Big data in vascular surgery: registries, international collaboration and future directions

Academic Article


  • Given the increasing availability of large data set, small single-institutional series raise decreasing attention. Rapid expansion of technology from electronic medical records to easily accessible internet access, and widespread use and acceptance of registries in the medical world has allowed for research and quality improvement efforts using ‘big data’. Big data, although technically not defined, typically refers to large databases that can be used to investigate common or rare disease processes or outcomes, describe variation in clinical practices across and between different specialties at various practice location, whilst allowing important information about trends over time. Big data have allowed investigators to quickly assimilate cohorts of patients and/or procedures to answer current questions, with more complete population representation and improved generalizability whilst decreasing the likelihood of power problems and type II errors. On the other hand, pitfalls still exist with the growing problem of hypothesis fishing, lack of granularity and the fear by many clinicians that registry transparency may have already gone too far, where surgery groups or individual surgeon outcomes are readily available to patients and referring providers. Within vascular surgery specifically, big data have expanded over the last decade and now includes regional, national and global registries that have major benefits of gathering specific clinical and procedural information within vascular surgery. In this review, we highlight the main vascular surgery registries and recap a few success stories of how the registries have been leveraged to benefit discovery, quality improvement and ultimately patient care. Additionally, we outline future directions that will be imperative for continued expansion, acceptance and adoption of ‘big data’ utilization inpatients with vascular disease.
  • Published In

    Digital Object Identifier (doi)

    Author List

  • Sutzko DC; Mani K; Behrendt CA; Wanhainen A; Beck AW
  • Start Page

  • 51
  • End Page

  • 61
  • Volume

  • 288
  • Issue

  • 1