Artificial intelligence review of physician notes discerns types of lower back pain

Researchers from the Icahn School of Medicine at Mount Sinai developed an artificial intelligence model that can scan physicians' notes and distinguish between acute and chronic lower back pain, according to findings published in the Journal of Medical Internet Research. "Several studies have documented increases in medication prescriptions and visits to physicians, physical therapists, and chiropractors for lower back pain episodes," Ismail Nabeel, MD, MPH, associate professor of environmental medicine and public health at the Icahn School of Medicine at Mount Sinai, said in a press release. "This study is important because artificial intelligence can potentially more accurately distinguish whether the pain is acute or chronic, which would determine whether a patient should return to normal activities quickly or rest and schedule follow-up visits with a physician." "This study also has implications for diagnosis, treatment and billing purposes in other musculoskeletal conditions, such as the knee, elbow, and shoulder pain, where the medical codes also do not differentiate by pain level and acuity," he added. To examine the feasibility of a system that automatically distinguishes acute lower back pain based on free-text clinical notes, Nabeel and colleagues used a dataset of 17,409 clinical notes from various primary care practices in the Mount Sinai Health System.