Literature DB >> 18693886

Evaluation of the VA/KP problem list subset of SNOMED as a clinical terminology for electronic prescription clinical decision support.

Surendranath Mantena1, Gunther Schadow.   

Abstract

A standardized terminology for medical indications is essential for building e-prescription applications with decision support. The FDA has adopted the Veteran Administration and Kaiser Permanente (VA/KP) Problem List Subset of SNOMED as the terminology to represent indications in electronic labels. In this paper, we evaluate the ability of this subset to represent the text phrases extracted from a medication decision support system and the indications section of existing drug labels. We compiled a test set of 1265 distinct indication phrases and mapped them to (1) UMLS, (2) Entire SNOMED, (3) All Precoordinated concepts from the "Clinical Finding" hierarchy of SNOMED, and (4) VA/KP Subset. 95% of the phrases mapped to concepts in UMLS, 90.3% to SNOMED, 79.5% to SNOMED Precordinated and 71.1% mapped completely or partially to concepts in the VA/KP subset. Our study suggests that the VA/KP Subset has significant limitations for coding drug indications; however, when focusing on indications as medical conditions only, the coverage seems more adequate.

Mesh:

Year:  2007        PMID: 18693886      PMCID: PMC2655897     

Source DB:  PubMed          Journal:  AMIA Annu Symp Proc        ISSN: 1559-4076


  10 in total

1.  Effective mapping of biomedical text to the UMLS Metathesaurus: the MetaMap program.

Authors:  A R Aronson
Journal:  Proc AMIA Symp       Date:  2001

2.  Extracting structured information from free text pathology reports.

Authors:  Gunther Schadow; Clement J McDonald
Journal:  AMIA Annu Symp Proc       Date:  2003

3.  Clinical decision support in electronic prescribing: recommendations and an action plan: report of the joint clinical decision support workgroup.

Authors:  Jonathan M Teich; Jerome A Osheroff; Eric A Pifer; Dean F Sittig; Robert A Jenders
Journal:  J Am Med Inform Assoc       Date:  2005-03-31       Impact factor: 4.497

Review 4.  Interface terminologies: facilitating direct entry of clinical data into electronic health record systems.

Authors:  S Trent Rosenbloom; Randolph A Miller; Kevin B Johnson; Peter L Elkin; Steven H Brown
Journal:  J Am Med Inform Assoc       Date:  2006-02-24       Impact factor: 4.497

Review 5.  Medication-related clinical decision support in computerized provider order entry systems: a review.

Authors:  Gilad J Kuperman; Anne Bobb; Thomas H Payne; Anthony J Avery; Tejal K Gandhi; Gerard Burns; David C Classen; David W Bates
Journal:  J Am Med Inform Assoc       Date:  2006-10-26       Impact factor: 4.497

6.  The Medical Gopher--a microcomputer system to help find, organize and decide about patient data.

Authors:  C J McDonald; W M Tierney
Journal:  West J Med       Date:  1986-12

7.  Adverse drug events in ambulatory care.

Authors:  Tejal K Gandhi; Saul N Weingart; Joshua Borus; Andrew C Seger; Josh Peterson; Elisabeth Burdick; Diane L Seger; Kirstin Shu; Frank Federico; Lucian L Leape; David W Bates
Journal:  N Engl J Med       Date:  2003-04-17       Impact factor: 91.245

8.  Evaluating the coverage of controlled health data terminologies: report on the results of the NLM/AHCPR large scale vocabulary test.

Authors:  B L Humphreys; A T McCray; M L Cheh
Journal:  J Am Med Inform Assoc       Date:  1997 Nov-Dec       Impact factor: 4.497

9.  The epidemiology of prescribing errors: the potential impact of computerized prescriber order entry.

Authors:  Anne Bobb; Kristine Gleason; Marla Husch; Joe Feinglass; Paul R Yarnold; Gary A Noskin
Journal:  Arch Intern Med       Date:  2004-04-12

10.  Requirements on content and format of labeling for human prescription drug and biological products. Final rule.

Authors: 
Journal:  Fed Regist       Date:  2006-01-24
  10 in total
  8 in total

1.  Comparative analysis of the VA/Kaiser and NLM CORE problem subsets: an empirical study based on problem frequency.

Authors:  Adam Wright; Joshua Feblowitz; Allison B McCoy; Dean F Sittig
Journal:  AMIA Annu Symp Proc       Date:  2011-10-22

2.  Corpus-Based Problem Selection for EHR Note Summarization.

Authors:  Tielman T Van Vleck; Noémie Elhadad
Journal:  AMIA Annu Symp Proc       Date:  2010-11-13

3.  A survey of SNOMED CT direct users, 2010: impressions and preferences regarding content and quality.

Authors:  Gai Elhanan; Yehoshua Perl; James Geller
Journal:  J Am Med Inform Assoc       Date:  2011-08-11       Impact factor: 4.497

4.  Handling age specification in the SNOMED CT to ICD-10-CM cross-map.

Authors:  Junchuan Xu; Kin Wah Fung
Journal:  AMIA Annu Symp Proc       Date:  2012-11-03

5.  Mapping ASTI patient's therapeutic-data model to virtual Medical Record: can VMR represent therapeutic data elements used by ASTI in clinical guideline implementations?

Authors:  Vahid Ebrahiminia; Mobin Yasini; Jean Baptiste Lamy
Journal:  AMIA Annu Symp Proc       Date:  2013-11-16

6.  Identifying inconsistencies in SNOMED CT problem lists using structural indicators.

Authors:  Ankur Agrawal; Yehoshua Perl; Yan Chen; Gai Elhanan; Mei Liu
Journal:  AMIA Annu Symp Proc       Date:  2013-11-16

7.  A method and knowledge base for automated inference of patient problems from structured data in an electronic medical record.

Authors:  Adam Wright; Justine Pang; Joshua C Feblowitz; Francine L Maloney; Allison R Wilcox; Harley Z Ramelson; Louise I Schneider; David W Bates
Journal:  J Am Med Inform Assoc       Date:  2011-05-25       Impact factor: 4.497

8.  Comparison of Knowledge Levels Required for SNOMED CT Coding of Diagnosis and Operation Names in Clinical Records.

Authors:  Shine Young Kim; Hyung Hoi Kim; Kyung Hwa Shin; Hwa Sun Kim; Jae Il Lee; Byung Kwan Choi
Journal:  Healthc Inform Res       Date:  2012-09-30
  8 in total

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