Assessment of Circulatory Dysfunction by Automated Processing of Vital Signs Data
Technical Report,02 Mar 2016,01 Dec 2018
Massachusetts General Hospital Boston United States
Pagination or Media Count:
Background Casualty care is challenging because caregivers may be inexperienced, or distracted by environmental dangers or multiple casualties. Objective To provide clinical data for development and validation of a system that executes, in real time, automated decision-assist tools that accurately identify key trauma patient conditions and guide relevant life-saving interventions. This system will be comprised of novel artificial intelligence algorithms that only rely on data measured by standard patient transport monitors. Specific Aims We will validate a, fully functional prototype of the decision-assist system, which can be provided to an industry partner for full productization. Study Design We will prospectively trial these algorithms by making use of our operational, IRB-approved plug-and-play system for clinical field-testing of algorithms, presently in use on board Boston Medflight helicopters and the MGH Emergency Dept. Relevance Because the necessary medical instrumentation, i.e., a standard travel monitor, is so very familiar to caregivers, these decision-assistance capabilities could be broadly deployed with a relative minimum of additional training, hardware acquisition, and up-front buy-in by clinicians.
- Medicine and Medical Research