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Developing Consensus on Appropriate Standards of Disaster Care for Children

Published online by Cambridge University Press:  08 April 2013

Robert K. Kanter ,
John S. Andrake ,
Nancy M. Boeing ,
James Callahan ,
Arthur Cooper ,
Christine A. Lopez-Dwyer ,
James P. Marcin ,
Folafoluwa O. Odetola ,
Anne E. Ryan  and
Thomas E. Terndrup
...Show all authors
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Abstract

Background: Neither professional consensus nor evidence exists to guide the choice of essential hospital disaster interventions. The objective of our study was to demonstrate a method for developing consensus on hospital disaster interventions that should be regarded as essential, quantitatively balancing needs and resources.

Methods: A panel of pediatric acute care practitioners developed consensus using a modified Delphi process. Interventions were chosen such that workload per staff member would not exceed the previously validated maximum according to the Therapeutic Intervention Scoring System. Based on published models, it was assumed that the usual numbers of staff would care for a disaster surge of 4 times the usual number of intensive care and non–intensive care hospital patients.

Results: Using a single set of assumptions on constrained resources and overwhelming needs, the panel ranked and agreed on essential interventions. A number of standard interventions would exceed crisis workload constraints, including detailed recording of vital signs and fluid balance, administration of vasoactive agents, invasive monitoring of pressures (central venous, intraarterial, intracranial), dialysis, and tube feedings.

Conclusions: The quantitative methodology and consensus development process described in the present report may have utility in future planning. Groups with appropriate expertise must develop action plans according to authority within each jurisdiction, addressing likely disaster scenarios, according to the needs in each medical service region, using available regional resources, and accounting for the capabilities of each institution. (Disaster Med Public Health Preparedness. 2009;3:27–32)

Keywords

critical careDelphi consensus processdisasterhospitalpediatricstandards
Type
Original Research and Critical Analysis
Information
Disaster Medicine and Public Health Preparedness , Volume 3 , Issue 1 , March 2009 , pp. 27 - 32
Copyright
Copyright © Society for Disaster Medicine and Public Health, Inc. 2009

