3 misconceptions hospital leaders have about artificial intelligence
Medical device companies continue to integrate new AI models into their products, and doing so often requires the help of development partners such as hospitals and health systems.
At the Reuters Medical Technology Conference in Boston, a panel of three medical device executives discussed how they work with these clinical partners to develop and refine their technology. Through these collaborations, they also highlighted three common misconceptions they believe hospital leaders often have about AI.
Artificial intelligence will take over the process
LaMont Bryant, Stryker's vice president of global government affairs and market access, noted that some health system leaders appear concerned that algorithms may become a more important part of the care delivery process than human judgment and expertise.
But he stressed that this was not the case.
“AI is not here to take over the process, but it is another tool that can help [clinicians] Make decisions based on better data and information,” Bryant said.
He noted that medical device companies understand that doctors and nurses know what's best for their patients, and said the tools Stryker sells are designed to enhance their clinical decision-making — not replace it. These tools are expected to help clinicians practice at the highest level of their license and reduce burnout associated with administrative tasks and manual processes.
Tech companies just want your data
Hospital leaders often think tech companies and AI startups just want to buy their data, said Nick Wilson, vice president of product and marketing at Philips.
“Every executive discussion I’m involved in inevitably comes up with some form of the question, ‘We have a huge database. What can we do – how can we sell it to you?’ Basically, I think that’s useful in some situations. But data monetization isn’t good enough unless we can turn that into insights and then translate that into actual change and action – that’s where the real hard work comes from, rather than sourcing the raw data,” he explains.
Wilson asserts that technology developers typically don't want to just buy hospital data and then use it themselves, they're looking for partners who can help them figure out how to turn that data into useful insights that lead to better clinical decisions and outcomes.
Clinical workflows are being fully automated
Amir Tahmasebi, head of AI algorithms and infrastructure at Becton Dickinson, noted that AI does not fully automate clinical tasks, and most healthcare technology developers have no intention of building the tools to do so anytime soon.
“AI is about augmenting everything, not automating everything,” he said.
Artificial intelligence can also make care safer, Tahmasebi added. For example, digital twins—virtual replicas of patients—allow care teams to track device performance and detect patterns that indicate problems. He explained that this allows for proactive intervention to prevent patients from going to the emergency room.
In short, medical device manufacturers want to send a clear message that AI is not meant to replace doctors or nurses, but to help them make better decisions, prevent adverse events and improve patient care.
