Pros and Cons of PACS, VNAs for Medical Image Data Storage

December 19, 2017 - As healthcare providers invest in new medical imaging technologies that produce increasingly large and complex data files, organizations need to implement infrastructure tools that can support the storage and appropriate access of necessary patient records.

Picture archiving and communication systems (PACS) and vendor neutral archives (VNAs) are critical tools for storing imaging and making them viewable to providers at the point of care, as well as enabling collaboration across provider teams.

“Today's move toward collaborative care means more physicians need to have access to these images and image data, like radiology reports,” said IDC Research. “Providers making care management decisions want longitudinal records that provide a 360-degree patient view.”

“This 360-degree view makes it easier for providers to identify, or use decision support tools to help identify, the most effective treatments and care plans for individual patients (or specific populations) derived from the combination and the analysis of structured and unstructured information.”  

Both PACS and VNAs provide organizations with the means to store and manage their imaging data.

But choosing which infrastructure components to implement, if and when to upgrade, how to migrate data between disparate systems, and how to enable collaboration across the enterprise can be challenging for executive leaders.

What are some of the benefits and drawbacks of PACS and VNAs, and how can organizations develop a cost-effective, forward-looking roadmap for their ongoing imaging data migration needs?

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What are PACS?

PACS provide storage and convenient access to medical images such as ultrasounds, MRIs, CTs, and x-rays. PACS started to become popular during the transition from film images to digital files.   

Since then, PACS have become more advanced and now allow clinicians to remotely access images, interface with EHRs, and enhance images to help with treatment decisions.

PACS use digital imaging and communications in medicine (DICOM) to store and transmit images. DICOM is both a protocol for transmitting images and a file format for storing them. Medical imaging devices communicate with the application server through the DICOM protocol. Clinicians can then locate and view the image they want to see at a workstation in an office or clinic setting.

PACS are typically used by individual departments, such as radiology, cardiology, dental, and pathology, to manage digital images and share data within the department. But when each department has their own PACS infrastructure, clinicians cannot always view images that were taken by a different part of the organization.  

“If you have three PAC systems, a physician wanting to look at a patient’s images across all systems would technically have to open three different viewers, log in three different times and search for the patient three different ways,” explained James Han, Dell EMC Senior Manager of Healthcare Business Development and Alliances.  

“Then the physician would need to manually look at and process the images, and assemble them in their head.”

This process can be problematic for clinicians.  Multiple logins are time consuming and fragmented data is difficult to use for patient care.  While PACS can reliably store large amounts of imaging data, they can quickly become inefficient in complex organizations seeking to coordinate care.

To improve data sharing and interoperability capabilities, many organizations are now turning to VNAs, which were specifically developed to address some of the most significant shortfalls of PACS.

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What are VNAs?

Similar to PACS, VNAs are archives for DICOM-based images and content. However, they allow organizations to integrate the viewing and storage of different health IT systems regardless of vendor restrictions.

VNAs decouple the PACS and workstations at the archival layer by developing an application engine that receives, integrates, and transmits data. VNAs provide one viewing experience regardless of where the images come from.

For large healthcare organizations with thousands of clinicians, a single interface can save time and money by reducing the need to train end-users on each individual PAC system.

IDC states that VNAs “evolved as a way to address the vast amount of siloed information that has been created by departments implementing PACS over the past 15–20 years.”

VNAs address two major interoperability issues brought about by PACS: the ability to read files when organizations switch PACS vendors and the ability to share data among multiple PACS within the same organization.

PACS vendors usually use their own proprietary software, which can cause problems when clinicians need to view a file. If an organization decides to change its PACS vendor, the new system may have difficulty reading the data because the format used could only be read by the original vendor system.

VNA vendors all generally agree upon the storage of DICOM images, a standard DICOM network interface, and administrative updates.These standards allows compatibility among disparate vendor software and systems so entities can access files without interoperability issues.

Once organizations migrate their imaging data to a VNA, the VNA will manage all the administrative updates so migrating data in the future will be much more straightforward and there is less chance of a compatibility error.

While VNAs are a valuable and necessary tool for healthcare, there are some challenges that come along with implementing them.

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Addressing the biggest challenge for PACS and VNAs: Data migration

Despite the benefits of implementing a VNA, migrating from a PACS to a VNA can be an expensive and difficult process.

“While everyone recognizes the longer you wait to migrate the bigger of a problem you’re creating, it is a costly expense and a lot of CTOs don’t want to put their neck on the line for something like a VNA migration because it’s hard to justify,” said Han.

