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A review for clinical outcomes research: hypothesis generation, data strategy, and hypothesis-driven statistical analysis

In recent years, more and more large, population-level databases have become available for clinical research. The size and complexity of these databases often present a methodological challenge for investigators. We propose that a “protocol” may facilitate the research process using these databases....

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Detalles Bibliográficos
Autores principales: Chang, David C., Talamini, Mark A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer-Verlag 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3116115/
https://www.ncbi.nlm.nih.gov/pubmed/21359904
http://dx.doi.org/10.1007/s00464-010-1543-7
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author Chang, David C.
Talamini, Mark A.
author_facet Chang, David C.
Talamini, Mark A.
author_sort Chang, David C.
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description In recent years, more and more large, population-level databases have become available for clinical research. The size and complexity of these databases often present a methodological challenge for investigators. We propose that a “protocol” may facilitate the research process using these databases. In addition, much like the structured History and Physical (H&P) helps the audience appreciate the details of a patient case more systematically, a formal outcomes research protocol can also help in the systematic evaluation of an outcomes research manuscript.
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spelling pubmed-31161152011-07-14 A review for clinical outcomes research: hypothesis generation, data strategy, and hypothesis-driven statistical analysis Chang, David C. Talamini, Mark A. Surg Endosc Article In recent years, more and more large, population-level databases have become available for clinical research. The size and complexity of these databases often present a methodological challenge for investigators. We propose that a “protocol” may facilitate the research process using these databases. In addition, much like the structured History and Physical (H&P) helps the audience appreciate the details of a patient case more systematically, a formal outcomes research protocol can also help in the systematic evaluation of an outcomes research manuscript. Springer-Verlag 2011-02-27 2011 /pmc/articles/PMC3116115/ /pubmed/21359904 http://dx.doi.org/10.1007/s00464-010-1543-7 Text en © The Author(s) 2011 https://creativecommons.org/licenses/by-nc/4.0/ This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.
spellingShingle Article
Chang, David C.
Talamini, Mark A.
A review for clinical outcomes research: hypothesis generation, data strategy, and hypothesis-driven statistical analysis
title A review for clinical outcomes research: hypothesis generation, data strategy, and hypothesis-driven statistical analysis
title_full A review for clinical outcomes research: hypothesis generation, data strategy, and hypothesis-driven statistical analysis
title_fullStr A review for clinical outcomes research: hypothesis generation, data strategy, and hypothesis-driven statistical analysis
title_full_unstemmed A review for clinical outcomes research: hypothesis generation, data strategy, and hypothesis-driven statistical analysis
title_short A review for clinical outcomes research: hypothesis generation, data strategy, and hypothesis-driven statistical analysis
title_sort review for clinical outcomes research: hypothesis generation, data strategy, and hypothesis-driven statistical analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3116115/
https://www.ncbi.nlm.nih.gov/pubmed/21359904
http://dx.doi.org/10.1007/s00464-010-1543-7
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