Nanomanagement networking: Organisational resilience to COVID-19 surge capacity in Egypt.

This paper draws on the literature of nanomanagement and organisational resilience to explore the reality of surge capacity in the context of the Egyptian government's effort to contain the recent COVID-19 pandemic. It utilises nanomanagement networking to explain the significant models of decision making, communication and sense making, taking into account the resilient interconnections and interdependence among organisations, to understand how these impact on the resilience of crisis management surge capacity. With a focus on COVID-19 crisis management in Egypt, the study analyses empirical data collected from interviews with actors from different governmental organisations. Following this, the paper focuses on the role of nanomanagement in realising the resilience of interorganisational network capacity to obtain accurate and up-to-date information in order to develop the system strategies and responses necessary to enable convenient surge capacity for COVID-19 crisis management.

Optimization of a Patient Distribution Framework: Second Wave COVID-19 Preparedness and Challenges in the Amsterdam Region.

To meet surge capacity and to prevent hospitals from being overwhelmed with COVID-19 patients, a regional crisis task force was established during the first pandemic wave to coordinate the even distribution of COVID-19 patients in the Amsterdam region. Based on a preexisting regional management framework for acute care, this task force was led by physicians experienced in managing mass casualty incidents. A collaborative framework consisting of the regional task force, the national task force, and the region's hospital crisis coordinators facilitated intraregional and interregional patient transfers. After hospital admission rates declined following the first COVID-19 wave, a window of opportunity enabled the task forces to create, standardize, and optimize their patient transfer processes before a potential second wave commenced. Improvement was prioritized according to 3 crucial pillars: process standardization, implementation of new strategies, and continuous evaluation of the decision tree. Implementing the novel "fair share" model as a straightforward patient distribution directive supported the regional task force's decisionmaking. Standardization of the digital patient transfer registration process contributed to a uniform, structured system in which every patient transfer was verifiable on intraregional and interregional levels. Furthermore, the regional task force team was optimized and evaluation meetings were standardized. Lines of communication were enhanced, resulting in increased situational awareness among all stakeholders that indirectly provided a safety net and an improved integral framework for managing COVID-19 care capacities. In this article, we describe enhancements to a patient transfer framework that can serve as an exemplary system to meet surge capacity demands during current and future pandemics.

Dynamic assessment of surge capacity in a large hospital network during COVID-19 pandemic.

BACKGROUND: The COVID-19 pandemic has provided an unprecedented scenario to deepen knowledge of surge capacity (SC), assessment of which remains a challenge. This study reports a large-scale experience of a multi-hospital network, with the aim of evaluating the characteristics of different hospitals involved in the response and of measuring a real-time SC based on two complementary modalities (actual, base) referring to the intensive care units (ICU). METHODS: Data analysis referred to two consecutive pandemic waves (March-December 2020). Regarding SC, two different levels of analysis are considered: single hospital category (referring to a six-level categorization based on the number of hospital beds) and multi-hospital wide (referring to the response of the entire hospital network). RESULTS: During the period of 114 days, the analysis revealed a key role of the biggest hospitals (>Category-4) in terms of involvement in the pandemic response. In terms of SC, Category-4 hospitals showed the highest mean SC values, irrespective of the calculation method and level of analysis. At the multi-hospital level, the analysis revealed an overall ICU-SC (base) of 84.4% and an ICU-SC (actual) of 106.5%. CONCLUSIONS: The results provide benchmarks to better understand ICU hospital response capacity, highlighting the need for a more flexible approach to SC definition.

Caring for COVID-19 patients through a pandemic in the intensive care setting: A narrative review.

