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Developing an Applied Biostatistical Sciences (ABS) network

INTRODUCTION: Access to qualified biostatisticians to provide input on research design and statistical considerations is critical for high-quality clinical and translational research. At diverse health science institutions, like the University of Michigan (U-M), biostatistical collaborators are scat...

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Autores principales: Khalatbari, Shokoufeh, Jazdzyk, Dianne, Capsouras, Janine, Downey, Brad, Samuels, Eli, Spino, Cathie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cambridge University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8057411/
https://www.ncbi.nlm.nih.gov/pubmed/33948241
http://dx.doi.org/10.1017/cts.2020.506
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author Khalatbari, Shokoufeh
Jazdzyk, Dianne
Capsouras, Janine
Downey, Brad
Samuels, Eli
Spino, Cathie
author_facet Khalatbari, Shokoufeh
Jazdzyk, Dianne
Capsouras, Janine
Downey, Brad
Samuels, Eli
Spino, Cathie
author_sort Khalatbari, Shokoufeh
collection PubMed
description INTRODUCTION: Access to qualified biostatisticians to provide input on research design and statistical considerations is critical for high-quality clinical and translational research. At diverse health science institutions, like the University of Michigan (U-M), biostatistical collaborators are scattered across the campus. This model can isolate applied statisticians, analysts, and epidemiologists from each other, which may negatively affect their career development and job satisfaction, and inhibits access to optimal biostatistical support for researchers. Furthermore, in the era of modern, complex translational research, it is imperative to elevate biostatistical expertise by offering innovative training. METHODS: The Michigan Institute for Clinical and Health Research established an Applied Biostatistical Sciences (ABS) network that is a campus-wide community of staff and faculty statisticians, epidemiologists, data scientists, and researchers, with the intention of supporting both researchers and biostatisticians, while promoting high-quality clinical and translational research. RESULTS: Since its inception in early 2018, the ABS Network has grown to several hundred faculty and staff members across a range of health and research disciplines. The ABS Network offers free trainings on innovative methods and tools in the biostatistical field, a web-based portal with resources and training lectures, and connections to U-M faculty and/or staff members for consultation and collaboration. CONCLUSIONS: Although challenging, if approached strategically, the creation of a collaboration network of biostatisticians can be accomplished. Furthermore, the process can be adopted and implemented for establishing collaboration with any network of professionals with common interests across different disciplines and professional fields regardless of size.
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spelling pubmed-80574112021-05-03 Developing an Applied Biostatistical Sciences (ABS) network Khalatbari, Shokoufeh Jazdzyk, Dianne Capsouras, Janine Downey, Brad Samuels, Eli Spino, Cathie J Clin Transl Sci Research Article INTRODUCTION: Access to qualified biostatisticians to provide input on research design and statistical considerations is critical for high-quality clinical and translational research. At diverse health science institutions, like the University of Michigan (U-M), biostatistical collaborators are scattered across the campus. This model can isolate applied statisticians, analysts, and epidemiologists from each other, which may negatively affect their career development and job satisfaction, and inhibits access to optimal biostatistical support for researchers. Furthermore, in the era of modern, complex translational research, it is imperative to elevate biostatistical expertise by offering innovative training. METHODS: The Michigan Institute for Clinical and Health Research established an Applied Biostatistical Sciences (ABS) network that is a campus-wide community of staff and faculty statisticians, epidemiologists, data scientists, and researchers, with the intention of supporting both researchers and biostatisticians, while promoting high-quality clinical and translational research. RESULTS: Since its inception in early 2018, the ABS Network has grown to several hundred faculty and staff members across a range of health and research disciplines. The ABS Network offers free trainings on innovative methods and tools in the biostatistical field, a web-based portal with resources and training lectures, and connections to U-M faculty and/or staff members for consultation and collaboration. CONCLUSIONS: Although challenging, if approached strategically, the creation of a collaboration network of biostatisticians can be accomplished. Furthermore, the process can be adopted and implemented for establishing collaboration with any network of professionals with common interests across different disciplines and professional fields regardless of size. Cambridge University Press 2020-07-06 /pmc/articles/PMC8057411/ /pubmed/33948241 http://dx.doi.org/10.1017/cts.2020.506 Text en © The Association for Clinical and Translational Science 2020 https://creativecommons.org/licenses/by/4.0/This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Khalatbari, Shokoufeh
Jazdzyk, Dianne
Capsouras, Janine
Downey, Brad
Samuels, Eli
Spino, Cathie
Developing an Applied Biostatistical Sciences (ABS) network
title Developing an Applied Biostatistical Sciences (ABS) network
title_full Developing an Applied Biostatistical Sciences (ABS) network
title_fullStr Developing an Applied Biostatistical Sciences (ABS) network
title_full_unstemmed Developing an Applied Biostatistical Sciences (ABS) network
title_short Developing an Applied Biostatistical Sciences (ABS) network
title_sort developing an applied biostatistical sciences (abs) network
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8057411/
https://www.ncbi.nlm.nih.gov/pubmed/33948241
http://dx.doi.org/10.1017/cts.2020.506
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