Background: Hospital readmissions are common and expensive. Numerous global efforts have been devoted to predicting readmissions. However, for many reasons including the variations in the studied populations and inconsistent definitions of readmissions, the outcomes of some studies can hardly be generalized to other studies inside or outside the same country or region. Objective: The objective was to identify highly generalizable risk factors for unplanned 30-day all-cause hospital readmissions to guide the selection of baseline predictor variables in different readmission studies. Methods: In July 2017, PubMed was searched to identify articles pertaining to the risk factors for unplanned 30-day all-cause hospital readmissions. To identify potentially eligible risk factors, characteristics of the selected studies were manually extracted. The generalizability of the risk factors was assessed with predefined criteria. Results: 13 articles were eligible for the review. A total of 42 risk factors were identified and 34 of them were found to be highly generalizable. Conclusions: The 34 risk factors are not specific to any populations or places, and the corresponding predictor variables can serve as baseline variables in readmission prediction studies. No major difference has been observed between the risk factors identified inside and outside the United States except that US studies appeared to prefer composite comorbidity measures. All the reviewed studies have used traditional statistical regression-based methods to identify risk factors and more applications of data mining techniques are expected in this field.
CITATION STYLE
Zhao, P., & Yoo, I. (2017). A Systematic Review of Highly Generalizable Risk Factors for Unplanned 30-Day All-Cause Hospital Readmissions. Journal of Health & Medical Informatics, 08(04). https://doi.org/10.4172/2157-7420.1000283
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