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Related Experiment Video

Updated: Jun 28, 2026

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
05:33

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

Published on: July 11, 2025

Real-time process "defect" collection within the anatomic pathology laboratory to facilitate informatics driven

Michael Riben1, Leslie Nesbitt, Shibu Ninan

  • 1M.D. Anderson Cancer Center, Houston, TX, USA.

AMIA ... Annual Symposium Proceedings. AMIA Symposium
|November 13, 2008
PubMed
Summary

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This study optimized anatomic pathology laboratory workflows by implementing a quick, two-part system for real-time defect tracking. The methods, using Post-it notes and software, are fast and applicable to other healthcare settings.

Area of Science:

  • Medical Laboratory Science
  • Healthcare Management
  • Process Improvement

Background:

  • Anatomic pathology laboratory workflows are complex and prone to process defects.
  • Efficient defect identification is crucial for optimizing laboratory operations and improving patient care.
  • Current methods for defect tracking may be time-consuming or inefficient.

Purpose of the Study:

  • To develop and evaluate a rapid, real-time process defect collection system for anatomic pathology.
  • To implement a dual-approach strategy for defect identification at both computerized and non-computerized workstations.
  • To assess the feasibility and time efficiency of the proposed defect collection methods.

Main Methods:

  • A two-pronged approach was developed for real-time process defect collection.

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Last Updated: Jun 28, 2026

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
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Published on: July 11, 2025

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Detection of Targetable Alterations in Non-small Cell Lung Cancer using Next-generation Sequencing

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  • Customized Post-it (3M) notes were utilized for non-computerized workstations.
  • A data collection module within a workflow integration software system was implemented for computerized workstations.
  • Each data collection method was designed to take less than 5 minutes.
  • Main Results:

    • Baseline data on process defects were collected pre-implementation.
    • The developed methods allow for rapid, real-time defect identification.
    • Both Post-it notes and the software module proved to be efficient data collection tools.

    Conclusions:

    • The developed 2-pronged approach offers an efficient solution for real-time defect collection in anatomic pathology.
    • The system's speed and simplicity facilitate workflow optimization.
    • The methodology shows potential applicability for process improvement in other healthcare domains.