Application of Text Mining and Natural Language Processing in Electronic Patient Records for text extraction and transformation into structured data
Text mining; Natural Language Processing; Anamnesis; Electronic medical record.
The patient's medical record is the essential document to ensure comprehensive and continuous care to the patient, providing the history of their health. Over the course of technological evolution, the patient's therapeutic records have shifted from paper records to the electronic medical record. However, the anamnesis is usually inserted through free text fields, leaving to the health professionals the way information is entered. In this way, traditional Structured Query Language queries are unable to retrieve this data. In order to overcome this problem, we apply Text Mining and Natural Language Processing aiming to extract understandable and standardized data. In this sense, the objective of this work is to evaluate and define the appropriate techniques for the Text Mining process on clinical data of adult patients of the Januário Cicco Maternity unit, aiming to retrieve clinical terms and structure them in order to relate them to the pathological diagnosis patterns.