Text Data Mining of In-patient Nursing Records Within Electronic Medical Records Using KeyGraph

This research used a text data mining technique to extract useful information from nursing records within Electronic Medical Records. Although nursing records provide a complete account of a patient’s information, they are not being fully utilized. Such relevant information as laboratory results and remarks made by doctors and nurses is not always considered. Knowledge concerning the condition and treatment of patients has been determined in a twofold manner: a text data mining technique identified the relations between feature vocabularies seen in past in-patient records accumulated on the University of Miyazaki Hospital’s Electronic Medical Record, and extractions were made. The qualitative analysis result of in-patient nursing records used a text data mining technique to achieve the initial goal: a visual record of such information. The analysis discovered vocabularies relating to proper treatment methods and concisely summarized their extracts from in-patient nursing records. Important vocabularies that characterize each nursing record were also revealed. The results of this research will contribute to nursing work evaluation and education.