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Meta-Analysis
. 2018 Jun;178(6):1280-1287.
doi: 10.1111/bjd.16340. Epub 2018 Apr 25.

Systematic review of atopic dermatitis disease definition in studies using routinely collected health data

M P Dizon  1 , A M Yu  2 , R K Singh  3 , J Wan  4 , M-M Chren  5 , C Flohr  6 , J I Silverberg  7 , D J Margolis  4   8 , S M Langan  9 , K Abuabara  1
Affiliations
Meta-Analysis

Systematic review of atopic dermatitis disease definition in studies using routinely collected health data

M P Dizon et al. Br J Dermatol. 2018 Jun.

Abstract

Background: Routinely collected electronic health data obtained for administrative and clinical purposes are increasingly used to study atopic dermatitis (AD). Methods for identifying AD patients in routinely collected electronic health data differ, and it is unknown how this might affect study results.

Objectives: To evaluate how patients with AD have been identified in studies using routinely collected electronic health data, to determine whether these methods were validated and to estimate how the method for identifying patients with AD affected variability in prevalence estimates.

Methods: We systematically searched PubMed, Embase and Web of Science for studies using routinely collected electronic health data that reported on AD as a primary outcome. Studies of localized AD and other types of dermatitis were excluded. The protocol for this review was registered in PROSPERO (CRD42016037968).

Results: In total, 59 studies met eligibility criteria. Medical diagnosis codes for inclusion and exclusion, number of occasions of a code, type of provider associated with a code and prescription data were used to identify patients with AD. Only two studies described validation of their methods and no study reported on disease severity. Prevalence estimates ranged from 0·18% to 38·33% (median 4·91%) and up to threefold variation in prevalence was introduced by differences in the method for identifying patients with AD.

Conclusions: This systematic review highlights the need for clear reporting of methods for identifying patients with AD in routinely collected electronic health data to allow for meaningful interpretation and comparison of results.

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