Electronic medical record search engine (EMERSE): An information retrieval tool for supporting cancer research

David A. Hanauer, Jill S. Barnholtz-Sloan, Mark F. Beno, Guilherme Del Fiol, Eric B. Durbin, Oksana Gologorskaya, Daniel Harris, Brett Harnett, Kensaku Kawamoto, Benjamin May, Eric Meeks, Emily Pfaff, Janie Weiss, Kai Zheng

Research output: Contribution to journalReview articlepeer-review

17 Scopus citations


PURPOSE The Electronic Medical Record Search Engine (EMERSE) is a software tool built to aid research spanning cohort discovery, population health, and data abstraction for clinical trials. EMERSE is now live at three academic medical centers, with additional sites currently working on implementation. In this report, we describe how EMERSE has been used to support cancer research based on a variety of metrics. METHODS We identified peer-reviewed publications that used EMERSE through online searches as well as through direct e-mails to users based on audit logs. These logs were also used to summarize use at each of the three sites. Search terms for two of the sites were characterized using the natural language processing tool MetaMap to determine to which semantic types the terms could be mapped. RESULTS We identified a total of 326 peer-reviewed publications that used EMERSE through August 2019, although this is likely an underestimation of the true total based on the use log analysis. Oncology-related research comprised nearly one third (n = 105; 32.2%) of all research output. The use logs showed that EMERSE had been used by multiple people at each site (nearly 3,500 across all three) who had collectively logged into the system. 100,000 times. Many user-entered search queries could not be mapped to a semantic type, but the most common semantic type for terms that did match was “disease or syndrome,” followed by “pharmacologic substance.” CONCLUSION EMERSE has been shown to be a valuable tool for supporting cancer research. It has been successfully deployed at other sites, despite some implementation challenges unique to each deployment environment.

Original languageEnglish
Pages (from-to)454-463
Number of pages10
JournalJCO clinical cancer informatics
StatePublished - 2020

Bibliographical note

Funding Information:
Supported in part by National Cancer Institute (NCI) Informatics Technology for Cancer Research, National Institutes of Health (NIH), Grant No. 1U24CA204863-01A1 and Clinical and Translational Science Award (CTSA)–supported Michigan Institute for Clinical and Translational Research Grant No. UL1TR002240; by the Cleveland Institute for Computational Biology and the Clinical and Translational Science Collaborative (CTSC) of Cleveland, funded by NIH National Center for Advancing Translational Science (NCATS) CTSA Grant No. UL1TR002548; by the North Carolina Translational and Clinical Sciences Institute, funded by NIH NCATS Grant No. UL1TR002489; and by the Markey Cancer Center Cancer Research Informatics Shared

Publisher Copyright:
© 2020 by American Society of Clinical Oncology

ASJC Scopus subject areas

  • Medicine (all)


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