{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,31]],"date-time":"2025-12-31T09:53:49Z","timestamp":1767174829689,"version":"build-2238731810"},"reference-count":33,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,1,15]],"date-time":"2025-01-15T00:00:00Z","timestamp":1736899200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2025,1,15]],"date-time":"2025-01-15T00:00:00Z","timestamp":1736899200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Med Inform Decis Mak"],"DOI":"10.1186\/s12911-024-02815-6","type":"journal-article","created":{"date-parts":[[2025,1,14]],"date-time":"2025-01-14T21:15:08Z","timestamp":1736889308000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["FHIR PIT: a geospatial and spatiotemporal data integration pipeline to support subject-level clinical research"],"prefix":"10.1186","volume":"25","author":[{"given":"Karamarie","family":"Fecho","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Juan J.","family":"Garcia","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hong","family":"Yi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Griffin","family":"Roupe","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ashok","family":"Krishnamurthy","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,1,15]]},"reference":[{"issue":"3","key":"2815_CR1","doi-asserted-by":"publisher","first-page":"309","DOI":"10.1093\/jamia\/ocx128","volume":"25","author":"C Brokamp","year":"2018","unstructured":"Brokamp C, Wolfe C, Lingren T, Harley J, Ryan P. Decentralized and reproducible geocoding and characterization of community and environmental exposures for multi-site studies. J Am Med Inform Assoc. 2018;25(3):309\u201314. https:\/\/doi.org\/10.1093\/jamia\/ocx128. https:\/\/degauss.org.","journal-title":"J Am Med Inform Assoc"},{"key":"2815_CR2","unstructured":"CAMP FHIR (Clinical Asset Mapping Program for HL7 Fast Healthcare Interoperability Resources), CAMP FHIR v1.0.4, released August 14, 2023. GitHub repository. https:\/\/github.com\/NCTraCSIDSci\/camp-fhir."},{"key":"2815_CR3","doi-asserted-by":"publisher","first-page":"291","DOI":"10.1007\/s40471-019-00205-5","volume":"6","author":"C Choirat","year":"2019","unstructured":"Choirat C, Braun D, Kioumourtzoglou M-A. Data science in environmental health research. Curr Epidemiol Rep. 2019;6:291\u20139.","journal-title":"Curr Epidemiol Rep"},{"key":"2815_CR4","doi-asserted-by":"publisher","unstructured":"Clark LP, Zilber D, Schmitt C, et al. A review of geospatial exposure models and approaches for health data integration. J Expo Sci Environ Epidemiol. Published online September 6, 2024. https:\/\/doi.org\/10.1038\/s41370-024-00712-8.","DOI":"10.1038\/s41370-024-00712-8"},{"key":"2815_CR5","doi-asserted-by":"publisher","first-page":"403","DOI":"10.3390\/toxics10070403","volume":"10","author":"Y Cui","year":"2022","unstructured":"Cui Y, Eccles KM, Kwok RK, Joubert BR, Messier KP, Balshaw DM, et al. Integrating multiscale geospatial environmental data into large population health studies: challenges and opportunities. Toxics. 2022;10:403.","journal-title":"Toxics"},{"key":"2815_CR6","unstructured":"The Dhall configuration language. https:\/\/dhall-lang.org\/."},{"key":"2815_CR7","unstructured":"Environmental Health Language Collaborative (EHLC). Environmental Health Language Collaborative: Harmonizing Data. Connecting Knowledge. Improving Health. December 11, 2023. https:\/\/www.niehs.nih.gov\/research\/programs\/ehlc."},{"key":"2815_CR8","doi-asserted-by":"publisher","unstructured":"Fecho K,* Ahalt SC, Appold S, Arunachalam S, Pfaff E, Stillwell L, Valencia A, Xu H, Peden D. Development and application of an open tool for sharing and analyzing integrated clinical and environmental exposures data: asthma use case. JMIR Form Res. 2022;6(4):e32357; https:\/\/doi.org\/10.2196\/32357.","DOI":"10.2196\/32357"},{"key":"2815_CR9","doi-asserted-by":"publisher","unstructured":"Fecho K,* Ahalt SC, Knowles M, Krishnamurthy A, Leigh M, Morton K, Pfaff E, Wang M, Yi H. Leveraging open electronic health record data and environmental exposures data to derive insights into rare pulmonary disease. Front Artif Intell. 