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Nursing Clinical Information System

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Related Experiment Video

Updated: Jun 2, 2026

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
07:41

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases

Published on: May 17, 2019

Web-based synoptic reporting for cancer checklists.

Brett W Baskovich1, Robert W Allan

  • 1Department of Pathology, Immunology and Laboratory Medicine, University of Florida College of Medicine, Gainesville, Florida.

Journal of Pathology Informatics
|May 17, 2011
PubMed
Summary
This summary is machine-generated.

Pathology departments can now automate cancer reporting with web-based synoptic report generators. This system simplifies data entry for critical elements, improving patient care and streamlining pathology information systems.

Keywords:
Cancer registrycancer checklistscancer report templatesynoptic reportingtumor reporting

Related Experiment Videos

Last Updated: Jun 2, 2026

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
07:41

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases

Published on: May 17, 2019

Area of Science:

  • Pathology informatics
  • Cancer reporting systems
  • Health information technology

Background:

  • Surgical pathology reports are crucial for cancer treatment guidance.
  • Increasing complexity of cancer reports leads to missing critical elements.
  • Standardized checklists from the American College of Surgeons Commission on Cancer (ACS-CoC) and College of American Pathologists (CAP) aim to ensure comprehensive reporting.

Purpose of the Study:

  • To develop a web-based system for generating synoptic cancer reports.
  • To automate the creation of reports based on CAP guidelines.
  • To integrate these reports into existing laboratory information systems (LIS).

Main Methods:

  • Developed a web-based system accessible across departmental workstations.
  • Utilized a parsing algorithm for automatic generation of web-based checklists.
  • Designed the system to output reports compatible with text-based anatomic pathology LIS.

Main Results:

  • Created multiple web-based synoptic report generators for ACS-CoC/CAP required elements.
  • Developed report generators for specific molecular tests (e.g., KRAS mutation) and FISH studies (e.g., UroVysion™).
  • Outputs can be pasted into LIS and compiled into a database.

Conclusions:

  • A straightforward method for automating web-based synoptic report development is presented.
  • The system facilitates entry into anatomic pathology LIS and databases.
  • This automation addresses challenges in reporting complex cancer data.