Healthcare Artificial Intelligence Outlook: Benefits, Projected Growth & Challenges
Why is there an uptick in healthcare artificial intelligence during a time in which hospitals are struggling financially? Pamela Peele, HIMSS 2018 AI panelist and chief analytics offer at University of Pittsburgh Medical Center Health Plan and UPMC Enterprises explains why healthcare AI growth is inevitable at this point in time:
“It’s because we have dense, robust algorithms, tons of data and the ability to handle it computationally. It’s the perfect storm.”
Despite the initial capital investments, maintenance costs, and repair charges – healthcare artificial intelligence (AI) is here to stay. The use of AI in healthcare is expected to grow 40 percent annually from 2016 to 2024 according to a study from Global Market Insights (GMI). The study identifies rapid adoption of AI in specific medical fields, such as:
- Drug discovery
- Medical imaging
In 2016, the healthcare sector spent approximately $760 million on artificial intelligence. Over the next six years, the study projects this figure to swell at a rate of approximately 40 percent per year. Thus, in 2024, the total spent on AI in healthcare would be upwards of $10bn.
Healthcare Artificial Intelligence Receives a Boost from an Organization
A group known as the Partnership for Artificial Intelligence and Automation in Healthcare (PATH) is committed to promoting the collaboration of:
- Health systems
…in order to expand healthcare artificial intelligence to achieve the following goals:
- Improve the overall delivery of medicine
- Reduce healthcare expenses, especially administrative expenses
- Expand and facilitate access to quality healthcare
- Improve accuracy of MRI scans, CT scans, and picture archiving communications (PAC)
Jonathan Linkous, a co-founder, and CEO of PATH talks about the potential of artificial intelligence in the medical field in a recent article in Gen Exclusives:
“AI and related innovations have already enabled industries such as banking, aviation, and entertainment to grow, provide higher-quality products, and allow consumers greater choice. With spiraling costs, increasing need, decreasing resources, and rapidly advancing technologies, healthcare desperately needs to catch up.”
AI Holds Promise for Reducing Healthcare Costs and Improving Population Health
It’s become common knowledge that Americans spend a massive amount of money on healthcare annually. A recent Kaiser Health study looks at this massive spending and provides the following comparison chart that shows how much is spent on average for healthcare in the U.S. compared to healthcare spending in other wealthy nations.
Healthcare Finance News points out in an article that AI holds the most promise in healthcare to reduce costs. While AI is already being used in certain areas of medical practice, such as diagnostic imaging, it’s being drastically underutilized in others. One of these areas is population health.
The article continues to explain that the overall goal of population health management is to “achieve a baseline of care delivery and quality across certain groups or populations, and once goals have been met, new ones emerge.” Considering the target is ever-moving and changing, population health makes a good candidate for the implementation of machine learning which is able to spot trends and patterns that physicians don’t usually catch. Virtually independent of human involvement, AI in healthcare can make use of EHR along with financial data to identify patient populations with specific characteristics. Preventative and predictive care can be planned more effectively with the smart use of this targeted data.
Furthermore, an article in Venture Beat describes how artificial intelligence can help reduce the administrative costs of healthcare. The article cites data from a report by the Journal of American Medical Association (JAMA) that reveals nearly half of all U.S. healthcare expenditures go into the regulating, planning, and managing medical services at the level of administration.
Venture Beat goes on to say that many industry experts are confident that artificial intelligence can be applied to effectively reduce much of this administrative spending. An expert in data security, digital health records, and healthcare regulation at Buchanan, Ingersoll & Rooney, Pamela Hepp explains that:
“A number of recent studies have found that [health care] administrative costs [in the U.S.] continue to rise and or remain higher than other countries. There is always room for improving efficiencies in the delivery of care and AI has some promise in that regard.”
Barriers to Overcome in the Implementation of Widespread Use of Artificial Intelligence (AI)
Currently, the growth of medical AI is held up by the costly initial investment, maintenance fees, and the fears of large-scale job losses due to industry disruptions. Industry experts that composed the study expressed that the concerns and fears should be outweighed by the general population’s better grasp on technology.
The fear surrounding the use of AI in healthcare is ever present and the PATH group aims to change this narrative. The Healthcare IT News article goes on to explain that major barriers to AI growth, such as the massive amount of big healthcare data in unusable formats that can contain biases. In the Gen Exclusives article, Linkous says:
“There are concerns about privacy, job safety, fear of the unknown, and allowing AI to take on complicated decision-making normally left to physicians and healthcare providers. Addressing and alleviating these concerns is a major reason for developing PATH. Our focus will be on the application of AI, automation, and robotics, which is already being used in surgery, to healthcare delivery.”
Compliance and regulatory issues in regard to advanced AI applications in healthcare are critical as pointed out in an article by Forbes. Considering there is currently not a legal or regulatory framework in place to indemnify software companies and review and approve up-and0coming technologies utilizing AI, which makes it a high-risk investment.
The Forbes article goes on to say that because artificial intelligence will be used in healthcare to help make decisions, in time, there need to be guidelines in the regulatory system specific to AI and advanced software. Furthermore, because these systems are based on algorithm technology, approval becomes increasingly difficult as the initial algorithm will require regulatory approval, and then the algorithm changes and adapts from learning more data, therefore is no longer the same algorithm. In other words, all the updates would need to be implemented to introduce the new learning. “The regulatory cycle is not set up to address the machine learning environment,” according to Elad Benjamin, who is the CEO & co-founder at Zebra Medical Vision. “The clinical, testing, approval process will be difficult for algorithmic adaption in the medical industry.”
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