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2.
Swiss Med Wkly ; 150: w20277, 2020 05 04.
Article in English | MEDLINE | ID: covidwho-2217319

ABSTRACT

In Switzerland, the COVID-19 epidemic is progressively slowing down owing to “social distancing” measures introduced by the Federal Council on 16 March 2020. However, the gradual ease of these measures may initiate a second epidemic wave, the length and intensity of which are difficult to anticipate. In this context, hospitals must prepare for a potential increase in intensive care unit (ICU) admissions of patients with acute respiratory distress syndrome. Here, we introduce icumonitoring.ch, a platform providing hospital-level projections for ICU occupancy. We combined current data on the number of beds and ventilators with canton-level projections of COVID-19 cases from two S-E-I-R models. We disaggregated epidemic projection in each hospital in Switzerland for the number of COVID-19 cases, hospitalisations, hospitalisations in ICU, and ventilators in use. The platform is updated every 3-4 days and can incorporate projections from other modelling teams to inform decision makers with a range of epidemic scenarios for future hospital occupancy.


Subject(s)
Coronavirus Infections , Forecasting/methods , Health Planning/methods , Hospital Bed Capacity , Intensive Care Units/supply & distribution , Pandemics , Pneumonia, Viral , Software , Ventilators, Mechanical/supply & distribution , COVID-19 , Coronavirus Infections/epidemiology , Decision Making, Computer-Assisted , Hospital Bed Capacity/statistics & numerical data , Hospitalization/statistics & numerical data , Hospitalization/trends , Humans , Intensive Care Units/statistics & numerical data , Models, Theoretical , Pandemics/statistics & numerical data , Patient Admission/statistics & numerical data , Pneumonia, Viral/epidemiology , Software/standards , Switzerland/epidemiology , Ventilators, Mechanical/statistics & numerical data
7.
J Intensive Care Med ; 36(8): 963-971, 2021 Aug.
Article in English | MEDLINE | ID: covidwho-1273202

ABSTRACT

In the first months of the COVID-19 pandemic in Europe, many patients were treated in hospitals using mechanical ventilation. However, due to a shortage of ICU ventilators, hospitals worldwide needed to deploy anesthesia machines for ICU ventilation (which is off-label use). A joint guidance was written to apply anesthesia machines for long-term ventilation. The goal of this research is to retrospectively evaluate the differences in measurable ventilation parameters between the ICU ventilator and the anesthesia machine as used for COVID-19 patients. In this study, we included 32 patients treated in March and April 2020, who had more than 3 days of mechanical ventilation, either in the regular ICU with ICU ventilators (Hamilton S1), or in the temporary emergency ICU with anesthetic ventilators (Aisys, GE). The data acquired during regular clinical treatment was collected from the Patient Data Management Systems. Available ventilation parameters (pressures and volumes: PEEP, Ppeak, Pinsp, Vtidal), monitored parameters EtCO2, SpO2, derived compliance C, and resistance R were processed and analyzed. A sub-analysis was performed to compare closed-loop ventilation (INTELLiVENT-ASV) to other ventilation modes. The results showed no major differences in the compared parameters, except for Pinsp. PEEP was reduced over time in the with Hamilton treated patients. This is most likely attributed to changing clinical protocol as more clinical experience and literature became available. A comparison of compliance between the 2 ventilators could not be made due to variances in the measurement of compliance. Closed loop ventilation could be used in 79% of the time, resulting in more stable EtCO2. From the analysis it can be concluded that the off-label usage of the anesthetic ventilator in our hospital did not result in differences in ventilation parameters compared to the ICU treatment in the first 4 days of ventilation.


Subject(s)
Anesthesiology/instrumentation , COVID-19 , Respiration, Artificial/methods , Ventilators, Mechanical , Aged , COVID-19/therapy , Europe , Humans , Intensive Care Units , Middle Aged , Pandemics , Retrospective Studies , Ventilators, Mechanical/supply & distribution
12.
A A Pract ; 15(3): e01392, 2021 Mar 09.
Article in English | MEDLINE | ID: covidwho-1151699

ABSTRACT

Ventilator shortages occurred due to the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). This in vitro study evaluated the effectiveness of 3-dimensional (3D)-printed splitters and 3D-printed air flow limiters (AFL) in delivering appropriate tidal volumes (TV) to lungs with different compliances. Groups were divided according to the size of the AFL: AFL-4 was a 4-mm device, AFL-5 a 5-mm device, AFL-6 a 6-mm device, and no limiter (control). A ventilator was split to supply TV to 2 artificial lungs with different compliances. The AFL improved TV distribution.


