Background Measures of socioeconomic disadvantage may enable improved targeting of programs to prevent rehospitalizations, but obtaining such information directly from patients can be difficult. Measures of US neighborhood socioeconomic disadvantage are more readily available, although rarely employed clinically. Objective To evaluate the association between neighborhood socioeconomic disadvantage at the census block-group level, as measured by Singh’s validated Area Deprivation Index (ADI), and 30-day rehospitalization. Design Retrospective cohort study Setting United States Patients Random 5% national sample of fee-for-service Medicare patients discharged with congestive heart failure, pneumonia or myocardial infarction, 2004–2009 (N = 255,744) Measurements 30-day rehospitalizations. Medicare data were linked to 2000 Census data to construct an ADI for each patient’s census block-group, which were then sorted into percentiles by increasing ADI. Relationships between neighborhood ADI grouping and rehospitalization were evaluated using multivariate logistic regression models, controlling for patient sociodemographics, comorbidities/severity, and index hospital characteristics. Results The 30-day rehospitalization rate did not vary significantly across the least disadvantaged 85% of neighborhoods, which had an average rehospitalization rate=21%. However, within the most disadvantaged 15% of neighborhoods, rehospitalization rates rose from 22% to 27% with worsening ADI. This relationship persisted after full adjustment, with the most disadvantaged neighborhoods having a rehospitalization risk (adjusted risk ratio = 1.09, confidence interval 1.05–1.12) similar to that of chronic pulmonary disease (1.06, 1.04–1.08) and greater than that of diabetes (0.95, 0.94–0.97). Limitations No direct markers of care quality, access Conclusions Residence within a disadvantaged US neighborhood is a rehospitalization predictor of magnitude similar to chronic pulmonary disease. Measures of neighborhood disadvantage, like the ADI, could potentially be used to inform policy and post-hospital care. Primary Funding Source National Institute on Aging

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BACKGROUND-It is unknown whether survival after in-hospital cardiopulmonary resuscitation (CPR) is improving and which patient and hospital characteristics predict survival.

Objective To determine the extent to which hospitals vary in the use of intensive care, and the proportion of variation attributable to differences in hospital practice that is independent of known patient and hospital factors. Data source Hospital discharge data in the State Inpatient Database for Maryland and Washington states in 2006. Study design Cross sectional analysis of 90 short-term acute, care hospitals with critical care capabilities. Data collection/methods We quantified the proportion of variation in intensive care use attributable to hospitals using intraclass correlation coefficients derived from mixed effects logistic regression models after successive adjustment for known patient and hospital factors. Principal findings The proportion of hospitalized patients admitted to an ICU across hospitals ranged from 3% to 55% (median 12%; IQR:9, 17%). After adjustment for patient factors, 19.7% (95%CI: 15.1, 24.4) of total variation in ICU use across hospitals was attributable to hospitals. When observed hospital characteristics were added, the proportion of total variation in intensive care use attributable to unmeasured hospital factors decreased by 26% to 14.6% (95% CI:11, 18.3%). Conclusions Wide variability exists in the use of intensive care across hospitals, not attributable to known patient or hospital factors, and may be a target to improve efficiency and quality of critical care.

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