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Published on: November 20, 2016
Geo-Mapping Using In-Hospital Massive Transfusion Data as a Method for Prehospital Blood Management for Trauma
Nicolle K Barmettler1, Coulter Knapp1, Ashley A Raposo-Hadley1
1From the Division of Trauma and Acute Care Surgery, Department of Surgery, University of Nebraska Medical Center, Omaha, NE (Barmettler, Knapp, Raposo-Hadley, Kemp, Barrett, Maginot, Boever, Evans, Henry).
Background:
Prehospital whole blood (PHWB) transfusion improves outcomes in trauma patients, but blood products are a scarce and costly resource. We hypothesized that massive transfusion protocol (MTP) activation could be an indicator for trauma patients who might benefit from PHWB, and we used geo-mapping to identify high need zones.
Study Design:
We retrospectively analyzed trauma registry data from 5 trauma centers in Omaha and Lincoln, Nebraska, including all patients who had MTP activated in the trauma bay from June 1, 2019, to March 31, 2025. Assault and motor vehicle crash data were collected from the Nebraska Department of Transportation and local police databases. Incidence of MTP, assaults, and motor vehicle crashs was mapped to identify the highest need zones. Chi-square tests of independence and Pearson's and Spearman's correlations compared MTP incidence by ZIP code Tabulated Areas with known trauma events.
Results:
A total of 338 MTP patients from Omaha and 89 from Lincoln were included. Geo-mapping revealed a greater need for PHWB in the downtown centers of both cities. Tests of independence showed significant associations between MTP incidence (Omaha: χ 2 = 741.22, df = 28, p < 0.001; Lincoln: χ 2 = 43.75, df = 13, p < 0.001). Spearman's and Pearson's correlations showed a positive linear correlation between MTP incidence and trauma incidence.
Conclusions:
Geo-mapping MTP data strongly correlated with known traumas, supporting MTP activation as a surrogate marker for PHWB need. This offers a novel method for cities to plan PHWB programs by determining high need zones and ensuring equitable and cost-effective distribution of scarce resources.
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