KECERDASAN BUATAN SEBAGAI PENDEKATAN YANG MENJANJIKAN UNTUK PENINGKATAN KUALITAS KODING KLINIS: STUDI LITERATUR

Abstract

Artificial Intelligence (AI) has become an interesting topic in the clinical coding system development. AI is the idea of how machines are able to mimic human intelligence to perform tasks. There are many AI approaches that can be applied in clinical coding systems. Our purpose is to syntesize the AI implementations for clinical coding systems development. This narrative literature review study was conducted based on Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) frameworks to ensure the quality of articles selection process. We searched the articles from Google Scholar, PubMed, Sciencedirect, IEEE, SagePub and ProQuest in 2016-2021. We used the instrument of Mixed Method Appraisal Tools (MMAT) 2018 version to ensure the articles quality. We obtained 19,734 articles from databases and met 29 articles that fulfilled our criteria and have a good quality based on the MMAT tool. There are various methods of the AI developments and have versatile purpose for health care services, including for clinical coding. The implementation of the AI in clinical coding systems may improve effectiveness and efficiency of disease coding process. AI can scale up the clinical coding quality and accuracy but needs further investigations