Subject(s)
COVID-19/epidemiology , COVID-19/therapy , Emergency Medical Services/methods , Lung Compliance/physiology , Printing, Three-Dimensional , Ventilators, Mechanical/supply & distribution , Humans , Lung/physiology , Male , Tidal Volume/physiology
13.
Ann Am Thorac Soc ; 18(3): 408-416, 2021 03.
Article in English | MEDLINE | ID: covidwho-1154097

ABSTRACT

The novel coronavirus disease (COVID-19) has exposed critical supply shortages both in the United States and worldwide, including those in intensive care unit (ICU) and hospital bed supply, hospital staff, and mechanical ventilators. Many of those who are critically ill have required days to weeks of supportive invasive mechanical ventilation (IMV) as part of their treatment. Previous estimates set the U.S. availability of mechanical ventilators at approximately 62,000 full-featured ventilators, with 98,000 non-full-featured devices (including noninvasive devices). Given the limited availability of this resource both in the United States and in low- and middle-income countries, we provide a framework to approach the shortage of IMV resources. Here we discuss evidence and possibilities to reduce overall IMV needs, discuss strategies to maximize the availability of IMV devices designed for invasive ventilation, discuss the underlying methods in the literature to create and fashion new sources of potential ventilation that are available to hospitals and front-line providers, and discuss the staffing needs necessary to support IMV efforts. The pandemic has already pushed cities like New York and Boston well beyond previous ICU capacity in its first wave. As hot spots continue to develop around the country and the globe, it is evident that issues may arise ahead regarding the efficient and equitable use of resources. This unique challenge may continue to stretch resources and require care beyond previously set capacities and boundaries. The approaches presented here provide a review of the known evidence and strategies for those at the front line who are facing this challenge.


Subject(s)
COVID-19/therapy , Health Resources/statistics & numerical data , Intensive Care Units/supply & distribution , Pandemics , Respiration, Artificial/statistics & numerical data , Ventilators, Mechanical/supply & distribution , COVID-19/epidemiology , Critical Care , Humans
14.
Health Care Manag Sci ; 24(2): 253-272, 2021 Jun.
Article in English | MEDLINE | ID: covidwho-1085646

ABSTRACT

The COVID-19 pandemic has created unprecedented challenges worldwide. Strained healthcare providers make difficult decisions on patient triage, treatment and care management on a daily basis. Policy makers have imposed social distancing measures to slow the disease, at a steep economic price. We design analytical tools to support these decisions and combat the pandemic. Specifically, we propose a comprehensive data-driven approach to understand the clinical characteristics of COVID-19, predict its mortality, forecast its evolution, and ultimately alleviate its impact. By leveraging cohort-level clinical data, patient-level hospital data, and census-level epidemiological data, we develop an integrated four-step approach, combining descriptive, predictive and prescriptive analytics. First, we aggregate hundreds of clinical studies into the most comprehensive database on COVID-19 to paint a new macroscopic picture of the disease. Second, we build personalized calculators to predict the risk of infection and mortality as a function of demographics, symptoms, comorbidities, and lab values. Third, we develop a novel epidemiological model to project the pandemic's spread and inform social distancing policies. Fourth, we propose an optimization model to re-allocate ventilators and alleviate shortages. Our results have been used at the clinical level by several hospitals to triage patients, guide care management, plan ICU capacity, and re-distribute ventilators. At the policy level, they are currently supporting safe back-to-work policies at a major institution and vaccine trial location planning at Janssen Pharmaceuticals, and have been integrated into the US Center for Disease Control's pandemic forecast.


Subject(s)
COVID-19 Drug Treatment , COVID-19 , Machine Learning , Aged , COVID-19/mortality , COVID-19/physiopathology , Databases, Factual , Female , Forecasting , Humans , Intensive Care Units , Male , Middle Aged , Models, Statistical , Pandemics , Policy Making , Prognosis , Risk Assessment/statistics & numerical data , SARS-CoV-2 , Ventilators, Mechanical/supply & distribution
15.
J Diabetes Sci Technol ; 15(5): 1005-1009, 2021 09.
Article in English | MEDLINE | ID: covidwho-1085175

ABSTRACT

The COVID-19 pandemic raised distinct challenges in the field of scarce resource allocation, a long-standing area of inquiry in the field of bioethics. Policymakers and states developed crisis guidelines for ventilator triage that incorporated such factors as immediate prognosis, long-term life expectancy, and current stage of life. Often these depend upon existing risk factors for severe illness, including diabetes. However, these algorithms generally failed to account for the underlying structural biases, including systematic racism and economic disparity, that rendered some patients more vulnerable to these conditions. This paper discusses this unique ethical challenge in resource allocation through the lens of care for patients with severe COVID-19 and diabetes.


