Understanding and predicting hospital readmission has been of interest for more than three decades. To strategically place readmission reduction resources where most beneficial, organizations use readmission risk-stratification tools. However, common tools used to assess 30-day risk do not incorporate health disparity and it is unknown how modifying currently validated tools affects their predictive value. The aims of this retrospective study were to describe the population of people who are admitted and re-admitted for hospital care in a rural population and examine the effectiveness of a common risk satisfaction tool to predict 30-day readmission in a rural population experiencing health disparities. This retrospective cohort study examined data from de-identified Electronic Health Record and included adult patients admitted to one general medicine service. The factors identified in this study that influence readmission are also identified in the literature and include number of co-morbid conditions and insurance status.
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