Critical care capacity during the COVID-19 pandemic: Global availability of intensive care beds.
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ABSTRACT:
SUBMITTER: Ma X
PROVIDER: S-EPMC7194590 | biostudies-literature | 2020 Aug
REPOSITORIES: biostudies-literature
Publications
Critical care capacity during the COVID-19 pandemic: Global availability of intensive care beds.
Ma Xiya X Vervoort Dominique D
Journal of critical care 20200423
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Project description:BackgroundAs the COVID-19 pandemic continues, there is a question of whether hospitals have adequate resources to manage patients. We aim to investigate global hospital bed (HB), acute care bed (ACB), and intensive care unit (ICU) bed capacity and determine any correlation between these hospital resources and COVID-19 mortality.MethodCross-sectional study utilizing data from the World Health Organization (WHO) and other official organizations regarding global HB, ACB, ICU bed capacity, and confirmed COVID-19 cases/mortality. Descriptive statistics and linear regression were performed.ResultsA total of 183 countries were included with a mean of 307.1 HBs, 413.9 ACBs, and 8.73 ICU beds/100,000 population. High-income regions had the highest mean number of ICU beds (12.79) and HBs (402.32) per 100,000 population whereas upper middle-income regions had the highest mean number of ACBs (424.75) per 100,000. A weakly positive significant association was discovered between the number of ICU beds/100,000 population and COVID-19 mortality. No significant associations exist between the number of HBs or ACBs per 100,000 population and COVID-19 mortality.ConclusionsGlobal COVID-19 mortality rates are likely affected by multiple factors, including hospital resources, personnel, and bed capacity. Higher income regions of the world have greater ICU, acute care, and hospital bed capacities. Mandatory reporting of ICU, acute care, and hospital bed capacity/occupancy and information relating to coronavirus should be implemented. Adopting a tiered critical care approach and targeting the expansion of space, staff, and supplies may serve to maximize the quality of care during resurgences and future disasters.
| S-EPMC7685049 | biostudies-literature
Project description:BackgroundThis paper describes a model for estimating COVID-19 related excess deaths that are a direct consequence of insufficient hospital ward bed and intensive care unit (ICU) capacity.MethodsCompartmental models were used to estimate deaths under different combinations of ICU and ward care required and received in England up to late April 2021. Model parameters were sourced from publicly available government information and organisations collating COVID-19 data. A sub-model was used to estimate the mortality scalars that represent increased mortality due to insufficient ICU or general ward bed capacity. Three illustrative scenarios for admissions numbers, 'Optimistic', 'Middling' and 'Pessimistic', were modelled and compared with the subsequent observations to the 3rd February.ResultsThe key output was the demand and capacity model described. There were no excess deaths from a lack of capacity in the 'Optimistic' scenario. Several of the 'Middling' scenario applications resulted in excess deaths-up to 597 deaths (0.6% increase) with a 20% reduction compared to best estimate ICU capacity. All the 'Pessimistic' scenario applications resulted in excess deaths, ranging from 49,178 (17.0% increase) for a 20% increase in ward bed availability, to 103,735 (35.8% increase) for a 20% shortfall in ward bed availability. These scenarios took no account of the emergence of the new, more transmissible, variant of concern (b.1.1.7).ConclusionsMortality is increased when hospital demand exceeds available capacity. No excess deaths from breaching capacity would be expected under the 'Optimistic' scenario. The 'Middling' scenario could result in some excess deaths-up to a 0.7% increase relative to the total number of deaths. The 'Pessimistic' scenario would have resulted in significant excess deaths. Our sensitivity analysis indicated a range between 49,178 (17% increase) and 103,735 (35.8% increase). Given the new variant, the pessimistic scenario appeared increasingly likely and could have resulted in a substantial increase in the number of COVID-19 deaths. In the event, it would appear that capacity was not breached at any stage at a national level with no excess deaths. it will remain unclear if minor local capacity breaches resulted in any small number of excess deaths.
