Enhancing Diversity in Biomedical Data Science

Background: Despite decades of research and interventions, significant health disparities persist. Seventeen years is the estimated time to translate scientific discoveries into public health action. This Narrative Review argues that the translation process could be accelerated if representative data were gathered and used in more innovative and efficient ways. Methods: The National Institute on Minority Health and Health Disparities led a multiyear visioning process to identify research opportunities designed to frame the next decade of research and actions to improve minority health and reduce health disparities. ''Big data'' was identified as a research opportunity and experts collaborated on a systematic vision of how to use big data both to improve the granularity of information for place-based study and to efficiently translate health disparities research into improved population health. This Narrative Review is the result of that collaboration. Results: Big data could enhance the process of translating scientific findings into reduced health disparities by contributing information at fine spatial and temporal scales suited to interventions. In addition, big data could fill pressing needs for health care system, genomic, and social determinant data to understand mechanisms. Finally, big data could lead to appropriately personalized health care for demographic groups. Rich new resources, including social media, electronic health records, sensor information from digital devices, and crowd-sourced and citizen-collected data, have the potential to complement more traditional data from health surveys, administrative data, and investigator-initiated registries or cohorts. This Narrative Review argues for a renewed focus on translational research cycles to accomplish this continual assessment. Conclusion: The promise of big data extends from etiology research to the evaluation of large-scale interventions and offers the opportunity to accelerate translation of health disparities studies. This data-rich world for health disparities research, however, will require continual assessment for efficacy, ethical rigor, and potential algorithmic or system bias.

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“…Training programs that support a data science concentration in health disparities are also needed. 60…”

Section: Discussionmentioning

confidence: 99%

Translational Health Disparities Research in a Data-Rich World

et al. 2019

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“…One such effort is ensuring that future generations of biostatisticians and data scientists fully engage and take advantage of the spectrum of diversity represented in the United States to access the widest pool of creativity and ingenuity. Some argue that the lack of diversity in science, technology, engineering, and mathematics (STEM) (Valantine and Collins 2015;Canner et al 2017;Nielsen et al 2017) disciplines greatly diminishes the nation's ability to maintain a competitive global economic edge (Commission on the Advancement of Women and Minorities in Science, Engineering and Technology Development 2001) and our ability to solve pressing health issues in all domains.…”

Section: The Importance Of Biostatistics In Biomedical and Public Heamentioning

confidence: 99%

Creating and Sustaining Effective Pipeline Initiatives to Increase Diversity in Biostatistics: The ENAR Fostering Diversity in Biostatistics Workshop

Benn

Tabb

Exum

et al. 2020

Journal of Statistics Education

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Biostatisticians with advanced degrees are highly sought after. Employment opportunities in the fields of mathematics and statistics are expected to increase dramatically by 2028. Underrepresentation of minorities in biostatistics has been a persistent problem, yielding a demographic landscape that differs substantially from the general U.S. population. In some instances, students may have the appropriate quantitative skills, but are unaware of biostatistics and in other instances, students may not yet have the appropriate quantitative background, but are intellectually capable and willing to shore up those skills once they learn about biostatistics as a viable, exciting career option. Therefore, to ensure robust scientific advancement, there must be a concerted effort to increase the pipeline of intellectually talented persons available with exposure to the appropriate quantitative skills who are interested in careers in biostatistics. The overarching goal of this article is to discuss the development, implementation, and impact of a federally funded pipeline initiative aimed at increasing the number of underrepresented minorities successful in graduate training and professional careers in biostatistics as well as establishing effective mentoring and networking relationships. Our findings provide a roadmap for the development of sustainable initiatives to promote diversity in biostatistics and science, technology, engineering, and mathematics fields more broadly. Supplementary files for this article are available online.

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“…Muchos hablan de una brecha digital cada vez mayor; sin embargo, también existe una brecha creciente y cada vez más evidente en Ciencia de Datos (Data Science) entre las instituciones de educación superior en los Estados Unidos. Hasta donde sabemos, no hay instituciones de educación superior que sirvan a población Hispana, Afroamericana o Nativa que tengan programas en Ciencia de Datos, y en general las instituciones que atienden a minorías enfrentan desafíos para integrarse a la comunidad computacional [1]. Otro tanto sucede en universidades públicas rurales, y colegios universitarios de dos años y universidades comunitarias (Community Colleges) [2].…”

Section: Reducción De La Brecha En Ciencia De Datosunclassified

“…En 2013 los Institutos Nacionales de Salud (NIH) crearon el programa de formación "Big Data to Knowledge" (BD2K) con el fin de incrementar la fuerza de trabajo en Ciencia de Datos aplicada a estudios biomédicos [5]. El programa "Increasing Diversity in Interdisciplinary Big Data to Knowledge" (IDI-BD2K) es uno de los proyectos de diversidad vinculados a la iniciativa BD2K, como se describe en [1].…”

Section: B Increasing Diversity In Interdisciplinary Big Data To Knounclassified

Estimulando la innovación en Ciencia de Datos Interdisciplinaria a través de ""Hackathons""

Franco¹,

Hernández²,

Zuázaga³

2018

Proceedings of the 16th LACCEI International Multi-Conference for Engineering, Education, and Technology: “Innovation in Educat

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There is a demand for biomedical scientists who can apply statistical analysis and computational methods to large volumes of data. The IDI-BD2K is a program that takes an interdisciplinary approach through informal teaching for faculty and students to create community and develop biomedical data science. This document describes the experience in the use of innovative hackathons and professional development workshops for teachers and students, as well as interdisciplinary courses to spur innovation in interdisciplinary data science in biomedical problems.

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Enhancing Diversity in Biomedical Data Science

Cited by 17 publications

References 13 publications

Translational Health Disparities Research in a Data-Rich World

Translational Health Disparities Research in a Data-Rich World

Creating and Sustaining Effective Pipeline Initiatives to Increase Diversity in Biostatistics: The ENAR Fostering Diversity in Biostatistics Workshop

Estimulando la innovación en Ciencia de Datos Interdisciplinaria a través de ""Hackathons""

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