Research Area: Machine Learning
Many studies have used Taiwans National Health Insurance Research database (NHIRD) to conduct psychiatric research. However, the accuracy of the diagnostic codes for psychiatric disorders in NHIRD is not validated, and the symptom profiles are not available either. This study aimed to evaluate the accuracy of diagnostic codes and use text mining to extract symptom profile and functional impairment from electronic health records (EHRs) to overcome the above research limitations.A total of 500 discharge notes were randomly selected from a medical centers database. Three annotators reviewed the notes to establish gold standards. The accuracy of diagnostic codes for major psychiatric illness was evaluated. Text mining approaches were applied to extract depressive symptoms and function profiles and to identify patients with major depressive disorder.
Keywords:
National Health Insurance Research database
Psychiatric research
Depressive symptoms
Depressive disorder
Electronic health records
Author(s) Name: Chi-Shin Wu, Chian-Jue Kuo, Chu-Hsien Su
Journal name: Using text mining to extract depressive symptoms and to validate the diagnosis of major depressive disorder from electronic health records
Conferrence name:
Publisher name: Elsevier
DOI: 10.1016/j.jad.2019.09.044
Volume Information: Volume 260
