AHRQ: Electronic Health Record Food Allergy Safety Warnings Need Improvement

Improvement is needed in the accuracy and terminology of food allergy safety warnings in hospitals’ electronic health records (EHR), according to an AHRQ-funded study. Researchers examined more than 158,000 records at two large Boston academic hospitals to determine the accuracy of how food sensitivities were described in their EHR systems. The study found that existing standard terminologies had gaps in food sensitivity definitions and that more precise terminology was needed to improve EHR documentation. “Food Entries in a Large Allergy Data Repository” and abstractwere published in the Journal of the American Medical Informatics Association.

2015 Sep 17. pii: ocv128. doi: 10.1093/jamia/ocv128. [Epub ahead of print]

Food entries in a large allergy data repository.

Plasek JM1, Goss FR2, Lai KH3, Lau JJ1, Seger DL3, Blumenthal KG4, Wickner PG5, Slight SP6, Chang FY7, Topaz M8, Bates DW8, Zhou L9.

Author information

Abstract

OBJECTIVE:

Accurate food adverse sensitivity documentation in electronic health records (EHRs) is crucial to patient safety. This study examined, encoded, and grouped foods that caused any adverse sensitivity in a large allergy repository using natural language processing and standard terminologies.

METHODS:

Using the Medical Text Extraction, Reasoning, and Mapping System (MTERMS), we processed both structured and free-text entriesstored in an enterprise-wide allergy repository (Partners' Enterprise-wide Allergy Repository), normalized diverse food allergen terms into concepts, and encoded these concepts using the Systematized Nomenclature of Medicine - Clinical Terms (SNOMED-CT) and Unique Ingredient Identifiers (UNII) terminologies. Concept coverage also was assessed for these two terminologies. We further categorized allergen concepts into groups and calculated the frequencies of these concepts by group. Finally, we conducted an external validation of MTERMS's performance when identifying foodallergen terms, using a randomized sample from a different institution.

RESULTS:

We identified 158 552 food allergen records (2140 unique terms) in the Partners repository, corresponding to 672 food allergen concepts. High-frequency groups included shellfish (19.3%), fruits or vegetables (18.4%), dairy (9.0%), peanuts (8.5%), tree nuts (8.5%), eggs (6.0%), grains (5.1%), and additives (4.7%). Ambiguous, generic concepts such as "nuts" and "seafood" accounted for 8.8% of the records. SNOMED-CT covered more concepts than UNII in terms of exact (81.7% vs 68.0%) and partial (14.3% vs 9.7%) matches.

DISCUSSION:

Adverse sensitivities to food are diverse, and existing standard terminologies have gaps in their coverage of the breadth of allergyconcepts.

CONCLUSION:

New strategies are needed to represent and standardize food adverse sensitivity concepts, to improve documentation in EHRs.

KEYWORDS:

allergy and immunology; controlled; electronic health records; food hypersensitivity; natural language processing; systematized nomenclature of medicine; vocabulary