EDMG541Wk3

Version 2. PLoS Curr. 2013 October 7 [revised 2013 October 7]; 5: ecurrents.dis.67c1afe8d78ac2ab0ea52319eb119688. Published online 2013 October 7. doi: 10.1371/currents.dis.67c1afe8d78ac2ab0ea52319eb119688:

10.1371/currents.dis.67c1afe8d78ac2ab0ea52319eb119688

PMCID: PMC3805833 PMID: 24162793

Critical Resources for Hospital Surge Capacity: An Expert Consensus Panel

Jamil D. Bayram, Lauren M. Sauer, Christina Catlett, Scott Levin, Gai Cole, Thomas D. Kirsch, Matthew Toerper, and Gabor Kelen

Jamil D. Bayram, Department of Emergency Medicine, School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA; Johns Hopkins Office of Critical Event Preparedness and Response, Baltimore, Maryland, USA; Center for Refugee and Disaster Response, Bloomberg School of Public Health, Johns Hopkins

University, Baltimore, Maryland, USA; Contributor Information.

This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.

Abstract

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 speci�ic catastrophic scenarios; namely, pandemic in�luenza, radiation, explosive, and nerve gas. Methods: We convened an ex- pert consensus panel comprised of 23 participants representing health providers (i.e., nurses and physicians), administrators, emer- gency planners, and specialists. Four disaster scenarios were examined by the panel. Participants were divided into 4 groups of �ive or six members, each of which were assigned two of four scenarios. They were asked to consider 132 hospital patient care re- sources- extracted from the AHRQ's hospital surge model- in order to identify the ones that would be critical in their opinion to pa- tient care. The de�inition 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 (modi�ied Delphi technique) until consensus was reached, which was de�ined as more than 50% agreement.

* *

Intraclass Correlation Coef�icients (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 scenar- ios 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 in�luenza scenario, 51 for radiation exposure, 41 for explosives, and 35 for nerve gas sce- nario. 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 in�luenza (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 in�luenza, 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.

Introduction

Hospital surge capacity is dependent on the ability to increase or conserve resources, in response to an in�lux of patients in a disas- ter situation . Adequate surge capacity depends on the fundamental understanding of which hospital resources are critical to patient care . Surge capacity has four conceptual components, three of which categorize resources; space, staff, and supplies . The fourth key component de�ining surge capacity is the “system” category, which denotes organization, processes, policies and proce- dures that govern and organize the allocation and conservation of the �irst three components.

In 2009, the Agency for Healthcare Research and Quality (AHRQ) developed a Hospital Surge Model that forecasted the hospital re- sources required to treat casualties resulting from 13 National Planning Scenarios . The AHRQ's planning tool was discontinued on June 30, 2011 . The objective of our study was to identify which of the AHRQ hospital resources were the most critical to care for pa- tients in four of the National Planning Scenarios: pandemic in�luenza, radiation event, explosion, and nerve gas attack . This informa- tion is essential for hospital preparedness planners to make supply-chain driven decisions based on the number of patients treated. In addition, we wished to determine which of these critical hospital resources were common across multiple types of events, and dis- tinguish resources that are critical only for speci�ic scenarios.

Methods

We organized and conducted a facilitated national expert consensus panel held during the spring of 2011. Twenty three expert pan- elists from various disciplines in the health care sector (Table 1) took part in a one day consensus-building set of exercises. The ma- jority of the participants were purposefully chosen to be healthcare providers, because the decision of what constitutes critical hos-

1

2 3 , 4 , 5

6

7

6

7

pital resource for patient care, and issues related to standards of care are primarily clinical. However, we did include allied profes- sionals to ensure other perspectives. The study was approved by an Institutional Review Board on Human Subjects Research, and all study participants provided appropriate consent.

