Addressing the Critical Challenge
One crucial yet unaddressed need is medical vocabulary standardization, vital for improving interoperability, patient safety, and clinical outcomes. While technical interoperability has been addressed through standards like DICOM, HL7, and FHIR, gaining insights from patient studies still falls short due to inconsistent data governance strategies in radiology studies. Different labels for similar exams make it challenging to search for similar cohorts, posing a dilemma for healthcare providers.
To make sense of the vast amounts of healthcare data generated daily, innovative analytical tools like artificial intelligence (AI) and machine learning (ML) are essential. These tools help healthcare organizations understand patient needs, identify patterns and trends, and develop personalized and effective treatments. Real-world evidence (RWE) frameworks, unlike traditional clinical trials conducted in controlled settings, offer insights into the effectiveness and safety of drugs and medical devices in real-world scenarios, reflecting diverse patient populations and clinical settings.
Enlitic's technology utilizes computer vision and natural language processing to analyze DICOM images, identifying various parameters like body parts, orientation, contrast, and slice thickness for CT, MR, and X-ray images. Additionally, the technology uses pixel data, metadata, and DICOM header tags to identify and protect Protected Health Information (PHI).
If you cannot easily control the way the studies and series descriptions are reaching you, then you need something like ENDEX™. Because otherwise, how do you expect the display protocols to work?
- Ernest Montañà, TMC
Our vision is to be the leading provider of data management and interoperability solutions for the medical imaging industry.
We believe that our Enlitic Curie™ framework can revolutionize the way healthcare professionals manage data and make decisions, leading to improved patient outcomes and more efficient clinical workflows. Our goal is to create a future where every healthcare provider has access to solutions that enable them to provide personalized care to every patient, no matter where they are in the world.
At Enlitic, we believe that the power of artificial intelligence can transform healthcare by enabling effective data management and improving clinical workflows.
Our mission at Enlitic is to intelligently manage healthcare data using the power of artificial intelligence to expand capacity and improve clinical workflows and create a foundation for a real-world evidence medical image database for healthcare providers.
Through our Enlitic Curie™ framework, we aim to reimagine healthcare intelligence, enabling healthcare professionals to make informed decisions and provide personalized care to every patient.
How We Add Value
Improving Data Quality
High quality data allows healthcare organizations to get full utilization on their tech stack and creates enterprise-wide efficiency gains.
Ensuring PHI Protection
While there are many freeware or add-on products that anonymize imaging data, most of them miss PHI. Our technology removes PHI from pixel data, metadata, and private tags ensuring patient information is protected and clinical information remains intact.
Advancing Patient Care
Standardized data allows for physicians to have accurate, consistent information quickly. They can better diagnose, treat, and monitor patients.
Realizing Monetization Strategies
By having high quality, actionable, standardized data organizations can begin to use it for data monetization. Additionally, our advanced anonymization allows it to be used safely.
Recouping Under-Billing Revenue
Patient findings often require a last-minute change in acquisition protocol and these changes are not always reflected in the billing system. Our technology finds these discrepancies and flags them so under coding issues can be resolved.
Accelerating Healthcare Innovation
Medical images are full of complex, diverse data that holds a lot of valuable insights if it is usable. While many new technologies require this data to improve, organizations know have what they need.