Implementation of an AI-Based Clinical Decision Support System Predicting In-Hospital Cardiac Arrest in General Wards: A Multicenter Staggered-Implementation Study in Secondary Hospitals in Korea.

Minjeong Kim¹, Dongjoon Yoo², Eunbi Noh³, Yongwook Jeong⁴, Minsoo Kim³, Kyung-Jae Cho³, Mincheol Kim³, You Dong Sohn⁵, Gyu Chong Cho⁵

¹Division of Pulmonology, Department of Internal Medicine, Shihwa Medical Center, Siheung 15063, Republic of Korea.

²Department of Critical Care Medicine and Emergency Medicine, Inha University Hospital, Incheon 22332, Republic of Korea.

³VUNO Inc., Seoul 06164, Republic of Korea.

⁴Department of Emergency Medicine, Naeun Hospital, Incheon 21565, Republic of Korea.

⁵Department of Emergency Medicine, School of Medicine, Hallym University, Seoul 05355, Republic of Korea.

PubMed PMC DOI PDF

Abstract

Background/Objectives: In-hospital cardiac arrest (IHCA) remains a devastating event associated with high morbidity and mortality among general ward patients. While Rapid Response Systems (RRS) can help identify deteriorating patients, maintaining these systems in secondary hospitals is frequently hindered by severe fiscal and personnel constraints. Consequently, evidence regarding the real-world…

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