Chronic Low Back Pain (cLBP) is a debilitating condition that affects millions of people globally. Despite increased utilization of interventions and rising medical costs, cLBP prevalence has continued to increase. This problem arises because cLBP is complex, heterogeneous and current diagnostics and treatments rely primarily on subjective metrics and do not target all the multidimensional biopsychosocial mechanisms associated with cLBP. Specifically, most diagnostics do not quantitively consider patient functional measures. This multidisciplinary effort proposes to address this problem by developing and validating a digital health platform and provide meaningful data-driven metrics that enable an integrated approach to clinical evaluation and treatment of cLBP. This platform will facilitate the use of quantitative spinal motion metrics (function), PROs and patient preference information to enable deep patient phenotyping and inform clinical decision-making on personalized treatments in order to improve outcomes. This effort will involve software and hardware development to enable data collection, analysis and visualization in clinical settings. Technology development effort will be done in partnership with Switchbox Inc. (Software Strategy) and Priority Designs Inc. (Regulatory Strategy).
The specific aims for UH2 phase are to: 1) Develop a Digital health platform for collecting, analyzing, and reporting core cLBP metrics; 2) Conduct a feasibility study to test the clinical operability, usability and utility of the prototype; and the specific Aims for UH3 phase are to: 1) Optimize Digital Health Platform for translation to clinical research use through BACPAC; 2) Validate the utility of the Digital Health Platform to identify cLBP patient phenotypes and inform clinical decision-making on optimal treatment pathways for individual patients. The outcome of this project will be a digital health platform with data to support regulatory submission for clinical use. At the end of this effort, we will have a validated tool for integration in clinical research studies supported by the BACPAC consortium.

Public Health Relevance

Chronic low back pain is the leading cause of disability globally. Current diagnostics and outcomes are subjective and fail to provide actionable information to improve patient outcomes. This multidisciplinary effort aims to develop and validate a digital health platform to enable the use of quantitative spinal motion metrics, PROs and patient preference information to facilitate patient phenotyping and enable clinical decision-making on personalized treatments to improve outcomes.

National Institute of Health (NIH)
National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)
Exploratory/Developmental Cooperative Agreement Phase I (UH2)
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Special Emphasis Panel (ZAR1)
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Zheng, Xincheng
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Ohio State University
Engineering (All Types)
Biomed Engr/Col Engr/Engr Sta
United States
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