AUTHOR=FitzPatrick Amy M. , Chin Aaron T. , Nirenberg Sharon , Cunningham-Rundles Charlotte , Sacco Keith , Perlmutter Jesse , Dasso Joseph F. , Tsalatsanis Athanasios , Maru Jay , Creech Jessica , Walter Jolan E. , Hartog Nicholas , Izadi Neema , Palmucci Mandy , Butte Manish J. , Loewy Klaus , Relan Anurag , Rider Nicholas L. 

TITLE=Piloting an automated query and scoring system to facilitate APDS patient identification from health systems

JOURNAL=Frontiers in Immunology

VOLUME=Volume 15 - 2024

YEAR=2025

URL=https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2024.1508780

DOI=10.3389/fimmu.2024.1508780

ISSN=1664-3224

ABSTRACT=IntroductionPatients with activated PI3Kδ syndrome (APDS) may elude diagnoses for nearly a decade. Methods to hasten the identification of these patients, and other patients with inborn errors of immunity (IEIs), are needed. We sought to demonstrate that querying electronic health record (EHR) systems by aggregating disparate signs into a risk score can identify these patients.MethodsWe developed a structured query language (SQL) script using literature-validated APDS-associated clinical concepts mapped to ICD-10-CM codes. We ran the query across EHRs from 7 large, US-based medical centers encompassing approximately 17 million patients. The query calculated an “APDS Score,” which stratified risk for APDS for all individuals in these systems. Scores for all known patients with APDS (n=46) were compared.ResultsThe query identified all but one known patient with APDS (98%; 45/46) as well as patients with other complex disease. Median score for all patients with APDS was 9 (IQR = 5.75; range 1-25). Sensitivity analysis suggested an optimal cutoff score of 7 (sensitivity = 0.70).ConclusionDisease-specific queries are a relatively simple method to foster patient identification across the rare-disease spectrum. Such methods are even more important for disorders such as APDS where an approved, pathway-specific treatment is available in the US.