Clinical Data: Sources and Types, Regulatory Constraints, Applications

Appold

et al. 2020

IJERPH

Self Cite

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.

Section: Discussionsupporting

confidence: 88%

Section: Discussionsupporting

confidence: 68%

Translator Exposure APIs: Open Access to Data on Airborne Pollutant Exposures, Roadway Exposures, and Socio-Environmental Exposures and Use Case Application

Valencia

Appold

et al. 2020

IJERPH

Self Cite

“…The validation data set consisted of~160,000 patients with "asthma-like" conditions from UNC Health Care System and the environmental data sources depicted in Fig. 1, focusing initially on data from calendar year 2010 [19][20][21]. FHIR PIT was used to integrate the clinical and environmental data and then de-identify the data and bin feature variables before openly exposing the integrated data using ICEES.…”

Section: Resultsmentioning

confidence: 99%

FHIR PIT: an open software application for spatiotemporal integration of clinical data and environmental exposures data

Cox

BMC Med Inform Decis Mak

et al. 2020

Self Cite

Background: Informatics tools to support the integration and subsequent interrogation of spatiotemporal data such as clinical data and environmental exposures data are lacking. Such tools are needed to support research in environmental health and any biomedical field that is challenged by the need for integrated spatiotemporal data to examine individual-level determinants of health and disease. Results: We have developed an open-source software application-FHIR PIT (Health Level 7 Fast Healthcare Interoperability Resources Patient data Integration Tool)-to enable studies on the impact of individual-level environmental exposures on health and disease. FHIR PIT was motivated by the need to integrate patient data derived from our institution's clinical warehouse with a variety of public data sources on environmental exposures and then openly expose the data via ICEES (Integrated Clinical and Environmental Exposures Service). FHIR PIT consists of transformation steps or building blocks that can be chained together to form a transformation and integration workflow. Several transformation steps are generic and thus can be reused. As such, new types of data can be incorporated into the modular FHIR PIT pipeline by simply reusing generic steps or adding new ones. We validated FHIR PIT in the context of a driving use case designed to investigate the impact of airborne pollutant exposures on asthma. Specifically, we replicated published findings demonstrating racial disparities in the impact of airborne pollutants on asthma exacerbations. Conclusions: While FHIR PIT was developed to support our driving use case on asthma, the software can be used to integrate any type and number of spatiotemporal data sources at a level of granularity that enables individual-level study. We expect FHIR PIT to facilitate research in environmental health and numerous other biomedical disciplines.

“…We validated FHIR PIT in the context of our driving use case for research and development of ICEES: impact of airborne pollutant exposures on asthma. The validation data set consisted of ~160,000 patients with "asthma-like" conditions from UNC Health Care System and the environmental data sources depicted in Figure 1, focusing initially on data from calendar year 2010 [19][20][21]. FHIR PIT was used to integrate the clinical and environmental data and then de-identify the data and bin feature variables before openly exposing the integrated data using ICEES.…”

Section: Resultsmentioning

confidence: 99%

FHIR PIT: an open software application for spatiotemporal integration of clinical data and environmental exposures data

Cox

et al. 2020

Preprint

Self Cite

Background Informatics tools to support the integration and subsequent interrogation of spatiotemporal data such as clinical data and environmental exposures data are lacking. Such tools are needed to support research in environmental health and any biomedical field that is challenged by the need for integrated spatiotemporal data to examine individual-level determinants of health and disease. Results We have developed an open-source software application—FHIR PIT (Health Level 7 Fast Healthcare Interoperability Resources Patient data Integration Tool)—to enable studies on the impact of individual-level environmental exposures on health and disease. FHIR PIT was motivated by the need to integrate patient data derived from our institution’s clinical warehouse with a variety of public data sources on environmental exposures and then openly expose the data via ICEES (Integrated Clinical and Environmental Exposures Service). FHIR PIT consists of transformation steps or building blocks that can be chained together to form a transformation and integration workflow. Several transformation steps are generic and thus can be reused. As such, new types of data can be incorporated into the modular FHIR PIT pipeline by simply reusing generic steps or adding new ones. We have validated FHIR PIT in the context of a driving use case designed to investigate the impact of airborne pollutant exposures on asthma. Specifically, we replicated published findings demonstrating racial disparities in the impact of airborne pollutants on asthma exacerbations. Conclusions While FHIR PIT was developed to support our driving use case, the software can be used to integrate any type and number of spatiotemporal data sources at a level of granularity that enables individual-level study. We expect FHIR PIT to facilitate research in environmental health and numerous other biomedical disciplines.