2022;5:918888 (special issue on Biomedical Informatics Applications in Rare Diseases). https:\/\/doi.org\/10.3389\/frai.2022.918888.","DOI":"10.3389\/frai.2022.918888"},{"key":"2815_CR10","unstructured":"Fecho K,* Garantziotis S, Krishnamurthy A, Pfaff E, Schmitt C, Schurman S, Shuptrine S, Xu H, Ahalt A. Open integrated analysis of multi-institutional data using ICEES. AMIA 2021 Virtual Annual Informatics Summit, March 2021."},{"issue":"10","key":"2815_CR11","doi-asserted-by":"publisher","first-page":"1064","DOI":"10.1093\/jamia\/ocz042","volume":"26","author":"K Fecho","year":"2019","unstructured":"Fecho K, Pfaff E, Xu H, Champion J, Cox S, Stillwell L, Bizon C, Peden D, Krishnamurthy A, Tropsha A, Ahalt SC. A novel approach for exposing and sharing clinical data: the translator integrated clinical and environmental exposures service. J Am Med Inform Assoc. 2019;26(10):1064\u201373. https:\/\/doi.org\/10.1093\/jamia\/ocz042.","journal-title":"J Am Med Inform Assoc"},{"key":"2815_CR12","doi-asserted-by":"publisher","unstructured":"Fecho K, Thessen AE, Baranzini SE, et al. Progress toward a universal biomedical data translator [published online ahead of print, 2022 May 25]. Clin Transl Sci. 2022;15(8):1838\u201347. https:\/\/doi.org\/10.1111\/cts.13301.","DOI":"10.1111\/cts.13301"},{"key":"2815_CR13","unstructured":"FHIR PIT input data, 2024: UNC Health EHR data in FHIR format (https:\/\/www.unchealthcare.org\/); NIEHS Personalized Environment and Genes Study (PEGS) participant data (formerly known as Environmental Polymorphisms Registry) (https:\/\/www.niehs.nih.gov\/research\/clinical\/studies\/pegs\/index.cfm); US Environmental Protection Agency airborne pollutant exposures data (https:\/\/www.epa.gov\/hesc\/rsig-related-downloadable-data-files); US Department of Transportation, Federal Highway Administration, Highway Performance Monitoring System major roadway\/highway exposures data (http:\/\/www.fhwa.dot.gov\/policyinformation\/travel_monitoring\/pubs\/aadt\/); US Census Bureau Topologically Integrated Geographic Encoding and Referencing (TIGER)\/Line roadway data (http:\/\/www.census.gov\/geo\/maps-data\/data\/tiger-line.html); US Census Bureau American Community Survey socio-economic exposures data (https:\/\/www.census.gov\/programs-surveys\/acs\/data.html); NC Department of Environmental Quality concentrated animal feeding operations (CAFO) exposures data (https:\/\/deq.nc.gov\/cafo-map); NC Department of Environmental Quality landfill exposures data (https:\/\/www.nconemap.gov\/datasets\/ncdenr::active-permitted-landfills\/about); and National Center for Education Statistics (https:\/\/nces.ed.gov\/datatools\/)."},{"key":"2815_CR14","unstructured":"Garcia JJ, Yi H, Fecho K, Krishnamurthy A. FHIR-PIT: Link FHIR records with environmental exposures. Poster presentation at BioIt World 2023, May 16-18, 2023."},{"issue":"122","key":"2815_CR15","doi-asserted-by":"publisher","first-page":"103","DOI":"10.1016\/j.cageo.2018.10.009","volume":"2019","author":"S Goodman","year":"2019","unstructured":"Goodman S, BenYishay A, Lv Z, Runfola D. GeoQuery: Integrating HPC systems and public web-based geospatial data tools. Comp Geosci. 2019;2019(122):103\u201312.","journal-title":"Comp Geosci"},{"key":"2815_CR16","doi-asserted-by":"publisher","first-page":"827","DOI":"10.1080\/10643389.2022.2093595","volume":"53","author":"H Hu","year":"2023","unstructured":"Hu H, Liu X, Zheng Y, He X, Hart J, James P, et al. Methodological challenges in spatial and contextual exposome-health studies. Crit Rev Environ Sci Technol. 