Cleveland Clinic Digital Chef: Choose AI problems that clinicians really care

Regarding the success of the AI, guaranteeing the membership of clinicians and other operational end users is one of the most delicate and important parties in the process, according to Rohit Chandra, digital director of the Cleveland Clinic.

He said it during an interview last week at La Reuters Digital Health Conference in Nashville.

When deploying a new AI solution in its ecosystem, a hospital must ensure that end users are fully committed – not only to understand the tool, but also to work with the seller to help refine it and integrate it transparently into existing work flows, said Chandra.

Navigating this change management process can be difficult for hospital leaders – since end users of AI tools are often doctors and nurses who are incredibly busy.

“They are all overloaded, so [you have to] Make sure you choose a problem that facilitates caregivers in a significant way. If it’s just interesting – “Oh, it would be something fun with” – it’s not good enough, “said Chandra.

To achieve membership of clinicians, hospitals should start by adopting AI solutions that solve the problems that doctors and nurses have identified as the most important for them, he said.

This is why IA scribes see such high adoption rates among clinicians, Chandra said. The burden of documentation is a major stress factor in their lives, so they are determined to use and refine a solution that addresses this problem.

Chandra also noted that clinicians are more likely to be behind AI solutions when hospital leadership clearly highlights their potential for improving the results for patients. After all, providing quality care to patients is the reason why most doctors and nurses enter the field in the first place.

He mentioned the prediction of sepsis AI as an example.

“No one will disagree that it is a critical problem – 1,000 people die in the country every day because of the septicemia complications. If you choose a problem where you have a common commitment to make a significant difference, it is a good starting point,” said Chandra.

Make sure that end users really care about the final objective of an AI solution is essential because the success of AI is often a long term. Membership must be a fact from the start, otherwise the clinicians will not remain attached to all the hard work which has just refined and adapting AI tools in hospitals, noted Chandra.

Overall, trust and membership can be a slow and progressive process-based on “success at the same time,” he said.

In its opinion, AI is about to transform most industries, and it is something that must be optimistic.

“If we bring together our act and if we do well, health care should be much more accessible, much more affordable and much better in terms of clinical results in three, five or seven years,” said Chandra.

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