Subject(s)
COVID-19/therapy , Diabetes Complications/therapy , Diabetes Mellitus/therapy , Resource Allocation , COVID-19/complications , COVID-19/epidemiology , Diabetes Complications/economics , Diabetes Complications/epidemiology , Diabetes Mellitus/economics , Diabetes Mellitus/epidemiology , Health Services Accessibility/economics , Health Services Accessibility/ethics , Health Services Accessibility/standards , Health Services Accessibility/statistics & numerical data , Health Status Disparities , Healthcare Disparities/economics , Healthcare Disparities/ethics , Healthcare Disparities/organization & administration , Healthcare Disparities/statistics & numerical data , Humans , Pandemics , Racism/ethics , Racism/statistics & numerical data , Resource Allocation/economics , Resource Allocation/ethics , Resource Allocation/organization & administration , Resource Allocation/statistics & numerical data , Triage/economics , Triage/ethics , United States/epidemiology , Ventilators, Mechanical/economics , Ventilators, Mechanical/statistics & numerical data , Ventilators, Mechanical/supply & distribution
16.
World Neurosurg ; 148: e172-e181, 2021 04.
Article in English | MEDLINE | ID: covidwho-1078227

ABSTRACT

BACKGROUND: The institution-wide response of the University of California San Diego Health system to the 2019 novel coronavirus disease (COVID-19) pandemic was founded on rapid development of in-house testing capacity, optimization of personal protective equipment usage, expansion of intensive care unit capacity, development of analytic dashboards for monitoring of institutional status, and implementation of an operating room (OR) triage plan that postponed nonessential/elective procedures. We analyzed the impact of this triage plan on the only academic neurosurgery center in San Diego County, California, USA. METHODS: We conducted a de-identified retrospective review of all operative cases and procedures performed by the Department of Neurosurgery from November 24, 2019, through July 6, 2020, a 226-day period. Statistical analysis involved 2-sample z tests assessing daily case totals over the 113-day periods before and after implementation of the OR triage plan on March 16, 2020. RESULTS: The neurosurgical service performed 1429 surgical and interventional radiologic procedures over the study period. There was no statistically significant difference in mean number of daily total cases in the pre-versus post-OR triage plan periods (6.9 vs. 5.8 mean daily cases; 1-tail P = 0.050, 2-tail P = 0.101), a trend reflected by nearly every category of neurosurgical cases. CONCLUSIONS: During the COVID-19 pandemic, the University of California San Diego Department of Neurosurgery maintained an operative volume that was only modestly diminished and continued to meet the essential neurosurgical needs of a large population. Lessons from our experience can guide other departments as they triage neurosurgical cases to meet community needs.


Subject(s)
COVID-19/epidemiology , Hospitals, University/organization & administration , Neurosurgery/organization & administration , Neurosurgical Procedures/statistics & numerical data , Academic Medical Centers/organization & administration , Brain Neoplasms/surgery , COVID-19/diagnosis , COVID-19 Nucleic Acid Testing , COVID-19 Serological Testing , California/epidemiology , Cerebrospinal Fluid Shunts/statistics & numerical data , Elective Surgical Procedures , Endovascular Procedures/statistics & numerical data , Hospital Bed Capacity , Hospital Departments/organization & administration , Humans , Infection Control , Information Dissemination/methods , Intensive Care Units , Laboratories, Hospital , Multi-Institutional Systems , Operating Rooms , Organizational Policy , Personal Protective Equipment/supply & distribution , Retrospective Studies , Risk Assessment , SARS-CoV-2 , Surge Capacity , Triage , Vascular Surgical Procedures/statistics & numerical data , Ventilators, Mechanical/supply & distribution , Wounds and Injuries/surgery
17.
Bioethics ; 35(2): 125-134, 2021 02.
Article in English | MEDLINE | ID: covidwho-1066621

ABSTRACT

In March 2020, the rapid increase in severe COVID-19 cases overwhelmed the healthcare systems in several European countries. The capacities for artificial ventilation in intensive care units were too scarce to care for patients with acute respiratory disorder connected to the disease. Several professional associations published COVID-19 triage recommendations in an extremely short time: in 21 days between March 6 and March 27. In this article, we compare recommendations from five European countries, which combine medical and ethical reflections on this situation in some detail. Our aim is to provide a detailed overview on the ethical elements of the recommendations, the differences between them and their coherence. In more general terms we want to identify shortcomings in regard to a common European response to the current situation.


