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Suggestion of a simpler and faster influenza-like illness surveillance system using 2014–2018 claims data in Korea
Influenza is an important public health concern. We propose a new real-time influenza-like illness (ILI) surveillance system that utilizes a nationwide prospective drug utilization monitoring in Korea. We defined ILI-related claims as outpatient claims that contain both antipyretic and antitussive a...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8159991/ https://www.ncbi.nlm.nih.gov/pubmed/34045533 http://dx.doi.org/10.1038/s41598-021-90511-0 |
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author | Choi, HeeKyoung Choi, Won Suk Han, Euna |
author_facet | Choi, HeeKyoung Choi, Won Suk Han, Euna |
author_sort | Choi, HeeKyoung |
collection | PubMed |
description | Influenza is an important public health concern. We propose a new real-time influenza-like illness (ILI) surveillance system that utilizes a nationwide prospective drug utilization monitoring in Korea. We defined ILI-related claims as outpatient claims that contain both antipyretic and antitussive agents and calculated the weekly rate of ILI-related claims, which was compared to weekly ILI rates from clinical sentinel surveillance data during 2014–2018. We performed a cross-correlation analysis using Pearson’s correlation, time-series analysis to explore actual correlations after removing any dubious correlations due to underlying non-stationarity in both data sets. We used the moving epidemic method (MEM) to estimate an absolute threshold to designate potential influenza epidemics for the weeks with incidence rates above the threshold. We observed a strong correlation between the two surveillance systems each season. The absolute thresholds for the 4-years were 84.64 and 86.19 cases per 1000claims for claims data and 12.27 and 16.82 per 1000 patients for sentinel data. The epidemic patterns were more similar in the 2016–2017 and 2017–2018 seasons than the 2014–2015 and 2015–2016 seasons. ILI claims data can be loaded to a drug utilization review system in Korea to make an influenza surveillance system. |
format | Online Article Text |
id | pubmed-8159991 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-81599912021-05-28 Suggestion of a simpler and faster influenza-like illness surveillance system using 2014–2018 claims data in Korea Choi, HeeKyoung Choi, Won Suk Han, Euna Sci Rep Article Influenza is an important public health concern. We propose a new real-time influenza-like illness (ILI) surveillance system that utilizes a nationwide prospective drug utilization monitoring in Korea. We defined ILI-related claims as outpatient claims that contain both antipyretic and antitussive agents and calculated the weekly rate of ILI-related claims, which was compared to weekly ILI rates from clinical sentinel surveillance data during 2014–2018. We performed a cross-correlation analysis using Pearson’s correlation, time-series analysis to explore actual correlations after removing any dubious correlations due to underlying non-stationarity in both data sets. We used the moving epidemic method (MEM) to estimate an absolute threshold to designate potential influenza epidemics for the weeks with incidence rates above the threshold. We observed a strong correlation between the two surveillance systems each season. The absolute thresholds for the 4-years were 84.64 and 86.19 cases per 1000claims for claims data and 12.27 and 16.82 per 1000 patients for sentinel data. The epidemic patterns were more similar in the 2016–2017 and 2017–2018 seasons than the 2014–2015 and 2015–2016 seasons. ILI claims data can be loaded to a drug utilization review system in Korea to make an influenza surveillance system. Nature Publishing Group UK 2021-05-27 /pmc/articles/PMC8159991/ /pubmed/34045533 http://dx.doi.org/10.1038/s41598-021-90511-0 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This 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/) . |
spellingShingle | Article Choi, HeeKyoung Choi, Won Suk Han, Euna Suggestion of a simpler and faster influenza-like illness surveillance system using 2014–2018 claims data in Korea |
title | Suggestion of a simpler and faster influenza-like illness surveillance system using 2014–2018 claims data in Korea |
title_full | Suggestion of a simpler and faster influenza-like illness surveillance system using 2014–2018 claims data in Korea |
title_fullStr | Suggestion of a simpler and faster influenza-like illness surveillance system using 2014–2018 claims data in Korea |
title_full_unstemmed | Suggestion of a simpler and faster influenza-like illness surveillance system using 2014–2018 claims data in Korea |
title_short | Suggestion of a simpler and faster influenza-like illness surveillance system using 2014–2018 claims data in Korea |
title_sort | suggestion of a simpler and faster influenza-like illness surveillance system using 2014–2018 claims data in korea |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8159991/ https://www.ncbi.nlm.nih.gov/pubmed/34045533 http://dx.doi.org/10.1038/s41598-021-90511-0 |
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