=296) will be highly penalized (TABLE). Conversely, 47% of small hospitals (n=503) will receive no payment cuts compared with 24% of large hospitals (n=108). Similarly, we found that major teaching hospitals are more likely to be highly penalized than nonteaching hospitals (44% [n=118] vs 33% [n=979], respectively) and less likely to not be penalized (19% [n=50] vs 35% [n=1043]). Safetynet hospitals are more likely to be highly penalized than nonSNHs (44% [n=337] vs 30% [n=760], respectively), and only 20% (n=157) will not be penalized. In multivariate analyses, we found that the adjusted odds of being highly penalized are greatest for SNHs (odds ratio, 2.38 [95% CI, 1.912.96]; P .001). Comment. We found that large hospitals, teaching hospitals, and SNHs are more likely to receive payment cuts under the HRRP. It is unclear exactly why these hospitals have higher readmission rates than their smaller, nonteaching, non-SNH counterparts, but prior research suggests that differences between hospitals are likely related to

A Path Forward on Medicare Readmissions

Under Medicares Hospital Readmissions Reduction Program, two thirds of U.S. hospitals will receive penalties of up to 1% of Medicare reimbursements. But the program could exacerbate disparities in care and create disincentives to providing care for the very ill.

Who Has Higher Readmission Rates for Heart Failure, and Why? Implications for Efforts to Improve Care Using Financial Incentives

Background— Reducing readmissions for heart failure is an important goal for policymakers. Current national policies financially penalize hospitals with high readmission rates, which may have unintended consequences if these institutions are resource-poor, either financially or clinically. Methods and Results— We analyzed national claims data for Medicare patients with heart failure discharged from US hospitals in 2006 to 2007. We used multivariable models to examine hospital characteristics, 30-day all-cause readmission rates, and likelihood of performing in the worst quartile of readmission rates nationally. Among 905 764 discharges in our sample, patients discharged from public hospitals (27.9%) had higher readmission rates than nonprofit hospitals (25.7%, P<0.001), as did patients discharged from hospitals in counties with low median income (29.4%) compared with counties with high median income (25.7%, P<0.001). Patients discharged from hospitals without cardiac services (27.2%) had higher readmission rates than those from hospitals with full cardiac services (25.1%, P<0.001); patients discharged from hospitals in the lowest quartile of nurse staffing (28.5%) had higher readmission rates than those from hospitals in the highest quartile (25.4%, P<0.001). Patients discharged from small hospitals (28.4%) had higher readmission rates than those discharged from large hospitals (25.2%, P<0.001). These same characteristics identified hospitals that were likely to perform in the worst quartile nationally. Conclusions— Given that many poor-performing hospitals also have fewer resources, they may suffer disproportionately from financial penalties for high readmission rates. As we seek to improve care for patients with heart failure, we should ensure that penalties for poor performance do not worsen disparities in quality of care.

Quality of Care and Patient Outcomes in Critical Access Rural Hospitals

CONTEXT Critical access hospitals (CAHs) play a crucial role in the US rural safety net. Current policy efforts have focused primarily on helping these small, isolated hospitals remain financially viable to ensure access for individuals living in rural areas in the United States; however, little is known about the quality of care they provide or the outcomes their patients achieve. OBJECTIVES To examine the quality of care and patient outcomes at CAHs and to understand why patterns of care might differ for CAHs vs non-CAHs. DESIGN, SETTING, AND PATIENTS A retrospective analysis in 4738 US hospitals of Medicare fee-for-service beneficiaries with acute myocardial infarction (AMI) (10,703 for CAHs vs 469,695 for non-CAHs), congestive heart failure (CHF) (52,927 for CAHs vs 958,790 for non-CAHs), and pneumonia (86,359 for CAHs vs 773,227 for non-CAHs) who were discharged in 2008-2009. MAIN OUTCOME MEASURES Clinical capabilities, performance on processes of care, and 30-day mortality rates, adjusted for age, sex, race, and medical comorbidities. RESULTS Compared with other hospitals (n = 3470), 1268 CAHs (26.8%) were less likely to have intensive care units (380 [30.0%] vs 2581 [74.4%], P < .001), cardiac catheterization capabilities (6 [0.5%] vs 1654 [47.7%], P < .001), and at least basic electronic health records (80 [6.5%] vs 445 [13.9%], P < .001). The CAHs had lower performance on processes of care than non-CAHs for all 3 conditions examined (concordance with Hospital Quality Alliance process measures for AMI, 91.0% [95% CI, 89.7%-92.3%] vs 97.8% [95% CI, 97.7%-97.9%]; for CHF, 80.6% [95% CI, 79.2%-82.0%] vs 93.5% [95% CI, 93.3%-93.7%]; and for pneumonia, 89.3% [95% CI, 88.6%-90.0%] vs 93.7% [95% CI, 93.6%-93.9%]; P < .001 for each). Patients admitted to CAHs had higher 30-day mortality rates for each condition than those admitted to non-CAHs (for AMI: 23.5% vs 16.2%; adjusted odds ratio [OR], 1.70; 95% confidence interval [CI], 1.61-1.80; P < .001; for CHF: 13.4% vs 10.9%; adjusted OR, 1.28; 95% CI, 1.23-1.32; P < .001; and for pneumonia: 14.1% vs 12.1%; adjusted OR, 1.20; 95% CI, 1.16-1.24; P < .001). CONCLUSION Compared with non-CAHs, CAHs had fewer clinical capabilities, worse measured processes of care, and higher mortality rates for patients with AMI, CHF, or pneumonia.

