tetano
Editor, Senior Moderator
J Med Internet Res. 2020 Apr 9. doi: 10.2196/18948. [Epub ahead of print]
Cloud-Based System for Effective Surveillance and Control of COVID-19: Useful Experiences From Hubei, China.
Gong M[SUP]1[/SUP], Li L[SUP]2[/SUP], Xin S[SUP]3[/SUP], Yue Y[SUP]2[/SUP], Wang S[SUP]4[/SUP], Hong Z[SUP]2,[/SUP][SUP]1[/SUP].
Author information
Abstract
Coronavirus disease (COVID-19) has been an unprecedented challenge to the global health care system. Tools that can improve the focus of surveillance efforts and clinical decision support are of paramount importance. To illustrate how new medical informatics technologies will enable effective control of the pandemic, the Honghu Hybrid System (HHS) for COVID-19 was developed and successfully deployed within 72 hours in the city of Honghu in Hubei, China. The HHS was designed for the collection, integration, standardization, and analysis of COVID-19-related data from multiple sources, which includes a case reporting system, diagnostic labs, electronic medical records, and social media on mobile devices. HHS supports four main features: syndromic surveillance on mobile devices, policy-making decision support, clinical decision support and prioritization of resources, and follow-up of discharged patients. The syndromic surveillance component in HHS covered over 95% of the population of over 900,000 people and provided near real time evidence for the control of epidemic emergencies. The clinical decision support component in HHS was also provided to improve patient care and prioritize the limited medical resources. However, the statistical methods still require further evaluations to confirm clinical effectiveness and appropriateness of disposition assigned in this study, which warrants further investigation. The facilitating factors and challenges are discussed to provide useful insights to other cities to build suitable solutions based on cloud technologies. The HHS for COVID-19 was shown to be feasible and effective in this real-world field study, and has the potential to be migrated.
PMID:32287040DOI:10.2196/18948
Cloud-Based System for Effective Surveillance and Control of COVID-19: Useful Experiences From Hubei, China.
Gong M[SUP]1[/SUP], Li L[SUP]2[/SUP], Xin S[SUP]3[/SUP], Yue Y[SUP]2[/SUP], Wang S[SUP]4[/SUP], Hong Z[SUP]2,[/SUP][SUP]1[/SUP].
Author information
Abstract
Coronavirus disease (COVID-19) has been an unprecedented challenge to the global health care system. Tools that can improve the focus of surveillance efforts and clinical decision support are of paramount importance. To illustrate how new medical informatics technologies will enable effective control of the pandemic, the Honghu Hybrid System (HHS) for COVID-19 was developed and successfully deployed within 72 hours in the city of Honghu in Hubei, China. The HHS was designed for the collection, integration, standardization, and analysis of COVID-19-related data from multiple sources, which includes a case reporting system, diagnostic labs, electronic medical records, and social media on mobile devices. HHS supports four main features: syndromic surveillance on mobile devices, policy-making decision support, clinical decision support and prioritization of resources, and follow-up of discharged patients. The syndromic surveillance component in HHS covered over 95% of the population of over 900,000 people and provided near real time evidence for the control of epidemic emergencies. The clinical decision support component in HHS was also provided to improve patient care and prioritize the limited medical resources. However, the statistical methods still require further evaluations to confirm clinical effectiveness and appropriateness of disposition assigned in this study, which warrants further investigation. The facilitating factors and challenges are discussed to provide useful insights to other cities to build suitable solutions based on cloud technologies. The HHS for COVID-19 was shown to be feasible and effective in this real-world field study, and has the potential to be migrated.
PMID:32287040DOI:10.2196/18948