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Visual Analytics Dashboard Promises to Improve Hypertension Guideline Implementation
BACKGROUND: Primary care management of hypertension under new guidelines incorporates assessment of cardiovascular disease risk and commonly requires review of electronic health record (EHR) data. Visual analytics can streamline the review of complex data and may lessen the burden clinicians face us...
Autores principales: | , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8557440/ https://www.ncbi.nlm.nih.gov/pubmed/34043744 http://dx.doi.org/10.1093/ajh/hpab081 |
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author | Fadel, Raef Ali Ross, Jacob Asmar, Timothy Sridasyam, Karthik Demertzis, Zachary Ahluwalia, Guneet Roumayah, Tamara Scott, Megan Ibrahim, Hanan Hammoudeh, Rawan Gandhi, Nitesh Flynn, Meaghan Haftka-George, Alexis Heidemann, Danielle Sims, Sarah Levy, Phillip Miller, Joseph |
author_facet | Fadel, Raef Ali Ross, Jacob Asmar, Timothy Sridasyam, Karthik Demertzis, Zachary Ahluwalia, Guneet Roumayah, Tamara Scott, Megan Ibrahim, Hanan Hammoudeh, Rawan Gandhi, Nitesh Flynn, Meaghan Haftka-George, Alexis Heidemann, Danielle Sims, Sarah Levy, Phillip Miller, Joseph |
author_sort | Fadel, Raef Ali |
collection | PubMed |
description | BACKGROUND: Primary care management of hypertension under new guidelines incorporates assessment of cardiovascular disease risk and commonly requires review of electronic health record (EHR) data. Visual analytics can streamline the review of complex data and may lessen the burden clinicians face using the EHR. This study sought to assess the utility of a visual analytics dashboard in addition to EHR in managing hypertension in a primary care setting. METHODS: Primary care physicians within an urban, academic internal medicine clinic were tasked with performing 2 simulated patient encounters for hypertension management: the first using standard EHR, and the second using EHR paired with a visual dashboard. The dashboard included graphical blood pressure trends with guideline-directed targets, calculated atherosclerotic cardiovascular disease risk score, and relevant medications. Guideline-appropriate antihypertensive prescribing, correct target blood pressure goal, and total encounter time were assessed. RESULTS: We evaluated 70 case simulations. Use of the dashboard with the EHR compared with use of the EHR alone was associated with greater adherence to prescribing guidelines (95% vs. 62%, P < 0.001) and more correct identification of blood pressure target (95% vs. 57%, P < 0.01). Total encounter time fell an average of 121 seconds (95% confidence interval 69–157 seconds, P < 0.001) in encounters that used the dashboard combined with the EHR. CONCLUSIONS: The integration of a hypertension-specific visual analytics dashboard with EHR demonstrates the potential to reduce time and improve hypertension guideline implementation. Further widespread testing in clinical practice is warranted. |
format | Online Article Text |
id | pubmed-8557440 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-85574402021-11-01 Visual Analytics Dashboard Promises to Improve Hypertension Guideline Implementation Fadel, Raef Ali Ross, Jacob Asmar, Timothy Sridasyam, Karthik Demertzis, Zachary Ahluwalia, Guneet Roumayah, Tamara Scott, Megan Ibrahim, Hanan Hammoudeh, Rawan Gandhi, Nitesh Flynn, Meaghan Haftka-George, Alexis Heidemann, Danielle Sims, Sarah Levy, Phillip Miller, Joseph Am J Hypertens Original Contributions BACKGROUND: Primary care management of hypertension under new guidelines incorporates assessment of cardiovascular disease risk and commonly requires review of electronic health record (EHR) data. Visual analytics can streamline the review of complex data and may lessen the burden clinicians face using the EHR. This study sought to assess the utility of a visual analytics dashboard in addition to EHR in managing hypertension in a primary care setting. METHODS: Primary care physicians within an urban, academic internal medicine clinic were tasked with performing 2 simulated patient encounters for hypertension management: the first using standard EHR, and the second using EHR paired with a visual dashboard. The dashboard included graphical blood pressure trends with guideline-directed targets, calculated atherosclerotic cardiovascular disease risk score, and relevant medications. Guideline-appropriate antihypertensive prescribing, correct target blood pressure goal, and total encounter time were assessed. RESULTS: We evaluated 70 case simulations. Use of the dashboard with the EHR compared with use of the EHR alone was associated with greater adherence to prescribing guidelines (95% vs. 62%, P < 0.001) and more correct identification of blood pressure target (95% vs. 57%, P < 0.01). Total encounter time fell an average of 121 seconds (95% confidence interval 69–157 seconds, P < 0.001) in encounters that used the dashboard combined with the EHR. CONCLUSIONS: The integration of a hypertension-specific visual analytics dashboard with EHR demonstrates the potential to reduce time and improve hypertension guideline implementation. Further widespread testing in clinical practice is warranted. Oxford University Press 2021-05-27 /pmc/articles/PMC8557440/ /pubmed/34043744 http://dx.doi.org/10.1093/ajh/hpab081 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of American Journal of Hypertension, Ltd. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Original Contributions Fadel, Raef Ali Ross, Jacob Asmar, Timothy Sridasyam, Karthik Demertzis, Zachary Ahluwalia, Guneet Roumayah, Tamara Scott, Megan Ibrahim, Hanan Hammoudeh, Rawan Gandhi, Nitesh Flynn, Meaghan Haftka-George, Alexis Heidemann, Danielle Sims, Sarah Levy, Phillip Miller, Joseph Visual Analytics Dashboard Promises to Improve Hypertension Guideline Implementation |
title | Visual Analytics Dashboard Promises to Improve Hypertension Guideline Implementation |
title_full | Visual Analytics Dashboard Promises to Improve Hypertension Guideline Implementation |
title_fullStr | Visual Analytics Dashboard Promises to Improve Hypertension Guideline Implementation |
title_full_unstemmed | Visual Analytics Dashboard Promises to Improve Hypertension Guideline Implementation |
title_short | Visual Analytics Dashboard Promises to Improve Hypertension Guideline Implementation |
title_sort | visual analytics dashboard promises to improve hypertension guideline implementation |
topic | Original Contributions |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8557440/ https://www.ncbi.nlm.nih.gov/pubmed/34043744 http://dx.doi.org/10.1093/ajh/hpab081 |
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