Surge capacity and capability of intensive care units across a large healthcare system: An operational blueprint for regional integration.

OBJECTIVE: Many hospitals were unprepared for the surge of patients associated with the spread of coronavirus disease 2019 (COVID-19) pandemic. We describe the processes to develop and implement a surge plan framework for resource allocation, staffing, and standardized management in response to the COVID-19 pandemic across a large integrated regional healthcare system. SETTING: A large academic medical center in the Cleveland metropolitan area, with a network of 10 regional hospitals throughout Northeastern Ohio with a daily capacity of more than 500 intensive care unit (ICU) beds. RESULTS: At the beginning of the pandemic, an equitable delivery of healthcare services across the healthcare system was developed. This distribution of resources was implemented with the potential needs and resources of the individual ICUs in mind, and epidemiologic predictions of virus transmissibility. We describe the processes to develop and implement a surge plan framework for resource allocation, staffing, and standardized management in response to the COVID-19 pandemic across a large integrated regional healthcare system. We also describe an additional level of surge capacity, which is available to well-integrated institutions called "extension of capacity." This refers to the ability to immediately have access to the beds and resources within a hospital system with minimal administrative burden. CONCLUSIONS: Large integrated hospital systems may have an advantage over individual hospitals because they can shift supplies among regional partners, which may lead to faster mobilization of resources, rather than depending on local and national governments. The pandemic response of our healthcare system highlights these benefits.

Ten minutes with Hassan Khouli, chair of Department of Critical Care Medicine, Respiratory Institute, Cleveland Clinic

Dr Khouli has special expertise in the evaluation and management of patients with complex critical illnesses including sepsis and septic shock, ARDS, multiorgan failure and decision-making at the end of life. Dr Khouli leads the Enterprise-Wide Department of Critical Care Medicine at the Cleveland Clinic that oversees 12 adult ICUs at eight hospitals including Main Campus and seven regional hospitals with over 170 ICU beds. First and foremost, are there any key leadership messages you want to get out to our readership? During the COVID-19 era, we as leaders have been focusing on protecting our vulnerable caregivers and teams from exposure to the COVID-19 virus and supporting their mental health and well-being as one of the most important priorities, while we aim continue to provide the best care for our patients.

An Algorithm for Classifying Patients Most Likely to Develop Severe Coronavirus Disease 2019 Illness.

OBJECTIVES: To develop an algorithm that predicts an individualized risk of severe coronavirus disease 2019 illness (i.e., ICU admission or death) upon testing positive for coronavirus disease 2019. DESIGN: A retrospective cohort study. SETTING: Cleveland Clinic Health System. PATIENTS: Those hospitalized with coronavirus disease 2019 between March 8, 2020, and July 13, 2020. INTERVENTIONS: A temporal coronavirus disease 2019 test positive cut point of June 1 was used to separate the development from validation cohorts. Fine and Gray competing risk regression modeling was performed. MEASUREMENTS AND MAIN RESULTS: The development set contained 4,520 patients who tested positive for coronavirus disease 2019 between March 8, 2020, and May 31, 2020. The validation set contained 3,150 patients who tested positive between June 1 and July 13. Approximately 9% of patients were admitted to the ICU or died of coronavirus disease 2019 within 2 weeks of testing positive. A prediction cut point of 15% was proposed. Those who exceed the cutoff have a 21% chance of future severe coronavirus disease 2019, whereas those who do not have a 96% chance of avoiding the severe coronavirus disease 2019. In addition, application of this decision rule identifies 89% of the population at the very low risk of severe coronavirus disease 2019 (< 4%). CONCLUSIONS: We have developed and internally validated an algorithm to assess whether someone is at high risk of admission to the ICU or dying from coronavirus disease 2019, should he or she test positive for coronavirus disease 2019. This risk should be a factor in determining resource allocation, protection from less safe working conditions, and prioritization for vaccination.

Lessons on Outbreak Preparedness From the Cleveland Clinic.

Disasters, including infectious disease outbreaks, are inevitable. Hospitals need to plan in advance to ensure that their systems can adapt to a rapidly changing environment if necessary. This review provides an overview of 10 general principles that hospitals and health-care systems should consider when developing disaster plans. The principles are consistent with an "all-hazards" approach to disaster mitigation. This approach is adapted to planning for a multiplicity of threats but emphasizes highly relevant scenarios, such as the coronavirus disease 2019 pandemic. We also describe specific ways these principles helped prepare our hospital for this pandemic. Key points include acting quickly, identifying and engaging key stakeholders early, providing accurate information, prioritizing employee safety and mental health, promoting a fully integrated clinical response, developing surge plans, preparing for ethical dilemmas, and having a cogent exit strategy for post-disaster recovery.