| S-EPMC8076441 | biostudies-literature
Project description:Background:Brazil faces some challenges in the battle against the COVID-19 pandemic, including: the risks for cross-infection (community infection) increase in densely populated areas; low access to health services in areas where the number of beds in intensive care units (ICUs) is scarce and poorly distributed, mainly in states with low population density. Objective:To describe and intercorrelate epidemiology and geographic data from Brazil about the number of intensive care unit (ICU) beds at the onset of COVID-19 pandemic. Methods:The epidemiology and geographic data were correlated with the distribution of ICU beds (public and private health systems) and the number of beneficiaries of private health insurance using Pearson's Correlation Coefficient. The same data were correlated using partial correlation controlled by gross domestic product (GDP) and number of beneficiaries of private health insurance. Findings:Brazil has a large geographical area and diverse demographic and economic aspects. This diversity is also present in the states and the Federal District regarding the number of COVID-19 cases, deaths and case fatality rate. The effective management of severe COVID-19 patients requires ICU services, and the scenario was also dissimilar as for ICU beds and ICU beds/10,000 inhabitants for the public (SUS) and private health systems mainly at the onset of COVID-19 pandemic. The distribution of ICUs was uneven between public and private services, and most patients rely on SUS, which had the lowest number of ICU beds. In only a few states, the number of ICU beds at SUS was above 1 to 3 by 10,000 inhabitants, which is the number recommended by the World Health Organization (WHO). Conclusions:Brazil needed to improve the number of ICU beds units to deal with COVID-19 pandemic, mainly for the SUS showing a late involvement of government and health authorities to deal with the COVID-19 pandemic.
| S-EPMC7427679 | biostudies-literature
Project description:Global healthcare systems are challenged by the COVID-19 pandemic. There is a need to optimize allocation of treatment and resources in intensive care, as clinically established risk assessments such as SOFA and APACHE II scores show only limited performance for predicting the survival of severely ill COVID-19 patients. Comprehensively capturing the host physiology, we speculated that proteomics in combination with new data-driven analysis strategies could produce a new generation of prognostic discriminators. We studied two independent cohorts of patients with severe COVID-19 who required intensive care and invasive mechanical ventilation. SOFA score, Charlson comorbidity index and APACHE II score were poor predictors of survival. Instead, using plasma proteomes quantifying 302 plasma protein groups at 387 timepoints in 57 critically ill patients on invasive mechanical ventilation, we found 14 proteins that showed trajectories different between survivors and non-survivors. A proteomic predictor trained on single samples obtained at the first time point at maximum treatment level (i.e. WHO grade 7) and weeks before the outcome, achieved accurate classification of survivors (AUROC 0.81, n=49). We tested the established predictor on an independent validation cohort (AUROC of 1.0, n=24). The majority of proteins with high relevance in the prediction model belong to the coagulation system and complement cascade. Our study demonstrates that predictors derived from plasma protein levels have the potential to substantially outperform current prognostic markers in intensive care.
2022-03-03 | PXD029009 | Pride
Project description:IntroductionGermany is experiencing the second COVID-19 pandemic wave. The intensive care unit (ICU) bed capacity is an important consideration in the response to the pandemic. The purpose of this study was to determine the costs and benefits of maintaining or expanding a staffed ICU bed reserve capacity in Germany.MethodsThis study compared the provision of additional capacity to no intervention from a societal perspective. A decision model was developed using, e.g. information on age-specific fatality rates, ICU costs and outcomes, and the herd protection threshold. The net monetary benefit (NMB) was calculated based upon the willingness to pay for new medicines for the treatment of cancer, a condition with a similar disease burden in the near term.ResultsThe marginal cost-effectiveness ratio (MCER) of the last bed added to the existing ICU capacity is €21,958 per life-year gained assuming full bed utilization. The NMB decreases with an additional expansion but remains positive for utilization rates as low as 2%. In a sensitivity analysis, the variables with the highest impact on the MCER were the mortality rates in the ICU and after discharge.ConclusionsThis article demonstrates the applicability of cost-effectiveness analysis to policies of hospital pandemic preparedness and response capacity strengthening. In Germany, the provision of a staffed ICU bed reserve capacity appears to be cost-effective even for a low probability of bed utilization.
