Key Focus Areas and Goals

The scope of cancer informatics at a cancer center is to serve informatics needs that span the cancer care and research continuum.

Cancer Research Data Commons

The Cancer Informatics Shared Resource (CISR), in close collaboration with other UF Health Cancer Center and UF entities, links cancer investigators to the data, methods and domain expertise on campus through the Cancer Enterprise Data Warehouse (Cancer EDW):

  • The large amount of unique data resources (e.g., UF Integrated Data Repository and OneFlorida+ Data Trust)
  • The appropriate cancer informatics tools and methods (e.g., data integration, terminology and ontology support, and data harmonization)
  • Analytical expertise

Cancer Informatics Tools and Methods

The CISR will provide support for informatics resources across their lifecycle, including the development of innovative methods and algorithms, early-stage software development, advanced stage software development and sustainment of high-value resources on which the UF Health Cancer Center community has come to depend. 

The CISR will:

  • Promote integration of informatics technology with hypothesis-driven cancer research and translational/clinical investigations
  • Provide flexible, scalable and sustainable informatics support using multiple mechanisms matched to the various needs of cancer investigators
  • Promote interdisciplinary collaborations in technology development and distribution
  • Promote technology dissemination and software reuse

Cancer Surveillance

The CISR will support the surveillance of cancer burden, cancer risk factors and cancer-related activities and research focusing on the UF Health Cancer Center catchment area and Florida, leveraging the heterogenous datasets in the center’s Cancer EDW (e.g., OneFlorida+, Florida Cancer Data System [FCDS], UFHealth EHRs, and local tumor registry data). These surveillance systems will be a shared resource for UF Health Cancer Center investigators to draw upon for their research and a tool for UF Health Cancer Center administrative leadership to visualize data that inform resource allocation, project prioritization and measurement of impact.

The CISR will generate data and maps of cancer statistics and cancer risk factors, including health behaviors and environmental factors to:

  • Support the evolving definition of the UF Health Cancer Center catchment area
  • Characterize the UF Health Cancer Center catchment area
  • Help conceive research ideas and identify research priorities
  • Identify communities and population subgroups at elevated cancer burden for outreach

eHealth and mHealth: Digital Health

The CISR will support the development and implementation of electronic health (eHealth) and mobile health (mHealth)—digital health interventions and programs. 

The CISR will facilitate the development and adoption of methods and tools to support:

  • The development and implementation of eHealth/mHealth applications and interventions
  • Data collection, processing and management in eHealth/mHealth applications
  • Integration of eHealth/mHealth applications to clinical systems (e.g., EHR systems) in close collaborations with the health system
  • Engagement of communities and key stakeholders in the development of eHealth/mHealth tools and other patient- or clinician-facing technologies that are relevant to addressing the needs of patients, especially those in the UF Health catchment area, in close collaboration with the UF Health Cancer Center Community Outreach and Engagement office

Natural Language Processing (NLP) Core

The NLP Core provides NLP resources and infrastructures to facilitate text analytics at the University of Florida Clinical and Translational Science Institute (CTSI) and the OneFlorida+ Clinical Research Network.

  • Providing key NLP resources and infrastructures in close collaborations with the Biomedical Informatics (BMI) program, UF Integrated Data Repository (IDR), OneFlorida, and the Cancer Informatics Shared Resource at the UF Health Cancer Center
  • Supporting OneFlorida as one of the NLP-enabled Clinical Data Research Networks (CDRNs) within PCORnet
  • Providing consultation regarding NLP solutions and tools for clinical research and applications
  • Providing NLP capability as a service at UF CTSI to bridge the gap of using unstructured clinical text for research
  • Developing NLP research and education programs to accelerate the UF Artificial Intelligence (AI) initiative
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