Hospital Medical Surge Capacity Assessment and Planning Tools for Disaster Response: A Systematic Review and Meta-analysis.

BackgroundAdequate and effective emergency preparedness for hospital surge capacity is a prerequisite to ensuring standard healthcare services for disaster victims. This study aimed to identify, review, and synthesize the preparedness activities for and the barriers to hospital surge capacity in disasters and emergencies. MethodsWe systematically searched seven databases (PubMed, MEDLINE, CINAHL, Scopus, Embase, Ovid, and PsycINFO). We included all English peer-reviewed studies published in January 2016 and July 2022 on surge capacity preparedness in hospital settings. Two independent researchers screened titles and abstracts, reviewed the full texts, and conducted data extractions using CADIMA software. We assessed the rigor of the included studies using the NIH quality assessment tools for quantitative studies, the Noyes et al. guidelines for qualitative studies, and the MMAT tool for mixed methods studies and summarized findings using the narrative synthesis method. We also used PRISMA reporting guidelines. ResultsFrom the 2560 studies identified, we finally include 13 peer-reviewed studies: 10 quantitative, one qualitative, and two mixed methods. Five studies were done in the USA, three in Iran (n = 3), and the remaining in Australia, Pakistan, Sweden, Taiwan, and Tanzania. The study identified various ways to increase hospital surge capacity preparedness in all four domains (staff, stuff, space, and system); among them, the use of the Hospital Medical Surge Preparedness Index and the Surge Simulation Tool for surge planning was noteworthy. Moreover, nine studies (69%) recognized several barriers to hospital surge capacity preparedness. ConclusionThe review provides synthesized evidence of contemporary literature on strategies for and barriers to hospital surge capacity preparedness. Despite the risk of selection bias due to the omission of gray literature, the study findings could help hospital authorities, public health workers, and policymakers to develop effective plans and programs for improving hospital surge capacity preparedness with actions, such as enhancing coordination, new or adapted flows of patients, disaster planning implementation, or the development of specific tools for surge capacity. Systematic review registrationPROSPERO CRD42022360332.

IntroductionThe COVID-19 pandemic will test the capacity of health systems worldwide and especially so in low- and middle-income countries. The objective of this study was to assess the surge capacity of the Kenyan of the Kenyan health system in terms of general hospital and ICU beds in the face of the COVID-19 pandemic.MethodsWe assumed that 2% of the Kenyan population get symptomatic infection by SARS-Cov-2 based on modelled estimates for Kenya and determined the health system surge capacity for COVID-19 under three transmission curve scenarios, 6, 12, and 18 months. We estimated four measures of hospital surge capacity namely: 1) hospital bed surge capacity 2) ICU bed surge capacity 3) Hospital bed tipping point, and 5) ICU bed tipping point. We computed this nationally and for all the 47 county governments.ResultsThe capacity of Kenyan hospitals to absorb increases in caseload due to COVID-19 is constrained by the availability of oxygen, with only 58% of hospital beds in hospitals with oxygen supply. There is substantial variation in hospital bed surge capacity across counties. For example, under the 6 months transmission scenario, the percentage of available general hospital beds that would be taken up by COVID-19 cases varied from 12% Tharaka Nithi county, to 145% in Trans Nzoia county. Kenya faces substantial gaps in ICU beds and ventilator capacity. Only 22 out of the 47 counties have at least 1 ICU unit. Kenya will need an additional 1,511 ICU beds and 1,609 ventilators (6 months transmission curve) to 374 ICU beds and 472 ventilators (18 months transmission curve) to absorb caseloads due to COVID-19.ConclusionSignificant gaps exist in Kenya’s capacity for hospitals to accommodate a potential surge in caseload due to COVID-19. Alongside efforts to slow and supress the transmission of the infection, the Kenyan government will need to implement adaptive measures and additional investments to expand the hospital surge capacity for COVID-19. Additional investments will however need to be strategically prioritized to focus on strengthening essential services first, such as oxygen availability before higher cost investments such as ICU beds and ventilators.

