Sepsis-Associated 30-Day Risk-Standardized Readmissions: Analysis of a Nationwide Medicare Sample*

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To determine national readmission rates among sepsis survivors, variations in rates between hospitals, and determine whether measures of quality correlate with performance on sepsis readmissions.


Cross-sectional study of sepsis readmissions between 2008 and 2011 in the Medicare fee-for-service database.


Acute care, Medicare participating hospitals from 2008 to 2011.


Septic patients as identified by International Classification of Diseases, Ninth Revision codes using the Angus method.



Measurements and Main Results:

We generated hospital-level, risk-standardized, 30-day readmission rates among survivors of sepsis and compared rates across region, ownership, teaching status, sepsis volume, hospital size, and proportion of underserved patients. We examined the relationship between risk-standardized readmission rates and hospital-level composite measures of quality and mortality. From 633,407 hospitalizations among 3,315 hospitals from 2008 to 2011, median risk-standardized readmission rates was 28.7% (interquartile range, 26.1–31.9). There were differences in risk-standardized readmission rates by region (Northeast, 30.4%; South, 29.6%; Midwest, 28.8%; and West, 27.7%; p < 0.001), teaching versus nonteaching status (31.1% vs 29.0%; p < 0.001), and hospitals serving the highest proportion of underserved patients (30.6% vs 28.7%; p < 0.001). The best performing hospitals on a composite quality measure had highest risk-standardized readmission rates compared with the lowest (32.0% vs 27.5%; p < 0.001). Risk-standardized readmission rates was lower in the highest mortality hospitals compared with those in the lowest (28.7% vs 30.7%; p < 0.001).


One third of sepsis survivors were readmitted and wide variation exists between hospitals. Several demographic and structural factors are associated with this variation. Measures of higher quality in-hospital care were correlated with higher readmission rates. Several potential explanations are possible including poor risk standardization, more research is needed.

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