Semantic integration of clinical laboratory tests from electronic health records for deep phenotyping and biomarker discovery

dc.contributor.authorZhang, Xingmin Aaron
dc.contributor.authorYates, Amy
dc.contributor.authorVasilevsky, Nicole
dc.contributor.authorGourdine, J. P.
dc.contributor.authorCallahan, Tiffany J.
dc.contributor.authorCarmody, Leigh C.
dc.contributor.authorDanis, Daniel
dc.contributor.authorJoachimiak, Marcin P.
dc.contributor.authorRavanmehr, Vida
dc.contributor.authorPfaff, Emily R.
dc.contributor.authorChampion, James
dc.contributor.authorRobasky, Kimberly
dc.contributor.authorXu, Hao
dc.contributor.authorFecho, Karamarie
dc.contributor.authorWalton, Nephi A.
dc.contributor.authorZhu, Richard L.
dc.contributor.authorRamsdill, Justin
dc.contributor.authorMungall, Christopher J.
dc.contributor.authorKöhler, Sebastian
dc.contributor.authorHaendel, Melissa A.
dc.contributor.authorMcDonald, Clement J.
dc.contributor.authorVreeman, Daniel J.
dc.contributor.authorPeden, David B.
dc.contributor.authorBennett, Tellen D.
dc.contributor.authorFeinstein, James A.
dc.contributor.authorMartin, Blake
dc.contributor.authorStefanski, Adrianne L.
dc.contributor.authorHunter, Lawrence E.
dc.contributor.authorChute, Christopher G.
dc.contributor.authorRobinson, Peter N.
dc.contributor.departmentMedicine, School of Medicineen_US
dc.date.accessioned2019-08-14T15:46:57Z
dc.date.available2019-08-14T15:46:57Z
dc.date.issued2019
dc.description.abstractElectronic Health Record (EHR) systems typically define laboratory test results using the Laboratory Observation Identifier Names and Codes (LOINC) and can transmit them using Fast Healthcare Interoperability Resource (FHIR) standards. LOINC has not yet been semantically integrated with computational resources for phenotype analysis. Here, we provide a method for mapping LOINC-encoded laboratory test results transmitted in FHIR standards to Human Phenotype Ontology (HPO) terms. We annotated the medical implications of 2923 commonly used laboratory tests with HPO terms. Using these annotations, our software assesses laboratory test results and converts each result into an HPO term. We validated our approach with EHR data from 15,681 patients with respiratory complaints and identified known biomarkers for asthma. Finally, we provide a freely available SMART on FHIR application that can be used within EHR systems. Our approach allows readily available laboratory tests in EHR to be reused for deep phenotyping and exploits the hierarchical structure of HPO to integrate distinct tests that have comparable medical interpretations for association studies.en_US
dc.identifier.citationZhang, X. A., Yates, A., Vasilevsky, N., Gourdine, J. P., Callahan, T. J., Carmody, L. C., … Robinson, P. N. (2019). Semantic integration of clinical laboratory tests from electronic health records for deep phenotyping and biomarker discovery. NPJ digital medicine, 2, 32. doi:10.1038/s41746-019-0110-4en_US
dc.identifier.urihttps://hdl.handle.net/1805/20361
dc.language.isoen_USen_US
dc.publisherSpringer Natureen_US
dc.relation.isversionof10.1038/s41746-019-0110-4en_US
dc.relation.journalNPJ Digital Medicineen_US
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/*
dc.sourcePMCen_US
dc.subjectTranslational researchen_US
dc.subjectAsthmaen_US
dc.subjectPredictive markersen_US
dc.titleSemantic integration of clinical laboratory tests from electronic health records for deep phenotyping and biomarker discoveryen_US
dc.typeArticleen_US
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