The National Center for the Study of Preparedness and Catastrophic Event Response (PACER) has created a publicly available simulation tool called Surge (accessible at http://www.pacerapps.org) to estimate surge capacity for user-defined hospitals. Based on user input, a Monte Carlo simulation algorithm forecasts available hospital bed capacity over a 7-day period and iteratively assesses the ability to accommodate disaster patients. Currently, the tool can simulate bed capacity for acute mass casualty events (such as explosions) only and does not specifically simulate staff and supply inventory. Strategies to expand hospital capacity, such as (1) opening unlicensed beds, (2) canceling elective admissions, and (3) implementing reverse triage, can be interactively evaluated. In the present application of the tool, various response strategies were systematically investigated for 3 nationally representative hospital settings (large urban, midsize community, small rural). The simulation experiments estimated baseline surge capacity between 7% (large hospitals) and 22% (small hospitals) of staffed beds. Combining all response strategies simulated surge capacity between 30% and 40% of staffed beds. Response strategies were more impactful in the large urban hospital simulation owing to higher baseline occupancy and greater proportion of elective admissions. The publicly available Surge tool enables proactive assessment of hospital surge capacity to support improved decision-making for disaster response. (Disaster Med Public Health Preparedness. 2018;12:513-522).

Methods of defining hospital disaster preparedness are poorly defined in the literature, leaving wide discrepancies between a hospital's self-reported preparedness and that assessed by an objective reviewer. This study compared self-reported surge capacity data from individual hospitals, obtained from a previously reported long-distance tabletop drill (LDTT) prior to the 2010 FIFA World Cup tournament in Cape Town, South Africa, with surge capacity data assessed by an on-site survey inspection team. In this prospective, observational study, contact persons used in the prior LDTT assessing hospital disaster preparedness in the lead-up to the 2010 FIFA World Cup made surge capacity assessments (licensed bed capacity plus surge capacity beds) for the respiratory intensive care unit (RICU), neonatal intensive care unit (NICU), medical intensive care unit (MICU), and general medical/surgical beds in each hospital. Following the 2010 World Cup, this data was then re-evaluated by an on-site survey team consisting of two of the authors. The contact persons for the individual hospitals from the LDTT underreported their individual hospital's surge capacity in 86% (95% CI, 46%-99%) of RICU beds; 100% (95% CI, 63%-100%) of MICU beds; 75% (95% CI, 40%-94%) of NICU beds; and 71% (95% CI, 35%-92%) of medical/surgical beds compared with the on-site inspection team. The contact persons for the LDTT overwhelmingly underreported surge capacity beds compared with the surge capacity determined by the on-site inspection team.

Introduction: The Emergo Train System (ETS) is a critical simulation tool widely used to train healthcare professionals for emergency and disaster scenarios. However, traditional ETS applications focus on prehospital mass-casualty events and surge capacity in the acute chain, excluding in-hospital ward dynamics. Here, a specialized patient bank tailored to in-hospital patients enables hospitals to simulate daily operational challenges such as patient surge and, in case of hospital emergency training, evacuation processes. Methods: The patient bank was developed using a structured workflow, which involved defining patient profiles and integrating diverse healthcare needs that reflect the complexities of in-hospital scenarios. The patients in this bank span various medical needs encountered in daily hospital operations, facilitating realistic training in patient management and interdepartmental coordination. The patient bank was pilot tested in exercises at three hospitals to assess its applicability and effectiveness in simulating daily hospital activities and surge capacity. Data were collected through exercise instructor feedback as well as observational analysis to refine patient scenarios and enhance realism. Results: The exercises demonstrated the versatility of the ETS patient bank in simulating real-time hospital operations. Instructors reported a dynamic training experience, highlighting that the bank could be used to improve preparedness for managing in-hospital surge capacity and evacuation processes. Feedback indicated that the simulated scenarios closely resembled daily hospital workflows, enhancing the perceived relevance and practical application of the training. Conclusion: This specialized ETS patient bank addresses a significant gap in hospital preparedness training, providing an innovative tool to simulate routine in-hospital activities and crisis responses. This in-hospital patient bank represents a valuable expansion of ETS, broadening its utility beyond disaster scenarios to hospital preparedness. The successful implementation across multiple hospitals exercises suggests its potential for wider adoption, providing an impactful resource for training healthcare personnel in both routine and crisis settings.

