@inproceedings{a9977c668530406b8562f870772d3635,
title = "Estimation of Asthma Severity from Electronic Prescription Records using British Thoracic Society and Scottish Intercollegiate Guidelines Network Treatment Steps",
abstract = "Asthma is a common chronic lung disease. National guidelines encourage a stepwise approach to pharmacotherapy, and as such, an individual's current treatment step can be considered as a severity categorization proxy. BTS/SIGN steps can be estimated from electronic prescription records, however substantial data processing is required including extracting information from free-text drug descriptions and dose instructions. Almost 4.5 million asthma controller inhalers were prescribed for people in the Asthma Learning Health System (ALHS) Scottish cohort between 2009 and 2017. Asthma treatment regimens were identified and categorized by the combination of medications prescribed in the 120 days preceding prescribing events. 26% of prescriptions had no primary controller (inhaled corticosteroid) prescriptions in the previous 120 days and were thus assigned Step 0. 16% of prescriptions were assigned to BTS/SIGN Step 1, 7% to Step 2, 21% to Step 3, and 30% to Step 4. We developed a robust methodology enabling researchers to easily replicate BTS/SIGN asthma treatment step estimates, to both describe the severity of asthma in a population and to demonstrate changes over time. This can provide valuable insights into population and patient-specific trajectories, to improve understanding and management of symptoms. ",
keywords = "asthma, electronic health records, prescribing, severity, treatment",
author = "Holly Tibble and Aziz Sheikh and Athanasios Tsanas",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021 ; Conference date: 09-12-2021 Through 12-12-2021",
year = "2022",
month = dec,
day = "14",
doi = "10.1109/BIBM52615.2021.9669455",
language = "English",
series = "Proceedings - 2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021",
publisher = "Institute of Electrical and Electronics Engineers",
pages = "3222--3223",
editor = "Yufei Huang and Lukasz Kurgan and Feng Luo and Hu, {Xiaohua Tony} and Yidong Chen and Edward Dougherty and Andrzej Kloczkowski and Yaohang Li",
booktitle = "Proceedings - 2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021",
address = "United States",
}