A Simulation-Based Failure Mode Analysis of SARS-CoV-2 Infection Control and Prevention in Emergency Departments.
Journal
Simulation in healthcare : journal of the Society for Simulation in Healthcare
ISSN: 1559-713X
Titre abrégé: Simul Healthc
Pays: United States
ID NLM: 101264408
Informations de publication
Date de publication:
01 Dec 2021
01 Dec 2021
Historique:
pubmed:
11
9
2020
medline:
15
12
2021
entrez:
10
9
2020
Statut:
ppublish
Résumé
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. 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 Stradiņš 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. 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. 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.
Sections du résumé
BACKGROUND
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
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 Stradiņš 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
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
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.
Identifiants
pubmed: 32910105
pii: 01266021-202112000-00003
doi: 10.1097/SIH.0000000000000506
doi:
Types de publication
Journal Article
Multicenter Study
Langues
eng
Sous-ensembles de citation
IM
Pagination
386-391Informations de copyright
Copyright © 2020 Society for Simulation in Healthcare.
Déclaration de conflit d'intérêts
The authors declare no conflict of interest.
Références
WHO Director-General's opening remarks at the media briefing on COVID-19 - 11 March 2020. Available at: https://www.who.int/dg/speeches/detail/who-director-general-s-opening-remarks-at-the-media-briefing-on-covid-19---11-march-2020 . Accessed April 20, 2020.
Remuzzi A, Remuzzi G. COVID-19 and Italy: what next? Lancet 2020;395(10231):1225–1228.
Wang J, Zhou M, Liu F. Reasons for healthcare workers becoming infected with novel coronavirus disease 2019 (COVID-19) in China. J Hosp Infect 2020;105:100–101.
Cook DA, Hatala R, Brydges R, et al. Technology-enhanced simulation for health professions education: a systematic review and meta-analysis. JAMA 2011;306(9):978–988.
Workman AD, Welling DB, Carter BS, et al. Endonasal instrumentation and aerosolization risk in the era of COVID-19: simulation, literature review, and proposed mitigation strategies. Int Forum Allergy Rhinol 2020;10(7):798–805.
Verbeek JH, Rajamaki B, Ijaz S, et al. Personal protective equipment for preventing highly infectious diseases due to exposure to contaminated body fluids in healthcare staff. Cochrane Database Syst Rev 2019;7(7):CD011621.
Dieckmann P, Torgeirsen K, Qvindesland SA, Thomas L, Bushell V, Langli Ersdal H. The use of simulation to prepare and improve responses to infectious disease outbreaks like COVID-19: practical tips and resources from Norway, Denmark, and the UK. Adv Simul (Lond) 2020;5:3.
Lamé G, Dixon-Woods M. Using clinical simulation to study how to improve quality and safety in healthcare. BMJ Simul Technol Enhanc Learn 2020;6(2):87–94.
WHO simulation exercise manual: a practical guide and tool for planning, conducting and evaluating simulation exercises for outbreaks and public health emergency preparedness and response. Available at: https://apps.who.int/iris/handle/10665/254741 . Accessed April 20, 2020.
Carvalho E, Castro P, León E, et al. Multi-professional simulation and risk perception of health care workers caring for Ebola-infected patients. Nurs Crit Care 2019;24(5):256–262.
Biddell EA, Vandersall BL, Bailes SA, et al. Use of simulation to gauge preparedness for Ebola at a free-standing children's hospital. Simul Healthc 2016;11(2):94–99.
Delaney H, Lucero P, Maves R, et al. Ebola virus disease simulation case series: patient with Ebola virus disease in the prodromal phase of illness (scenario 1), the “wet” gastrointestinal phase of illness (scenario 2), and the late, critically ill phase of disease (scenario 3). Simul Healthc 2016;11(2):106–116.
Poller B, Tunbridge A, Hall S, et al. A unified personal protective equipment ensemble for clinical response to possible high consequence infectious diseases: a consensus document on behalf of the HCID programme. J Infect 2018;77(6):496–502.
Okunromade OF, Lokossou VK, Anya I, et al. Performance of the public health system during a full-scale yellow fever simulation exercise in Lagos state, Nigeria, in 2018: how prepared are we for the next outbreak? Health Secur 2019;17(6):485–494.
Public health emergency preparedness for cases of viral haemorrhagic fever (Ebola) in Belgium: a peer review. Available at: https://www.ecdc.europa.eu/en/publications-data/public-health-emergency-preparedness-cases-viral-haemorrhagic-fever-ebola-belgium . Accessed April 20, 2020.
Phin NF, Rylands AJ, Allan J, Edwards C, Enstone JE, Nguyen-Van-Tam JS. Personal protective equipment in an influenza pandemic: a UK simulation exercise. J Hosp Infect 2009;71(1):15–21.