Both HACSC and HACST were computed for individual hospitals. These were compared to surge capacities declared by individual hospitals during EXPO 2015, and also to surge capacity evaluated during a simulation organized on August 23, 2016. Both HACSC and HACST were smaller compared to capacities measured and reported by the hospitals, as well as those found during the simulation. This resulted in significant differences in THC when this was computed from the different methods of calculation. Surge capacity is dependent on the method of measurement. Each method has its inherent deficiencies. Until more reliable methodologies are developed, there is a benefit to analyze surge capacity using several methods rather than just one. Emergency committee members should be aware of the importance of critical resources when looking to the hospital capacity to respond to an MCI, and to the possibility to effectively increase it with a good preparedness plan. Since hospital capacity during real events is not static but dynamic, largely depending on occupation of the available resources, it is important that the regional command center and the hospitals receiving casualties constantly communicate on specific agreed upon critical resources, in order for the regional command center to timely evaluate the overall regional capacity and guarantee the appropriate distribution of the patients. FaccincaniR, Della CorteF, SesanaG, StucchiR, WeinsteinE, AshkenaziI, IngrassiaP. Hospital surge capacity during Expo 2015 in Milano, Italy. Prehosp Disaster Med. 2018;33(5):459-465.

Surge capacity is a fundamental and critical approach to hospital preparedness. To successfully survive a typically unexpected situation, a well-developed disaster plan is essential. The aim of this review paper was to provide current evidence of the use of the hospital preparedness approach in managing emergencies and disasters. Between January 2014 and June 2024, a comprehensive search of published articles in English via EBSCO, CINAHL, Google Scholar, PubMed, and MEDLINE was conducted. The search included both quantitative and qualitative studies. In total, 44 articles were relevant to the review. All the identified relevant papers were reviewed to determine the studies related to this review. Two subtopics were identified: hospital preparedness and surge capacity. The findings of the reviewed studies provide an exciting opportunity to advance our knowledge of hospital preparedness and surge capacity. It is integral to healthcare system programs, particularly in disaster-prone areas, to manage the state of chaos effectively and control morbidity and mortality rates. Nurses, recognized as experts in planning and coordinating patient care, assume a primary role in disaster planning efforts. Understanding the concept of surge capacity, it becomes clearer that nurses and nurse managers play a crucial role in enhancing emergency preparedness plans.

During severe influenza pandemics, healthcare demand often exceeds clinical capacity for routine care. This systematic study examined secondary and tertiary hospital surge capacity interventions and outcomes during the H1N1 pandemic. We searched seven databases for original research on hospital, acute, secondary, and tertiary patient safety outcomes during the 2009–2020 influenza pandemic. A descriptive narrative synthesis assessed influenza-related data. We used the JBI Critical Appraisal Checklist for Cross-Sectional Studies to evaluate each study's methodology. The study found hospitals use various methods to manage their workforce during an influenza pandemic. All hospitals' surge capacity plans modified staff, resources, structure, and system which contributed to improve patient safety, patient and family satisfaction, fewer adverse events, shorter wait times, and better patient flow. Surge capacity strategies improved patient safety by influencing variables such as adverse events, patient and family satisfaction, wait times, and the number of patients who left without being seen. The findings highlight the significance of incorporating surge capacity strategies into healthcare pandemic planning. However, more research in a variety of settings and countries is required to strengthen the evidence base.

Background: Hospital surge capacity (HSC) is dependent on the ability to increase or conserve resources. The hospital surge model put forth by the Agency for Healthcare Research and Quality (AHRQ) estimates the resources needed by hospitals to treat casualties resulting from 13 national planning scenarios. However, emergency planners need to know which hospital resource are most critical in order to develop a more accurate plan for HSC in the event of a disaster.Objective: To identify critical hospital resources required in four specific catastrophic scenarios; namely, pandemic influenza, radiation, explosive, and nerve gas.Methods: We convened an expert consensus panel comprised of 23 participants representing health providers (i.e., nurses and physicians), administrators, emergency planners, and specialists. Four disaster scenarios were examined by the panel. Participants were divided into 4 groups of five or six members, each of which were assigned two of four scenarios. They were asked to consider 132 hospital patient care resources- extracted from the AHRQ's hospital surge model- in order to identify the ones that would be critical in their opinion to patient care. The definition for a critical hospital resource was the following: absence of the resource is likely to have a major impact on patient outcomes, i.e., high likelihood of untoward event, possibly death. For items with any disagreement in ranking, we conducted a facilitated discussion (modified Delphi technique) until consensus was reached, which was defined as more than 50% agreement. Intraclass Correlation Coefficients (ICC) were calculated for each scenario, and across all scenarios as a measure of participant agreement on critical resources. For the critical resources common to all scenarios, Kruskal-Wallis test was performed to measure the distribution of scores across all scenarios.Results: Of the 132 hospital resources, 25 were considered critical for all four scenarios by more than 50% of the participants. The number of hospital resources considered to be critical by consensus varied from one scenario to another; 58 for the pandemic influenza scenario, 51 for radiation exposure, 41 for explosives, and 35 for nerve gas scenario. Intravenous crystalloid solution was the only resource ranked by all participants as critical across all scenarios. The agreement in ranking was strong in nerve agent and pandemic influenza (ICC= 0.7 in both), and moderate in explosives (ICC= 0.6) and radiation (ICC= 0.5).Conclusion: In four disaster scenarios, namely, radiation, pandemic influenza, explosives, and nerve gas scenarios; supply of as few as 25 common resources may be considered critical to hospital surge capacity. The absence of any these resources may compromise patient care. More studies are needed to identify critical hospital resources in other disaster scenarios.

