David A Hanauer1, Jill S Barnholtz-Sloan2,3, Mark F Beno2,3, Guilherme Del Fiol4, Eric B Durbin5,6, Oksana Gologorskaya7, Daniel Harris5,6, Brett Harnett8, Kensaku Kawamoto4, Benjamin May9, Eric Meeks7, Emily Pfaff10, Janie Weiss9, Kai Zheng11. 1. Department of Pediatrics, University of Michigan Medical School, Ann Arbor, MI. 2. Case Western Reserve University School of Medicine, Cleveland, OH. 3. Cleveland Institute for Computational Biology, Cleveland, OH. 4. Department of Biomedical Informatics, University of Utah, Salt Lake City, UT. 5. Markey Cancer Center, UK HealthCare, Lexington, KY. 6. Division of Biomedical Informatics, University of Kentucky, Lexington, KY. 7. Clinical and Translational Science Institute, University of California San Francisco, San Francisco, CA. 8. Department of Biomedical Informatics, University of Cincinnati College of Medicine, Cincinnati, OH. 9. Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY. 10. North Carolina Translational and Clinical Sciences Institute, University of North Carolina School of Medicine, Chapel Hill, NC. 11. Department of Informatics, University of California, Irvine, CA.
Abstract
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.
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.
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