A novel approach for exposing and sharing clinical data: the Translator Integrated Clinical and Environmental Exposures Service

Abstract

Objective: This study aimed to develop a novel, regulatory-compliant approach for openly exposing integrated clinical and environmental exposures data: the Integrated Clinical and Environmental Exposures Service (ICEES).

Materials and methods: The driving clinical use case for research and development of ICEES was asthma, which is a common disease influenced by hundreds of genes and a plethora of environmental exposures, including exposures to airborne pollutants. We developed a pipeline for integrating clinical data on patients with asthma-like conditions with data on environmental exposures derived from multiple public data sources. The data were integrated at the patient and visit level and used to create de-identified, binned, "integrated feature tables," which were then placed behind an OpenAPI.

Results: Our preliminary evaluation results demonstrate a relationship between exposure to high levels of particulate matter ≤2.5 µm in diameter (PM2.5) and the frequency of emergency department or inpatient visits for respiratory issues. For example, 16.73% of patients with average daily exposure to PM2.5 >9.62 µg/m3 experienced 2 or more emergency department or inpatient visits for respiratory issues in year 2010 compared with 7.93% of patients with lower exposures (n = 23 093).

Discussion: The results validated our overall approach for openly exposing and sharing integrated clinical and environmental exposures data. We plan to iteratively refine and expand ICEES by including additional years of data, feature variables, and disease cohorts.

Conclusions: We believe that ICEES will serve as a regulatory-compliant model and approach for promoting open access to and sharing of integrated clinical and environmental exposures data.

Keywords: clinical data; data harmonization; data integration; environmental data; open science; patient privacy; regulatory compliance; semantic harmonization.

Figure 1.

Overview of the process through which the Integrated Clinical and Environmental Exposures Service (ICEES) integrated feature tables are created, including the data sources used to generate the tables. Arrows indicate data processing/integration steps; red denotes private clinical data on patients in the Carolina Data Warehouse for Health; dark blue denotes public data on environmental exposures; light blue denotes stages of processing and integration of clinical data and environmental exposures data, conducted under an Institutional Review Board–approved protocol and within a secure environment; dark green denotes raw, de-identified ICEES integrated feature tables; light green denotes the ICEES OpenAPI and user interface. ACS: American Community Service; API: application programming interface; CAMP FHIR: Clinical Asset Mapping Program for Fast Healthcare Interoperability Resource; DOT: Department of Transportation; FHIR: HL7 Fast Healthcare Interoperability Resource; ID: identifier; IE CMAQ: Institute for the Environment Community Multiscale Air Quality Modeling System; FHIR PIT: FHIR Patient data Integration Tool; UI: user interface.

Figure 2.

The Integrated Clinical and Environmental Exposures Service application programming interface.

Figure 3.

(A) Hypothesis-driven 2 × 2 feature association and (B) exploratory 1 × N feature association demonstrating an association between exposure to particulate matter <=2.5 μm in diameter (PM2.5) and emergency department (ED) and/or inpatient visits for respiratory issues among patients with asthma-like conditions in year 2010 (n = 23 093). Input for the results shown in panel A: {“feature_a”:{“TotalEDInpatientVisits”:{“operator”:“<”,“value”:2}},“feature_b”:{“AvgDailyPM2.5Exposure”:{“operator”:“<”,“value”:3}}}; version: 1.0.0; table: patient; year: 2010; cohort_id: 22. Bins for the results shown in panel A: Bin 1 = 1.58–9.62 µg/m³; Bin 2 = 9.62–17.33 µg/m³. Input for the results shown in panel B: {“feature”:{“TotalEDInpatientVisits”:{“operator”:“<”, “value”:2}},“maximum_p_value”:0.1}; version: 1.0.0; table: patient; year: 2010; cohort_id: 22. Bins for the results shown in panel B: Bin 1 = 6.77–42.02 µg/m³; Bin 2 = 42.02–46.21 µg/m³; Bin 3 = 46.21–47.06 µg/m³; Bin 4 = 47.06–51.72 µg/m³; Bin 5 = 51.72–114.94 µg/m³.