Dysfunctional though so many medical record systems are, there is undoubtedly a goldmine of information for those that do manage to successfully aggregate information about each patient.  The potential was highlighted by a recent study from Mount Sinai, which showed how AI could help to determine whether lower back pain was acute or chronic, simply by looking at the patients electronic medical records.

Lower back pain is something that affects around 80% of adults at some point in their life.  Indeed, it’s the most common form of job-related disability.  It’s often remedied by prescribing opioids, which many worry has been overdone, resulting in an opioid addiction crisis.

Thus, the researchers strove to more accurately determine the extent of lower back pain to better improve the management of it and reduce the unnecessary prescription of drugs.

Back pain

Acute and chronic lower back pain have crucial and fundamental differences, and require very unique treatments.  Despite this, they are often inserted into electronic medical records using the same code.  They can only be differentiated via a retrospective analysis of the patient’s chart, which includes their medical notes.

By having a single code, it prevents the appropriate treatment, including the correct way back into the workplace.  The AI model developed by the team aims to improve the accuracy of coding, billing, and subsequently treatment for any patient with lower back pain.

“Several studies have documented increases in medication prescriptions and visits to physicians, physical therapists, and chiropractors for lower back pain episodes,” the researchers conclude. “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.”