The longer organizations wait to migrate their data to a VNA, the more expensive it will be because there is more data to move. Organizations usually see an ROI in about two or three years, which is a very long wait in the fast-paced healthcare industry. The long period between investment and return is one reason why VNA adoption isn’t as high as it should be.

The PACS-to-VNA migration processes is also complicated due to the nature of the DICOM format, which has been in use for more than 20 years.

A typical data migration process consists of marking old archive files as read-only and copying the data to a new storage device. But a DICOM migration is more complicated, because a DICOM file contains multiple components that must all be updated correctly.

DICOM headers contain metadata, such as patient identification details. Headers are attached to each image, but the header is separate from the actual image.

The PACS also assigns that image a location pointer, which allows the system to retrieve the image from its storage location. The image, the header, and the pointers are all separate components of the file. When data is migrated from one system to another, images, headers, and pointers can become skewed.

If a pointer is not migrated correctly, the new system will not be able to retrieve the image from its location. If the header is not aligned with the image, the user will not be able to access that critical metadata and ensure they are looking at the right file.

When an organization migrates from a PACS to a VNA, it must go through a DICOM migration to essentially reset the images, pointers, and headers to ensure all of the information is correct.

If adopting a VNA, the organization only has to perform a DICOM migration once.  After that, the VNA will manage all necessary updates.

Every healthcare organization that relies on medical images will need to go through a DICOM migration eventually, either because they are upgrading their PACS or adopting a VNA.

Conducting a DICOM migration from one PACS to another PACS doesn’t guarantee that an additional DICOM migration won’t need to be performed in the future, whereas a VNA will eliminate the need to repeat the process.

Organizations that are prepared to do a DICOM migration need to think about the future of their medical imaging technology and the potential future expense of another DICOM migration.  They must also consider the risk that multiple migrations will compound the chance for errors.

“When data is discovered to be wrong at the end of the process during acceptance testing, organizations are months away from fixing it simply because of the work required to move the data,” said Informatica Chief Healthcare Strategist Richard Cramer. “Then there’s the problem of figuring out what went wrong.”

“The cost of getting it wrong is extraordinary, which is why there must be discipline and knowledge to invest in the infrastructure to do it right and as quickly as possible.”

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How to choose a VNA

Entities need to assess their current business and infrastructure needs as well as consider agility, scalability and how a prospective VNA fits into future IT infrastructure plans, according to IDC Research.

“In cases where VNA solutions meet business needs and offer more interoperability with an existing set of proprietary products, it is important to explore these offerings,” IDC advised.

“However, in the long run, the cost of migrating existing image archives to the platform will be significant, and buyers should evaluate platforms that support long-term business needs against those that offer cost or time-to-implement advantages in the short term, accordingly.”

“Providers need to understand their need for platform and/or specific workload and workflow capabilities when making VNA platform purchasing decisions.”

Organizations looking to purchase VNA infrastructure should:

• Assess the delivery model - considering a solution with cloud flexibility can make integrations and accessing data easier. Organizations should also look for solutions that have a good track record with HIPAA compliance.
• Build policies for working with a VNA - entities need to create policies that accommodate archive expansion. This clarifies which implementations are priority and allows entities to assign project time-frames more realistically.
• Seek out innovation - unstructured healthcare data will continue to grow and VNAs need to be able to adapt to new and better ways of sorting through data.
• Develop archiving best practices - each organization has different needs and priorities when it comes to archiving practices, which calls for constant experimentation and adjustments to approaches that will best benefit business needs, end users, and patients.
• Connect the VNA to other new technology investments - the advantages of VNAs don’t end with image viewing.  The tool can be integrated with EHRs, content management solutions, and mobile applications. Integrating with other IT infrastructure tools gives users a more dynamic way to access data no matter where they are.

Organizations also need to be aware of the influence of vendor name recognition. A recent PACS report found that many organizations chose a big-name vendor simply because they had a large customer base and were well-known in the industry.

For example, many organizations chose GE Healthcare because of name recognition. However, many customers reported dissatisfaction with how long it takes to resolve issues and noted GE’s more passive approach to solving problems.

While the poll referred to PACS vendor selection, the same caution can be used in the VNA market as well.

VNAs are a difficult technology to deploy, but they are necessary to improve imaging workflows and ensure adequate storage and access. Entities need to consider long-term goals that will support value-based care initiatives in order to justify this large health IT infrastructure deployment.

Organizations can still use PACS successfully, but in order to save money in the long run and quickly and effectively use medical images, VNAs should be considered as a promising option for reducing long-term costs and allowing greater interoperability around critical imaging data.