A real time provider identity verification service for a trusted telehealth video collaboration

Abstract

Video based telehealth is emerging as an important technology for effective and efficient collaboration between providers and patients. The advantages of receiving care at source not only account for convenience and cost effectiveness but also enable faster access to care. It brings access, experience and efficiencies in the care process. While there are multiple models of telehealth, in this work, we will focus on an on demand telehealth appointment between a provider and a patient. Given that the patient might not have a previous care relationship with the provider, it is extremely important to ensure that the patient is assured that the provider that he is communicating with is verified by a trusted third-party verification service. Today, basic methods such as authentication and authorization are used to verify the identity of the provider at entry. In this work, we take this model further by proposing a real-time in-session provider identity verification service. This leverages video stream analytics and computer vision models to validate the person involved in the session by a third-party verification service. We propose an architecture and method for enabling such a service, which will enhance the trust model - a critical factor in the adoption of on-demand telehealth.