2023;53:827\u201346.","journal-title":"Crit Rev Environ Sci Technol"},{"key":"2815_CR17","doi-asserted-by":"publisher","unstructured":"Lan B,* Haaland P, Krishnamurthy A, Peden DB, Schmitt PL, Sharma P, Sinha M, Xu H, Fecho K. Open application of statistical and machine learning models to explore the impact of environmental exposures on health and disease: an asthma use case. Int J Environ Res Public Health 2021;18(21):11398 [published as part of a special issue titled \u201cApplication of Biostatistical Modelling in Public Health and Epidemiology\u201d]; https:\/\/doi.org\/10.3390\/ijerph182111398.","DOI":"10.3390\/ijerph182111398"},{"issue":"12","key":"2815_CR18","doi-asserted-by":"publisher","first-page":"1882","DOI":"10.1289\/EHP92","volume":"124","author":"MC Mirabelli","year":"2016","unstructured":"Mirabelli MC, Vaidyanathan A, Flanders WD, Qin X, Garbe P. Outdoor PM2.5, Ambient air temperature, and asthma symptoms in the past 14 days among adults with active asthma. Environ Health Perspect. 2016;124(12):1882\u201390. https:\/\/doi.org\/10.1289\/EHP92.","journal-title":"Environ Health Perspect."},{"key":"2815_CR19","unstructured":"NumFOCUS, Inc. pandas.cut. 2024. https:\/\/pandas.pydata.org\/pandas-docs\/stable\/reference\/api\/pandas.cut.html."},{"key":"2815_CR20","unstructured":"NumFOCUS, Inc. pandas.qcut. 2024. https:\/\/pandas.pydata.org\/pandas-docs\/stable\/reference\/api\/pandas.qcut.html."},{"key":"2815_CR21","unstructured":"US Department of Health and Human Services (US DHHS). Health Insurance Privacy and Accountability Act, Safe Harbor Method for De-identification. October 25, 2022. https:\/\/www.hhs.gov\/hipaa\/for-professionals\/privacy\/special-topics\/de-identification\/index.html."},{"key":"2815_CR22","unstructured":"RENCI Environmental Exposures APIs (undated). Socioeconomic Exposures Service, https:\/\/bdt-social.renci.org\/socio_environmental_exposures_api\/v1\/ui\/; Airborne Pollutant Exposures Service, https:\/\/bdt-cmaq.renci.org\/cmaq_exposures_api\/v1\/ui\/; Roadway Exposures Service, https:\/\/bdt-proximity.renci.org\/roadway_proximity_api\/v1\/ui\/."},{"key":"2815_CR23","doi-asserted-by":"publisher","unstructured":"Pfaff ER, Champion J, Bradford RL, Clark M, Xu H, Fecho K, Krishnamurthy A, Cox S, Chute CG, Overby Taylor C, Ahalt S. Fast Healthcare Interoperability Resources (FHIR) as a meta model to integrate common data models: development of a tool and quantitative validation study. JMIR Med Inform. 2019;7(4):e15199. https:\/\/doi.org\/10.2196\/15199. https:\/\/github.com\/NCTraCSIDSci\/camp-fhir.","DOI":"10.2196\/15199"},{"key":"2815_CR24","doi-asserted-by":"publisher","unstructured":"Sharma P,* Haaland P, Krishnamurthy A, Lan B, Schmitt PL, Sinha M, Xu H, Fecho K. Evaluating robustness of a generalized linear model when applied to electronic health record data accessed using an openAPI. Health Inform J. 2023;29(2); https:\/\/doi.org\/10.1177\/14604582231170892.","DOI":"10.1177\/14604582231170892"},{"key":"2815_CR25","unstructured":"US Centers for Disease Control and Prevention (US CDC). (2023). National Environmental Public Health Tracking Network Data Explorer. https:\/\/ephtracking.cdc.gov\/DataExplorer\/."},{"key":"2815_CR26","unstructured":"US Department of Health and Human Services, Form Approved OMB# 0990\u20130379, Expiration Date 8\/31\/2023. https:\/\/www.hhs.gov\/hipaa\/for-professionals\/privacy\/special-topics\/de-identification\/index.html#safeharborguidance."},{"key":"2815_CR27","unstructured":"US Environmental Protection Agency (EPA). National Ambient Air Quality Standards (NAAQS) for PM. March 6, 2024. https:\/\/www.epa.gov\/pm-pollution\/national-ambient-air-quality-standards-naaqs-pm."},{"key":"2815_CR28","unstructured":"US NASA Socioeconomic Data and Applications Center (SEDAC). (2023). SEDAC: A data center in NASA's Earth Observing System Data and Information System (EOSDIS)- Hosted by CIESIN at Columbia University. https:\/\/sedac.ciesin.columbia.edu."