The move toward value-based reimbursement is shaking up traditional healthcare in all kinds of ways, as connectivity and cost-effectiveness become critical attributes in care delivery. Proprietary PACS used in image acquisition systems are starting to feel the squeeze from this dual pressure, as vendor-neutral archives (VNAs) take over many of their functions.
A recent study by research firm MarketsandMarkets predicts a PACS-less radiology world by 2018. Consultant Donald Dennison told attendees at the opening session of the Society for Imaging Informatics in Medicine's (SIIM) 2015 meeting that there are three external market forces trickling down into the imaging informatics world and leading to the demise of PACS: money, electronic health record (EHR) adoption, and consolidation. Dennison is a director-at-large for SIIM's board and also chair of the American College of Radiology (ACR) Connect Committee.
While PACS have traditionally been the workhorses of departmental diagnostic imaging (providing workflows, viewing, and archiving), their departmental focus creates silos that severely limit the ability of an organization to share images freely. PACS has also created unnecessary and expensive complications in managing storage. With the move toward value-based care, this siloed approach is rapidly being replaced by a patient-centric information model, and proprietary applications are rapidly going the way of the dinosaur.
As Dennison noted, the demise of proprietary PACS is driven by money (value-based payments), the adoption of EHRs (and the need to integrate image data with those applications), and the rapid pace of mergers and acquisitions in healthcare (which demands more ability to share data between enterprises to achieve value-based care). This combination of industry drivers and the adoption of vendor-neutral archiving is the meteor strike that will so radically change the care delivery model that the siloed beasts of proprietary PACS will no longer be equipped for survival.
At the heart of the new information model is the VNA. This technology can gather all of the pertinent data and images into a standardized, patient-centered storage model that makes image sharing much easier. Also, as VNAs have added enterprise workflows and diagnostic viewing capabilities, they have duplicated many of the functions of the departmental PACS.
VNAs will evolve
While having a VNA to unify all of your imaging is a good idea, it also has limitations. A simple VNA is more evolved than a PACS, but without more evolution and growth, it too will be unable to survive in the changed environment created by value-based payments and the need for integration and cross-enterprise sharing. Fortunately, the VNA model is more adaptable than most PACS and is rapidly evolving to be far more than a DICOM-image repository.
An important part of value-based care is the ability to unify all data associated with a patient and deliver the right parts of that data where and when they are needed. That requires not only DICOM images, but also associated clinical documents and non-DICOM documentary images (such as photos to document wound care). And all of that data must be integrated with the patient's electronic health record.
Finally, a layer of analytics is needed to ensure that relevant data can be extracted as needed. This offers two important benefits. First, it improves the quality of care by ensuring that relevant data are available for more precise diagnostics. Second, data extraction and analytics create a new opportunity to use machine vision for early detection of chronic disease, allowing providers to intervene at a time where prevention can make a big difference in outcomes.
The vision of the true VNA is to incorporate external data and combine it with the primary capture data to trigger workflows that enable a broader understanding of the patient's health status. This allows the image data to be used in ways that go far beyond what a departmental system is able to deliver.
Analytics offers broad benefits
Beyond improving immediate care for individual patients, we have an opportunity to learn more about the progression of diseases if we can use this unified data approach in predictive and population health analytics.
Imagine if you are an oncologist and you could analyze images of tumors from a large cohort of patients to compare with your patient's tumor. If you could also analyze the treatments and outcomes for those patients whose tumors most closely matched your patient's tumor, you would have valuable insight into what worked and what didn't work.
That could help you provide a more precise treatment plan for your patient. It could reduce the need for debilitating chemotherapy agents that aren't as effective, lower costs, and save your patient from needless suffering. It could possibly even offer the patient a longer survival time.
As the VNA grows beyond image archiving, maybe a new name will be needed. Judy Hanover, research director at IDC Health Insights, has defined a new name that might catch on: application-independent clinical archive (AICA). As she said in a 2014 article, "AICA is, in many ways, a second generation of VNA, but the AICA is differentiated from the VNA by the notion of patient centricity and the shift in focus from storage rationalization to enhancing clinical relevance."
Whatever name you call it, we are moving toward a truly patient-centered archive that will offer far more value to the enterprise than departmental PACS or the simpler versions of VNAs. That's good for all of us.
Dr. Nick van Terheyden is the chief medical officer of Dell Healthcare and Life Sciences.
The comments and observations expressed herein are those of the author and do not necessarily reflect the opinions of AuntMinnie.com.