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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
Descripción
Sumario: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.