Unlocking Data Flow: High-Performance Storage for Medical Imaging and Analytics

As healthcare organizations must juggle multiple priorities when it comes to data storage, including accessibility, security and scalability, it’s important for them to consider today’s data needs while planning for the future. 

“The headache of planning around data growth has led healthcare organizations to compromise data performance by buying cheaper, less expensive and slower storage,” Dobbs says. “But in the next 10 years, they need to think about how much more active or alive all data will be, especially with artificial intelligence adoption and new imaging technology coming to market.”

More Robust Storage Solutions Empower Patient Care

As the volume of radiology and cardiology imaging has grown, the number of physicians studying radiology has declined, according to the American College of Radiology. 

“Many healthcare organizations are looking toward AI as a solution to combat physician burnout, as fewer radiologists are entering the field, compounding the need for new ways to quickly and safely analyze the patient data,” Dobbs says, adding that AI can help physicians diagnose more quickly as long as it can access the data.

“The AI trend in EI began a while back, and we have close to 700 FDA-approved algorithms in the U.S. alone,” he adds. “In some cases, a single AI algorithm can process through 20,000 studies in an hour. Which is staggering when the average radiologist reads approximately 45 to 100 studies a day.” 

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EI aims to enhance clinical workflows, improve patient care and facilitate interoperability across departments. EI expands storage needs beyond radiology and cardiology data sets and into departments such as dermatology, digital pathology and genomics. Digital pathology data sets can be 10 times larger than that those used in radiology, leaving organizations to find highly scalable and cost-effective data platforms.

To combat EI data growth, cloud storage vendors rose to become a part of an overall strategy as a general-purpose storage solution that can be used for various types of data, providing scalable, flexible and remote storage options. Over the past decade, cloud storage options have provided relief to some organizations. 

“We are now hearing from customers and vendors that if they haven’t lifted their EI platforms into the cloud yet, then they may not move at this point, as the promise of cost savings and simplicity wasn’t really the story for EI data, and in some cases it worsened patient workflow,” Dobbs says. “Hybrid storage solutions may be best for enterprise imaging, as long as the combined solution is modern and carries the same values you get from cloud storage technology, be it on-premises or in public or private cloud.”

LEARN MORE: Look ahead to the future of medical imaging and AI with cloud-based applications.

Seeking Precision Medicine in Imaging

Healthcare organizations are looking at their storage solutions to also support better workflows so that physicians across departments can get to imaging data more quickly, which helps them work more efficiently with patients. 

“Data and digitization efforts have healthcare seeking this idea of precision medicine, and with enterprise imaging data, that means we need to deliver data platforms that can seamlessly tie together radiology, cardiology, pathology and genomics information and feed it to the physicians and AI algorithms that require it, when they require it. This drives the need for high-performance, scalable and simple data platforms,” Dobbs says.

On a larger scale, Dobbs says that healthcare organizations must consider how imaging data is used over its life span, not only by physicians but by everyone who would need access to the data.

“Patient imaging data isn’t just accessed by the radiologists or a few AI algorithms; its accessed by hundreds or thousands of users,” Dobbs says. He adds that access is important, as electronic health record systems are integrated to recall images and radiology reports across the entire enterprise, including by the referring physicians and the patients themselves.

Making Storage Solutions for the Future of Healthcare

Dobbs says healthcare organizations should be looking for highly scalable, performant, cost-optimized data platforms that minimize environmental impacts around power, space, e-waste and cooling. The data platform must be enterprise-grade and able to support both human and AI users.

Healthcare organizations should reflect on why and how they made data management choices for their EI applications. Short-term and long-term storage tiers may exist due to budget constraints or best practices established over a decade ago, Dobbs adds.

“It’s important to think about how your data needs will change over the coming three to five years, and how your patient data workflow may evolve,” Dobbs says. “Challenge your legacy storage deployment choices and build new best practices that serve your organization’s data needs. Do you have enough bandwidth, consistently low latency and scalability to support some or all of your EI data? Is a hybrid environment best? If so, what type of hybrid architecture? Does the cloud provide you value, or are there better storage alternatives for your organization to consider?”

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