Lessons from the adoption of AI in healthcare finance
By Pamela J. Gallagher
The emergence of artificial intelligence (AI) is the topic on every healthcare leader’s mind. In many ways, though, AI is old news to those of us in healthcare finance. I can say from experience that once an AI technology comes onto the scene, there is no stopping it. AI is here to stay. The question leaders must grapple with is how to embrace it wisely and with purpose.
We’ve increasingly used these technologies in an administrative setting for years now for functions such as insurance verification, billing, and collecting. This has allowed for the streamlining of essential processes for the organization, provider, and patient. As healthcare organizations look to possible clinical applications of AI, there is vast potential to bring the benefits we’ve seen on the administrative side to the care providers offer to patients, the foremost being a quicker and more accurate diagnosis.
However, more caution is required in a clinical setting than an administrative one, for obvious reasons. An automated system can make a mistake on a bill, and while that’s certainly not good, it’s also not a life-or-death situation. Human beings are complex, and no amount of data in the EMR can paint an entire picture of a person.
Still, there are several lessons we learned in the adoption of AI in healthcare finance that can serve as a guide as considerations are made for the advancement of AI in a clinical setting.
Get clarity on your mission.
The adoption of AI may be inevitable, but being on the cutting edge of the available technology makes for a terrible mission statement. Technology is foremost a tool. As with any tool, you can use it for its best purpose, or others that stretch it beyond the bounds of what it was designed to do.
The only way to be able to evaluate whether an emerging technology is a good fit to meet the particular needs of your organization or patients is to be crystal clear on your organization’s mission and values. What is it that you are trying to accomplish? That must be your guide.
Define your terms.
AI is being defined as it is being developed. It seems the numbers of types or categories of AI is constantly increasing. There are many calls for a set of standards to regulate the development and use of AI, and I agree that those are necessary (as I will discuss below). But it will be nearly impossible to have useful standards without a clear understanding or definition of the “product.”