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Area Deprivation Index Predicts Readmission Risk at an Urban Teaching Hospital
Jianhui Hu1, Amy J H Kind2,3, David Nerenz1
11 Henry Ford Health System, Detroit, MI.
Abstract:
A growing body of evidence has shown that neighborhood characteristics have significant effects on quality metrics that evaluate health plans or health care providers. Using a data set of an urban teaching hospital patient discharges, this study aimed to determine whether a significant effect of neighborhood characteristics, measured by the Area Deprivation Index, could be observed on patients' readmission risk, independent of patient-level clinical and demographic factors. This study found that patients residing in more disadvantaged neighborhoods had significantly higher 30-day readmission risks compared to those living in less disadvantaged neighborhoods, even after accounting for individual-level factors. Those who lived in the most extremely socioeconomically challenged neighborhoods were 70% more likely to be readmitted than their counterparts who lived in less disadvantaged neighborhoods. These findings suggest that neighborhood-level factors should be considered along with individual-level factors in future work on adjustment of quality metrics for social risk factors.
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However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.

