Diagnostic Algorithm for Pediatric Headaches: A Clinical Improvement Initiative

Background: The widespread variation in diagnosing primary headache disorders in children and ado-lescents results in reduced quality and high costs. Defining an algorithm for primary headache diagnoses in children and adolescents is part of a larger initiative to standardize and improve care. The aim of this algorithm was to increase the accuracy of headache diagnosis by formal criteria to more than 80% of patient encounters.Methods: A team of headache specialists, nurse practitioners, nurses, data analysts, and business spe-cialists developed an algorithm based on available scientific evidence. This algorithm was vetted and adapted by the neurology faculty and headache specialists until final consensus was reached. Following three months of testing and validation, the algorithm was disseminated to general pediatric neurology clinics. The following information was gathered: percent of encounters utilizing the algorithm, per-centage of encounters with appropriate diagnosis by formal criteria, percentage of encounters with appropriate testing ordered, and average cost per headache visit.Results: Correct diagnosis of primary headache by International Classification of Headache Disorders-3 criteria improved from 72% to 90% and appropriate testing improved from 80% to 94%. By the end of analysis, 94% of encounters were correctly implementing the algorithm. A year-long tracking revealed decreased cost of headache evaluation by 6% compared with the year prior.Conclusions: A standardized algorithm improved the diagnostic accuracy in general child neurology clinics. Expanding the algorithm to primary care and pediatric emergency rooms could have a greater impact on headache evaluation and diagnosis; this should result in improved care and outcomes with reduced cost.(c) 2023 Elsevier Inc. All rights reserved.