METHODS: We searched 3 major databases, i.e., PubMed, Embase and Lippincott Williams & Wilkins Journals@Ovid, for studies published up until 1May 2013 without language restrictions. All study designs were included in this review. The studies were identified and retrieved by two independent authors.
RESULTS: Of 118 titles scanned, 14 duplicates were removed, and a total of 13 abstracts from all three databases were identified for full-text retrieval. From the full text, eight articles met the inclusion criteria for this systematic review. These articles showed acceptable quality based on our scoring system. Most of the studies indicated that temporary threshold shifts were much lower when subjects were exposed to a noise level of 85 dBA or lower.
CONCLUSIONS: There were more threshold shifts in subjects adopting 90 dBA compared with 85 dBA. These temporary threshold shifts may progress to permanent shifts over time. Action curtailing noise exposure among employees would be taken earlier on adoption of 85 dBA as the permissible exposure limit, and hence prevalence of noise-induced hearing loss may be reduced.
OBJECTIVE: 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.
METHODS: 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.
RESULTS: 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.
CONCLUSIONS: 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.