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Indexing electronic medical records using a taxonomy

Published: 01 November 2013 Publication History

Abstract

With the move toward patient electronic medical records (EMRs), accessing information for insurance coding and research depends on standardized taxonomies to organize and index the content. Controlled vocabularies are necessary to interpret content consistently. Established quasi-taxonomies provide codes for medical conditions and treatments, but applying these codes as metadata to index the records is laborious, requiring translation from natural language in the EMR to a code's verbal equivalent to the code itself. Indexing systems can streamline the categorization process for greater efficiency and accuracy by using Bayesian engines or a rule-based approach. Analyzing discrepancies between human indexing and the software system results shows where editorial intervention is needed for continual improvement, with a goal of 85% or higher accuracy. Using a categorization system with a hierarchical taxonomy enables deep, precise indexing or quick, automatic filtering to more general concepts. The accuracy of medical indexing systems varies widely, based on the degree of automation and capacity for semantic analysis.

References

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Kern, L.M. 2013. Accuracy of electronically reported "meaningful use" clinical quality measures: A cross-sectional study. Annals of Internal Medicine. 2013: 158 (2): 77--83 DOI=10.7326/0003--4819--158--2--201301150-00001.
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  • (2015)Annotation of Chest Radiology Reports forźIndexing and RetrievalRevised Selected Papers from the First International Workshop on Multimodal Retrieval in the Medical Domain - Volume 905910.1007/978-3-319-24471-6_9(99-111)Online publication date: 29-Mar-2015

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cover image ACM Conferences
DARE '13: Proceedings of the 2013 international workshop on Data management & analytics for healthcare
November 2013
34 pages
ISBN:9781450324250
DOI:10.1145/2512410
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 November 2013

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Author Tags

  1. electronic medical records
  2. knowledge bases
  3. machine-aided indexing
  4. semantic analysis
  5. subject indexing
  6. taxonomies
  7. thesauris

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CIKM'13
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DARE '13 Paper Acceptance Rate 5 of 7 submissions, 71%;
Overall Acceptance Rate 5 of 7 submissions, 71%

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  • (2015)Annotation of Chest Radiology Reports forźIndexing and RetrievalRevised Selected Papers from the First International Workshop on Multimodal Retrieval in the Medical Domain - Volume 905910.1007/978-3-319-24471-6_9(99-111)Online publication date: 29-Mar-2015

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