Application of Algorithm-Based Treatment Approach to Low Back Pain in the Emergency Department.

Abstract

Low back pain accounts for nearly 4 million annual emergency department (ED) visits, and patient outcomes following an ED visit for low back pain are poor. Additionally, only a small portion of patients visiting the ED for low back pain follow up with outpatient physical therapy within 3 months, despite established benefits of early versus delayed physical therapy referral such as improved patient outcomes, less opioid use, and reduced downstream health care utilization. Integrating a physical therapist directly into the ED care team can facilitate evidence-based guideline concordant care and improve patient outcomes, however, physical therapists who are staffed into this role from other settings may lack experience with evaluating and managing patients with acute low back pain. Additionally, there are several unique considerations of the ED care environment which may make existing treatment-based classification approaches difficult to apply in this setting, including physical constraints (eg, delivering care in stretchers and hallways), higher symptom severity and psychosocial stressors necessitating an emergency visit, and greater likelihood of alternative medical diagnoses (eg, kidney stone, aortic aneurysm) contributing to symptoms of low back pain. This perspective presents a modified ED treatment-based classification system (ED-TBC) for low back pain with 3 illustrative case examples. The ED-TBC for low back pain can be used to facilitate guideline concordant care, increase physical therapist confidence in evaluating low back pain in the ED, and reduce clinical practice variation.