Much like the formation of New Year’s Resolutions, the prediction of technology trends for the coming year has become a tradition among pundits, analysts and vendors alike. As the calendar turned to 2020, Hyland, like many, took the opportunity to look into a crystal ball to predict what the future might hold for the software industry at large, as well as many of the key vertical markets in which it operates.
For example, Hyland leadership revealed six overarching trends for enterprise technology as well as key trends to watch for health IT. At the time, none of us could have foreseen that a global pandemic was coming that would turn all of these predictions on their collective ears.
Of course, the healthcare industry has been particularly impacted by COVID-19. Provider organizations have justifiably focused their attention on responding to the new patient care and staffing needs brought about by the virus. That said, all of the health IT trends Hyland outlined at the beginning of 2020 (interoperability, artificial intelligence and cloud adoption) still have relevance in today’s unprecedented landscape. Although, admittedly, the reasons these topics are trending are for vastly different reasons than we originally anticipated.
I want to revisit these trends under the lens of COVID-19 as well as add a few more to the list in light of current circumstances.
Original insight: Secure access to patient information at any facility throughout a care continuum is an imperative for delivering a longitudinal digital record that travels with the patient. The key is to ensure tight integration between disparate IT systems, and to include unstructured data in the interoperability equation. As much as 80% of essential patient information is in an unstructured format – such as digital photos and videos, or physician notes – and not natively included in an electronic medical record (EMR) system. When removed from a clinician’s view, the patient record is incomplete.
New relevance: Health IT interoperability was important prior to COVID-19, and it’s even more critical now. Providers, patients and public health officials need all-encompassing data in a standardized format to better understand this evolving illness and develop guidelines. The effort to identify risk, control spread and manage the treatment of afflicted patients is a coordinated effort among multiple healthcare providers and external care partners. The easier information can be shared among these varied stakeholders, the better equipped we’ll be to combat the virus.
Artificial Intelligence (AI)
Original insight: Realistic applications of AI are coming into focus in healthcare, showing where the technology will help providers optimize workflows and better analyze the vast amounts of information needed to support improved decision making. Experts view AI technology as complementary and a true asset when it comes to helping physicians analyze the overwhelming amount of patient data they receive daily. Physicians can implement AI to streamline or eliminate tedious tasks, such as manual documentation and data search, or cull information to help them focus on a key area of interest.
The medical imaging space in particular provides a tremendous area for the growth of AI and machine-learning technologies. Clinicians can use them to analyze thousands of anonymized diagnostic patient images to identify and detect indicators of everything from lung cancer to liver disease. These technologies are also being used to accelerate research.
New relevance: AI is being used in a number of ways to address the challenges of COVID-19. For example, AI algorithms have been used to identify the spread of new clusters of unexplained pneumonia cases. Other AI applications are being used to spot signs of COVID-19 infections in chest X-rays and identify patients at high-risk of coronavirus complications based on their pre-existing medical conditions. Still others are scanning the molecular breakdown of the virus itself as well as those of existing drug compounds to identify medications that can potentially target the virus and shorten the span of the illness or lessen the severity of the symptoms. In all of these scenarios, AI is quickly analyzing large segments of data to accelerate research and treatment. This automation is indispensable in an environment where medical staff are stretched to their limits, and the act of saving time could save lives.
Hyland Healthcare recently partnered with HIMSS Media to survey leaders from healthcare provider organizations on their current interoperability initiatives for its second annual Connected Care and the State of Interoperability study. The results are published in a whitepaper titled Connected Healthcare: Interoperability Progress and Challenges Ahead and an infographic titled Breaking Down Healthcare’s Interoperability Gaps.
The study indicates year-over-year improvement in healthcare providers achieving their top interoperability goals. However, several obstacles to improving interoperability were also identified, including the management of unstructured data and content. Survey respondents indicated that 73 percent of unstructured patient data remains inaccessible for analysis, leaving a significant gap in health information.
Key results from 2020 Connected Care and the State of Interoperability in Healthcare include:
Year-over-year improvements to top interoperability goals:
Organizations’ ability to effectively tackle improvements in patient satisfaction increased from 45 percent to 63 percent
86 percent of respondents stated they are better able to meet regulatory compliance requirements
The ability to maximize the value from the EMR investment grew by 23 percent (from 31 percent in 2019 to 54 percent in this year’s study)
Challenges to achieving interoperability goals:
More than half of survey respondents stated the major obstacles to improved interoperability is the ability to keep pace with patient expectations
The most significant obstacles to improving interoperability include: Integration (59 percent); Adoption (58 percent); Consumerism (55 percent); Managing unstructured data/content (53 percent); and Managing Multiple EMRs (48 percent)
On average, 73 percent of unstructured patient data is still unavailable for analysis.
