Consolidated radiology and pathology data brings precision to cancer care

Fragmented data is a barrier to improved cancer treatment goals
07:34 AM

Fragmented data is a barrier to improved cancer treatment goals

Photo: LumiNola / Getty Images / GE Healthcare

Radiology and pathology play interconnected roles, especially in cancer diagnosis. But the current fragmented approach poses challenges. By integrating data through efficient Enterprise Imaging strategies, care providers can improve speed and accuracy in treatment planning.

When it comes to cancer diagnosis, traditional practices within radiology and pathology often operate in isolation, despite their crucial interdependence. This fragmented approach poses significant challenges, particularly when comprehensive data integration is essential for accurate diagnosis and treatment planning. 

For example, while radiologists globally recognise the importance of imaging/pathologic correlation, its practical implementation remains limited in routine clinical settings. Helping to address this, GE Healthcare’s enterprise approach aims to provide clinical depth and AI at the point of care by making digital pathology images and results an integrated part of the imaging patient record within its VNA solution.

Rapid reporting

Thanks to collaboration with Tribun Health, GE Healthcare’s VNA solution makes more accurate pathology reports available more quickly, created with the assistance of artificial intelligence (AI) provided by Tribun Health’s Solutions. It enables collaboration among pathologists and clinicians by making data available in one consolidated location.

The benefits of integration can be illustrated by a typical scenario - a patient who presents with a breast tumour. Genomic analysis might suggest a benign course, while histopathologic and radiologic features might indicate a more aggressive phenotype which makes chemotherapy necessary.

This kind of conflict underscores the importance of collaboration between radiologists and pathologists. By integrating data from different specialties in a unique and accessible repository, healthcare providers can identify and address discrepancies early, enabling personalised treatment strategies tailored to each patient's unique profile.

With this approach, the entire oncology care pathway, with its complexity involving multiple specialists, tools, decisions, and datasets, can be simplified through data consolidation.

Joined-up data

From an IT perspective, the integration of pathology into the Enterprise Imaging (EI) solution offers significant advantages over standalone digitisation efforts. By consolidating radiology and pathology data in a unified platform, healthcare providers can streamline IT systems, reduce costs, and centralise integrations.

Cost savings are not the only benefit. An integrated multi-ology EI solution enhances clinical value by providing comprehensive patient information in a cohesive manner. The consolidation of IT systems not only cuts costs but also enhances clinical workflows and facilitates collaborative decision-making.

With integrated IT solutions, radiologists and pathologists can seamlessly access and analyse patient data, leading to more accurate diagnoses and personalised treatment plans. IT consolidation also enables scalability and interoperability, laying the foundation for future innovations in cancer diagnosis and management.

GE Healthcare’s Solutions for EI enable a connected care approach, offering efficient data management and streamlined access. With the addition of digital pathology information to the VNA, the solution provides a comprehensive view of the oncological patient record.

Having been a trusted partner for customers worldwide for over a decade, GE Healthcare supports many European customers (including in Spain, Sweden, United Kingdom, Italy, and France) who have recognized the value of integrated Enterprise Imaging strategies, leading to benefits at both clinical and operational levels.

To learn more, visit GE Healthcare at HIMSS24 Europe in Rome and request a demo.

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