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10.1097/SIH.0000000000000506 http://scihub22266oqcxt.onion/10.1097/SIH.0000000000000506 32910105!ä!32910105 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 245.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 245.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Simul+Healthc 2021 ; 16 (6): 386-391 Nephropedia Template TP {{tp|p=32910105|t=2021. A Simulation-Based Failure Mode Analysis of SARS-CoV-2 Infection Control and Prevention in Emergency Departments |pdf=|usr=}}{{32910105}} gab.com Text A Simulation-Based Failure Mode Analysis of SARS-CoV-2 Infection Control and Prevention in Emergency Departments JO: Simul Healthc http://www.kidney.de/pget.php?&tw=1&pmid=32910105 #FOAvip BACKGROUND: Severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2, the causative agent of coronavirus disease 2019 (COVID-19)] outbreak has been declared a global pandemic by the World Health Organization. The COVID-19 pandemic has highlighted problems of sustainable infection prevention and control measures worldwide, particularly the emerging issues with an insufficient supply of personal protective equipment. The aim of this study was to provide an action plan for mitigation of occupational hazards and nosocomial spread of SARS-CoV-2 through a failure mode analysis based on observations during in situ simulations. METHODS: A multicenter, cross-sectional, observational, simulation-based study was performed in Latvia from March 2 to 26, 2020. This study was conducted at 7 hospitals affiliated with Riga Stradins University. The presentation of a COVID-19 patient was simulated with an in situ simulations, followed by a structured debrief. Healthcare Failure Modes and Effects Analysis is a tool for conducting a systematic, proactive analysis of a process in which harm may occur. We used Healthcare Failure Modes and Effects Analysis to analyze performance gaps and systemic issues. RESULTS: A total of 67 healthcare workers from 7 hospitals participated in the study (range = 4-17). A total of 32 observed failure modes were rated using a risk matrix. Twenty-seven failure modes (84.4%) were classified as either medium or high risk or were single-point weaknesses, hence evaluated for action type and action; 11 (40.7%) were related to organizational, 11 (40.7%) to individual, and 5 (18.5%) to environmental factors. CONCLUSIONS: Simulation-based failure mode analysis helped us identify the risks related to the preparedness of the healthcare workers and emergency departments for the COVID-19 pandemic in Latvia. We believe that this approach can be implemented to assess and maintain readiness for the outbreaks of emerging infectious diseases in the future. Twit Text FOAVip A Simulation-Based Failure Mode Analysis of SARS-CoV-2 Infection Control and Prevention in Emergency Departments ????Simul Healthc http://www.kidney.de/pget.php?&tw=1&pmid=32910105 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32910105 #FOAvip English Wikipedia <ref>{{Cite pmid|32910105}}</ref> A Simulation-Based Failure Mode Analysis of SARS-CoV-2 Infection Control and Prevention in Emergency Departments #MMPMID32910105 Balmaks R; Gramatniece A; Vilde A; Lulla M; Dumpis U; Gross IT; Slezina I Simul Healthc 2021[Dec]; 16 (6): 386-391 PMID32910105show ga BACKGROUND: Severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2, the causative agent of coronavirus disease 2019 (COVID-19)] outbreak has been declared a global pandemic by the World Health Organization. The COVID-19 pandemic has highlighted problems of sustainable infection prevention and control measures worldwide, particularly the emerging issues with an insufficient supply of personal protective equipment. The aim of this study was to provide an action plan for mitigation of occupational hazards and nosocomial spread of SARS-CoV-2 through a failure mode analysis based on observations during in situ simulations. METHODS: A multicenter, cross-sectional, observational, simulation-based study was performed in Latvia from March 2 to 26, 2020. This study was conducted at 7 hospitals affiliated with Riga Stradins University. The presentation of a COVID-19 patient was simulated with an in situ simulations, followed by a structured debrief. Healthcare Failure Modes and Effects Analysis is a tool for conducting a systematic, proactive analysis of a process in which harm may occur. We used Healthcare Failure Modes and Effects Analysis to analyze performance gaps and systemic issues. RESULTS: A total of 67 healthcare workers from 7 hospitals participated in the study (range = 4-17). A total of 32 observed failure modes were rated using a risk matrix. Twenty-seven failure modes (84.4%) were classified as either medium or high risk or were single-point weaknesses, hence evaluated for action type and action; 11 (40.7%) were related to organizational, 11 (40.7%) to individual, and 5 (18.5%) to environmental factors. CONCLUSIONS: Simulation-based failure mode analysis helped us identify the risks related to the preparedness of the healthcare workers and emergency departments for the COVID-19 pandemic in Latvia. We believe that this approach can be implemented to assess and maintain readiness for the outbreaks of emerging infectious diseases in the future. |*COVID-19[MESH] |Cross-Sectional Studies[MESH] |Emergency Service, Hospital[MESH] |Health Personnel[MESH] |Humans[MESH] |Infection Control[MESH] |Pandemics[MESH]A Simulation-Based Failure Mode Analysis of SARS-CoV-2 Infection Contr(epmc).pdf DeepDyve Pubget Overpricing