Prior to the exercises, the investigators conducted a detailed review of the literature and produced a list of all patient care related re- sources (space, staff, supplies) that may be required for routine use and for speci�ic disaster scenarios based on four of the national planning scenarios chosen for these exercises (pandemic in�luenza scenario, radiation exposure, explosives, and nerve gas). The radia- tion scenario postulates a radiological dispersal device or “dirty bomb” detonated in 3 different sites moderate-to-large cities causing 180 fatalities; 270 injuries; 20,000 detectable contaminations (at each site). The pandemic in�luenza scenario posits a 15% attack rate: 87,000 fatalities; and 300,000 hospitalizations. In the nerve gas scenario, six spray dissemination devices and releases Sarin va- por into the ventilation systems of three large commercial of�ice buildings in a metropolitan area causing 6,000 fatalities (95% of building occupants). In the explosion scenario, improvised explosive devices (IEDs) were detonated a sports arena, an underground public transportation concourse, and in a parking facility near the entertainment complex causing 100 fatalities and 450 hospitalizations.

Participants were provided key background literature, as well as the URL to the original AHRQ model, and a list of the resources to review two weeks prior to the meeting. The �inalized resource list was provided to all participants at a meeting held the evening prior to the day of the exercises. To ensure uniform application of the planned methods the next day, two separate mock exercises (using different national planning scenarios) were conducted at the evening session with the entire group of expert panelists. During that session, participants were also briefed on the logistics of the consensus panel the following day. On the day of the formal exercises, participants were divided into 4 groups of �ive or six members. Each group was assigned two of the four scenarios. , i.e. each of the four scenarios was assigned to two separate groups, in various combinations. Each group had a facilitator to guide the proceedings and discussion. Weeks prior to the study, the PI and the Project Manager chose and trained four experienced facilitators. Panelists in each group were asked to consider 132 hospital patient care resources – extracted from the AHRQ's hospital surge model and the lit- erature – in order to identify the ones that would be critical to patient care. Both pediatric and adult patients were to be considered. The operational de�inition of a "critical" hospital resource was as follows: absence of the resource is likely to have a major impact on pa- tient outcomes, i.e., high likelihood of untoward event, possibly death.

By design, morbidity, mortality and the number of victims for various scenarios have no bearing on the outcomes of interest since the main objective of the study was to determine which speci�ic hospital resources were considered critical to care for patients of all levels of acuity, regardless of the clinical load. In this regard, two major assumptions were communicated to the panelists. First, they were asked to assume that basic hospital/unit operations, such as infrastructure, food, security, housekeeping, laundry, etc., remained intact, and that the hospital building was not degraded structurally in any way. Second, it was assumed that clinical standards of care would be maintained, i.e. panelists were asked to perform the exercise without considering the availability of alternate or compen-

satory resources that did not maintain equivalent standards of care. The PI of the study and the Project Manager continuously ro- tated among panels to clarify de�initions and methods, and to ensure that each panel was adhering to the protocols, but did not es- pouse any particular point of view.

For items with any disagreement in ranking within each group, a facilitated discussion (modi�ied Delphi technique) was conducted until consensus (de�ined as more than 50% agreement) was reached. To help mitigate potential dominance by one or more panel members, rankings by each individual panelist was done separately and in a blinded fashion. Each group was also encouraged to add potential hospital resources not already on the list. Panel members were asked to recuse themselves from exercising an opinion and score on resource items with which they were not familiar.

Analysis

To measure the agreement among all participants on assigning critical resources, intraclass correlation coef�icient (ICC) for every item was calculated individually for each scenario and collectively across all scenarios; Kruskal-Wallis test was performed to measure the distribution of scores for each resource across all scenarios.

Ethics Statement

This work was reviewed and approved by the Johns Hopkins School of Medicine Institutional Board and a waiver of consent was ap- proved and documented by the Program Manager. The waiver was given because the research involves no risk to participants as they were invited to participate and could choose at any time not to attend. They were offering their opinion on a subject they are experts in and all of their opinions and all related data were recorded unidenti�iable and anonymously. By recording their consent, we would be introducing identi�iers.

Results

Of the 132 hospital resources evaluated, 25 were considered critical in all four scenarios by more than 50% of participants (Table 2). There was 90% or more agreement among panelists on 16 of these 25 hospital resources, with agreement ranging from 64.7% to 100%. Crystalloid solution was the only resource that had 100% agreement on being critical, in all four scenarios.

