Pheno - A modern, multi-faceted, data-driven technology platform for addressing low back and neck pain
Back and neck pain is one of the world’s biggest health problems, and one which most people will experience during some stage in their lives. An estimated 80% of people will face this issue, although the severity of the pain may differ. Approximately 50 billion USD are spent by Americans each year to combat this ailment, which is evidence of the severity and demand of this ailment. Additionally, there an underlying lack of access to objective and reliable quantitative biomarkers for low back and neck pain meaning remedies for the pain are harder to find.
A technology driven platform has been developed as a tool for facilitating provider-patient engagement by setting and working towards quantitative goals, educating patients on their condition, and validating their experience with chronic low back and neck pain.
Dr. William Marras has revolutionized the problems faced in this industry by creating a modern, multi-faceted, data-driven technology platform for addressing low back and neck pain. The platform allows users to capture both existing and novel patient biomarkers derived from data captured from widely accepted and standardized digital questionnaires, biomedical imaging, electronic medical record transcriptions, and novel functional assessments of spine motion capabilities via wearable motion sensors. Captured biomarkers for an individual patient can be compared to large historical databases of patient outcome observations to objectively and quantitatively identify the relative status of an individual, as well as the probability that they will respond favorably to the variety of treatment options that are available
Dr. Marras holds the Honda Chair in the Department of Integrated Systems Engineering at the Ohio State University and serves as the Director of the Spine Research Institute at the Ohio State University. His research endeavors to understand spine disorders from a multidisciplinary systems perspective. He and his team at the SRI focus on understanding spine disorder causal pathways through an integrated analysis of occupational (epidemiological) and clinical observations, laboratory based studies to understand biomechanical functioning of the spine components, and computer modeling in order to assess spine forces at a personalized spine tissue level.