Development and Application of an Open Tool for Sharing and Analyzing Integrated Clinical and Environmental Exposures Data: Asthma Use Case

Karamarie Fecho; Stanley C Ahalt; Stephen Appold; Saravanan Arunachalam; Emily Pfaff; Lisa Stillwell; Alejandro Valencia; Hao Xu; David B Peden

doi:10.2196/32357

Development and Application of an Open Tool for Sharing and Analyzing Integrated Clinical and Environmental Exposures Data: Asthma Use Case

JMIR Form Res. 2022 Apr 1;6(4):e32357. doi: 10.2196/32357.

Authors

Affiliations

¹ Renaissance Computing Institute, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.
² Kenan-Flagler Business School, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.
³ Institute for the Environment, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.
⁴ North Carolina Translational and Clinical Sciences Institute, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.
⁵ Division of Allergy & Immunology, Department of Pediatrics, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.
⁶ Center for Environmental Medicine, Asthma and Lung Biology, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.

PMID: 35363149
PMCID: PMC9015759
DOI: 10.2196/32357

Abstract

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.

Keywords: airborne pollutant exposures; asthma exacerbation; electronic health records; medication exposures; open patient data; socioeconomic exposures.

©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.

Abstract

Grants and funding