Racial/Ethnic Disparities in Potentially Preventable Readmissions: The Case of Diabetes

Center for Delivery, Organization and Markets, Agency for Healthcare Research and Quality, 540 Gaither Rd, Rockville, MD 20850, USA.
American Journal of Public Health (Impact Factor: 4.55). 10/2005; 95(9):1561-7. DOI: 10.2105/AJPH.2004.044222
Source: PubMed


Considerable differences in prevalence of diabetes and management of the disease exist among racial/ethnic groups. We examined the relationship between race/ethnicity and hospital readmissions for diabetes-related conditions.
Nonmaternal adult patients with Medicare, Medicaid, or private insurance coverage hospitalized for diabetes-related conditions in 5 states were identified from the 1999 State Inpatient Databases of the Healthcare Cost and Utilization Project. Racial/ethnic differences in the likelihood of readmission were estimated by logistic regression with adjustment for patient demographic, clinical, and socioeconomic characteristics and hospital attributes.
The risk-adjusted likelihood of 180-day readmission was significantly lower for non-Hispanic Whites than for Hispanics across all 3 payers or for non-Hispanic Blacks among Medicare enrollees. Within each payer, Hispanics from low-income communities had the highest risk of readmission. Among Medicare beneficiaries, Blacks and Hispanics had higher percentages of readmission for acute complications and microvascular disease, while Whites had higher percentages of readmission for macrovascular conditions.
Racial/ethnic disparities are more evident in 180-day than in 30-day readmission rates, and greatest among the Medicare population. Readmission diagnoses vary by race/ethnicity, with Blacks and Hispanics at higher risk for those complications more likely preventable with effective postdischarge care.

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    • "This trend has been seen in many other studies [7,32], likely reflecting the fact that a large percentage of the hospital resources in our country are utilized by a small percentage of patients [10]. In previous studies, demographic factors such as marital status, age and gender have been shown to be predictive of 30-day readmission [21,33,34]. Single marital status was a predictor in the combined model, which may suggest a lack of power to detect a significant finding in the smaller cohorts. "
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    ABSTRACT: Readmissions after hospital discharge are a common occurrence and are costly for both hospitals and patients. Previous attempts to create universal risk prediction models for readmission have not met with success. In this study we leveraged a comprehensive electronic health record to create readmission-risk models that were institution- and patient- specific in an attempt to improve our ability to predict readmission. This is a retrospective cohort study performed at a large midwestern tertiary care medical center. All patients with a primary discharge diagnosis of congestive heart failure, acute myocardial infarction or pneumonia over a two-year time period were included in the analysis. The main outcome was 30-day readmission. Demographic, comorbidity, laboratory, and medication data were collected on all patients from a comprehensive information warehouse. Using multivariable analysis with stepwise removal we created three risk disease-specific risk prediction models and a combined model. These models were then validated on separate cohorts. 3572 patients were included in the derivation cohort. Overall there was a 16.2% readmission rate. The acute myocardial infarction and pneumonia readmission-risk models performed well on a random sample validation cohort (AUC range 0.73 to 0.76) but less well on a historical validation cohort (AUC 0.66 for both). The congestive heart failure model performed poorly on both validation cohorts (AUC 0.63 and 0.64). The readmission-risk models for acute myocardial infarction and pneumonia validated well on a contemporary cohort, but not as well on a historical cohort, suggesting that models such as these need to be continuously trained and adjusted to respond to local trends. The poor performance of the congestive heart failure model may suggest that for chronic disease conditions social and behavioral variables are of greater importance and improved documentation of these variables within the electronic health record should be encouraged.
    BMC Medical Informatics and Decision Making 08/2014; 14(1):65. DOI:10.1186/1472-6947-14-65 · 1.83 Impact Factor
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    • "Rehospitalizations occur disproportionately among socioeconomically disadvantaged groups, including AAs, those living in lower income zip codes, and those without private insurance (5,7). Furthermore, disadvantaged patients are more likely to be admitted for acute complications of their diabetes, as opposed to chronic complications (5). "
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    ABSTRACT: OBJECTIVE To explore the relationship between inpatient diabetes education (IDE) and hospital readmissions in patients with poorly controlled diabetes.RESEARCH DESIGN AND METHODS Patients with a discharge diagnosis of diabetes (ICD-9 code 250.x) and HbA1c >9% who were hospitalized between 2008 and 2010 were retrospectively identified. All-cause first readmissions were determined within 30 days and 180 days after discharge. IDE was conducted by a certified diabetes educator or trainee. Relationships between IDE and hospital readmission were analyzed with stepwise backward logistic regression models.RESULTSIn all, 2,265 patients were included in the 30-day analysis and 2,069 patients were included in the 180-day analysis. Patients who received IDE had a lower frequency of readmission within 30 days than did those who did not (11 vs. 16%; P = 0.0001). This relationship persisted after adjustment for sociodemographic and illness-related factors (odds ratio 0.66 [95% CI 0.51-0.85]; P = 0.001). Medicaid insurance and longer stay were also independent predictors in this model. IDE was also associated with reduced readmissions within 180 days, although the relationship was attenuated. In the final 180-day model, no IDE, African American race, Medicaid or Medicare insurance, longer stay, and lower HbA1c were independently associated with increased hospital readmission. Further analysis determined that higher HbA1c was associated with lower frequency of readmission only among patients who received a diabetes education consult.CONCLUSIONS Formal IDE was independently associated with a lower frequency of all-cause hospital readmission within 30 days; this relationship was attenuated by 180 days. Prospective studies are needed to confirm this association.
    Diabetes care 07/2013; 36(10). DOI:10.2337/dc13-0108 · 8.42 Impact Factor
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    • "Other studies have examined readmissions in minority patients and have noted no differences in readmission between Blacks, Hispanics and Whites (Deswal, Petersen, Souchek, Ashton, & Wray, 2004; Yancy et al., 2008). Our study, however, is consistent with previous research, which found that race was an important determinant of readmission in chronic conditions (Curtis et al., 2008; Friedman & Basu, 2004; Jiang et al., 2005; Philbin & DiSalvo, 1998; Rathore et al., 2003). "
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    ABSTRACT: Beginning in 2009, the Centers for Medicare & Medicaid Services started publicly reporting hospital readmission rates as part of the Hospital Compare website. Hospitals will begin having payments reduced if their readmission rates are higher than expected starting in fiscal year 2013. Value-based purchasing initiatives including public reporting and pay-for-performance incentives have the potential to increase quality of care. There is concern, however, that hospitals providing service to minority communities may be disproportionately penalized as a result of these policies due to higher rates of readmissions among racial and ethnic minority groups. Using 2008 Medicare data, we assess the risk for readmission for minorities and discuss implications for minority-serving institutions.
    Policy Politics &amp Nursing Practice 11/2010; 11(4):309-16. DOI:10.1177/1527154411398490
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