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Efficiency and accuracy of pathology reporting can increased with structured templates that are pre-filled with information from AI-analysed histological sections
About
Smart Reporting solutions for pathology can be used to develop standardised templates for gastrointestinal biopsy reporting. Guideline-based decision trees help to capture data efficiently to reduce the time histopathologists spend per report. They ensure that consistent scoring systems to grade disease can be used across pathologists and sites. As data is captured in a fully standardised and machine-readable way, it can be used for powerful clinical analytics, data mining and to train AI algorithms. Input from AI algorithms can be used to pre-populate reports based on automatically detected target structures in digitised histological sections. This can help to further speed up reporting, to direct pathologists’ attention to abnormal specimens or parts of slides with unusual morphology, to integrate quantitative measurements into reports, to automate quality assessment. The accuracy of AI algorithms can be accessed and improved via the corrections applied by pathologists to pre-filled reports. Structured data from gastrointestinal biopsy reporting in a real-world setting can be aggregated on a cohort-level to increase understanding of disease pathophysiology and impact of changes to treatment on patient outcomes. A comparison of pre-treatment disease activity or severity classification with post-treatment response can be facilitated by consistent data capture. Pathology laboratories can benefit from reduced time to report and automated workflows that retrieve images and other information from PACS, LIMS, HIS or EMR. Attention of skilled professionals can be directed to complicated specimens. Referring physicians benefit from standardised reports to improve decision-making regarding treatment and monitoring, and disease control. Patients benefit from improved diagnostic accuracy and time to diagnosis.
Key Benefits
Time Savings o Seamless integration and an array of workflow optimising features such as "normal findings" pre-sets can help pathologists to become faster in reporting - in both routine cases as well as complex clinical questions. Structured Data o Pathology reports have a structured and synoptic format, making them readily available for data mining and training of AI. Improved Completeness o Templates consist of context-specific decision trees and are continuously updated according to latest clinical guidelines. This guidance drives completeness Guideline-based Decision Trees o Decision trees are developed in collaboration with leading experts and incorporate latest classifications and guidelines. A unique modular approach enables pathologists to remain flexible to report on any patient's unique biology Consistency o A report is generated instantly as pathologists work their way through the decision tree. The reports are consistent in the terminology used and their format to improve communication and decision making – while texts can be edited wherever necessary. Interoperability & workflow integration o An interface ensures compatibility with existing IT-infrastructure and allows for the integration of Smart Reporting into existing workflows. Together with integration and technology partners, Smart Reporting is able to provide a streamlined reporting workflow and an enhanced user experience. Smart Reporting solutions can be embedded within existing RIS or PACS and used in conjunction with speech recognition solutions. Curated Digital Textbook o At relevant and critical stages within the decision tree pathologists are supported with context-specific clinical background information. This includes detailed description of guidelines, classifications or excerpts from relevant literature. These "info-boxes" typically also include graphical illustrations of the pathology and reference images.
Applications
Pathology, radiology