Preliminary exploratory data analysis of simulated national clinical data research network for future use in annotation of a rare tumor biobanking initiative

Alex S. Felmeister, Angela Jae Waanders, Sarah E.S. Leary, Jeff Stevens, Jennifer L. Mason, Rachel Teneralli, Xiaohua Hu, L. Charles Bailey

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Observational data resources based on the capture of clinical data in the electronic health record (EHR) have produced significant learning opportunities in many areas of medicine. These large data resources can span multiple hospital systems and employ common semantics, ontologies, and data models. They have uncovered critical safety issues for patients, and spurred observational research and clinical decision support. In the age of precision medicine there is also an increased need to obtain genomic and clinical data to discover novel treatments for the deadliest of diseases. With this, there are efforts to create deep-dive disease specific repositories that include tissue in biobanks. The latter require significant human annotation of biospecimens. Securing the data is especially critical in rare pediatric brain tumors. In the specific case of The Children's Brain Tumor Tissue Consortium (CBTTC) an international rare pediatric brain tumor repository, the number of patients that need to be followed prospectively is outpacing the ability of human annotation. In this preliminary study, we perform a prescribed data exploration analysis on simulation data in the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) employed by the pediatric data network PEDSNet with the intention to ascertain feasibility in automatic annotation of patient records in the CBTTC.

Original languageEnglish (US)
Title of host publicationProceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
EditorsIllhoi Yoo, Jane Huiru Zheng, Yang Gong, Xiaohua Tony Hu, Chi-Ren Shyu, Yana Bromberg, Jean Gao, Dmitry Korkin
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2098-2104
Number of pages7
ISBN (Electronic)9781509030491
DOIs
StatePublished - Dec 15 2017
Event2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017 - Kansas City, United States
Duration: Nov 13 2017Nov 16 2017

Publication series

NameProceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
Volume2017-January

Other

Other2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
Country/TerritoryUnited States
CityKansas City
Period11/13/1711/16/17

Keywords

  • Data Mining
  • Health Data Acquisition
  • Health Informatics
  • Translational Research

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics

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