The ability to consistently share picture and archiving communication system (PACS) images
“Healthcare interoperability has never been more important than it is today,” said Colleen Sirhal, chief clinical officer for Hyland Healthcare. “Providers, patients and public health officials need all-encompassing data to better understand the still-evolving coronavirus and inform guidelines and treatment. The more we focus on breaking down the barriers to sharing key health information with varied clinical stakeholders, the better prepared we’ll be to ensure the best public health outcomes.”
Another major gap uncovered by the research was the ability to consistently share PACS images. Ninety percent of respondents agreed that access to images at the point of care is important; however, 18 percent of imaging data is captured offline and not integrated with core clinical systems. Additionally, only 11 percent of respondents connect with a vendor-neutral archive (VNA) for digital imaging and communications (DICOM) and non-DICOM images.
The lingering problems with integrating unstructured patient content is concerning, particularly with the evolution to a value-based care practice. Healthcare providers increasingly need a structured way to see all patient information to know the appropriate tests were ordered, administered and ultimately assess the results. This helps save money by not ordering duplicate tests, but also improves patient satisfaction.
Each year, Hyland Healthcare conducts focus groups with HIMSS members representing top healthcare provider organizations. The interactive, in-depth discussions always reveal powerful insights we can use to improve our solutions.
This year’s topic was enterprise imaging. We wanted to gain a better understanding of the drivers, strategies, challenges and desires healthcare leaders have in this area.
Consensus from the group seemed to indicate that the evolution of healthcare in general is driving the demand for enterprise imaging. For example, increased consolidation, partner collaboration and merger and acquisition activity are creating imaging environments that are complex and extremely difficult to manage. It becomes problematic, expensive and risky to attempt to manage and maintain multiple silos of imaging data throughout all of these locations.
“The acquisition of outpatient imaging centers combined with the disparate imaging silos we already have internally creates a lot of waste,” said Peter Overeem, CTO of Adventist Healthcare. “Several efficiencies can be gained by bringing all our images — both inpatient and outpatient — together into one consolidated system.”
Furthermore, it was agreed upon that PACS is a dated technology that is centered on radiology and cardiology, and likely not the best equipped to handle the centralized management of images throughout an enterprise.
“With the advancement of AI, we need to start adopting enterprise tools,” said Michael Knopp, MD, professor and director at Ohio State University. “We can’t maintain an environment where everyone has their own departmental solution. PACS vendors are focused on specific niches and are fairly slow to add new innovations that benefit the enterprise. The solutions you implement today need to be capable of adapting and innovating at a much faster pace.”
One-size does not always fit all
The demand for enterprise imaging tools was clear from the group. However, participants also communicated several challenges and roadblocks when it comes to implementing solutions that satisfy the needs of all the stakeholders involved.
“We can’t get the different imaging-centric departments to agree on one technology platform that meets everyone’s needs,” said Overeem. “What one person likes, another hates. We’re concerned about implementing an enterprise solution that causes some departments to settle for a less optimal solution for their specialty.”
Due in large part to the HITECH Act and the meaningful use incentive program, electronic medical record (EMR) initiatives have dominated the IT efforts of healthcare providers for the better part of the past decade. Most of the focus over this time has been placed on simply implementing the technology and getting clinicians to embrace it.
Now that more than 95 percent of hospitals in the U.S. are currently using EMRs*, it seems the focus is beginning to shift. However, the move isn’t away from EMRs to some other groundbreaking technology. Instead, the focus is transferring from simply implementing EMRs to optimizing the software in order to squeeze more value out of it.
You see, most healthcare providers aren’t very happy with the ROI they are currently getting from their multimillion-dollar EMR investments. In fact, only 10 percent believe they are getting a positive or superb return from their EMRs, according to a recent survey of 1,100 healthcare professionals by Health Catalyst.
The remainder describe the ROI as terrible, poor or mediocre.
As a result, healthcare providers are turning their attention to enhancing their existing EMR systems. According to a recent Black Book Market Research survey, 61 percent of healthcare respondents say technology optimization is the highest priority IT engagement for their organizations by the end of 2020. Not surprisingly, EMR software and revenue cycle management systems are the primary targets of these optimization efforts.