Out of the 132 hospital resources, the number considered critical by more than 50% of participants varied from one scenario to an- other; 58 (44%) for the pandemic in�luenza scenario, 51 (39%) for radiation exposure, 41 (31%) for explosives, and 35 (27%) for nerve gas scenario (Table 3). There were an additional 10 scenario-speci�ic hospital resources considered critical by all participants (100% agreement), that were not considered as generally critical for all scenarios. These 10 resources were distributed as follows: 5

in the pandemic in�luenza scenario (isolation room/cohorting, respiratory therapist, facemasks, antiviral agents for in�luenza, and dialysis); 4 in the radiation scenario (radiation specialist, potassium iodide, Geiger counter, and decontamination capability); 1 in the explosives scenario (standard radiograph), and none speci�ic for nerve agents. There were a number of resources that were speci�ic to a single scenario (Table 3) as follows: pandemic in�luenza (isolation room/cohorting, respiratory therapist, facemasks, antiviral agents for in�luenza, and dialysis); radiation (radiation specialist, potassium iodide, Geiger counter, decontamination capability and isotope chelating agents); explosion (surgeon, packed red blood cells, Silvadene cream, gauze pads, fresh-frozen plasma, enteral feed- ing tubes); and nerve agent (Atropine and 2-PAM).

Agreement on all 132 resources was strong for the pandemic in�luenza (ICC= 0.7, CI: 0.624 to 0.746) and nerve gas scenarios (ICC=0.7, CI:0.636 to 0.753), and moderate for explosives (ICC=0.6, CI: 0.555 to 0.686) and radiation exposure scenarios (ICC=0.5, CI: 0.435 to 0.588). In general, there was similarity in the distribution (i.e. no signi�icant difference; p>0.05) of the identi�ied 25 critical hospital resources across all four scenarios (Table 2), with the exception of resources: sedatives (p=0.031), vasopressors (p=0.036), and non-sterile latex-free gloves (p=0.028).

Discussion

In the face of natural and man-made disasters, hospitals are at the forefront providing medical care for patients at all levels of acuity. While there has been considerable work related to surge capacity

, and national recommendations to itemize critical healthcare resources , detailed ac- counting of individual hospital resources that are critical for response to speci�ic types of disasters is lacking. Hospital administrators and disaster managers must identify the critical medical resources in all likely scenarios, and design robust storage and supply-chain protocols to maintain adequate supplies of these resources.

In 2009, Hick et al. categorized surge capacity according to three levels of graded response: “conventional,” “contingent,” or “crisis” level management. [2] A conventional response implies that routinely available resources can address the requirements imposed by the event, and standards of care can be maintained. Contingent response requires mobilization of additional measures to those rou- tinely in place, while standards of care are essentially maintained. Crisis response requires considerable alteration in routine opera- tions and available measures to meet the patient surge requirements, and standards of care cannot be maintained. We believe our study builds upon the model proposed by Hick et al., by identifying resources considered critical within the boundaries of conven- tional and contingency surge capacities.

The 25 resources identi�ied as critical – by consensus – for all 4 scenarios (pandemic in�luenza, radiation, explosives, and nerve agents) cover the three categories of hospital surge capacity resources; supplies (18), space (4), and staff (3). In the supplies cate- gory, intravenous crystalloid solution was the only resource unanimously ranked by participants as critical in all 4 scenarios. The ra-

1 , 2 , 3 , 4 , 5 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 ,

24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 35

tionale behind this categorization may be related to the ubiquitous use of crystalloid solutions in acute medical conditions resulting from various disaster scenarios. Other common supplies with consensus as being “critical,” include intubation equipment, ventilators, oxygen, sedatives, IV catheters, needles, gloves, and blood pressure cuffs. As expected, some resources are highly speci�ic and critical for response to a certain event. For example, for a disaster with radiation exposure, potassium iodide and a radiation expert were considered critical by 100% of the participants. In the space category, adult and pediatric intensive care and medical/surgical beds were identi�ied as critical resources for all four scenarios. These represent the main physical areas accommodating critical and mod- erately injured patients requiring admission. In the staff category, critical care physicians and nurses, in addition to non-critical care nurses, were considered critical across all scenarios. Interestingly, non-critical care physicians (e.g. internal medicine physicians) were considered critical by less than 50% of panelists in all four study scenarios. We note that our study panelists placed emphasis on specialized care in disaster response. This is understandable given the orientation of health care practice in the U.S., even during disasters. However, in many countries, primary care resources may play a larger role and would likely be judged as reaching critical hospital resource status in many disaster scenarios.

