Literature DB >> 20064797

MedEx: a medication information extraction system for clinical narratives.

Hua Xu1, Shane P Stenner, Son Doan, Kevin B Johnson, Lemuel R Waitman, Joshua C Denny.   

Abstract

Medication information is one of the most important types of clinical data in electronic medical records. It is critical for healthcare safety and quality, as well as for clinical research that uses electronic medical record data. However, medication data are often recorded in clinical notes as free-text. As such, they are not accessible to other computerized applications that rely on coded data. We describe a new natural language processing system (MedEx), which extracts medication information from clinical notes. MedEx was initially developed using discharge summaries. An evaluation using a data set of 50 discharge summaries showed it performed well on identifying not only drug names (F-measure 93.2%), but also signature information, such as strength, route, and frequency, with F-measures of 94.5%, 93.9%, and 96.0% respectively. We then applied MedEx unchanged to outpatient clinic visit notes. It performed similarly with F-measures over 90% on a set of 25 clinic visit notes.

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Mesh:

Year:  2010        PMID: 20064797      PMCID: PMC2995636          DOI: 10.1197/jamia.M3378

Source DB:  PubMed          Journal:  J Am Med Inform Assoc        ISSN: 1067-5027            Impact factor:   4.497


  29 in total

1.  MEDSYNDIKATE--a natural language system for the extraction of medical information from findings reports.

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Authors:  P J Haug; L Christensen; M Gundersen; B Clemons; S Koehler; K Bauer
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4.  Towards a comprehensive medical language processing system: methods and issues.

Authors:  C Friedman
Journal:  Proc AMIA Annu Fall Symp       Date:  1997

5.  Automating concept identification in the electronic medical record: an experiment in extracting dosage information.

Authors:  D A Evans; N D Brownlow; W R Hersh; E M Campbell
Journal:  Proc AMIA Annu Fall Symp       Date:  1996

6.  A general natural-language text processor for clinical radiology.

Authors:  C Friedman; P O Alderson; J H Austin; J J Cimino; S B Johnson
Journal:  J Am Med Inform Assoc       Date:  1994 Mar-Apr       Impact factor: 4.497

7.  Experience with a mixed semantic/syntactic parser.

Authors:  P J Haug; S Koehler; L M Lau; P Wang; R Rocha; S M Huff
Journal:  Proc Annu Symp Comput Appl Med Care       Date:  1995

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Authors:  C Friedman; S M Huff; W R Hersh; E Pattison-Gordon; J J Cimino
Journal:  J Am Med Inform Assoc       Date:  1995 Jan-Feb       Impact factor: 4.497

9.  Unlocking clinical data from narrative reports: a study of natural language processing.

Authors:  G Hripcsak; C Friedman; P O Alderson; W DuMouchel; S B Johnson; P D Clayton
Journal:  Ann Intern Med       Date:  1995-05-01       Impact factor: 25.391

10.  Medical errors related to discontinuity of care from an inpatient to an outpatient setting.

Authors:  Carlton Moore; Juan Wisnivesky; Stephen Williams; Thomas McGinn
Journal:  J Gen Intern Med       Date:  2003-08       Impact factor: 5.128

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  211 in total

1.  Using Electronic Health Records To Generate Phenotypes For Research.

Authors:  Sarah A Pendergrass; Dana C Crawford
Journal:  Curr Protoc Hum Genet       Date:  2018-12-05

2.  Using Medical Text Extraction, Reasoning and Mapping System (MTERMS) to process medication information in outpatient clinical notes.

Authors:  Li Zhou; Joseph M Plasek; Lisa M Mahoney; Neelima Karipineni; Frank Chang; Xuemin Yan; Fenny Chang; Dana Dimaggio; Debora S Goldman; Roberto A Rocha
Journal:  AMIA Annu Symp Proc       Date:  2011-10-22

3.  Trends in biomedical informatics: most cited topics from recent years.

Authors:  Hyeon-Eui Kim; Xiaoqian Jiang; Jihoon Kim; Lucila Ohno-Machado
Journal:  J Am Med Inform Assoc       Date:  2011-12       Impact factor: 4.497

4.  Linguistic approach for identification of medication names and related information in clinical narratives.

Authors:  Thierry Hamon; Natalia Grabar
Journal:  J Am Med Inform Assoc       Date:  2010 Sep-Oct       Impact factor: 4.497

5.  Extracting Rx information from clinical narrative.

Authors:  James G Mork; Olivier Bodenreider; Dina Demner-Fushman; Rezarta Islamaj Dogan; François-Michel Lang; Zhiyong Lu; Aurélie Névéol; Lee Peters; Sonya E Shooshan; Alan R Aronson
Journal:  J Am Med Inform Assoc       Date:  2010 Sep-Oct       Impact factor: 4.497

6.  Extracting medical information from narrative patient records: the case of medication-related information.

Authors:  Louise Deléger; Cyril Grouin; Pierre Zweigenbaum
Journal:  J Am Med Inform Assoc       Date:  2010 Sep-Oct       Impact factor: 4.497

7.  Lancet: a high precision medication event extraction system for clinical text.

Authors:  Zuofeng Li; Feifan Liu; Lamont Antieau; Yonggang Cao; Hong Yu
Journal:  J Am Med Inform Assoc       Date:  2010 Sep-Oct       Impact factor: 4.497

Review 8.  Natural language processing systems for capturing and standardizing unstructured clinical information: A systematic review.

Authors:  Kory Kreimeyer; Matthew Foster; Abhishek Pandey; Nina Arya; Gwendolyn Halford; Sandra F Jones; Richard Forshee; Mark Walderhaug; Taxiarchis Botsis
Journal:  J Biomed Inform       Date:  2017-07-17       Impact factor: 6.317

Review 9.  Overview of the First Natural Language Processing Challenge for Extracting Medication, Indication, and Adverse Drug Events from Electronic Health Record Notes (MADE 1.0).

Authors:  Abhyuday Jagannatha; Feifan Liu; Weisong Liu; Hong Yu
Journal:  Drug Saf       Date:  2019-01       Impact factor: 5.606

10.  Automatic lymphoma classification with sentence subgraph mining from pathology reports.

Authors:  Yuan Luo; Aliyah R Sohani; Ephraim P Hochberg; Peter Szolovits
Journal:  J Am Med Inform Assoc       Date:  2014-01-15       Impact factor: 4.497

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