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Establishing an expert consensus for the operational definitions of asthma-associated infectious and inflammatory multimorbidities for computational algorithms through a modified Delphi technique
BACKGROUND: A subgroup of patients with asthma has been reported to have an increased risk for asthma-associated infectious and inflammatory multimorbidities (AIMs). To systematically investigate the association of asthma with AIMs using a large patient cohort, it is desired to leverage a broad rang...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8573872/ https://www.ncbi.nlm.nih.gov/pubmed/34749701 http://dx.doi.org/10.1186/s12911-021-01663-y |
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author | Yoon, Jungwon Billings, Heather Wi, Chung-Il Hall, Elissa Sohn, Sunghwan Kwon, Jung Hyun Ryu, Euijung Shrestha, Pragya Liu, Hongfang Juhn, Young J. |
author_facet | Yoon, Jungwon Billings, Heather Wi, Chung-Il Hall, Elissa Sohn, Sunghwan Kwon, Jung Hyun Ryu, Euijung Shrestha, Pragya Liu, Hongfang Juhn, Young J. |
author_sort | Yoon, Jungwon |
collection | PubMed |
description | BACKGROUND: A subgroup of patients with asthma has been reported to have an increased risk for asthma-associated infectious and inflammatory multimorbidities (AIMs). To systematically investigate the association of asthma with AIMs using a large patient cohort, it is desired to leverage a broad range of electronic health record (EHR) data sources to automatically identify AIMs accurately and efficiently. METHODS: We established an expert consensus for an operational definition for each AIM from EHR through a modified Delphi technique. A series of questions about the operational definition of 19 AIMS (11 infectious diseases and 8 inflammatory diseases) was generated by a core team of experts who considered feasibility, balance between sensitivity and specificity, and generalizability. Eight internal and 5 external expert panelists were invited to individually complete a series of online questionnaires and provide judgement and feedback throughout three sequential internal rounds and two external rounds. Panelists’ responses were collected, descriptive statistics tabulated, and results reported back to the entire group. Following each round the core team of experts made iterative edits to the operational definitions until a moderate (≥ 60%) or strong (≥ 80%) level of consensus among the panel was achieved. RESULTS: Response rates for each Delphi round were 100% in all 5 rounds with the achievement of the following consensus levels: (1) Internal panel consensus: 100% for 8 definitions, 88% for 10 definitions, and 75% for 1 definition, (2) External panel consensus: 100% for 12 definitions and 80% for 7 definitions. CONCLUSIONS: The final operational definitions of AIMs established through a modified Delphi technique can serve as a foundation for developing computational algorithms to automatically identify AIMs from EHRs to enable large scale research studies on patient’s multimorbidities associated with asthma. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12911-021-01663-y. |
format | Online Article Text |
id | pubmed-8573872 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-85738722021-11-08 Establishing an expert consensus for the operational definitions of asthma-associated infectious and inflammatory multimorbidities for computational algorithms through a modified Delphi technique Yoon, Jungwon Billings, Heather Wi, Chung-Il Hall, Elissa Sohn, Sunghwan Kwon, Jung Hyun Ryu, Euijung Shrestha, Pragya Liu, Hongfang Juhn, Young J. BMC Med Inform Decis Mak Research Article BACKGROUND: A subgroup of patients with asthma has been reported to have an increased risk for asthma-associated infectious and inflammatory multimorbidities (AIMs). To systematically investigate the association of asthma with AIMs using a large patient cohort, it is desired to leverage a broad range of electronic health record (EHR) data sources to automatically identify AIMs accurately and efficiently. METHODS: We established an expert consensus for an operational definition for each AIM from EHR through a modified Delphi technique. A series of questions about the operational definition of 19 AIMS (11 infectious diseases and 8 inflammatory diseases) was generated by a core team of experts who considered feasibility, balance between sensitivity and specificity, and generalizability. Eight internal and 5 external expert panelists were invited to individually complete a series of online questionnaires and provide judgement and feedback throughout three sequential internal rounds and two external rounds. Panelists’ responses were collected, descriptive statistics tabulated, and results reported back to the entire group. Following each round the core team of experts made iterative edits to the operational definitions until a moderate (≥ 60%) or strong (≥ 80%) level of consensus among the panel was achieved. RESULTS: Response rates for each Delphi round were 100% in all 5 rounds with the achievement of the following consensus levels: (1) Internal panel consensus: 100% for 8 definitions, 88% for 10 definitions, and 75% for 1 definition, (2) External panel consensus: 100% for 12 definitions and 80% for 7 definitions. CONCLUSIONS: The final operational definitions of AIMs established through a modified Delphi technique can serve as a foundation for developing computational algorithms to automatically identify AIMs from EHRs to enable large scale research studies on patient’s multimorbidities associated with asthma. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12911-021-01663-y. BioMed Central 2021-11-08 /pmc/articles/PMC8573872/ /pubmed/34749701 http://dx.doi.org/10.1186/s12911-021-01663-y Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Yoon, Jungwon Billings, Heather Wi, Chung-Il Hall, Elissa Sohn, Sunghwan Kwon, Jung Hyun Ryu, Euijung Shrestha, Pragya Liu, Hongfang Juhn, Young J. Establishing an expert consensus for the operational definitions of asthma-associated infectious and inflammatory multimorbidities for computational algorithms through a modified Delphi technique |
title | Establishing an expert consensus for the operational definitions of asthma-associated infectious and inflammatory multimorbidities for computational algorithms through a modified Delphi technique |
title_full | Establishing an expert consensus for the operational definitions of asthma-associated infectious and inflammatory multimorbidities for computational algorithms through a modified Delphi technique |
title_fullStr | Establishing an expert consensus for the operational definitions of asthma-associated infectious and inflammatory multimorbidities for computational algorithms through a modified Delphi technique |
title_full_unstemmed | Establishing an expert consensus for the operational definitions of asthma-associated infectious and inflammatory multimorbidities for computational algorithms through a modified Delphi technique |
title_short | Establishing an expert consensus for the operational definitions of asthma-associated infectious and inflammatory multimorbidities for computational algorithms through a modified Delphi technique |
title_sort | establishing an expert consensus for the operational definitions of asthma-associated infectious and inflammatory multimorbidities for computational algorithms through a modified delphi technique |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8573872/ https://www.ncbi.nlm.nih.gov/pubmed/34749701 http://dx.doi.org/10.1186/s12911-021-01663-y |
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