ArticleBMC medical informatics and decision making2025
FHIR PIT: a geospatial and spatiotemporal data integration pipeline to support subject-level clinical research.
Article in BMC medical informatics and decision making, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Not yet cited in PubMed.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Corrections and comments
- Erratum issued
Authors and funding
5 authors.
Funding
Abstract
backgroundEnvironmental exposures such as airborne pollutant exposures and socio-economic indicators are increasingly recognized as important to consider when conducting clinical research using electronic health record (EHR) data or other sources of clinical data such as survey data. While numerous public sources of geospatial and spatiotemporal data are available to support such research, the data are challenging to work with due to inconsistencies in file formats and spatiotemporal resolutions, computational challenges with large file sizes, and a lack of tools for patient- or subject-level data integration.
resultsWe developed FHIR PIT (HL7® Fast Healthcare Interoperability Resources Patient data Integration Tool) as an open-source, modular, data-integration software pipeline that consumes EHR data in FHIR® format and integrates the data at the level of the patient or subject with environmental exposures data of varying spatiotemporal resolutions and file formats. We applied FHIR PIT to generate "integrated feature tables" containing patient- or subject-level EHR data integrated with environmental exposures data on two cohorts: one on patients with asthma and related common pulmonary disorders; and a second on patients with primary ciliary dyskinesia and related rare pulmonary disorders. The data were then exposed via the open Integrated Clinical and Environmental Exposures Service, which was then queried to explore relationships between exposures to two representative airborne pollutants (particulate matter and ozone) and annual emergency department or inpatient visits for respiratory issues. We found that hospitalizations for respiratory issues were more common among patients exposed to relatively high levels of particulate matter and ozone and were higher overall among patients with primary ciliary dyskinesia than among patients with asthma.
conclusionsOur manuscript describes a major release of FHIR PIT v1.0 and includes a technical demonstration use case and a clinical application on the use of FHIR PIT to support research on environmental exposures and health outcomes related to asthma and primary ciliary dyskinesia. For application of the tool to common data models (CDMs) other than FHIR, we offer open-source conversion tools to map from the PCORnet, i2b2, and OMOP CDMs to FHIR.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.