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Cloud-Based System for Effective Surveillance and Control of COVID-19: Useful Experiences From Hubei, China.
Gong, Mengchun; Liu, Li; Sun, Xin; Yang, Yue; Wang, Shuang; Zhu, Hong.
  • Gong M; Institute of Health Management, Southern Medical University, Guangzhou, China.
  • Liu L; Nanfang Hospital, Southern Medical University, Guangzhou, China.
  • Sun X; Chinese Evidence-Based Medicine Center, West China Hospital, Sichuan University, Chengdu, China.
  • Yang Y; Nanfang Hospital, Southern Medical University, Guangzhou, China.
  • Wang S; Institutes for Systems Genetics, West China Hospital, Sichuan University, Chengdu, China.
  • Zhu H; Institute of Health Management, Southern Medical University, Guangzhou, China.
J Med Internet Res ; 22(4): e18948, 2020 04 22.
Artículo en Inglés | MEDLINE | ID: covidwho-62910
ABSTRACT

BACKGROUND:

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.

OBJECTIVE:

The aim of this study was to illustrate how new medical informatics technologies may enable effective control of the pandemic through the development and successful 72-hour deployment of the Honghu Hybrid System (HHS) for COVID-19 in the city of Honghu in Hubei, China.

METHODS:

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.

RESULTS:

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.

CONCLUSIONS:

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.
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Texto completo: Disponible Colección: Bases de datos internacionales Base de datos: MEDLINE Asunto principal: Neumonía Viral / Infecciones por Coronavirus / Vigilancia de Guardia / Sistemas de Apoyo a Decisiones Clínicas / Nube Computacional Tipo de estudio: Estudio de cohorte / Estudio experimental / Estudio observacional / Estudio pronóstico / Investigación cualitativa Límite: Humanos País/Región como asunto: Asia Idioma: Inglés Revista: J Med Internet Res Asunto de la revista: Informática Médica Año: 2020 Tipo del documento: Artículo País de afiliación: 18948

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Texto completo: Disponible Colección: Bases de datos internacionales Base de datos: MEDLINE Asunto principal: Neumonía Viral / Infecciones por Coronavirus / Vigilancia de Guardia / Sistemas de Apoyo a Decisiones Clínicas / Nube Computacional Tipo de estudio: Estudio de cohorte / Estudio experimental / Estudio observacional / Estudio pronóstico / Investigación cualitativa Límite: Humanos País/Región como asunto: Asia Idioma: Inglés Revista: J Med Internet Res Asunto de la revista: Informática Médica Año: 2020 Tipo del documento: Artículo País de afiliación: 18948