Hypothesis Automation of labor-intensive, repetitive and critical sudden cardiac arrest (SCA) resuscitation tasks will result in improved resuscitation quality. Automated device-assisted SCA protocols and equipment will de-emphasize the hierarchical BLS-ALS classification of SCA resuscitation activities without adversely impacting resuscitation quality. A comprehensive, high-resolution simulation assessment methodology with meaningful objective metrics can be used to realistically and progressively assess standard and experimental approaches to prehospital SCA resuscitation. LUCAS2 chest compressor, automated external defibrillation (AED) guidance, supraglottic airway (SGA or ILMA), portable mechanical ventilator, EZ-IO access device, limited selection of SCA medication. Methods EMS teams (each comprising one EMT-B and one ALS provider) were randomized to control group or experimental group. Each team engaged in 3 SCA simulations: 1) baseline scenario in standard roles; 2) repeat scenario in standard roles; and 3) repeat scenario in reversed roles, for example, BLS provider performing ALS tasks. Control teams operated with standard state protocols and equipment only (with 30-min sham intervention on high-performance CPR); experimental teams used resuscitation-automating devices and accompanying goal-directed algorithmic resuscitation protocol for scenarios 2 and 3 (with 30-min in-servicing). Audiovisual records, simulator logs and PC screencaptures collected data on chest compression, defibrillation, airway management, ventilation, vascular access, medications and transport. Team performance data were extracted and scored on each dimension relative to the best and worst performances for each scenario, with ACLS guidelines used as the gold standard when possible. Results Five control teams and five experimental teams of an anticipated 20-team sample have completed the study (10 EMT-Bs, 6 EMT-Cs, 4 EMT-Ps; mean age 30 years [range 21-52], mean 6 years at primary practice [2-21]; mean 20 SCA patient experience [0-200]). Baseline performance of chest compression and defibrillation was poor in both groups. Control teams performed similarly across scenarios 1 and 2 despite high-performance CPR didactic and skills stations. Experimental teams’ resuscitations improved in most areas, i.e., compression (mean depth: 41% of best performance scenario 1; 91% scenario 2), proportion of adequate compressions (11%; 61%), airway management (40%; 80%), ventilation (22%; 79%), vascular access (20%; 100%) and medication administration (20%; 100%). These improvements persisted in experimental groups when provider roles were reversed for the third scenario; control groups with standard protocols and reversed roles exhibited reduced resuscitation quality in all areas. Conclusion Automated assistance of critical, time- and resource-intensive SCA resuscitation tasks by electromechanical adjuncts improved the in-simulation performance of 2-provider EMS teams on nearly all resuscitation parameters studied. These improvements were maintained in experimental teams even with reversal of BLS and ALS provider roles. Although there are costs and risks to implementing resuscitation-automating protocols and equipment, the early suggestion of a strong trend towards improved clinical management hints at the potential real-world value of this approach. The simulation assessment methodology employed by the ongoing study has facilitated the analysis and innovative representation of prehospital clinical practice performance and will be applied to continuing and future studies. Disclosures Leo Kobayashi receives grant support from the University Emergency Medicine Foundation and Lifespan. Nicolas Asselin’s spouse receives salary support and owns stock in Biogen, Idec of Cambridge Massachusetts.
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