Welcome to our three-part series on DICOM data migration, where we explore the revolutionary approach brought forth by the recent acquisition of Laitek by Enlitic. In October 2024, Enlitic’s acquisition of Laitek marked a significant milestone in the world of medical imaging data management, combining Laitek’s expertise in data migration with Enlitic’s advanced AI capabilities.
This series will delve into the different stages of AI-enabled DICOM data migration, showcasing how this powerful partnership is transforming the landscape of healthcare data management. We’ll explore how the integration of artificial intelligence is addressing long-standing challenges in data migration, offering solutions that are not only faster and more accurate but also less disruptive to healthcare operations.
In the coming posts, we’ll break down the migration process into three key stages, examining how AI is revolutionizing each step. From initial data assessment and planning to the actual migration process and post-migration optimization, we’ll uncover the innovative techniques that are setting new standards in the industry.
Stay tuned as we unravel the complexities of DICOM data migration and discover how AI is paving the way for a more efficient, accurate, and seamless future in healthcare data management.
Step One: Establish Project Inventory and Validate Scope
Migrating DICOM data from one Picture Archiving and Communication System (PACS) to another is a complex process that requires careful planning and execution. Before embarking on this journey, several crucial steps must be taken to ensure a smooth transition. Here’s a comprehensive guide to the pre-migration process:
Inventory: LAITEK begins each project by performing a comprehensive CFIND in legacy PACS to inform the project of all studies, data, and images that need to be migrated. This process is vital for LAITEK to understand not only how the legacy system interacts with other modalities and systems in the current site — through examination of the DICOM logic — but to confirm the contents of the PACS.
- Sites regularly misunderstand their own systems and the contents of their site PACS. A site may claim to have 60m images, but in fact they have 50m or 85m. The inventory is an extraordinarily important part of the project launch to ensure LAITEK not only moves everything, but moves it how it should be moved, to where it belongs.
- What LAITEK Looks For: Number of studies, type of studies, total number of images for patients, breakdown of modality, etc.
Validate: Confirm consistency between the EMR’s study & patient information and the data housed within the PACS Database. The EMR is the site’s source of truth as it is the most up-to-date content for every patient. This is the first level of defense when it comes to catching data errors and inconsistencies across data sets.
Step Two: Establish Legacy System Connection & Replicate DBMS
Establish Connection: Using one of the 60+ proprietary connectors LAITEK has developed, we establish a 1:1 connection with the legacy system to extract a copy of the PACS Database.
Create Replicate Environment: Using this Database copy, LAITEK replicates the legacy system’s structure into our MIGRATEK Software as an operational “nonproduction environment.”
- Why Does This Matter? PACS Databases are synced to the site’s EMR and should contain the most up-to-date patient information available. The Database, however, is held separate from the DICOM file storage. When a study is performed, it is stored with the patient information available at the time. If updates to the patient record are made, the Database is updated, but the stored file will retain outdated information until the study is retrieved.
- Example: A John Doe is admitted to the hospital with trauma to the head. Without any identification, the hospital must register him under unknown credentials. The radiologist performs necessary studies, which are stored in the PACS under the information available. Days later, the man comes-to and identifies himself. His patient record is updated through the EMR, which updates the Database. However, it is not until a physician retrieves his CT scan that the DICOM file passes back through the database. Once it does, the information is rewritten to the most current data available in the EMR. John Doe’s CT becomes Steven Richards’ CT.
- Why Does It Work This Way? PACS/VNAs hold petabytes of data. A single patient could have countless studies, labs, etc. within the site’s storage. To prevent taxing the system when a patient record is updated, files are only corrected when they are retrieved.
- Why Does LAITEK Replicate the Legacy PACS? LAITEK does not simply migrate data. During our MIGRATEK Advanced Migrations, we scan, match, normalize and clean the data to ensure the best possible version of the legacy PACS is migrated into the new system. Think of it like a moving service. But instead of a company that just shows up and moves all of your boxes into a van and dumps them on your front lawn, LAITEK makes sure each box is properly labeled, organized into the room that it should be moved to in the new place, wraps your furniture in protective packaging, and ensures that every single item that should make it to the new place, does. LAITEK does that for millions of images, amounting to petabytes of data. Not just data — vital patient information. This, understandably, requires an incredible amount of energy.
- What Difference Does It Make? LAITEK doesn’t just move the DICOM file data, we reconcile it, clean it, and format it into the best possible version of itself for the new PACS/VNA system — and it does this for every single file it processes. If LAITEK did all this work within the production environment of the site, the entire system would be burdened and be forced to slow down. This really isn’t an option for healthcare providers, which is why most migration companies manage their project during off hours. Because LAITEK replicates the legacy environment, we can validate, reconcile, and clean up data around the clock with zero burden to the site’s system performance.
- How does Artificial Intelligence Impact the Migration Laitek utilizes the Enlitic data standardization module ENDEX to assess the study and series descriptions. Using computer vision and natural language processing the module ensures that the study and series descriptions are:
- Correct: DICOM fields reflect accurate information
- Complete: Empty fields are completed
- Consistent: Descriptions for similar studies match throughout the database
As we conclude the first part of our three-part series on AI-enabled DICOM data migration, it’s clear that the initial assessment and planning stage has been revolutionized by the Laitek-Enlitic collaboration. This crucial first step sets the foundation for the entire migration process, and the integration of AI has brought about significant improvements in efficiency, accuracy, and strategic planning. Let’s recap the key points we’ve covered:
- AI-powered data discovery and analysis have dramatically reduced the time required for initial assessments, allowing for quicker project initiation.
- Machine learning algorithms now provide more accurate predictions of potential migration challenges, enabling better resource allocation and risk mitigation.
- Intelligent data mapping and classification have improved the quality of migration planning, ensuring a more seamless transition of complex DICOM datasets.
- The AI-driven approach has enhanced the ability to identify and prioritize critical data, ensuring that the most important information is migrated first.
These advancements in the initial stage of data migration are not just technical improvements; they represent a fundamental shift in how healthcare organizations can approach large-scale data projects. By leveraging AI in this crucial planning phase, institutions can now embark on migration projects with greater confidence, clearer objectives, and a more strategic roadmap.As we look ahead to the next part of our series, we’ll delve into how AI is transforming the actual migration process itself. We’ll explore the innovative techniques being employed to handle the complex task of moving and converting vast amounts of DICOM data with unprecedented speed and accuracy.
Stay tuned for Part 2, where we’ll continue our journey through the cutting-edge world of AI-enabled DICOM data migration. The foundation has been laid – now it’s time to see how AI is revolutionizing the core of the migration process.
Are you facing challenges with healthcare data workflows? Our team offers free consultations to help optimize your radiology processes and AI integration. Contact us today to schedule a meeting and discover how we can enhance your healthcare data management.
