Ease of adoption of clinical natural language processing software: An evaluation of five systems.

Journal: Journal of biomedical informatics
PMID: 26210361

Abstract

OBJECTIVE: In recognition of potential barriers that may inhibit the widespread adoption of biomedical software, the 2014 i2b2 Challenge introduced a special track, Track 3 - Software Usability Assessment, in order to develop a better understanding of the adoption issues that might be associated with the state-of-the-art clinical NLP systems. This paper reports the ease of adoption assessment methods we developed for this track, and the results of evaluating five clinical NLP system submissions.

Authors

  • Kai Zheng
    University of California, Irvine, Irvine, CA, USA.
  • V G Vinod Vydiswaran
    Department of Learning Health Sciences, University of Michigan Medical School, Ann Arbor, MI, USA.
  • Yang Liu
    Department of Computer Science, Hong Kong Baptist University, Hong Kong, China.
  • Yue Wang
    Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.
  • Amber Stubbs
    School of Library and Information Science, Simmons College, Boston, MA, USA. Electronic address: stubbs@simmons.edu.
  • Ozlem Uzuner
    Department of Information Studies, University at Albany, SUNY. Albany, NY.
  • Anupama E Gururaj
    The University of Texas School of Biomedical Informatics at Houston, Houston, TX, USA.
  • Samuel Bayer
    The MITRE Corporation, Bedford, MA, USA.
  • John Aberdeen
    The MITRE Corporation, Bedford, MA, USA.
  • Anna Rumshisky
    Department of Computer Science, University of Massachusetts Lowell. Lowell, MA.
  • Serguei Pakhomov
    Institute for Health Informatics, University of Minnesota, Minneapolis, Minnesota, USA.
  • Hongfang Liu
    Department of Artificial Intelligence & Informatics, Mayo Clinic, Rochester, MN, United States.
  • Hua Xu
    Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.

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