Abstract Introduction: BrainScope (BSc) is an FDA-cleared noninvasive device utilizing artificial intelligence and machine learning-derived brain algorithms of brain electric activity to assist clinicians in determining the likelihood of intracranial hemorrhage and need for head computed tomography (CT) after trauma. Methods: The objectives of this diagnostic implementation project are to measure patient and operator satisfaction, head CT utilization, and emergency department (ED) length of stay (LOS). We enrolled a convenience sample of ambulatory patients ages 18–85 with mild traumatic brain injury (mTBI) within the preceding 72 h and Glasgow Coma Scale (GCS) ≥13. A trained group of clinicians performed BSc diagnostic testing, recording patient demographics, injury time and cause, BSc results, and test performance time. Ease of device, patient prep, and patient satisfaction were recorded on 5-point Likert scales. Retrospective matched pairs of ED patients with mTBI and GCS ≥13 were derived from a query of Allscripts EHR. Analysis was performed with descriptive statistics and two-sample t -test with significance of P < 0.05. Results: Forty-three patients were enrolled: mean age 31.5 (standard deviation SD 13.6), 40% male, 44% with mTBI resulting from MVC, and 61% presenting 8–24 h after injury. The mean BSc testing time was 9.3 min (SD 3.9). Patient and operator satisfaction with BSc evaluation was rated high in 77% and 86%, respectively. BSc reduced CT utilization by 56% and reduced ED LOS by 197 min (SD 85). Conclusions: BSc offers a point-of-care solution for mTBI evaluation that has excellent patient and operator satisfaction scores while reducing CT utilization and ED LOS.
Garra et al. (Thu,) studied this question.