By Sahar Arshad, co-founder and COO of CloudMedx.
While artificial intelligence seems to suddenly be taking a much bigger role in all sorts of businesses, one of the largest, most powerful sectors has yet to tap into its potential. That reluctance is hurting everyone — companies, investors, and, most importantly, individuals from all backgrounds.
The healthcare sector makes up a huge portion of the economy — and the stock market. The latest analysis from IBISWorld, listing the 10 biggest industries in the United States in 2023, puts four health-related industries at the top: hospitals; drug wholesaling (along with cosmetics and toiletries); pharmaceuticals wholesaling; and “health and medical insurance.”
Healthcare is already notorious for being slow to adopt new technology. A recent study published by the National Bureau of Economic Research says the same is true for AI. “The potential of artificial intelligence (AI) to simplify existing healthcare processes and create new, more efficient ones is a major topic of discussion in the industry,” says the study from McKinsey and Harvard University. “Yet healthcare lags other industries in AI adoption.”
The researchers put a figure on it: “We estimate that wider adoption of AI could lead to savings of 5 to 10 percent in US healthcare spending—roughly $200 billion to $360 billion annually.” That’s a trillion dollars or more every three to five years.
Working in this space, I see a major force that is holding healthcare back — and ways to fix it.
Healthcare organizations rightfully need to make sure that any and all patient data remains absolutely secure. Anytime there’s a new digital tool, important questions arise about what happens to information that it processes.
Of course, similar concerns exist across all industries. A recent survey from Cisco finds that businesses have boosted their average spending on privacy efforts to $2.7 million in 2022, more than doubling from $1.2 million just three years earlier. Nearly all the organizations surveyed (more than 90%) say customers won’t buy from them if data is not properly protected, and that they need to do more to reassure customers.
But in healthcare there are special sensitivities, and numerous laws requiring that certain steps be taken. These companies cannot, for example, use a tool that might send certain information to a cloud server where others might find a way to access it.
The key for tech creators is to design tools that bring the power of AI inside a healthcare organization’s private network system. For example, my team has worked on a tool that uses AI to take on one of the biggest problems facing the healthcare industry: more than half a trillion dollars a year in administrative spending, according to a recent estimate. It makes healthcare far too expensive, and slows down the entire process, damaging health outcomes.
Administrative tasks are filled with all sorts of complex minutiae. Take the forms that healthcare providers need to fill out for insurers. With rules changing all the time, these providers constantly need to figure out which codes to use and which apply to which specific patients based on all sorts of demographic and clinical data. Having people responsible for these tasks requires heavy staffing, which is especially difficult as many healthcare workers leave the industry.
AI can help by automatically searching for the latest rules; piecing through records to determine the relevant data; understanding physicians’ notes (using natural language processing, or NLP); and much more. But all this can only be applied to healthcare when a tool is designed specifically for healthcare organizations. So we built a solution that stays within firewalls. The information entered does not leave the organization at any step in the process.
This also means that interoperability is key. These solutions must be developed in ways that allow them to be added easily to healthcare companies’ existing technology. Already overworked and overwhelmed, most people in the industry simply don’t have the time to learn an entirely new system.
For investors considering healthcare stocks, the key is to find out all you can about how a company is approaching AI. Is it adopting solutions to concrete problems? Are these solutions offering incremental improvements or are they transformative? Are they easy and secure to deploy, and for end users to work with? Is the company working to discover a wide array of technology solutions that will improve both health outcomes and the bottom line? Ask for specific examples and savings projections.
The more companies move in this direction, the faster the savings will add up — and those will show up in share values.
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