Surge capacity is the ability to manage sudden patient influxes beyond routine levels and can be evaluated using the 4S Framework: staff, stuff, system, and space. While low-resource settings like Rwanda face frequent mass casualty incidents (MCIs), most surge capacity research comes from high-resource settings and lacks generalisability. This study assessed Rwanda’s hospital surge capacity using a cross-sectional survey of emergency and surgical departments in all referral hospitals. Descriptive statistics, t-tests, Fisher’s exact test, ANOVA, and linear mixed-model regression were used to analyze responses. Of the 39 invited participants, 32 (82%) responded. On average, respondents believed that they could manage 13 MCI patients (95% CI: 10–16) while maintaining routine care, with significant differences between tertiary and secondary hospitals (11 vs. 22; p = 0.016). The intra-class correlation was poor for most variables except for CT availability and ICU beds. Surge capacity perception did not vary significantly by professional category, though less senior staff reported higher capacity. Significantly higher capacity was reported by those with continuous access to imaging (p < 0.01). Despite limited resources, Rwandan hospitals appear able to manage small to moderate MCIs. For larger incidents, patient distribution across facilities is recommended, with critical cases prioritized for tertiary hospitals.

High-consequence surge research involves a systems approach that includes elements such as healthcare facilities, out-of-hospital systems, mortuary services, public health, and sheltering. This article focuses on one aspect of this research, hospital surge capacity, and discusses a definition for such capacity, its components, and future considerations. While conceptual definitions of surge capacity exist, evidence-based practical guidelines for hospitals require enhancement. The Health Resources and Services Administration's (HRSA) definition and benchmarks are extrapolated from those of other countries and rely mainly on trauma data. The most significant part of the HRSA target, the need to care for 500 victims stricken with an infectious disease per one million population in 24 hours, was not developed using a biological model. If HRSA's recommendation is applied to a sample metropolitan area such as Orange County, California, this translates to a goal of expanding hospital capacity by 20%–25% in the first 24 hours. Literature supporting this target is largely consensus based or anecdotal. There are no current objective measures defining hospital surge capacity. The literature identifying the components of surge capacity is fairly consistent and lists them as personnel, supplies and equipment, facilities, and a management system. Studies identifying strategies for hospitals to enhance these components and estimates of how long it will take are lacking. One system for augmenting hospital staff, the Emergency System for Advance Registration of Volunteer Health Professionals, is a consensus-derived plan that has never been tested. Future challenges include developing strategies to handle the two different types of high-consequence surge events: 1) a focal, time-limited event (such as an earthquake) where outside resources exist and can be mobilized to assist those in need and 2) a widespread, prolonged event (such as pandemic influenza) where all resources will be in use and rationing or triage is needed.

Hospital surge capacity in multiple casualty events (MCE) is the core of hospital medical response, and an integral part of the total medical capacity of the community affected. To date, however, there has been no consensus regarding the definition or quantification of hospital surge capacity. The first objective of this study was to quantitatively benchmark the various components of hospital surge capacity pertaining to the care of critically and moderately injured patients in trauma-related MCE. The second objective was to illustrate the applications of those quantitative parameters in local, regional, national, and international disaster planning; in the distribution of patients to various hospitals by prehospital medical services; and in the decision-making process for ambulance diversion. A 2-step approach was adopted in the methodology of this study. First, an extensive literature search was performed, followed by mathematical modeling. Quantitative studies on hospital surge capacity for trauma injuries were used as the framework for our model. The North Atlantic Treaty Organization triage categories (T1-T4) were used in the modeling process for simplicity purposes. Hospital Acute Care Surge Capacity (HACSC) was defined as the maximum number of critical (T1) and moderate (T2) casualties a hospital can adequately care for per hour, after recruiting all possible additional medical assets. HACSC was modeled to be equal to the number of emergency department beds (#EDB), divided by the emergency department time (EDT); HACSC = #EDB/EDT. In trauma-related MCE, the EDT was quantitatively benchmarked to be 2.5 (hours). Because most of the critical and moderate casualties arrive at hospitals within a 6-hour period requiring admission (by definition), the hospital bed surge capacity must match the HACSC at 6 hours to ensure coordinated care, and it was mathematically benchmarked to be 18% of the staffed hospital bed capacity. Defining and quantitatively benchmarking the different components of hospital surge capacity is vital to hospital preparedness in MCE. Prospective studies of our mathematical model are needed to verify its applicability, generalizability, and validity.

