CoolSim: using industrial modeling techniques to examine the impact of selective head cooling in a model of perinatal regionalization.
OBJECTIVE
A selective head-cooling device for the treatment of moderate to severe hypoxic-ischemic encephalopathy has been approved by the Food and Drug Administration for use in the United States. To reflect the complexity of health care delivery at the systems level, we used the industrial modeling technique of discrete event simulation to analyze the impact of various deployment strategies for selective head cooling and its partner technology, amplitude-integrated electroencephalography.


METHODS
We modeled the course through the perinatal system of all births in Massachusetts over a 1-year period. Cohort and care characteristics were drawn from existing databases. Results of a recently published trial were used to estimate the effects of selective head cooling. One thousand cohort replications were conducted to assess uncertainty. Several policy alternatives were examined, including no use of selective head cooling and scenarios that altered the number and placement of selective head-cooling and amplitude-integrated electroencephalography units throughout the state. Patient-level outcome and cost data were assessed.


RESULTS
For all scenarios tested, the use of amplitude-integrated electroencephalography/selective head cooling resulted in better outcomes at lower cost. However, substantial differences in transfer rates, failure-to-cool rates, and total costs were seen across scenarios. Optimal decision-making regarding the number and placement of devices led to a 16% improvement in cost savings and a 10-fold decrease in failure-to-cool rates, compared with other deployment scenarios. These results were insensitive to significant changes in model inputs.


CONCLUSIONS
On the basis of currently available data, the package of amplitude-integrated electroencephalography and selective head cooling seems to be an economically desirable intervention. Quantifiable techniques to assess system-wide technology performance provide a powerful approach to informing decisions regarding the structure and function of health care systems.
Gray
James
J
Department of Neonatology, Beth Israel Deaconess Medical Center, 330 Brookline Ave, Boston, MA 02215, USA.
Geva
Alon
A
Zheng
Zheng
Z
Zupancic
John A F
JA
D001034:Apgar Score; D001931:Brain Mapping / Q000295:instrumentation / Q000379:methods; D003362:Cost-Benefit Analysis; D018795:Device Approval; D004569:Electroencephalography / Q000191:economics; D005260:Female; D006257:Head; D006801:Humans; D007036:Hypothermia, Induced / Q000191:economics* / Q000295:instrumentation* / Q000379:methods; D020925:Hypoxia-Ischemia, Brain / Q000175:diagnosis / Q000628:therapy*; D007231:Infant, Newborn; D008297:Male; D018803:Models, Economic; D018743:Perinatal Care; D012307:Risk Factors; D012680:Sensitivity and Specificity; D012720:Severity of Illness Index; D047929:Term Birth; D014481:United States; D014486:United States Food and Drug Administration