Dr. Kaeli Yuen, head of the Department of Veterans Affairs artificial intelligence products in the VA Office of the Chief Technology Officer, provided an update on the agency’s review of with various AI pilots at the American Technology-Industry Advisory Council of America. Exchange meeting in Washington, DC, this week.
WHY IS IT IMPORTANT?
Yuen said that while many veterans are skeptical about recording doctor’s visits, according to a report from MeriTalkPublic-private cooperation, enthusiastic doctors.
“It’s pretty incredible,” added Dr. Susan Kirsh, VA’s deputy undersecretary for health for discovery, education and affiliated networks.
Yuen said the VA is working to balance “the privacy and security that veterans expect, while also providing them with an easy experience.”
The Forum brings government employees together to improve government outcomes. On May 29, ACT-IAC hosted Yuen and Kirsch for an FIE event focused on VA’s journey to enhance veteran care by leveraging AI.
In 2021, more than 20 VA offices developed an agency AI strategy, becoming one of the first federal agencies with an AI roadmap, leading to pilot testing of AI for use in encounters clinical and benefit management.
Yuen said many offices within the VA are asking genAI tools to draft correspondence and documents and summarize information such as veteran user experience survey data, according to the story.
“People from all over the VA want this,” she said.
However, testing general AI interfaces to help address VA’s overall administrative burden is challenged by how to measure success with pre-existing workflows, Yuen said.
“I think what we were doing was applying these tools to a process that was built without those tools in mind, and maybe we should have done it a different way,” she said.
BIGGER TREND
According to Whende Carroll, clinical informatics consultant at HIMSS, parent company of Healthcare IT newsat the HIMSS23 Global Conference and Exhibition.
The fatigue it causes in doctors, nurses and other medical staff can worsen side effects, increase errors and lead to “complications” that lead to serious consequences, she said. poor treatment outcomes for patients.
While Carroll said AI, especially natural language processing, can reduce waste and help improve the productivity of medical documentation that fatigues clinicians, genAI was found to lead to lengthy and overly complex reports as well as increased risk of errors in government reporting.
Srini Iyer, chief technical officer at Leidos Health & Civil Sector, said before his HIMSS24 presentation that genAI designs to maximize benefits for healthcare organizations while testing Med-PaLM 2 of Google – a chatbot piloted by the Mayo Clinic and other organizations that federal lawmakers have questioned – his team encountered a challenge.
They focused on the top three needs of healthcare provider executives regarding use case testing, Iyer said.
He noted that by using the Leidos vector storage, researchers obtained better results when testing the accuracy of Med-PaLM 2. Using a dedicated storage, he explained, was ideal because it allows the large language model to find relationships between unstructured data points – this helps it remember those relationships over time.
The volume of information and complexity can increase the risk of errors, such as in mandatory regulatory reporting, “potentially impacting patient care and reimbursement,” Iyer said. ”.
ON PROFILE
“I think I can speak for the local community, we want to spend all our time taking care of patients,” Kirsch said.
“And the amount of documentation over the years has become quite high. So this is something transformative.”
Andrea Fox is a senior editor at Healthcare IT News.
Email: [email protected]
Healthcare IT News is a publication of HIMSS Media.
