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Development and Application of an Open Tool for Sharing and Analyzing Integrated Clinical and Environmental Exposures Data: Asthma Use Case
BACKGROUND: The Integrated Clinical and Environmental Exposures Service (ICEES) serves as an open-source, disease-agnostic, regulatory-compliant framework and approach for openly exposing and exploring clinical data that have been integrated at the patient level with a variety of environmental expos...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9015759/ https://www.ncbi.nlm.nih.gov/pubmed/35363149 http://dx.doi.org/10.2196/32357 |
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author | Fecho, Karamarie Ahalt, Stanley C Appold, Stephen Arunachalam, Saravanan Pfaff, Emily Stillwell, Lisa Valencia, Alejandro Xu, Hao Peden, David B |
author_facet | Fecho, Karamarie Ahalt, Stanley C Appold, Stephen Arunachalam, Saravanan Pfaff, Emily Stillwell, Lisa Valencia, Alejandro Xu, Hao Peden, David B |
author_sort | Fecho, Karamarie |
collection | PubMed |
description | BACKGROUND: The Integrated Clinical and Environmental Exposures Service (ICEES) serves as an open-source, disease-agnostic, regulatory-compliant framework and approach for openly exposing and exploring clinical data that have been integrated at the patient level with a variety of environmental exposures data. ICEES is equipped with tools to support basic statistical exploration of the integrated data in a completely open manner. OBJECTIVE: This study aims to further develop and apply ICEES as a novel tool for openly exposing and exploring integrated clinical and environmental data. We focus on an asthma use case. METHODS: We queried the ICEES open application programming interface (OpenAPI) using a functionality that supports chi-square tests between feature variables and a primary outcome measure, with a Bonferroni correction for multiple comparisons (α=.001). We focused on 2 primary outcomes that are indicative of asthma exacerbations: annual emergency department (ED) or inpatient visits for respiratory issues; and annual prescriptions for prednisone. RESULTS: Of the 157,410 patients within the asthma cohort, 26,332 (16.73%) had 1 or more annual ED or inpatient visits for respiratory issues, and 17,056 (10.84%) had 1 or more annual prescriptions for prednisone. We found that close proximity to a major roadway or highway, exposure to high levels of particulate matter ≤2.5 μm (PM(2.5)) or ozone, female sex, Caucasian race, low residential density, lack of health insurance, and low household income were significantly associated with asthma exacerbations (P<.001). Asthma exacerbations did not vary by rural versus urban residence. Moreover, the results were largely consistent across outcome measures. CONCLUSIONS: Our results demonstrate that the open-source ICEES can be used to replicate and extend published findings on factors that influence asthma exacerbations. As a disease-agnostic, open-source approach for integrating, exposing, and exploring patient-level clinical and environmental exposures data, we believe that ICEES will have broad adoption by other institutions and application in environmental health and other biomedical fields. |
format | Online Article Text |
id | pubmed-9015759 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-90157592022-04-19 Development and Application of an Open Tool for Sharing and Analyzing Integrated Clinical and Environmental Exposures Data: Asthma Use Case Fecho, Karamarie Ahalt, Stanley C Appold, Stephen Arunachalam, Saravanan Pfaff, Emily Stillwell, Lisa Valencia, Alejandro Xu, Hao Peden, David B JMIR Form Res Original Paper BACKGROUND: The Integrated Clinical and Environmental Exposures Service (ICEES) serves as an open-source, disease-agnostic, regulatory-compliant framework and approach for openly exposing and exploring clinical data that have been integrated at the patient level with a variety of environmental exposures data. ICEES is equipped with tools to support basic statistical exploration of the integrated data in a completely open manner. OBJECTIVE: This study aims to further develop and apply ICEES as a novel tool for openly exposing and exploring integrated clinical and environmental data. We focus on an asthma use case. METHODS: We queried the ICEES open application programming interface (OpenAPI) using a functionality that supports chi-square tests between feature variables and a primary outcome measure, with a Bonferroni correction for multiple comparisons (α=.001). We focused on 2 primary outcomes that are indicative of asthma exacerbations: annual emergency department (ED) or inpatient visits for respiratory issues; and annual prescriptions for prednisone. RESULTS: Of the 157,410 patients within the asthma cohort, 26,332 (16.73%) had 1 or more annual ED or inpatient visits for respiratory issues, and 17,056 (10.84%) had 1 or more annual prescriptions for prednisone. We found that close proximity to a major roadway or highway, exposure to high levels of particulate matter ≤2.5 μm (PM(2.5)) or ozone, female sex, Caucasian race, low residential density, lack of health insurance, and low household income were significantly associated with asthma exacerbations (P<.001). Asthma exacerbations did not vary by rural versus urban residence. Moreover, the results were largely consistent across outcome measures. CONCLUSIONS: Our results demonstrate that the open-source ICEES can be used to replicate and extend published findings on factors that influence asthma exacerbations. As a disease-agnostic, open-source approach for integrating, exposing, and exploring patient-level clinical and environmental exposures data, we believe that ICEES will have broad adoption by other institutions and application in environmental health and other biomedical fields. JMIR Publications 2022-04-01 /pmc/articles/PMC9015759/ /pubmed/35363149 http://dx.doi.org/10.2196/32357 Text en ©Karamarie Fecho, Stanley C Ahalt, Stephen Appold, Saravanan Arunachalam, Emily Pfaff, Lisa Stillwell, Alejandro Valencia, Hao Xu, David B Peden. Originally published in JMIR Formative Research (https://formative.jmir.org), 01.04.2022. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Formative Research, is properly cited. The complete bibliographic information, a link to the original publication on https://formative.jmir.org, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Fecho, Karamarie Ahalt, Stanley C Appold, Stephen Arunachalam, Saravanan Pfaff, Emily Stillwell, Lisa Valencia, Alejandro Xu, Hao Peden, David B Development and Application of an Open Tool for Sharing and Analyzing Integrated Clinical and Environmental Exposures Data: Asthma Use Case |
title | Development and Application of an Open Tool for Sharing and Analyzing Integrated Clinical and Environmental Exposures Data: Asthma Use Case |
title_full | Development and Application of an Open Tool for Sharing and Analyzing Integrated Clinical and Environmental Exposures Data: Asthma Use Case |
title_fullStr | Development and Application of an Open Tool for Sharing and Analyzing Integrated Clinical and Environmental Exposures Data: Asthma Use Case |
title_full_unstemmed | Development and Application of an Open Tool for Sharing and Analyzing Integrated Clinical and Environmental Exposures Data: Asthma Use Case |
title_short | Development and Application of an Open Tool for Sharing and Analyzing Integrated Clinical and Environmental Exposures Data: Asthma Use Case |
title_sort | development and application of an open tool for sharing and analyzing integrated clinical and environmental exposures data: asthma use case |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9015759/ https://www.ncbi.nlm.nih.gov/pubmed/35363149 http://dx.doi.org/10.2196/32357 |
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