Artificial intelligence to improve clinical coding practice in Scandinavia: a crossover randomized controlled trial

Chomutare, Taridzo, Svenning, Therese Olsen, Hernández, Miguel Ángel Tejedor, Ngo, Phuong Dinh, Budrionis, Andrius, Markljung, Kaisa, Hind, Lill Irene, Torsvik, Torbjørn, Mikalsen, Karl Øyvind, Babic, Aleksandar, Dalianis, Hercules

arXiv.org Artificial Intelligence 

International Statistical Classification of Diseases and Related Health Problems codes, tenth revision (ICD-10) [1] play an important role in healthcare. All hospitals in Scandinavia record their activity by summarizing patient encounters into ICD-10 codes. Clinical coding directly affects how health institutions function on a daily basis because they are partially reimbursed based on the codes they report. The same codes are used to measure both volume and quality of care, thereby providing an important foundation of knowledge for decision makers at all levels in the healthcare service. Clinical coding is a highly complex and challenging task that requires a deep understanding of both the medical terminology and intricate clinical documentation. Coders must accurately translate detailed patient records into standardized codes, navigating the inherently complex medical language, which make this task prone to errors and inconsistencies.