TitleSemantic integration of clinical laboratory tests from electronic health records for deep phenotyping and biomarker discovery.
Publication TypeJournal Article
Year of Publication2019
AuthorsZhang XAaron, Yates A, Vasilevsky N, Gourdine JP, Callahan TJ, Carmody LC, Danis D, Joachimiak MP, Ravanmehr V, Pfaff ER, Champion J, Robasky K, Xu H, Fecho K, Walton NA, Zhu RL, Ramsdill J, Mungall CJ, Köhler S, Haendel MA, McDonald CJ, Vreeman DJ, Peden DB, Bennett TD, Feinstein JA, Martin B, Stefanski AL, Hunter LE, Chute CG, Robinson PN
JournalNPJ Digit Med
Date Published2019

Electronic 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.

Alternate JournalNPJ Digit Med
PubMed ID31119199
PubMed Central IDPMC6527418
Grant ListK23 HD091295 / HD / NICHD NIH HHS / United States