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A study of diverse clinical decision support rule authoring environments and requirements for integration

BACKGROUND: Efficient rule authoring tools are critical to allow clinical Knowledge Engineers (KEs), Software Engineers (SEs), and Subject Matter Experts (SMEs) to convert medical knowledge into machine executable clinical decision support rules. The goal of this analysis was to identify the critica...

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Autores principales: Zhou, Li, Karipineni, Neelima, Lewis, Janet, Maviglia, Saverio M, Fairbanks, Amanda, Hongsermeier, Tonya, Middleton, Blackford, Rocha, Roberto A
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3554596/
https://www.ncbi.nlm.nih.gov/pubmed/23145874
http://dx.doi.org/10.1186/1472-6947-12-128
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author Zhou, Li
Karipineni, Neelima
Lewis, Janet
Maviglia, Saverio M
Fairbanks, Amanda
Hongsermeier, Tonya
Middleton, Blackford
Rocha, Roberto A
author_facet Zhou, Li
Karipineni, Neelima
Lewis, Janet
Maviglia, Saverio M
Fairbanks, Amanda
Hongsermeier, Tonya
Middleton, Blackford
Rocha, Roberto A
author_sort Zhou, Li
collection PubMed
description BACKGROUND: Efficient rule authoring tools are critical to allow clinical Knowledge Engineers (KEs), Software Engineers (SEs), and Subject Matter Experts (SMEs) to convert medical knowledge into machine executable clinical decision support rules. The goal of this analysis was to identify the critical success factors and challenges of a fully functioning Rule Authoring Environment (RAE) in order to define requirements for a scalable, comprehensive tool to manage enterprise level rules. METHODS: The authors evaluated RAEs in active use across Partners Healthcare, including enterprise wide, ambulatory only, and system specific tools, with a focus on rule editors for reminder and medication rules. We conducted meetings with users of these RAEs to discuss their general experience and perceived advantages and limitations of these tools. RESULTS: While the overall rule authoring process is similar across the 10 separate RAEs, the system capabilities and architecture vary widely. Most current RAEs limit the ability of the clinical decision support (CDS) interventions to be standardized, sharable, interoperable, and extensible. No existing system meets all requirements defined by knowledge management users. CONCLUSIONS: A successful, scalable, integrated rule authoring environment will need to support a number of key requirements and functions in the areas of knowledge representation, metadata, terminology, authoring collaboration, user interface, integration with electronic health record (EHR) systems, testing, and reporting.
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spelling pubmed-35545962013-01-29 A study of diverse clinical decision support rule authoring environments and requirements for integration Zhou, Li Karipineni, Neelima Lewis, Janet Maviglia, Saverio M Fairbanks, Amanda Hongsermeier, Tonya Middleton, Blackford Rocha, Roberto A BMC Med Inform Decis Mak Research Article BACKGROUND: Efficient rule authoring tools are critical to allow clinical Knowledge Engineers (KEs), Software Engineers (SEs), and Subject Matter Experts (SMEs) to convert medical knowledge into machine executable clinical decision support rules. The goal of this analysis was to identify the critical success factors and challenges of a fully functioning Rule Authoring Environment (RAE) in order to define requirements for a scalable, comprehensive tool to manage enterprise level rules. METHODS: The authors evaluated RAEs in active use across Partners Healthcare, including enterprise wide, ambulatory only, and system specific tools, with a focus on rule editors for reminder and medication rules. We conducted meetings with users of these RAEs to discuss their general experience and perceived advantages and limitations of these tools. RESULTS: While the overall rule authoring process is similar across the 10 separate RAEs, the system capabilities and architecture vary widely. Most current RAEs limit the ability of the clinical decision support (CDS) interventions to be standardized, sharable, interoperable, and extensible. No existing system meets all requirements defined by knowledge management users. CONCLUSIONS: A successful, scalable, integrated rule authoring environment will need to support a number of key requirements and functions in the areas of knowledge representation, metadata, terminology, authoring collaboration, user interface, integration with electronic health record (EHR) systems, testing, and reporting. BioMed Central 2012-11-12 /pmc/articles/PMC3554596/ /pubmed/23145874 http://dx.doi.org/10.1186/1472-6947-12-128 Text en Copyright ©2012 Zhou et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Zhou, Li
Karipineni, Neelima
Lewis, Janet
Maviglia, Saverio M
Fairbanks, Amanda
Hongsermeier, Tonya
Middleton, Blackford
Rocha, Roberto A
A study of diverse clinical decision support rule authoring environments and requirements for integration
title A study of diverse clinical decision support rule authoring environments and requirements for integration
title_full A study of diverse clinical decision support rule authoring environments and requirements for integration
title_fullStr A study of diverse clinical decision support rule authoring environments and requirements for integration
title_full_unstemmed A study of diverse clinical decision support rule authoring environments and requirements for integration
title_short A study of diverse clinical decision support rule authoring environments and requirements for integration
title_sort study of diverse clinical decision support rule authoring environments and requirements for integration
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3554596/
https://www.ncbi.nlm.nih.gov/pubmed/23145874
http://dx.doi.org/10.1186/1472-6947-12-128
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