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A Framework for Leveraging “Big Data” to Advance Epidemiology and Improve Quality: Design of the VA Colonoscopy Collaborative

OBJECTIVE: To describe a framework for leveraging big data for research and quality improvement purposes and demonstrate implementation of the framework for design of the Department of Veterans Affairs (VA) Colonoscopy Collaborative. METHODS: We propose that research utilizing large-scale electronic...

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Autores principales: Gupta, Samir, Liu, Lin, Patterson, Olga V., Earles, Ashley, Bustamante, Ranier, Gawron, Andrew J., Thompson, William K., Scuba, William, Denhalter, Daniel, Martinez, M. Elena, Messer, Karen, Fisher, Deborah A., Saini, Sameer D., DuVall, Scott L., Chapman, Wendy W., Whooley, Mary A., Kaltenbach, Tonya
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Ubiquity Press 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5983017/
https://www.ncbi.nlm.nih.gov/pubmed/29881762
http://dx.doi.org/10.5334/egems.198
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author Gupta, Samir
Liu, Lin
Patterson, Olga V.
Earles, Ashley
Bustamante, Ranier
Gawron, Andrew J.
Thompson, William K.
Scuba, William
Denhalter, Daniel
Martinez, M. Elena
Messer, Karen
Fisher, Deborah A.
Saini, Sameer D.
DuVall, Scott L.
Chapman, Wendy W.
Whooley, Mary A.
Kaltenbach, Tonya
author_facet Gupta, Samir
Liu, Lin
Patterson, Olga V.
Earles, Ashley
Bustamante, Ranier
Gawron, Andrew J.
Thompson, William K.
Scuba, William
Denhalter, Daniel
Martinez, M. Elena
Messer, Karen
Fisher, Deborah A.
Saini, Sameer D.
DuVall, Scott L.
Chapman, Wendy W.
Whooley, Mary A.
Kaltenbach, Tonya
author_sort Gupta, Samir
collection PubMed
description OBJECTIVE: To describe a framework for leveraging big data for research and quality improvement purposes and demonstrate implementation of the framework for design of the Department of Veterans Affairs (VA) Colonoscopy Collaborative. METHODS: We propose that research utilizing large-scale electronic health records (EHRs) can be approached in a 4 step framework: 1) Identify data sources required to answer research question; 2) Determine whether variables are available as structured or free-text data; 3) Utilize a rigorous approach to refine variables and assess data quality; 4) Create the analytic dataset and perform analyses. We describe implementation of the framework as part of the VA Colonoscopy Collaborative, which aims to leverage big data to 1) prospectively measure and report colonoscopy quality and 2) develop and validate a risk prediction model for colorectal cancer (CRC) and high-risk polyps. RESULTS: Examples of implementation of the 4 step framework are provided. To date, we have identified 2,337,171 Veterans who have undergone colonoscopy between 1999 and 2014. Median age was 62 years, and 4.6 percent (n = 106,860) were female. We estimated that 2.6 percent (n = 60,517) had CRC diagnosed at baseline. An additional 1 percent (n = 24,483) had a new ICD-9 code-based diagnosis of CRC on follow up. CONCLUSION: We hope our framework may contribute to the dialogue on best practices to ensure high quality epidemiologic and quality improvement work. As a result of implementation of the framework, the VA Colonoscopy Collaborative holds great promise for 1) quantifying and providing novel understandings of colonoscopy outcomes, and 2) building a robust approach for nationwide VA colonoscopy quality reporting.
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spelling pubmed-59830172018-06-07 A Framework for Leveraging “Big Data” to Advance Epidemiology and Improve Quality: Design of the VA Colonoscopy Collaborative Gupta, Samir Liu, Lin Patterson, Olga V. Earles, Ashley Bustamante, Ranier Gawron, Andrew J. Thompson, William K. Scuba, William Denhalter, Daniel Martinez, M. Elena Messer, Karen Fisher, Deborah A. Saini, Sameer D. DuVall, Scott L. Chapman, Wendy W. Whooley, Mary A. Kaltenbach, Tonya EGEMS (Wash DC) Protocol OBJECTIVE: To describe a framework for leveraging big data for research and quality improvement purposes and demonstrate implementation of the framework for design of the Department of Veterans Affairs (VA) Colonoscopy Collaborative. METHODS: We propose that research utilizing large-scale electronic health records (EHRs) can be approached in a 4 step framework: 1) Identify data sources required to answer research question; 2) Determine whether variables are available as structured or free-text data; 3) Utilize a rigorous approach to refine variables and assess data quality; 4) Create the analytic dataset and perform analyses. We describe implementation of the framework as part of the VA Colonoscopy Collaborative, which aims to leverage big data to 1) prospectively measure and report colonoscopy quality and 2) develop and validate a risk prediction model for colorectal cancer (CRC) and high-risk polyps. RESULTS: Examples of implementation of the 4 step framework are provided. To date, we have identified 2,337,171 Veterans who have undergone colonoscopy between 1999 and 2014. Median age was 62 years, and 4.6 percent (n = 106,860) were female. We estimated that 2.6 percent (n = 60,517) had CRC diagnosed at baseline. An additional 1 percent (n = 24,483) had a new ICD-9 code-based diagnosis of CRC on follow up. CONCLUSION: We hope our framework may contribute to the dialogue on best practices to ensure high quality epidemiologic and quality improvement work. As a result of implementation of the framework, the VA Colonoscopy Collaborative holds great promise for 1) quantifying and providing novel understandings of colonoscopy outcomes, and 2) building a robust approach for nationwide VA colonoscopy quality reporting. Ubiquity Press 2018-04-13 /pmc/articles/PMC5983017/ /pubmed/29881762 http://dx.doi.org/10.5334/egems.198 Text en Copyright: © 2018 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 Protocol
Gupta, Samir
Liu, Lin
Patterson, Olga V.
Earles, Ashley
Bustamante, Ranier
Gawron, Andrew J.
Thompson, William K.
Scuba, William
Denhalter, Daniel
Martinez, M. Elena
Messer, Karen
Fisher, Deborah A.
Saini, Sameer D.
DuVall, Scott L.
Chapman, Wendy W.
Whooley, Mary A.
Kaltenbach, Tonya
A Framework for Leveraging “Big Data” to Advance Epidemiology and Improve Quality: Design of the VA Colonoscopy Collaborative
title A Framework for Leveraging “Big Data” to Advance Epidemiology and Improve Quality: Design of the VA Colonoscopy Collaborative
title_full A Framework for Leveraging “Big Data” to Advance Epidemiology and Improve Quality: Design of the VA Colonoscopy Collaborative
title_fullStr A Framework for Leveraging “Big Data” to Advance Epidemiology and Improve Quality: Design of the VA Colonoscopy Collaborative
title_full_unstemmed A Framework for Leveraging “Big Data” to Advance Epidemiology and Improve Quality: Design of the VA Colonoscopy Collaborative
title_short A Framework for Leveraging “Big Data” to Advance Epidemiology and Improve Quality: Design of the VA Colonoscopy Collaborative
title_sort framework for leveraging “big data” to advance epidemiology and improve quality: design of the va colonoscopy collaborative
topic Protocol
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5983017/
https://www.ncbi.nlm.nih.gov/pubmed/29881762
http://dx.doi.org/10.5334/egems.198
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