Optimizing Virtual Health Technologies Through a Performance-based Readiness Model: Lessons From the Field Deployment of National Emergency Tele-Critical Care Network

Abstract

ABSTRACT Introduction The advancement of the Army’s National Emergency Tele-Critical Care Network (NETCCN) and planned evolution to an Intelligent Medical System rest on a digital transformation characterized by the application of analytic rigor anchored and machine learning. The goal is an enduring capability for telecritical care in support of the Nation’s warfighters and, more broadly, for emergency response, crisis management, and mass casualty situations as the number and intensity of disasters increase nationwide. That said, technology alone is unlikely to solve the most pressing issues in operational medicine and combat casualty care. Materials and Methods A total performance system (TPS) creates opportunities to address vulnerabilities and overcome barriers to success. As applied during the NETCCN project, the TPS captures the best performance-centric information and know-how, increasing the potential to save lives, improve readiness, and accomplish missions. Results The purpose of this project was to apply a performance-based readiness model to aid in the evaluation of Army telehealth technologies. Through various user-facing surveys, polls, and reporting techniques, the project aimed to measure the perceived value of telehealth technologies within a sample of the project team member population. By providing a detailed approach to the collection of lessons learned, researchers were able to determine the importance of information and methods versus a focus on technology alone. The use of an emoji-based feedback assessment indicated that most lessons learned were helpful to the project team. Conclusions Through the NETCCN TPS, we have been able to address product-related measures, knowledge of product efficacy, project metrics, and many implementation considerations that can be further investigated by setting and engagement type. Through the Technology in Disaster Environments learning accelerator, it was possible to rapidly acquire, process, organize, and disseminate best practices and learnings in near real time, providing a critical feedback and improvement loop.