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Effect of a Novel Clinical Decision Support Tool on the Efficiency and Accuracy of Treatment Recommendations for Cholesterol Management
BACKGROUND: The 2013 American College of Cardiology / American Heart Association Guidelines for the Treatment of Blood Cholesterol emphasize treatment based on cardiovascular risk. But finding time in a primary care visit to manually calculate cardiovascular risk and prescribe treatment based on ris...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Schattauer
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5373758/ https://www.ncbi.nlm.nih.gov/pubmed/28174820 http://dx.doi.org/10.4338/ACI-2016-07-RA-0114 |
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author | Scheitel, Marianne R. Kessler, Maya E. Shellum, Jane L. Peters, Steve G. Milliner, Dawn S. Liu, Hongfang Elayavilli, Ravikumar Komandur Poterack, Karl A. Miksch, Timothy A. Boysen, Jennifer J. Hankey, Ron A. Chaudhry, Rajeev |
author_facet | Scheitel, Marianne R. Kessler, Maya E. Shellum, Jane L. Peters, Steve G. Milliner, Dawn S. Liu, Hongfang Elayavilli, Ravikumar Komandur Poterack, Karl A. Miksch, Timothy A. Boysen, Jennifer J. Hankey, Ron A. Chaudhry, Rajeev |
author_sort | Scheitel, Marianne R. |
collection | PubMed |
description | BACKGROUND: The 2013 American College of Cardiology / American Heart Association Guidelines for the Treatment of Blood Cholesterol emphasize treatment based on cardiovascular risk. But finding time in a primary care visit to manually calculate cardiovascular risk and prescribe treatment based on risk is challenging. We developed an informatics-based clinical decision support tool, MayoExpertAdvisor, to deliver automated cardiovascular risk scores and guideline-based treatment recommendations based on patient-specific data in the electronic heath record. OBJECTIVE: To assess the impact of our clinical decision support tool on the efficiency and accuracy of clinician calculation of cardiovascular risk and its effect on the delivery of guideline-consistent treatment recommendations. METHODS: Clinicians were asked to review the EHR records of selected patients. We evaluated the amount of time and the number of clicks and keystrokes needed to calculate cardiovascular risk and provide a treatment recommendation with and without our clinical decision support tool. We also compared the treatment recommendation arrived at by clinicians with and without the use of our tool to those recommended by the guidelines. RESULTS: Clinicians saved 3 minutes and 38 seconds in completing both tasks with MayoExpertAdvisor, used 94 fewer clicks and 23 fewer key strokes, and improved accuracy from the baseline of 60.61% to 100% for both the risk score calculation and guideline-consistent treatment recommendation. CONCLUSION: Informatics solution can greatly improve the efficiency and accuracy of individualized treatment recommendations and have the potential to increase guideline compliance. |
format | Online Article Text |
id | pubmed-5373758 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Schattauer |
record_format | MEDLINE/PubMed |
spelling | pubmed-53737582017-04-06 Effect of a Novel Clinical Decision Support Tool on the Efficiency and Accuracy of Treatment Recommendations for Cholesterol Management Scheitel, Marianne R. Kessler, Maya E. Shellum, Jane L. Peters, Steve G. Milliner, Dawn S. Liu, Hongfang Elayavilli, Ravikumar Komandur Poterack, Karl A. Miksch, Timothy A. Boysen, Jennifer J. Hankey, Ron A. Chaudhry, Rajeev Appl Clin Inform Research Article BACKGROUND: The 2013 American College of Cardiology / American Heart Association Guidelines for the Treatment of Blood Cholesterol emphasize treatment based on cardiovascular risk. But finding time in a primary care visit to manually calculate cardiovascular risk and prescribe treatment based on risk is challenging. We developed an informatics-based clinical decision support tool, MayoExpertAdvisor, to deliver automated cardiovascular risk scores and guideline-based treatment recommendations based on patient-specific data in the electronic heath record. OBJECTIVE: To assess the impact of our clinical decision support tool on the efficiency and accuracy of clinician calculation of cardiovascular risk and its effect on the delivery of guideline-consistent treatment recommendations. METHODS: Clinicians were asked to review the EHR records of selected patients. We evaluated the amount of time and the number of clicks and keystrokes needed to calculate cardiovascular risk and provide a treatment recommendation with and without our clinical decision support tool. We also compared the treatment recommendation arrived at by clinicians with and without the use of our tool to those recommended by the guidelines. RESULTS: Clinicians saved 3 minutes and 38 seconds in completing both tasks with MayoExpertAdvisor, used 94 fewer clicks and 23 fewer key strokes, and improved accuracy from the baseline of 60.61% to 100% for both the risk score calculation and guideline-consistent treatment recommendation. CONCLUSION: Informatics solution can greatly improve the efficiency and accuracy of individualized treatment recommendations and have the potential to increase guideline compliance. Schattauer 2017-02-08 /pmc/articles/PMC5373758/ /pubmed/28174820 http://dx.doi.org/10.4338/ACI-2016-07-RA-0114 Text en © Copyright Schattauer 2017 https://creativecommons.org/licenses/by-nc-nd/4.0/ License terms: CC-BY-NC-ND (https://creativecommons.org/licenses/by-nc-nd/4.0/) |
spellingShingle | Research Article Scheitel, Marianne R. Kessler, Maya E. Shellum, Jane L. Peters, Steve G. Milliner, Dawn S. Liu, Hongfang Elayavilli, Ravikumar Komandur Poterack, Karl A. Miksch, Timothy A. Boysen, Jennifer J. Hankey, Ron A. Chaudhry, Rajeev Effect of a Novel Clinical Decision Support Tool on the Efficiency and Accuracy of Treatment Recommendations for Cholesterol Management |
title | Effect of a Novel Clinical Decision Support Tool on the Efficiency and Accuracy of Treatment Recommendations for Cholesterol Management |
title_full | Effect of a Novel Clinical Decision Support Tool on the Efficiency and Accuracy of Treatment Recommendations for Cholesterol Management |
title_fullStr | Effect of a Novel Clinical Decision Support Tool on the Efficiency and Accuracy of Treatment Recommendations for Cholesterol Management |
title_full_unstemmed | Effect of a Novel Clinical Decision Support Tool on the Efficiency and Accuracy of Treatment Recommendations for Cholesterol Management |
title_short | Effect of a Novel Clinical Decision Support Tool on the Efficiency and Accuracy of Treatment Recommendations for Cholesterol Management |
title_sort | effect of a novel clinical decision support tool on the efficiency and accuracy of treatment recommendations for cholesterol management |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5373758/ https://www.ncbi.nlm.nih.gov/pubmed/28174820 http://dx.doi.org/10.4338/ACI-2016-07-RA-0114 |
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