Untapping the potential of utilizing electronic medical records to identify patients with atopic dermatitis: an algorithm using ICD-10 codes

Atopic Dermatitis (AD) is a chronic, inflammatory skin condition that imposes an enormous personal and economic burden in the United States. Due to the ubiquity of the use of electronic medical records (EMR) in the United States, utilizing such data is critically important to studying common dermato...

Full description

Saved in:
Bibliographic Details
Published in:Archives of dermatological research 2022-07, Vol.314 (5), p.439-444
Main Authors: Fulton, Rachel L., Mitra, Nandita, Chiesa-Fuxench, Zelma, Sockler, Patrick G., Margolis, David J.
Format: Article
Language:English
Subjects:
Algorithms
Allergic rhinitis
Asthma
Atopic dermatitis
Classification
Cohort Studies
Dermatitis
Dermatitis, Atopic - diagnosis
Dermatology
Eczema
Electronic Health Records
Electronic medical records
Humans
Inflammation
International Classification of Diseases
Medical coding
Medical diagnosis
Medical records
Medicine
Medicine & Public Health
Original Paper
Patients
Skin diseases
United States
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Atopic Dermatitis (AD) is a chronic, inflammatory skin condition that imposes an enormous personal and economic burden in the United States. Due to the ubiquity of the use of electronic medical records (EMR) in the United States, utilizing such data is critically important to studying common dermatologic diseases, such as AD. Our goal was to create a simple-to-use algorithm applied to EMR data to accurately identify AD patients thereby making it possible to efficiently use EMR data to ascertain and then study individuals with AD. Our results suggest that the algorithm that is most likely to accurately identify AD patients from the EMR based on PPV utilizes ICD-10 code for L20.89, L20.9, or L20.84 in conjunction with a diagnosis code for asthma or allergic rhinitis, treatment code, and dermatology consult code. This approach yields a PPV of 95.00% in our training cohort and 100.00% in our validation cohort. Therefore, future studies can use this algorithm to better assure that a subject has AD for studies of the pathogenesis and/or potential treatment targets of AD.
ISSN:1432-069X
0340-3696
1432-069X
DOI:10.1007/s00403-021-02251-w