Using mobile health technology to improve assessments in lumbar spine disease
Beyond imaging and physical exam, traditional evaluations for patients with lumbar disease rely primarily on validated questionnaires typically administered once or twice before surgery. These are often repeated again once or twice after surgery to evaluate outcomes. However, disability related to lumbar disease is a dynamic process that may fluctuate throughout the day and interact with changes in activity and mood. The goal of this research, sponsored by NIAMS, is to investigate the role of mobile health assessments in providing more granular evaluations of lumbar disease. We hope to use such tools to improve preoperative counseling, patient selection and prehabilitation, and postoperative recovery.
This work is currently being funded by the National Institutes of Health (1K23AR082986-01A1) and has also been funded by grants from the AO Spine North America, the Cervical Spine Research Society, the Scoliosis Research Society, the Foundation for Barnes-Jewish Hospital, Washington University/BJC Healthcare Big Ideas Competition, the Fullgraf Foundation, and the National Institute of Mental Health (1F31MH124291-01A).
Using biomedical informatics and artificial intelligence to support the early diagnosis of degenerative cervical myelopathy
Degenerative cervical myelopathy (DCM) refers to chronic compression on the spinal cord in the neck from arthritis. DCM is a progressive disease, meaning that the longer symptoms progress, the more severe a patient’s ultimate disability typically is. The goal of this work, sponsored by the Department of Defense and WU/BJC, is to use informatics tools and artificial intelligence models to support early DCM diagnosis.
This work is supported by the Department of Defense and the Institute for Informatics, Data Science and Biostatistics (I2DB).
A smartphone application for precision assessments of degenerative cervical myelopathy
Aside from delayed diagnosis, one major challenge in caring for patients with degenerative cervical myelopathy (DCM) is the absence of objective tools to longitudinally measure disease severity in the home and clinic environments. To address this gap, we are developing a smartphone application to support precision assessments of DCM severity in the home environment.
This work is supported by the Missouri Spinal Cord Injury/Disease Research Program (SCIDRP)