As the world recovers from the devastating effects of the COVID pandemic, the state of our healthcare systems continues to be a pressing issue.

Many think generative artificial intelligence could provide the solution to problems caused by a decreasing workforce and rising patient admission rates.

“We are facing an inflection moment in time,” said José Pedro Almeida (pictured), chief AI strategist and health AI expert, “I think healthcare is probably the area that will benefit the most from this [generative AI]. The level of safety and efficiency you can bring into an organization is just unprecedented.”

Almeida spoke with theCUBE industry analyst Dave Vellante at Supercloud 4, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed the future of generative AI in healthcare and the necessary guardrails for implementing AI into an existing system.

Working with hospitals on the inside

Because of a dropping workforce in healthcare post-pandemic, there is a “huge pressure to the system,” according to Almeida, necessitating new solutions that can help manage the influx of patients, relieve healthcare workers of mundane tasks and harness the existing information in hospital databases.

“You need to unlock that data, bring it into … a centralized data platform, and then you start building the intelligence on top of that,” Almeida said.

He estimates that 97% of the hospital data being produced is not used, because 80% is in an unstructured form. “But all that intelligence is built side by side with clinicians,” he added.

The buck should stop at AI making patient diagnoses, believes Almeida, who highlights the human element — the doctor’s instinct — with diagnosis, and the need for unique strategies when it comes to implementing large language models into healthcare organizations.

“Go into their field, understand their problems, and then build the things with them,” said Almeida, who emphasizes the need for tech companies to work with hospitals and their staff. “These things are built as a team. They are not built outside-in, selling you a product and plugging into your system.”

Healthcare involves a lot of sensitive information that makes implementing AI-driven solutions tricky. Collaborating with healthcare professionals could allow more guardrails to be put in place, claims Almeida, who envisions a “multidisciplinary team” of software engineers, ethics experts and clinicians that would designate LLMs’ interactions within healthcare databases.

The future of AI in healthcare

Most hospitals are at least a couple years off from implementing large language models into their systems, Almeida clarified, but he believes that integrating LLMs into healthcare organizations’ existing databases could be transformative.

“Think about those clinical notes that are sitting in the database that are locked over there,” he said. “They are just being used for transactional care between the doctor and one patient. But you are not leveraging all the insights that are already there.”

The limited instances of AI in hospitals that already exist, such as the collaboration between HCA Healthcare and Google Cloud, are promising. Another example is the computational care Almeida developed at a public hospital in Portugal, which he claimed could identify signs of “hemodynamic instability” or potassium levels based on blood pressure and heart rate readings.

Although AI should not be diagnosing patients, there are much more pressing issues to be addressed, according to Almeida. With the right LLM, mundane tasks, such as summarizing patient episodes, could be done in a few seconds.

“Doctors will be much more productive. We’ll be able to see much more patients when they use these tools, because I’ve seen those tools working, and I know how powerful they are,” said Almeida, who imagines a future where AI could produce versions of a summary with different language for patients versus doctors.

Advancements that involve generative AI could significantly improve the quality of life for healthcare professionals, according to Almeida. “[Doctors] want to treat more patients, they want to treat them effectively. What they study for is to save lives, at the end of the day,” he said.

When asked about implementing generative AI worldwide, Almeida sees it as improving equity, especially in third-world countries, where patients can be hundreds of miles away from the nearest hospital.

“If you look at this trend, it is highly democratized. It is very easy to make this available globally, even today,” he said. “What exists today can already improve healthcare and can already lower costs of accessing healthcare.”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of Supercloud 4:

Photo: SiliconANGLE