A Literature Review on Predicting Unplanned Patient Readmissions

Part of the Healthcare Delivery in the Information Age book series (Healthcare Delivery Inform. Age)


Research on predicting unplanned readmissions in hospitals is becoming more popular with a larger amount of hospital data becoming available. To gain an in-depth observation of recent insights in the field, a literature review analysing contributions between the years of 2005 and 2017 is conducted. The aggregated results show the most important risk factors included in prediction models so far, evaluation metrics of both all-cause and diagnosis-specific prediction models as well as the most prominent classification methods used in this context. Furthermore, the development of research on predicting unplanned patient readmissions over time is shown, and current gaps are identified.


Risk prediction Predictive analytics Healthcare Data mining Readmissions 


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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.University of Erlangen-Nuremberg, Institute of Information SystemsNurembergGermany

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