Subject(s)
COVID-19/therapy , Health Care Rationing , Standard of Care/ethics , Triage/ethics , Age Factors , COVID-19/epidemiology , Europe/epidemiology , Health Personnel/ethics , Health Personnel/psychology , Health Priorities , Hospitalization , Human Rights , Humans , Intensive Care Units/ethics , Practice Guidelines as Topic , SARS-CoV-2/physiology , Treatment Outcome , Ventilators, Mechanical/supply & distribution , Withholding Treatment/ethics
18.
Nurs Inq ; 28(1): e12389, 2021 01.
Article in English | MEDLINE | ID: covidwho-1060488

ABSTRACT

The prioritisation of scarce resources has a particular urgency within the context of the COVID-19 pandemic crisis. This paper sets out a hypothetical case of Patient X (who is a nurse) and Patient Y (who is a non-health care worker). They are both in need of a ventilator due to COVID-19 with the same clinical situation and expected outcomes. However, there is only one ventilator available. In addressing the question of who should get priority, the proposal is made that the answer may lie in how the pandemic is metaphorically described using military terms. If nursing is understood to take place at the 'frontline' in the 'battle' against COVID-19, a principle of military medical ethics-namely the principle of salvage-can offer guidance on how to prioritise access to a life-saving resource in such a situation. This principle of salvage purports a moral direction to return wounded soldiers back to duty on the battlefield. Applying this principle to the hypothetical case, this paper proposes that Patient X (who is a nurse) should get priority of access to the ventilator so that he/she can return to the 'frontline' in the fight against COVID-19.


Subject(s)
COVID-19/prevention & control , Resource Allocation/standards , Salvage Therapy/trends , COVID-19/psychology , COVID-19/transmission , Humans , Intensive Care Units/organization & administration , Intensive Care Units/trends , Military Medicine/methods , Pandemics/prevention & control , Resource Allocation/methods , Salvage Therapy/psychology , Salvage Therapy/standards , Ventilators, Mechanical/supply & distribution
19.
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
20.
BMJ Open ; 11(1): e042945, 2021 01 26.
Article in English | MEDLINE | ID: covidwho-1050402

ABSTRACT

OBJECTIVE: In this study, we describe the pattern of bed occupancy across England during the peak of the first wave of the COVID-19 pandemic. DESIGN: Descriptive survey. SETTING: All non-specialist secondary care providers in England from 27 March27to 5 June 2020. PARTICIPANTS: Acute (non-specialist) trusts with a type 1 (ie, 24 hours/day, consultant-led) accident and emergency department (n=125), Nightingale (field) hospitals (n=7) and independent sector secondary care providers (n=195). MAIN OUTCOME MEASURES: Two thresholds for 'safe occupancy' were used: 85% as per the Royal College of Emergency Medicine and 92% as per NHS Improvement. RESULTS: At peak availability, there were 2711 additional beds compatible with mechanical ventilation across England, reflecting a 53% increase in capacity, and occupancy never exceeded 62%. A consequence of the repurposing of beds meant that at the trough there were 8.7% (8508) fewer general and acute beds across England, but occupancy never exceeded 72%. The closest to full occupancy of general and acute bed (surge) capacity that any trust in England reached was 99.8% . For beds compatible with mechanical ventilation there were 326 trust-days (3.7%) spent above 85% of surge capacity and 154 trust-days (1.8%) spent above 92%. 23 trusts spent a cumulative 81 days at 100% saturation of their surge ventilator bed capacity (median number of days per trust=1, range: 1-17). However, only three sustainability and transformation partnerships (aggregates of geographically co-located trusts) reached 100% saturation of their mechanical ventilation beds. CONCLUSIONS: Throughout the first wave of the pandemic, an adequate supply of all bed types existed at a national level. However, due to an unequal distribution of bed utilisation, many trusts spent a significant period operating above 'safe-occupancy' thresholds despite substantial capacity in geographically co-located trusts, a key operational issue to address in preparing for future waves.


Subject(s)
COVID-19/epidemiology , Hospital Bed Capacity , Hospitals/supply & distribution , Surge Capacity , Ventilators, Mechanical/supply & distribution , Bed Occupancy/statistics & numerical data , England/epidemiology , Health Personnel , Humans , Intensive Care Units/supply & distribution , SARS-CoV-2 , State Medicine
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