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Big data in pharmacy practice: current use, challenges, and the future
Pharmacy informatics is defined as the use and integration of data, information, knowledge, technology, and automation in the medication-use process for the purpose of improving health outcomes. The term “big data” has been coined and is often defined in three V’s: volume, velocity, and variety. Thi...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Dove Medical Press
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5741030/ https://www.ncbi.nlm.nih.gov/pubmed/29354523 http://dx.doi.org/10.2147/IPRP.S55862 |
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author | Ma, Carolyn Smith, Helen Wong Chu, Cherie Juarez, Deborah T |
author_facet | Ma, Carolyn Smith, Helen Wong Chu, Cherie Juarez, Deborah T |
author_sort | Ma, Carolyn |
collection | PubMed |
description | Pharmacy informatics is defined as the use and integration of data, information, knowledge, technology, and automation in the medication-use process for the purpose of improving health outcomes. The term “big data” has been coined and is often defined in three V’s: volume, velocity, and variety. This paper describes three major areas in which pharmacy utilizes big data, including: 1) informed decision making (clinical pathways and clinical practice guidelines); 2) improved care delivery in health care settings such as hospitals and community pharmacy practice settings; and 3) quality performance measurement for the Centers for Medicare and Medicaid and medication management activities such as tracking medication adherence and medication reconciliation. |
format | Online Article Text |
id | pubmed-5741030 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Dove Medical Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-57410302018-01-19 Big data in pharmacy practice: current use, challenges, and the future Ma, Carolyn Smith, Helen Wong Chu, Cherie Juarez, Deborah T Integr Pharm Res Pract Review Pharmacy informatics is defined as the use and integration of data, information, knowledge, technology, and automation in the medication-use process for the purpose of improving health outcomes. The term “big data” has been coined and is often defined in three V’s: volume, velocity, and variety. This paper describes three major areas in which pharmacy utilizes big data, including: 1) informed decision making (clinical pathways and clinical practice guidelines); 2) improved care delivery in health care settings such as hospitals and community pharmacy practice settings; and 3) quality performance measurement for the Centers for Medicare and Medicaid and medication management activities such as tracking medication adherence and medication reconciliation. Dove Medical Press 2015-08-06 /pmc/articles/PMC5741030/ /pubmed/29354523 http://dx.doi.org/10.2147/IPRP.S55862 Text en © 2015 Ma et al. This work is published by Dove Medical Press Limited, and licensed under Creative Commons Attribution – Non Commercial (unported, v3.0) License The full terms of the License are available at http://creativecommons.org/licenses/by-nc/3.0/. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. |
spellingShingle | Review Ma, Carolyn Smith, Helen Wong Chu, Cherie Juarez, Deborah T Big data in pharmacy practice: current use, challenges, and the future |
title | Big data in pharmacy practice: current use, challenges, and the future |
title_full | Big data in pharmacy practice: current use, challenges, and the future |
title_fullStr | Big data in pharmacy practice: current use, challenges, and the future |
title_full_unstemmed | Big data in pharmacy practice: current use, challenges, and the future |
title_short | Big data in pharmacy practice: current use, challenges, and the future |
title_sort | big data in pharmacy practice: current use, challenges, and the future |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5741030/ https://www.ncbi.nlm.nih.gov/pubmed/29354523 http://dx.doi.org/10.2147/IPRP.S55862 |
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