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10.2196/18948 http://scihub22266oqcxt.onion/10.2196/18948 32287040!7179239!32287040     free     free     free Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 249.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       J+Med+Internet+Res 2020 ; 22 (4): e18948 Nephropedia Template TP {{tp|p=32287040|t=2020. Cloud-Based System for Effective Surveillance and Control of COVID-19: Useful Experiences From Hubei, China |pdf=|usr=}}{{32287040}} gab.com Text Cloud-Based System for Effective Surveillance and Control of COVID-19: Useful Experiences From Hubei, China JO: J Med Internet Res http://www.kidney.de/pget.php?&tw=1&pmid=32287040 #FOAvip 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. Twit Text FOAVip Cloud-Based System for Effective Surveillance and Control of COVID-19: Useful Experiences From Hubei, China ????J Med Internet Res http://www.kidney.de/pget.php?&tw=1&pmid=32287040 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32287040 #FOAvip English Wikipedia <ref>{{Cite pmid|32287040}}</ref> Cloud-Based System for Effective Surveillance and Control of COVID-19: Useful Experiences From Hubei, China #MMPMID32287040 Gong M; Liu L; Sun X; Yang Y; Wang S; Zhu H J Med Internet Res 2020[Apr]; 22 (4): e18948 PMID32287040show ga 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. |*Cloud Computing[MESH] |*Decision Support Systems, Clinical[MESH] |*Sentinel Surveillance[MESH] |Betacoronavirus[MESH] |COVID-19[MESH] |China/epidemiology[MESH] |Coronavirus[MESH] |Coronavirus Infections/*epidemiology[MESH] |Delivery of Health Care[MESH] |Humans[MESH] |Mobile Applications[MESH] |Pandemics[MESH] |Patient Discharge[MESH] |Pneumonia, Viral/*epidemiology[MESH] |Public Health[MESH]Cloud-Based System for Effective Surveillance and Control of COVID-19:(epmc).pdf DeepDyve Pubget Overpricing