Development of a Nursing-care Freestyle Text Classification System

Abstract

The nursing-care quality improvement is very important in the medical field. Currently, nursing-care freestyle texts are collected from many hospitals in Japan through the Internet by using Web applications. Some nursing-care experts evaluate the collected data for improving nursing-care quality, and then return a recommendation for improvement to each nurse. Since this Web based nursing-care quality evaluation system is a novel system in Japan, participation of many hospitals is desired. However, it is very difficult to increase the number of hospitals because the only few experts evaluate the collected nursing-care texts. In this paper, for evaluating many nurses, we develop a support vector machine (SVM) based classification system. And we propose a new attribute definition by using the expert's knowledge such as the length of a text and words or expressions which are focused by experts. First, for generating numerical training data, we extract attribute values from the nursing-care freestyle texts. And then, we classify the nursing-care numerical data using the SVM. Computer simulation results show the effectiveness of our proposed attribute definition. From the result of this paper, since many nurses can be evaluated by our proposed system, we can expect the quality improvement of the nursing-care in Japan.