"Piloting an automated query and scoring system to facilitate APDS pati" by Amy M FitzPatrick, Aaron T Chin et al.
 

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

Document Type

Article

Publication Date

1-21-2024

Publication Title

Frontiers in immunology

Abstract

INTRODUCTION: Patients 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.

METHODS: We developed a structured query language (SQL) script using literature-validated APDS-associated clinical concepts mapped to

RESULTS: The 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).

CONCLUSION: Disease-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.

Volume

15

First Page

1508780

DOI

10.3389/fimmu.2024.1508780

ISSN

1664-3224

PubMed ID

39906746

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