ORLANDO – Reviewing patient charts for asthma risk factors using natural language processing can be done 8 times faster than reviewing the charts by hand, and with high levels of accuracy, researchers reported here.
Natural language processing (NLP) is a kind of artificial intelligence in which computers are “trained” through a reiterative process to understand human language.
Researchers at Mayo Clinic previously have shown that a program created in-house can successfully and quickly determine patients’ asthma status. In this study, they turned to assessment of asthma risk factors, Chung-Il Wi, MD, assistant professor of pediatrics at Mayo said in a presentation at the joint congress of the American Academy of Allergy, Asthma and Immunology and the World Asthma Organization.
They used a convenience sample of 177 patient charts to train the NLP system. The system extracted – from key terms and sentences in the electronic health record (EHR) – data such as breastfeeding history and history of atopic conditions such as allergic rhinitis, eczema, and food allergy. From parent charts, the system extracted terms related to family history of asthma and other atopic conditions. The performance of the NLP algorithm was assessed by comparison with results of a manual chart review in a test cohort of 220 patient charts.