Automated clinical coding of medical notes into the SNOMED CT Medical terminology structuring system

Abstract

Automated clinical coding is the computational process of annotating healthcare free-text data by detecting relevant medical concepts and linking them to a structured medical terminology system. One of the most significant of these systems is SNOMED CT, which contains a vast array of specific medical terms, each identified by a unique ID. This work focuses on the automatic clinical coding of medical notes within the SNOMED CT system. The study presents a comprehensive review of state-of-the-art methods in this field, followed by a detailed examination of two specific approaches, each tested and their results discussed. The first method employs a classical dictionary-based approach, while the second utilizes a deep learning BERT-based model. Additionally, the work introduces a novel contribution to one of these methods and demonstrates a practical application where automatic clinical coding facilitates the extraction of specific numerical values from medical discharge summaries.