» Articles » PMID: 28619959

Defining Asthma and Assessing Asthma Outcomes Using Electronic Health Record Data: a Systematic Scoping Review

Overview
Journal Eur Respir J
Specialty Pulmonary Medicine
Date 2017 Jun 17
PMID 28619959
Citations 30
Authors
Affiliations
Soon will be listed here.
Abstract

There is currently no consensus on approaches to defining asthma or assessing asthma outcomes using electronic health record-derived data. We explored these approaches in the recent literature and examined the clarity of reporting.We systematically searched for asthma-related articles published between January 1, 2014 and December 31, 2015, extracted the algorithms used to identify asthma patients and assess severity, control and exacerbations, and examined how the validity of these outcomes was justified.From 113 eligible articles, we found significant heterogeneity in the algorithms used to define asthma (n=66 different algorithms), severity (n=18), control (n=9) and exacerbations (n=24). For the majority of algorithms (n=106), validity was not justified. In the remaining cases, approaches ranged from using algorithms validated in the same databases to using nonvalidated algorithms that were based on clinical judgement or clinical guidelines. The implementation of these algorithms was suboptimally described overall.Although electronic health record-derived data are now widely used to study asthma, the approaches being used are significantly varied and are often underdescribed, rendering it difficult to assess the validity of studies and compare their findings. Given the substantial growth in this body of literature, it is crucial that scientific consensus is reached on the underlying definitions and algorithms.

Citing Articles

Prevalence and features of allergic bronchopulmonary aspergillosis, United States, 2016-2022.

Benedict K, Gold J, Toda M, Hsu J PLoS One. 2025; 20(1):e0317054.

PMID: 39813272 PMC: 11734977. DOI: 10.1371/journal.pone.0317054.


Validating the recording of exacerbations of asthma in electronic health records: a systematic review protocol.

Moore E, Gassasse Z, Quint J BMJ Open. 2024; 14(11):e088849.

PMID: 39532362 PMC: 11575333. DOI: 10.1136/bmjopen-2024-088849.


Inhaled Corticosteroids Attenuate the Association of Fine Particulate Matter and Acute Asthma Events.

Staggers K, Sierra P, Helmer D, Minard C, McCormack M, Wu T Am J Respir Crit Care Med. 2024; 210(7):948-951.

PMID: 39078230 PMC: 11506900. DOI: 10.1164/rccm.202404-0796RL.


Combining Federated Machine Learning and Qualitative Methods to Investigate Novel Pediatric Asthma Subtypes: Protocol for a Mixed Methods Study.

Xu J, Talankar S, Pan J, Harmon I, Wu Y, Fedele D JMIR Res Protoc. 2024; 13:e57981.

PMID: 38976313 PMC: 11263892. DOI: 10.2196/57981.


Improving reporting standards for phenotyping algorithm in biomedical research: 5 fundamental dimensions.

Wei W, Rowley R, Wood A, MacArthur J, Embi P, Denaxas S J Am Med Inform Assoc. 2024; 31(4):1036-1041.

PMID: 38269642 PMC: 10990558. DOI: 10.1093/jamia/ocae005.