The differences in agreement among participants regarding all 132 resources, when considering speci�ic scenarios, may be grounded in the degree of clinical and operational familiarity with the speci�ic scenario in question. For example, in�luenza epidemics occur reg- ularly, so both clinicians and hospital administrators are more familiar with the required critical resources (ICC=0.7),than those needed in a radiation disaster (ICC=0.5). The other interesting �inding of variation in the number of critical resources among differ- ent scenarios (e.g. 58 for pandemic in�luenza and 35 for nerve gas), is likely due to the clinical complexity of the scenario, in addition to the notion of familiarity mentioned above.

To the best of our knowledge, the derivation and importance ranking of 132 discrete potential hospital resources, is the only collec- tive attempt by subject matter experts to stratify the various hospital-based provisions required for the care of victims during the four scenarios considered in this study. The expert panelists noted which of these hospital resources were critical, and that their ab- sence represented a major risk of an untoward medical outcome. This information enables planners to further examine, describe and delineate their surge capacity beyond simple bed availability.

Limitations

There are several limitations to our study. First, the study is based on an expert panel consensus and not on a speci�ic functional ex- ercise or disaster event. Second, the size of each group (sub-panel) of experts was not very large (�ive or six members). Still, two sep- arate panels, i.e., 50% of the available panel members, considered each scenario. Third, group composition may not be comprehen- sive in representing the numerous specialties and sub-specialties that would typically take part in responding to the selected disaster scenarios. Representation from every type of hospital may also be lacking (e.g. rural hospitals were poorly represented). While we were thoughtful and deliberate regarding the composition of each group – seeking to optimize representation from a broad national

pool of expert practitioners – this limitation may affect the generalizability of our �inding. Finally, due to the objectives of the study, the results are applicable to only four national planning scenarios. To mitigate this limitation, we are planning on conducting further studies to explore identifying critical resources for the remaining national planning scenarios.

Conclusion

Twenty �ive hospital resources were found to be critical to maintain continuity medical care in four disaster planning scenarios; namely radiation, pandemic in�luenza, explosives, and nerve gas scenarios. However, some speci�ic disaster scenarios require addi- tional critical specialized resources necessary for the corresponding type of disaster. Planning for each hospital should be dictated by the hazard vulnerability analysis, gauging their vulnerabilities within the environment, in order to prioritize and maintain adequate supplies of scenario-speci�ic critical hospital resources. Further studies are needed in the �ield of hospital surge capacity, to validate these �indings, determine utilization rates for each of the resources during a surge event, and to identify appropriate alternatives to these critical hospital resources .

Competing Interests

The authors have declared that no competing interests exist and have no disclosures.

Biographies

•

*Associate Director, Of�ice of Critical Event Preparedness and Response (CEPAR) *Assistant Professor, School of Medicine- Department of Emergency Medicine Bloomberg School of Public Health- Department of International Health

•

Associate Professor Department of Emergency Medicine Department of International Health The Johns Hopkins University School of Medicine and Bloomberg School of Public Health

36

Funding Statement

This work is supported in part by the U.S. Department of Homeland Security through a grant (N00014-06-1-0991) awarded to the National Center for the Study of Preparedness and Critical Event Response (PACER) at the Johns Hopkins University. Any opinions, �inding, conclusions or recommendations expressed in this publication are those of the authors and do not represent the policy or position of the Department of Homeland Security. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Contributor Information

Jamil D. Bayram, Department of Emergency Medicine, School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA; Johns Hopkins Of�ice of Critical Event Preparedness and Response, Baltimore, Maryland, USA; Center for Refugee and Disaster Response, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, USA.

Lauren M. Sauer, Department of Emergency Medicine, School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA; Johns Hopkins Of�ice of Critical Event Preparedness and Response, Baltimore, Maryland, USA; Center for Refugee and Disaster Response, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, USA.