Association of Public Reporting for Percutaneous Coronary Intervention with Utilization and Outcomes among Medicare beneficiaries with Acute Myocardial Infarction

CONTEXT Public reporting of patient outcomes is an important tool to improve quality of care, but some observers worry that such efforts will lead clinicians to avoid high-risk patients. OBJECTIVE To determine whether public reporting for percutaneous coronary intervention (PCI) is associated with lower rates of PCI for patients with acute myocardial infarction (MI) or with higher mortality rates in this population. DESIGN, SETTING, AND PATIENTS Retrospective observational study conducted using data from fee-for-service Medicare patients (49,660 from reporting states and 48,142 from nonreporting states) admitted with acute MI to US acute care hospitals between 2002 and 2010. Logistic regression was used to compare PCI and mortality rates between reporting states (New York, Massachusetts, and Pennsylvania) and regional nonreporting states (Maine, Vermont, New Hampshire, Connecticut, Rhode Island, Maryland, and Delaware). Changes in PCI rates over time in Massachusetts compared with nonreporting states were also examined. MAIN OUTCOME MEASURES Risk-adjusted PCI and mortality rates. RESULTS In 2010, patients with acute MI were less likely to receive PCI in public reporting states than in nonreporting states (unadjusted rates, 37.7% vs 42.7%, respectively; risk-adjusted odds ratio [OR], 0.82 [95% CI, 0.71-0.93]; P = .003). Differences were greatest among the 6708 patients with ST-segment elevation MI (61.8% vs 68.0%; OR, 0.73 [95% CI, 0.59-0.89]; P = .002) and the 2194 patients with cardiogenic shock or cardiac arrest (41.5% vs 46.7%; OR, 0.79 [95% CI, 0.64-0.98]; P = .03). There were no differences in overall mortality among patients with acute MI in reporting vs nonreporting states. In Massachusetts, odds of PCI for acute MI were comparable with odds in nonreporting states prior to public reporting (40.6% vs 41.8%; OR, 1.00 [95% CI, 0.71-1.41]). However, after implementation of public reporting, odds of undergoing PCI in Massachusetts decreased compared with nonreporting states (41.1% vs 45.6%; OR, 0.81 [95% CI, 0.47-1.38]; P = .03 for difference in differences). Differences were most pronounced for the 6081 patients with cardiogenic shock or cardiac arrest (prereporting: 44.2% vs 36.6%; OR, 1.40 [95% CI, 0.85-2.32]; postreporting: 43.9% vs 44.8%; OR, 0.92 [95% CI, 0.38-2.22]; P = .03 for difference in differences). CONCLUSIONS Among Medicare beneficiaries with acute MI, the use of PCI was lower for patients treated in 3 states with public reporting of PCI outcomes compared with patients treated in 7 regional control states without public reporting. However, there was no difference in overall acute MI mortality between states with and without public reporting.

The association between hospital volume and processes, outcomes, and costs of care for congestive heart failure.

BACKGROUND Congestive heart failure (CHF) is common and costly, and outcomes remain suboptimal despite pharmacologic and technical advances. OBJECTIVE To examine whether hospitals with more experience in caring for patients with CHF provide better, more efficient care. DESIGN Retrospective cohort study. SETTING 4095 hospitals in the United States. PATIENTS Medicare fee-for-service patients with a primary discharge diagnosis of CHF. MEASUREMENTS Hospital Quality Alliance CHF process measures; 30-day, risk-adjusted mortality rates; 30-day, risk-adjusted readmission rates; and costs per discharge. National Medicare claims data from 2006 to 2007 were used to examine the relationship between hospital case volume and quality, outcomes, and costs for patients with CHF. RESULTS Hospitals in the low-volume group had lower performance on the process measures (80.2%) than did medium-volume (87.0%) or high-volume (89.1%) hospitals (P < 0.001). In the low-volume group, being admitted to a hospital with a higher case volume was associated with lower mortality, lower readmission, and higher costs. Similar, though smaller, relationships were found between case volume and both mortality and costs in the medium- and high-volume hospital groups. LIMITATIONS Analysis was limited to Medicare patients 65 years or older. Risk adjustment was performed by using administrative data. CONCLUSION Experience with managing CHF, as measured by an institutions volume, is associated with higher quality of care and better outcomes for patients but a higher cost. Understanding which practices employed by high-volume institutions account for these advantages can help improve quality of care and clinical outcomes for all patients with CHF. PRIMARY FUNDING SOURCE American Heart Association.