Construction and Application of an Intelligent Response System for COVID-19 Voice Consultation in China: A Retrospective Study - Shi, Jinming; Gao, Jinghong; Zhai, Yunkai; Ye, Ming; Lu, Yaoen; He, Xianying; Cui, Fangfang; Ma, Qianqian; Zhao, Jie (Frontiers in Medicine, 2021)
Background: The outbreak of novel coronavirus disease 2019 (COVID-19) has led to tremendous individuals flood into medical institutions for healthcare services. Public gatherings and close contact in clinics and emergency departments may increase the exposure and cross-infection of COVID-19. Objectives: The purpose of this study is to develop and deploy an intelligent response system for COVID-19 voice consultation, to provide suggestions of response measures based on users’ actual information, and screen COVID-19 suspected cases. Methods: Based on the requirements analysis of business, user, and function, the physical architecture, system architecture and core algorithms are designed and implemented. The system operation process is designed according to guidance documents of the National Health Commission and the actual experience of prevention, diagnosis, and treatment of COVID-19. Both of qualitative (system construction) and quantitative (system application) data from the real-world healthcare service of the system was retrospectively collected and analyzed. Results: The system realizes the functions such as remote deployment and operations, fast operation procedure adjustment, and multi-dimensional statistical report capability. The performance of the machine learning model used to develop the system is better than others, with the lowest Character Error Rate (CER) 8.13%. As of September 24, 2020, the system had received 12,264 times incoming calls and provided a total of 11,788 COVID-19 related consultation services for the public. 85.2% of the users are from Henan Province, and followed by Beijing (2.5%). Of all the incoming calls, China Mobile with the largest proportion (66%), while China Unicom and China Telecom are accounted for 23% and 11%. For the time users visited to the system, there is a peak period in the morning (08:00-10:00) and afternoon (14:00-16:00), respectively. Conclusions: The intelligent response system achieved appreciable practical implementation effects. Our findings reveal that the provision of inquiry services through intelligent voice consultation system may play a role in optimizing the allocation of healthcare resources, improving the efficiency of medical services, saving medical expenses, and protecting vulnerable groups.