Christina Catlett, Department of Emergency Medicine, School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA; Johns Hopkins Of�ice of Critical Event Preparedness and Response, Baltimore, Maryland, USA.

Scott Levin, Department of Emergency Medicine, School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA.

Gai Cole, Department of Emergency Medicine, School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA; Johns Hopkins Of�ice of Critical Event Preparedness and Response, Baltimore, Maryland, USA.

Thomas D. Kirsch, Department of Emergency Medicine, School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA; Johns Hopkins Of�ice of Critical Event Preparedness and Response, Baltimore, Maryland, USA; Center for Refugee and Disaster Response, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, USA.

Matthew Toerper, Department of Emergency Medicine, School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA.

Gabor Kelen, Department of Emergency Medicine, School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA; Johns Hopkins Of�ice of Critical Event Preparedness and Response, Baltimore, Maryland, USA.

References

1. Kelen GD, McCarthy ML. The science of surge. Acad Emerg Med. 2006; 13:1089–1094. [PubMed: 17085736]

2. Hick JL, Barbera JA, Macintyre AG, Kelen GD. Re�ining surge capacity: conventional, contingency, and crisis capacity. Disaster Med Public Health Preparedness. 2009;

3:S59–S67 [PubMed: 19349869]

3. Kaji A, Koenig KL, Bey T. Surge capacity for healthcare systems: a conceptual framework. Acad Emerg Med. 2006; 13:1157–1159. [PubMed: 16968688]

4. Barbisch D, Koenig KL. Understanding surge capacity: essential elements. Acad Emerg Med. 2006; 13:1098–1102. [PubMed: 17085738]

5. Hick JL, Koenig KL, Barbisch D, et al. Surge capacity concepts for health care facilities: the CO-S-TR model for initial incident assessment. Disaster Med Public Health Preparedness. 2008; 2:S51–S57. [PubMed: 18769268]

6. Agency for Healthcare Research on Quality (AHRQ). Hospital Surge Model. Accessed on January 16, 2012.

7. Federal Emergency Management Agency (FEMA). National Planning Scenarios Factsheet. Accessed on January 16, 2012.

8. Runge JW. Surge Medical Response Capability: What is it? How do we get it? How do we know when we have it? A white paper prepared for the June 10-11, 2009 workshop on medical surge capacity hosted by the Institute of Medicine Forum on Medical and Public Health Preparedness for Catastrophic Events.

9. Kelen GD, Kraus CK, McCarthy ML, et al. Inpatient disposition classi�ication for the creation of hospital surge capacity: a multiphase study. Lancet. 2006; 368:1984–

1990. [PMCID: PMC7138047] [PubMed: 17141705]

10. Hick JL, Han�ling D, Burstein JL, et al. Health care facility and community strategies for patient care surge capacity. Ann Emerg Med 2004; 44:253–61. [PMCID:

PMC7118880] [PubMed: 15332068]

11. Schultz CH, Stratton SJ. Improving hospital surge capacity: a new concept for emergency credentialing of volunteers. Ann Emerg Med. 2007; 49:602–609. [PubMed: 17112633]

12. Davis DP, Poste JC, Hicks T, et al. Hospital bed surge capacity in the event of a mass-casualty incident. Prehosp Disaster Med. 2005; 20:169–176. [PubMed: 16018505]

13. Soremukun OA, Zane RD, Walls A, Allen MB, Seefeld KJ, Pallin DJ: Cancellation of scheduled procedures as a mechanism to generate hospital bed surge capacity–A

pilot study. Prehosp Disaster Med 2011; 26(3):1–6. [PubMed: 22107776]

14. Burkle FM Jr. Population-based triage management in response to surge capacity requirements during a large-scale bioevent disaster. Acad Emerg Med. 2006; 13(11):1118–1129. [PubMed: 17015415]

15. Estacio PL. Surge capacity for health care systems: early detection, methodologies, and process. Acad Emerg Med. 2006; 13(11):1135–1137. [PubMed: 17085739]

