With the potential to disrupt care as we know it, AI continues to surge in interest among different parties in the healthcare industry. But in all the excitement some stakeholders are concerned that investment in the technology are hurt by disorganized and inconsistent approaches and methods.

“Everyone’s investing but there’s a little chaos in the salad going on in terms of AI products,” said Ingrid Vasiliu-Feltes, chief quality and innovation officer for MEDNAX, in a panel discussion this week at the Ai4 Healthcare conference in New York City. “Everybody wants to do a use case, but there’s no synergy and clear understanding of what you’re aiming to achieve and how it’s going to impact the population health, or precision medicine or whatever product you want to build," she continued. "I’m a little frustrated sometimes we’re not doing it [investing] in the most meaningful way.”

More than 85 speakers from across the U.S. and abroad gathered for the two-day event to discuss the impact of AI on their respective healthcare segments, which ranged from payors and pharma developers to medical device and biotech firms.

Sitting in on technical and non-technical lectures, participants listened as panel after panel delved into current and potential applications for AI, such as insight extraction for medical imaging, pharmaceutical decision-making, digital pathology multiplex image analysis, and fighting physician burnout.

Like Vasiliu-Feltes, many speakers had much to say about the issues plaguing the development and effective deployment of AI, particularly how providers and other entities are choosing which AI and machine learning solutions to use in their practices.

“For any organization, it’s important for us to make sure we are looking at the benefits of how the AI is connecting to our patients and the decisions that we’re making are related to connecting to AI partners,” said Tanya Scott, clinical services director for Kaiser Permanente, who was a member of the same panel discussion as Vasiliu-Feltes, How AI is Revolutionizing the Hospital. “Is the decision one that is going to provide us with the affordability that we need and at the same time give us the patient outcomes we’re looking for? When our outcomes are such, that we’re able to drive the cost of healthcare down and affordability is realized as a result of that, then it makes sense to make the investment in AI.”

This and other conversations looked into other necessary elements for leveraging the full potential of AI, including the need for clinicians' input during development stages for technology; the process in which data is delivered to patients; the elimination of mundane tasks by AI for radiologists; and the future direction of where AI is expected to go.

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