Decision Support Tool to Judiciously Assign High-Frequency Neurologic Examinations in Traumatic Brain Injury

Introduction: Traumatic brain injury (TBI) management includes serial neurologic exami-nations to assess for changes dictating neurosurgical interventions. We hypothesized hourly examinations are overassigned. We conducted a decision tree analysis to determine an algorithm to judiciously assign hourly examinations.Methods: A retrospective cohort study of 1022 patients with TBI admitted to a Level 1 trauma center from January 1, 2019, to December 31, 2019, was conducted. Patients with penetrating TBI or immediate or planned interventions and those with nonsurvivable in-juries were excluded. Patients were stratified by whether they underwent an unplanned intervention (e.g., craniotomy or invasive intracranial monitoring). Univariate analysis identified factors for inclusion in chi-square automatic interaction detection technique, classifying those at risk for unplanned procedures.Results: A total of 830 patients were included, 287 (35%) were assigned hourly (Q1) exami-nations, and 17 (2%) had unplanned procedures, with 16 of 17 (94%) on Q1 examinations. Patients requiring unplanned procedures were more likely to have mixed intracranial hemorrhage pattern (82% versus 39%; P = 0.001), midline shift (35% versus 14%; P = 0.023), an initial poor neurologic examination (Glasgow Comas Scale <8, 77% versus 14%; P < 0.001), and be intubated (88% versus 17%; P < 0.001). Using chi-square automatic interaction detection, the decision tree demonstrated low-risk (2% misclassification) and excellent discrimination (area under the curve = 0.915, 95% confidence interval 0.844-0.986; P < 0.001) of patients at risk of an unplanned procedure. By following the algorithm, 167 fewer pa-tients could have been assigned Q1 examinations, resulting in an estimated 6012 fewer examinations.Conclusions: Using a 4-factor algorithm can optimize the assignment of neuro examinations and substantially reduce neuro examination burden without sacrificing patient safety.(c) 2022 Elsevier Inc. All rights reserved.