16. McManus J, Huebner K, Scheulen J. The science of surge: detection and situational awareness. Acad Emerg Med. 2006; 13(11):1179–1182. [PubMed: 16968687]

17. Stratton SJ, Tyler RD. Characteristics of medical surge capacity demand for sudden-impact disasters. Acad Emerg Med. 2006; 13(11):1193–1197. [PubMed:

16885401]

18. Bonnett CJ, Peery BN, Cantrill SV, et al. Surge capacity: a proposed conceptual framework. Am J Emerg Med. 2007; 25(3):297–306. [PubMed: 17349904]

19. Han�ling D. Equipment, supplies, and pharmaceuticals: how much might it cost to achieve basic surge capacity? Acad Emerg Med. 2006; 13(11):1232–1237. [PubMed: 16801633]

20. Burt CW, McCaig LF. Staf�ing, capacity, and ambulance diversion in emergency departments: United States, 2003-04. Adv Data. 2006; 27(376):1–23. [PubMed: 17037024]

21. Voelker R. Mobile hospital raises questions about hospital surge capacity. JAMA. 2006; 295(13):1499–1503. [PubMed: 16595745]

22. Koenig KL, Kelen G. Proceedings of the Consensus Conference “The Science of Surge,” May 17, 2006, San Francisco, California, USA. Acad Emerg Med. 2006;

13:1087–1088. [PubMed: 17032943]

23. Eastman AL, Rinnert KJ, Nemeth IR, Fowler RL, Minei JP. Alternate site surge capacity in times of public health disaster maintains trauma center and emergency department integrity: Hurricane Katrina. J Trauma. 2007; 63(2):253–257 [PubMed: 17693820]

24. McCarthy ML, Aronsky D, Kelen GD. The measurement of daily surge and its relevance to disaster preparedness. Acad Emerg Med. 2006; 13(11):1138–1141. [PubMed: 17032946]

25. Davis DP, Poste JC, Hicks T, Polk D, Rymer TE, Jacoby I. Hospital bed surge capacity in the event of a mass-casualty incident. Prehosp Disaster Med. 2005; 20(3):169–176 [PubMed: 16018505]

26. DeLia D. Annual bed statistics give a misleading picture of hospital surge capacity. Ann Emerg Med. 2006; 48(4): 384–388. [PubMed: 16997673]

27. Challen K, Walter D. Accelerated discharge of patients in the event of a major incident: observational study of a teaching hospital. BMC Public Health. 2006; 6:108.

[PMCID: PMC1468403] [PubMed: 16638157]

28. Roccaforte JD, Cushman JG. Disaster preparedness, triage, and surge capacity for hospital de�initive care areas: optimizing outcomes when demands exceed resources. Anesthesiol Clin. 2007; 25(1):161–177. [PMCID: PMC7185660] [PubMed: 17400163]

29. Phillips S. Current status of surge research. Acad Emerg Med. 2006; 13(11):1103–1108. [PubMed: 17032944]

30. Asplin BR, Flottemesch TJ, Gordon BD. Developing models for patient �low and daily surge capacity research. Acad Emerg Med. 2006; 13(11):1109–1113. [PubMed: 17015412]

31. Rothman RE, Hsu EB, Kahn CA, Kelen GD. Research priorities for surge capacity. Acad Emerg Med. 2006; 13(11):1160–1168 [PubMed: 17032947]

32. Jenkins JL, O’Connor RE, Cone DC. Differentiating large-scale surge versus daily surge. Acad Emerg Med. 2006; 13(11):1169–1172 [PubMed: 17085741]

33. Davidson SJ, Koenig KL, Cone DC. Daily patient �low is not surge: “management is prediction.” Acad Emerg Med. 2006; 13(11):1095–1096. [PubMed: 17085737]

34. Bayram JD, Zuabi S, Subbarao I. Disaster metrics: quantitative benchmarking of hospital surge capacity in trauma-related multiple casualty events. Disaster Med

Public Health Prep. 2011 Jun; 5(2):117–24. Epub 2010 Sep 28. [PubMed: 21685307]

35. National guidance for healthcare system preparedness. Assistant Secretary for Preparedness and Response, Department of Health and Human Services. Healthcare preparedness capabilities- Washington, DC. 2012. Accessed May 22, 2013

