  Background Concept extraction, a subdomain of natural language processing
(NLP) with a focus on extracting concepts of interest, has been adopted to
computationally extract clinical information from text for a wide range of
applications ranging from clinical decision support to care quality
improvement.
  Objectives In this literature review, we provide a methodology review of
clinical concept extraction, aiming to catalog development processes, available
methods and tools, and specific considerations when developing clinical concept
extraction applications.
  Methods Based on the Preferred Reporting Items for Systematic Reviews and
Meta-Analyses (PRISMA) guidelines, a literature search was conducted for
retrieving EHR-based information extraction articles written in English and
published from January 2009 through June 2019 from Ovid MEDLINE In-Process &
Other Non-Indexed Citations, Ovid MEDLINE, Ovid EMBASE, Scopus, Web of Science,
and the ACM Digital Library.
  Results A total of 6,686 publications were retrieved. After title and
abstract screening, 228 publications were selected. The methods used for
developing clinical concept extraction applications were discussed in this
review.
