As clinical researchers at academic medical institutions across the United States increasingly become the gatekeepers of substantially complex patient databases and registries, they often lack the statistical expertise needed to utilize these data for research as well as clinical purposes. Not only does a lack of statistical knowledge prevent clinical researchers from correctly analyzing data from their own research projects, but this inadequacy can also inhibit their ability to accurately interpret published statistical findings in the medical literature. In response to PA11351, (R25), we propose to establish the Applied Statistical Independence in Biological Systems (ASIBS) Short Course to provide members of the academic medical community nationwide with the opportunity to increase their methodological capacity through short, yet rigorous, statistical training. Specifically we propose to accomplish the following specific aims: 1. Develop and implement the ASIBS Short Course for faculty and fellows from academic medical centers nationwide using a series of synchronous and asynchronous internet based lectures and a five day in person SAS lectures and applications. 2. Establish a Diversity Recruitment Advisory Board to ensure that the most effective strategies are employed to recruit underrepresented minority faculty and fellows from academic medical institutions into the ASIBS Short Course. 3. Enhance the dissemination phase of the ASIBS Short Course by packaging and uploading the asynchronous lectures and online critical thinking/problem solving assessments for free on commonly used online teaching resources, including MOOC, Coursera, and YouTube platforms. 4. Implement methods to evaluate the efficacy of the ASIBS Short Course by examining 1) the competencies and skills gained by the ASIBS Short Course participants, 2) the clarity and quality of the curriculum, 3) program logistics and operations, and 4) both the short term and long term applications of the ASIBS Short Course. The ASIBS Short Course will provide participants with a much needed foundation in applied statistical theory and statistical computing to answer important questions related to biological, social, and behavioral research. We believe that the ASIBS Short Course supports the mission of the National Institute of General Medical Sciences by enhancing the research capacity, thus increasing the productivity, of current and future leaders in academic medical environments.

Public Health Relevance

Biostatistics is at the core of clinical research, yet, many clinical researchers at academic medical institutions lack the knowledge and training of the fundamental elements of study design, data analysis, and computational tools to independently carry out their research projects, interpret statistical findings in the medical literature, and to contribute quantitative expertise to their research collaboration. The overall goal of the proposed ASIBS Short Course is to provide formal applied statistical training to faculty and fellows activel involved in research at US academic medical institutions. The ASIBS Short Course will provide participants with a much needed foundation in applied statistical tools to answer important questions related to biological, social, and behavioral research and increase the productivity of current and future leaders in academic medical environments.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Education Projects (R25)
Project #
5R25GM111239-02
Application #
9059139
Study Section
Biodata Management and Analysis Study Section (BDMA)
Program Officer
Marcus, Stephen
Project Start
2015-05-01
Project End
2020-03-31
Budget Start
2016-04-01
Budget End
2017-03-31
Support Year
2
Fiscal Year
2016
Total Cost
Indirect Cost
Name
Icahn School of Medicine at Mount Sinai
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
078861598
City
New York
State
NY
Country
United States
Zip Code
10029
Benn, Emma K T; Tu, Chengcheng; Palermo, Ann-Gel S et al. (2017) The ASIBS Short Course: A unique strategy for increasing statistical competency of junior investigators in academic medicine. J Clin Transl Sci 1:235-239