When it comes to achieving AI success, ensuring buy-in from clinicians and other operational end-users is the one of the trickiest and most important parts of the process, according to Rohit Chandra, chief digital officer at Cleveland Clinic.
He said this during an interview last week at the Reuters Digital Health conference in Nashville.
When deploying a new AI solution in its ecosystem, a hospital must ensure that end-users are fully engaged — not only to understand the tool, but also to work with the vendor to help refine it and integrate it seamlessly into existing workflows, Chandra explained.
Navigating this change management process can be challenging for hospital leaders — given that AI tools’ end-users are often physicians and nurses who are incredibly busy.
“They’re all overworked, so [you have to] make sure you pick a problem that makes the caregivers’ job easier in some meaningful way. If it’s just interesting — ‘Oh, this would be something fun to play with’ — that’s not good enough,” Chandra declared.
To achieve clinician buy-in, hospitals should start by adopting AI solutions that address the problems that physicians and nurses have identified as most important to them, he said.
This is why AI scribes are seeing such high adoption rates among clinicians, Chandra pointed out. Documentation burden is a major stressor in their lives, so they’re committed to using and fine-tuning a solution that addresses this issue.
Chandra also noted that clinicians are more likely to get behind AI solutions when hospital leadership clearly emphasizes their potential to improve patient outcomes. After all, providing quality care to patients is the reason most physicians and nurses enter the field in the first place.
He mentioned sepsis prediction AI as an example.
“Nobody will disagree that it’s a critical problem — 1,000 people die in the country every day because of sepsis-related complications. If you pick a problem where you have a shared commitment to making a meaningful difference, that is a good starting point,” Chandra stated.
Making sure that end-users truly care about an AI solution’s end goal is essential because achieving AI success is often a long haul. Buy-in has to be a given from the start, or else clinicians won’t remain committed to all the hard work that comes along with refining and adapting AI tools at hospitals, Chandra remarked.
Overall, building trust and buy-in can be a slow, incremental process — relying on “one success at a time,” he said.
In his opinion, AI is poised to transform most industries, and this is something to be optimistic about.
“If we get our act together and if we do this well, healthcare should be much more accessible, much more affordable and much better in terms of clinical outcomes three, five or seven years from now,” Chandra declared.
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