The role of modeling studies in asthma management and clinical decision-making: a Delphi survey of physician knowledge and perceptions
Autor: | Thitiwat Sriprasart, Ma Bella Siasoco, Bhumika Aggarwal, Gur Levy, Abhay Phansalkar, Giap Vu Van, Mark Cohen, Terence Seemungal, Marcia M. M. Pizzichini, Mahmoud Mokhtar, Peter Daley-Yates |
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Rok vydání: | 2023 |
Předmět: | |
Zdroj: | Journal of Asthma. :1-15 |
ISSN: | 1532-4303 0277-0903 |
DOI: | 10.1080/02770903.2023.2180748 |
Popis: | To investigate the knowledge and perceptions of physicians on the role of modeling studies in asthma, using a modified Delphi procedure. Group opinions among a panel of respiratory experts were obtained using two online questionnaires and a virtual scientific workshop. A consensus was pre-defined as agreement by >75% of participants. From 26 experts who agreed to participate, 22 completed both surveys. At the end of the process, the panel rated their own understanding of modeling as good (77%) but that among physicians in general as poor (77%). Participants agreed that data from modeling studies should be used, at least sometimes, to inform treatment guidelines (91%) and could be useful for guiding clinical decisions (100%). Perceived barriers to using modeling studies were ‘A lack of understanding’ (81%) and ‘A lack of standardized methodology’ (82%). Based on data from two modeling studies, no consensus was reached on physicians recommending regular inhaled corticosteroids (ICS) versus as-needed therapy for patients with mild asthma, whereas 77% agreed that they would recommend regular ICS over maintenance and reliever therapy for ≥80% of their patients with moderate asthma. No consensus was reached on the value of modeling data in relation to empirical data. There is overall support among respiratory experts for the usefulness of modeling data to guide asthma treatment guidelines and clinical decision making. More publications on modeling data using robust models and accessible terminology will aid the understanding of physicians in general and help clarify the evidence-based value of modeling studies. |
Databáze: | OpenAIRE |
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