F1: Clinical Engineering

PREDICTING RESURGERIES IN INTENSIVE CARE USING DATA MINING

Filipe Portela1, Ricardo Peixoto, Manuel Filipe Santos, José Machado, António Abelha, Fernando Rua2

1University of Minho, Portugal;
2Centro Hospitalar do Porto

The field of critical care medicine is confronted every day with cases of surgical interventions. When Data Mining is properly applied in this field, it is possible through predictive models to identify if a patient, should or should not have surgery again upon the same problem. The goal of this work is to use Data Mining techniques to predict future surgeries in a Intensive Care Unit. By knowing the common characteristics of the re-intervention patients it will be possible to help the physician to predict a future resurgery. For this study various attributes were used related to the patient’s health problems like heart problems or organ failure. For this study it was also considered important aspects such as age and what type of surgery the patient was submitted. Classes were created with the patients’ age and the number of days in admission. Another class was created where the type of surgery that the patient was operated upon was identified. This study comprised values of accuracy, sensitivity and specificity higher than 80%. The used variables, in addition to being provided by Hospital de Santo António in Porto, they are provided from the electronic medical record. As result a set of Data Mining models were induced in order to predict the probabaility of a patient be reinterved to the same problem.

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