Establishing a Data Science Unit in an Academic Medical Center: An Illustrative Model.

Journal Article (Journal Article)

The field of data science has great potential to address critical questions relevant for academic medical centers. Data science initiatives are consequently being established within academic medicine. At the cornerstone of such initiatives are scientists who practice data science. These scientists include biostatisticians, clinical informaticians, database and software developers, computational scientists, and computational biologists. Too often, however, those involved in the practice of data science are viewed by academic leadership as providing a noncomplex service to facilitate research and further the careers of other academic faculty. The authors contend that the success of data science initiatives relies heavily on the understanding that the practice of data science is a critical intellectual contribution to the overall science conducted at an academic medical center. Further, careful thought by academic leadership is needed for allocation of resources devoted to the practice of data science. At the Stanford University School of Medicine, the authors have developed an innovative model for a data science collaboratory based on 4 fundamental elements: an emphasis on collaboration over consultation, a subscription-based funding mechanism that reflects commitment by key partners, an investment in the career development of faculty who practice data science, and a strong educational component for data science members in team science and for clinical and translational investigators in data science. As data science becomes increasingly essential to learning health systems, centers that specialize in the practice of data science are a critical component of the research infrastructure and intellectual environment of academic medical centers.

Full Text

Duke Authors

Cited Authors

  • Desai, M; Boulos, M; Pomann, GM; Steinberg, GK; Longo, FM; Leonard, M; Montine, T; Blomkalns, AL; Harrington, RA

Published Date

  • January 1, 2022

Published In

Volume / Issue

  • 97 / 1

Start / End Page

  • 69 - 75

PubMed ID

  • 33769342

Pubmed Central ID

  • PMC8458473

Electronic International Standard Serial Number (EISSN)

  • 1938-808X

Digital Object Identifier (DOI)

  • 10.1097/ACM.0000000000004079


  • eng

Conference Location

  • United States