Roadmap to a comprehensive clinical data warehouse for precision medicine applications in oncology

David J. Foran, Wenjin Chen, Huiqi Chu, Evita Sadimin, Doreen Loh, Gregory Riedlinger, Lauri A. Goodell, Shridar Ganesan, Kim Hirshfield, Lorna Rodriguez, Robert S. Dipaola

Research output: Contribution to journalArticlepeer-review

29 Scopus citations

Abstract

Leading institutions throughout the country have established Precision Medicine programs to support personalized treatment of patients. A cornerstone for these programs is the establishment of enterprise-wide Clinical Data Warehouses. Working shoulder-to-shoulder, a team of physicians, systems biologists, engineers, and scientists at Rutgers Cancer Institute of New Jersey have designed, developed, and implemented the Warehouse with information originating from data sources, including Electronic Medical Records, Clinical Trial Management Systems, Tumor Registries, Biospecimen Repositories, Radiology and Pathology archives, and Next Generation Sequencing services. Innovative solutions were implemented to detect and extract unstructured clinical information that was embedded in paper/text documents, including synoptic pathology reports. Supporting important precision medicine use cases, the growing Warehouse enables physicians to systematically mine and review the molecular, genomic, image-based, and correlated clinical information of patient tumors individually or as part of large cohorts to identify changes and patterns that may influence treatment decisions and potential outcomes.

Original languageEnglish
Article number1176935117694349
JournalCancer Informatics
Volume16
DOIs
StatePublished - Mar 2 2017

Bibliographical note

Publisher Copyright:
© The Author(s) 2017.

Keywords

  • Clinical data warehouse
  • Precision medicine
  • Semantic interoperability
  • Synoptic pathology reports

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

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