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References

REFERENCES

1.Bravata, DM, McDonald, KM, Owens, DK, et alRegionalization of Bioterrorism Preparedness and Response: Evidence Report/Technology Assessment No. 96. AHRQ publication 04-E016-2. Rockville, MD: Agency for Healthcare Research and Quality; 2004.Google Scholar
2. Pediatric Disaster Toolkit: Hospital Guidelines for Pediatrics in Disasters. New York City, 2006. New York City Department of Health and Mental Hygiene Web site. http://www.nyc.gov/html/doh/html/bhpp/bhpp-focus-ped-toolkit.shtml. Accessed April 13, 2007.Google Scholar
3.Foltin, GL, Schonfeld, DJ, Shannon, MW, et alPediatric Terrorism and Disaster Preparedness: A Resource for Pediatricians. AHRQ publication 06(07)-0056. Rockville, MD: Agency for Healthcare Research and Quality; 2006.Google Scholar
4.Kanter, RK, Moran, JR. Hospital emergency surge capacity: an empiric New York statewide study. Ann Emerg Med. 2007;50:314–319.Google Scholar
5.Health Systems Research, Inc. Altered Standards of Care in Mass Casualty Events. AHRQ publication 05-0043. Rockville, MD: Agency for Healthcare Research and Quality; 2005.Google Scholar
6.Phillips, S, Knebel, A. Providing Mass Medical Care With Scarce Resources: A Community Planning Guide. AHRQ publication 07-0001. Rockville, MD: Agency for Healthcare Research and Quality; 2006.Google Scholar
7. Skidmore S, Wall WT, Church JK. Modular Emergency Medical System: Concept of Operations for the Acute Care Center. http://www.nnemmrs.org/documents/Acute%20Care%20Center%20-%20Concept%20of%20Operations.pdf. Accessed February 2, 2006.Google Scholar
8.Hick, JL, O’Laughlin, DT. Concept of operations for triage of mechanical ventilation in an epidemic. Acad Emerg Med. 2006;13:223–229.CrossRefGoogle Scholar
9.Rubinson, L, Nuzzo, JB, Talmor, DS, et alAugmentation of hospital critical care capacity after bioterrorist attacks or epidemics: recommendations of the Working Group on Emergency Mass Critical Care. Crit Care Med. 2005;33:2393–2403.Google Scholar
10.Hogan, DE, Lairet, JR Triage. In: Hogan DE, Burstein JL Disaster Medicine. 2nd ed. Philadelphia: Lippincott Williams & Wilkins; 2007.Google Scholar
11.Okie, S. Dr. Pou and the hurricane—implications for patient care during disasters. N Engl J Med. 2008;358:1–5.Google Scholar
12. Fiscal Year 2004 Continuation Guidance, National Bioterrorism Hospital Preparedness Program: Washington, DC, 2004. Health Resources and Services Administration Web site. http://www.hrsa.gov/bioterrorism/hrsa04biot.htm#beds. Accessed August 9, 2005.Google Scholar
13.Kanter, RK, Moran, JR. Pediatric hospital and intensive care unit capacity in regional disasters: expanding capacity by altering standards of care. Pediatrics. 2007;119:94–100.CrossRefGoogle ScholarPubMed
14.Kanter, RK. Strategies to improve pediatric disaster surge response capability: potential mortality reduction and tradeoffs. Crit Care Med. 2007;35:2837–2842.Google Scholar
15. Hupert N, Cuomo J. Computer Staffing Model for Bioterrorism Response. Rockville, MD: Agency for Healthcare Research and Quality; 2005. http://www.ahrq.gov/research/biomodel.htm. Accessed November 13, 2006.Google Scholar
16.Fink, A, Kosecoff, J, Chassin, M, et alConsensus methods: characteristics and guidelines for use. Am J Public Health. 1984;74:979–983.Google Scholar
17.Jones, J, Hunter, D. Qualitative research: consensus methods for medical and health services research. BMJ. 1995;311:376–380.Google Scholar
18.Hearnshaw, HM, Harker, RM, Cheater, FM, et alExpert consensus on the desirable characteristics of review criteria for improvement of health care quality. Qual Health Care. 2001;10:173–178.Google Scholar
19.Graham, B, Regehr, G, Wright, JG. Delphi as a method to establish consensus for diagnostic criteria. J Clin Epidemiol. 2003;56:1150–1156.Google Scholar
20.Cullen, DJ, Nemeskal, AR, Zaslavsky, AM. Intermediate TISS: a new intermediate intervention scoring system for non-ICU patients. Crit Care Med. 1994;22:1406–1411.Google Scholar
21.Miranda, DR, Rijk, A, Schaufeli, W. Simplified Therapeutic Intervention Scoring System: The TISS-28 items—results from a multicenter study. Crit Care Med. 1996;24:64–73.Google Scholar
22.Marcin, JP, Rutan, E, Rapetti, PM, et alNurse staffing and unplanned extubation in the pediatric intensive care unit. Pediatr Crit Care Med. 2005;6:254–257.CrossRefGoogle ScholarPubMed
23. Spetz J. Revised Cost Estimates of Minimum Nurse-to-Patient Ratio Proposals. San Francisco: UCSF Center for the Health Professions; 2001. http://www.futurehealth.ucsf.edu/pdf_files/cost_est.pdf. Accessed February 27, 2006.Google Scholar
24.Cullen, DJ, Civetta, JM, Briggs, BA. Therapeutic Intervention Scoring System: a method for quantitative comparison of patient care. Crit Care Med. 1974;2:57–60.Google Scholar
25.Phillips, S. Current status of surge research. Acad Emerg Med. 2006;13:1103–1108.CrossRefGoogle ScholarPubMed
26.Koenig, KL, Cone, DC, Burstein, JL, et alSurging to the right standard of care. Acad Emerg Med. 2006;13:195–198.Google Scholar
27.National Center for Injury Prevention and Control. In a Moment’s Notice: Surge Capacity for Terrorist Bombings. Atlanta: Centers for Disease Control and Prevention; 2007.Google Scholar
28.Irvin, C, Cindrich, L, Patterson, W, et alHospital personnel response during a hypothetical influenza epidemic: will they come to work? [abstract]. Acad Emerg Med. 2007;14:S13.Google Scholar
29. Predicting Casualty Severity and Hospital Capacity. 2003. Centers for Disease Control and Prevention Web site. http://www.bt.cdc.gov/masscasualties/capacity.asp. Accessed November 13, 2006.Google Scholar
30.Hirschberg, A, Scott, BC, Granchi, T, et alHow does casualty load affect trauma care in urban bombing incidents: a quantitative analysis. J Trauma. 2005;58:6686–6695.Google Scholar
31.Laterre, PF, Levy, H, Clermont, G, et alHospital mortality and resource use in subgroups of the recombinant human activated protein C worldwide evaluation in severe sepsis trial. Crit Care Med. 2004;32:2207–2218.Google Scholar
32.Metnitz, PGH, Velely, H, Valentine, A, et alEvaluation of an interdisciplinary data set for national intensive care unit assessment. Crit Care Med. 1999;27:1486–1491.CrossRefGoogle ScholarPubMed
33.Graf, J, Wagner, J, Graf, C, et alFive year survival, quality of life, and individual costs of 303 consecutive medial intensive care patients—a cost utility analysis. Crit Care Med. 2005;33:547–555.Google Scholar
34.Kissoon, N, Walia, MS. The critically ill child in the emergency department. Ann Emerg Med. 1989;18:30–33.Google Scholar
35.Lee, LL, Yeung, KL, Lo, WY, et alEvaluation of a simplified therapeutic intervention scoring system (TISS-28) and the modified early warning score (MEWS) in predicting physiological deterioration during inter-facility transport. Resuscitation. 2008;76:47–51.Google Scholar
36.Reinoud, JBJ, Bonsel, GK, McDonnell, J, et alPatient characteristics and resource utilization in pediatric intensive care. Arch Dis Child. 1994;71:291–296.Google Scholar
37.Neyman, G, Irvin, CB. A single ventilator for multiple simulated patients to meet disaster surge. Acad Emerg Med. 2006;13:1246–1249.Google Scholar
38.Redlener, I. Americans at Risk. New York: Alfred A. Knopf; 2006 22.Google Scholar
39.Powell, T, Christ, KC, Birkhead, GS. Allocation of ventilators in a public health disaster. Disaster Med Public Health Preparedness. 2008;2:20–26.Google Scholar