Since the declaration of the novel SARS-CoV-2 virus pandemic, health systems/ health-care-workers globally have been overwhelmed by a vast number of COVID-19 related hospitalizations and intensive care unit (ICU) admissions. During the early stages of the pandemic, the lack of formalized evidence-based guidelines in all aspects of patient management was a significant challenge. Coupled with a lack of effective pharmacotherapies resulted in unsatisfactory outcomes in ICU patients. The anticipated increment in ICU surge capacity was staggering, with almost every ICU worldwide being advised to increase their capacity to allow adequate care provision in response to multiple waves of the pandemic. This increase in surge capacity required advanced planning and reassessments at every stage, taking advantage of experienced gained in combination with emerging evidence. In University Hospital Southampton General Intensive Care Unit (GICU), despite the initial lack of national and international guidance, we enhanced our ICU capacity and developed local guidance on all aspects of care to address the rapid demand from the increasing COVID-19 admissions. The main element of this success was a multidisciplinary team approach intertwined with equipment and infrastructural reorganization. This narrative review provides an insight into the approach adopted by our center to manage patients with COVID-19 critical illness, exploring the initial planning process, including contingency preparations to accommodate (360% capacity increment) and adaptation of our management pathways as more evidence emerged throughout the pandemic to provide the most appropriate levels of care to our patients. We hope our experience will benefit other intensive care units worldwide. This article is categorized under: Infectious Diseases > Genetics/Genomics/Epigenetics.

Dynamic assessment of surge capacity in a large hospital network during COVID-19 pandemic.

BACKGROUND: The COVID-19 pandemic has provided an unprecedented scenario to deepen knowledge of surge capacity (SC), assessment of which remains a challenge. This study reports a large-scale experience of a multi-hospital network, with the aim of evaluating the characteristics of different hospitals involved in the response and of measuring a real-time SC based on two complementary modalities (actual, base) referring to the intensive care units (ICU). METHODS: Data analysis referred to two consecutive pandemic waves (March-December 2020). Regarding SC, two different levels of analysis are considered: single hospital category (referring to a six-level categorization based on the number of hospital beds) and multi-hospital wide (referring to the response of the entire hospital network). RESULTS: During the period of 114 days, the analysis revealed a key role of the biggest hospitals (>Category-4) in terms of involvement in the pandemic response. In terms of SC, Category-4 hospitals showed the highest mean SC values, irrespective of the calculation method and level of analysis. At the multi-hospital level, the analysis revealed an overall ICU-SC (base) of 84.4% and an ICU-SC (actual) of 106.5%. CONCLUSIONS: The results provide benchmarks to better understand ICU hospital response capacity, highlighting the need for a more flexible approach to SC definition.

Hospitals early challenges and interventions combatting COVID-19 in the Eastern Mediterranean Region.

BACKGROUND: During rapidly evolving outbreaks, health services and essential medical care are interrupted as facilities have become overwhelmed responding to COVID-19. In the Eastern Mediterranean Region (EMR), more than half of countries are affected by emergencies, hospitals face complex challenges as they respond to humanitarian crises, maintain essential services, and fight the pandemic. While hospitals in the EMR have adapted to combat COVID-19, evidence-based and context-specific recommendations are needed to guide policymakers and hospital managers on best practices to strengthen hospitals' readiness, limit the impact of the pandemic, and create lasting hospital sector improvements towards recovery and resilience. AIM: Guided by the WHO/EMR's "Hospital readiness checklist for COVID-19", this study presents the experiences of EMR hospitals in combatting COVID-19 across the 22 EMR countries, including their challenges and interventions across the checklist domains, to inform improvements to pandemic preparedness, response, policy, and practice. METHODS: To collect in-depth and comprehensive information on hospital experiences, qualitative and descriptive quantitative data was collected between May-October 2020. To increase breadth of responses, this comprehensive qualitative study triangulated findings from a regional literature review with the findings of an open-ended online survey (n = 139), and virtual in-depth key informant interviews with 46 policymakers and hospital managers from 18 out of 22 EMR countries. Purposeful sampling supported by snowballing was used and continued until reaching data saturation, measures were taken to increase the trustworthiness of the results. Led by the checklist domains, qualitative data was thematically analyzed using MAXQDA. FINDINGS: Hospitals faced continuously changing challenges and needed to adapt to maintain operations and provide essential services. This thematic analysis revealed major themes for the challenges and interventions utilized by hospitals for each of hospital readiness domains: Preparedness, Leadership, Operational support, logistics, supply management, Communications and Information, Human Resources, Continuity of Essential Services and Surge Capacity, Rapid Identification and Diagnosis, Isolation and Case Management, and Infection, Prevention and Control. CONCLUSION: Hospitals are the backbone of COVID-19 response, and their resilience is essential for achieving universal health coverage. Multi-pronged (across each of the hospitals readiness domains) and multi-level policies are required to strengthen hospitals resilience and prepare health systems for future outbreaks and shocks.

