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<p>Modern cancer centers face increasing data-driven demands from institutional, state, and federal stakeholders, as well as from patients and communities. Data now functions as a strategic asset that supports care delivery, research, education, community engagement, and policy improvement and development. However, many cancer centers continue to operate with fragmented systems, limited interoperability, and underdeveloped analytics capacity, which constrain their ability to meet expectations or drive innovation. This perspective advocates for adopting a Learning Health System - Learning Health Community (LHS-LHC) framework as a strategic approach to modernizing cancer data and data science infrastructure. We outline how cancer centers can develop integrated, interoperable, and inclusive data systems that enable continuous learning, promote equity-driven outcomes, and generate real-world impact. By embedding data and data science as core institutional infrastructure, and by aligning investments across health systems, funders, and community partners, cancer centers can enhance their role as regional anchors for coordinated, patient-centered care and lead a national transition toward data-enabled oncology.</p>

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Modernizing data and data science infrastructure as a strategic asset for cancer center

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年1月9日

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  • Yi Guo,
  • Thomas J. George,
  • Alison M. Ivey,
  • Jonathan D. Licht,
  • Gigi Lipori,
  • Aik Choon Tan,
  • Lang Li,
  • Emily C. Webber,
  • Christina M. Scifres,
  • Kun Huang,
  • David A. Haggstrom,
  • Kelvin P. Lee,
  • Rachel E. Patzer,
  • Jiang Bian

摘要

Modern cancer centers face increasing data-driven demands from institutional, state, and federal stakeholders, as well as from patients and communities. Data now functions as a strategic asset that supports care delivery, research, education, community engagement, and policy improvement and development. However, many cancer centers continue to operate with fragmented systems, limited interoperability, and underdeveloped analytics capacity, which constrain their ability to meet expectations or drive innovation. This perspective advocates for adopting a Learning Health System - Learning Health Community (LHS-LHC) framework as a strategic approach to modernizing cancer data and data science infrastructure. We outline how cancer centers can develop integrated, interoperable, and inclusive data systems that enable continuous learning, promote equity-driven outcomes, and generate real-world impact. By embedding data and data science as core institutional infrastructure, and by aligning investments across health systems, funders, and community partners, cancer centers can enhance their role as regional anchors for coordinated, patient-centered care and lead a national transition toward data-enabled oncology.