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Pathology Informatics: 5 Trends Shaping the Future of the Industry

mTuitive has been engaged in multiple pathology informatics initiatives and gatherings over the years. As the methods used and attitudes towards this approach have changed, we thought we’d share five observations of the biggest current trends in the industry.


Data integration is improving

Pathology informatics is transforming the way data is managed, analyzed, and utilized in the field of pathology. One notable advancement is the integration of digital pathology with laboratory information systems (LIS) and electronic health records (EHR). This integration enables seamless data flow between various systems, allowing pathologists to access patient information, previous test results, and clinical data alongside digital slide images. This integration not only improves workflow efficiency but also enhances the ability to correlate pathology findings with clinical data—leading to more comprehensive and accurate diagnoses.


AI, of course

The subject of artificial intelligence (AI) is EVERYWHERE these days and pathology informatics is no different. The application of AI and machine learning algorithms in pathology informatics has gained considerable momentum. AI algorithms can analyze vast amounts of pathology data, including images, text/reports, and molecular profiles to identify patterns, predict outcomes, and aid in decision-making. These algorithms can assist in tasks such as tumor grading, quantification of biomarkers, and identification of prognostic factors. The integration of AI in pathology informatics has the potential to augment pathologists' capabilities, reduce diagnostic errors, and improve patient management.


Whole Slide pathology is proving transformative

Whole slide pathology has witnessed remarkable advancements that have transformed the field of digital pathology. Whole slide imaging (WSI) technology—which allows high-resolution scanning of entire glass slides containing tissue samples—has become more sophisticated and widely adopted. These advancements have significantly enhanced the efficiency and accuracy of diagnostic processes in pathology. The development of faster and more powerful scanning systems allowed for the creation of large-scale digital slide repositories, enabling remote access to slides and facilitating collaboration among pathologists worldwide.


Big data and analytics

Another important development in pathology informatics is the utilization of big data analytics. Pathology laboratories generate enormous amounts of data and leveraging this data through advanced analytics can yield valuable insights. Big data analytics can identify trends, patterns, and associations within pathology information which facilitates research, quality improvement, and population health management. The ability to harness and analyze large datasets has the potential to advance precision medicine by enabling personalized treatment strategies based on individual patient characteristics and/or molecular profiles.


Workflows, Workflows, Workflows

All of these developments are contributing to the continuing improvement of pathology workflows. The adoption of both digital workflows and laboratory automation has significantly enhanced efficiency and standardization in pathology informatics. Automated systems for specimen tracking, barcoding, and data entry minimize human error and streamline processes. Digital workflows also enable real-time collaboration, bolstering interdisciplinary communication and reducing turnaround times for critical diagnoses.

These developments in pathology informatics, including integration with LIS/EHR systems, the application of AI and machine learning, the utilization of big data analytics, the transformative possibilities of whole slide imaging, and the implementation of digital workflows, are revolutionizing the field. These advancements have improved diagnostic accuracy, workflow efficiency, and data utilization, leading to enhanced patient care, research opportunities, and the potential for more personalized medicine in pathology.

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