Avoiding Crisis Conditions in the Healthcare Infrastructure: 2 Case Studies in Statewide Collaboration.

In fall 2020, COVID-19 infections accelerated across the United States. For many states, a surge in COVID-19 cases meant planning for the allocation of scarce resources. Crisis standards of care planning focuses on maintaining high-quality clinical care amid extreme operating conditions. One of the primary goals of crisis standards of care planning is to use all preventive measures available to avoid reaching crisis conditions and the complex triage decisionmaking involved therein. Strategies to stay out of crisis must respond to the actual experience of people on the frontlines, or the "ground truth," to ensure efforts to increase critical care bed numbers and augment staff, equipment, supplies, and medications to provide an effective response to a public health emergency. Successful management of a surge event where healthcare needs exceed capacity requires coordinated strategies for scarce resource allocation. In this article, we examine the ground truth challenges encountered in response efforts during the fall surge of 2020 for 2 states-Nebraska and California-and the strategies each state used to enable healthcare facilities to stay out of crisis standards of care. Through these 2 cases, we identify key tools deployed to reduce surge and barriers to coordinated statewide support of the healthcare infrastructure. Finally, we offer considerations for operationalizing key tools to alleviate surge and recommendations for stronger statewide coordination in future public health emergencies.

Primary Care's Historic Role in Vaccination and Potential Role in COVID-19 Immunization Programs.

PURPOSE: Coronavirus disease 2019 (COVID-19) pandemic recovery will require a broad and coordinated effort for infection testing, immunity determination, and vaccination. With the advent of several COVID-19 vaccines, the dissemination and delivery of COVID-19 immunization across the nation is of concern. Previous immunization delivery patterns may reveal important components of a comprehensive and sustainable effort to immunize everyone in the nation. METHODS: The delivery of vaccinations were enumerated by provider type using 2017 Medicare Part B Fee-For-Service data and the 2013-2017 Medical Expenditure Panel Survey. The delivery of these services was examined at the service, physician, and visit level. RESULTS: In 2017 Medicare Part B Fee-For-Service, primary care physicians provided the largest share of services for vaccinations (46%), followed closely by mass immunizers (45%), then nurse practitioners/physician assistants (NP/PAs) (5%). The Medical Expenditure Panel Survey showed that primary care physicians provided most clinical visits for vaccination (54% of all visits). CONCLUSIONS: Primary care physicians have played a crucial role in delivery of vaccinations to the US population, including the elderly, between 2012-2017. These findings indicate primary care practices may be a crucial element of vaccine counseling and delivery in the upcoming COVID-19 recovery and immunization efforts in the United States.

Optimizing Nurse Staffing During a Pandemic.

This article describes how a health care organization optimized staffing during the COVID-19 crisis by capitalizing on the expertise of nursing professional development practitioners to create a rapid deployment onboarding plan. The rapid onboarding training plan provided Riley Hospital for Children at Indiana University Health with a sense of stability in an uncertain time. Designing a plan that easily could be modified allowed the organization to be prepared during the pandemic and at a point where staffing needs must meet surge capacity. [J Contin Educ Nurs. 2021;52(3):109-111.].

How the COVID-19 pandemic will change the future of critical care.

Coronavirus disease 19 (COVID-19) has posed unprecedented healthcare system challenges, some of which will lead to transformative change. It is obvious to healthcare workers and policymakers alike that an effective critical care surge response must be nested within the overall care delivery model. The COVID-19 pandemic has highlighted key elements of emergency preparedness. These include having national or regional strategic reserves of personal protective equipment, intensive care unit (ICU) devices, consumables and pharmaceuticals, as well as effective supply chains and efficient utilization protocols. ICUs must also be prepared to accommodate surges of patients and ICU staffing models should allow for fluctuations in demand. Pre-existing ICU triage and end-of-life care principles should be established, implemented and updated. Daily workflow processes should be restructured to include remote connection with multidisciplinary healthcare workers and frequent communication with relatives. The pandemic has also demonstrated the benefits of digital transformation and the value of remote monitoring technologies, such as wireless monitoring. Finally, the pandemic has highlighted the value of pre-existing epidemiological registries and agile randomized controlled platform trials in generating fast, reliable data. The COVID-19 pandemic is a reminder that besides our duty to care, we are committed to improve. By meeting these challenges today, we will be able to provide better care to future patients.

