Curie|ENDEX
The Curie|ENDEX application transforms medical imaging data to a consistent, clinically relevant standard nomenclature and enables relevant clinical content linkage across different IT systems. Endex enables consistent display of hanging protocols, improves image routing and orchestration intelligence. It forms the foundation of any successful artificial intelligence strategy and is crucial in developing a real world evidence database.
HOW IT WORKS
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Endex maps heterogenous DICOM headers to a defined universal ontology
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Studies and series now appear with normalized descriptions enabling effective hanging protocols
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Relevant, uniform descriptions facilitate faster reporting time, easily queried studies, and less frustration from radiologists
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Manual intervention is reduced by 16 seconds on average per study
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PACS Administrators and technologists reclaim time from mundane tasks
Reduced Mouse Mileage
Improves Satisfaction with PACS
Return on Investment
Based on Study Results
On Average Saved per Study
Reclaiming Lost or Wasted Time
Curie|ENDEX will:
Enhance your workflow and increase operational productivity by reducing manual intervention
Improve radiologist job satisfaction by reducing frustration with hanging protocols
Reduce your physician burnout by eliminating repetitive tasks and reducing reporting times
Decrease the complexities of PACS hanging protocols by better enabling their operation
Reduce potential repetitive stress injury by reducing mouse mileage
Expand capacity across multiple roles by reclaiming time
Why ENDEX is Right for You
In today’s imaging department countless hours are wasted dealing with problems that affect hanging protocols, image routing and AI orchestration. At the core of our healthcare interoperability challenges is non-standardized clinical data.
- Studies and series are technically identical but labelled differently creating display and processing issues
- Series descriptions lack clinical relevance
- Different facilities label studies differently making comparisons impossible
- Data is missing for a variety of reasons, including anonymization for research purposes
- Medical imaging data is excluded from analysis due to incomplete or irrelevant data labels
- Patient studies are routed incorrectly to work lists or workstations because of mislabeling
And more…
Benefits for All
Radiologists Reduce Frustration with PACS
PACS Admin Reclaim Time from Mundane Tasks
Department Leaders Improve Operational Productivity
C-Suite Increases Staff Satisfaction and Higher Efficiencies
