Orr et al. MEASUREMENT OF PEDIATRIC ILLNESS SEVERITY
133
This study is the first attempt in developing a
benchmarking process for pediatric transport that did
not use a previously validated scoring system for
PICU evaluation. Variables used in this study as pre-
dictors of outcome were consistently available and
easy to obtain in the transport arena. If this model
proves to be valid in other regions, it might be useful
as a simple method of classifying children when mak-
ing comparisons between different types of transport
systems. For example, do pediatric specialized care
transport systems improve outcome (morbidity and
mortality) of children when compared with other
teams who transport children? Individual transport
teams could be compared and studied for factors asso-
ciated with quality, e.g., education and experience in
caring for critically ill children, so that systemwide
improvements can be made.
This study has a number of limitations. First, in-hos-
pital mortality is not necessarily related to what occurs
on transport, but to a number of factors, including
severity of illness, disease process and in-hospital
complications. One might consider studying only
those patients who died within the first 24–48 hours
following the acute illness, which might correlate bet-
ter to transport issues. However, there would have
been very small patient numbers, and because of
advancement of PICU technology (e.g., ECMO),
patients who historically would have died sooner dur-
ing their illness are now surviving for longer periods
during their hospitalization. Second, pretransport risk
of mortality does not necessarily prescribe what needs
to be done during the transport. Therefore, this model
should not be applied to individual patients for the
purpose of triage or decision making during the trans-
port process. Third, this study is limited by the devel-
opment and validation of a model from a single, terti-
ary pediatric center that used pediatric specialty care
teams exclusively for interfacility transport and, there-
fore, should be considered preliminary. It has not been
evaluated in the prehospital setting or for victims of
trauma. Fourth, calibration of this model might have
been improved by using laboratory values and per-
haps even diagnosis in the logistic model. However,
this might also add complexity and variables to the
model that might not always be available in the trans-
port setting.
multicenter fashion will enable severity-adjusted
assessment of children requiring transport and might
prove to be useful in making comparisons between
different transport systems.
The authors sincerely thank all the members of the transport team
for their time and effort in collecting the data for the study. They
also thank Ms. Patricia Boyle for her editorial assistance.
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CONCLUSION
This study substantiated our hypothesis that simple
pretransport variables can reasonably predict in-hos-
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risk of mortality based on pretransport variables
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