The Power of Modeling in Emergency Preparedness for COVID-19: A Moonshot Moment for Hospitals.

Before coronavirus disease 2019 (COVID-19), few hospitals had fully tested emergency surge plans. Uncertainty in the timing and degree of surge complicates planning efforts, putting hospitals at risk of being overwhelmed. Many lack access to hospital-specific, data-driven projections of future patient demand to guide operational planning. Our hospital experienced one of the largest surges in New England. We developed statistical models to project hospitalizations during the first wave of the pandemic. We describe how we used these models to meet key planning objectives. To build the models successfully, we emphasize the criticality of having a team that combines data scientists with frontline operational and clinical leadership. While modeling was a cornerstone of our response, models currently available to most hospitals are built outside of their institution and are difficult to translate to their environment for operational planning. Creating data-driven, hospital-specific, and operationally relevant surge targets and activation triggers should be a major objective of all health systems.

The potential effectiveness of the WHO International Health Regulations capacity requirements on control of the COVID-19 pandemic: a cross-sectional study of 114 countries.

OBJECTIVES: We examined if the WHO International Health Regulations (IHR) capacities were associated with better COVID-19 pandemic control. DESIGN: Observational study. SETTING: Population-based study of 114 countries. PARTICIPANTS: General population. MAIN OUTCOME MEASURES: For each country, we extracted: (1) the maximum rate of COVID-19 incidence increase per 100,000 population over any 5-day moving average period since the first 100 confirmed cases; (2) the maximum 14-day cumulative incidence rate since the first case; (3) the incidence and mortality within 30 days since the first case and first COVID-19-related death, respectively. We retrieved the 13 country-specific International Health Regulations capacities and constructed linear regression models to examine whether these capacities were associated with COVID-19 incidence and mortality, controlling for the Human Development Index, Gross Domestic Product, the population density, the Global Health Security index, prior exposure to SARS/MERS and Stringency Index. RESULTS: Countries with higher International Health Regulations score were significantly more likely to have lower incidence (ß coefficient -24, 95% CI -35 to -13) and mortality (ß coefficient -1.7, 95% CI -2.5 to -1.0) per 100,000 population within 30 days since the first COVID-19 diagnosis. A similar association was found for the other incidence outcomes. Analysis using different regression models controlling for various confounders showed a similarly significant association. CONCLUSIONS: The International Health Regulations score was significantly associated with reduction in rate of incidence and mortality of COVID-19. These findings inform design of pandemic control strategies, and validated the International Health Regulations capacities as important metrics for countries that warrant evaluation and improvement of their health security capabilities.

Hospital bed capacity and usage across secondary healthcare providers in England during the first wave of the COVID-19 pandemic: a descriptive analysis.

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.

The J-IDEA Pandemic Planner: A Framework for Implementing Hospital Provision Interventions During the COVID-19 Pandemic.

