Artificial Intelligence to Improve Clinical Coding Practice in Scandinavia: Crossover Randomized Controlled Trial

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Authors

Taridzo Chomutare · Hansen Protection (Norway)

Therese Olsen Svenning · Norwegian Directorate of Health

Miguel Ángel Tejedor Hernández · Norwegian Directorate of Health

Phuong Dinh Ngo · Norwegian Directorate of Health

Andrius Budrionis · Norwegian Directorate of Health

Kaisa Markljung · Norwegian Directorate of Health

Lill Irene Hind

Abstract

This study demonstrates the potential of AI to transform common tasks in clinical workflows, with ostensible positive impacts on work efficiencies for clinical coding tasks with more demanding longer text sequences. Further studies within hospital workflows are required before these presumed impacts can be more clearly understood.

Topics & Keywords

Medical Coding and Health Information Biomedical Text Mining and Ontologies Electronic Health Records Systems

UN Sustainable Development Goals

Partnerships for the goals

Publication Details

Published in: Journal of Medical Internet Research

Volume 27, pp. e71904-e71904

DOI: 10.2196/71904

Field-Weighted Citation Impact: 17.65