Page 47 - Journal of Special Operations Medicine - Spring 2014

Arguably the biggest challenge in using a scientific ap- Disclosures
proach to develop better emergency response methods The authors have no relevant financial conflicts of inter-
is that there are no available data that can be used in est in regard to the submitted work.
estimating some of the crucial model parameters. While
this challenge may be less of an issue when exploring
the problem at a highly abstract level, as we did when References
we developed the model given in Figure 2, the practical 1. Jenkins JL, et al. Mass-casualty triage: time for an evidence-
usefulness of the specific methods we propose, namely based approach. Prehosp Disaster Med. 2008;23:3–8.
ReSTART and Simple-ReSTART, depends on the qual- 2. Lerner EB, Schwartz RB, Coule PL, et al. Mass casualty
ity of the estimates. In fact, one of the best features of triage: an evaluation of the data and development of a
ReSTART and Simple-ReSTART is that they require es- proposed national guideline. Disaster Med Public Health
Prep. 2008;2(Suppl 1):S25–S34.
timation of very few parameters, and except for the pa- 3. Lerner EB, et al. Mass casualty triage: an evaluation of
rameter T (the time point at which deterioration rate of the science and refinement of a national guideline. Disas-
delayed patients exceeds that of immediate patients), they ter Med Public Health Prep. 2011;5:129–137.
are all easy to determine. To the best of our knowledge, 4. Frykberg ER. Triage: principles and practice. Scand J
there are simply no data available to estimate parameter Surg. 2005;94:272–278.
T, and thus an important next step is to conduct research 5. Sacco WJ, Navin DM, Fiedler KE, et al. Precise for-
that specifically aims to estimate this parameter, or more mulation and evidence-based application of resource-
broadly, to estimate the survival probability functions constrained triage. Acad Emerg Med. 2005;12:759–770.
depicted in Figure 1, which might in turn be used to de- 6. Sacco WJ, Navin DM, Waddell RK, et al. A new resource-
termine T. Estimation of the whole survival probability constrained triage method applied to victims of penetrat-
function would be more challenging but nevertheless ing injury. J Trauma. 2007;63:316–325.
much more useful because these functions can be used 7. Cone DC, MacMillan DS. Mass-casualty triage systems: a
hint of science. Acad Emerg Med. 2005;12:739–741.
in simulation studies that compare different prioritization 8. Mills AF, Argon NT, Ziya S. Resource-based patient pri-
policies. The approach the developers of STM used to get oritization in mass-casualty incidents. Manuf Serv Oper
around this problem was using the Delphi method, that Manage. 2013;15:1–17.
is, asking a panel of experts to give their best estimates 9. Ingolfsson A, Budge S, Erkut E. Optimal ambulance loca-
on the survival probability of a patient given the patient’s tion with random delays and travel times. Health Care
RPM score and how this score changed with time. A simi- Manage Sci. 2008;11:262–274.
lar study can be carried out to estimate survival prob- 10. Green L. Queuing analysis in healthcare. In Hall RW,
abilities given a patient’s START class. These estimates editor. Patient flow: reducing delay in healthcare delivery.
can also differ depending on the type of the event or the New York, NY: Springer; 2006:281–307.
nature of the patents’ injuries. While the scientific cred-
ibility of this approach is uncertain, it might serve as a
good starting point and the estimates can be improved
as more data are gathered in future mass-casualty events. Dr. Mills is affiliated with the Department of Operations and
Decision Technologies, Kelley School of Business, Indiana Uni-
versity. Bloomington, Indiana; this research was partially con-
Conclusions ducted while he was a student at University of North Carolina
at Chapel Hill, North Carolina.
This study puts forth a novel framework for taking re-
source limitations into account when prioritizing pa- Dr. Argon is affiliated with the Department of Statistics and
tients in the aftermath of mass-casualty incidents and Operations Research, University of North Carolina at Chapel
Hill, North Carolina.
gives precise descriptions for two new methods that are
based on this framework. Uncertainty exists as to defin- Dr. Ziya is affiliated with the Department of Statistics and
ing key parameters such as expected survival times, and Operations Research, University of North Carolina at Chapel
this is a key area for future research. Hill, North Carolina.
Dr. Hiestand is affiliated with the Department of Emergency
Medicine, Wake Forest School of Medicine, Winston-Salem,
Disclaimers
North Carolina. E-mail: bhiestan@wfubmc.edu.
This research was supported by National Science Founda- Dr. Winslow is affiliated with the Department of Emergency
tion grants CMMI-0927607, CMMI-0927668, CMMI- Medicine, Wake Forest School of Medicine, Winston-Salem,
1234212, and CMMI-1234260. North Carolina.

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