BACKGROUND: Planning for extreme surges in demand for hospital care of patients requiring urgent life-saving treatment for coronavirus disease 2019 (COVID-19), while retaining capacity for other emergency conditions, is one of the most challenging tasks faced by health care providers and policymakers during the pandemic. Health systems must be well-prepared to cope with large and sudden changes in demand by implementing interventions to ensure adequate access to care. We developed the first planning tool for the COVID-19 pandemic to account for how hospital provision interventions (such as cancelling elective surgery, setting up field hospitals, or hiring retired staff) will affect the capacity of hospitals to provide life-saving care. METHODS: We conducted a review of interventions implemented or considered in 12 European countries in March to April 2020, an evaluation of their impact on capacity, and a review of key parameters in the care of COVID-19 patients. This information was used to develop a planner capable of estimating the impact of specific interventions on doctors, nurses, beds, and respiratory support equipment. We applied this to a scenario-based case study of 1 intervention, the set-up of field hospitals in England, under varying levels of COVID-19 patients. RESULTS: The Abdul Latif Jameel Institute for Disease and Emergency Analytics pandemic planner is a hospital planning tool that allows hospital administrators, policymakers, and other decision-makers to calculate the amount of capacity in terms of beds, staff, and crucial medical equipment obtained by implementing the interventions. Flexible assumptions on baseline capacity, the number of hospitalizations, staff-to-beds ratios, and staff absences due to COVID-19 make the planner adaptable to multiple settings. The results of the case study show that while field hospitals alleviate the burden on the number of beds available, this intervention is futile unless the deficit of critical care nurses is addressed first. DISCUSSION: The tool supports decision-makers in delivering a fast and effective response to the pandemic. The unique contribution of the planner is that it allows users to compare the impact of interventions that change some or all inputs.

Estimating the COVID-19 epidemic trajectory and hospital capacity requirements in South West England: a mathematical modelling framework.

OBJECTIVES: To develop a regional model of COVID-19 dynamics for use in estimating the number of infections, deaths and required acute and intensive care (IC) beds using the South West England (SW) as an example case. DESIGN: Open-source age-structured variant of a susceptible-exposed-infectious-recovered compartmental mathematical model. Latin hypercube sampling and maximum likelihood estimation were used to calibrate to cumulative cases and cumulative deaths. SETTING: SW at a time considered early in the pandemic, where National Health Service authorities required evidence to guide localised planning and support decision-making. PARTICIPANTS: Publicly available data on patients with COVID-19. PRIMARY AND SECONDARY OUTCOME MEASURES: The expected numbers of infected cases, deaths due to COVID-19 infection, patient occupancy of acute and IC beds and the reproduction ('R') number over time. RESULTS: SW model projections indicate that, as of 11 May 2020 (when 'lockdown' measures were eased), 5793 (95% credible interval (CrI) 2003 to 12 051) individuals were still infectious (0.10% of the total SW population, 95% CrI 0.04% to 0.22%), and a total of 189 048 (95% CrI 141 580 to 277 955) had been infected with the virus (either asymptomatically or symptomatically), but recovered, which is 3.4% (95% CrI 2.5% to 5.0%) of the SW population. The total number of patients in acute and IC beds in the SW on 11 May 2020 was predicted to be 701 (95% CrI 169 to 1543) and 110 (95% CrI 8 to 464), respectively. The R value in SW was predicted to be 2.6 (95% CrI 2.0 to 3.2) prior to any interventions, with social distancing reducing this to 2.3 (95% CrI 1.8 to 2.9) and lockdown/school closures further reducing the R value to 0.6 (95% CrI 0.5 to 0.7). CONCLUSIONS: The developed model has proved a valuable asset for regional healthcare services. The model will be used further in the SW as the pandemic evolves, and-as open-source software-is portable to healthcare systems in other geographies.

Population Health Strategies to Support Hospital and Intensive Care Unit Resiliency During the COVID-19 Pandemic: The Italian Experience.

Italy was one of the countries most affected by the number of people infected and dead during the first COVID-19 wave. The authors describe the rapid rollout of a population health clinical and organizational response in preparedness and capabilities to support the first wave of the COVID-19 pandemic in the Italian province of Modena. The authors review the processes, the challenges faced, and describe how excess demand for hospital services was successfully mitigated and thus overwhelming the healthcare services avoided the collapse of the local health care system. An analysis of bed occupancy in the region predicted during the first weeks of the epidemic. The SEIR model estimated the number of infected people under different containment measures. Community resources were mobilized to reduce provincial hospitals' burden of care. A population health approach, based on a radical reorganization of the workflow and emergency patient management, was implemented. The bed saturation of the Modena Healthcare Agency was measured by an ad hoc, newly implemented intensive care unit (ICU) bed occupancy and COVID-19 centralized governance dashboard. ICU bed occupancy increased by 114%, avoiding saturation of the Modena Healthcare Agency system. The Emilia-Romagna region achieved a higher rate of ICU bed availability at 2.15 ICU beds per 10,000 inhabitants as compared with community 1 ICU bed availability prior to the pandemic. Rapid and radical local reorganization of regional efforts helped inform the successful development and implementation of strategic choices within the hospital and the community to prevent the saturation of key facilities.

