Accelerating Food Allergy Research: Need for a Data Commons.

Food allergy is a significant health problem affecting approximately 8% of children and 11% of adults in the United States. It exhibits all the characteristics of a "complex" genetic trait; therefore, it is necessary to look at very large numbers of patients, far more than exist at any single organization, to eliminate gaps in the current understanding of this complex chronic disorder. Advances may be achieved by bringing together food allergy data from large numbers of patients into a Data Commons, a secure and efficient platform for researchers, comprising standardized data, available in a common interface for download and/or analysis, in accordance with the FAIR (Findable, Accessible, Interoperable, and Reusable) principles. Prior data commons initiatives indicate that research community consensus and support, formal food allergy ontology, data standards, an accepted platform and data management tools, an agreed upon infrastructure, and trusted governance are the foundation of any successful data commons. In this article, we will present the justification for the creation of a food allergy data commons and describe the core principles that can make it successful and sustainable.

Development of Food Allergy Data Dictionary: Toward a Food Allergy Data Commons.

BACKGROUND: Food allergy (FA) data lacks a common base of terminology and hinders data exchange among institutions. OBJECTIVE: To examine the current FA concept coverage by clinical terminologies and to develop and evaluate a Food Allergy Data Dictionary (FADD). METHODS: Allergy/immunology templates and patient intake forms from 4 academic medical centers with expertise in FA were systematically reviewed, and in-depth discussions with a panel of FA experts were conducted to identify important FA clinical concepts and data elements. The candidate ontology was iteratively refined through a series of virtual meetings. The concepts were mapped to existing clinical terminologies manually with the ATHENA vocabulary browser. Finally, the revised dictionary document was vetted with experts across 22 academic FA centers and 3 industry partners. RESULTS: A consensus version 1.0 FADD was finalized in November 2020. The FADD v1.0 contained 936 discrete FA concepts that were grouped into 14 categories. The categories included both FA-specific concepts, such as foods triggering reactions, and general health care categories, such as medications. Although many FA concepts are included in existing clinical terminologies, some critical concepts are missing. CONCLUSIONS: The FADD provides a pragmatic tool that can enable improved structured coding of FA data for both research and clinical uses, as well as lay the foundation for the development of standardized FA structured data entry forms.