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

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Abstract

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.

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Funding

This work was funded in part through NIAMS 1P30AR069589-01 and R01-AR060962.

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Authors and Affiliations

  1. Department of Dermatology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA

    Rachel L. Fulton, Zelma Chiesa-Fuxench, Patrick G. Sockler & David J. Margolis

  2. Department of Biostatistics and Epidemiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA

    Nandita Mitra & David J. Margolis

Authors
  1. Rachel L. Fulton
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  2. Nandita Mitra
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  3. Zelma Chiesa-Fuxench
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  4. Patrick G. Sockler
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  5. David J. Margolis
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Contributions

Conceptualization: RLF, DJM. Data curation: DJM, RLF, PS. Formal Analysis: RLF, DJM. Funding acquisition: DJM. Investigation: RLF, DJM. Methodology: RLF, DJM. Project administration: DJM. Resources: DJM. Software: DJM. Supervision: DJM. Validation: RLF, DJM, Visualization: RLF, DJM. Writing—original draft: RLF. Writing—review and editing: RLF, DJM, NM, PGS, ZC-F.

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Correspondence to Rachel L. Fulton.

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Fulton, R.L., Mitra, N., Chiesa-Fuxench, Z. et al. Untapping the potential of utilizing electronic medical records to identify patients with atopic dermatitis: an algorithm using ICD-10 codes. Arch Dermatol Res 314, 439–444 (2022). https://doi.org/10.1007/s00403-021-02251-w

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  • DOI: https://doi.org/10.1007/s00403-021-02251-w

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