COVID-19: IoT Healthcare Applications and Companies to Watch

COVID-19 continues to grab international headlines with little good news, especially for the healthcare systems and its patients. The healthcare industry is among the most resistant and adverse to cloud and streaming technologies, predominantly due to data privacy and security concerns. However, it is becoming apparent that data sharing and data accumulation could have addressed some of the most challenging topics faced by the industry today, such as mask availability, Intensive Care Unit (ICU) bed availability and movement, patients in a “high risk/vulnerable” category, etc.

ABI Research believes that, as a result of COVID-19, the healthcare system and subsequently healthcare-enabling technologies are being pushed to depart from illness-centric to patient-centric models. In an illness-centric model, the main deterministic variable is the disease; hence, the doctor’s expertise, tests, and diagnosis constitute the largest component of the assessment. Comparatively, in the patient-centric model, the personalized healthcare approach is deployed more rapidly, especially if the patient’s information, history, current medication, and additional physical information is available. Emerging medical data-centered technologies are successfully facilitating this transition, resulting in a shift in both approach and technological coverage within the healthcare system. Based on such trends, the following section outlines a couple of companies to watch, since their services could enable the greater transition to telehealth products and help healthcare systems with valuable information.

ScaleOut is a horizontal Internet of Things (IoT) platform that can find itself highly applicable and among the companies to watch in the time of the pandemic. ScaleOut’s StreamServer is a scalable stream processing compute engine that performs data management and processing functionality for the IoT data by using an in-memory data grid and enables real-time computations. The precise and individual analysis of the data source telemetry enables ScaleOut to construct in memory digital twins, which in the medical application can be used to track patient medical history, current conditions, history of medications, and other special transmitter-related indicators. Additionally, an increasingly important application ScaleOut could ensure for assisting with the SARS-CoV-2 crisis is the tracking and monitoring of the availability of ICU beds. Since the majority of the streaming and processing solutions are running toward mass aggregation, ScaleOut analyzes each telemetry individually, which enables to compute each data source as a separate model. Hence, such objector programming would allow to monitor ICU beds’ availability individually and provide information regarding medical assistance on a grand scale.

Parallax Health Sciences is an edge technology firm that specializes in the remote diagnosis, monitoring, and telehealth system via its proprietary platform and additional purpose build services. The firm focuses on testing, data management, and disease tracking; remote patient monitoring; and telehealth and behavioral intervention. Since the global COVID-19 outbreak, Parallax Health Sciences has been playing an active role in testing technologies, including its proprietary Target Analyzer, a testing solution equipped with an action bar code that identifies the test to be analyzed. The mass scale of the tests is currently in a stage of negotiations with various diagnostics firms globally.

These two are among many companies that could make a difference during the pandemic. However, what is particularly interesting with ScaleOut Software is that the platform execution layer is provided by ScaleOut, while the application layer can be written for a specific vertical application. Other vertical orientated IoT platforms and software merge these components, which makes their modifications, re-configuration, changes and application for a different use case more time consuming and expensive venture. Scale Out enables speedy deployment for various healthcare applications, which seems to be extremely relevant. The applications can be configured toward tracking ICU beds and medical supplies, monitoring equipment, etc., whereas Parallex’s ability to conduct the test, which is recognized by software on a device, enables rapid testing with specific sequences. With this care, flu-like symptoms and COVID-19 could be rapidly distinguished from other diseases or seasonal flu. Interestingly, the technology stimulates patient-centric care, as it can acquire individual data and allocate it to the “personalized” digital model, which can be utilized later, and rapidly establishes the point of treatment via a decentralized system.

Hence, it is becoming clear, platforms with a real-time application and quick deployment, remote diagnostic, and monitoring will lead the way during the coronavirus, as well as in the near future after the pandemic.

Finally, as mentioned in ABI Research’s recent COVID-19: Impact on M2M, IoT, and IoE (WP-WNGH-168) Whitepaper, big data and data analytics might not have a remedy for the virus, but the medically enabled technologies have some answers to tackle the panic, monitor patients, and navigate and prepare the infrastructure for the outbreak in one country or another. As an impact, there clearly will be mode development and growth in the smart devices, embedded medical devices, medical wearable devices, and alternate patient engagement channels, which can include affinity webpages and hospital kiosks. Hopefully, we would also see the lowering of barriers for technology penetration in the medical sector, which greater information sharing and shift toward digitalization and accumulation of the patient information with simpler accessibility. Like most of the medical professionals on the frontline, who are doing an incredible job with COVID-19, it would be up to medical personal to ensure and pursue the transition toward patience-centric models. Some countries are speeding up the adoption of the technologies and easing the barriers of information flow; for example in March 2020 the U.S Federal Court ruled that patients will be able to access their medical records via smartphones, whereas China was using Artificial Intelligence (AI) for Computerized Axial Tomography (CAT) scan analysis during the outbreak. There will be a need for greater paradigm acceptance, expansion in the ecosystem (on the technology side of things), and partnership between the public and private medical institutions, well as IoT vendors.