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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...

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Autores principales: James, Brent C., Edwards, David P., James, Alan F., Bradshaw, Richard L., White, Keith S., Wood, Chris, Huff, Stan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Ubiquity Press 2017
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.
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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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