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Front Psychiatry ; 12: 622098, 2021.
Article in English | MEDLINE | ID: covidwho-1221981

ABSTRACT

Context: This study is a quanti-qualitative analysis of all contacts to a helpline service for hospital workers during the COVID-19 crisis. Our aim was to describe the nature of mental burden in hospital workers and factors subjectively associated to this burden from the workers' perspective. Methods: We included all 50 contacts from 25 different workers and 10 different professions over the course of 1 month. We described the corpus and reported the computerized qualitative analysis of summary of contacts. We performed a descendant hierarchical analysis and analyzed specificities of classes of age with a correspondence factor analysis. Results: The corpus was composed of three classes: (1) distress specific to the COVID-19 situation, (2) help provided, and (3) pre-existing psychological vulnerability. Factors subjectively responsible for mental distress were: (a) the contamination risk, (b) confinement, and (c) the rapidly evolving situation and changing instructions. Lack of "COVID-free time" seemed to increase negative emotions. Reassignment to a high viral density unit was a stressor, especially in older workers. Young workers mentioned pre-existing vulnerability more than others. Fear of death was shared by all classes of age, regardless of the objective risk of contamination. Discussion: Hospital workers experience mental distress factors both in common with the general population and specific to the hospital environment. Preserving and organizing support for the mental health of all hospital workers is a critical challenge, including those with poorly recognized professions. Leads for institutions to avoid additional stressors for hospital workers are presented. Young workers with pre-existing vulnerability seem particularly impacted.

2.
Anaesth Crit Care Pain Med ; 39(6): 709-715, 2020 Dec.
Article in English | MEDLINE | ID: covidwho-1059695

ABSTRACT

BACKGROUND: Whereas 5415 Intensive Care Unit (ICU) beds were initially available, 7148 COVID-19 patients were hospitalised in the ICU at the peak of the outbreak. The present study reports how the French Health Care system created temporary ICU beds to avoid being overwhelmed. METHODS: All French ICUs were contacted for answering a questionnaire focusing on the available beds and health care providers before and during the outbreak. RESULTS: Among 336 institutions with ICUs before the outbreak, 315 (94%) participated, covering 5054/5531 (91%) ICU beds. During the outbreak, 4806 new ICU beds (+95% increase) were created from Acute Care Unit (ACU, 2283), Post Anaesthetic Care Unit and Operating Theatre (PACU & OT, 1522), other units (374) or real build-up of new ICU beds (627), respectively. At the peak of the outbreak, 9860, 1982 and 3089 ICU, ACU and PACU beds were made available. Before the outbreak, 3548 physicians (2224 critical care anaesthesiologists, 898 intensivists and 275 from other specialties, 151 paediatrics), 1785 residents, 11,023 nurses and 6763 nursing auxiliaries worked in established ICUs. During the outbreak, 2524 physicians, 715 residents, 7722 nurses and 3043 nursing auxiliaries supplemented the usual staff in all ICUs. A total number of 3212 new ventilators were added to the 5997 initially available in ICU. CONCLUSION: During the COVID-19 outbreak, the French Health Care system created 4806 ICU beds (+95% increase from baseline), essentially by transforming beds from ACUs and PACUs. Collaboration between intensivists, critical care anaesthesiologists, emergency physicians as well as the mobilisation of nursing staff were primordial in this context.


Subject(s)
COVID-19/epidemiology , Hospital Bed Capacity/statistics & numerical data , Intensive Care Units/statistics & numerical data , National Health Programs , Pandemics , SARS-CoV-2 , Bed Conversion/statistics & numerical data , France/epidemiology , Health Care Surveys/statistics & numerical data , Hospitalization/statistics & numerical data , Humans , Personnel Staffing and Scheduling/statistics & numerical data , Personnel, Hospital/supply & distribution , Retrospective Studies , Ventilators, Mechanical/supply & distribution
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