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Application of a Graphical Depiction of Longitudinal Study Designs to Managed Care Pharmacy Research
Managed care pharmacists apply real-world evidence (RWE) to support activities such as pipeline forecasting, clinical policy development, and contracting for pharmaceutical products. Managed care pharmacy researchers strive to produce studies that can be applied in practice. While asking the right r...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Academy of Managed Care Pharmacy
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10391135/ https://www.ncbi.nlm.nih.gov/pubmed/32105168 http://dx.doi.org/10.18553/jmcp.2020.26.3.268 |
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author | Happe, Laura E. Brown, Joshua D. Gatwood, Justin Schneeweiss, Sebastian Wang, Shirley |
author_facet | Happe, Laura E. Brown, Joshua D. Gatwood, Justin Schneeweiss, Sebastian Wang, Shirley |
author_sort | Happe, Laura E. |
collection | PubMed |
description | Managed care pharmacists apply real-world evidence (RWE) to support activities such as pipeline forecasting, clinical policy development, and contracting for pharmaceutical products. Managed care pharmacy researchers strive to produce studies that can be applied in practice. While asking the right research question is necessary, it is not sufficient. As with all studies, consumers of RWE look for internal and external validity, as well as sources of bias, to determine how the study findings can be applied in their work. To date, however, some of the safeguards that exist for clinical trials—such as public registration of study protocols—are lacking for RWE. Several leading professional organizations have initiatives dedicated to improving the credibility and reliability of such research. One component common to these initiatives is enhanced transparency and completeness of methodologic reporting. Graphical representations of study designs can improve the reporting and design of research conducted in health care databases, specifically by enhancing the transparency and clarity of often complex studies. As such, Schneeweiss et al. (2019) proposed a graphical framework for longitudinal study designs in health care databases. Herein, we apply this framework to 2 studies published in the Journal of Managed Care & Specialty Pharmacy that represent common research designs and report how application of the framework revealed deficiencies in reporting. We advocate for adoption of this framework in the effort to increase the usability of RWE studies using health care databases by managed care pharmacy. |
format | Online Article Text |
id | pubmed-10391135 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Academy of Managed Care Pharmacy |
record_format | MEDLINE/PubMed |
spelling | pubmed-103911352023-08-02 Application of a Graphical Depiction of Longitudinal Study Designs to Managed Care Pharmacy Research Happe, Laura E. Brown, Joshua D. Gatwood, Justin Schneeweiss, Sebastian Wang, Shirley J Manag Care Spec Pharm Viewpoints Managed care pharmacists apply real-world evidence (RWE) to support activities such as pipeline forecasting, clinical policy development, and contracting for pharmaceutical products. Managed care pharmacy researchers strive to produce studies that can be applied in practice. While asking the right research question is necessary, it is not sufficient. As with all studies, consumers of RWE look for internal and external validity, as well as sources of bias, to determine how the study findings can be applied in their work. To date, however, some of the safeguards that exist for clinical trials—such as public registration of study protocols—are lacking for RWE. Several leading professional organizations have initiatives dedicated to improving the credibility and reliability of such research. One component common to these initiatives is enhanced transparency and completeness of methodologic reporting. Graphical representations of study designs can improve the reporting and design of research conducted in health care databases, specifically by enhancing the transparency and clarity of often complex studies. As such, Schneeweiss et al. (2019) proposed a graphical framework for longitudinal study designs in health care databases. Herein, we apply this framework to 2 studies published in the Journal of Managed Care & Specialty Pharmacy that represent common research designs and report how application of the framework revealed deficiencies in reporting. We advocate for adoption of this framework in the effort to increase the usability of RWE studies using health care databases by managed care pharmacy. Academy of Managed Care Pharmacy 2020-03 /pmc/articles/PMC10391135/ /pubmed/32105168 http://dx.doi.org/10.18553/jmcp.2020.26.3.268 Text en Copyright © 2020, Academy of Managed Care Pharmacy. All rights reserved. https://creativecommons.org/licenses/by/4.0/This article is licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Viewpoints Happe, Laura E. Brown, Joshua D. Gatwood, Justin Schneeweiss, Sebastian Wang, Shirley Application of a Graphical Depiction of Longitudinal Study Designs to Managed Care Pharmacy Research |
title | Application of a Graphical Depiction of Longitudinal Study Designs to Managed Care Pharmacy Research |
title_full | Application of a Graphical Depiction of Longitudinal Study Designs to Managed Care Pharmacy Research |
title_fullStr | Application of a Graphical Depiction of Longitudinal Study Designs to Managed Care Pharmacy Research |
title_full_unstemmed | Application of a Graphical Depiction of Longitudinal Study Designs to Managed Care Pharmacy Research |
title_short | Application of a Graphical Depiction of Longitudinal Study Designs to Managed Care Pharmacy Research |
title_sort | application of a graphical depiction of longitudinal study designs to managed care pharmacy research |
topic | Viewpoints |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10391135/ https://www.ncbi.nlm.nih.gov/pubmed/32105168 http://dx.doi.org/10.18553/jmcp.2020.26.3.268 |
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