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The Structured Process to Identify Fit‐For‐Purpose Data: A Data Feasibility Assessment Framework
To complement real‐world evidence (RWE) guidelines, the 2019 Structured Preapproval and Postapproval Comparative study design framework to generate valid and transparent real‐world Evidence (SPACE) framework elucidated a process for designing valid and transparent real‐world studies. As an extension...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9299818/ https://www.ncbi.nlm.nih.gov/pubmed/34716990 http://dx.doi.org/10.1002/cpt.2466 |
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author | Gatto, Nicolle M. Campbell, Ulka B. Rubinstein, Emily Jaksa, Ashley Mattox, Pattra Mo, Jingping Reynolds, Robert F. |
author_facet | Gatto, Nicolle M. Campbell, Ulka B. Rubinstein, Emily Jaksa, Ashley Mattox, Pattra Mo, Jingping Reynolds, Robert F. |
author_sort | Gatto, Nicolle M. |
collection | PubMed |
description | To complement real‐world evidence (RWE) guidelines, the 2019 Structured Preapproval and Postapproval Comparative study design framework to generate valid and transparent real‐world Evidence (SPACE) framework elucidated a process for designing valid and transparent real‐world studies. As an extension to SPACE, here, we provide a structured framework for conducting feasibility assessments—a step‐by‐step guide to identify decision grade, fit‐for‐purpose data, which complements the United States Food and Drug Administration (FDA)’s framework for a RWE program. The process was informed by our collective experience conducting systematic feasibility assessments of existing data sources for pharmacoepidemiology studies to support regulatory decisions. Used with the SPACE framework, the Structured Process to Identify Fit‐For‐Purpose Data (SPIFD) provides a systematic process for conducting feasibility assessments to determine if a data source is fit for decision making, helping ensure justification and transparency throughout study development, from articulation of a specific and meaningful research question to identification of fit‐for‐purpose data and study design. |
format | Online Article Text |
id | pubmed-9299818 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-92998182022-07-22 The Structured Process to Identify Fit‐For‐Purpose Data: A Data Feasibility Assessment Framework Gatto, Nicolle M. Campbell, Ulka B. Rubinstein, Emily Jaksa, Ashley Mattox, Pattra Mo, Jingping Reynolds, Robert F. Clin Pharmacol Ther Reviews To complement real‐world evidence (RWE) guidelines, the 2019 Structured Preapproval and Postapproval Comparative study design framework to generate valid and transparent real‐world Evidence (SPACE) framework elucidated a process for designing valid and transparent real‐world studies. As an extension to SPACE, here, we provide a structured framework for conducting feasibility assessments—a step‐by‐step guide to identify decision grade, fit‐for‐purpose data, which complements the United States Food and Drug Administration (FDA)’s framework for a RWE program. The process was informed by our collective experience conducting systematic feasibility assessments of existing data sources for pharmacoepidemiology studies to support regulatory decisions. Used with the SPACE framework, the Structured Process to Identify Fit‐For‐Purpose Data (SPIFD) provides a systematic process for conducting feasibility assessments to determine if a data source is fit for decision making, helping ensure justification and transparency throughout study development, from articulation of a specific and meaningful research question to identification of fit‐for‐purpose data and study design. John Wiley and Sons Inc. 2021-12-01 2022-01 /pmc/articles/PMC9299818/ /pubmed/34716990 http://dx.doi.org/10.1002/cpt.2466 Text en © 2021 The Authors. Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. |
spellingShingle | Reviews Gatto, Nicolle M. Campbell, Ulka B. Rubinstein, Emily Jaksa, Ashley Mattox, Pattra Mo, Jingping Reynolds, Robert F. The Structured Process to Identify Fit‐For‐Purpose Data: A Data Feasibility Assessment Framework |
title | The Structured Process to Identify Fit‐For‐Purpose Data: A Data Feasibility Assessment Framework |
title_full | The Structured Process to Identify Fit‐For‐Purpose Data: A Data Feasibility Assessment Framework |
title_fullStr | The Structured Process to Identify Fit‐For‐Purpose Data: A Data Feasibility Assessment Framework |
title_full_unstemmed | The Structured Process to Identify Fit‐For‐Purpose Data: A Data Feasibility Assessment Framework |
title_short | The Structured Process to Identify Fit‐For‐Purpose Data: A Data Feasibility Assessment Framework |
title_sort | structured process to identify fit‐for‐purpose data: a data feasibility assessment framework |
topic | Reviews |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9299818/ https://www.ncbi.nlm.nih.gov/pubmed/34716990 http://dx.doi.org/10.1002/cpt.2466 |
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