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Artificial intelligence (AI) and healthcare – how do these two worlds come together?
What AI tools can benefit providers and patients?
Can AI play a leading role in advancing healthcare quality and spurring innovation without replacing the practice of medicine?
As lawmakers consider federal policy related to the use of AI in healthcare, what is reasonable to ensure transparency and protect individual rights and safety, while retaining needed flexibility and nimbleness to adapt to an evolving technology landscape?
Recently, Premier hosted a virtual briefing to address these considerations with more than 100 Congressional staff, reporters, Premier members and other healthcare organizations in attendance. Premier experts led the conversation which explored the intersection of AI and healthcare, its current use cases, and a potential legislative and regulatory framework for policymakers to think through moving forward.
Soumi Saha, Premier’s Senior Vice President of Government Affairs, and Mason Ingram, Premier’s Director of Payer Policy, kicked the discussion off with a 101 on the types of AI technology that are used in healthcare – including generative AI, predictive AI, machine learning (ML) and natural language processing (NLP) – and Premier’s application of these AI technologies in five key areas:
“AI isn’t something that’s new to Premier. It’s something that we’ve been focusing on for a quite a while,” explained Saha. “We spent a lot of time really thinking through what AI’s use in healthcare actually means and how it’s really impacting operations.”
“For Premier, AI is a tool to cut through the noise, particularly in big data, unstructured data. We use it to draw meaningful conclusions and to help inform our next steps,” added Ingram.
Denise Juliano, Premier’s Group Vice President of Life Sciences, described how Premier’s use of AI helped identify patients at high risk of lung cancer from 60 million medical records in just three weeks.
“This was a really exciting project we undertook at Premier,” Juliano noted. “Alongside our life sciences partners, we had a hunch that many patients were getting lung scans during the COVID-19 pandemic and that some insights could be gleaned from those scans. Parsing through the largest health information exchange in the country, we thought we’d find 10,000 to 20,000 patients with an indication of early-stage lung disorder; however, when we attached ML and NLP capabilities to the data, we actually found 152,000 patients with the presence of pulmonary nodules.”
Juliano also discussed Premier’s support for innovation in clinical trials and how AI can be used to help promote diversity in recruitment efforts and lower drug costs.
“It costs a lot of money to bring a new drug to market – more than $2.6 billion,” she said. “Furthermore, it could cost a life sciences partner $600,000 to $8 million per day if a clinical trial is delayed. Poor site selection also contributes to increased trial costs. And lastly, but importantly, diversity in clinical trials or lack thereof, also affects recruitment timelines and a clinical trial’s ultimate success. We feel strongly that Premier can help support our clinicians and health systems accelerate some of the clinical trials that are underway.”
Looking to supply chain, Angela Lanning, Premier’s Chief Operating Officer of Healthcare Informatics and Technology Services, spoke about how Premier utilizes big data and AI to predict and mitigate product shortages, ensuring uninterrupted patient care during supply disruptions.
“We’ve spent a lot of time on creating tools that enable supply chain resiliency, particularly since the COVID-19 pandemic where we learned how catastrophic supply disruptions can impact our healthcare system’s ability to provide safe, timely care to patients,” Lanning said.
Pivoting from supply chain to healthcare administration, Lanning next discussed the use of AI to streamline the burdensome prior authorization (PA) process and the benefits to patients, providers and the healthcare system.
With today’s PA process, providers must submit specific paperwork to payers to obtain approval of a healthcare service or medication before care is administered – a time-consuming, manual task that may cause care delays and put patients at risk. Cloud-based solutions that leverage AI-powered tools can help enable quick, efficient PA decisions so treatment plans can move forward right away.
“It was important for Premier to figure out how we could work with our health systems and the health plans to identify patients that are eligible for a procedure or medication, along with the appropriate indications to authorize them in real time,” explained Lanning. “It’s wonderful for the patients because they get their treatment plan while in the physician’s office. It reduces time for the physician as forms don’t have to be manually submitted. And it also helps strengthen payer-provider relationships by eliminating a lot of tension that’s inherent in manual processes.”
In the following example, Lanning illustrated how cumbersome the PA process is around radiology benefits management and how AI-driven automation can alleviate the burden.
To conclude the briefing, Saha raised a number of important issues and ethical considerations surrounding what comes first and how do we intentionally move forward with AI, including:
“One of the challenges we’re facing right now is that everyone is interested in AI,” said Saha. “Everyone’s interested, but I don’t know that anyone is clear on what that something is or should be. And that’s okay.”
Ingram added to the closing discussion by sharing insights from Premier’s policy and advocacy work to inform thoughtful AI governance frameworks as described in the company’s AI Policy Roadmap, which outlines Premier’s support for the responsible development and implementation of AI tools across the healthcare industry.
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