Clinical relevance of pharmacist intervention: Development of a named entity recognition model on unstructured comments

Abstract

We developed a clinical named entity recognition model to predict clinical relevance of pharmacist interventions (PIs) by identifying and labelling expressions from unstructured comments of PIs. Three labels, drug, kidney and dosage, had a great inter-annotator agreement (>60%) and could be used as reference labelization. These labels also showed a high precision (>70%) and a variable recall (50-90 %). © 2021 European Federation for Medical Informatics (EFMI) and IOS Press.