CHICAGO--(BUSINESS WIRE)-- Promptly following the Food and Drug Administration’s (FDA) sanctioned labeling of pinpointIQ^TM and its multivariate change index (MCI) to allow for remote monitoring of patients with COVID-19, physIQ released its set of clinical “rules” representative of clinical deterioration in patients diagnosed with or exposed to COVID-19. PhysIQ is uniquely positioned to develop such analytics after having previously supported the fight against Ebola in Sierra Leone. With this extensive experience monitoring Ebola patients, in combination with the over one million hours of annotated physiologic data, physIQ has provided a unique perspective on how to develop this new set of rules. PhysIQ’s analytics leverage their large trove of physiologic data, that was collected in partnership with the life-science industry and Veterans Affairs Administration (VA), and uses iterative processing and artificial intelligence modeling to learn the baseline physiologic patterns of individual patients under normal conditions. From that “normal” baseline, the analytics continuously monitor for statistical changes, suggestive of clinical deterioration.

PinpointIQ^TM can deliver on two additional principles that are critical to management of COVID-19. First, remote monitoring may ease the burden on hospitals and other healthcare facilities by reducing the risk of exposure for patients and healthcare professionals to SARS-CoV-2 (the virus that causes COVID-19) and to conserve resources for the very sickest. Secondly, early detection of clinical deterioration associated with COVID-19 may promote better outcomes. The potential utility of pinpointIQ^TM used with COVID-19 patients is corroborated by the work physIQ has done with USAID in patients with Ebola, as well as in clinical studies conducted with the VA in patients with severe congestive heart failure.

“This capability does not happen overnight, and not something that can be developed in a few days or few weeks if done correctly,” said Stephan Wegerich, physIQ’s Chief Science Officer. “We’ve learned what it takes to effectively apply analytics from the hundreds of thousands of hours of data we’ve collected from chronically ill patients and patients undergoing treatment for a variety of illnesses. This is not something we just started working on since COVID-19 came to the United States.”

“Our entire healthcare infrastructure is strained at best by COVID-19,” noted Gary Conkright, CEO of physIQ. “In many cases, we will have more patients than hospital beds and our only option is to find ways to better care for patients at home. With clinical grade wearable sensors and our proprietary, FDA-cleared analytics, we are providing hospitals with personalized physiologic visibility into their homebound high-risk COVID-19 patients. We believe this will not only free up hospital capacity, but also reduce clinician exposure to this highly virulent disease.”

PhysIQ is pursuing multiple clinical use cases in parallel including COVID-19, chronic diseases such as heart failure or COPD, and responses to chemotherapy and other immune-suppressive therapy. The system is prescribed by a physician and is shipped directly to patient’s home without requiring direct physical contact from a clinician.

About physIQ

PhysIQ is a leading digital medicine company dedicated to generating unprecedented health insight using continuous wearable biosensor data and advanced analytics. Our enterprise-ready cloud platform continuously collects and processes data from any wearable biosensor using a deep portfolio of FDA-cleared analytics. We have published one of the most rigorous clinical studies to date in digital medicine and are pioneers in developing, validating, and achieving regulatory approval of Artificial Intelligence-based analytics. With applications in both healthcare and clinical trial support, physIQ is transforming continuous physiological data into insight for health systems, payers, and pharmaceutical companies. For more information, please visit www.physIQ.com. Follow us on Twitter and LinkedIn.

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