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

Department of Health Policy and Management, Harvard School of Public Health, Division of Cardiovascular Medicine, Brigham and Women's Hospital, Boston, Massachusetts 02115, USA.
JAMA The Journal of the American Medical Association (Impact Factor: 35.29). 02/2011; 305(7):675-81. DOI: 10.1001/jama.2011.123
Source: PubMed


Understanding whether and why there are racial disparities in readmissions has implications for efforts to reduce readmissions.
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.
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.
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.
Risk-adjusted odds of 30-day readmission.
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.
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.

Download full-text


Available from: Karen E Joynt, Oct 01, 2015
75 Reads
  • Source
    • "Several factors were noted to be associated with increased readmission rates for patients with CHF. These included being discharged from a publically owned hospital in a county with low median income, a hospital lacking cardiac services, small hospitals and units with lower nursing staffing (Joynt, et al, 2011 "
    [Show abstract] [Hide abstract]
    ABSTRACT: Abstract Hospital readmissions affect over 80 percent of all Medicare enrollees. Hospitals have a responsibility to their Medicare patients to keep them safe after discharge in their homes and communities. With changes in the Medicare reimbursement model, hospitals are examining efficient methods of decreasing avoidable re-admissions. A Faith Community Nurse Transitional Care Program may be just the answer to improve patient’s discharge experience, ensure post-discharge support and reduce re-hospitalization. Methods In preparations for testing a Faith Community Nurse Transitional Care Program Model, a systematic integrative review was needed. Using PRISMA, a search was done, inclusion criteria identified, and articles retrieved. Sixty-two articles were collected, compared, and combined using a descriptive matrix template. Results Chronic diseases such as heart failure, COPD, diabetes mellitus, cancer, stroke and/or psychosis, depression, and lower mental health status have the highest risks. Patient variables include Medicare and Medicaid payer status, markers of frailty and elderly with complex medical, social and financial needs. Lack of caregiver or social support, poor health literacy, inability to navigate the health care system, are non-clinical needs leading to readmissions. Methods or interventions leading to decreased readmissions are early discharge planning, case management, self-management skills enhanced, medication education, and standardized tools.
  • Source
    • "Westert et al. (2002) conducted an international study, including three U.S. states and three countries, to find patterns in the profiles of readmitted patients. The findings are divided into demographic and social factors, clinical factors (Billings et al. 2006, Southern et al. 2004), and hospital operations factors (Benbassat and Taragin 2000, Davidson et al. 2007, Joynt et al. 2011, Scuteri et al. 2011, VanSuch et al. 2006, Westert et al. 2002). A study of 26 readmission risk-prediction models concluded that after reviewing 7,843 citations, none of the models analyzed could suitably predict future hospital readmissions (Kansagara et al. 2011). "
    [Show abstract] [Hide abstract]
    ABSTRACT: When we encounter an unexpected critical health problem, a hospital's emergency department (ED) becomes our vital medical resource. Improving an ED's timeliness of care, quality of care, and operational efficiency while reducing avoidable readmissions, is fraught with difficulties, which arise from complexity and uncertainty. In this paper, we describe an ED decision support system that couples machine learning, simulation, and optimization to address these improvement goals. The system allows healthcare administrators to globally optimize workflow, taking into account the uncertainties of incoming patient injuries and diseases and their associated care, thereby significantly reducing patient length of stay. This is achieved without changing physical layout, focusing instead on process consolidation, operations tracking, and staffing. First implemented at Grady Memorial Hospital in Atlanta, Georgia, the system helped reduce length of stay at Grady by roughly 33 percent. By repurposing existing resources, the hospital established a clinical decision unit that resulted in a 28 percent reduction in ED readmissions. Insights gained from the implementation also led to an investment in a walk-in center that eliminated more than 32 percent of the nonurgent-care cases from the ED. As a result of these improvements, the hospital enhanced its financial standing and achieved its target goal of an average ED length of stay of close to seven hours. ED and trauma efficiencies improved throughput by over 16 percent and reduced the number of patients who left without being seen by more than 30 percent. The annual revenue realized plus savings generated are approximately $190 million, a large amount relative to the hospital's $1.5 billion annual economic impact. The underlying model, which we generalized, has been tested and implemented successfully at 10 other EDs and in other hospital units. The system offers significant advantages in that it permits a comprehensive analysis of the entire patient flow from registration to discharge, enables a decision maker to understand the complexities and interdependencies of individual steps in the process sequence, and ultimately allows the users to perform system optimization.
    Interfaces 02/2015; 45(1):58-82. DOI:10.1287/inte.2014.0788 · 0.42 Impact Factor
  • Source
    • "Readmission disparities among different races have been welldocumented among multiethnic populations (Joynt et al., 2011). Among elderly Medicare (US) recipients, African Americans have higher readmission rates compared to Caucasians (Joynt et al., 2011). "
    [Show abstract] [Hide abstract]
    ABSTRACT: Objective: To investigate whether number of doses per day and number of medications are significantly associated with the number of readmissions and to study the association of readmission frequency with other medical and socio-demographic variables. Methods: Retrospective cross-sectional study involving 432 patients who were readmitted within 15. days of previous hospital discharge between January 1, 2013 and March 31, 2013. Relevant medical records were collected from the national electronic databases of every public tertiary hospital in Singapore. Significant variables (. p<. 0.05) were identified using forward selection and modeled using generalized linear mixed models. Results: A total of 649 unplanned readmissions were reviewed. At a multivariable level, number of readmission was significantly associated with the number of medications (. p=. 0.002) and number of doses per day (. p=. 0.003) after adjusting for race, liver disease, schizophrenia and non-compliance. Conclusion: Complex medication regimen (i.e. multiple medications and multiple doses per day) is a statistically significant predictor of number of readmissions. Simplifying therapeutic regimens with alternatives such as longer-acting or fixed-dose combination drugs may facilitate better patient adherence and reduce costly readmissions.
    12/2014; 1:43-47. DOI:10.1016/j.pmedr.2014.10.001
Show more