Optimizing Hospital Patient Flow by Predicting Aftercare Requests from Fuzzy Time Series

Predictive modelling can be a huge benefit when it comes to optimizing patient flows in a hospital. Hospital beds are considered critical resources, thus the need for optimizing patient flow is evident. This paper focuses on predicting the out-flow of hospital patients to external aftercare facilities, to mitigate the waiting times that currently dominate this flow and have a negative influence on the patient recovery process. In order to achieve this, we analyze hospital patient time series data in the form of aftercare requests. Such predictions allow hospital and aftercare facilities to be aligned such that, as soon as a patient is medically ready for discharge, the aftercare facility can immediately allocate the patient, avoiding for such patient to stay longer in the hospital occupying a bed while waiting for a place in the aftercare facility.