Optimization of the allergen classification of the International Classification Of Diseases, 11th Revision (ICD-11).

BACKGROUND: Accurate diagnosis of triggers or causative allergens is essential for appropriate risk assessment, providing correct advice to patients with allergy and their caregivers and personalized treatment. However, allergens have never been represented in the World Health Organization International Classification of Diseases (ICD). OBJECTIVE: In this article, we present the process of selection of allergens to better fit the ICD, 11th Revision (ICD-11) structure and the outcomes of this process. METHODS: The Logical Observation Identifiers Names and Codes database, containing 1444 allergens, was used as the basis for the selection process. Two independent experts were responsible for the first selection of the allergens according to specific technical criteria. The second step of the selection process was based on real-life relevance of the allergens according to the frequency of requests regarding each of them. RESULTS: We selected 1109 allergens (76.8%) from all 1444 present in the Logical Observation Identifiers Names and Codes database, with considerable agreement between experts (Cohen κ = 8.6). After assessment of real-life data, 297 additional relevant allergens worldwide were selected and grouped as plants (36.4%), drugs (32.6%), animal proteins (21%), mold and other microorganisms (1.5%), occupational allergens (0.4%), and miscellaneous allergens (0.5%). CONCLUSION: The stepwise approach allowed us to select the most relevant allergens in practice, which is the first step to building a classification of allergens for the WHO ICD-11. Aligned with the achievement in the construction of the pioneer section addressed to the allergic and hypersensitivity conditions in the ICD-11, the introduction of a classification for allergens can be considered timely and much needed in clinical practice.

Drug allergy awareness and perspectives with the implementation of the International Classification of Diseases-11.

PURPOSE OF REVIEW: To understand the current global scale of drug hypersensitivity (DH) and drug allergy (DA), and to identify possible strategies to increase the accuracy of epidemiological data. RECENT FINDINGS: Global patterns of DH/DA seem to be changing and increasing worldwide, but there are still great challenges in capturing quality DH/DA mortality and morbidity statistics (MMS). DH/DA MMS may gain new perspectives with the global implementation of the International Classification of Diseases (ICD)-11. Improving the quality of epidemiological data related to DH/DA should clarify areas of uncertainty, which would lead to better strategies to reduce the burden of these conditions. SUMMARY: DH/DA remains a complex and unaddressed problem globally that often deprives patients of optimal medication choices and places them at risk for life-threatening reactions. DH/DA labels should contribute to people well being, by protecting true allergic individuals from being re-exposed to their allergic drugs and providing needed medications to individuals wrongly labeled as allergic or who have lost allergic sensitivity. The true rate of DH/DA is in fact unknown due to a number of factors, such as misdiagnosis, miscoding and under- and over-notification, among others. Moreover, there is lack of data about DH/DA epidemiology in many countries. Difficulties on collecting accurate and comparable data should be acknowledged, with great impact in the correct labeling DH/DA in electronic health records and official statistics. More accurate definitions, classification and coding may contribute to a better-quality MMS thanks to the ICD-11, under implementation worldwide. Improving the quality of epidemiological data related to DH/DA should clarify areas of uncertainty, which would lead to better strategies to reduce the burden of these conditions. As knowledge derived from populations is key information for more realistic decision-making, the construction of the new section addressed to DH/DA in the ICD-11 will allow the collection of more accurate epidemiological data to support quality management of patients, and facilitate healthcare planning to implement public health measures to prevent and reduce the morbidity and mortality attributable to these conditions.