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Bringing generative AI into the doctor’s office is not just a matter of connecting to the technology, but a way to save time for everyone.
Kiran Mysore, chief data and analytics officer at Sutter Health, and Aashima Gupta, Google Cloud director of global healthcare, said during a panel discussion at VentureBeats Transform in July that generative AI has helped reduce many administrative tasks related to doctor visits.
“These are productivity use cases that are just beginning to emerge. We want to solve the problem of ‘pajama time,’ which means that for every hour doctors spend with their patients, they spend two hours looking up information and putting things together,” Gupta said.
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The healthcare space is nothing new when it comes to technological advancements. Mysore said systems like Epic, a platform where patients can enter their health information and medical staff can send messages, have helped accelerate digitization. When Covid struck, more people expected to receive more information about their health, so the industry had to respond quickly.
There are many use cases for AI in healthcare, from improving workflows to scanning and analyzing medical images. Many large organizations in the field, like Kaiser Permanente, have integrated AI into their work, including by using predictive analytics to proactively monitor patients. Gupta and Mysore said one significant use case is making the doctor’s visit easier and more personal for both patient and doctor.
Sutter Health said in Mysore that AI is helping improve the experience of patients and doctors.
“We’re focused on two types of patient experiences,” Mysore said. “The first is when you go to the doctor and you’re talking to the back of the doctor’s head because they’re typing. The other is implementing features that allow you to essentially listen in on the conversation between the patient and the doctor and record it in real time.”
He added that AI helps doctors better understand a patient’s medical history and can spend more time talking to the patient and finding out what’s wrong with them.
Not yet for diagnostics
Gupta specifically pointed out that AI will not be used to diagnose patients, as the technology is still in its infancy. Instead, Google Cloud wants to give its customers the ability to look at the existing data and develop appropriate tools.
“From a Google Cloud perspective, we are an opportunity creator company, meaning we create the foundation and the tool technologies that we bring to the healthcare ecosystem,” Gupta said.
She said one use case Google Cloud customers have explored is combating healthcare worker burnout. Google introduced MedLM, an industry-specific model that runs on its Gemini platform that helps summarize nurses’ shifts. It eliminates the need for a shift to write a report on what happened during the night. Google Cloud also enables hospitals and other medical providers to use its tools to look for connections between diseases and medications, so less time is spent trying to figure out whether one prescription counteracts another.
The question of data protection and adoption
Both Gupta and Mysore acknowledge that some people still feel uncomfortable with AI and that doctors tend to stick with the technology they are familiar with.
“When we approach physicians, we look for the people who are most open to change, and we’ve made them the leaders by surrounding them with the right technology and support,” Mysore said. “People lose trust quickly, especially if the first response from an LLM (Large Language Model) isn’t very good. That’s why we talk to the people involved to explain everything to them.”
Gupta said that in any industry, especially one that is highly regulated like healthcare, the stakes are high, so it is important to listen to concerns and work closely with users. She added that it is helpful to stress that there is still a human involved.
Both panelists emphasized that patient and doctor data is confidential and only authorized persons have access to it.
