Morales Hugo M P, Guedes Murilo, Silva Jennifer S, Massuda Adriano
Department of Research, Instituto Laura Fressatto, Curitiba, Brazil.
School of Medicine, Pontifícia Universidade Católica Do Paraná, Curitiba, Brazil.
Front Digit Health. 2021 Jun 17;3:648585. doi: 10.3389/fdgth.2021.648585. eCollection 2021.
The novel coronavirus disease (COVID-19) forced rapid adaptations in the way healthcare is delivered and coordinated by health systems. Brazil has a universal public health system (Sistema Unico de Saúde-SUS), being the main source of care for 75% of the population. Therefore, a saturation of the system was foreseen with the continuous increase of cases. The use of Artificial Intelligence (AI) to empower telehealth could help to tackle this by increasing a coordinated patient access to the health system. In the present study we describe a descriptive case report analyzing the use of Laura Digital Emergency Room-an AI-powered telehealth platform-in three different cities. It was computed around 130,000 interactions made by the chatbot and 24,162 patients completed the digital triage. Almost half (44.8%) of the patients were classified as having mild symptoms, 33.6% were classified as moderate and only 14.2% were classified as severe. The implementation of an AI-powered telehealth to increase accessibility while maintaining safety and leveraging value amid the unprecedent impact of the COVID-19 pandemic was feasible in Brazil and may reduce healthcare overload. New efforts to yield sustainability of affordable and scalable solutions are needed to truly leverage value in health care systems, particularly in the context of middle-low-income countries.
新型冠状病毒病（COVID-19）迫使卫生系统在医疗服务的提供和协调方式上迅速做出调整。巴西拥有全民公共卫生系统（单一卫生系统-SUS），是75%人口的主要医疗服务来源。因此，随着病例的持续增加，预计该系统会不堪重负。利用人工智能（AI）赋能远程医疗有助于通过增加患者对卫生系统的协调访问来解决这一问题。在本研究中，我们描述了一份描述性病例报告，分析了人工智能驱动的远程医疗平台Laura数字急诊室在三个不同城市的使用情况。聊天机器人进行了约130,000次交互，24,162名患者完成了数字分诊。几乎一半（44.8%）的患者被归类为症状轻微，33.6%被归类为中度，只有14.2%被归类为重度。在巴西，实施人工智能驱动的远程医疗以增加可及性，同时在COVID-19大流行的前所未有的影响下保持安全性并提升价值是可行的，并且可能减少医疗负担过重的情况。需要做出新的努力，以实现负担得起且可扩展的解决方案的可持续性，从而真正在医疗系统中提升价值，特别是在中低收入国家的背景下。
