- The HIT infrastructure landscape is rapidly changing, and organizations should keep their eyes on artificial intelligence (AI), cultural advancement, and processes becoming products as the result if increased digital capabilities and continuous conceptual changes in technology, according to Gartner.
Gartner analysts explored the near future of enterprise technology as a result of its rapidly accelerating pace at the research analyst firm’s recent Gartner Symposium.
“As the advance of technology concepts continues to outpace the ability of enterprises to keep up, organizations now face the possibility that so much change will increasingly seem chaotic,” said Gartner Fellow and Vice President Daryl Plummer in a statement. “But chaos does not mean there is no order. The key is that CIOs will need to find their way to identifying practical actions that can be seen within the chaos.”
“Continuous change can be made into an asset if an organization sharpens its vision in order to see the future coming ahead of the change that vision heralds,” he continued. “Failing that, there must be a focus on a greater effort to see the need to shift the mindset of the organization. With either of these two methods, practical actions can be found in even the seemingly unrelated predictions of the future.”
Several predictions made at the symposium speak to the healthcare industry as AI technology continues to enhance how healthcare organizations handle workloads.
Gartner predicts that by 2023, U.S. emergency department visits will be reduced by 20 million because of the enrollment of chronically ill patients in AI-enhanced virtual care.
“Clinician shortages, particularly in rural and some urban areas, are driving healthcare providers to look for new approaches to delivering care,” said Gartner analysts. “In many cases, virtual care has shown it can offer care more conveniently and cost-effectively than conventional face-to-face care.”
“Gartner research shows that successful use of virtual care helps control costs, improves quality of delivery and improves access to care,” analysts continued. “Without change, the traditionally rigid physical care delivery methods will increasingly render healthcare providers noncompetitive. This transition will not come easily and will require modification of cultural attitudes and healthcare financial models.”
As AI becomes more prominent in healthcare, organizations should also keep an eye on what it takes to run these solutions. The increase in the number of AI projects across many different organizations has limited the expertise of many AI professionals. Organizations may find themselves in competition with other health systems to employ AI talent.
“The large majority of existing AI techniques talents are skilled at cooking a few ingredients, but very few are competent enough to master a few recipes, let alone invent new dishes,” said Plummer.
“Through 2020, a large majority of AI projects will remain craftily prepared in artisan IT kitchens. The premises of a more systematic and effective production will come when organizations stop treating AI as an exotic cuisine and start focusing on business value first.”
The limited talent available for AI deployments can hinder the industry, making it a long way off before healthcare organizations can achieve a prediction like the one Gartner stated.
The ONC explained the healthcare industry needs to rise to the demand of AI.
“The rapid digitization of health data through the use of heath information technology (health IT) in the United States has created major opportunities in the use of AI,” ONC commented in a blog post. “Innovators and experts see potential in using digital health data to improve healthcare and health outcomes from the home to the clinic to the community.”
“Yet, current AI is powered and limited by its access to digital data. With a range of health-related data sets, AI could potentially help improve the health of Americans,” ONC continued.
The actual implementation of AI is a heavy IT infrastructure undertaking. Applications need to be built and organizations may need to invest in hardware with enough computing power to handle and process the increased amount of data.
ONC stressed that it’s important to understand the limitations of AI in healthcare. Organizations need to be realistic about their AI goals and implementations.
A JASON report released late last year suggested that organizations focus on using AI for capturing and collecting data. Capturing smartphone data using apps that monitor patient health can be integrated to support AI applications. Social and environmental data can also be integrated to capture social behaviors and how they impact health.
The report also stressed the importance of development of AI technology. A standard needs to be set for AI to be truly successful in healthcare long-term.
ONC and AHRQ are working with the NIH and the FDA to identify and define AI opportunities in healthcare. The agencies also hope to create an interoperable and standardized way to use AI to improve patient care.
The JASON report highlighted the importance of competition to improve AI technology. This competition could help spread talent throught health IT staff.
“Crowdsourcing is becoming a growing success for AI in Health algorithm development via online competitions,” the JASON report explained. “The crowdsourcing competitions are able to engage top data scientists and programmers who are not health care domain experts.”
“AI competitions have already demonstrated their value in 1) encouraging the creation of large corpuses of data for broad use, and 2) demonstrating of the capabilities of AI in health, when provided data that are curated into a well labeled (namely high information content) format,” report authors added.
The report concluded that the use of AI in healthcare is not only promising, but doable.
“We are excited about the possibilities that AI has to improve healthcare quality, help clinicians take the best care of their patients, and empower patients to take control of their own health,” said ONC.