Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2018 Jan:77:34-49.
doi: 10.1016/j.jbi.2017.11.011. Epub 2017 Nov 21.

Clinical information extraction applications: A literature review

Yanshan Wang  1 , Liwei Wang  1 , Majid Rastegar-Mojarad  1 , Sungrim Moon  1 , Feichen Shen  1 , Naveed Afzal  1 , Sijia Liu  1 , Yuqun Zeng  1 , Saeed Mehrabi  1 , Sunghwan Sohn  1 , Hongfang Liu  2
Affiliations
Review

Clinical information extraction applications: A literature review

Yanshan Wang et al. J Biomed Inform. 2018 Jan.

Abstract

Background: With the rapid adoption of electronic health records (EHRs), it is desirable to harvest information and knowledge from EHRs to support automated systems at the point of care and to enable secondary use of EHRs for clinical and translational research. One critical component used to facilitate the secondary use of EHR data is the information extraction (IE) task, which automatically extracts and encodes clinical information from text.

Objectives: In this literature review, we present a review of recent published research on clinical information extraction (IE) applications.

Methods: A literature search was conducted for articles published from January 2009 to September 2016 based on Ovid MEDLINE In-Process & Other Non-Indexed Citations, Ovid MEDLINE, Ovid EMBASE, Scopus, Web of Science, and ACM Digital Library.

Results: A total of 1917 publications were identified for title and abstract screening. Of these publications, 263 articles were selected and discussed in this review in terms of publication venues and data sources, clinical IE tools, methods, and applications in the areas of disease- and drug-related studies, and clinical workflow optimizations.

Conclusions: Clinical IE has been used for a wide range of applications, however, there is a considerable gap between clinical studies using EHR data and studies using clinical IE. This study enabled us to gain a more concrete understanding of the gap and to provide potential solutions to bridge this gap.

Keywords: Application; Clinical notes; Electronic health records; Information extraction; Natural language processing.

PubMed Disclaimer

Conflict of interest statement

Competing Interests

None.

Conflict statement

We have nothing to disclose.

Figures

Figure 1
Figure 1
The number of natural language processing (NLP)-related articles compared to the number of electronic health record (EHR) articles from 2002 through 2015.
Figure 2
Figure 2
Article selection flow chart.
Figure 3
Figure 3
Categorization of publication venues.
Figure 4
Figure 4
Distribution of included studies, stratified by category and year (from January 1, 2009, to September 6, 2016).
Figure 5
Figure 5
The distribution of studies in terms of clinical narrative data utilized per year.
See this image and copyright information in PMC

References

    1. Blumenthal D. Launching hitech. New England Journal of Medicine. 2010;362:382–5. - PubMed
    1. Ellsworth MA, Dziadzko M, O’Horo JC, Farrell AM, Zhang J, Herasevich V. An appraisal of published usability evaluations of electronic health records via systematic review. J Am Med Inform Assoc. 2017;24:218–26. - PMC - PubMed
    1. Goldstein BA, Navar AM, Pencina MJ, Ioannidis J. Opportunities and challenges in developing risk prediction models with electronic health records data: a systematic review. J Am Med Inform Assoc. 2017;24:198–208. - PMC - PubMed
    1. Jensen K, Soguero-Ruiz C, Mikalsen KO, Lindsetmo R-O, Kouskoumvekaki I, Girolami M, et al. Analysis of free text in electronic health records for identification of cancer patient trajectories. Scientific Reports. 2017:7. - PMC - PubMed
    1. Sarawagi S. Information extraction. Foundations and Trends® in Databases. 2008;1:261–377.

Publication types