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 (PM2.5) 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.
ABSTRACT
Environmental exposures have profound effects on health and disease. While public repositories exist for a variety of exposures data, these are generally difficult to access, navigate, and interpret. We describe the research, development, and application of three open application programming interfaces (APIs) that support access to usable, nationwide, exposures data from three public repositories: airborne pollutant estimates from the US Environmental Protection Agency; roadway data from the US Department of Transportation; and socio-environmental exposures from the US Census Bureau's American Community Survey. Three open APIs were successfully developed, deployed, and tested using random latitude/longitude values and time periods as input parameters. After confirming the accuracy of the data, we used the APIs to extract exposures data on 2550 participants from a cohort within the Environmental Polymorphisms Registry (EPR) at the National Institute of Environmental Health Sciences, and we successfully linked the exposure estimates with participant-level data derived from the EPR. We then conducted an exploratory, proof-of-concept analysis of the integrated data for a subset of participants with self-reported asthma and largely replicated our prior findings on the impact of select exposures and demographic factors on asthma exacerbations. Together, the three open exposures APIs provide a valuable resource, with application across environmental and public health fields.
