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Quantitative Consensus in Systematic Reviews: Current and Future Challenges in Translational Science
Translational science conceptualizes healthcare as a concerted set of processes that integrate research findings from the bench to the bedside. This model of healthcare is effectiveness-focused, patient-centered, and evidence-based, and yields evidence-based revisions of practice-based guidelines, w...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Biomedical Informatics
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5879943/ https://www.ncbi.nlm.nih.gov/pubmed/29618905 http://dx.doi.org/10.6026/97320630014086 |
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author | Chiappelli, Francesco Kasar, Vandan R. Balenton, Nicole Khakshooy, Allen |
author_facet | Chiappelli, Francesco Kasar, Vandan R. Balenton, Nicole Khakshooy, Allen |
author_sort | Chiappelli, Francesco |
collection | PubMed |
description | Translational science conceptualizes healthcare as a concerted set of processes that integrate research findings from the bench to the bedside. This model of healthcare is effectiveness-focused, patient-centered, and evidence-based, and yields evidence-based revisions of practice-based guidelines, which emerge from research synthesis protocols in comparative effectiveness research that are disseminated in systematic reviews. Systematic reviews produce qualitative and quantitative consensi of the best available evidence. The quantitative consensus is derived from meta-analysis protocols that are often achieved by probabilistic approach Bayesian statistical models. |
format | Online Article Text |
id | pubmed-5879943 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Biomedical Informatics |
record_format | MEDLINE/PubMed |
spelling | pubmed-58799432018-04-04 Quantitative Consensus in Systematic Reviews: Current and Future Challenges in Translational Science Chiappelli, Francesco Kasar, Vandan R. Balenton, Nicole Khakshooy, Allen Bioinformation Review Translational science conceptualizes healthcare as a concerted set of processes that integrate research findings from the bench to the bedside. This model of healthcare is effectiveness-focused, patient-centered, and evidence-based, and yields evidence-based revisions of practice-based guidelines, which emerge from research synthesis protocols in comparative effectiveness research that are disseminated in systematic reviews. Systematic reviews produce qualitative and quantitative consensi of the best available evidence. The quantitative consensus is derived from meta-analysis protocols that are often achieved by probabilistic approach Bayesian statistical models. Biomedical Informatics 2018-02-28 /pmc/articles/PMC5879943/ /pubmed/29618905 http://dx.doi.org/10.6026/97320630014086 Text en © 2018 Biomedical Informatics http://creativecommons.org/licenses/by/3.0/ This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License. |
spellingShingle | Review Chiappelli, Francesco Kasar, Vandan R. Balenton, Nicole Khakshooy, Allen Quantitative Consensus in Systematic Reviews: Current and Future Challenges in Translational Science |
title | Quantitative Consensus in Systematic Reviews: Current and Future Challenges in Translational Science |
title_full | Quantitative Consensus in Systematic Reviews: Current and Future Challenges in Translational Science |
title_fullStr | Quantitative Consensus in Systematic Reviews: Current and Future Challenges in Translational Science |
title_full_unstemmed | Quantitative Consensus in Systematic Reviews: Current and Future Challenges in Translational Science |
title_short | Quantitative Consensus in Systematic Reviews: Current and Future Challenges in Translational Science |
title_sort | quantitative consensus in systematic reviews: current and future challenges in translational science |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5879943/ https://www.ncbi.nlm.nih.gov/pubmed/29618905 http://dx.doi.org/10.6026/97320630014086 |
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