Introducing generative AI into doctors' clinics is not just a matter of inserting technology, but also a way to save time for everyone. At VentureBeat's July Transformation Forum, Kiran Mysore, Chief Data and Analytics Officer at Sutter Health, and Aashima Gupta, Global Director of Healthcare Solutions at Google Cloud, stated in a panel discussion that generative AI has already helped reduce many administrative tasks during clinical visits.

"These are very early productivity use cases; what we are trying to solve is the 'pajama time' problem, which means for every hour a doctor spends on a patient, they spend two hours searching for information and piecing things together," Gupta said.

The healthcare industry is no stranger to technological advancements. Mysore mentioned that systems like Epic, where patients can input their health information and healthcare providers can send messages, have helped accelerate the digitization process. Since the outbreak of the COVID-19 pandemic, more people are seeking more information about their health, and the industry must respond quickly.

In the healthcare field, generative AI has many use cases, ranging from improving workflows to scanning and analyzing medical imaging. Many large organizations in this field, such as Kaiser Permanente, have already implemented AI in their work, including using predictive analytics for proactive patient monitoring. Gupta and Mysore stated that an important use case is to make it easier and more humane for patients and doctors to receive medical care.

Mysore mentioned that for Sutter Health, AI helps improve the experience for both patients and doctors.

"We focus on two patient experiences," Mysore said. "One is when you go to see a doctor, and they are busy typing, and you can only talk to the back of their head. The other is enabling a functionality where you can listen to conversations between patients and doctors in real-time and capture those conversations."

He added that AI helps doctors better understand patients' medical history and allows them to spend more time conversing with patients to understand their condition.

Not yet used for diagnosis

Gupta cautiously pointed out that generative AI has not yet been used for diagnosing patients, stating that this technology is still in its early stages. Instead, Google Cloud aims to provide customers with the ability to view their existing data and build tools around it.

"From Google Cloud's perspective, we are an empowering company, which means we are building the foundation, tools, and technology for the healthcare ecosystem," Gupta said.

She mentioned that one use case explored by a Google Cloud customer is addressing healthcare worker burnout. Google has launched MedLM, a customized model running on its Gemini platform that helps summarize nurse shift information. It eliminates the need for nurses to write night reports. Google Cloud also allows hospitals and other healthcare providers to use its tools to search for connections between diseases and medications, reducing the time it takes to determine if one medication counteracts another.

Privacy and adoption concerns

Both Gupta and Mysore acknowledged that some people still have concerns about AI, and doctors often insist on using technologies they are familiar with.

"When we engage with doctors, we look for those who are most receptive to change and make them advocates of the transformation by providing them with appropriate technology and support," Mysore said. "People can easily lose trust, especially when the initial response from large language models (LLMs) is not ideal, so we engage with stakeholders and explain everything."

Gupta stated that in every industry, especially highly regulated ones like healthcare, there are high risks, so it is crucial to listen to people's concerns and work closely with users. She added that emphasizing human involvement throughout this process is helpful.

Both guests emphasized that patient and doctor data remains private and only authorized personnel can access it.