High-consequence surge research involves a systems approach that includes elements such as healthcare facilities, out-of-hospital systems, mortuary services, public health, and sheltering. This article focuses on one aspect of this research, hospital surge capacity, and discusses a definition for such capacity, its components, and future considerations. While conceptual definitions of surge capacity exist, evidence-based practical guidelines for hospitals require enhancement. The Health Resources and Services Administration's (HRSA) definition and benchmarks are extrapolated from those of other countries and rely mainly on trauma data. The most significant part of the HRSA target, the need to care for 500 victims stricken with an infectious disease per one million population in 24 hours, was not developed using a biological model. If HRSA's recommendation is applied to a sample metropolitan area such as Orange County, California, this translates to a goal of expanding hospital capacity by 20%-25% in the first 24 hours. Literature supporting this target is largely consensus based or anecdotal. There are no current objective measures defining hospital surge capacity. The literature identifying the components of surge capacity is fairly consistent and lists them as personnel, supplies and equipment, facilities, and a management system. Studies identifying strategies for hospitals to enhance these components and estimates of how long it will take are lacking. One system for augmenting hospital staff, the Emergency System for Advance Registration of Volunteer Health Professionals, is a consensus-derived plan that has never been tested. Future challenges include developing strategies to handle the two different types of high-consequence surge events: 1) a focal, time-limited event (such as an earthquake) where outside resources exist and can be mobilized to assist those in need and 2) a widespread, prolonged event (such as pandemic influenza) where all resources will be in use and rationing or triage is needed.

The congressionally authorized National Disaster Medical System Pilot Program was created in December 2019 to strengthen the medical surge capability, capacity, and interoperability of affiliated healthcare facilities in 5 regions across the United States. The COVID-19 pandemic provided an unprecedented opportunity to learn how participating healthcare facilities handled medical surge events during an active public health emergency. We applied a modified version of the Barbisch and Koenig 4-S framework (staff, stuff, space, systems) to analyze COVID-19 surge management practices implemented by healthcare stakeholders at 5 pilot sites. In total, 32 notable practices were identified to increase surge capacity during the COVID-19 pandemic that have potential applications for other healthcare facilities. We found that systems was the most prevalent domain of surge capacity among the identified practices. Systems and staff were discussed across all 5 pilot sites and were the 2 domains co-occurring most often within each surge management practice. These results can inform strategies for scaling up and optimizing medical surge capability, capacity, and interoperability of healthcare facilities nationwide. This study also specifies areas of surge capacity worthy of strategic focus in the pilot's planning and implementation efforts while more broadly informing the US healthcare system's response to future large-scale, medical surge events.

Background: The basic step in planning and policy-making for hospital surge capacity in disasters is the awareness of the current situation and problems. This issue is of greater importance in hospitals of developing countries that usually face many problems in ordinary situations; this paper aimed at identifying the status of hospitals in a developing country for surge capacity and the associated challenges at the time of disasters, and strategies to solve them. Methods: In this qualitative study, semi-structured interviews were conducted with 27 participants, who were mostly officials of hospitals and the authorities of the ministry of health in Iran. Thematic analysis was used for analyzing the data. Results: In this study, 40 subthemes and 12 themes under 4 main categories, including space, medication/supplies, manpower, and functional structures/plans, were identified. Some of these themes included shortage of space inside the structures, weakness in providing medication/emergency medical supplies, general shortage of manpower, weakness in maintaining and recalling staff at the time of hospital surge capacity in disasters, content defect in hospitals disaster preparedness plan, and weakness in training for disasters Conclusions: Generally, there are various challenges hospital surge capacity at the time of disasters, and hospitals are disadvantaged in this regard. However, implementing strategies recognized in this study may help resolve these challenges.