| S-EPMC7801567 | biostudies-literature
Project description:BACKGROUND:Following the regional outbreak in China, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread all over the world, presenting the healthcare systems with huge challenges worldwide. In Germany the coronavirus diseases 2019 (COVID-19) pandemic has resulted in a slowly growing demand for health care with a sudden occurrence of regional hotspots. This leads to an unpredictable situation for many hospitals, leaving the question of how many bed resources are needed to cope with the surge of COVID-19 patients. OBJECTIVE:In this study we created a simulation-based prognostic tool that provides the management of the University Hospital of Augsburg and the civil protection services with the necessary information to plan and guide the disaster response to the ongoing pandemic. Especially the number of beds needed on isolation wards and intensive care units (ICU) are the biggest concerns. The focus should lie not only on the confirmed cases as the patients with suspected COVID-19 are in need of the same resources. MATERIAL AND METHODS:For the input we used the latest information provided by governmental institutions about the spreading of the disease, with a special focus on the growth rate of the cumulative number of cases. Due to the dynamics of the current situation, these data can be highly variable. To minimize the influence of this variance, we designed distribution functions for the parameters growth rate, length of stay in hospital and the proportion of infected people who need to be hospitalized in our area of responsibility. Using this input, we started a Monte Carlo simulation with 10,000 runs to predict the range of the number of hospital beds needed within the coming days and compared it with the available resources. RESULTS:Since 2 February 2020 a total of 306 patients were treated with suspected or confirmed COVID-19?at this university hospital. Of these 84 needed treatment on the ICU. With the help of several simulation-based forecasts, the required ICU and normal bed capacity at Augsburg University Hospital and the Augsburg ambulance service in the period from 28 March 2020 to 8 June 2020 could be predicted with a high degree of reliability. Simulations that were run before the impact of the restrictions in daily life showed that we would have run out of ICU bed capacity within approximately 1 month. CONCLUSION:Our simulation-based prognosis of the health care capacities needed helps the management of the hospital and the civil protection service to make reasonable decisions and adapt the disaster response to the realistic needs. At the same time the forecasts create the possibility to plan the strategic response days and weeks in advance. The tool presented in this study is, as far as we know, the only one accounting not only for confirmed COVID-19 cases but also for suspected COVID-19 patients. Additionally, the few input parameters used are easy to access and can be easily adapted to other healthcare systems.
| S-EPMC7441598 | biostudies-literature
Project description:ObjectivesTo describe critical care nurses' perception of moral distress during the second year of the COVID-19 pandemic.Design/methodsA cross-sectional study involving a questionnaire was conducted. Participants responded to the Italian version of the Moral Distress Scale-Revised, which consists of 14 items divided in dimensions Futile care (three items), Ethical misconduct (five items), Deceptive communication (three items) and Poor teamwork (three items). For each item, participants were also invited to write about their experiences and participants' intention to leave a position now was measured by a dichotomous question. The data were analysed with descriptive statistics and qualitative content analysis. The study followed the checklist (CHERRIES) for reporting results of internet surveys.SettingCritical care nurses (n = 71) working in Swedish adult intensive care units.ResultsCritical care nurses experienced the intensity of moral distress as the highest when no one decided to withdraw ventilator support to a hopelessly ill person (Futile care), and when they had to assist another physician or nurse who provided incompetent care (Poor teamwork). Thirty-nine percent of critical care nurses were considering leaving their current position because of moral distress.ConclusionsDuring the COVID-19 pandemic, critical care nurses, due to their education and experience of intensive care nursing, assume tremendous responsibility for critically ill patients. Throughout, communication within the intensive care team seems to have a bearing on the degree of moral distress. Improvements in communication and teamwork are needed to reduce moral distress among critical care nurses.
| S-EPMC9167948 | biostudies-literature
Project description: Not available
| S-EPMC10954973 | biostudies-literature
Project description:Because geographic variation in medical care utilization is jointly determined by both supply and demand, it is difficult to empirically estimate whether capacity itself has a causal impact on utilization in health care. In this paper, I exploit short-term variation in Neonatal Intensive Care Unit (NICU) capacity that is unlikely to be correlated with unobserved demand determinants. I find that available NICU beds have little to no effect on NICU utilization for the sickest infants, but do increase utilization for those in the range of birth weights where admission decisions are likely to be more discretionary.
| S-EPMC5142636 | biostudies-literature
Project description:To understand and analyse the global impact of COVID-19 on outpatient services, inpatient care, elective surgery, and perioperative colorectal cancer care, a DElayed COloRectal cancer surgery (DECOR-19) survey was conducted in collaboration with numerous international colorectal societies with the objective of obtaining several learning points from the impact of the COVID-19 outbreak on our colorectal cancer patients which will assist us in the ongoing management of our colorectal cancer patients and to provide us safe oncological pathways for future outbreaks.
| 2346925 | ecrin-mdr-crc