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10.1093/jamia/ocaa076 http://scihub22266oqcxt.onion/10.1093/jamia/ocaa076 32548636!7337779!32548636     free     free     free Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 243.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 243.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 243.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       J+Am+Med+Inform+Assoc 2020 ; 27 (7): 1026-1131 Nephropedia Template TP {{tp|p=32548636|t=2020. Measure what matters: Counts of hospitalized patients are a better metric for health system capacity planning for a reopening |pdf=|usr=}}{{32548636}} gab.com Text Measure what matters: Counts of hospitalized patients are a better metric for health system capacity planning for a reopening JO: J Am Med Inform Assoc http://www.kidney.de/pget.php?&tw=1&pmid=32548636 #FOAvip OBJECTIVE: Responding to the COVID-19 pandemic requires accurate forecasting of health system capacity requirements using readily available inputs. We examined whether testing and hospitalization data could help quantify the anticipated burden on the health system given shelter-in-place (SIP) order. MATERIALS AND METHODS: 16,103 SARS-CoV-2 RT-PCR tests were performed on 15,807 patients at Stanford facilities between March 2 and April 11, 2020. We analyzed the fraction of tested patients that were confirmed positive for COVID-19, the fraction of those needing hospitalization, and the fraction requiring ICU admission over the 40 days between March 2nd and April 11th 2020. RESULTS: We find a marked slowdown in the hospitalization rate within ten days of SIP even as cases continued to rise. We also find a shift towards younger patients in the age distribution of those testing positive for COVID-19 over the four weeks of SIP. The impact of this shift is a divergence between increasing positive case confirmations and slowing new hospitalizations, both of which affects the demand on health systems. CONCLUSION: Without using local hospitalization rates and the age distribution of positive patients, current models are likely to overestimate the resource burden of COVID-19. It is imperative that health systems start using these data to quantify effects of SIP and aid reopening planning. Twit Text FOAVip Measure what matters: Counts of hospitalized patients are a better metric for health system capacity planning for a reopening ????J Am Med Inform Assoc http://www.kidney.de/pget.php?&tw=1&pmid=32548636 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32548636 #FOAvip English Wikipedia <ref>{{Cite pmid|32548636}}</ref> Measure what matters: Counts of hospitalized patients are a better metric for health system capacity planning for a reopening #MMPMID32548636 Kashyap S; Gombar S; Yadlowsky S; Callahan A; Fries J; Pinsky BA; Shah NH J Am Med Inform Assoc 2020[Jul]; 27 (7): 1026-1131 PMID32548636show ga OBJECTIVE: Responding to the COVID-19 pandemic requires accurate forecasting of health system capacity requirements using readily available inputs. We examined whether testing and hospitalization data could help quantify the anticipated burden on the health system given shelter-in-place (SIP) order. MATERIALS AND METHODS: 16,103 SARS-CoV-2 RT-PCR tests were performed on 15,807 patients at Stanford facilities between March 2 and April 11, 2020. We analyzed the fraction of tested patients that were confirmed positive for COVID-19, the fraction of those needing hospitalization, and the fraction requiring ICU admission over the 40 days between March 2nd and April 11th 2020. RESULTS: We find a marked slowdown in the hospitalization rate within ten days of SIP even as cases continued to rise. We also find a shift towards younger patients in the age distribution of those testing positive for COVID-19 over the four weeks of SIP. The impact of this shift is a divergence between increasing positive case confirmations and slowing new hospitalizations, both of which affects the demand on health systems. CONCLUSION: Without using local hospitalization rates and the age distribution of positive patients, current models are likely to overestimate the resource burden of COVID-19. It is imperative that health systems start using these data to quantify effects of SIP and aid reopening planning. |*Betacoronavirus[MESH] |*Health Planning[MESH] |Adolescent[MESH] |Adult[MESH] |Age Distribution[MESH] |Aged[MESH] |Aged, 80 and over[MESH] |COVID-19[MESH] |Child[MESH] |Child, Preschool[MESH] |Coronavirus Infections/diagnosis/*epidemiology[MESH] |Electronic Health Records[MESH] |Female[MESH] |Forecasting[MESH] |Hospital Bed Capacity/*statistics & numerical data[MESH] |Hospitalization/*statistics & numerical data[MESH] |Humans[MESH] |Male[MESH] |Middle Aged[MESH] |Models, Statistical[MESH] |Pandemics[MESH] |Pneumonia, Viral/diagnosis/*epidemiology[MESH] |Quarantine[MESH] |SARS-CoV-2[MESH] |United States/epidemiology[MESH]Measure what matters: Counts of hospitalized patients are a better met(epmc).pdf DeepDyve Pubget Overpricing