Rapid Assessment for Prehospital Triage of Evacuation and Medical Resources En Route Care Award (RAPTER ERCA)
Abstract
Both military and civilian medics must make quick decisions about treatment and priority for evacuation from the point of injury. Currently, this relies on using vital signs and injury patterns to identify Soldiers who have life-threatening injuries. However, little is known about how to help medics pick out the most important signs of injury to identify and treat the sickest patients reducing their risk of death. To address this gap, our objective for this research is to develop a decision tool that includes specific criteria of more advanced vital signs and injury patterns that predict injured Soldiers that need a life-saving procedure. This will help medics decide which patients need to be evacuated to a higher level of trauma care immediately and those that can wait longer. Because the advanced vital signs require recording of continuous waveform data from bulky patient monitors, we will also test the accuracy of a small wearable sensor that sticks to the patient and can capture the data needed to determine whether using these wearable sensors can reduce the equipment and manpower required for medics in a combat environment or mass casualty events. This proposal directly aligns with ERCA focus area: Mode, timing, and regulation of movement for ill, injured, resuscitated, and post-operative patients using manned or unmanned systems. The expected product of this research is a clinical decision tool that identifies patients that require early evacuation based on predicting the need for life-saving procedures. We will also validate use of a non-invasive wearable sensor technology with our clinical decision tool that is low size, weight, and power (SWaP) to allow placement on the Warfighter rapidly after wounding. We expect over the 2-year performance period that we will have the clinical decision tool developed with machine learning and validated with traditional statistical methods, as well as wearable sensors validated for use with the clinical decision tool. We expect next steps over the subsequent 2 to 3 years will include further validation in other civilian and military settings to support widespread deployment, as well as integrating the decision tool into other monitors and military medical communication technology such as MEDHUB or BATDOK as implementation platforms. This research will help both injured Soldiers and civilian patients. In operational environments where evacuation is delayed or impossible, our decision tool will help medics provide medical resources to casualties most likely to benefit. Our clinical decision tool will help to discriminate casualties requiring immediate evacuation from those that may tolerate prolonged field care if only a limited number can be evacuated early. It will also prioritize patients when evacuation becomes possible. Our decision tool will be critical in near-peer operations where we lack air superiority or operate in a denied environment. This minimizes the skill required to place and can be done as part of buddy aid while extending the medic s ability to monitor multiple casualties. Our decision tool will also have secondary benefits for re-triage and anticipation of deterioration on long-haul and Critical Care Air Transport Team platforms caring for multiple casualties between higher Role facilities. This proposal will additionally help civilian medics decide which patients may benefit from evacuation during a mass casualty event or which require air medical transport to minimize time to reach a trauma center. The decision tool will also determine which patients need advanced care en route to the trauma center. Deploying wearable devices during mass casualty incidents will also allow triage over a large number of casualties with less manpower. This research and its future work will be foundational to establishing a robust evidence-based approach to advancing evacuation and triage decision-making for both the military and civilian medic caring for injure
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Dec 28, 2022
- Source ID
- W81XWH2210610
Entities
People
- Francis Guyette
Organizations
- United States Army
- University of Pittsburgh