A comprehensive survey of collaborative biostatistics units in academic health centers

Alexandra L. Hanlon, Alicia J. Lozano, Swathi Prakash, Emily B. Bezar, Walter T. Ambrosius, Guy Brock, Manisha Desai, Brad H. Pollock, Mary D. Sammel, Heidi Spratt, Leah J. Welty, Gina Maria Pomann

Research output: Contribution to journalArticlepeer-review


The organizational structures of collaborative biostatistics units in academic health centers (AHCs) in the United States and their important contributions to research are an evolving and active area of discussion and inquiry. Collaborative biostatistics units may serve as a centralized resource to investigators across various disciplines or as shared infrastructure for investigators within a discipline (e.g., cancer), or a combination of both. The characteristics of such units vary greatly, and there has been no comprehensive review of their organizational structures described in the literature to date. This manuscript summarizes the current infrastructure of such units using responses from 129 leaders. Most leaders were over 45 years old, held doctoral degrees, and were on a 12-month appointment. Over half were tenured or on a tenure track and held primary appointments in a school of medicine. Career advancement metrics most important included being funded as co-investigator on NIH grants and being either first or second author on peer-reviewed publications. Team composition was diverse in terms of expertise and training, and funding sources were typically hybrid. These results provide a benchmark for collaboration models and evaluation and may be used by institutional administrators as they build, evaluate, or restructure current collaborative quantitative support infrastructure.

Original languageEnglish (US)
Article numbere521
Issue number1
StatePublished - Dec 2022


  • biostatistics
  • collaboration
  • consultation
  • data science
  • evaluation metrics
  • leadership
  • workforce

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty


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