Virtual care for cyber–physical systems (VH_CPS): NODE-RED, community of practice and thick data analytics ecosystem

Abstract

Virtual care is changing from the mere Face-to-Face Services, which includes telephone visits in addition to audio and video visits to include several non Face-to-Face Services, including E-visits, community of practice consultations and remote Patient Monitoring (RPM). Virtual care has the capacity to transform how people interact and collaborate with each other using the cyber–physical systems’ services. However, the use of cyber–physical​ systems (CPS) in healthcare is still in its infancy and there exist many challenges to be solved. The future of virtual care based on CPS will be require the availability of an ecosystem that leverages range of technologies to enable care to shift away from the legacy clinical setting when appropriate. In order to provide such open loop type of connectivity and interfacing, this article presents a solution VH_CPS ecosystem that push beyond the telehealth visit to create an ecosystem that integrates the care team collaboration with other essential virtual services such as remote monitoring and diagnostics as well as chronic care management services. Moreover, this article incorporate at VH_CPS ecosystem a component that enables the care team to assist in driving more in depth analytics based on qualitative techniques borrowed from the paradigm of thick data analytics. The Siamese Neural Network used in this paper is an example where care team members like a radiologist can feed few labelled CT-Scans to let the decision making component of the VH_CPS to learn the diagnosis of COVID cases. Our VH_CPS ecosystem uses a scalable Node-RED framework with the care team as well as to the remote patient monitoring devices. Our ecosystem will enable more patients to access the care they need, keep more patients in a low-risk care setting, and contribute to better outcomes at lower costs.