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An Efficient, Clinically-Natural Electronic Medical Record System that Produces Computable Data
Current commercially-available electronic medical record systems produce mainly text-based information focused on financial and regulatory performance. We combined an existing method for organizing complex computer systems—which we label activity-based design—with a proven approach for integrating c...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Ubiquity Press
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5982922/ https://www.ncbi.nlm.nih.gov/pubmed/29881757 http://dx.doi.org/10.5334/egems.202 |
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author | James, Brent C. Edwards, David P. James, Alan F. Bradshaw, Richard L. White, Keith S. Wood, Chris Huff, Stan |
author_facet | James, Brent C. Edwards, David P. James, Alan F. Bradshaw, Richard L. White, Keith S. Wood, Chris Huff, Stan |
author_sort | James, Brent C. |
collection | PubMed |
description | Current commercially-available electronic medical record systems produce mainly text-based information focused on financial and regulatory performance. We combined an existing method for organizing complex computer systems—which we label activity-based design—with a proven approach for integrating clinical decision support into front-line care delivery—Care Process Models. The clinical decision support approach increased the structure of textual clinical documentation, to the point where established methods for converting text into computable data (natural language processing) worked efficiently. In a simple trial involving radiology reports for examinations performed to rule out pneumonia, more than 98 percent of all documentation generated was captured as computable data. Use cases across a broad range of other physician, nursing, and physical therapy clinical applications subjectively show similar effects. The resulting system is clinically natural, puts clinicians in direct, rapid control of clinical content without information technology intermediaries, and can generate complete clinical documentation. It supports embedded secondary functions such as the generation of granular activity-based costing data, and embedded generation of clinical coding (e.g., CPT, ICD-10 or SNOMED). Most important, widely-available computable data has the potential to greatly improve care delivery management and outcomes. |
format | Online Article Text |
id | pubmed-5982922 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Ubiquity Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-59829222018-06-07 An Efficient, Clinically-Natural Electronic Medical Record System that Produces Computable Data James, Brent C. Edwards, David P. James, Alan F. Bradshaw, Richard L. White, Keith S. Wood, Chris Huff, Stan EGEMS (Wash DC) Empirical Research Current commercially-available electronic medical record systems produce mainly text-based information focused on financial and regulatory performance. We combined an existing method for organizing complex computer systems—which we label activity-based design—with a proven approach for integrating clinical decision support into front-line care delivery—Care Process Models. The clinical decision support approach increased the structure of textual clinical documentation, to the point where established methods for converting text into computable data (natural language processing) worked efficiently. In a simple trial involving radiology reports for examinations performed to rule out pneumonia, more than 98 percent of all documentation generated was captured as computable data. Use cases across a broad range of other physician, nursing, and physical therapy clinical applications subjectively show similar effects. The resulting system is clinically natural, puts clinicians in direct, rapid control of clinical content without information technology intermediaries, and can generate complete clinical documentation. It supports embedded secondary functions such as the generation of granular activity-based costing data, and embedded generation of clinical coding (e.g., CPT, ICD-10 or SNOMED). Most important, widely-available computable data has the potential to greatly improve care delivery management and outcomes. Ubiquity Press 2017-12-15 /pmc/articles/PMC5982922/ /pubmed/29881757 http://dx.doi.org/10.5334/egems.202 Text en Copyright: © 2017 The Author(s) http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. See http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Empirical Research James, Brent C. Edwards, David P. James, Alan F. Bradshaw, Richard L. White, Keith S. Wood, Chris Huff, Stan An Efficient, Clinically-Natural Electronic Medical Record System that Produces Computable Data |
title | An Efficient, Clinically-Natural Electronic Medical Record System that Produces Computable Data |
title_full | An Efficient, Clinically-Natural Electronic Medical Record System that Produces Computable Data |
title_fullStr | An Efficient, Clinically-Natural Electronic Medical Record System that Produces Computable Data |
title_full_unstemmed | An Efficient, Clinically-Natural Electronic Medical Record System that Produces Computable Data |
title_short | An Efficient, Clinically-Natural Electronic Medical Record System that Produces Computable Data |
title_sort | efficient, clinically-natural electronic medical record system that produces computable data |
topic | Empirical Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5982922/ https://www.ncbi.nlm.nih.gov/pubmed/29881757 http://dx.doi.org/10.5334/egems.202 |
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