Lim Hooi Min, Teo Chin Hai, Ng Chirk Jenn, Chiew Thiam Kian, Ng Wei Leik, Abdullah Adina, Abdul Hadi Haireen, Liew Chee Sun, Chan Chee Seng
Department of Primary Care Medicine, University of Malaya Medical Centre, Kuala Lumpur, Malaysia.
eHealth Unit, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia.
JMIR Med Inform. 2021 Feb 26;9(2):e23427. doi: 10.2196/23427.
During the COVID-19 pandemic, there was an urgent need to develop an automated COVID-19 symptom monitoring system to reduce the burden on the health care system and to provide better self-monitoring at home.
This paper aimed to describe the development process of the COVID-19 Symptom Monitoring System (CoSMoS), which consists of a self-monitoring, algorithm-based Telegram bot and a teleconsultation system. We describe all the essential steps from the clinical perspective and our technical approach in designing, developing, and integrating the system into clinical practice during the COVID-19 pandemic as well as lessons learned from this development process.
CoSMoS was developed in three phases: (1) requirement formation to identify clinical problems and to draft the clinical algorithm, (2) development testing iteration using the agile software development method, and (3) integration into clinical practice to design an effective clinical workflow using repeated simulations and role-playing.
We completed the development of CoSMoS in 19 days. In Phase 1 (ie, requirement formation), we identified three main functions: a daily automated reminder system for patients to self-check their symptoms, a safe patient risk assessment to guide patients in clinical decision making, and an active telemonitoring system with real-time phone consultations. The system architecture of CoSMoS involved five components: Telegram instant messaging, a clinician dashboard, system administration (ie, back end), a database, and development and operations infrastructure. The integration of CoSMoS into clinical practice involved the consideration of COVID-19 infectivity and patient safety.
This study demonstrated that developing a COVID-19 symptom monitoring system within a short time during a pandemic is feasible using the agile development method. Time factors and communication between the technical and clinical teams were the main challenges in the development process. The development process and lessons learned from this study can guide the future development of digital monitoring systems during the next pandemic, especially in developing countries.
在新冠疫情期间，迫切需要开发一个自动化的新冠症状监测系统，以减轻医疗系统的负担，并在家中提供更好的自我监测。
本文旨在描述新冠症状监测系统（CoSMoS）的开发过程，该系统由一个基于算法的自我监测Telegram机器人和一个远程会诊系统组成。我们从临床角度描述了在新冠疫情期间设计、开发并将该系统整合到临床实践中的所有基本步骤，以及从这一开发过程中吸取的经验教训。
CoSMoS分三个阶段开发：（1）需求形成，以识别临床问题并起草临床算法；（2）使用敏捷软件开发方法进行开发测试迭代；（3）整合到临床实践中，通过反复模拟和角色扮演设计有效的临床工作流程。
我们在19天内完成了CoSMoS的开发。在第一阶段（即需求形成），我们确定了三个主要功能：患者每日自动症状自查提醒系统、指导患者进行临床决策的安全患者风险评估，以及实时电话会诊的主动远程监测系统。CoSMoS的系统架构包括五个组件：Telegram即时通讯、临床医生仪表板、系统管理（即后端）、数据库以及开发和运营基础设施。将CoSMoS整合到临床实践中需要考虑新冠病毒的传染性和患者安全。
本研究表明，在疫情期间短时间内开发新冠症状监测系统，采用敏捷开发方法是可行的。时间因素以及技术团队与临床团队之间的沟通是开发过程中的主要挑战。本研究的开发过程和经验教训可为下一次疫情期间数字监测系统的未来发展提供指导，尤其是在发展中国家。
