Digital health systems can tell clinicians when someone’s heart-disease risk calls for a drug to lower cholesterol or whether insulin shots are warranted for a person with type 2 diabetes.
But for millions of low-back pain sufferers, care decisions rely heavily on subjective measures of patient discomfort — often leading to expensive tests and treatments (back pain is the third-highest U.S. health care expenditure, after diabetes and heart disease) that don’t necessarily offer a permanent solution.
Ohio State University engineering and medical researchers are developing a digital health system approach designed to enhance back-pain clinical decision-making. After completing a series of studies testing precise, objective measurements they’ve perfected in the lab, the team aims to apply the data-driven practices to the assessment and repair of back problems brought on by dysfunction in the spine.
In a recent study published in Clinical Biomechanics, researchers combined self-reported pain and disability measures with data from a wearable motion-sensing system to evaluate low-back function in lumbar fusion surgery patients. While post-operative pain relief and lower disability were self-reported within six weeks, the objective metrics didn’t detect actual functional improvement in the spine for at least six months after surgery.
These precise motion-based measures, and their inclusion in a burgeoning national database of patient spine-function scores and other medical data, could form the basis of more objective clinical decision-making for surgical patients, the researchers concluded.
“You simply can’t only ask people how they feel about their back,” said senior author William Marras, executive director of the Spine Research Institute at Ohio State.
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