},{"issue":"14","key":"2815_CR29","doi-asserted-by":"publisher","first-page":"5243","DOI":"10.3390\/ijerph17145243","volume":"17","author":"A Valencia","year":"2020","unstructured":"Valencia A, Stillwell L, Appold S, Arunachalam S, Cox S, Xu H, Schmitt CP, Schurman SH, Garantziotis S, Xue W, Ahalt SC, Fecho K. Translator Exposure APIs: open access to data on airborne pollutant exposures, roadway exposures, and socio-environmental exposures and use case application. IJERHP. 2020;17(14):5243. https:\/\/doi.org\/10.3390\/ijerph17145243.","journal-title":"IJERHP"},{"key":"2815_CR30","doi-asserted-by":"publisher","first-page":"105887","DOI":"10.1016\/j.envint.2020.105887","volume":"143","author":"P Vineis","year":"2020","unstructured":"Vineis P, Robinson O, Chadeau-Hyam M, Dehghan A, Mudway I, Dagnino S. What is new in the exposome? Environ Int. 2020;143:105887. https:\/\/doi.org\/10.1016\/j.envint.2020.105887.","journal-title":"Environ Int"},{"key":"2815_CR31","doi-asserted-by":"publisher","first-page":"1847","DOI":"10.1158\/1055-9965.EPI-05-0456","volume":"14","author":"CP Wild","year":"2005","unstructured":"Wild CP. Complementing the genome with an \u201cexposome\u201d: the outstanding challenge of environmental exposure measurement in molecular epidemiology. Cancer Epidemiol Biomarkers Prev. 2005;14:1847\u201350.","journal-title":"Cancer Epidemiol Biomarkers Prev"},{"key":"2815_CR32","doi-asserted-by":"publisher","first-page":"53","DOI":"10.21203\/rs.2.19633\/v1","volume":"20","author":"H Xu","year":"2020","unstructured":"Xu H, Cox S, Stillwell L, Pfaff E, Champion J, Ahalt SC, Fecho K. FHIR PIT: an open software application for spatiotemporal integration of clinical data and environmental exposures data. BMC Med Inform Decis Mak. 2020;20:53. https:\/\/doi.org\/10.21203\/rs.2.19633\/v1.","journal-title":"BMC Med Inform Decis Mak."},{"key":"2815_CR33","unstructured":"Yi H. pcornet-to-fhir mapping tool. 2024. https:\/\/github.com\/RENCI\/tx-pcornet-to-fhir."}],"updated-by":[{"DOI":"10.1186\/s12911-025-02940-w","type":"correction","label":"Correction","source":"publisher","updated":{"date-parts":[[2025,2,25]],"date-time":"2025-02-25T00:00:00Z","timestamp":1740441600000}}],"container-title":["BMC Medical Informatics and Decision Making"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12911-024-02815-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s12911-024-02815-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12911-024-02815-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,2,26]],"date-time":"2025-02-26T02:29:43Z","timestamp":1740536983000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcmedinformdecismak.biomedcentral.com\/articles\/10.1186\/s12911-024-02815-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,1,15]]},"references-count":33,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["2815"],"URL":"https:\/\/doi.org\/10.1186\/s12911-024-02815-6","relation":{},"ISSN":["1472-6947"],"issn-type":[{"value":"1472-6947","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,1,15]]},"assertion":[{"value":"14 June 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 December 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 January 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"25 February 2025","order":4,"name":"change_date","label":"Change Date","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"Correction","order":5,"name":"change_type","label":"Change Type","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"A Correction to this paper has been published:","order":6,"name":"change_details","label":"Change Details","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"https:\/\/doi.org\/10.1186\/s12911-025-02940-w","URL":"https:\/\/doi.org\/10.1186\/s12911-025-02940-w","order":7,"name":"change_details","label":"Change Details","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The work described in this manuscript was approved by the Institutional Review Board at the University of North Carolina at Chapel Hill (studies #16\u20132978 [asthma] and #21\u20130099 [PCD]).","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"24"}}