36. Olympia RP, Rivera R, Heverley S, Anyanwu U, Gregorits M. Natural disasters and mass-casualty events affecting children and families: a description of emergency preparedness and the role of the primary care physician. Clin Pediatr. 2010 Jul;49(7):686-98. Epub 2010 Mar 31. [PubMed: 20356922]

Figures and Tables

Table 1. Expert panel composition

(in alphabetical order)

Participant Type Number

Administration and hospital operations 4

Adult intensive care nurse 2

Adult intensive care physician 2

Burn specialist 1

Infectious disease physician 1

Internal medicine physician 2

Medical/surgical nurse 2

Pediatric intensive care nurse 1

Pediatric intensive care physician 2

Pediatric nurse 2

Pediatric physician 2

Radiation specialist 1

Trauma physician 1

Table 2 -Critical hospital resources common to all four scenarios

*Signi�icant difference in score distribution among the four scenarios

Resource Percent scored as 3 (Critical) p-value (Kruskal-Wallis)

Crystalloid solution with IV tubing 100 1

Adult ICU capacity 97.8 0.364

Ambu bag, adult 97.8 0.364

Endotracheal tube 97.8 0.364

Laryngoscope, adult 97.8 0.364

Oxygen source and tubing 97.8 0.364

Ambu bag, pediatric 95.7 0.526

Adult mechanical ventilator set 95.7 0.089

Pediatric mechanical ventilator set 95.7 0.089

Critical care nurse 95.7 0.526

Suction catheter and suction apparatus 95.7 0.089

Laryngoscope, peds 95.7 0.561

Critical care physician 93.5 0.803

Sedatives* 93.5 0.031

Peds ICU capacity 93.5 0.775

Adult medical/surgical bed 91.3 0.56

Needles, sterile 80.4 0.166

Non-critical care nurse 80.4 0.234

Latex-free, non-sterile gloves* 78.3 0.036

IV catheters (18-24g), and heplocks 78.3 0.158

Pressors* 76.1 0.028

BP ff d l 71 7 0 078

Table 3 - Scenario-Specific Critical Hospital Resources

Pandemic In�luenza Radiation Explosives Nerve Gas

Resource % ranked as critical

Resource % ranked as critical

Resource % ranked as critical

Resource % ranked as critical

1. Crystalloid solution (NS or LR) IV, 1000 ml, and IV tubing*

100 1. Crystalloid solution (NS or LR) IV, 1000 ml, and IV tubing

100 1. Crystalloid solution (NS or LR) IV, 1000 ml, and IV tubing

100 1. Crystalloid solution (NS or LR) IV, 1000 ml, and IV tubing

100

2. Adult ICU capacity 100 2. Decontamination capability

100 2. Adult ICU capacity 100 2. Peds ICU capacity 100

3. ICU MD 100 3. Potassium iodide 100 3. Critical care nurse (CCN)

100 3. Critical care nurse (CCN)

100

4. Respiratory Therapist

(RT)

100 4. Radiation expert 100 4. Pressors 100 4. Sedatives 100

5. Case Speci�ic Antibiologic (ex - Antivirals for PanFlu)

100 5. Geiger counter 100 5. Adult med/surg bed 100 5. Adult ICU capacity 100

6. Sedatives 100 6. Sedatives 100 6. Suction catheter and suction apparatus

100 6. Suction catheter and suction apparatus

100

7. IV catheters, small bore (18-24g), and heplock

100 7. Standard radiograph 90.9 7. Adult mechanical ventilator set

100 7. Adult mechanical ventilator set

100

8. Airborne isolation room

or cohorting

100 8. Isotope chelating agents 90.9 8. Pediatric mechanical

ventilator set

100 8. Pediatric mechanical

ventilator set

100

9. Suction catheter and suction apparatus

100 9. Ambu bag, adult 90.9 9. Endotracheal tube 100 9. Endotracheal tube 100

10. Adult mechanical ventilator set

100 10. Ambu bag, pediatric 90.9 10. Laryngoscope, adult

100 10. Laryngoscope, adult 100