For Hyland, interoperability, clinical AI and cloud adoption are the HIMSS20 trends to watch
Update: HIMSS20 has been canceled due to the coronavirus. Read more here.
Hyland, a vendor of content services and enterprise imaging technologies, will have a major presence at the HIMSS20 Global Conference. It’s a big player in healthcare information technology, and has a team with decades of experience in the industry.
Ahead of HIMSS20, Healthcare IT News interviewed Susan deCathelineau, senior vice president of healthcare sales and services at Hyland. She offers her perspective on the key trends impacting conference attendees. She identifies interoperability, AI for clinical uses, and providers finally embracing the cloud as three trends that healthcare CIOs and other health IT leaders should be on top of.
Interoperability in healthcare
The healthcare industry is more than 10 years removed from the passing of the Health Information Technology for Economic and Clinical Health Act (HITECH) and much of the industry still is struggling with health IT interoperability.
Achieving an infrastructure where patient information is securely and easily exchanged not only within a health system but also throughout the care continuum is important because it is the basis for delivering a longitudinal digital record that travels with the patient, deCathelineau asserted. Furthermore, it is absolutely essential to delivering on the promise of patient-centered care, she added.
“Universal adoption of technology standards and integration with dated legacy systems are obviously two hurdles to interoperability that need to be overcome,” she said. “However, another is ensuring unstructured data is properly identified, consolidated and managed as part of the overall digital patient record.”
"HIMSS 2020 attendees should be sure they’re including unstructured data considerations in their interoperability initiatives."
Susan deCathelineau, Hyland
Much of the interoperability focus to date has been on ensuring structured patient data is easily interoperable and exchanged. On the other hand, unstructured information – such as clinical documents, narratives, consents and images – has largely been overlooked and often represents a larger chunk of the historical data that exists on a patient, she said.
“In fact, analysts like Gartner and IDC estimate that as much as 80% of patient information exists in an unstructured format outside of core clinical systems such as an electronic health record,” she added.
The importance of unstructured data to the interoperability equation was accentuated by some recent research HIMSS Media conducted with support from Hyland Healthcare. More than 115 healthcare leaders from healthcare provider organizations were surveyed for this research and 53% of respondents identified managing unstructured data as a primary barrier to interoperability.
Survey participants also mentioned that, on average, 73% of the unstructured patient data that exists in their organizations is inaccessible to key clinical stakeholders for review and analysis. When this information is absent from the digital patient record, a clinician’s view of that patient is woefully incomplete, she asserted.
“HIMSS 2020 attendees should be sure they’re including unstructured data considerations in their interoperability initiatives,” she advised.
Artificial intelligence for clinical support
AI is one of the hottest trends in healthcare and for good reason: It has the potential to truly transform healthcare from a clinical perspective, deCathelineau said.
“The industry finally seems to be gaining some perspective on how to leverage and apply AI in healthcare settings to achieve results,” she continued. “Futuristic visions of AI replacing physicians – and the fear, uncertainty and doubt that goes along with them – are being replaced by realistic applications of the technology that focus on automating mundane tasks, optimizing workflows and analyzing vast seas of data to support clinical decision making.”
AI now is being viewed as a much-needed complement to physicians at a time where they are being overwhelmed by data, she stated.
“The technology can help make these clinicians more effective by streamlining or eliminating tedious tasks, such as manual documentation and data search,” she explained. “It can help cull information, helping physicians to focus on key areas of interest, expediting diagnosis and improving accuracy. At the same time, it can free up physicians so they can spend more time with their patients.”
One of the hottest applications of AI in healthcare is in the medical imaging space. AI and machine learning algorithms are being leveraged to analyze thousands of anonymized diagnostic patient images to identify and detect indicators of everything from lung cancer to liver disease. AI is helping to accelerate the valuable research being conducted in each of these areas, she noted.
“While the potential of AI is exciting, it is important to note that any AI algorithm is ultimately dependent upon the data that feeds it,” she cautioned. “In other words, a healthcare provider must ensure its data pool is complete, consolidated and clean in order to achieve optimal results from any AI initiative.”
Providers finally embracing the cloud
The healthcare industry has long been branded as a laggard when it comes to its technology maturity. This is particularly true when it comes to cloud adoption, deCathelineau said.
“Healthcare providers have historically been hesitant to move to the cloud due to fears about giving up control of their data and putting patient privacy at risk,” she said. “However, the hesitancy that used to surround cloud adoption in healthcare now is being replaced by the realization of its ultimate inevitability. Once again, this shift in mindset largely has to do with data overload.”
The compounded growth of EHR data, medical images and video combined with the emergence of genomic data and information from smart devices has outgrown the capabilities of most on-premises healthcare data centers, she said.
“The ability to not only store this information but ensure it is properly encrypted and fully redundant requires an infrastructure that, for most, is only realistically available in the cloud,” she contended. “Add to that the computing power necessary to take advantage of aforementioned AI and machine learning initiatives and you have a market ripe for cloud adoption.”
While data drivers are necessitating a move to the cloud, it also is an optimal move to ensure the evolution of healthcare as an industry, she said.
“For example, technology infrastructures based on modern, cloud-based architectural styles, such as representational state transfer (REST) APIs help ensure speed of implementation and deployment and are purpose-built for mobile environments. By moving to the cloud, the healthcare industry is that much closer to providing a user experience that is more similar to the web-based environments that consumers enjoy in other industries.”
A blockchain move for Hyland
On a different note, Hyland recently has acquired Learning Machine, a blockchain credentialing vendor that helps organizations easily design their records, import recipient data, issue records and manage the entire credentialing lifecycle, rooted in any blockchain they choose.
According to Hyland’s President and CEO Bill Priemer: “This acquisition is a major step toward our goal of revolutionizing the way organizations electronically exchange trusted records. The addition of Learning Machine’s digital credentialing solutions to Hyland’s content services platform will enable our customers to generate and manage digital documents that are both easily shareable and instantly verifiable.”
Hyland will be at HIMSS20 in March in Booths 2759, 2773 and 8300-101.