Ramping Up a Pediatric Hospital Medicine Advanced Practice Provider Team Rapidly.

Pediatric Hospital Medicine (PHM) is a growing subspecialty with a broad scope. The Covid-19 pandemic demands flexible staffing models. Advanced practice providers (APPs) can be a valuable addition to hospital medicine teams, although there is no established training program for APPs within PHM. The authors' purpose is to describe how one institution rapidly established a PHM APP team by collaborating with experienced APPs working in other areas of the hospital. This APP team cared for 16% of the average daily census during the pilot period with no significant difference in length of stay compared to traditional teams.

Estimated Impact of Public and Private Sector COVID-19 Diagnostics and Treatments on US Healthcare Resource Utilization.

INTRODUCTION: Coronavirus disease 2019 (COVID-19) has imposed a considerable burden on the United States (US) health system, with particular concern over healthcare capacity constraints. METHODS: We modeled the impact of public and private sector contributions to developing diagnostic testing and treatments on COVID-19-related healthcare resource use. RESULTS: We estimated that public sector contributions led to at least 30% reductions in COVID-19-related healthcare resource utilization. Private sector contributions to expanded diagnostic testing and treatments led to further reductions in mortality (- 44%), intensive care unit (ICU) and non-ICU hospital beds (- 30% and - 28%, respectively), and ventilator use (- 29%). The combination of lower diagnostic test sensitivity and proportions of patients self-isolating may exacerbate case numbers, and policies that encourage self-isolating should be considered. CONCLUSION: While mechanisms exist to facilitate research, development, and patient access to diagnostic testing, future policies should focus on ensuring equitable patient access to both diagnostic testing and treatments that, in turn, will alleviate COVID-19-related resource constraints.

Cancellation of Elective Surgery and Intensive Care Unit Capacity in New York State: A Retrospective Cohort Analysis.

BACKGROUND: In response to the coronavirus disease 2019 (COVID-19) pandemic, New York State ordered the suspension of all elective surgeries to increase intensive care unit (ICU) bed capacity. Yet the potential impact of suspending elective surgery on ICU bed capacity is unclear. METHODS: We retrospectively reviewed 5 years of New York State data on ICU usage. Descriptions of ICU utilization and mechanical ventilation were stratified by admission type (elective surgery, emergent/urgent/trauma surgery, and medical admissions) and by geographic location (New York metropolitan region versus the rest of New York State). Data are presented as absolute numbers and percentages and all adult and pediatric ICU patients were included. RESULTS: Overall, ICU admissions in New York State were seen in 10.1% of all hospitalizations (n = 1,232,986/n = 12,251,617) and remained stable over a 5-year period from 2011 to 2015. Among n = 1,232,986 ICU stays, sources of ICU admission included elective surgery (13.4%, n = 165,365), emergent/urgent admissions/trauma surgery (28.0%, n = 345,094), and medical admissions (58.6%, n = 722,527). Ventilator utilization was seen in 26.3% (n = 323,789/n = 1232,986) of all ICU patients of which 6.4% (n = 20,652), 32.8% (n = 106,186), and 60.8% (n = 196,951) was for patients from elective, emergent, and medical admissions, respectively. New York City holds the majority of ICU bed capacity (70.0%; n = 2496/n = 3566) in New York State. CONCLUSIONS: Patients undergoing elective surgery comprised a small fraction of ICU bed and mechanical ventilation use in New York State. Suspension of elective surgeries in response to the COVID-19 pandemic may thus have a minor impact on ICU capacity when compared to other sources of ICU admission such as emergent/urgent admissions/trauma surgery and medical admissions. More study is needed to better understand how best to maximize ICU capacity for pandemics requiring heavy use of critical care resources.