An Integrated System for Precision Warfighter Spine Health
Abstract
Objective and Rationale: Musculoskeletal injuries in the form of neck and low back pain pose a significant burden in terms of personnel and societal cost. Despite the massive medical expenditure, patient outcomes have not significantly improved over the same time period. Thus, given the prevalence, the human impact, as well as operational and economic costs to the military, there is a need to develop better strategies to reduce neck and low back injuries and improve treatment outcomes. The primary reason neck and low back pain treatment has grown in cost but not in effectiveness is that providers, payers, and employers lack objective and clinically actionable metrics for quantifying the severity and nature of spine disorders. This unavailability of metrics results in a treatment practice based largely on trial and error, which makes it difficult to efficiently diagnose, monitor, and devise effective treatment plans, leading to increased costs. The long-term objective of this project is to enhance clinical evaluations of spine disorders through the use of an integrated spine health platform that leverages wearable motion data along with other meta data to quantify impairment and predict long-term outcomes in military personnel. Specifically for this effort, we will utilize AI/deep learning-based algorithms to (1) differentiate healthy and impaired spine function using data acquired from wearable motion sensors; (2) test the utility of a wearable platform to facilitate deep patient phenotyping, track disease patterns and recovery profiles, and support clinical decision-making for the treatment of neck and low back disorders. Impact and Applicability: Clinical decisions in spine care rely on population-based guidelines and are not optimized to a spine patient s condition. The proposed integrated spine health platform will leverage novel motion-based metrics derived from wearable sensors, as well as other relevant medical information known to influence back and neck pain. This platform will be a scientifically based disruptive technology utilizing wearable sensors that can, for the first time, provide the clinician with objective biomechanically meaningful information about the functional impairment status of the Warfighter. Central access to this full spectrum of biopsychosocial metrics will enable artificial intelligence and deep patient phenotyping algorithms to account for disease heterogeneity and enhance outcome predictions. Through large reference databases, systems will be able to predict recovery trajectories and enable the identification of patient phenotypes that do or do not respond well to specific treatment pathways. Ultimately, providing this information via an accessible and intuitive technology solution will enable an integrated approach to personalize spine care that will enhance clinical decision-making, improve patient outcomes, minimize recurrences, and reduce costs.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Mar 10, 2021
- Source ID
- W81XWH2010878
Entities
People
- William Marras
Organizations
- Ohio State University
- United States Army