Cargando…
Infectious diseases prevention and control using an integrated health big data system in China
BACKGROUND: The Yinzhou Center for Disease Prevention and Control (CDC) in China implemented an integrated health big data platform (IHBDP) that pooled health data from healthcare providers to combat the spread of infectious diseases, such as dengue fever and pulmonary tuberculosis (TB), and to iden...
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8984075/ https://www.ncbi.nlm.nih.gov/pubmed/35387590 http://dx.doi.org/10.1186/s12879-022-07316-3 |
_version_ | 1784682101895856128 |
---|---|
author | Zhou, Xudong Lee, Edmund Wei Jian Wang, Xiaomin Lin, Leesa Xuan, Ziming Wu, Dan Lin, Hongbo Shen, Peng |
author_facet | Zhou, Xudong Lee, Edmund Wei Jian Wang, Xiaomin Lin, Leesa Xuan, Ziming Wu, Dan Lin, Hongbo Shen, Peng |
author_sort | Zhou, Xudong |
collection | PubMed |
description | BACKGROUND: The Yinzhou Center for Disease Prevention and Control (CDC) in China implemented an integrated health big data platform (IHBDP) that pooled health data from healthcare providers to combat the spread of infectious diseases, such as dengue fever and pulmonary tuberculosis (TB), and to identify gaps in vaccination uptake among migrant children. METHODS: IHBDP is composed of medical data from clinics, electronic health records, residents’ annual medical checkup and immunization records, as well as administrative data, such as student registries. We programmed IHBDP to automatically scan for and detect dengue and TB carriers, as well as identify migrant children with incomplete immunization according to a comprehensive set of screening criteria developed by public health and medical experts. We compared the effectiveness of the big data screening with existing traditional screening methods. RESULTS: IHBDP successfully identified six cases of dengue out of a pool of 3972 suspected cases, whereas the traditional method only identified four cases (which were also detected by IHBDP). For TB, IHBDP identified 288 suspected cases from a total of 43,521 university students, in which three cases were eventually confirmed to be TB carriers through subsequent follow up CT or T-SPOT.TB tests. As for immunization screenings, IHBDP identified 240 migrant children with incomplete immunization, but the traditional door-to-door screening method only identified 20 ones. CONCLUSIONS: Our study has demonstrated the effectiveness of using IHBDP to detect both acute and chronic infectious disease patients and identify children with incomplete immunization as compared to traditional screening methods. |
format | Online Article Text |
id | pubmed-8984075 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-89840752022-04-06 Infectious diseases prevention and control using an integrated health big data system in China Zhou, Xudong Lee, Edmund Wei Jian Wang, Xiaomin Lin, Leesa Xuan, Ziming Wu, Dan Lin, Hongbo Shen, Peng BMC Infect Dis Research BACKGROUND: The Yinzhou Center for Disease Prevention and Control (CDC) in China implemented an integrated health big data platform (IHBDP) that pooled health data from healthcare providers to combat the spread of infectious diseases, such as dengue fever and pulmonary tuberculosis (TB), and to identify gaps in vaccination uptake among migrant children. METHODS: IHBDP is composed of medical data from clinics, electronic health records, residents’ annual medical checkup and immunization records, as well as administrative data, such as student registries. We programmed IHBDP to automatically scan for and detect dengue and TB carriers, as well as identify migrant children with incomplete immunization according to a comprehensive set of screening criteria developed by public health and medical experts. We compared the effectiveness of the big data screening with existing traditional screening methods. RESULTS: IHBDP successfully identified six cases of dengue out of a pool of 3972 suspected cases, whereas the traditional method only identified four cases (which were also detected by IHBDP). For TB, IHBDP identified 288 suspected cases from a total of 43,521 university students, in which three cases were eventually confirmed to be TB carriers through subsequent follow up CT or T-SPOT.TB tests. As for immunization screenings, IHBDP identified 240 migrant children with incomplete immunization, but the traditional door-to-door screening method only identified 20 ones. CONCLUSIONS: Our study has demonstrated the effectiveness of using IHBDP to detect both acute and chronic infectious disease patients and identify children with incomplete immunization as compared to traditional screening methods. BioMed Central 2022-04-06 /pmc/articles/PMC8984075/ /pubmed/35387590 http://dx.doi.org/10.1186/s12879-022-07316-3 Text en © The Author(s) 2022 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 Zhou, Xudong Lee, Edmund Wei Jian Wang, Xiaomin Lin, Leesa Xuan, Ziming Wu, Dan Lin, Hongbo Shen, Peng Infectious diseases prevention and control using an integrated health big data system in China |
title | Infectious diseases prevention and control using an integrated health big data system in China |
title_full | Infectious diseases prevention and control using an integrated health big data system in China |
title_fullStr | Infectious diseases prevention and control using an integrated health big data system in China |
title_full_unstemmed | Infectious diseases prevention and control using an integrated health big data system in China |
title_short | Infectious diseases prevention and control using an integrated health big data system in China |
title_sort | infectious diseases prevention and control using an integrated health big data system in china |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8984075/ https://www.ncbi.nlm.nih.gov/pubmed/35387590 http://dx.doi.org/10.1186/s12879-022-07316-3 |
work_keys_str_mv | AT zhouxudong infectiousdiseasespreventionandcontrolusinganintegratedhealthbigdatasysteminchina AT leeedmundweijian infectiousdiseasespreventionandcontrolusinganintegratedhealthbigdatasysteminchina AT wangxiaomin infectiousdiseasespreventionandcontrolusinganintegratedhealthbigdatasysteminchina AT linleesa infectiousdiseasespreventionandcontrolusinganintegratedhealthbigdatasysteminchina AT xuanziming infectiousdiseasespreventionandcontrolusinganintegratedhealthbigdatasysteminchina AT wudan infectiousdiseasespreventionandcontrolusinganintegratedhealthbigdatasysteminchina AT linhongbo infectiousdiseasespreventionandcontrolusinganintegratedhealthbigdatasysteminchina AT shenpeng infectiousdiseasespreventionandcontrolusinganintegratedhealthbigdatasysteminchina |