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10.1016/j.jacr.2020.09.020 http://scihub22266oqcxt.onion/10.1016/j.jacr.2020.09.020 32979322!7476574!32979322     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=32979322&cmd=llinks): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 215       J+Am+Coll+Radiol 2020 ; 17 (11): 1460-1468 Nephropedia Template TP {{tp|p=32979322|t=2020. COVID-19: Recovery Models for Radiology Departments |pdf=|usr=}}{{32979322}} gab.com Text COVID-19: Recovery Models for Radiology Departments JO: J Am Coll Radiol http://www.kidney.de/pget.php?&tw=1&pmid=32979322 #FOAvip The coronavirus disease 2019 (COVID-19) pandemic has greatly affected demand for imaging services, with marked reductions in demand for elective imaging and image-guided interventional procedures. To guide radiology planning and recovery from this unprecedented impact, three recovery models were developed to predict imaging volume over the course of the COVID-19 pandemic: (1) a long-term volume model with three scenarios based on prior disease outbreaks and other historical analogues, to aid in long-term planning when the pandemic was just beginning; (2) a short-term volume model based on the supply-demand approach, leveraging increasingly available COVID-19 data points to predict examination volume on a week-to-week basis; and (3) a next-wave model to estimate the impact from future COVID-19 surges. The authors present these models as techniques that can be used at any stage in an unpredictable pandemic timeline. Twit Text FOAVip COVID-19: Recovery Models for Radiology Departments ????J Am Coll Radiol http://www.kidney.de/pget.php?&tw=1&pmid=32979322 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32979322 #FOAvip English Wikipedia <ref>{{Cite pmid|32979322}}</ref> COVID-19: Recovery Models for Radiology Departments #MMPMID32979322 Guitron S; Pianykh OS; Succi MD; Lang M; Brink J J Am Coll Radiol 2020[Nov]; 17 (11): 1460-1468 PMID32979322show ga The coronavirus disease 2019 (COVID-19) pandemic has greatly affected demand for imaging services, with marked reductions in demand for elective imaging and image-guided interventional procedures. To guide radiology planning and recovery from this unprecedented impact, three recovery models were developed to predict imaging volume over the course of the COVID-19 pandemic: (1) a long-term volume model with three scenarios based on prior disease outbreaks and other historical analogues, to aid in long-term planning when the pandemic was just beginning; (2) a short-term volume model based on the supply-demand approach, leveraging increasingly available COVID-19 data points to predict examination volume on a week-to-week basis; and (3) a next-wave model to estimate the impact from future COVID-19 surges. The authors present these models as techniques that can be used at any stage in an unpredictable pandemic timeline. |*Health Services Needs and Demand[MESH] |*Workload[MESH] |Boston/epidemiology[MESH] |COVID-19/*epidemiology[MESH] |Forecasting[MESH] |Humans[MESH] |Models, Organizational[MESH] |Pandemics[MESH] |Planning Techniques[MESH] |Radiology Department, Hospital/*organization & administration[MESH]COVID-19: Recovery Models for Radiology Departments (epmc).pdf DeepDyve Pubget Overpricing