Watson CM, Duval-Arnould JM, McCrory MC, et al. Simulated pediatric resuscitation use for personal protective equipment adherence measurement and training during the 2009 influenza (H1N1) pandemic. Jt Comm J Qual Patient Saf 2011;37(11):AP1–AP523.
Institute for Healthcare Improvement. QI Essentials Toolkit: Failure Modes and Effects Analysis (FMEA). 2017.
Dharamsi A, Yi S, Hayman K. COVID-19: respiratory failure. EM Sim Cases 2020. Available at: https://emsimcases.com/2020/02/18/suspected-covid-19/ . Accessed April 20, 2020.
Rudolph JW, Simon R, Dufresne RL, Raemer DB. There's no such thing as “nonjudgmental” debriefing: a theory and method for debriefing with good judgment. Simul Healthc 2006;1(1):49–55.
DeRosier J, Stalhandske E, Bagian JP, Nudell T. Using Health Care Failure Mode and Effect Analysis™: the VA National Center for patient safety's prospective risk analysis system. Jt Comm J Qual Improv 2002;28(5):248–267.
Moore D, Gamage B, Bryce E, Copes R, Yassi A. BC Interdisciplinary Respiratory Protection Study Group. Protecting health care workers from SARS and other respiratory pathogens: organizational and individual factors that affect adherence to infection control guidelines. Am J Infect Control 2005;33(2):88–96.
Davis S, Riley W, Gurses AP, Miller K, Hansen H. Failure modes and effects analysis based on in situ simulations: a methodology to improve understanding of risks and failures. In: Henriksen K, Battles JB, Keyes MA, Grady ML, eds. Advances in Patient Safety: New Directions and Alternative Approaches (Vol 3: Performance and Tools) . Rockville, MD: Agency for Healthcare Research and Quality (US); 2008. (Advances in Patient Safety). Available at: http://www.ncbi.nlm.nih.gov/books/NBK43662/ . Accessed April 20, 2020.
NHS National Patient Safety Agency. A risk matrix for risk managers. 2008. Available at: https://www.neas.nhs.uk/media/118673/foi.16.170_-_risk_matrix_for_risk_managers_v91.pdf . Accessed April 20, 2020.
Nielsen DS, Dieckmann P, Mohr M, Mitchell AU, Østergaard D. Augmenting health care failure modes and effects analysis with simulation. Simul Healthc 2014;9(1):48–55.
Personal protective equipment (PPE) needs in healthcare settings for the care of patients with suspected or confirmed novel coronavirus (2019-nCoV). European Centre for Disease Prevention and Control 2020. Available at: https://www.ecdc.europa.eu/en/publications-data/personal-protective-equipment-ppe-needs-healthcare-settings-care-patients . Accessed April 20, 2020.
Adams JG, Walls RM. Supporting the health care workforce during the COVID-19 global epidemic. JAMA 2020 Mar 12. doi: 10.1001/jama.2020.3972. Online ahead of print.
doi: 10.1001/jama.2020.3972.
DeJoy DM, Searcy CA, Murphy LR, Gershon RR. Behavior–diagnostic analysis of compliance with universal precautions among nurses. J Occup Health Psychol 2000;5(1):127–141.
Ran L, Chen X, Wang Y, Wu W, Zhang L, Tan X. Risk factors of healthcare workers with corona virus disease 2019: a retrospective cohort study in a designated hospital of Wuhan in China. Clin Infect Dis 2020 Mar 17. doi: 10.1093/cid/ciaa287. Online ahead of print.
doi: 10.1093/cid/ciaa287.
Ong SWX, Tan YK, Chia PY, et al. Air, surface environmental, and personal protective equipment contamination by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from a symptomatic patient. JAMA 2020;323(16):1610–1612. Available at: https://jamanetwork.com/journals/jama/fullarticle/2762692 . Accessed April 20, 2020.
Reason J. Human error: models and management. BMJ 2000;320(7237):768.
Balmaks R, Whitfill TM, Ziemele B, et al. Pediatric readiness in the emergency department and its association with patient outcomes in critical care: a prospective cohort study. Pediatr Crit Care Med 2020;21(5):e213–e220.
Pārtrauc COVID-19 izplatību!. Available at: https://www.partrauc-izplatibu.lv/ . Accessed April 20, 2020.
OECD/European Observatory on Health Systems and Policies (2017), Latvia: Country Health Profile 2017. Brussels, OECD Publishing, 2017. Available at: https://www.oecd-ilibrary.org/content/publication/9789264283466-en . Accessed April 20, 2020.
Cardeñosa N, Domínguez A, Carratalà J, et al. Usefulness of simulated cases for assessing pandemic influenza preparedness plans. Clin Microbiol Infect 2010;16(9):1364–1367.